Brief Summary of Minutes of Annual Meeting

Summary of the 2025 Annual Meeting Minutes:

The 2025 annual meeting took place at the Texas A&M AgriLife Research Center in El Paso, Texas. The first day of the meeting was September 11, 2025, and the annual meeting ended on September 12, 2025.

Day 1

• The meeting started with a welcome by Dr. Beth Racine (El Paso AgriLife Center Director), who shared El Paso’s arid water management under complex regulations, regional crop research, food supply chain challenges, research on human food choices and their human, and sustainability of arid agriculture, military in Fort Bliss, and desert environment in the Far West Texas.
• Later, from the Texas A&M AgriLife Research leadership, Dr. Amir Ibrahim (Associate Director and Chief Scientific Officer) presented AgriLife’s role in advancing Texas research with 600+ faculty and supporting >$319M annual research expenditures across 13 AgriLife Research and Extension stations throughout the state, emphasizing community engagement, industrial partnerships, and socio-economic strengthening.
• Latif updated that the S1089 project had won the SE Research Award earlier, but didn’t win the National Award in 2024, so it was resubmitted.
• Fouad shared updated about the Journal of Environmental Management (JEMA) Special Issue (2025) on “Advances and Gaps in Mitigation and Management Practices in Critical Landscapes,” – originated from Rafa’s 2020–21 idea, is being guest-edited by Soni, Latif, Fouad, and Alesky, includes 26 paper contributions, and is awaiting the final paper before the editorial.
• Sara, who lead the new S1089 proposal writing team with Kevin, Francois, and Sushant, and supported by Latif and Alesky for final cleanup/submission, presented the new S1089 project aiming to drive practical innovation, integrate proposals under a broad watershed management theme, ensure stakeholder-informed impact beyond research, and achieve objectives that include (i) developing next-generation hybrid watershed models, (ii) advancing sensing and high-resolution monitoring, (iii) optimizing best management practice placement for multiple outcomes, and (iv) engaging stakeholders in participatory model development.
• This year, instead of state presentations/reports, the meeting centered on the “Big Idea” theme, chaired by Emine, with each participant allocated 5-minutes with no Q&A. Each participant (in person plus online) presented Big Ideas to the group. These presentations highlighted innovative research directions, including Young’s modeling of ungauged basins using graph theory and AI, Jasmeet’s One Health approach to control ammonia emissions from poultry litter, Francois’s modeling of hydro-biogeochemical “hot moments,” Soni’s focus on green infrastructure with potential AI integration, and Latif’s work on scaling hydrological connectivity using high-resolution data. After a short-break, presentations continued by covering real-time monitoring (Adel), regional nutrient imbalances (Zachary), infrastructure funding (Trisha), data-driven natural infrastructure (Sara), HAWQS modeling (Srini), green stormwater solutions (Fouad), flood monitoring with smart sensors (Emine), chemical transport mechanisms (Rafa), ML-integrated erosion models (Aleksy), transboundary water system dynamics (Santosh), stakeholder-friendly real-time modeling tools (Kevin), and community-driven grazing program with water quality benefits (Sushant).
• The presentation session concluded with QR code voting, and the top ideas were awarded to (1) Francois Birgand (NCSU), (2) Fouad Jaber (Texas A&M), and (3) a joint third place to Latif Kalin (Auburn University) and Kevin Wagner (Oklahoma State University).
• The 2025–2026 Executive Board was elected with Latif as Past Chair, Emine as President, Sushant as Vice Chair, and Santosh as Secretary. Sushant shared the secretary’s role and responsibilities that include compiling reports, facilitating meetings, maintaining participant records, coordinating impact reports, collecting photos, and managing awards.
• The group selected Knoxville, TN, as the 2026 meeting venue (September 3–4), citing opportunities for field showcases, such as rain gardens, constructed wetlands, and the NEON site. Although the group agreed that in-person attendance should be required for collaboration, remote participation remains acceptable for reports.
• The first day of the meeting concluded with a field visit to the Kay Bailey Hutchison Desalination Plant in El Paso, Texas, which is the World’s largest inland desalination plant.

