S1089: Advanced Understanding and Prediction of Pollutants in Critical Landscapes in Watersheds

(Multistate Research Project)

Status: Active

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SAES-422 Reports

Annual/Termination Reports:

[12/02/2021] [11/09/2022] [11/09/2022] [11/07/2023] [10/21/2024]

Date of Annual Report: 12/02/2021

Report Information

Annual Meeting Dates: 09/02/2021 - 09/03/2021
Period the Report Covers: 10/01/2020 - 09/30/2021

Participants

In-person attendees: Soni M. Pradhanang, Rafael Muñoz-Carpena, Francois Birgand, Aleksey Seshukov, Fouad Jaber, Young Gu Her

Virtual Attendees: Adel Shirmohammadi, Brian Benham, David Sample, Elizabeth Boyer Kevin Wagner, Latif Kalin, George Vellidis, Rabin Bhattarai, Sara McMillam, Sanjiv Kumar, Saurav Kumar, Shreeram Inamdar, Zachary Easton

Brief Summary of Minutes

The annual meeting was held at the University of Florida, FL in September 2021 focused on addressing S1089 objectives, accomplishments, and identifying potential tasks or research products to be initiated or continued by the members of the Multistate Exchange Group. Presentations of the different accomplishments and future goals to be pursued by members of S1089 were held during the annual meeting. Live and virtual members’ presentations involved the members’ involvement and the project accomplishments.

The project team, both in-person and virtual attendees, spent about 2 hours discussing the journal special issue collection, brainstormed research topics, and potential journals. Dr. Muñoz-Carpena gave a brief insight to how the special issues need to be handled. He emphasized improving science with quality publications.

The in-person project members then went to Sweetwater Branch Watershed for the field trip. The next annual meeting will be held in Texas A&M, Dallas.

The project team members decided to develop a special issue articles collection for the Journal of Environmental Management.

Minutes Attachment:

S1089 2020-2021 annual report_12-02-21.pdf

Accomplishments

The principal focus of this project is to evaluate the effectiveness of best management practices (BMPs) at the watershed scale. This includes the water quality and environmental benefits of mitigation practices as well as their cost-effectiveness. This will be achieved through monitoring at sub-watershed scales, modeling at larger spatial scales, and analysis of uncertainty in both monitoring and modeling efforts.  This report summarizes the activity on this project from October 2020 to September 2021, and the following sections highlight accomplishments from project teams:   Texas A&M (Fouad Jaber) Texas A&M team has developed TMDL Report Selection Tool (http://Occviz.com/tmdl ). This tool uses natural language processing to understand linkages between modeling tools and impairments. Other tools such as BMP-Net, a deep neural network based on PlanetScope data, was also developed to identify vegetative and structural BMPs in the world from satellite imagery. The member of the team works closely with USEPA to develop national scale water quality models at huc8, 10, 12, and 14 digits for the entire U.S. and to develop GIS Tool for determining flood prone areas in Denton county for use in Hazard Mitigation Planning. In addition, the Texas A&M team works closely with Nature Conservancy to develop Green stormwater infrastructure prioritization maps for Dallas flooding. University of Florida (R. Muńoz-Carpena) We started (1) reviewing existing BMP practices and modeling options available for Florida and other participating states and (2) exploring new ones applicable to the States. We investigated important hydrology and pollution processes in critical landscapes including preferential flow in riparian areas (Orozco-Lopez and R. Muñoz-Carpena, 2021; Guertault et al., 2021; Orozco-Lopez et al., 2021), ephemeral gully development, and conservation tillage (Luquin et al., 2021), pathogen transport and concentration in agricultural irrigation ponds (Vazquez et al., 2021), impacts of irrigation at the watershed scale (Mompremier et al., 2020), algal blooms in coastal areas and lakes affected by terrestrial sources (Medina et al, 2020; Nelson et al. 2020), combining satellite remote sensing with groundwater monitoring to estimate historical wetland changes affected by upland development (Alonso et al., 2020), forecasting of stream recession hydrographs for critical events (Delforge et al., 2020), uncertainty and sensitivity analysis of models  (Nelson et al., 2020; Moreno-Cadena et al., 2020). Dr. Muñoz-Carpena is also starting as Chair of this Hatch Project for the next year and will coordinate the reporting and efforts. Under the organization of this group, we will also submit and develop a special journal collection on the topic of "Advances and gaps in agricultural and urban BMPs across critical scales” that will be submitted to a top-tier journal in the specialty. Oklahoma State University (Kevin Wagner) Oklahoma State University team has an active research project that is focused towards understanding & improving grazing land water quality. The objective of this research is to quantify nutrient, E. coli, and sediment runoff concentrations and loadings from a variety of land uses and land covers and small Watershed Monitoring.  The research team also uses UAV imagery and GIS analysis for vegetation characterization, groundcover visual estimation, relative cattle/wildlife density with game camera deployment. The sub-objectives of the research include assessing “background” loadings, assessing how “background” loadings change with wildlife habitat, and assessing the effects of grazing on loadings. University of Georgia (G. Vellidis) The University of Georgia team is currently working on the project that focuses on the measurement and simulation of the Environmental Effects of High Maize Yields in Georgia. The objectives are to (i) evaluate the water quality effects of fertilization rates used to achieve high yield goals (350 – 500 kg N ha-1), (ii) use the HYDRUS-1D transport model to simulate the system and estimate N leaching losses, (iii) Use the HYDRUS-1D and DSSAT CERES-Maize models to evaluate maize irrigation scheduling management scenarios that would result in high yields while minimizing leaching of NO3-N. Other project includes (i) Best Management Practice Evaluation in the Lower Flint River Basin, (ii) Evaluate “cutting-edge” management strategies/tools with potential to improve nitrogen and water use efficiency, (iii) Fertigation in corn and cotton, (iv)ET-based irrigation scheduling tools on smartphone platforms, (v) DSSAT (CERES-Maize and CSM-CROPGRO-Cotton), and (vi) provide data for regional modeling with SWAT in collaboration with Auburn University. Purdue University (S. McMillan) At Purdue University, McMillan is working on research related to floodplain restoration in agricultural landscapes. Restored riverine floodplains trap sediments and associated pollutants, promote denitrification but enhance phosphorus release. These patterns are driven by floodplain geomorphology, soil microbes, and vegetation highlighting opportunities for the restoration design. Water quality impacts of agricultural conservation practices include (i) multi-year monitoring and modeling to link water quality outputs to agricultural conservation practices, (ii) connecting stakeholders with scientists & engineers to better implement and evaluate environmental outcomes, and (iii) time series analysis using historical monitoring data for change detection. University of Rhode Island (S Pradhanang) Supported by USDA-AFRI, the Pradhanang Lab is advancing research to evaluate riparian zone functions in glaciated settings for decision-support purposes with respect to N and P fluxes. Supported by the RI DOT, a study to evaluate the effectiveness of improved roadside best management practices in maintaining stormwater quality was completed in early 2021. The project developed a stormwater runoff model for sub-urban areas in Southern Rhode Island, as well as assessed model uncertainty and calibration through the application of Bayesian statistics. A research project on the impacts of saltwater intrusion in coastal aquifers due to storm surges was completed in early 2021. Observation and model-based nutrient transport research supported by EPA is still ongoing. The sUAS-thermal infra-red-based imaging study to track shallow groundwater plumes and contaminants is still underway. The statewide water uses, and availability database project started in 2020 and will end in 2022. Gold and the team have been working on New England Dams and stormwater quality studies using high-frequency sensors. Kansas State University (A. Sheshukov) At KSU, the Sheshukov watershed research lab has active projects from USDA-ARS, USDA-NRCS, and USGS on improving soil health on agricultural fields and water quality in Kansas water bodies. Specifically, the activity is focused on: (i) developing a validated methodology for defining and prioritizing areas in the agricultural landscape susceptible to ephemeral gully erosion and identifying most beneficial BMPs, (ii) providing a prediction framework for cyanoHAB occurrence in lakes and reservoirs by accounting for mechanisms that drive cyanobacterial growth and toxin production, and (iii) evaluating the applicability of cotton production in Kansas and its effects on soil health. Each project is in its first year of activities, and we are collecting field data and developing datasets that will be used for specific models’ validation. For the ephemeral gully project, we are collecting data from various sources (LiDAR, historic aerial imagery, historic maps, etc) to identify and map the gullies in 30 MPRAs (or >100 HUC-12 watersheds) across Kansas, Iowa, Nebraska, and Missouri. The sampling equipment has been installed in Marion Reservoir (KS) for HAB specific data collection. For the cotton project, two metro stations with above and below ground sampling equipment were installed on three fields, and evaluation of four different irrigation practices and two crop densities are presently underway. The activity in these projects will continue in 2022. North Carolina State University (F. Birgand) The NCSU team has an active research project that focuses on the assessment of tools used for monitoring of BMPs. The focus is on monitoring stormwater wetland nutrient influxes UV-Vis in situ spectrophotometer is used largely for data collected. The research focuses on providing guidelines on how to obtain best data, estimating uncertainties on annual and event load values, accounting for uncertainties associated with Q-proportional sampling. The main outcome of the research is (i) sampling the entire event, in practice capture peak flow and 60% duration, assuming majority of pollutants is transported in the first part, (ii) too few samples brings error, too many might not sample entire event (best guides suggest a collection of ~12-16 (field based) & 30 (statistics) samples per event to estimate within 10-20% error range, and (iii) early pollutant peaks if collected can lead to overestimation of EMC, but we still want to start sampling early within the event.   University of Illinois (R. Bhattarai) UI-UC team is currently working on a few research projects such as (i) the web-based decision support tool for winter cover crop management (ii) Watershed-scale response of agricultural systems to drainage water management in Central Illinois (iii) Effect of subsurface drain depth and spacing on water quality and crop yield (iv) Probabilistic assessment of adequacy and development of nutrient load reduction goals under a changing climate (v)Balancing water quality, nutrient management, and yield goals for the sustainable intensification of agricultural systems in Illinois   Penn State University (E. Boyer) The team has an active project on the transport of nitrogen-rich groundwater to surface waters by riparian macropore flow in an agriculturally dominated watershed. The goal is to quantify how much of the streamflow nitrogen load (under base-flow conditions in an agricultural watershed) comes from groundwater seeps, versus diffuse matrix flow through the streambed? University of Kentucky (W. Ford) Research at the University of Kentucky has focused on quantifying source provenance and hydrologic pathways of contaminants in karst and tile-drained landscapes, as well as the fate and transport of contaminants in headwater streams, restored stream reaches, and river-tributary confluences.  Research in tile drained landscapes have focused on monitoring sediment transport and flow pathway dynamics at the edge of the field.  Research in heterogeneous karst watersheds has focused on the impacts of flow pathways and water source dynamics on nitrate and dissolved reactive P loadings at the watershed scale.  Research in fluvial systems has focused on aquatic vegetation characterization using UAVs, impacts of stream restoration on hydrology and water quality in karst landscapes, and fate and transport of sediments and nutrients in river-tributary confluences.  Research over the past year has focused on the collection of novel datasets that will be implemented within hydrologic and water quality modeling frameworks in subsequent years.  Datasets include high-frequency in situ sensors, stable isotopes of dissolved and particulate-bound nutrients, and remotely sensed aerial images using visible and multispectral cameras attached to UAVs.  Auburn University (J. Lamba) Research at the Auburn university has focused on field and lab-scale, mixed with mathematical modeling, modeling non-point source pollution and wetland nutrient cycles addressing all the four objectives. Research examples include land-use change and climate variability and extremes, with the goal of improving predictability and quantifying uncertainty in the availability of natural resources at sub-seasonal to decadal time scales, and providing data-driven quantitative information to decision-makers about long-term management of natural resources. University of Maryland (A. Shirmohammadi) The University of Maryland has been working on interfacing SWAT Hydrologic/Water Quality model with Agent-Based Modeling and Diagnostic Decision Support System (DDSS) to facilitate targeted BMP implementation with social, economic, and policy feasibilities included. The team expanded their approach to include nonlinear optimization in the form of Genetic Algorithms (GAs) and social modeling strategy to better account for heterogeneity in individual behavior in cases where spatial fluctuations in mean behavior are mild within a study watershed. The team is using the existing database from multiple sources (USGS, NLCD, NLDAS, SSURGO, etc.) and collecting IRB-approved stakeholder surveys to use for calibration and validation of our multi-faceted modeling technologies.

Publications

Peer Reviewed Journal Publications: <ol> <li>Budhathoki., S., J. Lamba, P. Srivastava, K. Malhotra, S. Katuwal, and T. R. Way. 2021. Using X-ray Computed Tomography to Quantify Variability in Soil Macropore Characteristics in Pastures. Soil and Tillage Research. Accepted.</li> <li>Kumar, K., P. Srivastava, B. V. Ortiz, G. Morata, B. S. Takhellambam, J. Lamba, and L. Bondesan. 2021. Field-Scale Spatial and Temporal Soil Water Variability in Irrigated Croplands. Transactions of the ASABE: 64 (4), 1277-1294. doi: 10.13031/trans.14335</li> <li>Bhatta, A, R. Prasad, D. Chakraborty, J.N. Shaw, J. Lamba, E. Brantley, H.A. Torbert. 2021. Mehlich 3 as a generic soil test extractant for environmental phosphorus risk assessment across Alabama soil regions. Agrosyst Geosci Environ. 2021; 4:e20187. https://doi.org/10.1002/agg2.20187</li> <li>Duan, Y., Kumar, S., & Kinter, J. L. (2021). Evaluation of long-term temperature trend and variability in CMIP6 multimodel ensemble. Geophysical Research Letters, 48, e2021GL093227. <a href="https://doi.org/10.1029/2021GL093227">https://doi.org/10.1029/2021GL093227</a></li> <li>Sutton, C., Kumar, S., Lee, M.-K., Davis, E. (2021). Human imprint of water withdrawals in the wet environment: a case study of declining groundwater in Georgia, USA. Journal of Hydrology – Regional Studies. In press.</li> <li>Esit, M., Kumar, S., Pandey, A., Lawrence, D. M., Rangwala, I., and Yeager S.  Seasonal to multi-year soil moisture drought forecasting. npj Clim Atmos Sci 4, 16 (2021). <a href="https://doi.org">https://doi.org/10.1038/s41612-021-00172-z</a></li> <li>Duan, Y., & Kumar, S. (2020). Predictability of Seasonal Streamflow and Soil Moisture in National Water Model and a Humid Alabama-Coosa-Tallapoosa River Basin. Journal of Hydrometeorology, DOI: 10.1175/JHM-D-19-0206.1</li> <li>Kumar, S., Newman, M., Lawrence, D. M., Lo, M. H., Akula, S., Lan, C. W., ... & Lombardozzi, D. (2020). The GLACE-Hydrology Experiment: Effects of Land-Atmosphere Coupling on Soil Moisture Variability and Predictability. Journal of Climate, (2020). DOI: 10.1175/JCLI-D-19-0598.1 </li> <li>Bhandari, R., Kalra, A., & Kumar, S. (2020). Analyzing the effect of CMIP5 climate projections on streamflow within the Pajaro River Basin. Open Water Journal, 6(1), 5.</li> <li>Singh, A., Kumar, S., Akula, S., Lawrence, D. M., & Lombardozzi, D. L. (2020). Plant Growth Nullifies the Effect of Increased Water Use Efficiency on Streamflow Under Elevated CO2 in the Southeastern United States. Geophysical Research Letters, e2019GL086940.</li> <li>He*, J., M. Hantush, L. Kalin, M. Rezaeianzadeh*, S. Isik*, "Two-Layer Vertically-Averaged Soil Moisture Dynamics: Numerical Model", Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2021.126797.</li> <li>Yao, Y., H. Tian, L. Kalin, S. Pan, M. Friedrichs, J. Wang, Y. Li (2021), "Contrasting stream water temperature responses to global change in the Mid-Atlantic Region of the United States: A process-based modeling study", Journal of Hydrology, Vol 601, https://doi.org/10.1016/j.jhydrol.2021.126633.</li> <li>Tian, D., X. He, P. Srivastava, L. Kalin (2021), "A hybrid framework for forecasting monthly reservoir inflow based on machine learning techniques with dynamic climate forecasts, satellite-based data, and climate phenomenon information", Stochastic Environmental Research and Risk Assessment. https://doi.org/10.1007/s00477-021-02023-y.</li> <li>Wang, F., D. Tian, L. Lowe, L. Kalin, J. Lehrter (2021), “Deep Learning for Daily Precipitation and Temperature Downscaling”, Water Resources Research.  doi: 10.1029/2020WR029308.</li> <li>Karki*, R., P. Srivastava, L. Kalin, S. Mitra, S. Singh (2021), “Assessment of impact in groundwater levels and stream-aquifer interaction due to increased groundwater withdrawal in the lower Apalachicola-Chattahoochee-Flint (ACF) River Basin using MODFLOW”, Journal of Hydrology: Regional Studies. Vol 34. https://doi.org/10.1016/j.ejrh.2021.100802.</li> <li>Celik*, S., C. Anderson, L. Kalin, M. Rezaeianzadeh* (2021), “Long-term salinity, hydrology, and forested wetlands along a tidal freshwater gradient”, Estuaries and Coast. https://doi.org/10.1007/s12237-021-00911-8.</li> <li>Ramesh*, R. L. Kalin, M. Hantush, A. Chaudhary (2021), “A Secondary Assessment of Sediment Trapping Effectiveness by Vegetated Buffers”, Ecological Engineering. https://doi.org/10.1016/j.ecoleng.2020.106094.</li> <li>Noori*, N., L. Kalin, S. Isik* (2020), “Water Quality Prediction Using SWAT-ANN Coupled Approach”, Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2020.125220.</li> <li>Ramesh*, R., C. Anderson, L. Kalin (2020), “Characterizing Nitrogen Attenuation by Headwater Slope Wetlands across Different Land Uses”, Ecological Engineering. Vol 149. https://doi.org/10.1016/j.ecoleng.2020.105833.</li> <li>Dosdogru*, F., L. Kalin, R. Wang*, H. Yen (2020), "Potential Impacts of Land Use/Cover and Climate Changes on Ecologically Relevant Flows", Journal of Hydrology, Vol 584, https://doi.org/10.1016/j.jhydrol.2020.124654.</li> <li>Karki*, R., P. Srivastava, D. Bosch, L. Kalin, J. Lamba, T. Strickland (2020), “Multi-variable sensitivity analysis, calibration, and validation of a field-scale SWAT model: Building Stakeholder Trust in Hydrologic/Water Quality Modeling”, Transactions of the ASABE. 63(2): 523-539. DOI: 10.13031/trans.13576.</li> <li>Ramesh*, R. L. Kalin, M. Hantush, M. Rezaeinzadeh*, C. Anderson (2020), “Challenges in Calibrating Hydrology for Groundwater-Fed Wetlands: A Headwater Wetland Case Study”, Environmental Modeling & Assessment. DOI: 10.1007/s10666-019-09684-8.</li> <li>Pickering, C., Ford, W.I. In Press. Effect of watershed disturbance and river-tributary confluences on watershed sedimentation in the Western Allegheny Plateau. Journal of Hydrology. </li> <li>Nazari, S., Ford, W.I., King, K. In Press.  Quantifying Field-scale Hydrologic Pathway and Connectivity Dynamics in Tile-Drainage: Implications for P concentrations. Vadose Zone Journal</li> <li>Hood, R., G. Shenk, R. Dixon, W. Ball, J. Bash, P. Claggett, Z.M. Easton, M. Friedrichs, T. Ihde, L. Linker, A. Miller, G. Noe, K. Rose, J. Testa, R. Tian, T. Veith, L. Wainger, D. Weller, J. Zhang. 2021. The Chesapeake Bay Program management modeling system: progress, challenges, and prospects. Ecological Modeling. <a href="https://doi.org/10.1016/j.ecolmodel.2021.109635">https://doi.org/10.1016/j.ecolmodel.2021.109635</a></li> <li>Nayeb Yazdi, M., Scott, D., Sample, D. J., and Wang, X., 2021. Efficacy of a retention pond in treating stormwater nutrients and sediment. Journal of Cleaner Production, 290, 125787. <a href="https://doi.org/10.1016/j.jclepro.2021.125787">https://doi.org/10.1016/j.jclepro.2021.125787</a></li> <li>Nayeb Yazdi, M., Sample, D., Scott, D., Wang, X., and Ketabchy, M., 2021. The effects of land use characteristics on urban stormwater quality and watershed pollutant loads. Science of the Total Environment, <a href="https://doi.org/10.1016/j.scitotenv.2021.145358">https://doi.org/10.1016/j.scitotenv.2021.145358</a></li> <li>Twombly, C., J. Faulkner, A. Collick, Z.M. Easton. 2021. Identification of P Index improvements through model comparisons across topographic regions in a small agricultural watershed in Vermont, USA. Soil Science Society of America Journal.  <a href="http://doi.org/10.1002/saj2.20254">http://doi.org/10.1002/saj2.20254</a></li> <li> Xu, Y., D. Bosch, M. Wagena, A. Collick, and Z.M. Easton. 2020. Reducing costs of mitigating nitrogen loadings by within- and cross-county targeting. J. Environ. Manag.   <a href="https://doi.org/10.1016/j.jenvman.2020.110333">https://doi.org/10.1016/j.jenvman.2020.110333</a></li> <li>Modi, P., D.R. Fuka, and Z.M. Easton. 2021. Impacts of climate change on terrestrial hydrological components and crop water use in the Chesapeake Bay watershed. J. Hydrol. Regional Studies.  <a href="https://doi.org/10.1016/j.ejrh.2021.100830">https://doi.org/10.1016/j.ejrh.2021.100830</a></li> <li>Li, W., Cheng, X., Zheng, Y., Lai, C., Sample, D. J., Zhu, D., and Wang, Z., 2021. Response of non-point source pollution to landscape pattern: case study in mountain-rural region, China. Environmental Science and Pollution Research. <a href="https://doi.org/10.1007/s11356-020-12196-8">https://doi.org/10.1007/s11356-020-12196-8</a></li> <li>Ahmadisharaf, E., & Benham, B. L. 2020. Risk-based decision making to evaluate pollutant reduction scenarios. SCIENCE OF THE TOTAL ENVIRONMENT, 702, 10 pages. doi:<a href="http://doi.org/10.1016/j.scitotenv.2019.135022">10.1016/j.scitotenv.2019.135022</a></li> <li>Ahmadisharaf, E., Lacher, I. L., Fergus, C., Benham, B. L., Akre, T., & Kline, K. S. 2020. Projecting land use change impacts on nutrients, sediment and runoff in multiple spatial scales: Business-as-usual vs. stakeholder-informed scenarios. JOURNAL OF CLEANER PRODUCTION, 257, 14 pages. doi:<a href="http://doi.org/10.1016/j.jclepro.2020.120466">10.1016/j.jclepro.2020.120466</a></li> <li>Bock, E., and Z.M. Easton. 2020. Export of nitrogen and phosphorus from golf courses in the Mid Atlantic, are current export rates accurate? J. Environ. Manag. <a href="https://doi.org/10.1016/j.jenvman.2019.109817">https://doi.org/10.1016/j.jenvman.2019.109817</a></li> <li>Coffey, R., Butcher, J., Benham, B., & Johnson, T. 2020. Modeling the effects of future hydroclimatic conditions on microbial water quality and management practices in two agricultural watersheds. TRANSACTIONS OF THE ASABE, 63(3), 753-770. doi:<a href="http://doi.org/10.13031/trans.13630">10.13031/trans.13630</a></li> <li>Dos Reis B., Z.M. Easton, R.R. White and D.R. Fuka. 2021.<a href="https://scholar.google.com/scholar?oi=bibs&cluster=14024963733617023966&btnI=1&hl=en"> A LoRa sensor network for monitoring pastured livestock location and activity</a>. Translational Animal Science. <a href="https://doi.org/10.1093/tas/txab010">https://doi.org/10.1093/tas/txab010</a></li> <li>Dos Reis B., D.R. Fuka, Z.M. Easton, and R.R. White. 2021. An open-source research tool to study triaxial inertial sensors for monitoring selected behaviors in sheep. Translational Animal Science 4(4):01 Oct 2020. doi.org/10.1093/tas/txaa188</li> <li>Dos Reis B., D.R. Fuka, Z.M. Easton, and R.R. White. 2020. An open-source microprocessor-based sensor for monitoring grazing animal behaviors. Journal of Dairy Science 103:9, 0022-0302</li> <li>Easton, Z.M., E.M. Bock, and K. Stephenson. 2020. Feasibility of employing bioreactors to treat legacy nutrients in emergent groundwater. Environ. Sci and Technology. <a href="http://dx.doi.org/10.1021/acs.est.9b04919">http://dx.doi.org/10.1021/acs.est.9b04919</a></li> <li>Wagena, M.B., D.G. Goering, A.S. Collick, E.M. Bock, A.R. Buda, D.R. Fuka, and Z.M. Easton. 2020. A comparison of short-term streamflow forecasting using stochastic time series, neural networks, process-based, and Bayesian models. Environ. Model & Software. <a href="about:blank">https://10.1016/j.envsoft.2020.104669</a>.</li> <li> Almadari, N., D. Sample, A. Ross, and Z.M. Easton. 2020. Evaluating the impact of climate change on water quality and quantity in an urban watershed using an ensemble approach. Estuaries and Coasts. 1-17. 10.1007/s12237-019-00649-4.</li> <li>Wagena, M.B., G. Bhatt, A.R. Sommerlot, E. Buell, D.R. Fuka, and Z.M. Easton. 2020. Quantifying structural model uncertainty using a Bayesian multi model ensemble. Env. Model Software. <a href="https://doi.org/10.1016/j.envsoft.2019.03.013">https://doi.org/10.1016/j.envsoft.2019.03.013</a></li> <li>Schmadel N, J Harvey, R Alexander, E Boyer, G Schwarz, J Gomez-Velez, D Scott, and C Konrad (2020).  Low threshold for nitrogen concentration saturation in headwaters increases regional and coastal delivery.  Environmental Research Letters, DOI: 10.1088/1748-9326/ab751b </li> <li>Redder BW, CD Kennedy, AR Buda, G Folmar, and EW Boyer (2021).  Groundwater contributions of flow and nitrogen in a headwater agricultural watershed. Hydrological Processes, DOI: 10.1002/hyp.14179</li> <li>Lewis, E., S.M. Inamdar, A.J. Gold, K. Addy, T. Trammell, D. Merritts, S., M. Peipoch, P.M. Groffman, J. Hripto, M. Sherman, J. Kan, R. Walter and E.P. Lewis. 2021. Draining the landscape: How do nitrogen concentrations in riparian groundwater and stream water change following milldam removal? Journal of Geophysical Research – Biogeosciences. <a href="https://doi.org/10.1029/2021JG006444">https://doi.org/10.1029/2021JG006444</a></li> <li>Suriano, Z. J., C. M. Siegert, D. J. Leathers, A. J. Gold, K. Addy, A. W. Schroth, E. Seybold, S. Inamdar, and D. F. Levia. 2021. Effects of atmospheric circulation on stream chemistry in forested watersheds across the northeastern United States: Part 2. Interannual weather type variability. Journal of Geophysical Research: Atmospheres.  e2021JD034546.</li> <li>Hollister. J. W., Kellogg, D. Q., Kreakie, B. J., Shivers, S., Milstead, W. B., Herron, E., Green, L., Gold, A. 2021. Increasing Chlorophyll, a Amid Stable Nutrient Concentrations in Rhode Island Lakes and Reservoirs. Ecosphere 12, no. 6 (2021): e03555.</li> <li>Suchy, A., P. Groffman, L. Band, J. Duncan, A.J. Gold, J. M. Grove, D. Locke, L.A.  Templeton, Laura A. 2021.  Landscape approach to nitrogen cycling in urban lawns reveals the interaction between topography and human behaviors. Biogeochemistry.  152:73–92</li> <li> Siegert, CM, ZJ Suriano, DJ Leathers, AJ Gold, K Addy, AW Schroth, E Seybold, S Inamdar, DF Levia. 2021. Effects of Atmospheric Circulation on Stream Chemistry in Forested Watersheds across the Northeastern United States: Part 1. Synoptic-scale Forcing. Journal of Geophysical Research – Atmospheres.</li> <li> Inamdar, S., M. Peipoch, A.J. Gold, E. Lewis, J. Hripto, K. Addy, D. Merritts, J. Kan, P. M. Groffman, R. Walter, and T. Trammell. 2021. Ghosts of landuse past: Legacy effects of milldams for riparian water quality and ecosystem function. Environ. Research Letters. 16: 035016</li> <li>  Moatar, F., M. Floury, A.J. Gold, M. Meybeck, B. Renard, A. Chandesris, C. Minaudo, K. Addy, J. Piffady and G. Pinay. 2020. Stream solutes and particulates export regimes: A new framework to optimize their monitoring. Frontiers in Ecology and Evolution. 7:516.</li> <li>Panthi, J., Talchabhadel, R., Ghimire, G.R., Sharma, S., Dahal, P., Baniya, R., Boving, T., Pradhanang, S.M. and Parajuli, B., 2021. Hydrologic Regionalization under Data Scarcity: Implications for Streamflow Prediction. Journal of Hydrologic Engineering, 26(9), p.05021022.</li> <li>Tamanna, M., Pradhanang, S.M., Gold, A.J., Addy, K. and Vidon, P.G., 2021. Riparian Zone Nitrogen Management through the Development of the Riparian Ecosystem Management Model (REMM) in a Formerly Glaciated Watershed of the US Northeast. Agriculture, 11(8), p.743.</li> <li>Jahan, K., Pradhanang, S.M. and Bhuiyan, M.A.E., 2021. Surface Runoff Responses to Suburban Growth: An Integration of Remote Sensing, GIS, and Curve Number. Land, 10(5), p.452.</li> <li>Young, K.S. and Pradhanang, S.M., 2021. Small Unmanned Aircraft (sUAS)-Deployed Thermal Infrared (TIR) Imaging for Environmental Surveys with Implications in Submarine Groundwater Discharge (SGD): Methods, Challenges, and Novel Opportunities. Remote Sensing, 13(7), p.1331.</li> <li>Jahan, K. and Pradhanang, S.M., 2020. Predicting Runoff Chloride Concentrations in Suburban Watersheds Using an Artificial Neural Network (ANN). Hydrology, 7(4), p.80.</li> <li>Tamanna, M., Pradhanang, S.M., Gold, A.J., Addy, K., Vidon, P.G. and Bingner, R.L., 2020. Evaluation of AnnAGNPS Model for Runoff Simulation on Watersheds from Glaciated Landscape of USA Midwest and Northeast. Water, 12(12), p.3525.</li> <li>Clearing up cloudy waters: a review of sediment impacts to unionid freshwater mussels https://doi.org/10.1139/er-2020-0080 (Jaber)</li> <li>How does increasing impervious surfaces affect urban flooding in response to climate variability? https://doi.org/10.1016/j.ecolind.2020.106774 (Jaber)</li> <li>Advanced filtration in greywater treatment: a modelling approach with water reuse perspectives <a href="https://doi.org/10.1080/1573062X.2020.1828498">https://doi.org/10.1080/1573062X.2020.1828498</a> (Jaber)</li> <li>Selecting Reliable Models for TMDL <a href="https://doi.org/10.1061/(ASCE)HE.1943-5584.0002102">https://doi.org/10.1061/(ASCE)HE.1943-5584.0002102</a> (Kumar)</li> <li>Margin of Safety in TMDLs: Natural Language Processing-Aided Review <a href="https://doi.org/10.1061/(ASCE)HE.1943-5584.0001889">https://doi.org/10.1061/(ASCE)HE.1943-5584.0001889</a> (Kumar)</li> <li>ASCE-EWRI Manual of Practice for TMDL development (in press) (Kumar)</li> <li>Koudahe, K., Sheshukov, A.Y., Aguilar, J., Djaman, K. (2021) Irrigation-Water Management and Productivity of Cotton: A Review. Sustainability. 131: 70. <a href="https://doi.org/10.3390/su131810070">https://doi.org/10.3390/su131810070</a></li> <li>Oker, T.E., A.Y. Sheshukov, J. Aguilar, D.H. Rogers, I. Kisekka. (2021) Evaluating Soil Water Redistribution under Mobile Drip Irrigation, Low-Elevation-Spray-Application, and Low-Energy-Precision-Application using HYDRUS. Irrigation and Drainage Science Engineering. 147 (6), 04021016. <a href="https://doi.org/10.1061/(ASCE)IR.1943-4774.0001553">https://doi.org/10.1061/(ASCE)IR.1943-4774.0001553</a> </li> <li>A.Y. Sheshukov, Gao, J., K.R. Douglas-Mankin, H. Yen. (2021) Observed Data Source used for Bias Correction Introduces Variability and Uncertainty to Downscaled Climate Projections for Hydrologic Modeling. Transactions of the ASABE. 64(2): 203-220. <a href="https://doi.org/10.13031/trans.14061">https://doi.org/10.13031/trans.14061</a>. </li> <li>Orozco-Lopez*, E. and R. Muñoz-Carpena, R. 2021. Comparative non-Darcian modelling of subsurface preferential flow experimental observations in a riparian buffer. Trans. ASABE 64(5). <a href="https://doi.org/10.13031/trans.14559">doi:10.13031/trans.14559</a>.</li> <li>Vazquez*, K.M, R. Muñoz-Carpena, M.D. Danyluk, A.H. Havelaar. 2021. Parsimonious mechanistic modeling of bacterial runoff to inform food safety management of agricultural water quality. Appl. Environ. Microbiol. 87(15): e00596-21. <a href="https://doi.org/10.1128/AEM.00596-21">doi:10.1128/AEM.00596-21.</a></li> <li>Luquin*, E., M.A. Campo-Bescós, R. Muñoz-Carpena, R.L. Bingner, R.M. Cruse, H.G. Momm, R.R. Wells, J.Casalí. 2021. Evaluation of model prediction capacity of ephemeral gully temporal evolution in conservation tillage systems. Earth Surf. Process. Landf. 46(10):1909-1925. <a href="https://doi.org/10.1002/esp.5134">doi:10.1002/esp.5134</a></li> <li>Guertault, L. G.A.Fox, D. Heeren, T. Hallihan and R Muñoz-Carpena. 2021. Quantifying the importance of preferential flow in a riparian buffer. Trans. ASABE 64(3):937-947. <a href="https://doi.org/10.13031/trans.14286">doi:10.13031/trans.14286</a>.</li> <li>Orozco-López*, R. Muñoz-Carpena, B. Gao and G.A. Fox. 2021. High resolution pore-scale water content measurement in a translucent soil profile from light transmission. Trans. ASABE64(3):949-962.<a href="https://doi.org/10.13031/trans.14292">doi:10.13031/trans.14292</a>.</li> <li>Medina M.*, R. Huffaker, R. Muñoz-Carpena and G. Kiker. 2021. An empirical nonlinear dynamics approach to analyzing emergent behavior of agent-based models. AIP Advances11:035133. <a href="https://doi.org/10.1063/5.0023116">doi:10.1063/5.0023116</a></li> <li>Medina*, M., R. Huffaker, J.W. Jawitz, and R. Muñoz-Carpena. 2020. Seasonal dynamics of terrestrially sourced nitrogen influenced Karenia brevis blooms off Florida's southern Gulf Coast. Harmful Algae 98:101900.<a href="https://doi.org/10.1016/j.hal.2020.101900"> doi:10.1016/j.hal.2020.101900</a></li> <li>Mompremier, R.*, Y. Her, G. Hoogenboom, K. Migliaccio, R. Muñoz-Carpena, Z. Brym, R. W. Colbert, and W. Jeune. 2020. Modeling the response of dry bean yield to irrigation water availability controlled by watershed hydrology. Agric. Water Manage. 243:106429. <a href="https://doi.org/10.1016/j.agwat.2020.106429">doi:10.1016/j.agwat.2020.106429</a></li> <li>Nelson, N.G.*, R. Muñoz-Carpena, and E. Phlips. 2020. Parameter uncertainty drives important incongruities between simulated chlorophyll-a and phytoplankton functional group dynamics in a mechanistic management model.  Env. Modeling & Soft. 129:104708. <a href="https://doi.org/10.1016/j.envsoft.2020.104708">doi:10.1016/j.envsoft.2020.104708</a>.</li> <li>Alonso, A.*, R. Muñoz-Carpena, and D. Kaplan. 2020. Coupling high-resolution water level sensors and MODIS for mapping wetland historical hydroperiod at high temporal frequency. Remote Sensing of Environment 247:111807. <a href="https://doi.org/10.1016/j.rse.2020.111807">doi:10.1016/j.rse.2020.111807</a>.</li> <li>Moreno-Cadena, L.P.*, G. Hoogenboom, M.J. Fisher, J. Ramirez-Villegas, S.D. Prager, L.A. Becerra Lopez-Lavalle, P. Pypers, M.S. Mejia de Tafur, D. Wallach, R. Muñoz-Carpena, S. Asseng. 2020. Importance of genetic parameters and uncertainty of MANIHOT, a new mechanistic model of cassava. Europ. J. Agronomy 115:126031.<a href="https://doi.org/10.1016/j.eja.2020.126031"> doi:10.1016/j.eja.2020.126031</a></li> <li>Delforge, D.*, R. Muñoz-Carpena, M. Van Camp, M. Vanclooster. 2020. A parsimonious empirical approach to streamflow recession analysis and forecast. Wat. Resour. Res.56(2): e2019WR025771. <a href="https://doi.org/10.1029/2019WR025771">doi: 10.1029/2019WR025771</a></li> </ol>   Thesis/Dissertation: <ol> <li>Radcliff, Cory, "Quantifying the source and pathway of dissolved reactive phosphate in karst drainage of the Inner-Bluegrass" (2021). Theses and Dissertations--Biosystems and Agricultural Engineering. 81.</li> <li>Nazari, Saeid, "Impact of preferential flow, source water connectivity, and agricultural management practices on sediment and particulate phosphorus dynamics in midwestern tile-drained landscapes" (2021). Theses and Dissertations--Biosystems and Agricultural Engineering. 82.</li> <li>Nayeb Yazdi, M., 2020. Understanding the role of scale in assessing sediment and nutrient loads from Coastal Plain watersheds delivered to the Chesapeake Bay, Ph.D. Dissertation, Virginia Tech, p. 181, Advisor: D. Sample.</li> <li>Jahan, K. J., 2021. Effectiveness of Roadside Best Management Practices (BMPs) on Maintaining Stormwater Quality Through Monitoring and Modeling. Doctoral Dissertation submitted to University of Rhode Island (Advisor: S. M. Pradhanang)</li> <li>Tamanna, M, 2021 Optimization of Riparian Zone Nitrogen and Phosphorus Management through the Development of Riparian Model Doctoral. Dissertation submitted to University of Rhode Island (Advisor: S. M. Pradhanang)</li> </ol>   Proposals: <ol> <li>Impact of Broiler Litter Application Method on Phosphorus Loss in Leachate. AAES Agriculture Research Enhancement and Seed (ARES) funding program. Grant amount $50,000 (PI: Jasmeet Lamba)</li> <li>Understanding Preferential Flow Patterns in No-Till Manured Pastures Using Dye Tracer and X-Ray CT Image Analysis. USGS-AWRRI. Grant amount $5,000 (Co-PI Lamba)</li> <li>Leveraging Machine Learning for Sustainable Water and Nutrient Management Across Agro Climatic Zones. USDA-NIFA. Grant amount $650,000 (Co-PI Lamba)</li> <li>A Transdisciplinary Approach to Secure the Safety of the Food Supply System While Protecting the Environment. USDA-NIFA. Grant amount $10 million. (Co-PI Lamba)</li> <li> “A coupled natural-human framework for risk assessment of coastal communities from land-use and climate change”, National Academy of Science – Restore, 2020-2023, $1,110,000, (Co-PI Kalin and Kumar).</li> <li> “Coupling SWAT and WetQual for Improved N, P, and C Processing in Wetland Dominated Agricultural Watersheds”, USDA-NIFA, 2020-2024, $499,932 (PI Kalin).</li> <li> “Ecohydrology and Watershed Modeling”, US-EPA, 2020-2021, $25,000 (PI Kalin).</li> <li>FACT: Interactive Deep Learning Platform and Multi-source Data Integration for Improved Soil Moisture Forecasting (PI Kumar, Co-PIs: W. Lee, and I. Rangwala). Funded by USDA-NIFA. Total support: $500K, Project period: Sept. 2020 to Aug. 2023.</li> <li>Investigation of soil moisture predictability on sub-seasonal to inter-annual time scales (PI Kumar). Funded by AAES AgrSEED program, Total support $50K; Project period: Oct. 2019 to Sept. 2021.</li> <li>Fox, J., Ford, W., Malzone, J., Armstead, M. GP-GO: The Appalachian SUCCESS Program: Strengthening students classified as Underrepresented in STEM by inspiring Confidence, Curriculum and Enriching Sensing Skillsets.  NSF GP-GO. $314,807.  Role: Co-Investigator. September 2021-August 2024.</li> <li>Ford, W.I.  RII Track-4: Elucidating controls of sediment phosphorus delivery to tile-drains.  NSF-EPSCoR, RII-4, $226,757.  Role: Principal Investigator. January 2021 to December 2022.  </li> <li>Ford, W.I., Fox, J., Sama. M. Impact of regenerative stream design on water and nitrogen budgets at reach to watershed scales. USDA-AFRI, $750,000.  Role: PD. Submitted</li> <li>Messer, T., Ford, W., Bartlet-Hunt Shannon. Implications of Microplastic Contributions from Biosolid Applications to the Nitrogen Cycle in Agroecosystems.  USDA-AFRI, $750,000. Role: Co-PD, Submitted.</li> <li>Easton, Z.M., D.R. Fuka, and R.R. White. Developing and evaluating rapidly deployable inexpensive weather, soil moisture, shock, and streamflow sensors to aid the monitoring, inspection, and rehabilitation of aging dams. USDA-Cooperative Agreement.  $75,000. June 2021-Nov 2021.</li> <li>Easton, Z.M. and D.R. Fuka.  Integrating the SWAT Model into the MINT Framework. DARPA-USC $64,000. June 2021-Nov 2021</li> <li>Collick, A.S., Z.M. Easton, and R. Bryant. UMES Stormwater Management Research Facility: Investigating nutrient and sediment reduction from poultry house stormwater drainage systems. USDA NIFA $399,000. Sept 2020-Aug 2022.</li> <li>Easton, Z.M. A Systematic Review of Chesapeake Bay Climate Change Impacts on Tidal and Near Tidal BMPs. NOAA-CBP $73,400. Dec 2020-Sept 2021.</li> <li>Easton, Z.M. A Conservation Effects Assessment Project (CEAP) Watershed Assessment Study: A collaboration between the University of Vermont, Virginia Tech, the Natural Resources Conservation Service, and the Agricultural Research Service. USDA CEAP $123,000. Oct 2020-Sept 2022.</li> <li>Flood Reduction Potential of Urban Forests in Virginia Beach: Development of urban watershed models that improve calculation of evapotranspiration and soil moisture to assess the flood reduction benefits of urban forests in coastal Virginia. Amount: $92,276. PIs: D. Sample, D. McGlauglin, Y. Shao, 1/1/2020-10/31/2022. Sponsor: City of Virginia Beach, The Nature Conservancy.</li> <li>Bluestone River, Mountain Run, and Lewis Creek PCB TMDLs: Data Analysis and Modeling, and TMDL Development Statement of Work, VA Department of Environmental Quality, $649,950, 06/01/2019 - 01/31/2022, PI: B. Benham.</li> <li>TMDL Implementation Plan Development for Buffalo River (Amherst and Nelson Counties) Statement of Work, VA Department of Environmental Quality, $27,155, 07/01/2019 - 10/30/2020, PI: B. Benham.</li> <li>TMDL Implementation Plan Development for McClure River (Dickenson County), VA Department of Environmental Quality, $21,660, 06/01/2019 - 05/31/2020, PI: B. Benham.</li> <li>White, R., D.R. Fuka, E. Feuerbacher, Z.M. Easton. Collaborative Research: CPS: Medium: Greener Pastures: A pasture sanitation cyber physical system for environmental enhancement and animal monitoring. NSF CPS (Cyber-Physical Systems). $998,232. June 2021-May 2024.</li> <li>Designing ESD for Climate Change for Increased Resiliency: Assessing the impact of climate change on hydrology, upland environmental site design (ESD) practices and downstream channel stability. Amount: $107,250. PIs: D. Sample, T.W, Thompson, 7/1/2021-12/31/2022. Sponsor: Chesapeake Bay Trust (thru Tetratech, Inc.)</li> <li>Savage, B., Pradhanang, S. M., Boving, T. Mapping Bedrock and Saltwater Intrusion in Rhode Island, USGS $90,000 (09/2021-08/2022)</li> <li>Kayastha-Pradhanang, S, Kumar, R, and Rashid T, Floating Treatment Wetland System (FTWS) - Sustainable green technology to remediate polluted surface water bodies in the COVID 19-era, Asia-Pacific Network $78,000 (09/2021-08/2023)</li> <li>Pradhanang, S. M., Boving, T., and Savage, B. The Rhode Island Water Resources Board (RIWRB) and University of Rhode Island (URI) Statewide Water Withdrawal Data Enhancement and Database Development Project. RIWRB-USGS 197,488 (10/20-09/22)</li> <li>Pradhanang, S. M., and Boving T., Harmful Algal Blooms (HABs): Treatment Optimization Protocol (TOP) Development, RI Department of Health $34,980 (05/20-08/20)</li> <li> J. Aguilar, A. Sheshukov, B. Golden, L. Haag, D. Devlin. Collaborative Research on Cotton Production in Thermo-limited Regions of the High Plains. Ogallala Aquifer program, USDA-ARS. $300,000.  (09/2020 - 08/2025)</li> <li>T. Moore, A. Sheshukov, L. Shamir, D. Flippo. Integrated data science - mechanistic modeling framework to predict cyanoHABS in contrasting freshwater systems. USGS $249,776 (10/2020-09/2023)</li> <li>T. Franti, A. Sheshukov, T. Cruse, B. Gelder, J. Lory. NRCS Ephemeral Gully Erosion Planning Grant PHASE 2: A Regional Assessment of High-Risk Areas for Ephemeral Gully Formation. USDA-NRCS $344,538 (09/2021-12/2023)</li> </ol>   Reports: <ol> <li>National Academies of Sciences, Engineering, and Medicine. 2020. Review of the New York City Watershed Protection Program. Washington, DC: The National Academies Press. doi: <a href="https://doi.org/10.17226/25851">https://doi.org/10.17226/25851</a> (Boyer, Easton, Pradhanang)</li> <li>Easton, Z.M., K., Stephenson, A. Collick, P.M. Fleming, E. Kellner, J. Martin, M. Ribaudo, and G. Shenk. 2020. Increasing Effectiveness and Reducing the Cost of Non-Point Source Best Management Practice Implementation: Is Targeting the Answer? STAC Publication Number 20-002.</li> <li>Sample, D.J., Nayeb Yazdi, M., Wang, X., and Shahed Behrouz, M., 2021. Characterization of Runoff Water Quality, Treatment in Noncomforming Ponds, and Modeling Implications for the City of Virginia Beach, Virginia, Final Report, p. 170.</li> <li>Kline, K., Moneymaker, J., & Benham, B. 2020. A Water Quality Improvement Plan to Reduce Bacterial Contamination and Sediment Loads in Buffalo River located in Amherst County, Virginia.: A Water Quality Improvement Plan to Reduce Bacterial Contamination and Sediment Loads in Buffalo River located in Amherst County, Virginia. Virginia Department of Environmental Quality.</li> <li>Pradhanang, S. M., Boving, T.B, Brown, R and Jahan, K., 2021. Effectiveness of roadside best management practices in managing water quality (submitted to the Rhode Island Department of Transportation).</li> <li>Pradhanang, S. M., Boving, T.B and Panthi, J., Ismail, M., and Shrestha, S., 2020. Assessing Saltwater Intrusion under Extreme Storm Conditions for Coastal Aquifers (submitted to the Rhode Island Housing and Urban Development).</li> </ol>   Book Chapters: <ol> <li>Pradhanang, S. M. and Jahan*, K., 2021 Urban Water Security for Sustainable Cities in the Context of Climate Change. In Pandey et al. eds Water, Climate Change, and Sustainability, Wiley Publications.</li> <li>Pradhanang, S.M., and Jahan*, K., 2021 Structural Best Management Practices and Watershed Management. In Encyclopedia of the UN Sustainable Development: Clean Water and Sanitation.  Springer Publications</li> <li>Pradhanang, S. M., and Tamanna*, M. 2020 Water Management: South Asia. In Wang, Y. ed., 2020. Fresh Water and Watersheds. CRC Press</li> </ol>   Conference presentations: <ol> <li>Workshop for the Association of Clean Water Administrators on Natural Language Processing for TMDL review (Texas A&M- Kumar)</li> <li>3-introductory and advanced workshops on watershed/water quality modeling (Texas A&M- Srini</li> <li>25 Stream restoration and green stormwater infrastructure workshops (Texas A&M- Jaber)</li> <li>Kmetz, J., Aiken, R., Young, K., Pradhanang, S.M.  Allen, L.,2021. Submarine Groundwater Discharge (SGD) resolved at high resolutions in Rhode Island Coastal Estuaries, Ninigret and Green Hill Ponds, using small Unmanned Aircraft System (sUAS) deployed Thermal Infrared (TIR) imaging, UCOWR, NWRI June 10, 2021 </li> <li>Young, K., Pradhanang, S.M.,  Kmetz, J.,  Aiken,R.,  Allen, L., 2021, Analysis of Submarine Groundwater Discharge (SGD) temporal dynamics in Northern Ninigret Pond, Coastal Rhode Island using Radon-222 and small Unmanned Aircraft Systems (sUAS) deployed Thermal Infrared (TIR) imaging, UCOWR, NWRI June 10, 2021 </li> <li>Young, K., Pradhanang, S.M., 2021.Small Unmanned Aircraft (sUAS) deployed thermal infrared (TIR) imaging for environmental surveys with implications in submarine groundwater discharge (SGD): methods, challenges, and novel opportunities. UCOWR, NWRI June 10, 2021</li> <li>Pradhanang, S.M., Campbell, A. and Kouhi, S., 2020, December. Streamflow High Spells Analysis to Evaluate Flood Risks and Severity. In AGU Fall Meeting Abstracts (Vol. 2020, pp. GC084-0005).</li> <li>Pradhanang, S. M., Meisinger, E., Kirby, K., and Kmetz, J., 2020. Water Treatment Innovation Using Floating Wetland Islands, North American Lake Management Society, November 18, 2020.</li> </ol>