Day 2

• The second day meeting began with a discussion on advancing multi-state collaboration under the new S1089 proposal, followed by rotating group activities that addressed next-generation hybrid watershed models, high-resolution monitoring, BMP optimization, and stakeholder engagement. During discussions, participants shared insights on improving model realism, integrating AI and citizen science, addressing uncertainty and data reliability, and linking experiments with models.
• During the multi-state collaboration activity, Group 1 discussed the Systematic Evaluation of Models, Data Trust & Uncertainty, and Stakeholder Engagement and BMPs. Group 2 discussed Missing Processes, Hot Moments/Hot Spots, BMP Placement, and Citizen Science Integration.
• The action items focused on several key areas: agreeing on the need for a survey with emphasis on encouraging in-person attendance; conducting systematic reviews and evaluations of process-based watershed models, including identifying missing elements and assessing data repository needs; developing a framework for hydro-biogeochemical “hot spots” led by Francois, distributing a survey to determine future meeting formats; compiling and sharing meeting chats; sharing meeting photos via Google Drive; and preparing the final S1089 impact report.
• The winners of the first day ‘Big Idea’ competition were awarded prizes from Latif and Rafa (past-chairs) that were offered by the host, Santosh.
• The group planned to prepare a synthetic editorial paper for the ASABE Journal Special Collections, circulating ideas broadly to involve both in-person and virtual members in collaborations, and seeking budget and collaborative proposal opportunities to integrate data monitoring and modeling. The group will consider organizing a workshop with USDA NIFA technical advisers and establish a GitHub repository, led by Sushant, to serve as a collaborative platform for sharing data, articles, and presentations, reflecting the strong momentum and energy of the group for future proposal writing and collaboration.
• Finally, the 2025 annual meeting concluded with a mini-symposium, during which most in-person participants presented their posters from the 2025 scientific/technical conferences.

Elected Officers (2025-2026):

• Chair : Emine Fidan             (University of Tennessee)
• Vice Chair : Sushant Mehan         (South Dakota State University)
• Secretary : Santosh Palmate       (Texas A&M AgriLife, TAMU)

Past Chairs:

• Soni Pradhanang (2020-2021)
• Rafa Munoz-Carpena (2021-2022)
• Fouad Jaber (2022-2023)
• Aleksey Sheshukov (2023-2024)
• Latif Kalin (2024-2025)

Accomplishments:

The main focus of this project is to improve the ability to better understand and predict the 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 the overall goals of the S1089 Committee, here are the accomplishments and impacts reported by each state:

AL – Auburn University

• Accomplishments: Research teams at Auburn University advanced agricultural and environmental management in Alabama by improving the understanding of nutrient movement through soils. The team evaluated the impact of biochar, poultry litter, and wastewater on phosphorus, nitrogen, and metal transport, and refined watershed and wetland models to better predict water quality and pesticide dynamics. Climate and hydrology studies enhanced soil moisture forecasting and clarified how land use and climate feedback shape regional environmental change.
• Impact: This research promotes sustainable management of Alabama’s land and water resources. Results guide farmers and land managers in adopting practices that reduce nutrient and metal runoff while maintaining productivity. Upgraded watershed models and climate forecasts enable agencies to protect water quality and prepare for extreme weather, thereby supporting long-term environmental health and resilience.

FL – University of Florida

• Accomplishments: University of Florida researchers advanced studies on sustainable intensification, pesticide transport, and hydrologic modeling by combining mechanistic and artificial intelligence approaches. The team developed new models to assess pesticide risk, pollutant degradation, and soil–runoff dynamics. The team also launched the online Stormwater Qualified Inspection Training (SQuInT) program and developed an auditing tool to identify barriers to the use of green infrastructure. Additional projects addressed coastal groundwater hazards, community resilience through green stormwater infrastructure, and agrivoltaics for specialty crops.
• Impacts: These efforts enhance water quality management, climate resilience, and sustainable land use across agricultural and urban systems. The research supports improved regulatory compliance, promotes adoption of green infrastructure, and strengthens community capacity to adapt to environmental change in Florida.

IA – Iowa State University

• Accomplishments: An Iowa State University researcher developed experiments, monitoring systems, and models to study the effects of conservation and stream restoration practices on nutrient and sediment movement. The team used high-frequency sensors and stream metabolism data to assess restoration performance, including the benefits of two-stage ditches for floodplain connection and nutrient retention. This work improved predictive tools and methods for prioritizing restoration and conservation placement.
• Impacts: This research informs effective watershed and restoration planning, supporting cleaner water, reduced flooding, and sustained agricultural productivity. It helps stakeholders make informed decisions on conservation implementation while enhancing long-term watershed stability and ecosystem resilience.

KS – Kansas State University

• Accomplishments: The KSU team advanced soil and water conservation efforts by evaluating management practices across both rural and urban settings, utilizing modeling and field data. Additional projects with the USGS, Iowa State University, and the Kansas Water Office have improved tools for monitoring algal blooms, mapping ephemeral gullies, and assessing BMP effectiveness across various regions.
• Impact: These initiatives enhance water quality, reduce sediment loss, and create cost-effective conservation solutions for communities. The team strengthens local and regional partnerships while supporting sustainable watershed management across Kansas. For instance, the collaboration with the City of Wichita resulted in an off-site BMP program that saved $6.28 million and reduced 2,672 tons of sediment annually. A new partnership with the City of Manhattan began to design a similar program focused on local water quality issues.

KY – University of Kentucky

• Accomplishments: Research advanced understanding of contaminant transport in tile-drained and karst landscapes through collaborations with USDA research units in Ohio and Indiana. Published studies on sediment leachate, phosphate isotopes, and sediment organic matter support ongoing modeling and field data efforts. Deep learning models using the USDA monitoring network successfully predicted tile drainage hydrology and water quality. Additional work explored sediment and organic matter transport in floodplains, with manuscripts under review and new funding secured for studies on harmful algal blooms in the Ohio River.
• Impacts: These studies improve the prediction and management of nutrient and sediment movement in agricultural and karst watersheds. The modeling tools and research findings guide more effective conservation practices and enhance understanding of water quality risks such as harmful algal blooms.

MD - University of Maryland College Park

• Accomplishments: Researchers developed Artificial Neural Network models using satellite-based data to accurately forecast groundwater table fluctuations in Maryland, achieving predictions with an accuracy of within 5 cm over 12 months. A climate vulnerability study analyzed historical and projected precipitation trends using CMIP6 models, revealing an increase in the frequency of extreme rainfall events under high-emission scenarios. Another project assessed the economic feasibility of reclaimed water for agricultural irrigation in two Maryland watersheds, identifying areas where its use can conserve significant freshwater quantities under dry conditions.
• Impacts: These projects enhance predictive capabilities for groundwater and climate-related risks, supporting more informed water resource and agricultural management strategies. The findings inform adaptation planning for extreme precipitation events and promote the sustainable use of reclaimed water to conserve freshwater resources across vulnerable regions.

NC – North Carolina State University

• Accomplishments: Research activities focused on improving water quality monitoring and modeling techniques. Field spectrometry, image-based monitoring, and multi-parameter modeling were tested to assess stormwater and stream restoration impacts. Innovative methods, including low-cost trail cameras for water stage monitoring and data-driven models to nowcast fecal bacteria concentrations using basic water quality sensors, demonstrated strong performance. Additional efforts advanced nutrient source apportionment through SWAT modeling and evaluated national nutrient inventories for phosphorus assessment.
• Impacts: These advancements offer affordable and practical tools for enhancing real-time water quality monitoring and management. The findings support more effective restoration evaluation, nutrient management, and protection of aquatic environments in both agricultural and coastal systems.