Impact Statements

Date of Annual Report: 11/09/2022

Report Information

Annual Meeting Dates: 07/17/2022 - 07/17/2022
Period the Report Covers: 10/01/2021 - 09/30/2022

Participants

Participants:
In person attendees (7):
● Fouad Jaber - Texas A&M
● Adel Shirmohammadi - University of Maryland
● Rafael Muñoz-Carpena - University of Florida
● Jasmeet Lamba - Auburn University
● Bill Ford - University of Kentucky
● Arun Bawa - Texas A&M
● Soni Pradhanang - University of Rhode Island

Virtual Attendees (4):
● Aleksey Sheshukov - Kansas State University
● David Sample - Virginia Tech
● Latif Kalin - Auburn University
● Elizabeth Boyer - Penn State University

Brief Summary of Minutes

The annual meeting was held in Marriott Marquis Hotel in Houston, TX on July 17, 2022, a day prior to the start of the ASABE Annual International Meeting. Discussion topics of the meeting focused on addressing S1089 objectives, presenting accomplishments, and identifying potential tasks and/or research products delivered by the members of the Multistate Exchange Group. Meeting participants submitted state reports, highlighted accomplishments in 2021-2022 year, and posed future goals. All presentations were carried out either in-person or via Zoom.

Committee chair, Dr. Rafael Muñoz-Carpena, overviewed the previous project on TMDL and expressed that the project was successful and focused on process level models and problem centric solutions and recommendations. He concluded that coherence and success of journal collection can be important for multistate activities. Dr. Soni M Pradhanang presented an overview and history of the S1089 project, reporting requirements, and results of last year's meeting.

Project members, in-person and virtual, had extensive discussions on the special collection introduced during 2021 meeting. All participants participated in selection of overarching topic, research subtopics, potential journals, and individual papers. Dr. Adel Shirmohammadi overviewed the efforts of previous multistate projects that resulted in special collections. Journal of Environmental Management was selected as a top priority journal for this collection. Proposals for the special collection will need to be completed and submitted to the journal for consideration in 2022. Below is a tentative list of proposed papers, responsible authors, and brief overviews.

Cover (synthesis) paper: Advances and gaps in BMPs (agricultural, urban, forestry, etc.) across critical landscapes and scales (collection editor(s))

Using integrative metrics and data sources to characterize additive ecosystem services provided by urban stormwater management (McMillan, Jaber, Birgand, Saurav)
1. This is a framework paper with the first part describing the key paradigms, barriers, opportunities (where are they placed, how are they designed, what is the goal, maintenance, etc.). Case study examples that integrate at least two dimensions (social, economic, biophysical) across scales from neighborhood or watershed.

Advances and gaps in the Monitoring of BMPs: a critical review of methods to enhance BMP understanding, effectiveness, modeling and design (François Birgand, Bryan Maxwell, Randall Entheridge, Tiffany Messer, Jaber, Sheshukov, McMillan, Young, Hunt, Burchell, Pradhanang, Saurav)

Progress Toward Achieving Nutrient and Sediment Reduction Goals Through Watershed Management: A regional review (Beth Boyer, Soni Pradhanang, Sanjiv Kumar, Zach Easton, Kevin Wagner, Shreeram Inamdar, Aleksey Sheshukov, Philippe Vidon, Bill Ford, Jasmeet Lamba)

Limitations and uncertainties in predicting mitigation of runoff contaminants with vegetation buffers at the field and watershed scale (Soni Pradhanang, Rafa Muñoz-Carpena, Marzia Tamanna, Arthur Gold, Philippe Vidon, Shreeram Inamdar, Kelly Addy)

Critical Spatio-Temporall Scales for BMP design: Systems thinking applied to BMP development and management (Rafa Muñoz-Carpena, Adel Shirmohammadi, Jasmeet Lamba, Saurav, Bill Ford, Aleksey Sheshukov)
1. Critical BMP physical process scales and human scales; Critical BMP human scales: Data, Management Action, Lifecycle and Maintenance, Societal Benefit; Lag time in BMP response and policy implication; Gaps between scales

Alternative water resources in the context of climate change (Adel Shirmohammadi, Fuad Jaber, Masoud Negahban-Azar, Hubert Montas)
1. Stress on Water Resources under Climate and Future Climate Scenarios; Rain water harvesting; Reusable water (e.g., WTP discharge, Food processing units, desalination, etc); Economic, Social, and policy (e.g., FSMA -Food Safety Modernization Act); Feasibility of Alternative Water Resources.

Legacy nutrients and sediments impacting the efficiency of BMP performance: Model assessment and improvement needs (Jasmeet Lamba)

A spatial framework for detecting water quality and targeting BMPs in agricultural watersheds (Kevin Wagner)

Role of AI/Machine Learning in identifying hotspots and allocation of BMPs (Saurav Kumar)

Time and location of the next annual meeting was discussed and several options are presented below. The leadership group will meet during the year and decide on the potential location of next year’s annual meeting:

UNL at Lincoln, NE to tag along with next year’s ASABE conference

Iowa State University at Ames, IA as it is close to next year’s ASABE conference

University of Puerto Rico - Fouad and Soni will inquire about adding participants from there

Auburn University at Auburn, AL

Kansas State University at Manhattan, KS to tag along with next year’s ASABE conference

Elected officers (2022-2023):

Secretary: Latif Kalin (Auburn U)

Vice Chair: Aleksey Sheshukov (KSU)

Chair: Fouad Jaber (Texas A&M)

Past Chairs:

Rafa Munoz-Carpena (2020-2022)

Soni Pradhanang (2020-2021)

Accomplishments

Accomplishments: The main focus of this project is to improve the abilities to better understand and predict pollutants and evaluate the effectiveness of best management practices (BMPs) on critical landscapes at the watershed scale. This includes hillslope soil health, water quality of streams and waterbodies, environmental benefits of mitigation practices and cost effectiveness of BMPs. The objectives will be met through the following activities: monitoring at sub-watershed scales, modeling at larger spatial scales, and analyzing uncertainty in both monitoring and modeling efforts. Short-term Outcomes: Project activities from October 2021 to September 2022 are summarized in the following state reports: Texas A&M (F. Jaber) Texas A&M developed TMDL Report Selection Tool (http://Occviz.com/tmdl), a tool that uses natural language processing to understand linkages between modeling tools and impairments. In addition, we developed BMP-Net a deep neural network based on PlanetScope data to identify vegetative and structural BMPs. We worked with USEPA to develop national scale water quality models at HUC8, 10, 12, and 14 digits for the entire U.S and a GIS Tool for determining flood prone areas in Denton county. In collaboration with Nature Conservancy we developed Green stormwater infrastructure prioritization maps for Dallas flooding, a watershed protection plan for Rowlett Creek, Plano, TX, estimated impact of riparian cover on critical shear stress, and developed and implemented HAWQS. Auburn University (J. Lamba, L. Kalin, S. Kumar) A hybrid biophysical-Artificial Intelligence (Physics-AI) model is developed from the first principle to estimate streamflow forecast errors at ungauged locations, improving the forecast's reliability. The first principle refers to identifying the need for the hybrid Physics-AI model, determining physically interpretable and machine identifiable model inputs, followed by the Deep Learning (DL) model development and its evaluations, and finally, a biophysical interpretation of the hybrid model. A very high-resolution National Water Model (NWM) forecast, developed by the National Oceanic and Atmospheric Administration, serves as the biophysical component of the hybrid model. Out of 2.7 million daily forecasts, less than 1% of the forecasts can be verified using the traditional hydrological method of comparing the forecast with the observations, motivating the need for the AI technique to improve forecast reliability at millions of ungauged locations. An exploratory analysis followed by the Classification and Regression Tree analysis successfully determines the dependency of the forecast errors on the biophysical attributes, which along with the NWM forecast, are used for the DL model development. The hybrid model is evaluated in a sub-tropical humid climate of Alabama, and Georgia states in the United States. Long-term streamflow forecasts from zero-day lead to 30-day lead forecasts are archived and analyzed for 979 days (Dec. 2018 to Aug. 2021) and 389 USGS gauging stations. The forecast reliability is assessed as the probability of capturing the observations in its ensemble range. As a result, the forecast reliability increased from 21(±1) % in the NWM only forecasts to 82(±3) % in the hybrid Physics-AI model. University of Kentucky (B. Ford) Research at the University of Kentucky has focused on source, fate and transport of contaminants in karst and tile-drained landscapes, as well as river-tributary confluences.  Seven graduate students have worked on the project (5 contributing during the 21-22 reporting period).  Research in tile drained landscapes has focused on monitoring and modeling of sediment transport in subsurface drainage including ongoing collaborations with the USDA-ARS SDRU in Ohio and USDA-ARS NSERL in Indiana. Deliverables include a peer-reviewed manuscript (Nazari et al., 2022) and a new proposal funded by H2Ohio (ODA) in collaboration with the USDA-ARS SDRU. Research in karst watersheds of central KY has focused on impacts of karst hydrologic and biogeochemical processes on nitrate and dissolved reactive P loadings at the watershed-scale.  During the reporting period, two students have worked on this topic, with one (McGill) receiving his MS degree.  An NSF BPE proposal was funded, and an NSF EPSCOR proposal was submitted to support students, monitoring and modeling initiatives related to this topic.  Two papers (Radcliff et al., 2021 and Husic et al., 2022) were published on this topic.  Research on fate and transport of contaminants in streams has focused on aquatic vegetation characterization using UAVs, impacts of stream restoration on hydrology and water quality in karst landscapes, accumulation of PFAS in benthic sediments, and fate and transport of sediments and nutrients in river-tributary confluences.  During the reporting period, three students have been supported on this topic (with one graduate), and one peer-reviewed paper published (Riddle et al., 2022).   University of Rhode Island (S. Pradhanang) Water use and withdrawal research focused on developing private water suppliers' water use database and web interface for the State of. Rhode Island. The research is a part of USGS’s water use database research program.  In collaboration with the EPA and RI Water Resources Board, agricultural water uses, and allocation optimization model is being developed for southern RI. The Electrical Resistivity survey done in combination with other geophysical methods are used to study saltwater intrusion. The NASA EPSCoR funded grant to study methane and greenhouse gasses in marshes and groundwater aims at understanding whether deep groundwater functions as storage or sink of potent greenhouse gasses. Various stormwater basins within RI Roger Williams Park are monitored to study various pollutants including algae in water.  The USGS supported State map project focuses on mapping the surface geology statewide and focuses on specific areas at a smaller scale for mapping additional layers. RIGS, with partners in the state, plans to develop a hydrogeologic model at the watershed scale to inform statewide planning for water resources, flood preparation and response, and drought monitoring. Kansas State University (A. Sheshukov) The activities were centered over development of w/q models at the watershed, hillslope, and reservoir scales. We developed and calibrated a SWAT model for the Prairie Band Potawatomi Nation tribal area within the Soldier Creek watershed north of Topeka, KS. The model accounts for specific ag cropland and rangeland practices utilized within the tribal land that were obtained with close partnership with KDHE, tribal community, and local residents. Based on the results we developed a plan of BMP implementation for water-quality improvement. We installed a multi sensor stationary buoy in Marion Reservoir in Kansas for detecting valuable blue-green algae characteristics instrumented with in-situ sensors for near continuous measurements of water temperature, specific conductance, dissolved oxygen, pH, dissolved organic matter, turbidity, light penetration and chlorophyll and phycocyanin fluorescence. We studied the benefits (production and environmental) of cotton production in western Kansas by collecting and analyzing data on three cotton fields. The updated crop coefficient function was developed to better reflect thermo-limited conditions of southern Kansas. We analyzed crop field susceptibility to ephemeral gully erosion by collecting data from various sources (LiDAR, historic imagery, drones, etc.) and using geospatial and machine learning approaches. Novel approaches to detection of gully formations from aerial images were developed and applied in a HUC-12 area. University of Maryland (A. Shirmohammadi) Work was focused on post model outcome development; interfacing SWAT model with agent-based model; identifying hotspots using genetic algorithms; social acceptability and cost effectiveness of modeling results on NPS pollution hotspots. We looked at the importance of picking BMPs based on hotspot identification rather than random allocation. The studies at Warner Creek Watershed in the Monocracy River Basin and Choptank River Watershed in the Coastal Plain of Maryland were on modeling based on available long-term monitoring data, while multicriteria decision analysis framework was developed for water reuse and irrigation economics in agriculture. University of Florida (R. Muñoz-Carpena, Y. Her) The accomplishments from the Florida team are about BMP adoption in Florida (Dr. Young Gu Her) and analysis of the effectiveness and long-term effects of a commonly adopted BMP (vegetative filter strips) form surface runoff pollution control, including the regulatory implications (Dr. Muñoz-Carpena). We also study large-scale hydrological, water quality and ecological impacts of agricultural development of smallholders in Africa (Laikipia, Kenya) and adoption of BMP (reduced tillage, soil management) to assess the distant ecological degradation of the dry African savanna introduced by these developments (Dr. Muñoz-Carpena). Dr. Muñoz-Carpena serves as Chair of this Hatch Project for this year and will coordinate the reporting and efforts. Under the organization of this group, we will submit and develop a special journal collection on the topic of "Advances and gaps in agricultural and urban BMPs across critical scales” that will be submitted to a top-tier journal in the specialty. Virginia Tech (D. Sample) Watershed research at Virginia Tech is focused upon stormwater management, watershed modeling, and well water quality. Stormwater research at Virginia Tech is currently focused on 1) monitoring runoff from urban catchments with homogenous land use, and using these data for calibration of hydrologic/water quality models; 2) developing integrated urban hydrologic/sediment transport models of urbanized catchments using SWMM and HEC-RAS with and without best management practices (BMPs) to assess which projects and criteria enhance stream stability. Watershed modeling and management is currently focused on 1) quantifying nitrogen removal rates from spring bioreactors treating legacy nitrogen in groundwater, specifically the effect of nitrogen loading and flow permanence and variability on removal rates. This includes working with partners at Virginia Dept of Environmental Quality (DEQ) to develop a $1 million pilot program using bioreactors to treat legacy nitrogen; 2) integrating real-time animal/environmental sensing using IoT sensors and modeling with autonomous robotics to manage pasture-based manure nutrients; 3) developing integrated agroecosystem models to evaluate the impacts of climate change, best management practices, uncertainty, and management actions on natural resources and farm viability. Twelve journal articles (10 published and 2 in press), 1 dissertation, and 6 proposals were produced and/or awarded, and 6 presentations were made during 2021-22. Ten students were mentored during this period. University of Georgia (G. Vellidis) Research at the University of Georgia focused on developing and evaluating BMPs for the traditional cotton-peanut-corn crop rotation used in the agricultural areas of the state. All crops were planted into a rye cover crop using strip tillage following burndown with glyphosate. Three irrigation × three fertilization treatments were evaluated in the corn and cotton plots.  These consisted of two irrigation and two fertilization BMPs compared to standard practice. Fertilization BMPs that were evaluated include using fertigation to apply side-dress N on corn and cotton and using UAV-derived NDVI to apply side-dress N on cotton. Irrigation scheduling BMPs include using soil moisture sensors and ET-based scheduling tools.  Since N fertilizer is not applied to peanut during the growing season, nine irrigation treatments were evaluated in peanut. These included seven irrigation scheduling BMPs compared to a rainfed treatment and a farmer-standard irrigation scheduling practice.  Data collected include continuous soil moisture measured with matric potential type soil moisture sensors and soil nitrogen and crop biomass measured at regular intervals for the corn and cotton crops. Biomass included dry weight of separate plant tissues as well as Total Kjeldahl Nitrogen (TKN) and yield. Soil samples were analyzed for Nitrate, Ammonium, and TKN. Purdue University (S. McMillan) Our project goals are to better understand the mechanisms for effective agricultural conservation practices at the site and watershed scales. This work focuses on identifying environmental controls using experiments and monitoring data to incorporate knowledge in management and restoration strategies. We have multiple projects to address this in wetlands, floodplains, and infield practices on working farms. Our work in wetlands (USDA NIFA) and floodplains (NSF) focuses on maximizing nutrient retention while mitigating the deleterious climate effects of CH4 and N2O release. In paired watershed studies (EPA), we are working at the HUC-12 scale to link changes in stream chemistry and nutrient loading to land use practices. Together this work will help generate models that are informed by ecosystem processes as we design restoration practices from site to watershed scales that are optimized to improve water quality through nutrient retention, minimize climate impact by reducing GHG emissions, and maximize agricultural productivity. University of Delaware (S. Inamdar) Our overall goal is to better understand the concentrations, forms, and fluxes of nitrogen (N) in watersheds and how land use activities and BMPs affect this pollutant. Currently we have three emphasis areas where we are studying the fate and transport of N.  These three focus areas are: (1) the effect of milldams and similar barriers on the concentrations, forms, fate and transport of N in stream and riparian zones; (2) the concentrations, fate and transport of N associated with suspended legacy sediment transport in watersheds; and (3) the concentrations and fate of N in restored stream floodplains. We have multiple NSF and USDA AFRI projects addressing these areas of research. Oklahoma State University (K. Wagner) Watershed research at the Oklahoma Water Resources Center focuses on evaluating implementation of novel regenerative agricultural BMPs and virtual fencing. Through small watershed scale monitoring of water quality and quantity, we are working to inform watershed scale modeling and provide insights into processes that determine pollutant fate and transport and the role these novel BMPs play in pollutant reduction. With funding from USDA-NIFA, 12 small watershed sites were installed this year in Altus, Oklahoma to evaluate the benefits of regenerative agriculture practices in cotton production systems. Samples were collected from 8 runoff events this project period. With funding from OSU’s Thomas E. Berry Professorship, monitoring of runoff from 10 small watersheds at the Cross Timbers Experimental Range continued, helping improve understanding of how natural sources and conventional grazing practices impact grazing land water quality. 104 samples were collected over 17 events this project period. Finally, with funding from EPA, 2 paired watersheds were installed this year to evaluate the water resource benefits of using virtual fencing to improve grazing management. 33 samples were collected over 13 runoff events this project period. This first year, continuous grazing is being implemented at all sites to serve as a baseline for evaluation. In year 2, virtual fencing will be used to implement rotational grazing and riparian protection.   Outputs: Publications, conferences, reports and thesis: Journals: 75; Thesis/Dissertations: 8; Proposals: 27   Impacts: Activities: The technical committee and the officers met virtually every other month to discuss project objectives and plans for the annual meeting.