OK – Oklahoma State University

• Accomplishments: The Oklahoma Water Resources Center advanced watershed research to evaluate conservation practices through monitoring runoff, nutrients, and soil moisture in cotton systems under regenerative agriculture. Studies conducted at the Cross Timbers Experimental Range examined the effects of grazing, wildlife, and prescribed burning on water quality, aided by valuable pre- and post-wildfire data. Additional work on virtual fencing demonstrated its success in reducing cattle presence in riparian zones without added stress. These projects collectively trained five graduate students and produced multiple publications.
• Impacts: This research enhances sustainable land and water management by improving the understanding of how agricultural and grazing practices impact watershed health. The results guide implementation of conservation methods that enhance water quality, support producer efficiency, and protect natural ecosystems across Oklahoma.

SD – South Dakota State University

• Accomplishments: Research advanced understanding of soil–water interactions and hydrologic modeling under climate extremes. Studies integrated remote sensing and machine learning to improve predictions of soil moisture and evapotranspiration, while new models enhanced the simulation of soil heat, moisture, and groundwater dynamics. Field-scale analyses revealed a link between topography and crop yield variation. Outreach activities engaged producers, students, and agencies through workshops, conferences, and educational programs, strengthening partnerships and technology transfer across the region.
• Impacts: These efforts enhance the accuracy of predicting water dynamics and agricultural performance under changing climate conditions. The work supports more resilient water and crop management strategies while fostering collaboration between researchers, producers, and policymakers to enhance sustainable agriculture in South Dakota.

TN – University of Tennessee

• Accomplishments: Research advanced S1089 objectives by developing monitoring and modeling tools to guide BMP implementation and assess long-term effectiveness using soil health metrics. A weighted soil health index proved more reliable for tracking BMP performance. The RUSLE2/Ephgee model was refined to integrate hillslope and gully erosion, while a Bayesian model of Hurricane Florence floodwaters identified rainfall and nearby operations as key sources of contamination. High-resolution LiDAR was also tested successfully for detecting concentrated erosion zones.
• Impacts: These efforts improve understanding of how land management practices influence erosion, soil health, and water quality. The findings strengthen predictive modeling, enhance BMP evaluation methods, and support more targeted conservation and watershed management strategies.

TX – Texas A&M AgriLife

• Accomplishments: Over the past year, the Texas research team has made significant advancements in arid hydrology, water quality, and digital agriculture. The team developed advanced modeling and AI tools, such as XGBest, for nutrient and sediment prediction, and contributed to international hydrologic datasets and decision support systems, including TXSELECT. Field and watershed projects included the completion of the Rowlett Creek Watershed Protection Plan and the implementation of rain gardens for urban runoff mitigation in Arlington, as well as community gardens. Green stormwater infrastructure demonstration sites were built at Houston Community College, featuring rain gardens and rainwater harvesting systems. Ongoing projects focus on transportation-related stormwater management in the Trinity River basin to reduce urban flooding risks.
• Impacts: These efforts enhance watershed health, improve stormwater management, and promote agricultural sustainability through innovative modeling, monitoring, and stakeholder-driven planning. The research enhances climate resilience, supports local water quality restoration, and informs infrastructure design for sustainable urban growth across Texas.

RI – University of Rhode Island

• Accomplishments: Research at the University of Rhode Island advanced work on nature-based climate solutions, groundwater methane dynamics, and urban stormwater treatment. Projects with local municipalities focused on equitable climate adaptation, mapping the saltwater–freshwater interface, and assessing innovative biochar and Jellyfish filtration technologies. Ongoing efforts include groundwater and wetland assessments, as well as hydrogeologic modeling, to support statewide water planning and resilience.
• Impacts: These projects strengthen Rhode Island’s capacity for climate resilience, sustainable water management, and environmental equity. The results guide local and state agencies in adopting effective nature-based infrastructure and inform long-term strategies for flood prevention, drought response, and groundwater protection.

VA – Virginia Tech

• Accomplishments: Virginia Tech advanced watershed research in stormwater management, modeling, and groundwater quality. Studies monitored urban runoff to calibrate hydrologic models and assess BMP performance on stream stability. Projects also quantified nitrogen removal in groundwater bioreactors and integrated real-time IoT sensing and robotics for nutrient and manure management.
• Impacts: This research supports improved stormwater and nutrient management, enhancing water quality and ecosystem resilience. The findings inform cost-effective nitrogen reduction strategies and drive innovation in agricultural and urban watershed management across Virginia and beyond.