Publications

<ol> <li>Nazari, S., Ford, W.I., King, K. 2022.  Impact of flow pathway and source water connectivity on subsurface sediment and particulate phosphorus dynamics in tile-drained agroecosystems. Agricultural Water Management. 269: 107641. https://doi.org/10.1016/j.agwat.2022.107641. </li> <li>Riddle, B., Fox, J., Mahoney, D. T., Ford, W., Wang, Y., Pollock, E., Backus, J. 2022. Investigation of carbon and nitrogen stable isotope tracers (non)conservativeness for sediment fingerprinting. Science of the Total Environment. 817: 152640. https://doi.org/10.1016/j.scitotenv.2021.152640. </li> <li>Radcliff, C., Ford, W.I., Nazari, S. Sheppard, C.  2021. Impact of water source dynamics on dissolved reactive phosphorus loadings in heterogeneous karst agroecosystems with phosphatic limestones. Hydrological Processes. 35(11): e14422. <a href="https://doi.org/10.1002/hyp.14422">36Thttps://doi.org/10.1002/hyp.14422</a>36T. </li> <li>Husic, A., Fox, J., Al Aamery, N., Ford, W., Pollock, E., Backus, J. 2021. Seasonality of recharge drives spatial and temporal nitrate removal in a karst conduit as evidenced by nitrogen isotope modeling. JGR Biogeosciences. e2021JG006454. <a href="https://doi.org/10.1029/2021JG006454">https://doi.org/10.1029/2021JG006454</a>. </li> <li>Shahed Behrouz, M.S., Yazdi, M.N., Sample, D.J., 2022. Using Random Forest, a machine learning approach to predict nitrogen, phosphorus, and sediment event mean concentrations in urban runoff. J. Environ. Manage. 317, 115412. https://doi.org/10.1016/j.jenvman.2022.115412</li> <li>Shahed Behrouz, M. S., Yazdi, M. N., Sample, D. J., Scott, D., and Owen, J. S., 2022. What are the relevant sources and factors affecting event mean concentrations (EMCs) of nutrients and sediment in stormwater? Science of the Total Environment, 828, 154368. https://doi.org/10.1016/j.scitotenv.2022.154368</li> <li>Alamdari, N., Claggett, P., Sample, D., Easton, Z., and Nayeb Yazdi, M., 2022. Evaluating the joint effects of climate and land use change on runoff and pollutant loading. Journal of Cleaner Production, 330, 129953, doi:10.1016/j.jclepro.2021.129953 </li> <li>Sangster, S., Gruver, M., Lacerda, L., Perry, C., Washington, B., Vellidis, G. 2021. Evaluation of irrigation and fertilization strategies to improve irrigation and nitrogen water use efficiencies in cotton. 2021 ASA, CSSA, SSSA International Annual Meeting, 08 November 2021, Salt Lake City, UT, USA, <a href="https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/136430">https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/136430</a> </li> <li>Vellidis, G., Butts, C., Gallios, I., Ortiz, B. 2021. CropFIT - an integrated SmartIrrigation mobile app for corn, cotton, peanut, and soybean. 2021 ASA, CSSA, SSSA International Annual Meeting, 08 November 2021, Salt Lake City, UT, USA, <a href="https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/135167">https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/135167</a></li> <li>Gallios, I., Butts, C., Perry, C., Vellidis, G. 2021. Making Irrigator Pro and easier to use irrigation scheduling tool. 2021 ASA, CSSA, SSSA International Annual Meeting, 08 November 2021, Salt Lake City, UT, USA, <a href="https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/135255">https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/135255</a> </li> <li>Shrestha, S.G. and Pradhanang, S.M., 2022. Optimal selection of representative climate models and statistical downscaling for climate change impact studies: a case study of Rhode Island, USA. Theoretical and Applied Climatology.</li> <li>Sharma, S., Talchabhadel, R., Nepal, S., Ghimire, G., Rakhal, B., Panthi, J., Adhikari, B., Pradhanang, S. M., Maskey, S., and Kumar, S., 2022. Increasing risk of cascading hazards in the central Himalayas. Nat Hazards. <a href="https://doi.org/10.1007/s11069-022-05462-0">https://doi.org/10.1007/s11069-022-05462-0</a></li> <li>Panthi, J., Pradhanang, S.M., Nolte, A. and Boving, T.B., 2022. Saltwater intrusion into coastal aquifers in the contiguous United States—A systematic review of investigation approaches and monitoring networks. Science of The Total Environment, p.155641.</li> <li>Pengfei Liu, Yu Wang, Wei Zhang, "<a href="https://onlinelibrary.wiley.com/doi/full/10.1111/ajae.12316">The Influence of the Environmental Quality Incentives Program on Local Water Quality</a>", American Journal of Agricultural Economics. 2022. <a href="https://doi.org/10.1111/ajae.12316">https://doi.org/10.1111/ajae.12316</a></li> <li>Odeh, T., Mohammad, A.H., Pradhanang, S.M., Ismail, M. and Rödiger, T., 2021. GIS-based Analytical Modeling on Evaluating Impacts of Urbanization in Amman Water Resources, Jordan.</li> <li>Panthi, J., Talchabhadel, R., Ghimire, G.R., Sharma, S., Dahal, P., Baniya, R., Boving,  T., Pradhanang, S.M. and Parajuli, B., 2021. Hydrologic  Regionalization under Data Scarcity: Implications for Streamflow Prediction. Journal of Hydrologic Engineering, 26(9), p.05021022.</li> <li>Inamdar, S., Peipoch, M., Gold, A.J., Lewis, E., Hripto, J., Sherman, M., Addy, K., Merritts, D., Kan, J., Groffman, P.M. and Walter, R., 2021. Ghosts of landuse past: legacy effects of milldams for riparian nitrogen (N) processing and water quality functions.  Environmental Research Letters, 16(3), p.035016.</li> <li>Hollister, J.W., Kellogg, D.Q., Lei-Parent, Q., Wilson, E., Chadwick, C., Dickson, D., Gold, A. and Arnold, C., 2022. nsink: An R package for flow path nitrogen removal estimation. Journal of Open Source Software, 7(71), p.4039.</li> <li>Lewis, E., S.M. Inamdar, A.J. Gold, K. Addy, T. Trammell, D. Merritts, S., M. Peipoch, P.M. Groffman, J. Hripto, M. Sherman,  J. Kan, R. Walter and E.P. Lewis. 2021. Draining the landscape: How do nitrogen concentrations in riparian groundwater and stream water change following milldam removal? Journal of Geophysical Research – Biogeosciences</li> <li>Suriano, Z. J., C. M. Siegert, D. J. Leathers, A. J. Gold, K. Addy, A. W. Schroth, E. Seybold, S. Inamdar, and D. F. Levia. 2021. Effects of atmospheric circulation on stream chemistry in forested watersheds across the northeastern United States: Part 2. Interannual weather type variability. Journal of Geophysical Research: Atmospheres.  e2021JD034546.</li> <li>Hollister. J. W., Kellogg, D. Q., Kreakie, B. J., Shivers, S., Milstead, W. B., Herron, E., Green, L., Gold, A. 2021. Increasing Chlorophyll a Amid Stable Nutrient  Concentrations in Rhode Island Lakes and Reservoirs. Ecosphere 12, no. 6 (2021): e03555.</li> <li>Muñoz-Carpena, R., Z. Yu, A. Carmona-Cabrero, G. Fox, O. Batelaan, A. Bardossy. 2022. Convergence of mechanistic modeling and artificial intelligence (AI) in hydrologic science and engineering. (under review, J. Hydrology).</li> <li>Muñoz-Carpena, R., Reichenberger S., Sittig S., Sur R. (2022). Complex effects of leaching, sedimentation, sorption and degradation on runoff remobilization of pesticide residues in vegetative filter strips (under review, ACS Environmental AU).</li> <li>Reichenberger, R., R. Sur, S. Sittig, S. Multsch, Á. Carmona-Cabrero, J.J. López and R Muñoz-Carpena. 2022. Dynamic prediction of effective runoff sediment particle size for improved assessment of pesticide mitigation efficiency with vegetative filter strips (under review, Sci. Total Env.)</li> <li>Muñoz-Carpena, R., A. Ritter, R. Sur, S. Reichenberger. 2022. Effect of hydrograph type on the calculation of pesticide mitigation efficiencies of vegetative filter strips with VFSMOD in the regulatory context. (Under review, Integr. Environ. Assess. Manag.). </li> <li>Zhang, Y., R. Bhattarai and R. Muñoz-Carpena. 2022. Effectiveness of vegetative filter strips for sediment control from steep construction areas. (Under review, Catena)</li> <li>Orozco-López E., R. Muñoz-Carpena and B. Gao. 2022. Quantification of solute transport in a soil profile with activated macropore networks using light transmission experiments. (Under review, J Hydrology)</li> <li>Muñoz-Carpena, R., C. Lauvernet, N. Carluer and G.A. Fox. 2021. Comment on “Modeling slope rainfall-infiltration-runoff process with shallow water table during complex rainfall patterns” by Wu et al. 2021. J. Hydrology X 13:100133. <a href="https://doi.org/10.1016/j.hydroa.2021.100113">doi:10.1016/j.hydroa.2021.100113.</a></li> <li>Barchiesi*, S., A. Alonso, M. Pazmiño-Hernandez, J.M. Serrano-Sandí, R. Muñoz-Carpena, C. Angelini. 2021. Wetland hydropattern and vegetation greenness predict avian populations in Palo Verde, Costa Rica. Ecological Applications. <a href="https://doi.org/10.1002/eap.2493">doi:10.1002/eap.2493.</a></li> <li>Orozco-Lopez*, E. and R. Muñoz-Carpena, R. 2021. Comparative non-Darcian modelling of subsurface preferential flow experimental observations in a riparian buffer. Trans. ASABE 64(5). <a href="https://doi.org/10.13031/trans.14559">doi:10.13031/trans.14559</a>.</li> <li>Vazquez*, K.M, R. Muñoz-Carpena, M.D. Danyluk, A.H. Havelaar. 2021. Parsimonious mechanistic modeling of bacterial runoff to inform food safety management of agricultural water quality. Appl. Environ. Microbiol. 87(15):e00596-21. <a href="https://doi.org/10.1128/AEM.00596-21">doi:10.1128/AEM.00596-21.</a></li> <li>Luquin*, E., M.A. Campo-Bescós, R. Muñoz-Carpena, R.L. Bingner, R.M. Cruse, H.G. Momm, R.R. Wells, J.Casalí. 2021. Evaluation of model prediction capacity of ephemeral gully temporal evolution in conservation tillage systems. Earth Surf. Process. Landf. 46(10):1909-1925. <a href="https://doi.org/10.1002/esp.5134">doi:10.1002/esp.5134</a></li> <li>Guertault, L. G.A.Fox, D. Heeren, T. Hallihan and R Muñoz-Carpena. 2021. Quantifying the importance of preferential flow in a riparian buffer. Trans. ASABE 64(3):937-947. <a href="https://doi.org/10.13031/trans.14286">doi:10.13031/trans.14286</a>.</li> <li>Orozco-López*, R. Muñoz-Carpena, B. Gao and G.A. Fox. 2021. High resolution pore-scale water content measurement in a translucent soil profile from light transmission. Trans. ASABE64(3):949-962.<a href="https://doi.org/10.13031/trans.14292">doi:10.13031/trans.14292</a>.</li> <li>Medina M.*, R. Huffaker, R. Muñoz-Carpena and G. Kiker. 2021. An empirical nonlinear dynamics approach to analyzing emergent behavior of agent-based models. AIP Advances11:035133. <a href="about:blank">doi:10.1063/5.0023116</a></li> <li>Song, J.H., Her, Y. and Guo, T., 2022. Quantifying the contribution of direct runoff and baseflow to nitrogen loading in the Western Lake Erie Basins. Scientific Reports, 12(1), pp.1-13.</li> <li>G. Granco, M. Caldas, J. Bergtold, J.L. Heier Stamm, M. Mather, M. Sanderson, M. Daniels, A.Y. Sheshukov, D. Haukos, S. Ramsey. (2022) Local Environment and Individuals’ Beliefs: The Dynamics Shaping Public Support for Sustainability Policy in an Agricultural Landscape. Journal of Environmental Management. 301, 113776. (https://doi.org/10.1016/j.jenvman.2021.113776)</li> <li>Koudahe, K., Sheshukov, A.Y., Aguilar, J., Djaman, K. (2021) Irrigation-Water Management and Productivity of Cotton: A Review. Sustainability. 131: 70. <a href="https://doi.org/10.3390/su131810070">https://doi.org/10.3390/su131810070</a></li> <li>Song, J.H., Her, Y. and Guo, T., 2022. Quantifying the contribution of direct runoff and baseflow to nitrogen loading in the Western Lake Erie Basins. Scientific Reports, 12(1), pp.1-13. https://doi.org/10.1038/s41598-022-12740-1.</li> <li>Inamdar et al., Saturated, suffocated, and salty: Human legacies produce hotspots of nitrogen in riparian zones. Journal of Geophysical Research Biogeosciences (In review).</li> <li>Bhatta, A, R. Prasad, D. Chakraborty, J.N. Shaw, J. Lamba, E. Brantley, H.A. Torbert. 2021. Mehlich 3 as a Generic Soil Test Extractant for Environmental Phosphorus Risk Assessment Across Alabama Soil Regions. Agrosyst Geosci Environ. 2021; 4:e20187. <a href="https://doi.org/10.1002/agg2.20187">https://doi.org/10.1002/agg2.20187</a></li> <li>Kumar, K., P. Srivastava, B. V. Ortiz, G. Morata, B. S. Takhellambam, J. Lamba, and L. Bondesan. 2021. Field-Scale Spatial and Temporal Soil Water Variability in Irrigated Croplands. Transactions of the ASABE: 64 (4), 1277-1294. doi: 10.13031/trans.14335</li> <li>Singh, R., R. Prasad, B. Guertal, K. Balkcom and J. Lamba. 2021. Effects of Broiler Litter Application Rate and Time on Corn Yield and Environmental Nitrogen Loss. Agronomy Journal. doi:<a href="https://doi.org/10.1002/agj2.20944">https://doi.org/10.1002/agj2.20944</a>.</li> <li>Stephenson, K., L. Shabman, J. Shortle, Z.M. Easton. 2022. Confronting our agricultural nonpoint source control policy problem. Journal of the American Water Resources Association. <a href="https://doi.org/10.1111/1752-1688.13010">https://doi.org/10.1111/1752-1688.13010</a></li> <li>Deval, C., E.S. Brooks, M. Dobre, R. Lew, P.R. Robichaud, A. Fowler, J. Boll, A.S. Collick, Z.M. Easton. 2022. Pi-VAT: A web-based visualization tool for decision support using spatially complex water quality model outputs. Journal of Hydrology. <a href="https://doi.org/10.1016/j.jhydrol.2022.127529">https://doi.org/10.1016/j.jhydrol.2022.127529</a></li> <li>Fleming, P., K.S. Stephenson, A.S. Collick, Z.M. Easton. 2022. Targeting for Nonpoint Source Pollution Reduction: A Synthesis of Lessons Learned, Remaining Challenges, and Emerging Opportunities. Journal of Environmental Management. DOI: <a href="https://doi.org/10.1016/j.jenvman.2022.114649">10.1016/j.jenvman.2022.114649</a></li> <li>Modi, P., J. Czuba, Z.M. Easton. 2022. Coupling a land surface model with a hydrodynamic model for regional flood risk assessment due to climate change: application to the Susquehanna River. Journal of Flood Risk Management. <a href="http://doi.org/10.1111/jfr3.12763">http://doi.org/10.1111/jfr3.12763</a></li> <li> Alamdari, N., P. Claggett, D.J. Sample, Z.M. Easton, M. Yazdi. 2022. Evaluating the joint effects of climate and land use change on runoff and pollutant loading in a rapidly developing watershed. Journal of Cleaner Production. <a href="https://doi.org/10.1016/j.jclepro.2021.129953">https://doi.org/10.1016/j.jclepro.2021.129953</a></li> <li> Ketterings, Q. C. Twombly, A. Collick, J. Faulkner, Z.M. Easton. 2022. An evaluation BMP performance using a regional P Index and process-based watershed models. Journal of Environmental Quality (In Press).</li> <li> Ebadi N., D. Bosch, R.R. White, M. Wagena, A.S. Collick, Z.M. Easton. 2022. costs of reducing emissions from a dairy farm: a constrained optimization approach. Agricultural Systems. (In Press).</li> <li> Modi, P., D.R. Fuka, Z.M. Easton. 2021. Impacts of climate change on terrestrial hydrological components and crop water use in the Chesapeake Bay watershed. Journal of Hydrology Regional Studies. <a href="https://doi.org/10.1016/j.ejrh.2021.100830">https://doi.org/10.1016/j.ejrh.2021.100830</a></li> <li> Modi, P., D.R. Fuka, Z.M. Easton. 2021. Data in Short “Impacts of Climate Change on Terrestrial Hydrological Components and Crop Water Requirement in the Chesapeake Bay Watershed. Journal of Hydrology Regional Studies. <a href="https://doi.org/10.6084/M9.FIGSHARE.14049569">https://doi.org/10.6084/M9.FIGSHARE.14049569</a></li> <li>Stephenson, K., W. Ferris, E. Bock, Z.M. Easton. 2021. Treatment of legacy nitrogen as a compliance option to meet Chesapeake Bay TMDL requirements. Environmental Science & Technology. <a href="https://doi.org/10.1021/acs.est.1c04022">https://doi.org/10.1021/acs.est.1c04022</a></li> <li>Duan, Y., Akula, S., Kumar, S., Lee, W. & Khajehei, S. A Hybrid Physics-AI Model to Improve Hydrological Forecasts. Artificial Intelligence for the Earth Systems accepted, doi:10.1175/AIES-D-22-0023.1 (2022).</li> <li>Pan, Z., Kumar, S., Zhang, Y., & Shi, C (2022). Central continental boreal summer “warming holes” modulated by Atlantic Multidecadal Oscillation via low‐level jets. Journal of Geophysical Research: Atmospheres, e2021JD035217.</li> <li>Hripto*, J., Inamdar, S., Sherman, M., Peck, E., Gold, A., Bernasconi, S., Addy, K., & Peipoch, M. Effects of relic low-head dams on stream denitrification potential: seasonality and biogeochemical controls. Aquatic Sciences. <a href="https://doi.org/10.1007/s00027-00894-z">https://doi.org/10.1007/s00027-00894-z</a> (2022) 84:60</li> <li>Peck*, E., Inamdar, S., Sherman, M., Hripto, J., Peipoch, M., Gold, A., & Addy, K. Nitrogen sinks or sources? Denitrification and nitrogen removal potential in riparian legacy sediment terraces affected by milldams. Journal of Geophysical Research Biogeosciences. https://doi.org/10.1007/s00027-022-00894-z</li> <li>Sherman*, M., Hripto, J., Peck, E., Gold, A., Peipoch, M., Imhoff, P., & Inamdar, S. Backed-up, Saturated, and Stagnant: Effect of Milldams on Upstream Riparian Groundwater Hydrologic and Mixing Regimes. Water Resources Research <a href="https://doi.org/10.1029/2022WR033038">https://doi.org/10.1029/2022WR03303</a></li> <li>Dey, S., Saksena, S., Winter, D., Merwade, V. and McMillan, S., 2022. Incorporating Network Scale River Bathymetry to Improve Characterization of Fluvial Processes in Flood Modeling. Water Resources Research, p.e2020WR029521.</li> <li>Hanna, K., Paul, M., Negahban-Azar, M., and Shirmohammadi, A. (2021). Developing a Decision Support System for Economic Analysis of Irrigation Applications in Temperate Zones. Water. <a href="https://doi.org/10.3390/w13152044">https://doi.org/10.3390/w13152044</a></li> <li>Paul, M., Rajib, A., Negahban-Azar, M., Shirmohammadi, A., Srivastava, P. 2021. Improved Agricultural Water Management in Data-scarce Semi-arid Watersheds: Value of Integrating Remotely Sensed Leaf Area Index in Hydrological Modeling. Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2021.148177</li> <li>Paul, M., M. Negahban-Azar, A. Shirmohammadi, and H. Montas. 2021. Developing a Multicriteria Decision Analysis Framework to Evaluate Reclaimed Wastewater Use for agricultural Irrigation: The Case Study of Maryland. Hydrology 8(4):18p.</li> <li>Huang, Y., R. Bawa, J. Mullen, N. Hoghooghi, L. Kalin, P. Dwivedi (2022), “A Stochastic Dynamic Optimization Approach for Understanding Expected Land Use Changes to Meet Potential Water Quality Regulations: A Case Study from Georgia, United States”, Agricultural Water Management. 271, 107799.</li> <li>Bian, Z., S. Pan, Z. Wang, Y. Yao, R. Xu, H. Shi, L. Kalin, C. Anderson, D. Justic, S. Lohrenz, H. Tian (2022), “A century-long trajectory of phosphorus loading and export from Mississippi River Basin to the Gulf of Mexico: Contributions of multiple environmental changes”, Global Biogeochemical Cycles. 36, e2022GB007347. https://doi.org/10.1029/2022GB007347.</li> <li>Haas, H., L. Kalin, P. Srivastava (2022), “Improved Forest Dynamics Leads to Better Hydrological Predictions in Watershed Modeling”, Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2022.153180.</li> <li>Haas, H., M. Reaver, R. Karki, L. Kalin, P. Srivastava, D. Kaplan, C.A. Gonzalez-Benecke (2021), “Improving the representation of forests in hydrological models”, Science of Total Environment. https://doi.org/10.1016/j.scitotenv.2021.151425.</li> <li>Haas, H, F. Dosdogru, L. Kalin, H. Yen (2021), “Land use and land cover input data affects the prediction of ecologically relevant flows in hydrologic modeling Corresponding Author”, Water. 13(21), 2947. https://doi.org/10.3390/w13212947.</li> <li>Karki, R., P. Srivastava, L. Kalin, S. Mitra, S. Singh (2021), “Assessment of impact in groundwater levels and stream-aquifer interaction due to increased groundwater withdrawal in the lower Apalachicola-Chattahoochee-Flint (ACF) River Basin using MODFLOW”, Journal of Hydrology: Regional Studies. Vol 34. https://doi.org/10.1016/j.ejrh.2021.100802.</li> <li>Ramesh, R. L. Kalin, M. Hantush, A. Chaudhary (2021), “A Secondary Assessment of Sediment Trapping Effectiveness by Vegetated Buffers”, Ecological Engineering. Vol 159. <a href="https://doi.org/10.1016/j.ecoleng.2020.106094">https://doi.org/10.1016/j.ecoleng.2020.106094</a>.</li> <li>Wagner, K.L., T.J. Gentry, R.D. Harmel, E.C. Pope, L.A. Redmon. 2021. Grazing effects on bovine-associated and background fecal indicator bacteria levels in edge-of-field runoff. Water 2021, 13, 928. <a href="https://doi.org/10.3390/w13070928">https://doi.org/10.3390/w13070928</a>.</li> </ol> <ol start="71"> <li>Boyer EW, MA Moritz, and MG Brown (2022). Smoke deposition to water surfaces drives hydrochemical changes. Hydrological Processes, 36(6), e14626, DOI: 10.1002/hyp.14626</li> <li>Clark KH, DD Iwanowicz, LR Iwanowicz, SJ Mueller, JM Wisor, C Bradshaw-Wilson, WB Schill, JR Stauffer, Jr., and EW Boyer (2022). Freshwater unionid mussels threatened by predation of Round Goby (Neogobius melanostomus). Scientific Reports, 12, 12859, DOI: 10.1038/s41598-022-16385-y (plus supporting dataset at HydroShare public data repository, DOI: 10.4211/hs.e46d4769a8a346fcaed7a27fcceb20ad)</li> <li>Clark KH, JM Wisor, SJ Mueller, C Bradshaw-Wilson, EW Boyer, and JR Stauffer, Jr. (2021). Status of freshwater mussels (Unionidae) in the French Creek watershed, USA at the onset of invasion by Round Goby, Neogobius melanostomus. Water, 13(21), 3064; DOI: 10.3390/w13213064</li> <li>Zhang K, J. Shen, L Guo, EW Boyer, CR Mello, P Lan, H Liu, J Gao, and B Fan (2021). Flood drainage rights in watersheds based on the harmonious allocation method. Journal of Hydrology, DOI: 10.1016/j.jhydrol.2021.126627</li> <li>Zhang L, G Qin, P Lan, L Yang, CR Mello, EW Boyer, and L Guo (2021). Evaluation of three gridded precipitation products in a data scarce region in mountainous areas of the west China. Remote Sensing, 13:3795, DOI:10.3390/rs13193795</li> </ol> 2) Thesis/Dissertation: <ol> <li>Timothy McGill. Assessing machine learning utility in predicting hydrologic and nitrate dynamics in karst agroecosystems, MS Student (Primary Advisor, Fall 2019-May 2022).</li> <li>Rosalia Agioutanti. Classifying and mapping aquatic vegetation in heterogenous stream ecosystems using visible and multispectral uav imagery, MS Student (Primary Advisor, Fall 2019-May 2022).</li> <li>Gina DeGraves. Sediment nitrogen dynamics in backwater wetland confluences of a regulated river, MS Student (Primary Advisor, Summer 2019-Fall 2021).</li> <li>Lorena Lacerda. 2021. Using remote sensing to develop irrigation scheduling tools for variable rate irrigation, Ph.D. Dissertation, University of Georgia, pp 183.</li> <li>Shahed Behrouz, M., 2022. Improving Predictions of Stormwater Quantity and Quality through the Application of Modeling and Data Analysis Techniques from National to Catchment Scales, Ph.D. Dissertation, Virginia Tech, pp 203.</li> <li>Umme Fatema Piu. 2022. Evaluating evapotranspiration rates for corn and cotton in thermo-limited climate of southwest Kansas. MS, Kansas State University.</li> <li>Dey, S., 2021. Enabling large-scale hydrologic and hydraulic modeling through improved topographic representation. PhD dissertation, Purdue University.</li> <li>Phillippe, A.J. 2022. Determining bacterial and nutrient concentrations and loadings of surface runoff from differing grazer access and vegetative cover in Northcentral Oklahoma. MS Thesis, Oklahoma State University.</li> </ol> 3) Proposals Awarded/Submitted: <ol> <li>Fox, J., Ford, W., Mahoney, D., Armstead, M., Dadi, G. BPE-Track 3:  Inclusive Mentoring Hub for Enabling Pathways from Inner-City and Rural Appalachian Households to Engineering in Kentucky and West Virginia. NSF-BPE. $799,445. Role Co-Investigator. July 2022-July 2027</li> <li>Ford, W. Using edge-of-field data and modeling to inform H2Ohio. Ohio department of agriculture  $150,000 (as sub-award from USDA-ARS). Role: Principal Investigator.</li> <li>Fox, J., Mahoney, D., Ford, W., Armstead, M. RII-BEC: Undergraduate research as a model of excellence to broaden STEM participation in EPSCoR jurisdictions: What are the mentoring costs? NSF RII-BEC. $1,000,000. Role Co-Investigator.</li> <li>Improving the Sustainability of Georgia Cotton by Increasing Nitrogen and Water Use Efficiencies, Georgia Cotton Commission, 2021-2022, $58,000, Vellidis PI</li> <li>Expansion of an Irrigation Scheduling Application to the U.S, Cotton Incorporated, 2021-2022, $50,000, Vellidis PI</li> <li>Incorporating Volumetric Water Content (Capacitance) Sensors into the Irrigator Pro-Based Irrigation Scheduling Tool, 2021-2022, $18,000, Vellidis PI</li> <li>Making Irrigator Pro an Easier-to-Use Irrigation Scheduling Tool, 2021-2022, Southern Peanut Research Initiative, $25,000, Vellidis PI.</li> <li>Sample, D.J. and Scott, D., Vibrant Virginia-Improving the Resilience of Stormwater Treatment in Fredericksburg: Amount: $60,000. Sponsor: VT Center for Economic and Community Engagement, 1/01/2021 - 06/30/2022.</li> <li>Shahed Behrouz, M., 2021. New Conceptualizations of Catchment-Scale Stormwater Pollution Generation Processes, Virginia Water Resources Research Center Competitive Grant, $7,000, 10/1/21-8/31/22. </li> <li>Cardace, D., Pradhanang, S. M., and Moseman-Valtiera, S., Planetary Methane in Ultramafic Contexts: Searching for Cyclicity in Methane Emissions at a Planetary Analog Site in Northern California, NASA-EPSCoR $735,000 (6/2022-6/2025)</li> <li>Savage, B., Pradhanang, S. M., Boving, T. Mapping Bedrock and Saltwater Intrusion in Rhode Island, USGS $90,000 (09/2021-08/2022)</li> <li>Savage, B., Pradhanang, S. M., Boving, T., Mapping Bedrock and Saltwater Intrusion in Rhode Island USGS $117,337 (09/2022-08/2023)</li> <li>Pradhanang, S., Kumar, R, and Rashid T, Floating Treatment Wetland System (FTWS) - Sustainable green technology to remediate polluted surface water bodies in the COVID 19-era , Asia- Pacific  Network $78,000 (09/2021-08/2023)</li> <li>Pradhanang, S. M., Boving, T., and Savage, B. The Rhode Island Water Resources Board (RIWRB) and University of Rhode Island (URI) Statewide Water Withdrawal Data Enhancement and Database Development Project. RIWRB-USGS $197,488 (10/20-09/22)</li> <li>T Franti, A. Sheshukov, J. Lory, R. Cruse. Developing and assessing innovative ephemeral gully erosion control practices. (2021-2023). USDA $344,538</li> <li>R.L. North, A. Ohler, L. McCann, T. Moore, A. Sheshukov. Valuing Water Quality Improvements in Heartland Reservoirs. (2022-2025) EPA $741,285</li> <li>Pradhanang, S.M., Liu, P. Water Availability through the Integration of Hydrologic Model and Water Management Optimization Tool for Chipuxet River Watershed, Rhode Island. RIWRC-USGS. (2022-2023) USGS $50,000</li> <li>USDA-Cooperative Agreement. Fuka, D.R., Z.M. Easton, R.R. White. Developing and evaluating rapidly deployable inexpensive weather, soil moisture, shock, and streamflow sensors to aid the monitoring, inspection, and rehabilitation of aging dams. $225,000. Dec 2021-Nov 2022.</li> <li>USDA-Cooperative Agreement. Easton, Z.M. Modeling the Lake Champlain Basin CEAP watersheds to understand and predict conservation effects on legacy phosphorus. $134,223. Oct 2021-Sept 2023.</li> <li>Virginia Tech CALS Strategic Plan Advancement. Easton, Z.M., R.R. White, K. Hamed, D.R. Fuka, M. Eick. Eyes in the Sky and Boots on the Ground: Collaborative Technologies for Monitoring and Managing Livestock Pastures. $60,000. Oct 2021-May 2023.</li> <li>NSF CPS (Cyber-Physical Systems). White, R.R., E. Feuerbacher, Z.M. Easton. Collaborative Research: CPS: Medium: Greener Pastures: A pasture sanitation cyber physical system for environmental enhancement and animal monitoring. $998,232. Jan 2022-Dec 2024.</li> <li>Lewis, K., K. Wagner, A. Berthold, P. DeLaune, J. Bell, D. Miller Sustainable. Agricultural Intensification and Enhancement through the Utilization of Regenerative Agricultural Management Practices. Amount: $583,438 (Total Award: $10,000,000). Sponsor: USDA-NIFA Sustainable Ag Systems Program, 9/1/2021-8/31/2026.</li> <li>Wagner, K. Dam Analysis Modernization of Tools, Applications, Guidance, and Standardization (DAM-TAGS) Project – Year 1. Amount: $478,238. Sponsor: USDA-ARS Cooperative Agreement, 6/10/2021-6/9/2022.</li> <li>Wagner, K., R. Bonett, A. Sewell, J. Gonzalez Estrella, S. Kim, A. Dzialowski. Oklahoma Water Resources Research Institute Program (USGS Base Funds FY21). Amount: $125,000. Sponsor: USGS, 9/1/2021-8/31/2022.</li> <li>Mirchi, A, K. Wagner, S. Taghvaeian, Sarah Alian, R. Bailey. Conjunctive Freshwater-Saltwater Management for Climate-Resilient Agroecosystems. Amount: $181,568 (Total Award: $749,786). Sponsor: USDA-NIFA Foundational Program, 12/31/2021-12/12/2025.</li> <li>Wagner, K., S. Sharma, S. Taghvaeian, S. Frazier, J. Warren, A. Mirchi. Oklahoma Master Irrigator Program and Ogallala Aquifer Study. Amount: $150,000. Sponsor: Oklahoma Conservation Commission, 7/1/2021-6/30/2022.</li> <li>Reuter, R., K. Wagner, L. Goodman, C. Duchardt, B. Murray. Increasing the pace & scale of adoption of prescribed grazing through virtual fence technology. Amount: $93,188 (Total Award: $1,365,774). Sponsor: USDA-NRCS Conservation Innovation Grant, 7/1/2022-6/30/2025.</li> </ol>

Impact Statements

Date of Annual Report: 11/09/2022

Report Information

Annual Meeting Dates: 07/17/2022 - 07/17/2022
Period the Report Covers: 10/01/2021 - 09/30/2022

Participants

Brief Summary of Minutes

Brief summary of minutes of annual meeting:

Cover (synthesis) paper: Advances and gaps in BMPs (agricultural, urban, forestry, etc.) across critical landscapes and scales (collection editor(s))

Using integrative metrics and data sources to characterize additive ecosystem services provided by urban stormwater management (McMillan, Jaber, Birgand, Saurav)
1. This is a framework paper with the first part describing the key paradigms, barriers, opportunities (where are they placed, how are they designed, what is the goal, maintenance, etc.). Case study examples that integrate at least two dimensions (social, economic, biophysical) across scales from neighborhood or watershed.

Advances and gaps in the Monitoring of BMPs: a critical review of methods to enhance BMP understanding, effectiveness, modeling and design (François Birgand, Bryan Maxwell, Randall Entheridge, Tiffany Messer, Jaber, Sheshukov, McMillan, Young, Hunt, Burchell, Pradhanang, Saurav)

Progress Toward Achieving Nutrient and Sediment Reduction Goals Through Watershed Management: A regional review (Beth Boyer, Soni Pradhanang, Sanjiv Kumar, Zach Easton, Kevin Wagner, Shreeram Inamdar, Aleksey Sheshukov, Philippe Vidon, Bill Ford, Jasmeet Lamba)

Limitations and uncertainties in predicting mitigation of runoff contaminants with vegetation buffers at the field and watershed scale (Soni Pradhanang, Rafa Muñoz-Carpena, Marzia Tamanna, Arthur Gold, Philippe Vidon, Shreeram Inamdar, Kelly Addy)

Critical Spatio-Temporall Scales for BMP design: Systems thinking applied to BMP development and management (Rafa Muñoz-Carpena, Adel Shirmohammadi, Jasmeet Lamba, Saurav, Bill Ford, Aleksey Sheshukov)
1. Critical BMP physical process scales and human scales; Critical BMP human scales: Data, Management Action, Lifecycle and Maintenance, Societal Benefit; Lag time in BMP response and policy implication; Gaps between scales

Alternative water resources in the context of climate change (Adel Shirmohammadi, Fuad Jaber, Masoud Negahban-Azar, Hubert Montas)
1. Stress on Water Resources under Climate and Future Climate Scenarios; Rain water harvesting; Reusable water (e.g., WTP discharge, Food processing units, desalination, etc); Economic, Social, and policy (e.g., FSMA -Food Safety Modernization Act); Feasibility of Alternative Water Resources.

Legacy nutrients and sediments impacting the efficiency of BMP performance: Model assessment and improvement needs (Jasmeet Lamba)

A spatial framework for detecting water quality and targeting BMPs in agricultural watersheds (Kevin Wagner)

Role of AI/Machine Learning in identifying hotspots and allocation of BMPs (Saurav Kumar)

UNL at Lincoln, NE to tag along with next year’s ASABE conference

Iowa State University at Ames, IA as it is close to next year’s ASABE conference

University of Puerto Rico - Fouad and Soni will inquire about adding participants from there

Auburn University at Auburn, AL

Kansas State University at Manhattan, KS to tag along with next year’s ASABE conference

Elected officers (2022-2023):

Secretary: Latif Kalin (Auburn U)

Vice Chair: Aleksey Sheshukov (KSU)

Chair: Fouad Jaber (Texas A&M)

Past Chairs:

Rafa Munoz-Carpena (2020-2022)

Soni Pradhanang (2020-2021)

Minutes Attachment:

appendix_d_s1089_2022.pdf

Accomplishments

Accomplishments: The main focus of this project is to improve the abilities to better understand and predict pollutants and evaluate the effectiveness of best management practices (BMPs) on critical landscapes at the watershed scale. This includes hillslope soil health, water quality of streams and waterbodies, environmental benefits of mitigation practices and cost effectiveness of BMPs. The objectives will be met through the following activities: monitoring at sub-watershed scales, modeling at larger spatial scales, and analyzing uncertainty in both monitoring and modeling efforts. Short-term Outcomes: Project activities from October 2021 to September 2022 are summarized in the following state reports: Texas A&M (F. Jaber) Texas A&M developed TMDL Report Selection Tool (http://Occviz.com/tmdl), a tool that uses natural language processing to understand linkages between modeling tools and impairments. In addition, we developed BMP-Net a deep neural network based on PlanetScope data to identify vegetative and structural BMPs. We worked with USEPA to develop national scale water quality models at HUC8, 10, 12, and 14 digits for the entire U.S and a GIS Tool for determining flood prone areas in Denton county. In collaboration with Nature Conservancy we developed Green stormwater infrastructure prioritization maps for Dallas flooding, a watershed protection plan for Rowlett Creek, Plano, TX, estimated impact of riparian cover on critical shear stress, and developed and implemented HAWQS. Auburn University (J. Lamba, L. Kalin, S. Kumar) A hybrid biophysical-Artificial Intelligence (Physics-AI) model is developed from the first principle to estimate streamflow forecast errors at ungauged locations, improving the forecast's reliability. The first principle refers to identifying the need for the hybrid Physics-AI model, determining physically interpretable and machine identifiable model inputs, followed by the Deep Learning (DL) model development and its evaluations, and finally, a biophysical interpretation of the hybrid model. A very high-resolution National Water Model (NWM) forecast, developed by the National Oceanic and Atmospheric Administration, serves as the biophysical component of the hybrid model. Out of 2.7 million daily forecasts, less than 1% of the forecasts can be verified using the traditional hydrological method of comparing the forecast with the observations, motivating the need for the AI technique to improve forecast reliability at millions of ungauged locations. An exploratory analysis followed by the Classification and Regression Tree analysis successfully determines the dependency of the forecast errors on the biophysical attributes, which along with the NWM forecast, are used for the DL model development. The hybrid model is evaluated in a sub-tropical humid climate of Alabama, and Georgia states in the United States. Long-term streamflow forecasts from zero-day lead to 30-day lead forecasts are archived and analyzed for 979 days (Dec. 2018 to Aug. 2021) and 389 USGS gauging stations. The forecast reliability is assessed as the probability of capturing the observations in its ensemble range. As a result, the forecast reliability increased from 21(±1) % in the NWM only forecasts to 82(±3) % in the hybrid Physics-AI model. University of Kentucky (B. Ford) Research at the University of Kentucky has focused on source, fate and transport of contaminants in karst and tile-drained landscapes, as well as river-tributary confluences.  Seven graduate students have worked on the project (5 contributing during the 21-22 reporting period).  Research in tile drained landscapes has focused on monitoring and modeling of sediment transport in subsurface drainage including ongoing collaborations with the USDA-ARS SDRU in Ohio and USDA-ARS NSERL in Indiana. Deliverables include a peer-reviewed manuscript (Nazari et al., 2022) and a new proposal funded by H2Ohio (ODA) in collaboration with the USDA-ARS SDRU. Research in karst watersheds of central KY has focused on impacts of karst hydrologic and biogeochemical processes on nitrate and dissolved reactive P loadings at the watershed-scale.  During the reporting period, two students have worked on this topic, with one (McGill) receiving his MS degree.  An NSF BPE proposal was funded, and an NSF EPSCOR proposal was submitted to support students, monitoring and modeling initiatives related to this topic.  Two papers (Radcliff et al., 2021 and Husic et al., 2022) were published on this topic.  Research on fate and transport of contaminants in streams has focused on aquatic vegetation characterization using UAVs, impacts of stream restoration on hydrology and water quality in karst landscapes, accumulation of PFAS in benthic sediments, and fate and transport of sediments and nutrients in river-tributary confluences.  During the reporting period, three students have been supported on this topic (with one graduate), and one peer-reviewed paper published (Riddle et al., 2022). University of Rhode Island (S. Pradhanang) Water use and withdrawal research focused on developing private water suppliers' water use database and web interface for the State of. Rhode Island. The research is a part of USGS’s water use database research program.  In collaboration with the EPA and RI Water Resources Board, agricultural water uses, and allocation optimization model is being developed for southern RI. The Electrical Resistivity survey done in combination with other geophysical methods are used to study saltwater intrusion. The NASA EPSCoR funded grant to study methane and greenhouse gasses in marshes and groundwater aims at understanding whether deep groundwater functions as storage or sink of potent greenhouse gasses. Various stormwater basins within RI Roger Williams Park are monitored to study various pollutants including algae in water.  The USGS supported State map project focuses on mapping the surface geology statewide and focuses on specific areas at a smaller scale for mapping additional layers. RIGS, with partners in the state, plans to develop a hydrogeologic model at the watershed scale to inform statewide planning for water resources, flood preparation and response, and drought monitoring. Kansas State University (A. Sheshukov) The activities were centered over development of w/q models at the watershed, hillslope, and reservoir scales. We developed and calibrated a SWAT model for the Prairie Band Potawatomi Nation tribal area within the Soldier Creek watershed north of Topeka, KS. The model accounts for specific ag cropland and rangeland practices utilized within the tribal land that were obtained with close partnership with KDHE, tribal community, and local residents. Based on the results we developed a plan of BMP implementation for water-quality improvement. We installed a multi sensor stationary buoy in Marion Reservoir in Kansas for detecting valuable blue-green algae characteristics instrumented with in-situ sensors for near continuous measurements of water temperature, specific conductance, dissolved oxygen, pH, dissolved organic matter, turbidity, light penetration and chlorophyll and phycocyanin fluorescence. We studied the benefits (production and environmental) of cotton production in western Kansas by collecting and analyzing data on three cotton fields. The updated crop coefficient function was developed to better reflect thermo-limited conditions of southern Kansas. We analyzed crop field susceptibility to ephemeral gully erosion by collecting data from various sources (LiDAR, historic imagery, drones, etc.) and using geospatial and machine learning approaches. Novel approaches to detection of gully formations from aerial images were developed and applied in a HUC-12 area. University of Maryland (A. Shirmohammadi) Work was focused on post model outcome development; interfacing SWAT model with agent-based model; identifying hotspots using genetic algorithms; social acceptability and cost effectiveness of modeling results on NPS pollution hotspots. We looked at the importance of picking BMPs based on hotspot identification rather than random allocation. The studies at Warner Creek Watershed in the Monocracy River Basin and Choptank River Watershed in the Coastal Plain of Maryland were on modeling based on available long-term monitoring data, while multicriteria decision analysis framework was developed for water reuse and irrigation economics in agriculture. University of Florida (R. Muñoz-Carpena, Y. Her) The accomplishments from the Florida team are about BMP adoption in Florida (Dr. Young Gu Her) and analysis of the effectiveness and long-term effects of a commonly adopted BMP (vegetative filter strips) form surface runoff pollution control, including the regulatory implications (Dr. Muñoz-Carpena). We also study large-scale hydrological, water quality and ecological impacts of agricultural development of smallholders in Africa (Laikipia, Kenya) and adoption of BMP (reduced tillage, soil management) to assess the distant ecological degradation of the dry African savanna introduced by these developments (Dr. Muñoz-Carpena). Dr. Muñoz-Carpena serves as Chair of this Hatch Project for this year and will coordinate the reporting and efforts. Under the organization of this group, we will submit and develop a special journal collection on the topic of "Advances and gaps in agricultural and urban BMPs across critical scales” that will be submitted to a top-tier journal in the specialty. Virginia Tech (D. Sample) Watershed research at Virginia Tech is focused upon stormwater management, watershed modeling, and well water quality. Stormwater research at Virginia Tech is currently focused on 1) monitoring runoff from urban catchments with homogenous land use, and using these data for calibration of hydrologic/water quality models; 2) developing integrated urban hydrologic/sediment transport models of urbanized catchments using SWMM and HEC-RAS with and without best management practices (BMPs) to assess which projects and criteria enhance stream stability. Watershed modeling and management is currently focused on 1) quantifying nitrogen removal rates from spring bioreactors treating legacy nitrogen in groundwater, specifically the effect of nitrogen loading and flow permanence and variability on removal rates. This includes working with partners at Virginia Dept of Environmental Quality (DEQ) to develop a $1 million pilot program using bioreactors to treat legacy nitrogen; 2) integrating real-time animal/environmental sensing using IoT sensors and modeling with autonomous robotics to manage pasture-based manure nutrients; 3) developing integrated agroecosystem models to evaluate the impacts of climate change, best management practices, uncertainty, and management actions on natural resources and farm viability. Twelve journal articles (10 published and 2 in press), 1 dissertation, and 6 proposals were produced and/or awarded, and 6 presentations were made during 2021-22. Ten students were mentored during this period. University of Georgia (G. Vellidis) Research at the University of Georgia focused on developing and evaluating BMPs for the traditional cotton-peanut-corn crop rotation used in the agricultural areas of the state. All crops were planted into a rye cover crop using strip tillage following burndown with glyphosate. Three irrigation × three fertilization treatments were evaluated in the corn and cotton plots.  These consisted of two irrigation and two fertilization BMPs compared to standard practice. Fertilization BMPs that were evaluated include using fertigation to apply side-dress N on corn and cotton and using UAV-derived NDVI to apply side-dress N on cotton. Irrigation scheduling BMPs include using soil moisture sensors and ET-based scheduling tools.  Since N fertilizer is not applied to peanut during the growing season, nine irrigation treatments were evaluated in peanut. These included seven irrigation scheduling BMPs compared to a rainfed treatment and a farmer-standard irrigation scheduling practice.  Data collected include continuous soil moisture measured with matric potential type soil moisture sensors and soil nitrogen and crop biomass measured at regular intervals for the corn and cotton crops. Biomass included dry weight of separate plant tissues as well as Total Kjeldahl Nitrogen (TKN) and yield. Soil samples were analyzed for Nitrate, Ammonium, and TKN. Purdue University (S. McMillan) Our project goals are to better understand the mechanisms for effective agricultural conservation practices at the site and watershed scales. This work focuses on identifying environmental controls using experiments and monitoring data to incorporate knowledge in management and restoration strategies. We have multiple projects to address this in wetlands, floodplains, and infield practices on working farms. Our work in wetlands (USDA NIFA) and floodplains (NSF) focuses on maximizing nutrient retention while mitigating the deleterious climate effects of CH4 and N2O release. In paired watershed studies (EPA), we are working at the HUC-12 scale to link changes in stream chemistry and nutrient loading to land use practices. Together this work will help generate models that are informed by ecosystem processes as we design restoration practices from site to watershed scales that are optimized to improve water quality through nutrient retention, minimize climate impact by reducing GHG emissions, and maximize agricultural productivity. University of Delaware (S. Inamdar) Our overall goal is to better understand the concentrations, forms, and fluxes of nitrogen (N) in watersheds and how land use activities and BMPs affect this pollutant. Currently we have three emphasis areas where we are studying the fate and transport of N.  These three focus areas are: (1) the effect of milldams and similar barriers on the concentrations, forms, fate and transport of N in stream and riparian zones; (2) the concentrations, fate and transport of N associated with suspended legacy sediment transport in watersheds; and (3) the concentrations and fate of N in restored stream floodplains. We have multiple NSF and USDA AFRI projects addressing these areas of research. Oklahoma State University (K. Wagner) Watershed research at the Oklahoma Water Resources Center focuses on evaluating implementation of novel regenerative agricultural BMPs and virtual fencing. Through small watershed scale monitoring of water quality and quantity, we are working to inform watershed scale modeling and provide insights into processes that determine pollutant fate and transport and the role these novel BMPs play in pollutant reduction. With funding from USDA-NIFA, 12 small watershed sites were installed this year in Altus, Oklahoma to evaluate the benefits of regenerative agriculture practices in cotton production systems. Samples were collected from 8 runoff events this project period. With funding from OSU’s Thomas E. Berry Professorship, monitoring of runoff from 10 small watersheds at the Cross Timbers Experimental Range continued, helping improve understanding of how natural sources and conventional grazing practices impact grazing land water quality. 104 samples were collected over 17 events this project period. Finally, with funding from EPA, 2 paired watersheds were installed this year to evaluate the water resource benefits of using virtual fencing to improve grazing management. 33 samples were collected over 13 runoff events this project period. This first year, continuous grazing is being implemented at all sites to serve as a baseline for evaluation. In year 2, virtual fencing will be used to implement rotational grazing and riparian protection. Outputs: Publications, conferences, reports and thesis: Journals: 75; Thesis/Dissertations: 8; Proposals: 27   Impacts: Activities: The technical committee and the officers met virtually every other month to discuss project objectives and plans for the annual meeting.