1. Publications (128 Publications)

AL – Auburn University

1. Haas^*, H., Kalin, D. Tian, J. Lehrter (2025), “Dynamic land-use/cover improves simulations of long-term watershed-scale streamflow and water quality trends”, Journal of Hydrology. Vol 661. https://doi.org/10.1016/j.jhydrol.2025.133744.
2. Yan^*, H., Kalin, H. Peng, D. Allasia, Y. Yao, Z. Bian, J. Lamba (2025), “Agricultural nitrogen loss and downstream effects in the transboundary La Plata basin driven by soybean rotations”, Journal of Environmental Management. Vol 380. https://doi.org/10.1016/j.jenvman.2025.125159.
3. Lee^*, D., R. Karki^*, Kalin, P. Srivastava, X. Zhang (2025), “Management Strategies for Dissolved Organic Carbon Reduction from Forested Watersheds using the SWAT-C model”, Agriculture, Ecosystems and Environment. Doi: 10.1007/s00267-025-02128-y.
4. Bradley, E., B.G. Lockaby, S. Madere, S.A. Bolds, Kalin, S. Ditchkoff, V. Brown (2025), “Stream Pathogenic Bacteria Levels Rebound Post-Population Control of Invasive Wild Pigs”, Journal of Environmental Quality. https://doi.org/10.1002/jeq2.70004. 
5. Karki^*, R., Kalin, P. Srivastava, K. Rowles, M. Masters, W. Bartels (2025), “Stakeholder-driven assessment of watershed management strategies for agriculture and ecological sustainability: A case study in the lower Apalachicola-Chattahoochee-Flint (ACF) River Basin, Journal of Environmental Management. Vol 373. https://doi.org/10.1016/j.jenvman.2024.123628.
6. Kaur, P., Lamba, T.R. Way, K. Balkcom, and D. Watts. 2025. Effect of Image Resolution and Soil Core Diameter on Soil Pore Characteristics Quantified using X-ray Computed Tomography. Journal of Soils and Sediments. https://doi.org/10.1007/s11368-025-04105-8. 
7. Brar, G, K. Malhotra*, R. Kumar, Lamba, T. Way, R. Prasad, S. Adhikari. 2025. Elucidating the Impact of Broiler Litter and Pinewood Biochar Application Method on Metal Retention and Leaching in Undisturbed Soil Columns Using Simulated Rainfall. Journal of Hazardous Materials Advances. https://doi.org/10.1016/j.hazadv.2025.100860.
8. Malhotra, K., Lamba, T. R. Way, R. Prasad, and P. Srivastava. 2025. Effect of Poultry Litter Application and Preferential Flow on Metal Loss in Pastures. Journal of Environmental Management (in press). https://doi.org/10.1016/j.jenvman.2025.126415.
9. Kumar, R, A. Rahman*, Lamba, S. Adhikari, and H.A. Torbert. 2025. Harnessing Biochar for Nitrate Removal from Contaminated Soil and Water Environments: Economic Implications, Practical Feasibility, and Future Perspectives. Biochar (in press). https://doi.org/10.1007/s42773-025-00486-8.
10. Brar, G, K. Malhotra, R. Kumar, Lamba, T. Way, R. Prasad, S. Adhikari. 2025. Investigating the Impact of Broiler Litter Application Method and Biochar on Phosphorus Leaching. Water, Air, & Soil Pollution 236,558 (2025). https://doi.org/10.1007/s11270-025-08177-7. 