Publications

<ol> <li>Nazari, S., Ford, W.I., King, K. 2022.  Impact of flow pathway and source water connectivity on subsurface sediment and particulate phosphorus dynamics in tile-drained agroecosystems. Agricultural Water Management. 269: 107641. https://doi.org/10.1016/j.agwat.2022.107641. </li> <li>Riddle, B., Fox, J., Mahoney, D. T., Ford, W., Wang, Y., Pollock, E., Backus, J. 2022. Investigation of carbon and nitrogen stable isotope tracers (non)conservativeness for sediment fingerprinting. Science of the Total Environment. 817: 152640. https://doi.org/10.1016/j.scitotenv.2021.152640. </li> <li>Radcliff, C., Ford, W.I., Nazari, S. Sheppard, C.  2021. Impact of water source dynamics on dissolved reactive phosphorus loadings in heterogeneous karst agroecosystems with phosphatic limestones. Hydrological Processes. 35(11): e14422. <a href="https://doi.org/10.1002/hyp.14422">36Thttps://doi.org/10.1002/hyp.14422</a>36T. </li> <li>Husic, A., Fox, J., Al Aamery, N., Ford, W., Pollock, E., Backus, J. 2021. Seasonality of recharge drives spatial and temporal nitrate removal in a karst conduit as evidenced by nitrogen isotope modeling. JGR Biogeosciences. e2021JG006454. <a href="https://doi.org/10.1029/2021JG006454">https://doi.org/10.1029/2021JG006454</a>. </li> <li>Shahed Behrouz, M.S., Yazdi, M.N., Sample, D.J., 2022. Using Random Forest, a machine learning approach to predict nitrogen, phosphorus, and sediment event mean concentrations in urban runoff. J. Environ. Manage. 317, 115412. https://doi.org/10.1016/j.jenvman.2022.115412</li> <li>Shahed Behrouz, M. S., Yazdi, M. N., Sample, D. J., Scott, D., and Owen, J. S., 2022. What are the relevant sources and factors affecting event mean concentrations (EMCs) of nutrients and sediment in stormwater? Science of the Total Environment, 828, 154368. https://doi.org/10.1016/j.scitotenv.2022.154368</li> <li>Alamdari, N., Claggett, P., Sample, D., Easton, Z., and Nayeb Yazdi, M., 2022. Evaluating the joint effects of climate and land use change on runoff and pollutant loading. Journal of Cleaner Production, 330, 129953, doi:10.1016/j.jclepro.2021.129953 </li> <li>Sangster, S., Gruver, M., Lacerda, L., Perry, C., Washington, B., Vellidis, G. 2021. Evaluation of irrigation and fertilization strategies to improve irrigation and nitrogen water use efficiencies in cotton. 2021 ASA, CSSA, SSSA International Annual Meeting, 08 November 2021, Salt Lake City, UT, USA, <a href="https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/136430">https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/136430</a> </li> <li>Vellidis, G., Butts, C., Gallios, I., Ortiz, B. 2021. CropFIT - an integrated SmartIrrigation mobile app for corn, cotton, peanut, and soybean. 2021 ASA, CSSA, SSSA International Annual Meeting, 08 November 2021, Salt Lake City, UT, USA, <a href="https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/135167">https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/135167</a></li> <li>Gallios, I., Butts, C., Perry, C., Vellidis, G. 2021. Making Irrigator Pro and easier to use irrigation scheduling tool. 2021 ASA, CSSA, SSSA International Annual Meeting, 08 November 2021, Salt Lake City, UT, USA, <a href="https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/135255">https://scisoc.confex.com/scisoc/2021am/prelim.cgi/Paper/135255</a> </li> <li>Shrestha, S.G. and Pradhanang, S.M., 2022. Optimal selection of representative climate models and statistical downscaling for climate change impact studies: a case study of Rhode Island, USA. Theoretical and Applied Climatology.</li> <li>Sharma, S., Talchabhadel, R., Nepal, S., Ghimire, G., Rakhal, B., Panthi, J., Adhikari, B., Pradhanang, S. M., Maskey, S., and Kumar, S., 2022. Increasing risk of cascading hazards in the central Himalayas. Nat Hazards. <a href="https://doi.org/10.1007/s11069-022-05462-0">https://doi.org/10.1007/s11069-022-05462-0</a></li> <li>Panthi, J., Pradhanang, S.M., Nolte, A. and Boving, T.B., 2022. Saltwater intrusion into coastal aquifers in the contiguous United States—A systematic review of investigation approaches and monitoring networks. Science of The Total Environment, p.155641.</li> <li>Pengfei Liu, Yu Wang, Wei Zhang, "<a href="https://onlinelibrary.wiley.com/doi/full/10.1111/ajae.12316">The Influence of the Environmental Quality Incentives Program on Local Water Quality</a>", American Journal of Agricultural Economics. 2022. <a href="https://doi.org/10.1111/ajae.12316">https://doi.org/10.1111/ajae.12316</a></li> <li>Odeh, T., Mohammad, A.H., Pradhanang, S.M., Ismail, M. and Rödiger, T., 2021. GIS-based Analytical Modeling on Evaluating Impacts of Urbanization in Amman Water Resources, Jordan.</li> <li>Panthi, J., Talchabhadel, R., Ghimire, G.R., Sharma, S., Dahal, P., Baniya, R., Boving,  T., Pradhanang, S.M. and Parajuli, B., 2021. Hydrologic  Regionalization under Data Scarcity: Implications for Streamflow Prediction. Journal of Hydrologic Engineering, 26(9), p.05021022.</li> <li>Inamdar, S., Peipoch, M., Gold, A.J., Lewis, E., Hripto, J., Sherman, M., Addy, K., Merritts, D., Kan, J., Groffman, P.M. and Walter, R., 2021. Ghosts of landuse past: legacy effects of milldams for riparian nitrogen (N) processing and water quality functions.  Environmental Research Letters, 16(3), p.035016.</li> <li>Hollister, J.W., Kellogg, D.Q., Lei-Parent, Q., Wilson, E., Chadwick, C., Dickson, D., Gold, A. and Arnold, C., 2022. nsink: An R package for flow path nitrogen removal estimation. Journal of Open Source Software, 7(71), p.4039.</li> <li>Lewis, E., S.M. Inamdar, A.J. Gold, K. Addy, T. Trammell, D. Merritts, S., M. Peipoch, P.M. Groffman, J. Hripto, M. Sherman,  J. Kan, R. Walter and E.P. Lewis. 2021. Draining the landscape: How do nitrogen concentrations in riparian groundwater and stream water change following milldam removal? Journal of Geophysical Research – Biogeosciences</li> <li>Suriano, Z. J., C. M. Siegert, D. J. Leathers, A. J. Gold, K. Addy, A. W. Schroth, E. Seybold, S. Inamdar, and D. F. Levia. 2021. Effects of atmospheric circulation on stream chemistry in forested watersheds across the northeastern United States: Part 2. Interannual weather type variability. Journal of Geophysical Research: Atmospheres.  e2021JD034546.</li> <li>Hollister. J. W., Kellogg, D. Q., Kreakie, B. J., Shivers, S., Milstead, W. B., Herron, E., Green, L., Gold, A. 2021. Increasing Chlorophyll a Amid Stable Nutrient  Concentrations in Rhode Island Lakes and Reservoirs. Ecosphere 12, no. 6 (2021): e03555.</li> <li>Muñoz-Carpena, R., Z. Yu, A. Carmona-Cabrero, G. Fox, O. Batelaan, A. Bardossy. 2022. Convergence of mechanistic modeling and artificial intelligence (AI) in hydrologic science and engineering. (under review, J. Hydrology).</li> <li>Muñoz-Carpena, R., Reichenberger S., Sittig S., Sur R. (2022). Complex effects of leaching, sedimentation, sorption and degradation on runoff remobilization of pesticide residues in vegetative filter strips (under review, ACS Environmental AU).</li> <li>Reichenberger, R., R. Sur, S. Sittig, S. Multsch, Á. Carmona-Cabrero, J.J. López and R Muñoz-Carpena. 2022. Dynamic prediction of effective runoff sediment particle size for improved assessment of pesticide mitigation efficiency with vegetative filter strips (under review, Sci. Total Env.)</li> <li>Muñoz-Carpena, R., A. Ritter, R. Sur, S. Reichenberger. 2022. Effect of hydrograph type on the calculation of pesticide mitigation efficiencies of vegetative filter strips with VFSMOD in the regulatory context. (Under review, Integr. Environ. Assess. Manag.). </li> <li>Zhang, Y., R. Bhattarai and R. Muñoz-Carpena. 2022. Effectiveness of vegetative filter strips for sediment control from steep construction areas. (Under review, Catena)</li> <li>Orozco-López E., R. Muñoz-Carpena and B. Gao. 2022. Quantification of solute transport in a soil profile with activated macropore networks using light transmission experiments. (Under review, J Hydrology)</li> <li>Muñoz-Carpena, R., C. Lauvernet, N. Carluer and G.A. Fox. 2021. Comment on “Modeling slope rainfall-infiltration-runoff process with shallow water table during complex rainfall patterns” by Wu et al. 2021. J. Hydrology X 13:100133. <a href="https://doi.org/10.1016/j.hydroa.2021.100113">doi:10.1016/j.hydroa.2021.100113.</a></li> <li>Barchiesi*, S., A. Alonso, M. Pazmiño-Hernandez, J.M. Serrano-Sandí, R. Muñoz-Carpena, C. Angelini. 2021. Wetland hydropattern and vegetation greenness predict avian populations in Palo Verde, Costa Rica. Ecological Applications. <a href="https://doi.org/10.1002/eap.2493">doi:10.1002/eap.2493.</a></li> <li>Orozco-Lopez*, E. and R. Muñoz-Carpena, R. 2021. Comparative non-Darcian modelling of subsurface preferential flow experimental observations in a riparian buffer. Trans. ASABE 64(5). <a href="https://doi.org/10.13031/trans.14559">doi:10.13031/trans.14559</a>.</li> <li>Vazquez*, K.M, R. Muñoz-Carpena, M.D. Danyluk, A.H. Havelaar. 2021. Parsimonious mechanistic modeling of bacterial runoff to inform food safety management of agricultural water quality. Appl. Environ. Microbiol. 87(15):e00596-21. <a href="https://doi.org/10.1128/AEM.00596-21">doi:10.1128/AEM.00596-21.</a></li> <li>Luquin*, E., M.A. Campo-Bescós, R. Muñoz-Carpena, R.L. Bingner, R.M. Cruse, H.G. Momm, R.R. Wells, J.Casalí. 2021. Evaluation of model prediction capacity of ephemeral gully temporal evolution in conservation tillage systems. Earth Surf. Process. Landf. 46(10):1909-1925. <a href="https://doi.org/10.1002/esp.5134">doi:10.1002/esp.5134</a></li> <li>Guertault, L. G.A.Fox, D. Heeren, T. Hallihan and R Muñoz-Carpena. 2021. Quantifying the importance of preferential flow in a riparian buffer. Trans. ASABE 64(3):937-947. <a href="https://doi.org/10.13031/trans.14286">doi:10.13031/trans.14286</a>.</li> <li>Orozco-López*, R. Muñoz-Carpena, B. Gao and G.A. Fox. 2021. High resolution pore-scale water content measurement in a translucent soil profile from light transmission. Trans. ASABE64(3):949-962.<a href="https://doi.org/10.13031/trans.14292">doi:10.13031/trans.14292</a>.</li> <li>Medina M.*, R. Huffaker, R. Muñoz-Carpena and G. Kiker. 2021. An empirical nonlinear dynamics approach to analyzing emergent behavior of agent-based models. AIP Advances11:035133. <a href="about:blank">doi:10.1063/5.0023116</a></li> <li>Song, J.H., Her, Y. and Guo, T., 2022. Quantifying the contribution of direct runoff and baseflow to nitrogen loading in the Western Lake Erie Basins. Scientific Reports, 12(1), pp.1-13.</li> <li>G. Granco, M. Caldas, J. Bergtold, J.L. Heier Stamm, M. Mather, M. Sanderson, M. Daniels, A.Y. Sheshukov, D. Haukos, S. Ramsey. (2022) Local Environment and Individuals’ Beliefs: The Dynamics Shaping Public Support for Sustainability Policy in an Agricultural Landscape. Journal of Environmental Management. 301, 113776. (https://doi.org/10.1016/j.jenvman.2021.113776)</li> <li>Koudahe, K., Sheshukov, A.Y., Aguilar, J., Djaman, K. (2021) Irrigation-Water Management and Productivity of Cotton: A Review. Sustainability. 131: 70. <a href="https://doi.org/10.3390/su131810070">https://doi.org/10.3390/su131810070</a></li> <li>Song, J.H., Her, Y. and Guo, T., 2022. Quantifying the contribution of direct runoff and baseflow to nitrogen loading in the Western Lake Erie Basins. Scientific Reports, 12(1), pp.1-13. https://doi.org/10.1038/s41598-022-12740-1.</li> <li>Inamdar et al., Saturated, suffocated, and salty: Human legacies produce hotspots of nitrogen in riparian zones. Journal of Geophysical Research Biogeosciences (In review).</li> <li>Bhatta, A, R. Prasad, D. Chakraborty, J.N. Shaw, J. Lamba, E. Brantley, H.A. Torbert. 2021. Mehlich 3 as a Generic Soil Test Extractant for Environmental Phosphorus Risk Assessment Across Alabama Soil Regions. Agrosyst Geosci Environ. 2021; 4:e20187. <a href="https://doi.org/10.1002/agg2.20187">https://doi.org/10.1002/agg2.20187</a></li> <li>Kumar, K., P. Srivastava, B. V. Ortiz, G. Morata, B. S. Takhellambam, J. Lamba, and L. Bondesan. 2021. Field-Scale Spatial and Temporal Soil Water Variability in Irrigated Croplands. Transactions of the ASABE: 64 (4), 1277-1294. doi: 10.13031/trans.14335</li> <li>Singh, R., R. Prasad, B. Guertal, K. Balkcom and J. Lamba. 2021. Effects of Broiler Litter Application Rate and Time on Corn Yield and Environmental Nitrogen Loss. Agronomy Journal. doi:<a href="https://doi.org/10.1002/agj2.20944">https://doi.org/10.1002/agj2.20944</a>.</li> <li>Stephenson, K., L. Shabman, J. Shortle, Z.M. Easton. 2022. Confronting our agricultural nonpoint source control policy problem. Journal of the American Water Resources Association. <a href="https://doi.org/10.1111/1752-1688.13010">https://doi.org/10.1111/1752-1688.13010</a></li> <li>Deval, C., E.S. Brooks, M. Dobre, R. Lew, P.R. Robichaud, A. Fowler, J. Boll, A.S. Collick, Z.M. Easton. 2022. Pi-VAT: A web-based visualization tool for decision support using spatially complex water quality model outputs. Journal of Hydrology. <a href="https://doi.org/10.1016/j.jhydrol.2022.127529">https://doi.org/10.1016/j.jhydrol.2022.127529</a></li> <li>Fleming, P., K.S. Stephenson, A.S. Collick, Z.M. Easton. 2022. Targeting for Nonpoint Source Pollution Reduction: A Synthesis of Lessons Learned, Remaining Challenges, and Emerging Opportunities. Journal of Environmental Management. DOI: <a href="https://doi.org/10.1016/j.jenvman.2022.114649">10.1016/j.jenvman.2022.114649</a></li> <li>Modi, P., J. Czuba, Z.M. Easton. 2022. Coupling a land surface model with a hydrodynamic model for regional flood risk assessment due to climate change: application to the Susquehanna River. Journal of Flood Risk Management. <a href="http://doi.org/10.1111/jfr3.12763">http://doi.org/10.1111/jfr3.12763</a></li> <li> Alamdari, N., P. Claggett, D.J. Sample, Z.M. Easton, M. Yazdi. 2022. Evaluating the joint effects of climate and land use change on runoff and pollutant loading in a rapidly developing watershed. Journal of Cleaner Production. <a href="https://doi.org/10.1016/j.jclepro.2021.129953">https://doi.org/10.1016/j.jclepro.2021.129953</a></li> <li> Ketterings, Q. C. Twombly, A. Collick, J. Faulkner, Z.M. Easton. 2022. An evaluation BMP performance using a regional P Index and process-based watershed models. Journal of Environmental Quality (In Press).</li> <li> Ebadi N., D. Bosch, R.R. White, M. Wagena, A.S. Collick, Z.M. Easton. 2022. costs of reducing emissions from a dairy farm: a constrained optimization approach. Agricultural Systems. (In Press).</li> <li> Modi, P., D.R. Fuka, Z.M. Easton. 2021. Impacts of climate change on terrestrial hydrological components and crop water use in the Chesapeake Bay watershed. Journal of Hydrology Regional Studies. <a href="https://doi.org/10.1016/j.ejrh.2021.100830">https://doi.org/10.1016/j.ejrh.2021.100830</a></li> <li> Modi, P., D.R. Fuka, Z.M. Easton. 2021. Data in Short “Impacts of Climate Change on Terrestrial Hydrological Components and Crop Water Requirement in the Chesapeake Bay Watershed. Journal of Hydrology Regional Studies. <a href="https://doi.org/10.6084/M9.FIGSHARE.14049569">https://doi.org/10.6084/M9.FIGSHARE.14049569</a></li> <li>Stephenson, K., W. Ferris, E. Bock, Z.M. Easton. 2021. Treatment of legacy nitrogen as a compliance option to meet Chesapeake Bay TMDL requirements. Environmental Science & Technology. <a href="https://doi.org/10.1021/acs.est.1c04022">https://doi.org/10.1021/acs.est.1c04022</a></li> <li>Duan, Y., Akula, S., Kumar, S., Lee, W. & Khajehei, S. A Hybrid Physics-AI Model to Improve Hydrological Forecasts. Artificial Intelligence for the Earth Systems accepted, doi:10.1175/AIES-D-22-0023.1 (2022).</li> <li>Pan, Z., Kumar, S., Zhang, Y., & Shi, C (2022). Central continental boreal summer “warming holes” modulated by Atlantic Multidecadal Oscillation via low‐level jets. Journal of Geophysical Research: Atmospheres, e2021JD035217.</li> <li>Hripto*, J., Inamdar, S., Sherman, M., Peck, E., Gold, A., Bernasconi, S., Addy, K., & Peipoch, M. Effects of relic low-head dams on stream denitrification potential: seasonality and biogeochemical controls. Aquatic Sciences. <a href="https://doi.org/10.1007/s00027-00894-z">https://doi.org/10.1007/s00027-00894-z</a> (2022) 84:60</li> <li>Peck*, E., Inamdar, S., Sherman, M., Hripto, J., Peipoch, M., Gold, A., & Addy, K. Nitrogen sinks or sources? Denitrification and nitrogen removal potential in riparian legacy sediment terraces affected by milldams. Journal of Geophysical Research Biogeosciences. https://doi.org/10.1007/s00027-022-00894-z</li> <li>Sherman*, M., Hripto, J., Peck, E., Gold, A., Peipoch, M., Imhoff, P., & Inamdar, S. Backed-up, Saturated, and Stagnant: Effect of Milldams on Upstream Riparian Groundwater Hydrologic and Mixing Regimes. Water Resources Research <a href="https://doi.org/10.1029/2022WR033038">https://doi.org/10.1029/2022WR03303</a></li> <li>Dey, S., Saksena, S., Winter, D., Merwade, V. and McMillan, S., 2022. Incorporating Network Scale River Bathymetry to Improve Characterization of Fluvial Processes in Flood Modeling. Water Resources Research, p.e2020WR029521.</li> <li>Hanna, K., Paul, M., Negahban-Azar, M., and Shirmohammadi, A. (2021). Developing a Decision Support System for Economic Analysis of Irrigation Applications in Temperate Zones. Water. <a href="https://doi.org/10.3390/w13152044">https://doi.org/10.3390/w13152044</a></li> <li>Paul, M., Rajib, A., Negahban-Azar, M., Shirmohammadi, A., Srivastava, P. 2021. Improved Agricultural Water Management in Data-scarce Semi-arid Watersheds: Value of Integrating Remotely Sensed Leaf Area Index in Hydrological Modeling. Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2021.148177</li> <li>Paul, M., M. Negahban-Azar, A. Shirmohammadi, and H. Montas. 2021. Developing a Multicriteria Decision Analysis Framework to Evaluate Reclaimed Wastewater Use for agricultural Irrigation: The Case Study of Maryland. Hydrology 8(4):18p.</li> <li>Huang, Y., R. Bawa, J. Mullen, N. Hoghooghi, L. Kalin, P. Dwivedi (2022), “A Stochastic Dynamic Optimization Approach for Understanding Expected Land Use Changes to Meet Potential Water Quality Regulations: A Case Study from Georgia, United States”, Agricultural Water Management. 271, 107799.</li> <li>Bian, Z., S. Pan, Z. Wang, Y. Yao, R. Xu, H. Shi, L. Kalin, C. Anderson, D. Justic, S. Lohrenz, H. Tian (2022), “A century-long trajectory of phosphorus loading and export from Mississippi River Basin to the Gulf of Mexico: Contributions of multiple environmental changes”, Global Biogeochemical Cycles. 36, e2022GB007347. https://doi.org/10.1029/2022GB007347.</li> <li>Haas, H., L. Kalin, P. Srivastava (2022), “Improved Forest Dynamics Leads to Better Hydrological Predictions in Watershed Modeling”, Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2022.153180.</li> <li>Haas, H., M. Reaver, R. Karki, L. Kalin, P. Srivastava, D. Kaplan, C.A. Gonzalez-Benecke (2021), “Improving the representation of forests in hydrological models”, Science of Total Environment. https://doi.org/10.1016/j.scitotenv.2021.151425.</li> <li>Haas, H, F. Dosdogru, L. Kalin, H. Yen (2021), “Land use and land cover input data affects the prediction of ecologically relevant flows in hydrologic modeling Corresponding Author”, Water. 13(21), 2947. https://doi.org/10.3390/w13212947.</li> <li>Karki, R., P. Srivastava, L. Kalin, S. Mitra, S. Singh (2021), “Assessment of impact in groundwater levels and stream-aquifer interaction due to increased groundwater withdrawal in the lower Apalachicola-Chattahoochee-Flint (ACF) River Basin using MODFLOW”, Journal of Hydrology: Regional Studies. Vol 34. https://doi.org/10.1016/j.ejrh.2021.100802.</li> <li>Ramesh, R. L. Kalin, M. Hantush, A. Chaudhary (2021), “A Secondary Assessment of Sediment Trapping Effectiveness by Vegetated Buffers”, Ecological Engineering. Vol 159. <a href="https://doi.org/10.1016/j.ecoleng.2020.106094">https://doi.org/10.1016/j.ecoleng.2020.106094</a>.</li> <li>Wagner, K.L., T.J. Gentry, R.D. Harmel, E.C. Pope, L.A. Redmon. 2021. Grazing effects on bovine-associated and background fecal indicator bacteria levels in edge-of-field runoff. Water 2021, 13, 928. <a href="https://doi.org/10.3390/w13070928">https://doi.org/10.3390/w13070928</a>.</li> </ol> <ol start="71"> <li>Boyer EW, MA Moritz, and MG Brown (2022). Smoke deposition to water surfaces drives hydrochemical changes. Hydrological Processes, 36(6), e14626, DOI: 10.1002/hyp.14626</li> <li>Clark KH, DD Iwanowicz, LR Iwanowicz, SJ Mueller, JM Wisor, C Bradshaw-Wilson, WB Schill, JR Stauffer, Jr., and EW Boyer (2022). Freshwater unionid mussels threatened by predation of Round Goby (Neogobius melanostomus). Scientific Reports, 12, 12859, DOI: 10.1038/s41598-022-16385-y (plus supporting dataset at HydroShare public data repository, DOI: 10.4211/hs.e46d4769a8a346fcaed7a27fcceb20ad)</li> <li>Clark KH, JM Wisor, SJ Mueller, C Bradshaw-Wilson, EW Boyer, and JR Stauffer, Jr. (2021). Status of freshwater mussels (Unionidae) in the French Creek watershed, USA at the onset of invasion by Round Goby, Neogobius melanostomus. Water, 13(21), 3064; DOI: 10.3390/w13213064</li> <li>Zhang K, J. Shen, L Guo, EW Boyer, CR Mello, P Lan, H Liu, J Gao, and B Fan (2021). Flood drainage rights in watersheds based on the harmonious allocation method. Journal of Hydrology, DOI: 10.1016/j.jhydrol.2021.126627</li> <li>Zhang L, G Qin, P Lan, L Yang, CR Mello, EW Boyer, and L Guo (2021). Evaluation of three gridded precipitation products in a data scarce region in mountainous areas of the west China. Remote Sensing, 13:3795, DOI:10.3390/rs13193795</li> </ol> 2) Thesis/Dissertation: <ol> <li>Timothy McGill. Assessing machine learning utility in predicting hydrologic and nitrate dynamics in karst agroecosystems, MS Student (Primary Advisor, Fall 2019-May 2022).</li> <li>Rosalia Agioutanti. Classifying and mapping aquatic vegetation in heterogenous stream ecosystems using visible and multispectral uav imagery, MS Student (Primary Advisor, Fall 2019-May 2022).</li> <li>Gina DeGraves. Sediment nitrogen dynamics in backwater wetland confluences of a regulated river, MS Student (Primary Advisor, Summer 2019-Fall 2021).</li> <li>Lorena Lacerda. 2021. Using remote sensing to develop irrigation scheduling tools for variable rate irrigation, Ph.D. Dissertation, University of Georgia, pp 183.</li> <li>Shahed Behrouz, M., 2022. Improving Predictions of Stormwater Quantity and Quality through the Application of Modeling and Data Analysis Techniques from National to Catchment Scales, Ph.D. Dissertation, Virginia Tech, pp 203.</li> <li>Umme Fatema Piu. 2022. Evaluating evapotranspiration rates for corn and cotton in thermo-limited climate of southwest Kansas. MS, Kansas State University.</li> <li>Dey, S., 2021. Enabling large-scale hydrologic and hydraulic modeling through improved topographic representation. PhD dissertation, Purdue University.</li> <li>Phillippe, A.J. 2022. Determining bacterial and nutrient concentrations and loadings of surface runoff from differing grazer access and vegetative cover in Northcentral Oklahoma. MS Thesis, Oklahoma State University.</li> </ol> 3) Proposals Awarded/Submitted: <ol> <li>Fox, J., Ford, W., Mahoney, D., Armstead, M., Dadi, G. BPE-Track 3:  Inclusive Mentoring Hub for Enabling Pathways from Inner-City and Rural Appalachian Households to Engineering in Kentucky and West Virginia. NSF-BPE. $799,445. Role Co-Investigator. July 2022-July 2027</li> <li>Ford, W. Using edge-of-field data and modeling to inform H2Ohio. Ohio department of agriculture $150,000 (as sub-award from USDA-ARS). Role: Principal Investigator.</li> <li>Fox, J., Mahoney, D., Ford, W., Armstead, M. RII-BEC: Undergraduate research as a model of excellence to broaden STEM participation in EPSCoR jurisdictions: What are the mentoring costs? NSF RII-BEC. $1,000,000. Role Co-Investigator.</li> <li>Improving the Sustainability of Georgia Cotton by Increasing Nitrogen and Water Use Efficiencies, Georgia Cotton Commission, 2021-2022, $58,000, Vellidis PI</li> <li>Expansion of an Irrigation Scheduling Application to the U.S, Cotton Incorporated, 2021-2022, $50,000, Vellidis PI</li> <li>Incorporating Volumetric Water Content (Capacitance) Sensors into the Irrigator Pro-Based Irrigation Scheduling Tool, 2021-2022, $18,000, Vellidis PI</li> <li>Making Irrigator Pro an Easier-to-Use Irrigation Scheduling Tool, 2021-2022, Southern Peanut Research Initiative, $25,000, Vellidis PI.</li> <li>Sample, D.J. and Scott, D., Vibrant Virginia-Improving the Resilience of Stormwater Treatment in Fredericksburg: Amount: $60,000. Sponsor: VT Center for Economic and Community Engagement, 1/01/2021 - 06/30/2022.</li> <li>Shahed Behrouz, M., 2021. New Conceptualizations of Catchment-Scale Stormwater Pollution Generation Processes, Virginia Water Resources Research Center Competitive Grant, $7,000, 10/1/21-8/31/22. </li> <li>Cardace, D., Pradhanang, S. M., and Moseman-Valtiera, S., Planetary Methane in Ultramafic Contexts: Searching for Cyclicity in Methane Emissions at a Planetary Analog Site in Northern California, NASA-EPSCoR $735,000 (6/2022-6/2025)</li> <li>Savage, B., Pradhanang, S. M., Boving, T. Mapping Bedrock and Saltwater Intrusion in Rhode Island, USGS $90,000 (09/2021-08/2022)</li> <li>Savage, B., Pradhanang, S. M., Boving, T., Mapping Bedrock and Saltwater Intrusion in Rhode Island USGS $117,337 (09/2022-08/2023)</li> <li>Pradhanang, S., Kumar, R, and Rashid T, Floating Treatment Wetland System (FTWS) - Sustainable green technology to remediate polluted surface water bodies in the COVID 19-era , Asia- Pacific  Network $78,000 (09/2021-08/2023)</li> <li>Pradhanang, S. M., Boving, T., and Savage, B. The Rhode Island Water Resources Board (RIWRB) and University of Rhode Island (URI) Statewide Water Withdrawal Data Enhancement and Database Development Project. RIWRB-USGS $197,488 (10/20-09/22)</li> <li>T Franti, A. Sheshukov, J. Lory, R. Cruse. Developing and assessing innovative ephemeral gully erosion control practices. (2021-2023). USDA $344,538</li> <li>R.L. North, A. Ohler, L. McCann, T. Moore, A. Sheshukov. Valuing Water Quality Improvements in Heartland Reservoirs. (2022-2025) EPA $741,285</li> <li>Pradhanang, S.M., Liu, P. Water Availability through the Integration of Hydrologic Model and Water Management Optimization Tool for Chipuxet River Watershed, Rhode Island. RIWRC-USGS. (2022-2023) USGS $50,000</li> <li>USDA-Cooperative Agreement. Fuka, D.R., Z.M. Easton, R.R. White. Developing and evaluating rapidly deployable inexpensive weather, soil moisture, shock, and streamflow sensors to aid the monitoring, inspection, and rehabilitation of aging dams. $225,000. Dec 2021-Nov 2022.</li> <li>USDA-Cooperative Agreement. Easton, Z.M. Modeling the Lake Champlain Basin CEAP watersheds to understand and predict conservation effects on legacy phosphorus. $134,223. Oct 2021-Sept 2023.</li> <li>Virginia Tech CALS Strategic Plan Advancement. Easton, Z.M., R.R. White, K. Hamed, D.R. Fuka, M. Eick. Eyes in the Sky and Boots on the Ground: Collaborative Technologies for Monitoring and Managing Livestock Pastures. $60,000. Oct 2021-May 2023.</li> <li>NSF CPS (Cyber-Physical Systems). White, R.R., E. Feuerbacher, Z.M. Easton. Collaborative Research: CPS: Medium: Greener Pastures: A pasture sanitation cyber physical system for environmental enhancement and animal monitoring. $998,232. Jan 2022-Dec 2024.</li> <li>Lewis, K., K. Wagner, A. Berthold, P. DeLaune, J. Bell, D. Miller Sustainable. Agricultural Intensification and Enhancement through the Utilization of Regenerative Agricultural Management Practices. Amount: $583,438 (Total Award: $10,000,000). Sponsor: USDA-NIFA Sustainable Ag Systems Program, 9/1/2021-8/31/2026.</li> <li>Wagner, K. Dam Analysis Modernization of Tools, Applications, Guidance, and Standardization (DAM-TAGS) Project – Year 1. Amount: $478,238. Sponsor: USDA-ARS Cooperative Agreement, 6/10/2021-6/9/2022.</li> <li>Wagner, K., R. Bonett, A. Sewell, J. Gonzalez Estrella, S. Kim, A. Dzialowski. Oklahoma Water Resources Research Institute Program (USGS Base Funds FY21). Amount: $125,000. Sponsor: USGS, 9/1/2021-8/31/2022.</li> <li>Mirchi, A, K. Wagner, S. Taghvaeian, Sarah Alian, R. Bailey. Conjunctive Freshwater-Saltwater Management for Climate-Resilient Agroecosystems. Amount: $181,568 (Total Award: $749,786). Sponsor: USDA-NIFA Foundational Program, 12/31/2021-12/12/2025.</li> <li>Wagner, K., S. Sharma, S. Taghvaeian, S. Frazier, J. Warren, A. Mirchi. Oklahoma Master Irrigator Program and Ogallala Aquifer Study. Amount: $150,000. Sponsor: Oklahoma Conservation Commission, 7/1/2021-6/30/2022.</li> <li>Reuter, R., K. Wagner, L. Goodman, C. Duchardt, B. Murray. Increasing the pace & scale of adoption of prescribed grazing through virtual fence technology. Amount: $93,188 (Total Award: $1,365,774). Sponsor: USDA-NRCS Conservation Innovation Grant, 7/1/2022-6/30/2025.</li> </ol>

Impact Statements

Date of Annual Report: 11/07/2023

Report Information

Annual Meeting Dates: 09/12/2023 - 09/13/2023
Period the Report Covers: 10/01/2022 - 09/30/2023

Participants

● Participants:
In person attendees (11):
● Fouad Jaber - Texas A&M
● Rafael Muñoz-Carpena - University of Florida
● Francois Birgand - NCSU
● Jasmeet Lamba - Auburn University
● Latif Kalin - Auburn University
● Aleksey Sheshukov - Kansas State University
● Emine Fidan - University of Tennessee
● Eban Bean - University of Florida
● Young Gu Her - University of Florida
● Sanjiv Kumar - Auburn University
● Rakesh Kumar - Auburn University

Virtual Attendees (13):
● Soni Pradhanang - University of Rhode Island
● Adel Shirmohammadi - University of Maryland
● Bill Ford - University of Kentucky
● Zach Easton - Virginia Tech
● Elizabeth Boyer - Penn State University
● Arun Bawa - Texas A&M
● Raghavan Srinivasan - Texas A&M
● Natalie Nelson - North Carolina State University
● Sara McMillan - Iowa State University
● Prem Parajuli- Mississippi State University
● Rabin Bhattarai- University of Illinios-UC
● Mary Savin - University of Arkansas
● Josef Gorres - University of Vermont

Participants Attachment:

appendix_d_s1089_2023.docx

Brief Summary of Minutes

The annual meeting was held in the College of Forestry, Wildlife and Environment (CFWE) at Auburn University in Auburn, AL on September 12-13, 2023 with participation of 13 members on Zoom and 11 members in-person. The meeting agenda included state reports of accomplishments and active projects, discussions on collaborative activities, special collection of journal papers on BMP monitoring and management, a proposal for the next cycle of this Hatch project, and potential submission of a proposal for Experiment Station Section Award for Excellence in Multistate Research. The meeting featured a workshop on the impact reporting provided by the Multistate Research Fund Impacts Program. Prior to the meeting, the members submitted their state reports. A brief overview of the activities during the meeting is below:

The meeting started with Dr. Paul Patterson, Dean of the College of Agriculture and Director of the Ag Experimental Station of Auburn University, welcoming the participants to Auburn and presenting an overview of college mission and activities. Then, Dr. Mary Savin, a NIFA advisor, and Dr. Fouad Jaber, S1089 chair, provided recaps of USDA-NIFA’s Hatch program and a history of prior S1089 projects, respectively. A recap of the annual S1089 meeting in Houston in 2022 completed a morning part of the meeting.

After the break, S1089 members (in person and virtual) reported on their state activities and accomplishments, including active projects, funded proposals, and students and publications. A discussion on multistate collaborative efforts followed the individual reporting.

Impact writing workshop. The afternoon of Day 1 was dedicated to the impact writing workshop virtually led by Sara Delheimer (delheimer@colostate.edu), a program coordinator and impact writer for the Multistate Research Fund Impacts Program (www.mrfimpacts.org). Ms. Delheimer shared the best practices on how to better articulate the impact of multistate projects and activities, to demonstrate the value to stakeholders, funding agencies, and the general public. Examples of different impact statements from Hatch Multistate project reports were presented and discussed.

Kalin and a director of the Alabama Water Center led a field trip of the LID facility in Auburn. This concluded Day 1.

Journal special collection. Day 2 was fully dedicated to the discussion on journal special collection started in 2021.
- Journal of Environmental Management (Elsevier, IF=8.7) was selected
- Fouad updated on communication with the journal and informed of the need to submit a proposal for approval
- 16 initial contributions were identified from the project members on new insights and gaps in BMP research at field and watershed scales including monitoring, modeling and interdisciplinary and translational studies, specifically the following topics were of particular interest:
  - Advances in BMP design
  - Advances in BMP monitoring
  - Quantification of BMP ecosystem services
  - Achieving Nutrient and Sediment Reduction Goals Through Watershed Management
  - Limitations and uncertainties in predicting mitigation of runoff contaminants with BMPs
  - Alternative water resources in the context of climate change
  - Legacy nutrients and sediments impacting the efficiency of BMP performance
  - Using advanced techniques in identifying and targeting BMPs in urban, agricultural and forested watersheds.
- Proposed guest editors are: Fouad Jaber (Texas), Latif Kalin (Alabama), Soni Pradhanang (Rhode Island), Aleksey Sheshukov (Kansas).

Hatch project award. S1089 members expressed their interest in exploring nomination for the Experiment Station Section Award for Excellence in Multistate Research. Project officers were tasked to discuss the conditions of the award and prepare a draft of nomination documents.

Next project cycle proposal. Current S1089 project ends in September 2025. To avoid a gap in project continuation and funding, a new proposal should be prepared shortly after the end of the 2023-24 fiscal year. Project officers and a leadership group will work on drafting the proposal in 2024.

Next annual meeting location: Kansas City, KS
- Project officers will communicate with NIFA for the meeting location and potential participation. As an alternative, Dr. Sheshukov will organize a meeting at the K-State's campus in Olathe, KS.

Annual S1089 project report: Need to be submitted within 60 days after the annual meeting. Project officers will compile individual state submissions and summarize the accomplishments.

Election: Dr. Emine Fidan was nominated by Dr. Munoz-Carpena and elected project Secretary for 2023-24. This concluded Day 2. Meeting was adjourned.

Elected officers (2023-2024):

Secretary: Emine Fidan (U Tennessee)

Vice Chair: Latif Kalin (Auburn U)

Chair: Aleksey Sheshukov (KSU)

Past Chairs:

Soni Pradhanang (2020-2021)

Rafa Munoz-Carpena (2021-2022)

Fouad Jaber (2022-2023)

Accomplishments

The main focus of this project is to improve the abilities to better understand and predict fate and transport of pollutants and evaluate the effectiveness of best management practices (BMPs) on critical landscapes at the watershed scale. This includes hillslope soil health, water quality of streams and waterbodies, environmental benefits of mitigation practices and cost effectiveness of BMPs. The objectives will be met through the following activities: monitoring at sub-watershed scales, model development and applications at various spatial and temporal scales, and analyzing uncertainty in both monitoring and modeling efforts.   Below are a few examples to the accomplishments from various projects: <ul> <li>Rainfall simulation experiments were conducted to determine the influence of manure application on pollutant leaching in pastures. Results show that loss of contaminants can be significant in leachate, and topography plays a critical role. Therefore, care and good planning (e.g. timing) is needed before applications.</li> <li>The comparison of pore characteristics as a function of treatments showed that soil columns under cover crop treatment had comparatively higher values of porosity and pore number density for the top 100 mm of soil. This is another evidence to the benefits of cover crops.</li> <li>A new cell-averaged numerical model is being developed for subsurface vegetated treatment wetlands. The use for treatment wetlands as BMPs to treat both NPS and point source pollutants has seen increase. Tools like these can better help designing such wetlands and understanding flow and nutrient transport.</li> <li>A new methodology that combines geospatial and machine learning approaches has been developed to identify gully locations. The developed algorithm will help with the gully detection efforts in larger areas and can be useful for targeting implementation of BMPs.</li> <li>Muñoz-Carpena’s team at UF quantified the effect of vegetative filter strips (VFS) for mitigation of agrochemical pollutants at the field and landscape levels in a variety of agroecological scenarios in the USA and EU using the VFSMOD model they developed. New work was started to quantify the pesticide runoff mitigation efficiency of “spot-applications” in cereal fields using the latest precision/smart agriculture technologies. The work is groundbreaking because up to now there is no method to quantify expected reductions in pesticide runoff off the field compared to typical broadcasting applications.</li> </ul>   Short-term Outcomes: Project activities from 2022-2023 are summarized in the following state reports:   Texas A&M (F. Jaber) Texas A&M AgriLife (AgriLife) program consisted of projects to enhance SWAT modeling both locally and globally and research in nature-based solutions for water volume and quality solutions. AgriLife  worked on a national SWAT hydrological and water quality calibration at HUC12 subbasin scale (with USEPA). In addition, a project to enhance modeling of ungaged watersheds using machine learning (ML) techniques is currently underway. Also, a project to develop a 10 km x 1- km gridded global SWAT model is being developed with the Nature Conservancy (TNC). AgriLife also worked on quantifying the impact of nature-based solutions on flooding and water quality. The Transportation Stormwater Infrastructure project funded by the Texas Water Development Board investigates the impact of Nature-based solutions integrated with future development on flooding in the DFW metroplex. The project involves modeling and development of educational material.   University of Florida (R. Muñoz-Carpena, Y. Her, E. Bean) Research at the University of Florida has focused on water quality dynamics across different landscapes. In particular, these projects advanced our understanding of the dynamic relationship between the internal hydrodynamics and water quality of a shallow water body (i.e., Lake Okeechobee) and the effectiveness of crop rotation between sugarcane and flooded rice in the Everglades Agricultural Areas. In addition, researchers also evaluated the impacts of sea level rise and weather pattern change on groundwater level and saltwater intrusion in Southeast Florida, the effect of vegetative filter strips for mitigation of agrochemical pollutants at the field and landscape levels, and the impacts of agricultural development of small holders in Africa (Laikipia, Kenya) and adoption of BMP (reduced tillage, soil management) to assess the distant ecological degradation of the dry African savanna introduced by these developments.   Auburn University (L. Kalin, J. Lamba, S. Kumar) Researchers are Auburn University have been involved in several projects to enhance water quality research. Research focuses are to quantify nutrient losses from fields fertilized with animal manure, examine soil macropore characteristics in cover cropping systems, develop effective adaptation strategies to enhance the resilience of farmers under changing climate, forecast soil moisture through multi-source data integration, develop a cell-averaged numerical model for one-dimensional subsurface flow in a sloping wetland bed for treatment wetlands, and model wetland hydrology and carbon flux modeling in natural wetlands to better understand their carbon sequestration potential.   North Carolina State University (F. Birgand, N. Nelson) The activities spearheaded by Birgand focused on development of new techniques to monitor stormwater flow from culverts (Obj. 1), and the use of advanced monitoring techniques to monitor the fate of nitrate in a salt marsh, to measure Fe and Mn in lakes, and to test the effects of flow rate on volumetric nitrate removal rates in a woodchip bioreactor (Obj. 2). For the first project, the team used images and videos taken using trail cameras (<$500) to measure water stage in perched culverts. We have used a combination of machine vision and machine learning techniques to tackle the problem. Machine learning techniques such as fast R-CNN (Fast Region-Based Convolutional Neural Network) have provided a wonderful solution to insurmountable culvert detection problems in low light situations. In the second project, the research team tested whether or not increased flow rate through a porous medium would increase volumetric nitrate removal rates from a woodchip bioreactor. The research spearheaded by Nelson focused on water quality dynamics in coastal settings. The first project developed a framework for nowcasting fecal contamination in coastal waters using in situ sampling and machine learning modeling. The second project reconstructed historical bloom exports from reservoirs near Lake Okeechobee with Sentinel-3 OLCI imagery to evaluate bloom locations in relation to water control structures and discharge patterns.   University of Tennessee (E. Fidan, D. Yoder) One thrust in this time period was focused on S1089 Objective 1 Develop tools that utilize both monitoring and modeling to better inform targeted BMP implementation. This examined soil health as a measure of the long-term success of BMP implementation, with an emphasis on soil health measurement and quantification. Findings included that a weighted soil health provided a more robust indication of soil health, and that soil health does serve as a useful measure of long-term BMP implementation. As second thrust related to S1089 Objective 2 Advance water quantity and quality models for mixed-watershed use included continued development of the RUSLE2/Ephgee whole-field erosion model, combining hillslope and ephemeral gully erosion. Additional work addressing Objective 2 included the development of a pluvial flood model for agricultural landscapes. Predictive flood maps were developed for North Carolina after Hurricane Matthew (2016). In addition, a Bayesian flood water quality model was built to understand drivers and watershed characteristics of flood water contamination after Hurricane Florence (2018). Findings show high presence of pathogenic bacteria Arcobacter in floodwaters. Model results indicate that rainfall is a major driver, with overtopped WWTPs and nearby agricultural operations being potential sources of contaminants. A third thrust related to S1089 Objective 3 Test advanced / new monitoring techniques to detect water quality issues compared classical plot sediment delivery monitoring as “truth”, comparing that to high-resolution ground-based LIDAR to determine if the latter can accurately measure soil loss through da decrease in the soil surface elevation. This study found that even over three years of erosion, LIDAR could accurately see areas of concentrated erosion, but could not see normal sheet and rill hillslope erosion.   University of Rhode Island (S. Pradhanang) Research at the University of Rhode Island has focused on agricultural water uses and allocation through integrated modeling (SWAT-MODFLOW-WMOST), methane in groundwater, urban stormwater monitoring, saltwater intrusion and bedrock mapping in the coastal areas, and floating wetlands treatment systems. Specifically, water availability during low flow conditions for Chipuxet basin is done using coupled SWAT and MODFLOW models. Further the model is tied to the WMOST water allocation and optimization model to develop water use scenarios. The research project to study methane and greenhouse gasses in marshes and groundwater aims at understanding whether deep groundwater functions as storage or sink of potent greenhouse gasses. Various stormwater basins within RI Roger Williams Park are monitored to study various pollutants including algae in water.  The NASA Space Grant and USGS supported State map research focuses on mapping the surface geology statewide and focuses on specific areas at a smaller scale for mapping additional layers. RIGS, with partners in the state, plans to develop a hydrogeologic model at the watershed scale to inform statewide planning for water resources, flood preparation and response, and drought monitoring. Floating wetland treatment studies were conducted for lakes in Nepal, India, and Bangladesh as a part of Asia Pacific Network Research grant.   Kansas State University (A. Sheshukov) Major activities in 2023 were centered on development of various computer models and data collection at watershed, hillslope, and reservoir scales. Specifically: - Ephemeral gully management and detection: We used geospatial and machine learning approaches to identify gully locations on agricultural hillslopes of central Kansas. We processed LiDAR elevation datasets and applied a combination of terrain-index and machine learning algorithms for gully detection. We used additional Hatch funding to develop a new methodology on gully detection from historical images/Google Earth imagery and successfully tested it Turkey creek watershed north of the city of Wichita. The developed algorithm will help with the gully detection efforts in a larger area and can be useful for targeting implementation of BMPs. - Watershed management. We completed a SWAT model development for the Prairie Band Pottawatomie Nation tribal area within the Soldier Creek watershed north of Topeka, KS. The model accounts for specific cropland and rangeland practices that are utilized within the tribal land and obtained from local stakeholders with close partnership with KDHE and tribal community. Based on the results, a plan for BMP implementation in the watershed was included in a watershed management plan submitted to EPA. - Blue green algae. We continued data collection from a multi sensor stationary buoy in Marion Reservoir in Kansas for recording various in-situ water properties and meteorological variables. The buoy is instrumented with in-situ sensors for near continuous measurements of water temperature, specific conductance, dissolved oxygen, pH, dissolved organic matter, turbidity, light penetration and chlorophyll and phycocyanin fluorescence. Forecasting of potential harmful algal blooms and recommendation for lake management is a goal of this study. PD Sheshukov coordinated with KSRE extension specialists a trial study on the effectiveness of rapid blue green algae tests for the use by extension agents and local producers and homeowners. - Cotton production management. We studied the benefits (economic and environmental) of cotton production in western Kansas by analyzing the data on three cotton fields collected from above and below ground sensors of the flux towers. We completed the plot study (2021-2023) in a center-pivot field in SWREC on the efficiency and water use of different irrigation technologies (LESA, LEPA, MDI). We developed water-productivity functions and analyzed specific crop coefficient functions to better reflect thermo-limited conditions of southern Kansas.   University of Maryland (A. Shirmohammadi) Monitoring and Modeling based on Long-Term Monitoring Data: Warner Creek Watershed in the Monocracy River Basin: Using paired watershed and upstream-downstream monitoring design, we collected 11 years (2001-2012) of stream flow and water quality constituents (TSS, NH4, NO3-, TN, Ortho-P and TP) in an 850-acre watershed with three Dairy operators located in Frederick County, Maryland. Results indicated that sub-watershed B with about 270 milking cows, with no slurry storage facility, with loafing ground located at the slope at the top of the sub-watershed, and with no riparian or grass filter around the stream had the highest level of pollution. Results also indicated that climate variability had a great impact on the flow and pollutant discharge from the watershed. Using the monitored data, we calibrated and validated a SWAT model and then we developed a Diagnostic Decision Support Systems (DDSS) to capture the most critical areas of the watershed and make sure the appropriate BMPs were implemented.   Other research projects include: optimization of urban stormwater management BMPs using combination of SWAT and genetic algorithms; multi-criteria water resources management using SWAT, DSS, and Agent Based Modeling (ABM); decision support tool for economic evaluation of irrigation applications in temperate zones; use of multiple regression and optimization models to assess the effectiveness of BMPs in pollution reduction and likelihood of BMP implementation; and assessment of agricultural land suitability for irrigation with reclaimed water using geospatial multi-criteria decision analysis.   University of Delaware (S. Inamdar) A primary research goal that University of Delaware researchers focus on is to better understand the concentrations, forms, and fluxes of nitrogen (N) in watersheds and how land use activities and BMPs affect this pollutant. Currently we have three emphasis areas where we are studying the fate and transport of N.  These three focus areas are: (1) the effect of milldams and similar barriers on the concentrations, forms, fate and transport of N in stream and riparian zones; (2) the concentrations, fate and transport of N associated with suspended legacy sediment transport in watersheds; and (3) the concentrations and fate of N in restored stream floodplains. We have multiple NSF and USDA AFRI projects addressing these areas of research. USDA Hatch funds were used for installing redox sensors in riparian zones upstream of the milldams. Hatch funds were also used to purchase a Hach spectrophotometer for analysis of dissolved Fe2+ in groundwater samples.   Pennsylvania State University (E. Boyer, J. Duncan) Research at Penn State has focused on: Coupled hydrological and biogeochemical processes controlling streamflow and water quality; impacts of multiple stressors (e.g., atmospheric deposition, land use, and climate change) on responses of terrestrial and aquatic ecosystems; application of nature-based watershed management techniques to mitigate environmental problems; terrestrial and aquatic linkages, especially focusing on connectivity in riparian zones and dynamic variable source areas. Outcomes include: Measurements and models identify sources of nutrient pollution, hotspots of nutrient inputs to the landscape and exports to streamflow, informing where mitigation and management efforts should be targeted. Models yield estimates of uncertainty in nutrient loading exports from the landscape to the stream, highlighting areas where additional measurements will help to improve understanding or predictability. Measurements and models have generated understanding, and new hypotheses, about how hydrological and biogeochemical processes combine to control streamflow and water quality. We are using a suite of models, from physically based to data driven, to simulate flow and water quality, and to explore how watersheds may respond to changing environmental conditions.   Oklahoma State University (K. Wagner) Watershed research at the Oklahoma Water Resources Center focuses on evaluating implementation of novel regenerative agricultural BMPs and virtual fencing. Through small watershed scale monitoring of water quality and quantity, we are working to inform watershed scale modeling and provide insights into processes that determine pollutant fate and transport and the role these novel BMPs play in pollutant reduction. With funding from USDA-NIFA, 12 small watershed sites were monitored this year in Altus, Oklahoma to evaluate the benefits of regenerative agriculture practices in cotton production systems. Preliminary results suggest that total discharge and nutrient concentrations in runoff are reduced in watersheds where cover crops are used. When the cover crop (winter wheat) was actively growing, soil moisture levels were depleted compared to watersheds with no cover crops; however, throughout the remainder of the year, soil moisture levels were similar regardless of whether cover crops were used or not. With funding from OSU’s Thomas E. Berry Professorship, monitoring of runoff from 10 small watersheds at the OSU Cross Timbers Experimental Range continued, helping improve understanding of how natural sources and conventional grazing practices impact grazingland water quality. E. coli numbers were not significantly different among the 10 watersheds with one exception, the most heavily grazed prairie watershed (GP1), which is used for spring calving, had greater numbers. The lack of significance among watersheds is likely due to the grazed sites being rotationally (and lightly) grazed and wildlife contributions. Finally, with funding from EPA and NRCS, 2 paired watersheds were monitored this year to evaluate the water resource benefits of using virtual fencing to improve grazing management.   Iowa State University (S. McMillan) Research at Iowa State University has been surrounding the quantification of ecosystem services and climate resilience of restored and constructed wetlands in agricultural landscapes. Current work has focused on linking hydroclimatic and watershed variables to nitrate storm dynamics in the Midwest, using annual mass loading curves and storm metrics to characterize nutrient pathways and sources, and identifying the role of conservation at the small watershed scale by leveraging historical data and high temporal resolution monitoring.   Virginia Tech University (Z. Easton, D. Sample, B. Benham) Work at Virginia Tech University has ranged across landscapes and disciplines. For objective 1, we are monitoring and evaluating the first large scale spring bioreactor designed to remove legacy N from groundwater as a way to meet TMDL goals. Additional activities include field identification and verification of candidate sites for legacy N treatment and working cooperatively with Virginia DEQ to formalize a feasible, low-cost N crediting protocol to quantify and certify legacy N reductions from bioreactors for TMDL compliance. Additionally, another project began with a 6-yr monitoring effort to characterize runoff, nutrients and sediment discharges from Virginia Utility Scale Solar Sites (USS), assessing existing models and developing new ones to improve effectiveness of BMPs. To add on, we completed and received EPA approval for an implementation planning document that specified the type and number for BMPs needed to address a bacteria impairment TMDL for the Peak Creek Watershed, a tributary to the New River in SW Virginia. For objective 2, we assessed the impacts of climate change on terrestrial hydrological components and Crop Water Use (CWU). Results show a reduction (13 % and 17 % respectively) in CWU is estimated for corn and soybeans, resulting from increased total precipitation and rising CO2 levels suppressing evapotranspiration. Our results indicate that even in a warmer regime, crop water use decreased due to rising CO2 concentrations from climate change. Additional research addressing objective 2 assessed Environmental Site Design (ESD) guidance and climate change impacts on stream stability, as well as developed TMDLs to address PCB impairments in the Mountain Run watershed and the James River Watershed upstream of Richmond, VA. For objective 3, we are developing sensors and the associated analytics to predict livestock manure excretion events and distribution based on animal sensor data and in situ environmental sensors. Sensor data are used to initialize a model of critical runoff/nutrient source areas and to optimize the path of an autonomous robot capable of managing deposited manure. Another similar research project developed a partnership with a nonprofit organization to develop and deploy a secure network of sensors on the Rappahannock River (SmartRiver) for monitoring urban stormwater BMP effectiveness. In summary, in 2022-23 project members: <ul> <li>Published 80 research publications</li> <li>Received 31 awarded proposals</li> <li>Advised 21 PhDs (9 defended), 11 MS, and 14 undergraduate students</li> <li>Mentored 4 Postdocs and Visiting Scientists</li> </ul>   Activities: The technical committee and the officers met virtually every other month to discuss project objectives, project activities, and plans for the annual meeting.

Publications

1). Publications: <ol> <li>Larios, K., S. Gerber, R. Muñoz-Carpena, P. Inglett, K.R. Reddy, M. Chimney. 2023. Effects of increasing complexity in biogeochemistry and hydrology on variability of total phosphorus concentration in models of a low flow subtropical wetland. Ecological Engineering xxx (xxxx) 107131. <a href="https://doi.org/10.1016/j.ecoleng.2023.107131">doi:10.1016/j.ecoleng.2023.107131</a>.</li> <li>Chen. H., D.S. Carley, R. Muñoz-Carpena, G. Ferruzzi, Y. Yuan, A. Blankinship, T.L. Veith, R. Breckels, G. Fox, Y. Luo, D. Osmond, H.E. Preisendanz, Z. Tang, K. Armbrust, K. Costello, L.L. McConnell, P. Rice, J. Westgate, M. Whiteside. 2023. Incorporating the benefits of vegetative filter strips into risk assessment and risk management of pesticides. Integr Environ Assess Manag (IEAM). <a href="https://doi.org/10.1002/ieam.4824">doi:10.1002/ieam.4824</a>.</li> <li>Muñoz-Carpena, R., A. Carmona-Cabrero, Z. Yu, G.A. Fox, O. Batelaan. 2023. Convergence of mechanistic modeling and artificial intelligence in hydrologic science and engineering. PLOS Water. <a href="https://doi.org/10.1371/journal.pwat.0000059">doi:10.1371/journal.pwat.0000059</a></li> <li>Shin*, S., Y. Her, R. Muñoz-Carpena, X. Yu, C. Martinez and A. Singh. 2023. Climate change impacts on water quantity and quality of a watershed-lake system using a spatially integrated modeling framework in the Kissimmee River-Lake Okeechobee system. J. of Hydrology: Regional Studies 47:101408.  <a href="https://doi.org/10.1016/j.ejrh.2023.101408">doi:j.ejrh.2023.101408</a></li> <li>Shin*, S, Y. Her, R. Muñoz-Carpena and Y. Xiao. 2023. Quantifying the contribution of external loadings and internal hydrodynamic processes to the water quality of Lake Okeechobee. Sci. Total Env. 883:163713 <a href="https://doi.org/10.1016/j.scitotenv.2023.163713">doi:10.1016/j.scitotenv.2023.163713</a></li> <li>Shin*, S., Y. Her, R. Muñoz-Carpena, and Y.P. Khare. 2023. Multi-parameter approaches for improved ensemble prediction accuracy in hydrology and water quality modeling. J. Hydrology622(Part A):129458.  <a href="https://doi.org/10.1016/j.jhydrol.2023.129458">doi:10.1016/j.jhydrol.2023.129458</a></li> <li>Zhang*, Y., R. Bhattarai and R. Muñoz-Carpena. 2023. Effectiveness of vegetative filter strips for sediment control from steep construction landscapes. Catena 226:10705. <a href="https://doi.org/10.1016/j.catena.2023.107057">doi:10.1016/j.catena.2023.107057</a></li> <li>Morgan*, S., R. Huffaker, R. Giménez, M.A. Campo-Bescos, R. Muñoz-Carpena, and G. Govers. 2023. Experimental evidence that rill-bed morphology is governed by emergent nonlinear spatial dynamics. Scientific Reports-Nature 12:21500.<a href="https://www.nature.com/articles/s41598-022-26114-0"> </a><a href="https://www.nature.com/articles/s41598-022-26114-0">doi:10.1038/s41598-022-26114-0.</a></li> <li>Reichenberger S., R. Sur, S. Sittig, S. Multsch, Á. Carmona-Cabrero, J.J. López and R. Muñoz-Carpena. 2023. Dynamic prediction of effective runoff sediment particle size for improved assessment of erosion mitigation efficiency with vegetative filter strips. Sci. Total Env. 857(3):159572. <a href="https://doi.org/10.1016/j.scitotenv.2022.159572">doi:10.1016/j.scitotenv.2022.159572</a></li> <li>Oh*, W.S., A. Carmona-Cabrero, R. Muñoz-Carpena, R. Muneepeerakul. 2022. On the interplay among multiple factors: effects of factor configuration in a proof-of-concept migration agent-based model. Journal of Artificial Societies and Social Simulation (JASSS) 25(2):7. <a href="https://doi.org/10.18564/jasss.4793">doi:10.18564/jasss.4793.</a></li> <li>Kim, J., Y. Her, R, Bhattarai, and H. Jeong (2023), Improving nitrate load simulation of the SWAT model in an extensively tile-drained watershed, Science of the Total Environment, 904, p166331, <a href="https://doi.org/10.1016/j.scitotenv.2023.166331">https://doi.org/10.1016/j.scitotenv.2023.166331</a></li> <li>Dubey, S. K., J. Kim, Y. Her, D. Sharma, and H. Jeong (2023), Hydroclimatic Impact Assessment using the SWAT Model in India - State of the Art Review, Sustainability, 15(22), 15779. <a href="https://doi.org/10.3390/su152215779">https://doi.org/10.3390/su152215779</a> </li> <li>Dubey, S. K., J. Kim, S. Hwang, Y. Her, and H. Jeong (2023), Variability of precipitation and temperature extreme events in coastal and inland areas of South Korea during 1961-2020, Sustainability, 15(16), 12537. <a href="https://doi.org/10.3390/su151612537">https://doi.org/10.3390/su151612537</a></li> <li>Shin, S.*, Y. Her, and Y. Khare, Evaluation of impacts of climate change on natural and managed wetland basins (2023), Journal of the American Water Resources Association, Published Online. <a href="https://doi.org/10.1111/1752-1688.13140">https://doi.org/10.1111/1752-1688.13140</a></li> <li>Glick, R., J. Jeong, R. Srinivasan, J. G. Arnold, and Y. Her (2023), Adaptation of SWAT watershed model for stormwater management in urban catchments, Water, 15(9), 1770. <a href="https://doi.org/10.3390/w15091770">https://doi.org/10.3390/w15091770</a></li> <li>Rose, P.K., V. Poonia, R. Kumar, N. Kataria, P. Sharma, J. Lamba, and P. Bhattacharya. 2023. Congo red dye removal using modified banana leaves: Adsorption equilibrium, kinetics, and reusability analysis. Groundwater for Sustainable Development: 101005. doi:https://doi.org/10.1016/j.gsd.2023.101005.</li> <li>Kaur, P*., J. Lamba, T.R. Way, V. Sandhu, K. Balkcom, A. Sanz-Saez, and Dexter Watts. 2023 Cover crop effects on X-ray computed tomography derived soil pore characteristics. Journal of Soils and Sediments. https://doi.org/10.1007/s11368-023-03596-7</li> <li>Kumar, H*., P. Srivastava, J. Lamba,, B. Lena, E. Diamantopoulos, B. Ortiz, G. Morata, B. Takhellambam*, and L Bondesan. 2023. A methodology to optimize site-specific field capacity and</li> <li>irrigation thresholds. Agricultural Water Management, 286, 108385. https://doi.org/10.1016/j.agwat.2023.108385</li> <li>Malhotra, K*., Zheng, J., A. Abebe, and J. Lamba. 2023. Application of Sediment Fingerprinting to Apportion Sediment Sources: Using Machine Learning Models. Journal of the ASABE. doi: 10.13031/ja.14906</li> <li>Singh, R., R. Prasad, K. Balkcom, K., J. Lamba., and D. B Watts. 2023. Broiler Litter Application Rate and Time Impacts on Corn Ear Mineral Composition. Agranomy Scicne, 00, 00– 00. https://doi.org/10.1002/agj2.21292</li> <li>Takhellambam, B.S*., P. Srivastava, J. Lamba, R.P. McGehee, H. Kumar* and D. Tian. 2023. Projected mid-century rainfall erosivity under climate change over the southeastern United States. Science of The Total Environment 865: 161119. doi:https://doi.org/10.1016/j.scitotenv.2022.161119.</li> <li>Anandhi, A., P. Srivastava, R.H. Mohtar, R.G. Lawford, S. Sen and J. Lamba. 2023. Methodologies and principles for developing nexus definitions and conceptualizations: Lessons from FEW nexus studies. Journal of the ASABE 0: 0. doi:https://doi.org/10.13031/ja.14539.</li> <li>Kumar, H*., P. Srivastava, J. Lamba, B.V. Ortiz, T.R. Way, L. Sangha*, B. Takhellambam*, G. Morata, and R. Molinari. 2022. Within-field variability in nutrients for site-specific agricultural management in irrigated cornfield. Journal of the ASABE. 65(4):865-880. https://doi.org/10.13031/ja.15042.</li> <li>Kumar, H*., P. Srivastava, J. Lamba, E. Diamantopoulos, B. Ortiz, G. Morata. B. Takhellambam, and L Bondesan. 2022. Site-Specific Irrigation Scheduling Using One-Layer Soil Hydraulic Properties and Inverse Modeling. Agricultural Water Management. 273: 107877. doi:https://doi.org/10.1016/j.agwat.2022.107877.</li> <li>Takhellambam, B.S*., P. Srivastava, J. Lamba, R.P. McGehee, H. Kumar* and D. Tian. 2022. Temporal disaggregation of hourly precipitation under changing climate over the Southeast United States. Scientific Data 9: 211. doi:10.1038/s41597-022-01304-7.</li> <li>Huang, Y.K., R. Karki*, L, Kalin, P. Dwivedi (2023), “Potential Impacts of Land Use Change on Streamflow and Groundwater Resources Under Changing Climate in the Flint River Basin, Georgia, United States”, Environmental Research Communications, 5(9):095010.</li> <li>Dai, Q., J. Zhu, G. Lv, L. Kalin, Y. Yao, S. Zhang, J. Zhang, Z. Wang, D. Han (2023), “Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale”, Science Advances. 9.32 (2023): eadg5551.</li> <li>Isik*, S., H. Haas*, L. Kalin, M.M. Hantush, C. Nietch (2023), “Nutrient Removal Potential of Headwater Wetlands in Coastal Plains of Alabama, USA”, Water, 15, 2687. https://doi.org/10.3390/w15152687.</li> <li>Jiang, M., H. Peng, S. Liang, S. Wanga, L. Kalin, E. Baltaci*, Y. Liu (2023), “Impact of extreme rainfall on non-point source nitrogen loss in coastal basins of Laizhou Bay, China”, Science of the Total Environment. http://dx.doi.org/10.1016/j.scitotenv.2023.163427.</li> <li>Bawa, R., N. Hoghooghi, L. Kalin, P. Dwivedi, Y. Huang (2023), “Designing Watersheds for Integrated Development (DWID): Combining hydrological and economic modeling for optimizing land use change to meet water quality regulations”, Water Resources and Economics. 41, 100209. https://doi.org/10.1016/j.wre.2022.100209.</li> <li>He, J., M. Hantush, L. Kalin, S. Isik* (2022), “A Two-Layer Numerical Model of Soil Moisture Dynamics: Model Assessment and Bayesian Uncertainty Estimation”, Journal of Hydrology. 613, 128327.</li> <li>Lombardozzi, D. L., Wieder, W. R., Sobhani, N., Bonan, G. B., Durden, D., Lenz, D., SanClements, M., Weintraub-Leff, S., Ayres, E., Florian, C. R., Dahlin, K., Kumar, S., Swann, A. L. S., Zarakas, C., Vardeman, C., and Pascucci, V. (2023, expected): Overcoming barriers to enable convergence research by integrating ecological and climate sciences: The NCAR-NEON system Version 1, Geoscientific Model Development, EGUsphere  https://doi.org/10.5194/egusphere-2023-271, 2023.</li> <li>Lee R, Boll J and Kumar S. (2023) Editorial: Limits and permanence of modern interventions in the water cycle. Front. Water 5:1179819. doi: 10.3389/frwa.2023.1179819.</li> <li>Kumar, S., Dewes, C. F., Newman, M., & Duan*, Y. (2023). Robust changes in North America's hydroclimate variability and predictability. Earth's Future, 11(4), e2022EF003239.</li> <li>Duan, Y., Akula, S., Kumar, S., Lee, W., & Khajehei, S. (2023). A Hybrid Physics-AI Model to Improve Hydrological Forecasts. Artificial Intelligence for the Earth Systems, 2(1), e220023.</li> <li>Pan, Z., Kumar, S., Zhang, Y., & Shi, C. Central continental boreal summer "warming holes" modulated by Atlantic Multi-decadal Oscillation via low level jets. Journal of Geophysical Research: Atmospheres, e2021JD035217.</li> <li>Phillippe, Austin J., Kevin L. Wagner, Rodney E. Will, Chris B. Zou. Accepted. Escherichia coli efflux from rangeland ecosystems in the southcentral Great Plains, USA. Journal of Environmental Quality.</li> <li>Wagner, K.L.; Gregory, L.; Gerlich, J.A.; Rhodes, E.C.; deVilleneuve, S. 2023. Edge-of-Field Runoff Analysis following Grazing and Silvicultural Best Management Practices in Northeast Texas. Water 2023, 15, 3537. https://doi.org/10.3390/w15203537</li> <li>Yang, J., C. Zou, R. Will, K. Wagner, Y. Ouyang, C. King, H. Tian. 2023. River flow decline across the entire Arkansas River Basin in the 21st Century. Journal of Hydrology: Regional Studies 618 (2023) 129253. https://doi.org/10.1016/j.jhydrol.2023.129253</li> <li>Schipanski, M.E., M. Sanderson, L. Estelí Méndez Barrientos, A. Kremen, P. Gowda, D. Porter, K. Wagner, C. West, C. Rice, M. Marsalis, B. Guerrero, E. Haacker, J. Dobrowolski, C. Ray, B. Auvermann. 2023. Shared groundwater resources: Moving from measurement to governance. Nature Water 1, pages 30–36 (2023). https://doi.org/10.1038/s44221-022-00008-x.</li> <li>Mirchi, A., M. Samimi, D. Moriasi, Z. Sheng, D. Gutzler, S. Taghvaeian, S. Alian, K. Wagner, W. Hargrove. 2023. Adapting irrigated agriculture in the Middle Rio Grande to a warm-dry future. Journal of Hydrology: Regional Studies 45 (2023) 101307. https://doi.org/10.1016/j.ejrh.2022.101307.</li> <li>Qiao, L., R. Will, K. Wagner, T. Zhang, C. Zou. 2022. Using SWAT to improve evapotranspiration estimates for grasslands of the Southern Great Plains. Journal of Hydrology: Regional Studies 44 (2022) 101275. https://doi.org/10.1016/j.ejrh.2022.101275.</li> <li>Mansaray, A.S., P. Kayastha, A.R. Dzialowski, S.H. Stoodley, K.L. Wagner. 2022. Effect of Time Window on Satellite and Ground-Based Data for Estimating Chlorophyll-a in Reservoirs. Remote Sensing 2022, 14, 846. https://doi.org/10.3390/rs14040846.</li> <li>Conoscenti, C., Sheshukov, A. Y. (2023). Regional variability of terrain index and machine learning model applications for prediction of ephemeral gullies. Geomorphology, 442, 108915. https://doi.org/10.1016/j.geomorph.2023.108915 </li> <li>G. Granco, M. Caldas, J. Bergtold, J.L. Heier Stamm, M. Mather, M. Sanderson, M. Daniels, A.Y. Sheshukov, D. Haukos, S. Ramsey. (2022) Local Environment and Individuals’ Beliefs: The Dynamics Shaping Public Support for Sustainability Policy in an Agricultural Landscape. Journal of Environmental Management. 301, 113776. (https://doi.org/10.1016/j.jenvman.2021.113776)</li> <li>Zhang, Z., H. Montas, A. Shirmohammadi, P.T. Leisnham, and A. Rockler. 2023. Modeling Spatio-Temporal Dynamics of BMPs Adoption for Stormwater Management in Urban Areas. Water (2023) 15, 2549. https://doi.org/10.3390/w15142549</li> <li>Zhang, Z., H. Montas, A. Shirmohammadi, P.T. Leisnham, and M. Negahban-Azar. 2023. Effectiveness of BMP plans in different land covers, with random, targeted, and optimized allocation. Science of The Total Environment, Volume 892, 20 September 2023, 164428.</li> <li>Shoushtarian, F., Negahban-Azar, M., and Crooks, A. Investigating the Microscale Dynamics of Water Reuse Adoption by Farmers, and the Impacts on Local Water Resources Using an Agent Based Model. (2022). Socio-Environmental Systems Modeling. 4, 18148. https://doi.org/10.18174/sesmo.18148</li> <li>Levia D, S Bischoff, M-C Gruselle, K Näthe, DR Legates, AN Lutgen, EW Boyer, and B Michalzik (2023). Geometric configurations of particulate matter in terrestrial solutions of a temperate beech forest. Journal of Aerosol Science. DOI: 10.1016/j.jaerosci.2023.106196</li> <li>Boyer EW, JW Wagenbrenner, and Lu Zhang (2022). Wildfire and Hydrological Processes. Hydrological Processes, 36(7), e14640, DOI: 10.1002/hyp.14640</li> <li>Boyer EW, MA Moritz, and MG Brown (2022). Smoke deposition to water surfaces drives hydrochemical changes. Hydrological Processes, 36(6), e14626, DOI: 10.1002/hyp.14626 (plus supporting dataset at HydroShare public data repository, DOI: 10.4211/hs.33c36d2fc1c94d96ba9e40f0460f665e)</li> <li>Sena, M. et al. Seasonal variation and drivers of elevated riparian groundwater ammonium concentrations upstream of milldams. Journal of Geophysical Research Biogeosciences (In Preparation – to be submitted Oct 2023).</li> <li>Kan, J. et al. 2023. Mill dams impact microbiome structure and depth distribution in riparian sediments. Frontiers in Microbiology. 14, 2023.</li> <li>Peck, E. et al. 2023. Influence of relict milldams on riparian sediment biogeochemistry. Journal of Soils and Sediments 23 (6), 2584-2599.</li> <li>Grande, E., E. C. Seybold, C. Tatariw, A. Visser, A. Braswell, B. Arora, F. Birgand, J. Haskins, and M. Zimmer (2023). “Seasonal and tidal variations in hydrologic inputs drive salt marsh porewater nitrate dynamics”. En. In: Hydrol. Process. 37.8. DOI: 10.1002/hyp.14951.</li> <li>Hammond, N. W., F. Birgand, C. C. Carey, B. Bookout, A. Breef-Pilz, and M. E. Schreiber (2023). “High-frequency sensor data capture short-term variability in Fe and Mn concentrations due to hypolimnetic oxygenation and seasonal dynamics in a drinking water reservoir”. In: Water Research, p. 120084. DOI: 10.1016/j.watres.2023.120084.</li> <li>Harmel, R. D., H. E. Preisendanz, K. W. King, D. Busch, F. Birgand, and D. Sahoo (2023). “A Review of Data Quality and Cost Considerations for Water Quality Monitoring at the Field Scale and in Small Watersheds”. In: Water 15, p. 3110. DOI: 10.3390/w15173110.</li> <li>Emine Fidan, Natalie G. Nelson, Josh Gray, Barbara Doll (2023), Machine Learning Approach for Modeling Daily Pluvial Flood Dynamics in Agricultural Landscapes, Environmental Modelling & Software, 167: 105758</li> <li>Mahmoud Shehata, Pierre Gentine, Natalie Nelson, Chadi Sayde (2023), Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study, Journal of Hydrology, 620, part A, 129449</li> <li>Natalie Reynolds, Blake A. Schaeffer, Lucie Guertault, Natalie G. Nelson (2023), Satellite and in situ cyanobacteria monitoring: Understanding the impact of monitoring frequency on management decisions, Journal of Hydrology, 619: 129278</li> <li>Lise R. Montefiore, Natalie G. Nelson, Michelle D. Staudinger, Adam Terando (2023), Vulnerability of Estuarine Systems in the Contiguous United States to Water Quality Change Under Future Climate and Land-Use, Earth's Future, 11(3): e2022EF002884.</li> <li>Panthi, J., Johnson, C.D., Pradhanang, S.M., Savage, B., Ismail, M.Y. and Boving, T.B., 2023. Delineating bedrock topography with geophysical techniques: An implication for groundwater mapping. Catena, 230, p.107258.</li> <li>Larson, A., Hendawi, A., Boving, T., Pradhanang, S.M. and Akanda, A.S., 2023. Discerning Watershed Response to Hydroclimatic Extremes with a Deep Convolutional Residual Regressive Neural Network. Hydrology, 10(6), p.116.</li> <li>Adhikari, T.R., Talchabhadel, R., Shrestha, S., Sharma, S., Aryal, D. and Pradhanang, S.M., 2022. The evaluation of climate change impact on hydrologic processes of a mountain river basin. Theoretical and Applied Climatology, 150(1-2), pp.749-762.</li> <li>Fidan, E. N., N. G. Nelson, J. Gray, B. Doll (2023) Machine learning approach for modeling daily pluvial flood dynamics in agricultural landscapes. Environmental Modelling & Software, 167. 105758. https://doi.org/10.1016/j.envsoft.2023.105758</li> <li>Singh, S., S. Jagadamma, D. Yoder, and Xinhua Yin.  2023.  A weighted soil health index approach for refined assessment of soil health in cropping systems. Frontiers of Soil Science 11 August 2023. https://doi.org/10.3389/fsoil.2023.1118526 </li> <li>Bailey, G., Y. Liu, N. McKinney, D. Yoder, W. Wright, and H. Herrero.  2022.  Comparison of ground point filtering algorithms for high-density point clouds collected by terrestrial LIDAR. Remote Sensing 14(19) 4776. https://doi.org/10.3390/rs14194776.</li> <li>Bailey, G., Y. Liu, N. McKinney, D. Yoder, W. Wright, R. Washington-Allen.  2022.  Las2DoD: Change detection based on digital Elevation models derived from dense point clouds with spatially varied uncertainty. Remote Sensing 14(7):1537.  https://doi.org/10.3390/rs14071537.</li> <li>Singh, S., S. Jagadamma, D. Yoder, X. Yin, and F. Walker.  2021. Cropping system management responses to Cornell and Alabama soil health assessment methods in the Southeastern United States. Soil Science Society of America Journal. 88(1):106-117. DOI: 10.1002/saj2.20357.</li> <li>Yoder, D.C., S. Jagadamma, S. Singh, A. Nouri, S. Xu, D. Saha, S.M. Schaeffer, N. Adotey, F.R. Walker, J. Lee, and M. Budipradigdo.  2021.  Soil health: meaning, measurement, and value through a critical zone lens. Journal of Soil and Water Conservation. DOI: https://doi.org/10.2489/jswc.2022.00042.</li> <li>Nouri, A., D.C. Yoder, M. Raji, S, Ceylan, S. Jagadamma, J. Lee, F.R. Walker, X. Yin, J. Fitzpatrick, B. Trexler, P. Arelli, and A.M. Saxton.  2021.  Conservation agriculture increases the soil resilience and cotton yield stability in climate extremes of the southeast US. Communications: earth and environment. https://doi.org/10.1038/s43247-021-00223-6.</li> <li>Bawa, A., Mendoza, K., Srinivasan, R., Parmar, R., Smith, D., Wolfe, K., Johnston, J.M., and Corona, J. National SWAT Hydrological Calibration at HUC12 subbasin scale: Case Study- the Mid-Atlantic Region (HUC2- 02). Journal of hydrology. [In review]</li> <li>Bawa, A., Mendoza, K., Srinivasan, R., Parmar, R., Smith, D., Wolfe, K., Johnston, J.M., and Corona, J. Enhancing Hydrological Modeling of Ungaged Watersheds through Machine Learning and Physical Similarity-based Regionalization of Calibration Parameters: A Case Study of the HUC2- Mid-Atlantic Region. Water Resource Research. [In review]</li> <li>Yared Bayissa, Yihun Dile, Raghavan Srinivasan, Claudia Ringler, Nicole Lefore, and A. W. Worqlul. 2023. "Evaluating the impacts of watershed rehabilitation and irrigation interventions on vegetation greenness and soil erosion using remote sensing and biophysical modeling in Feresmay watershed in Ethiopia."  All Earth. https://doi.org/10.1080/27669645.2023.2202968</li> <li>Abdu Y.Yimam, Feleke K. Sishu, Tewodros T. Assefa, Tammo S. Steenhuis, Manuel R. Reyes, Raghavan Srinivasan, and Seifu A. Tilahun. 2023. "Modifying the water table fluctuation method for calculating recharge in sloping aquifers."  Journal of Hydrology: Regional Studies 46:101325.</li> <li>Baogui Li, Gary W. Marek, Thomas H. Marek, Dana O. Porter, Srinivasulu Ale, Jerry E. Moorhead, David K. Brauer, Raghavan Srinivasan, Yong Chen. 2023. "Impacts of Ongoing Land-Use Change on Watershed Hydrology and Crop  Production Using an Improved Swat Model" Land 12, no. 3: 591.</li> <li>Heidari B., Prideaux V., Jack K. and Jaber F. H. 2023. A planning framework to mitigate localized urban stormwater inlet flooding using distributed Green Stormwater Infrastructure at an urban scale: Case study of Dallas, Texas. Journal of Hydrology. Volume 621. https://doi.org/10.1016/j.jhydrol.2023.129538.</li> <li>Heidari, B., Randle, S., Minchillo, D., & Jaber, F. H. (2022). Green stormwater infrastructure: A critical review of the barriers and solutions to widespread implementation. WIREs Water, e1625. https://doi-org.srv-proxy1.library.tamu.edu/10.1002/wat2.1625</li> <li>Goldsmith A M, F. H. Jaber, H. Ahmari, and C R. Randklev. 2022. “Clearing up cloudy waters: A review of sedimentation impacts to unionid freshwater mussels” Environmental Reviews. https://doi.org/10.1139/er-2020-0080</li> </ol>