11. Kumar, R, Lamba, S. Adhikari, N. Kasera, and H. A. Torbert. 2025. Co-transport and Retention of Arsenic and Pine Wood Biochar in Saturated Porous Media: Fate and interaction mechanisms under solution chemistry and practical feasibility.  ACS ES&T Water. https://doi.org/10.1021/acsestwater.5c00232.
12. Yan, H, L. Kalin, H. Peng, D. Gustavo Allasia Piccilli, Y. Yao, Z. Bian, and Lamba. 2025. Agricultural Nitrogen Loss and Downstream Effects in the Transboundary La Plata Basin Driven by Soybean Rotations. Journal of Environmental Management 380 (2025): 125159. https://doi.org/10.1016/j.jenvman.2025.125159. 
13. Kumar, R., P. K. Rose, P. K. Sharma, Lamba, M. Kumar and P. Bhattacharya. 2025. Micro(nano)plastic and Per- and Polyfluoroalkyl Substances in Soil/Sediment-Water Ecosystems: Sources, Transport, Interactions, and Challenges. Current Opinion in Chemical Engineering. https://doi.org/10.1016/j.coche.2025.101125. 
14. Malhotra, K., Lamba, T. R. Way, C. Williams, K. G. Karthikeyan, R. Prasad, P. Srivastava, and J. Zheng. 2025. Investigating the Effect of Animal Manure on Colloidal Facilitated Phosphorus Transport. Geoderma. https://doi.org/10.1016/j.geoderma.2025.117203. 
15. Sandhu, V, Lamba, P. Kaur, K. Malhotra, T. R. Way, K.S. Balkcom and R. Prasad. 2025. Effect of Cover Crops on Phosphorus and Trace Metal Leaching in Agricultural Soils. Agricultural Water Management. https://doi.org/10.1016/j.agwat.2025.109343. 
16. Kumar, R, Lamba, S. Adhikari, N. Kasera, and H. A. Torbert. 2025. Influence of Iron-Modified Biochar on Phosphate Transport and Deposition in Saturated Porous Media under Varying pH, Ionic Strength, and Biochar Dosage. Chemosphere 370: 143932. https://doi.org/10.1016/j.chemosphere.2024.143932. 
17. Eva, E., L. Marzen, Lamba, S.M. Ahsanullah, and C. Mitra. 2024. Projection of Land Use and Land Cover Changes Based on Land Change Modeler and Integrating both Land Use and Land Cover and Climate Change on the Hydrological Response of Big Creek Lake Watershed, South Alabama. Journal of Environmental Management 370: 122923. https://doi.org/10.1016/j.jenvman.2024.122923.
18. Kennedy, D., Dagon, K., Lawrence, D. M., Fisher, R. A., Sanderson, B. M., Collier, N., …Kavoo, T., Kumar, S., … & Wood, A. W. (2025). One‐at‐a‐time parameter perturbation ensemble of the Community Land Model, version 5.1. Journal of Advances in Modeling Earth Systems, 17(8), e2024MS004715.
19. Duan, Y., Kumar, S., Maruf, M. et al.Enhancing sub-seasonal soil moisture forecasts through land initialization. npj Clim Atmos Sci 8, 100 (2025). https://doi.org/10.1038/s41612-025-00987-0
20. Best, M. J., Lock, A. P., Balsamo, G., Bazile, E., Beau, I., Cuxart, J., … & Zheng, W. (2025). Rolling DICE to advance knowledge of land–atmosphere interactions. Quarterly Journal of the Royal Meteorological Society, e4944.
21. Haas, H., Kalin, L., Sun, G., & Kumar, S. (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, 640, 131739.
22. 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
23. 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. https://doi.org/10.1088/2752-5295/ad3a0c