Impact Statements

Date of Annual Report: 10/21/2024

Report Information

Annual Meeting Dates: 08/27/2024 - 08/28/2024
Period the Report Covers: 10/01/2023 - 09/30/2024

Participants

● Participants:
In person attendees (13):
• Latif (Auburn)
• Kevin (Oklahoma)
• Emine (Tennessee)
• Jerrad (Oregon)
• Sushant (South Dakota)
• Trisha (Kansas)
• Fouad (Texas)
• Santosh (Texas)
• Sara (Iowa)
• Aleksey (Kansas)
• Jeeban (Kansas - Postdoc)
• Laura (Kansas - PhD)
• Tyler (Kansas - PhD)

Virtual Attendees (6):
● Francois (NC - virtual)
● Mary (AA - virtual)
● Soni (Rhode Island - virtual)
● Zach (Virginia - virtual)
● Natalie (NC - virtual)
● David (Virginia - virtual)

Brief Summary of Minutes

Summary of minutes of annual meeting:

The meeting took place at the Ice Conference Room at Kansas State University in Manhattan, Kansas. The first day of the meeting was August 27, 2024 and the annual meeting ended on August 28, 2024.

The meeting started with a welcome by chair/host (Aleksey), as well as welcomes from the Kansas Water Institute (Susan Metzger), College of Engineering (Stacy Hutchinson), BAE (Mark Wilkins).

Next, we met with USDA Administrative Advisor (Mary Savin). Mary mentioned that we were awarded the Regional Multistate Research Award, but not the National Award. She mentioned that we are strongly encouraged to resubmit next year. Additionally, Mary stressed that the project will end next September and the approval process is a year-long process, so we need to start now with proposal writing and administrative review.

Host and Chair, Aleksey, prepared a presentation on the “History and activities of S1089”

Previous S1089 Officer, Fouad, shared updates on the Special Collection we set up in the Journal of Environmental Management. He shared that we need more reviewers and help from members of S1089 because the Special Collection is inundated with submissions.

Each state shared updates to the group, which is summarized in the section below.

The first day concluded with a discussion the direction for the new S1089 proposal, as well as an impact statement discussion with Sara Delheimer.

The second day’s meeting kicked off with a continuation of the previous day’s discussion surrounding the direction for the new S1089 proposal. During discussions, two committees were formed: a committee to spearhead the new S1089 proposal (consisting of Sara McMillan, Francois Birgand, Kevin Wagner, Sushant Mehan, Santosh Palmate, and Gerrad Jones) and a committee to write the agExcellence award nomination (consisting of Soni Pradhanang, Aleksey Sheshukov, Emine Fidan, Latif Kalin, and Rafa Munoz-Carpena).

Finally, the annual meeting ended with nominations of a new Secretary (a honor bestowed to Sushant Mehan) and the selection of next meeting location (hosted by Texas AgriLife in El Paso, Texas)

Elected officers (2024-2025):

Secretary: Sushant Mehan (South Dakota State U)

Vice Chair: Emine Fidan (U Tennessee)

Chair: Latif Kalin (Auburn U)

Past Chairs:

Soni Pradhanang (2020-2021)

Rafa Munoz-Carpena (2021-2022)

Fouad Jaber (2022-2023)

Aleksey Sheshukov (2023-2024)

Accomplishments

<ol start="2"> <li> Accomplishments:</li> </ol> The main focus of this project is to improve the abilities to better understand and predict fate and transport of pollutants and evaluate the effectiveness of best management practices (BMPs) on critical landscapes at the watershed scale. This includes hillslope soil health, water quality of streams and waterbodies, environmental benefits of mitigation practices and cost effectiveness of BMPs. The objectives will be met through the following activities: monitoring at sub-watershed scales, model development and applications at various spatial and temporal scales, and analyzing uncertainty in both monitoring and modeling efforts. Based on overall goals of S1089 Committee, here are the accomplishments and impacts reported by each state: Texas <ul> <li>Accomplishments: The Texas team focused on calibrating the Soil and Water Assessment Tool (SWAT) model at the HUC12 scale using data from over 4,000 monitoring stations across the United States. They implemented an R-programming-based automated calibration tool that enhances modeling efficiency. This tool was successfully piloted in the Arkansas-Red-White region, where more than 3,500 sub-basins were calibrated.</li> <li>Impact: Developing and implementing a large-scale, automated SWAT calibration tool significantly improved the efficiency and accuracy of hydrological model predictions across multiple basins. The tool’s effectiveness in large-scale applications will facilitate better BMP targeting in watersheds by identifying critical areas contributing to nonpoint source pollution, ultimately improving water quality at the regional scale.</li> </ul> Kentucky <ul> <li>Accomplishments: Researchers at the University of Kentucky focused on understanding the transport and fate of contaminants in karst and tile-drained landscapes through monitoring and modeling. They used both AI and physically-based models to enhance predictions and have ongoing collaborations with USDA-ARS to evaluate contaminant transport in these complex landscapes.</li> <li>Impact: These efforts provided critical insights into the unique challenges of managing water quality in karst and tile-drained areas, where conventional BMPs are often less effective. The improved understanding of nutrient and contaminant movement will enable more precise targeting of BMPs and better management of water resources in regions with similar landscape features.</li> </ul> North Carolina State University <ul> <li>Accomplishments: NC State developed novel stormwater monitoring techniques using low-cost sensors and machine vision models (e.g., fast R-CNN, YoloV8) to monitor flow and water quality in complex urban and agricultural settings. Additionally, nutrient source apportionment methods were developed using SWAT to better inform BMP placement.</li> <li>Impact: The use of innovative, low-cost monitoring tools and AI-based image analysis provided a scalable solution for continuous monitoring of stormwater and nutrient pathways, reducing monitoring costs. This allowed for more frequent and accurate assessment of BMP effectiveness, improving decision-making processes for stormwater management in urban and peri-urban environments.</li> </ul> Oklahoma <ul> <li>Accomplishments: The Oklahoma team focused on evaluating regenerative agricultural BMPs, such as no-till and cover cropping, through small watershed-scale monitoring. They found that implementing a winter cover crop on high cotton seeding rate plots significantly reduced runoff volume.</li> <li>Impact: The findings contributed to the understanding of how regenerative practices can reduce water quality impacts in cotton production systems. This data supports the adoption of these practices, demonstrating their potential to reduce runoff and improve water quality in similar agricultural settings.</li> </ul> Virginia Tech <ul> <li>Accomplishments: Virginia Tech focused on urban stormwater management and BMP effectiveness in reducing nitrogen loads in mixed-use watersheds. They also developed integrated urban hydrologic models using SWMM and HEC-RAS to assess BMP impacts on stream stability.</li> <li>Impact: Their modeling and monitoring efforts informed the design of stormwater infrastructure, improving urban water management strategies. This work supports urban planners in identifying cost-effective BMPs that enhance water quality and stabilize stream environments in rapidly developing areas.</li> </ul> Iowa State University <ul> <li>Accomplishments: ISU conducted paired watershed studies to evaluate nutrient reduction potentials of various BMPs using high-frequency sensors. They also integrated these data into predictive models to improve understanding of nutrient transport dynamics at small watershed scales.</li> <li>Impact: ISU’s work highlighted the importance of high-resolution monitoring in capturing nutrient dynamics, leading to more effective targeting and evaluation of BMPs. Their findings support refined nutrient management strategies, particularly in tile-drained agricultural landscapes.</li> </ul> Kansas State University <ul> <li>Accomplishments: Kansas State focused on developing models for ephemeral gully erosion detection and management, as well as assessing the efficacy of streambank stabilization practices. They successfully applied machine learning and topographic analysis to identify gully locations and developed a 2-D hydraulic model to simulate streambank erosion.</li> <li>Impact: Their modeling tools provided crucial insights into soil erosion and sediment management, supporting the targeting of BMPs for erosion control. These tools will help reduce sediment loadings in vulnerable watersheds, enhancing water quality and soil health.</li> </ul> Auburn University <ul> <li>Accomplishments: Auburn advanced climate and water quality modeling to predict BMP effectiveness under changing climate conditions. They developed tools for soil moisture forecasting and improved understanding of land-climate interactions in agricultural watersheds.</li> <li>Impact: These models are helping to build more resilient agricultural systems by providing data-driven insights into the interactions between land use, BMPs, and climate. Auburn’s efforts will inform adaptive BMP strategies that are better suited to future climate scenarios.</li> </ul> University of Tennessee <ul> <li>Accomplishments: Tennessee focused on developing the RUSLE2/Ephgee whole-field erosion model to combine hillslope and ephemeral gully erosion. They also created predictive flood maps and a Bayesian water quality model to understand the impacts of flooding on water contamination.</li> <li>Impact: Their models provide a comprehensive view of erosion and flood impacts, enabling the prioritization of BMPs in erosion-prone and flood-vulnerable areas. This supports the design of more effective BMPs for controlling soil loss and managing water quality during extreme events.</li> </ul> South Dakota State University <ul> <li>Accomplishments: South Dakota State University refined the SWAT model to simulate drainage water management and assessed its parameter transferability in different hydrological settings. Additionally, remote sensing and AI models were developed to predict surface soil moisture and actual evapotranspiration, particularly in semi-arid regions. They also published a series of practical guides on water management and ag cybersecurity.</li> <li>Impact: SDSU’s advancements in modeling and AI applications provide crucial tools for managing water resources in the Northern Great Plains. The practical outreach publications expanded awareness and adoption of best practices for water quality and cybersecurity management among stakeholders, enhancing overall landscape resilience.</li> </ul> Overall Impact The combined efforts of participating states under Objective 1 have significantly advanced the development and application of monitoring and modeling tools to target and implement BMPs more effectively across diverse landscapes. These contributions support enhanced water quality management at local, regional, and national scales, making significant strides in mitigating nonpoint source pollution and improving watershed health. Products <ol> <li>Publications – 58</li> <li>Award money secured - $ 8.6 m</li> <li>Number of Student – 59</li> <li>Thesis/Dissertation – 7</li> <li>Presentations – 43</li> <li>Popular Articles - 7</li> </ol>

Publications

Publications (58 Publications) South Dakota State University <ol> <li>Mankin, K. R., Mehan, S., Green, T. R., and Barnard, D. M.: Review of Gridded Climate Products and Their Use in Hydrological Analyses Reveals Overlaps, Gaps, and Need for More Objective Approach to Model Forcings, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2024-58, accepted, 2024.</li> <li>Lamichhane, Manoj, Abin Raj Chapagain, Sushant Mehan, Daniel P. Ames, and Sagar Kafle. "Integrating Solar-Induced Chlorophyll Fluorescence with Traditional Remote Sensing and Environmental Variables for Enhanced Rice Yield Prediction in Nepal Using Machine Learning." Remote Sensing Applications: Society and Environment, vol. 32, 2024, DOI: 10.1016/j.rsase.2024.101371.</li> <li>Amatya, D. M., Williams, T. M., Skaggs, R., Wayne; N., Jami E., and Mehan, S. (2024). Silvicultural Practices and Water Table Dynamics of Coastal Forested Wetlands in a Changing Climate. Accepted for publication in Journal of Natural Resources and Agricultural Ecosystems (ASABE Journals).</li> <li>Sharma, A., Mehan, S., McDaniel, R., Arnold, J. Trooien, T., Sammons, N., and Amegbletor, L. (2024). Assessing SWAT+ Performance in Simulating Drainage Water Management and Parameter Transferability for Watershed-Scale Applications. Journal of Hydrology. (Accepted for Publication)</li> <li>Lamichhane, M.*, Phuyal, S., Mahato, R., Shrestha, A., Pudasaini, U., Lama, S.D., Chapagain, A.R., Mehan, S. and Neupane, D. (2024). Assessing Climate Change Impacts on Streamflow and Baseflow in the Karnali River Basin, Nepal: A CMIP6 Multi-Model Ensemble Approach Using SWAT and Web-Based Hydrograph Analysis Tool. Sustainability, 16(8), p.3262. https://doi.org/10.3390/su16083262</li> </ol> Auburn University <ol> <li>Kumar, R., Kundu, D., Kormoker, T., Joshi, S., Rose, P. K., Kumar, S., Sahoo, P. K., Sharma, P., & Lamba, J. 2024. Phycoremediation of potentially toxic elements for agricultural and industrial wastewater treatment: Recent advances, challenges, and future prospects. Desalination and Water Treatment, 100505. https://doi.org/10.1016/j.dwt.2024.100505</li> <li>Biswas, S. Adhikari, H. Jahromi, M. Ammar, J. Baltrusaitis, A. Torbert, J. Linhoss and J. Lamba. 2024. Magnesium doped biochar for simultaneous adsorption of phosphate and nitrogen ions from aqueous solution. Chemosphere. https://doi.org/10.1016/j.chemosphere.2024.142130.</li> <li>Malhotra, K., J. Lamba, T. R. Way, C. Williams, K. G. Karthikeyan, S. Budhathoki*, R. Prasad, P. Srivastava, and J. Zheng, J. 2024. Preferential flow of phosphorus and nitrogen under steady-state saturated conditions. Vadose Zone Journal. https://doi.org/10.1002/vzj2.20331</li> <li>Eva, E., L. Marzen and J. Lamba. 2024. Modeling the Effect of LULC change on Water Quantity and Quality in Big Creek Lake Watershed, South Alabama USA. Egyptian Journal of Remote Sensing.</li> <li>Kaur, P., J. Lamba, T.R. Way, K. Balkcom, A. Sanz-Saez, and D. Watts. 2024 Characterization of soil pores in strip-tilled and conventionally-tilled soil using X-ray computed tomography. Soil and Tillage Research. 239, 106035.</li> <li>Takhellambam, B.S., P. Srivastava, J. Lamba, W. Zhao, H. Kumar, D. Tian, and R. Molinari. 2024. Artificial Neural Network-Empowered Projected Future Rainfall Intensity-Duration-Frequency Curves under Changing Climate. Atmospheric Research. Volume 297, 107122. https://doi.org/10.1016/j.atmosres.2023.107122.</li> <li>Kaur, P., J. Lamba, T.R. Way, V. Sandhu, K. Balkcom, A. Sanz-Saez, and D. Watts. 2024. Cover crop effects on X-ray computed tomography derived soil pore characteristics. Journal of Soils and Sediments. https://doi.org/10.1007/s11368-023-03596-7</li> <li>Bickley, S., S. Isik, C. Anderson, L. Kalin (2024), “Land Use and Runoff Effects on Tidal Creek Ecosystem Metabolism”, Marine Ecology Progress Series. Accepted.</li> <li>Baltaci, E., L. Kalin (2024), “A Low-Impact Development-based Modeling Framework for Flood Mitigation in a Coastal Community”, Water. 16(19), 2772; https://doi.org/10.3390/w16192772.</li> <li>Haas, H., L. Kalin, S. Kumar, G. Sun (2024). “Understanding the effects of afforestation on water quantity and quality at watershed scale by considering the influences of tree species and local moisture recycling”. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2024.131739.</li> <li>Wang, Z., H. Tian, S. Pan, H. Shi, J. Yang, N. Liang, L. Kalin, C. Anderson (2024), “Phosphorus Limitation on CO2 Fertilization Effect in Tropical Forests Informed by A Coupled Biogeochemical Model”, Forest Ecosystems. https://doi.org/10.1016/j.fecs.2024.100210.</li> <li>Yin, Z., Y. Liu, C. Li, Z. Si, L. Kalin, E. Baltaci, H. Peng, S. Saitoh, Q. Li (2024), “Marine aquaculture spatial planning on market orientation for Pacific oyster in Shandong, China”, Aquaculture. https://doi.org/10.1016/j.aquaculture.2024.741144.</li> <li>Haas, H., L. Kalin, H. Yen (2024), “Improved forest canopy evaporation leads to better predictions of ecohydrological processes”, Ecological Modeling. Vol 489. https://doi.org/10.1016/j.ecolmodel.2024.110620.</li> <li>Haas, H., L. Kalin, E. Baltaci (2024), “How wide is the problem? Scrutinizing the importance of channel geometry representation in watershed modeling”, Environmental Modeling and Software. Vol 172. https://doi.org/10.1016/j.envsoft.2023.105935.</li> <li>Tassi, R. E.J. Seidel, D.M. da Motta-Marques, A.O.N. Villanueva, L. Kalin (2023), “Wildlife roadkill driven by hydrological regime in a subtropical wetland”, Water. 15(24), pg. 4307. https://doi.org/10.3390/w15244307.</li> <li>Karki, R., P. Srivastava, L. Kalin (2023), “Evaluating climate change impacts in a heavily irrigated karst watershed using a coupled surface and groundwater model”, Journal of Hydrology: Regional Studies. https://doi.org/10.1016/j.ejrh.2023.101565.</li> <li>Zihao, B., H. Tian, S. Pan, H. Shi, C. Lu, C. Anderson, W-J Cai, C. Hopkinson, D. Justic, L. Kalin, S. Lohrenz, S. McNulty, N. Pan, G. Sun, Z. Wang, Y. Yao, Y. You (2023), “Soil legacy nutrients contribute to the decreasing stoichiometric ratio of N and P loading from the Mississippi River Basin”, Global Change Biology. http://doi.org/10.1111/gcb.16976.</li> <li>Singh, A., Kumar, S., Chen, L., Maruf, M., Lawrence, P., & Lo, M. H. (2024). Land Use Feedback under Global Warming–A Transition from Radiative to Hydrological Feedback Regime. Journal of Climate. 37 (14), 3847-3866. https://doi.org/10.1175/JCLI-D-23-0426.1</li> <li>Duan, Y., & Kumar, S. (2024). A revised interpretation of signal-to-noise ratio paradox and its application to constrain regional climate projections. Environmental Research: Climate. DOI 10.1088/2752-5295/ad3a0c</li> <li>Richter, J. H., Glanville, A. A., King, T., Kumar, S., Yeager, S. G., Davis, N. A., Duan, Y.,... & Oleson, K. (2024). Quantifying sources of subseasonal prediction skill in CESM2. npj Climate and Atmospheric Science, 7(1), 59.</li> </ol>   University of Tennessee <ol> <li>Singh, S., S. Jagadamma, D. Yoder, and Xinhua Yin.  2023.  A weighted soil health index approach for refined assessment of soil health in cropping systems. Frontiers of Soil Science 11 August 2023. <a href="https://doi.org/10.3389/fsoil.2023.1118526">https://doi.org/10.3389/fsoil.2023.1118526</a>. Role:  assisted in project design & data analysis</li> <li>Fidan, E., J. Gray, B. Doll, N. G. Nelson (2023). Machine learning approach for modeling daily pluvial flood dynamics in agricultural landscapes. Environmental Modeling and Software, 167. <a href="https://doi.org/10.1016/j.envsoft.2023.105758">https://doi.org/10.1016/j.envsoft.2023.105758</a></li> </ol> Kansas State University <ol> <li>Koudahe, K., Aguilar, J., Djaman, K., Sheshukov, A. (2024) Evapotranspiration, fiber yield and quality, and water productivity of cotton (Gossypium hirsutum L.) under different irrigation technologies in a semiarid climate. Irrigation Science. https://doi.org/10.1007/s00271-024-00922-w</li> <li>Akin, A., Nguyen, G.T., A.Y. Sheshukov. (2024) Infiltration-Caused Variability of Soil Erodibility Parameters Using the Jet Erosion Test. Water, 16(7), 981; https://doi.org/10.3390/w16070981</li> <li>Zhou, W., Zhang, L., Sheshukov, A., Wang, J., Zhu, M., Sargsyan, K., Xu, D., Liu, D., Zhang, T., Mazepa, V., Sokolov, A., Valdayskikh, V., Ivanov, V. (2024). Ground heat flux reconstruction using Bayesian uncertainty quantification machinery and surrogate modeling. Earth and Space Science, 11, e2023EA003435. https://doi.org/10.1029/2023EA003435</li> <li>Conoscenti, C., Sheshukov, A. Y. (2023). Regional variability of terrain index and machine learning model applications for prediction of ephemeral gullies. Geomorphology, 442, 108915. https://doi.org/10.1016/j.geomorph.2023.108915</li> <li>Mather, M., Granco, G., Bergtold, J., Caldas, M., Heier Stamm, J., Sheshukov, A., Sanderson, M., Daniels, M. (2023) Achieving success with RISE: A widely implementable, iterative, structured process for mastering interdisciplinary team science collaborations, BioScience, 73(12), 891–905, https://doi.org/10.1093/biosci/biad097</li> <li>Bigham, K.A., Keane, T.D., Moore, T.L. 2023 Can deciduous tree revetments reduce streambank erosion rates on a sand-bed stream? River Research and Applications 39(9): 1696-1708. https://doi.org/10.1002/rra.4190</li> <li>Bigham, K.A., Keane, T.D., Moore, T.L. (2024). Effect of flow regulation on streambank erosion: a perspective downstream of a flood control dam, Kansas, USA. River Research and Applications 40(1): 14-28. https://doi.org/10.1002/rra.4212</li> <li>Kyle Kohman, Lior Shamir, Aleksey Sheshukov (2023) Automatic Gully Mapping Using Generative Adversarial Network. Governor’s conference of the future of water in Kansas. Manhattan, KS</li> </ol> Iowa State University <ol> <li>Frankenberger, J., S.K. McMillan, M.R. Williams, K. Mazer, J. Ross, B. Sohngen. 2023. Drainage water management: A review of nutrient load reductions and cost effectiveness. Journal of the ASABE. doi: 10.13031/ja.15549.</li> <li>Rudko, N., S.K. McMillan, J. Frankenberger, D. Winter Lay, A. Limiac. 2024. Water quality sampling provides insight into nutrient sources and pathways in an agricultural watershed in the Midwestern USA. Journal of Natural Resources and Agricultural Ecosystems. Accepted 6/20/2024.</li> </ol> Virginia Tech <ol> <li>Towsif Khan, S. Wynn‐Thompson, T.M., Sample, D., Al‐Smadi, M., Shahed Behrouz, M., 2024. Effectiveness of stormwater control measures in protecting stream channel stability, Hydrological Processes 38 (6), e151784.</li> <li>Shahed Behrouz, M., Sample, D.J., Kisila, O.B., Harrison, M., Nayeb Yazdi, M., Garna, R.K., 2024. Parameterization of nutrients and sediment build-up/wash-off processes for simulating stormwater quality from specific land uses, Journal of Environmental Management 358, 12076</li> <li>Garna, R., D.R. Fuka, R.R. White, J.W. Faulkner, A.S. Collick, Z.M. Easton. 2023. Development of a dairy model for the Soil and Water Assessment Tool (SWAT) to direct water quality management of livestock. (In Review).</li> <li>Garna, R., Z.M. Easton, J.W. Faulkner, A.S. Collick, D.R. Fuka. 2023. Employing higher density lower reliability weather data from the Global Historical Climatology Network (GHCN) monitors to generate serially complete weather data for watershed modeling. Hydrological Processes 37(11), e15013. https://doi.org/10.1002/hyp.15013</li> <li>Garna, R., D.R. Fuka, J.W. Faulkner, A.S. Collick, Z.M. Easton. 2023. Watershed model parameter estimation in low data environments. Journal of Hydrology Regional Studies. 45 (2023) 101306. https://doi.org/10.1016/j.ejrh.2022.101306</li> </ol> Oklahoma State University <ol> <li>Khodkar, K., A. Mirchi, V. Nourani; A. Kaghazchi; J.M. Sadler; A. Mansaray; K. Wagner; P.D. Alderman; S. Taghvaeian; R.T. Bailey. 2024. Stream Salinity Prediction in Data-Scarce Regions: Application of Transfer Learning and Uncertainty Quantification. Journal of Contaminant Hydrology Sep;266:104418. doi: 10.1016/j.jconhyd.2024.104418.</li> <li>Murray, B., K. Wagner, R. Reuter, L. Goodman. 2024. Use of virtual fencing to implement critical conservation practices. Rangelands (Accepted).</li> <li>Qiao, L., D. Livsey, J. Wise, K. Kadavy, S. Hunt, K. Wagner. 2024. Predicting Flood Stages in Watersheds with Different Scales Using Hourly Rainfall Dataset: A High-Volume Rainfall Features Empowered Machine Learning Approach. Science of the Total Environment Volume 950, 2024, 175231, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2024.175231.</li> <li>Eck, C., K. Wagner. 2024. Flowing Perceptions: Exploring Secondary Students’ Perceptions of Water. Advancements in Agricultural Development. https://doi.org/10.37433/aad.v5i1.405</li> <li>Phillippe, Austin J., Kevin L. Wagner, Rodney E. Will, Chris B. Zou. 2023. Escherichia coli efflux from rangeland ecosystems in the southcentral Great Plains, USA. Journal of Environmental Quality, 00, 1-12. <a href="https://doi.org/10.1002/jeq2.20527">https://doi.org/10.1002/jeq2.20527</a></li> </ol> NCSU <ol> <li>Sauers N, Rok A., Birgand F, Evidence of Nitrate Removal ‘hot Moments’ During Flow and Nitrate Pulses in a Denitrification ‘hot Spot’. J. ASABE. In revision.</li> <li>Julia Harrison, Christopher Osburn, Angela Harris, Natalie G. Nelson, Tryptophan-like fluorescence in brackish waters for applications in bacterial water quality monitoring, In revision with ACS ES&T Water</li> <li>Natalie Chazal, Megan Carr, A.K. Leight, Sheila Saia, Natalie G. Nelson (2024), <a href="https://doi.org/10.1016/j.marpolbul.2024.116053">Short-Term Forecasting of Fecal Coliforms in Shellfish Growing Waters</a>, Marine Pollution Bulletin, 200: 116053</li> <li>Qicheng Tang, Owen W. Duckworth, Daniel R. Obenour, Stephanie B. Kulesza, Nathan A. Slaton, Andrew H. Whitaker, Natalie G. Nelson (2024), <a href="http://doi.org/10.1002/jeq2.20622">Relationship between soil-test-phosphorus and agricultural surplus phosphorus</a>, Journal of Environmental Quality, In press</li> </ol> University of Kentucky <ol> <li>Agioutanti, R., Ford, W., Sama, M., McGill, T.  (2024). Impacts of aquatic vegetation dynamics on nitrate removal in karst agricultural streams: Insights from unmanned aircraft systems and in situ sensing. Journal of the ASABE, 67(2) 89-104, doi: 10.13031/ja.15747.</li> <li>Ford, W., Williams, M.R. Mumbi, R.C. (In Review). Subsurface sediment transport in the shallow vadose zone of fine-textured soils with heterogenous preferential flows. Hydrological Processes, Revised Resubmission.</li> <li>McGill, T., Ford, W. (2024). Extreme learning machine predicts high-frequency stream flow and nitrate concentrations in a karst agricultural watershed. Journal of the ASABE, 67(2) 73-87, doi: 10.13031/ja.15747.</li> <li>Mumbi, R., Williams, M., Ford, W., Penn, C. (In Review). Dissolved phosphorus leaching reflects the dynamic interaction between hydrology and soil phosphorus kinetics.  Vadose Zone Journal, Under Review.</li> <li>Williams, M. R., Ford, W. I., & Mumbi, R. C. (2023). Preferential flow in the shallow vadose zone: Effect of rainfall intensity, soil moisture, connectivity, and agricultural management. Hydrological Processes, 37(12), e15057.</li> </ol>   University of Maryland <ol> <li>Rahman, A., M. Negahban-Azar, A. Shirmohammadi, and R. Karki. 2024. Evaluating the potential of recycled water use for irrigation in southern Maryland: impact on groundwater conservation and crop yield. Water Supply 24(7):2451-2472, <a href="https://doi.org/10.2166/ws.2024.137">https://doi.org/10.2166/ws.2024.137</a>.</li> <li>Shirmohammadi, A., L. Olson, E. Davidson, N. Dixit, R. Epanchin-Niell, P. Goeringer, A. Leslie, M. Negahban-Azar, N. Rawat, E. Rico, A. Ruiz-Barradas, and J. Timmons. 2024. Science and Technology Based Approach (STBA) to Minimize Climate Vulnerability and Achieve Sustainable and Resilient Food Production Systems (SRFP) in Maryland. Final Project Report submitted to the Hughese Center for Agroecology, Wye Reserch and Education Center, University of Maryland, June 15, 2024. 198p.</li> </ol>   Proposals Awarded ($8,615,382) The total award amounts for each institution are as follows: <ul> <li>South Dakota State University: $401,326</li> <li>University of Tennessee: $634,343</li> <li>Iowa State University: $1,233,162</li> <li>Virginia Tech: $4,981,428</li> <li>Oklahoma State University: $964,592</li> <li>North Carolina State University (NCSU): $400,531</li> </ul> The overall total amount awarded to all institutions combined is $8,615,382 South Dakota State University <ol> <li>Bridging Community insights and solutions in Water Resources Management: A Pathway to Water Resources Program in South Dakota. $99, 514 Awarded 2024</li> <li>United States Geological Survey (USGS) 104 (b). Integrated Remote Sensing and Water Quality Analysis for Spatiotemporal Assessment of Surface Water Quality in Eastern South Dakota. $15,000 Awarded 2024</li> <li>United States Geological Survey (USGS) 104 (b). Development of a non-contact, AI-driven method for rapid assessment of surface water quality based on imagery and smells. $12,372 Awarded             2024</li> <li>East Dakota Water Development District. Assessing the Environmental and Economic Efficacy of the SRAM Program in the Big Sioux River Watershed. $120,553 Awarded. 2024</li> <li>2024 South Dakota Nutrient Research and Education Council. Utilization of Laser-Induced Graphene-Based Sensor for Soil NPK Measurements and Development of Nutrients Maps - $63,412 Awarded. 2024</li> <li>PD – USDA ARS (Agricultural Research Service) Non-Assistance Cooperative Agreement - $60,475. Awarded (Geospatial Analysis and Modeling of Agrohydrological Variability in the Water-limited Great Plains.). #58-3012-3-019/Amendment01. $30,000 (Awarded). 2023</li> </ol> University of Tennessee <ol> <li>RUSLE2 Maintenance. D. Yoder. USDA-NRCS through CESU agreement with Clemson University. $159,305 from 2022-2027</li> <li>RUSLE2 Development. D. Yoder. USDA-NRCS through CESU agreement with Clemson University. $125,740 from 2022-2025</li> <li>Fidan (Co-PI). Deep learning empowered real-time high-fidelity flood hazard forecast system. The University of Tennessee– AI TENNessee. $50,000. 07/01/2024 – 6/30/2025</li> <li>Fidan (Lead PI). Environmental Justice in the City: Socio-Economic Dimensions of Urban Stream Health. The University of Tennessee– Institute for a Secure & Sustainable Environment. $50,000. 07/01/2024 – 6/30/2025</li> <li>Fidan (Co-PI). Institute for Climate and Community Resilience. The University of Tennessee Track II. $249,298. 07/01/2024 – 06/30/2027</li> </ol> Kansas State University <ol> <li>Developing and assessing innovative ephemeral gully erosion control practices. T Franti, A. Sheshukov, J. Lory, R. Cruse. (2021-2024) USDA-NRCS </li> <li>Valuing Water Quality Improvements in Heartland Reservoirs. R.L. North, A. Ohler, L. McCann, T. Moore, A. Sheshukov. (2022-2025) EPA-STAR</li> <li>Early Detection of Harmful Algal Blooms in Kansas Lakes and Reservoirs Using Satellite Remote Sensing. J. Panthi, T. Moore, A. Sheshukov. USGS 104b. (2024-2026)</li> <li>Effectiveness of agricultural BMPs at the regional scale under current and future climatic trends with a KanDEP model. A. Sheshukov, B. Gelder, R. Cruse. Kansas Water Office.  (2024-2027)</li> <li>Assessment of water quality improvement and sediment reduction outcomes from land use improvements in Red Hills watershed associated with grassland management. A. Sheshukov. The Nature Conservancy. (2024-2025)</li> <li>Offsite BMP Program to bring urban and rural stakeholders for water-quality benefits. A. Sheshukov, T. Moore. USDA-NIFA. (2023-2024)</li> <li>Development of an alternative stormwater compliance program for the City of Manhattan. T. Moore. City of Manhattan. (2023-2024). </li> <li>Evaluation of reach-scale effects of streambank stabilization on the Cottonwood River, Kansas. K. Bigham, T. Layzell, and T. Moore. Kansas Water Office (2023-2024). </li> </ol> Iowa State University <ol> <li>Two-stage agricultural channels in Iowa’s drained landscape to improve water quality and long-term resilience. $149,036. 8/1/2024 – 7/31/2026. PI: S.W. McMillan. CoPIs: A. Arenas, P. Moore, K. Schilling, J. Swanson, A. Brown.</li> <li>Fourmile Creek: Assessment of restoration effectiveness. $379,751. 7/1/2024 – 6/30/2028. PI: P. Moore. CoPIs: T. Isenhart, S.W. McMillan.</li> <li>Iowa Mayors Design Workshop. Funded by Iowa State University. $70,000. 6/1/2024 – 5/31/2025. PI: E. Olson-Douglas. CoPIs: A. Dunn, S.W. McMillan, J. Robison, C. Rogers.</li> <li>Scott County, Iowa - Working lands for resilient communities. Funded by NRCS-RCPP. Lead institution is Ducks Unlimited (total grant $8,000,000); subaward to ISU ($268,095). 5/1/2024 – 4/30/2029. PI: S.W. McMillan, CoPI: R. McGehee.</li> <li>Sensor integration to demonstrate benefits of regenerative agriculture on soil health. Funded by NSF-IUCRC (Industry University Cooperative Research Centers). $50,000. 2/1/2024 – 1/31/2025. PI: S.W. McMillan, CoPIs: D. Anderson, C. Gomes, N. Hoover, M. Soupir.</li> <li>Nutrient Reduction Research Program: Sources and mitigation of sediment and phosphorus in agricultural streams. Funded by State of Iowa Department of Agricultural and Land Stewardship. $316,280. 1/1/2024 – 12/31/2027. PI: S.W. McMillan, CoPI: P. Moore.</li> </ol> Virginia Tech <ol> <li>Bell, N., Xia, K., Sample, D. Investigation of traditional and innovative stormwater management practices to reduce contaminants of emerging concern in socioeconomically disadvantaged communities. Award: $199,973.May 2024-April 2026.</li> <li>USDA-Cooperative Agreement. Easton, Z.M. Modeling the Lake Champlain Basin CEAP watersheds to understand and predict conservation effects on legacy phosphorus $134,223. Oct 2021-Sept 2025.</li> <li>Collick, A.S., Z.M. Easton, and R. Bryant. UMES Stormwater Management Research Facility: Investigating nutrient and sediment reduction from poultry house stormwater drainage systems. $399,000. Sept 2020-Aug 2024</li> <li>NSF CPS (Cyber-Physical Systems). White, R.R., E. Feuerbacher, Z.M. Easton. Collaborative Research: CPS: Medium: Greener Pastures: A pasture sanitation cyber physical system for environmental enhancement and animal monitoring. $998,232. June 2022-May 2025.</li> <li>Virginia Dept of Environmental Quality.Easton, Z,M & K.S. Stepheson. Bioreactors to Remove Legacy Nitrogen to meet VA TMDL goals. $250,000. Dec 2023-Dec 2025.</li> <li>USDA-NRCS CIG- On-Farm Trials. Delaware Soil and Water Conservation District, Z.M. Easton, Q. Kettering. $3,000,000. Jan 2024-Dec 2028.</li> </ol> Oklahoma State University <ol> <li>Title: MRI: Track 1 Acquisition of an Advanced Low-altitude Earth Observing System (ALEOS) with Hyperspectral and LiDAR Capabilities to Advance Interdisciplinary Research and Training. Funding Agency: NSF MRI. Principal Investigator: H. Gholizadeh (OSU). Co-Investigators: G. Wilson, K. Baum, J. Jacob, S. Fuhlendorf, R. Will, C. Zou, K. Wagner, B. Bachelot, E. Schnitzler, L. Zhai (OSU). Status: Funded 9/1/2023-8/31/2026 ($467,796)</li> <li>Title: Building Water Quality and Rural Health Education Capacity through Private Well Screenings and Training. Funding Agency: USDA Rural Health and Safety Education Competitive Grants Program. Principal Investigator: Nicole Colston (OSU). Co-Investigators: K. Wagner, Abu Mansaray, J. Sadler (OSU). Status: Funded 9/1/2023-8/31/2026 ($349,956)</li> <li>Title: FY23 104b State Water Resources Research Institute Program. Funding Agency: USGS. Principal Investigator: K. Wagner. Co-Investigators: M. Foltz, M. Krzmarzick, K. Mangalgiri, N. Materer, A. Mirchi, K. Sallam (OSU). Status: Funded 9/1/2023-8/31/2024 ($146,840)</li> </ol> NCSU <ol> <li>AI-driven, Web-deployed, Low-Cost Visual Sensing of Stormwater Outlet Flow. F Birgand, L Wiang. NC DOT $400,531</li> </ol> Students Mentored (59 Students) South Dakota State University Serving as a primary adviser <ol> <li>Manoj Lamichhane, PhD Student in Ag and Biosystems Engineering – May 2026</li> <li>Kayode B. Adebayo, PhD Student in Ag and Biosystems Engineering – December 2026</li> <li>Azar Movaghatian, PhD Student in Biological Sciences – May 2026</li> </ol> Serving as a committee member <ol> <li>Maryam Sahraei, PhD Candidate in Ag and Biosystems Engineering – May 2025</li> <li>Umar Javed, PhD Candidate in Ag and Biosystems Engineering – May 2025</li> <li>Faisal Almitairi, Civil and Environmental Engineering</li> </ol> MS Students <ol> <li>Tulsi Ram Pokhrel, MS Student in Ag and Biosystems Engineering – January 2026</li> </ol> Undergraduate Students <ol> <li>Kyle Maher, BS, SDSU Data Science</li> <li>Sara Abbasi Benhangi, Department of Civil and Environmental Engineering</li> </ol> University of Tennessee <ol> <li>Ryan Ackett, PhD Student working with Dr. Fidan as part of their committee</li> <li>Conlan Burbrink, PhD Student working with Dr. Fidan as part of their committee</li> <li>Henley Sartin, Master’s Student working with Dr. Fidan as part of their committee</li> <li>Savannah Jobkar, Master’s Student working with Dr. Fidan</li> <li>Abby Worth, Undergraduate Student with Dr. Fidan</li> <li>Evelyn Hedrick, Undergraduate Student with Dr. Fidan</li> <li>Hannah Thomas, Undergraduate Student with Dr. Fidan</li> </ol>   Kansas State University <ol> <li>Jeeban Panthi, Postdoctoral Associate, BAE</li> <li>Laura Krueger, PhD student, BAE</li> <li>Corben Monzon, MS Student, BAE – graduated 2024</li> <li>Averi Baker, MS Student, BAE – graduated 2024</li> <li>Srijana Mahat, MS Student, BAE</li> <li>Sean Hackenberg, REU student, Computer Science</li> <li>Kyle Kohman, REU student, Computer Science</li> <li>Josiah Quinlan, Undergraduate student - BAE</li> <li>Sophia Steffenmiester, Undergraduate student - Environmental science</li> </ol> Iowa State University <ol> <li>Noah Rudko (2024): Ross Graduate Fellow; currently Postdoctoral Fellow at University of Arkansas.</li> <li>Danielle Winter (2023) NSF Graduate Research Fellow, Purdue Doctoral Fellow; currently Extension Specialist at Purdue University.</li> <li>Ian Chesla (2022-) Purdue University (co-advised by Dr. Jacob Hosen)</li> <li>Wendy Yarborley Abbey (2023-), Iowa State University, Agricultural & Biosystems Engineering</li> <li>Joseph Bergeron (2024-), Iowa State University, Environmental Science</li> <li>Sage Coffman (2024-), Iowa State University, Environmental Science</li> </ol> Virginia Tech <ol> <li>Maliha Mushtari1 PhD Student (anticipated graduation Spring, 2026).</li> <li>Sami Towsif Khan1, PhD Student ((graduated Spring, 2024).)</li> <li>Hossein Ahmadi2 PhD Student (anticipated graduation Spring, 2025).</li> <li>Michael Harrison, MS Student (Graduated Spring, 2024).</li> <li>Savanna Blackburn, MS Student, Student (graduated Spring, 2024).</li> <li>Sabrina Mehzabin, PhD Student (Graduation Spring, 2025).</li> <li>Binyam Asfaw, PhD Student (Graduation, Spring, 2025).</li> <li>Siam Maksud, PhD Student (Graduation, Spring, 2025).</li> <li>Ella Lewis, Undergraduate (Junior).</li> <li>Stella Bryant, Undergraduate (Junior).</li> </ol> 1Coadvised with T. Thompson 2Coadviseds with D. Scott Oklahoma State University. <ol> <li>Lindsey Berube, MS, Environmental Science, Oklahoma State University</li> <li>Cole Davis, MS, Environmental Science, Oklahoma State University</li> <li>Jack Edwards, MS, Environmental Science, Oklahoma State University</li> <li>Austin Phillippe, PhD, Natural Resource Ecology and Management, Oklahoma State University</li> </ol> NCSU <ol> <li>Qianyu Hang, Ph.D. student</li> <li>Mohammad Nooshzadi, M.S. student </li> <li>Nora Sauers, undergraduate student</li> <li>Julia Harrison, PhD student</li> <li>Hector Fajardo, PhD student</li> <li>Christopher Oates, PhD student</li> <li>Taj Hewitt, undergraduate student</li> <li>Abby Studnek, undergraduate student</li> </ol> University of Kentucky <ol> <li>Nabil Al Aamery, Postdoctoral Fellow</li> <li>Tiffany Coogle, MS Student (Anticipated Graduation Spring 2026)</li> <li>Tyler Botts, MS Student (Anticipated Graduation Spring 2026)</li> <li>Abby Berry, MS Student (Anticipated Graduation Spring 2025)</li> <li>Quinn Rison, Undergraduate Researcher (Graduates Spring 2025)</li> <li>Hunter Walters, Undergraduate Researcher (Graduated Spring 2024)</li> </ol>   Thesis/Dissertation (7) Kansas State University <ol> <li>Monzon, C. 2024. Evaluation of streambank stabilization structures on upstream and downstream bank erosion, MS, Kansas State University.</li> <li>Baker, A. (2024) Effects of wind on reservoir mixing and stratification: a case study from Kansas. MS, Kansas State University</li> </ol> Iowa State University <ol> <li>Ciupak, Meghan. 2023. Biogeochemical factors influencing dissolved greenhouse gasses within two Indiana wetlands. MS Thesis. Purdue University.</li> <li>Winter Lay, Danielle. 2023. Optimizing design and management of restored wetlands and floodplains in agricultural watersheds. PhD Dissertation. Purdue University.</li> <li>Rudko, Noah. 2024. The impact of agricultural conservation practices on water quality in tile-drained watersheds. PhD Dissertation. Purdue University.</li> </ol> Virginia Tech <ol> <li>Towif Kahn, S., 2024. Impacts of Stormwater Management Practices and Climate Change on Flow Regime and Channel Stability, Ph.D. dissertation, 167 p.</li> </ol> NCSU <ol start="2"> <li>Nooshzadi, M. Low-Cost Visual Sensing of Stormwater Outflow. M.S. thesis. NC State University, Raleigh, NC.</li> </ol> Presentations (43 Presentations) Virginia Tech <ol> <li>Thompson, T., Sample, D., Stephenson, K., Towsif Khan, S., & Macdonald, K., 2024. Cost-effective methods for reducing sediment loads in Lick Run. In Watershed Science in Action:  A Roanoke Stormwater Symposium.</li> <li>Thompson, T., Sample, D., Al-Smadi, M., Towsif Khan, S., Shahed Behrouz, M., & Miller, A., 2023. Effectiveness of Stormwater Management Practices in Protecting Stream Channel Stability. In Stepping Up Our Efforts:  Now is the Time.  29th Annual Conference of the Maryland Water Monitoring Council. Baltimore, MD.</li> <li>Thompson, T., Sample, D., Al-Smadi, M., Towsif Khan, S., Shahed Behrouz, M., Miller, A., & Butcher, J., 2023. Effectiveness of stormwater management practices in protecting stream channel stability. In Pooled Monitoring Forum: Restoration Research to make Science and Regulatory Connections. Baltimore, MD.</li> <li>Thompson, T., Sample, D., Al-Smadi, M., Towsif Khan, S., Shahed Behrouz, M., Miller, A., & Butcher, J., 2024. Do Maryland's Stormwater Management Regulations Protect Channel Stability? Presentation (not at a conference)/Webinar for the Maryland Stream Restoration Association. 84 participants, 20 Jun 2024.</li> <li>Thompson, T., Sample, D., Al-Smadi, M., Towsif Khan, S., Shahed Behrouz, M., & Miller, A., 2024. Effectiveness of stormwater management practices in protecting stream channel stability. Online Presentation (not at a conference) Graduate seminar for Department of Geography & Environmental Systems at University of Maryland, Baltimore County  Presentation date: 06 Mar 2024.</li> <li>Towsif Khan, S., Thompson, T., & Sample, D., 2024. Assessing the Efficacy of Stream Restoration and SCM Retrofitting for Channel Stability in Urbanized Catchments. I presented at the meeting of the American Ecological Engineering Society 24th Annual Conference. Blacksburg, VA.</li> <li>Maliha, M., Al-Smadi, M., Sample, D., Thompson, T., Miller, A., & Shahed Behrouz, M., 2024. Traditional Stormwater Management vs Environmental Site Design (ESD): Modeling impacts of stormwater management practices on surface runoff in an urban watershed. Poster session presented at the meeting of the American Ecological Engineering Society 24th Annual Conference. Blacksburg, VA.</li> <li>Thompson, T., Sample, D., Alsmadi, M., Towsif Khan, S., Shahed Behrouz, M., Miller, A., & Butcher, J., 2024. Effectiveness of stormwater management practices in protecting stream channel stability. University of Maryland, Baltimore County.</li> <li>Mehzabin, S., K. Stephenson, D.R Fuka, and Z.M. Easton. 2024. Environmental and management impacts of legacy nitrogen remediation with bioreactors. American Ecological Engineering Society Annual Meeting. Blacksburg VA, May 2024.</li> <li>Mehzabin, S., K. Stephenson, D.R Fuka, and Z.M. Easton. 2024. Environmental and Management Impacts of Legacy Nitrogen Remediation Using Bioreactors. Chesapeake Community Research Symposium, Annapolis, Maryland. June 2024.</li> <li>Foster, M., Z.M. Easton, and N. Bell. 2024. Denitrifying bioreactors for legacy nitrate removal from springs in the Chesapeake Bay watershed. American Ecological Engineering Society Annual Meeting. Blacksburg VA, May 2024.</li> <li>Asfaw B. W., D. Fuka, A. Collick, R. White, Z.M. Easton. (2024, July 29). Enhanced identification of spatiotemporal dynamics of critical source areas [Poster Abstract]. ASABE Annual International Meeting, Anaheim, California. https://asabemeetings.org/</li> <li>Asfaw B. W., D. Fuka, A. Collick, R. White, Z.M. Easton. (2024, March 29). Investigating terrain properties for improved identification of soil wetness patterns [Poster Abstract]. CAIA Big Event, Blacksburg, Virginia.</li> <li>Asfaw B. W., D. Fuka, A. Collick, Z.M. Easton. (2024, May 30). Characterizing topographic indices for model parametrization [Poster Abstract]. AEES, Blacksburg, Virginia. <a href="https://www.ecoeng.org/2024-annual-meeting">https://www.ecoeng.org/2024-annual-meeting</a>.</li> <li>Asfaw B. W., D. Fuka, A. Collick,  R. White, Z.M. Easton. (2024, June 11). Characterizing topographic indices for model parametrization. Chesapeake Community Research Symposium, Annapolis, Maryland. https://ccmp2024.chesapeake.org/</li> <li>Easton, Z.M., and K.S. Stephenson. 2023. The nonpoint source challenge-is the watershed responding to management as expected. In USGS Factors Team Group Meeting. Oct. 2023 </li> <li>Easton, Z.M., B. Benham, and K.S. Stepheson. 2023. The nonpoint source challenge. Virginia Soil and Water Conservation Districts-Soil and Water Conservation Society Annual Meeting. Nov. 2023. Extension Presentation.</li> <li>Easton, Z.M., and K.S. Stephenson. 2023. The nonpoint source challenge-is the watershed responding to management as expected. In Delmarva Land and Litter Collaborative Annual Meeting. Aug. 2023. Extension Presentation.</li> </ol> Oklahoma State University <ol> <li>Edwards, J. 2023. Evaluating the Impact of Regenerative Agricultural Practices on Soil Health and Water Quality in Altus, Oklahoma. Oklahoma Governor’s Water Conference and Research Symposium in Norman, OK on November 29-30, 2023.</li> <li>Kaghazchi, Afsaneh. 2023. Evaluation of the hydrologic effects of grazing practices in small watersheds. Oklahoma Governor’s Water Conference and Research Symposium in Norman, OK on November 29-30.</li> <li>Abubakarr Mansaray, Kevin Wagner, Ryan Reuter, Ali Mirchi, and Alayna Gerhardt. Ephemeral Stream Health Assessment in Virtually Fenced Grazinglands. Oklahoma Clean Lakes and Watersheds Association Conference, April 10-11, 2024.</li> <li>Afsaneh Kaghazchi, Ali Mirchi, et al. Assessing the Effectiveness of Rotational Grazing and Riparian Buffers for Reducing Nutrient Loads in Small Watersheds. Oklahoma Clean Lakes and Watersheds Association Conference, April 10-11, 2024.</li> <li>Goodman, L.E., K. Wagner, R. Reuter, B. Murray, A. Michi. 2024. Virtual Fencing for Improved Grazing and Pasture Management. Southern Association of Agricultural Experiment Station Directors, April 17-20, 2024.</li> <li>Reuter, R., K. Wagner, L. Goodman, B. Murray, C. Duchardt, A. Gerhardt, F. La Manna, T. Olsen, and K. Pfaffenberger. 2024. Virtual fencing to control cattle for improved ecosystem services. 79th SWCS International Annual Conference, July 21-24, 2024, Myrtle Beach, SC.</li> <li>Wagner, K. 2024. Managing Grazing For Improved Water Quality. U.S. Roundtable for Sustainable Beef – Water Workgroup (August 5).</li> <li>Wagner, K. 2024. Watershed monitoring to inform watershed scale modeling at Oklahoma State University. S1089 Multi-State Hatch Project Annual Meeting (August 27).</li> </ol> South Dakota State University Conference presentations (* Grad Students) <ol> <li>Adebayo, K.*, and Mehan, S. (2024, October 15). Climate dynamics of the Great Plains of the United States (1924-2023) [Abstract submitted]. In South Dakota Student Water Conference, Brookings, SD, United States.</li> <li>Lamichhane, M.*, Mehan, S., and Mankin, K. (2024, July 28 - August 1). Comparison of hybrid machine learning models with classical machine learning models to predict actual evapotranspiration in semi-arid region. In ASABE Annual International Meeting, Anaheim, CA, United States.</li> <li>Mehan, S., Sharma, A., McDaniel, R., Arnold, J. G., Trooien, T., Sammons, N., and Amegbletor, L. (2024, July 28-31). Evaluating the performance of SWAT+ for simulating drainage water management (DWM) and model parameter transferability spatially in Eastern SD [Abstract ID: 2401216]. In ASABE Annual International Meeting, Anaheim, CA, United States.</li> <li>Sahraei, M., Hentegs, M., McMaine, J., Trooien, T., Mehan, S., Osterloh, K., and Moradi, H. (2024, July 28-31). Management practices and field characteristics that drive nutrient loss in tile drainage in eastern South Dakota [Abstract ID: 2400904]. In ASABE Annual International Meeting, Anaheim, CA, United States</li> <li>Adebayo, K.*, Mehan, S. , and Mankin, K.(2024, July 28-August 1). Analyzing climate change trends in the Great Plains of the United States (1900-2022) [Conference presentation]. In ASABE Annual International Meeting, Anaheim, CA, United States.</li> <li>Lamichhane, M.*, Mehan, S., Mankin, K., and Maitinyazi, M. (2024, April 18). Machine learning models to predict actual evapotranspiration in semi-arid region. In 2024 Western South Dakota Hydrology Conference, Rapid City, SD, United States.</li> <li>Adebayo, K.*, and Mehan, S. (2024, April 18). Comprehensive analysis of drought dynamics in South Dakota using the aridity index and standardized precipitation evapotranspiration index. In 2024 Western South Dakota Hydrology Conference, Rapid City, SD, United States.</li> <li>Lamichhane, M.*, Mehan, S., and Mankin, K. (2024, April 11-12). Actual evapotranspiration prediction based on harmonized Landsat sentinel indices with a few weather variables using machine learning algorithms in semi-arid regions. In 2024 ASABE North Central Regional Meeting, Brookings, SD, United States.</li> <li>Adebayo, K.*, Mehan, S., and Mankin, K. (2024, April 11-12). A comparative analysis of change point detection methods for hydrologic data. In 2024 ASABE North Central Regional Meeting, Brookings, SD, United States.</li> <li>Lamichhane, M.*, Mehan, S., and Maimaitijian, M. (2024, April 4). Soil moisture prediction using multimodal remote sensing data fusion and machine learning algorithms in diverse crop fields. Poster session presented at the 55th Geography Conference, Brookings, SD, United States.</li> <li>Mehan, S. (2024, April 3-5). Effectiveness of SWAT simulating drainage water management using edge-of-field data in OH. In Annual Meeting for the Conservation Drainage Network and NCERA-217: Drainage Design and Management Practices to Improve Water Quality, Westerville, OH, United States.</li> <li>Muehlman, J., Prasad, L., Thompson, A., Mehan, S., Osterholz, W., King, K., Arriaga, F., and Kalcic, M. (2024, April 25-26). Improving the representation of cold season hydrology in SWAT. In WI AWRA 2024 Annual Meeting, Appleton, WI, United States.</li> <li>Lamichhane, M.*, and Mehan, S. (2023, October 10). Enhancing evapotranspiration (ETa) estimation through machine learning driven satellite image fusion. In 2023 South Dakota Student Water Conference, Brookings, SD, United States.</li> <li>Lamichhane, M.*, Mehan, S., and Maimaitijian, M. (2023, November 15). Machine learning models to predict actual evapotranspiration (ETa) based on harmonized Landsat Sentinel (HLS) and climate variables in semi-arid regions. Poster session presented at EROS Center Fall Poster Session, Sioux Falls, SD, United States</li> <li>Mehan, S., and Amatya, D. (2023, December 11-15). Development of an open-source forest fire prediction tool using machine learning algorithms. In American Geophysical Union Fall Meeting, San Francisco, CA, United States.</li> <li>Mehan, S., Mankin, K., Barnard, D., and Green, T. (2023, July 9-12). GeoSpatial hydrometeorological data in the contiguous U.S.: Sources, characteristics, accessibility, and applicability – A review and synthesis. In ASABE Annual International Meeting, Omaha, NE, United States.</li> <li>Mankin, K., Wells, R., Edmunds, D., McMaster, G., Green, T., Kipka, H., Mehan, S., Fox, F., Wagner, L., and Barnard, D. (2023, July 9-12). Crop phenology modeling and calibration using UPGM for corn, sorghum, wheat, sunflower, and dry bean. In ASABE Annual International Meeting, Omaha, NE, United States.</li> </ol> Popular articles  (7 Popular Articles) South Dakota State University Popular/Extension articles <ol> <li>Mehan, S., & Buterbaugh, R. (2024). Educating about flooding and associated activities. South Dakota State University Extension. https://extension.sdstate.edu/educating-about-flooding-and-associated-activities</li> <li>Mehan, S., & Buterbaugh, R. (2024). Understanding Flood Hazards in the United States. South Dakota State University Extension. https://extension.sdstate.edu/understanding-flood-hazards-united-states</li> <li>Mehan, S., & Buterbaugh, R. (2024). Flood Preparedness. South Dakota State University Extension. https://extension.sdstate.edu/flood-preparedness</li> <li>Mehan, S., & Buterbaugh, R. (2024). Global and U.S. Perspectives on Flooding. South Dakota State University Extension https://extension.sdstate.edu/global-and-us-perspectives-flooding</li> <li>Mehan, S., & Buterbaugh, R. (2024). Restoring and Sampling Private Wells in South Dakota. South Dakota State University Extension. https://extension.sdstate.edu/restoring-and-sampling-private-wells-south-dakota</li> <li>Mehan, S., & Buterbaugh, R. (2024). Where do floodwaters go and what do they leave behind? South Dakota State University Extension. https://extension.sdstate.edu/where-do-floodwaters-go-and-what-do-they-leave-behind</li> <li>Klopp, H., Bly, A., Nunes, V.L.N., Mehan. S. (2024). Carbon to Nitrogen Ratio of Healthy Soils. South Dakota State University Extension. https://extension.sdstate.edu/carbon-nitrogen-ratio-healthy-soils</li> </ol>