FL – University of Florida

1. Ali, A., Campbell, D.N., Pilco, F., Ballou, J., Bean, E. Z., Chase, C. A., and Athearn, K. 2025. Mineral amendments benefit soil moisture but not nutrient cycling or crop productivity in a Florida organic vegetable system established on a sandy soil. Agr. 15 473-491. DOI: 10.1007/s13165-025-00510-y . 
2. Bai, X., S. J. Smidt, Y. Fan, T. Brophy, Her, N. Manirakiza, Y. Li, J. Bhadha (2024), Farming shallow soils: Impacts of soil depth on crop growth in Everglades Agricultural Area of Florida, USA, Field Crops Research, 316, 109523. https://doi.org/10.1016/j.fcr.2024.109523. 
3. Bai, X., S. J. Smidt, Her, Y. Li, D. Kim, N. Manirakiza(g), L. Duriancik, and J. H. Bhadha (2025), Sensitivity of oxic condition to irrigation practice in a rotational flooded rice (Oryza sativa) cropping system, Journal of Environmental Quality, In Press.
4. Bridgemohan, R. Deitch, M., Harmon, E., Whiles, M., Wilson, P., Bean, E., Bridgemohan, P., Bisesi, J., Nichola, J., Redhead, A., and Bachoon, D. 2024. Spatiotemporal assessment of pathogenic Leptospria in subtropical coastal watersheds. Water Health. 22(5): 923-938. DOI:10.2166/wh.2024.038
5. Canatan*, M., R. Muñoz-Carpena, Z. Boz. 2025. Continuous surface temperature monitoring of refrigerated fresh produce through visible and thermal IR sensor fusion. Postharvest Biology and Technology222:113354. doi: 10.1016/j.postharvbio.2024.113354.
6. Carmona-Cabrero*, A., Muñoz-Carpena, R. Muneepeerakul, W.S. Oh*. 2024. Decomposing variance for stochastic models: application to a proof-of-concept human migration agent-based model.Journal of Artificial Societies and Social Simulation (JASSS) 27(1) 16, doi:10.18564/jasss.5174
7. Hathaway, J., Bean, E., Bernagros, J., Christian, D., Davani, H., Ebrahimian, A., Fairbaugh, C., Gulliver, J., McPhillips, L., Palinog, G., Strecker, E., Tirpak, A., van Duin, B., Weinstein, N. and Winston, R. 2024. A synthesis of climate change impacts on stormwater control measures in the U.S.: Designing for resiliency and future challenges.  Sustain. Water Buil. 10(2): 1-9. DOI: 10.1061/JSWBAY/SWENG-533. 
8. Huffaker, R. R. Muñoz-Carpena and K.W. Migliaccio. 2024. Sensor records can be used to forecast complex soil moisture dynamics with symbiosis of empirical nonlinear dynamics and echo state neural network AI.  Electron. Agric.222:109031. doi:10.1016/j.compag.2024.109031.
9. Huffaker, R., M. Campo-Bescós, E. Luquin, J. Casalí, and Muñoz-Carpena. 2024. Hydrological records can be used to reconstruct the resilience of watersheds to climatic extremes. Nature Communications Earth & Environment5, 19. doi:10.1038/s43247-023-01181-x.
10. Iverson, G., Humphrey, C., O’Driscoll, M., Sanderford, C., and Bean, E. 2024. Quantifying nitrogen treatment by an in-stream bioreactor in a watershed served by septic systems. Process. 11(22). DOI:10.1007/s40710-024-00701-x
11. Kim, D. Her, and T. Jang (2025), Optimizing rice paddy conservation practices for sustainable agricultural systems in changing climate, Agricultural Systems, 230, 104486. https://doi.org/10.1016/j.agsy.2025.104486. 
12. Kim, D., T. Wade, Z. Brym, L. Ogisma, R. Bhattarai, X. Bai, R. Bhattari, J. Bhadha, and Her (2025), Assessing the agricultural, environmental, and economic effects of crop diversity management: A comprehensive review on crop rotation and cover crop practices, Journal of Environmental Management, 387, 125833. https://doi.org/10.1016/j.jenvman.2025.125833. 
13. Kim, D., Her, L. Cheng, H. Park, and T. Jang (2025), Improving wheat yield and water use efficiency through soil water-guided furrow irrigation and hydraulic simulation, Agricultural Water Management. 318, 109746. https://doi.org/10.1016/j.agwat.2025.109746. 
14. Lee, J., S. Lee, Y. Jeong, B. Seo, D. Kim, Y. Seo, Her, and W. Choi (2024), Enhancing flood wave modelling of reservoir failure: A comparative study of structure-from-motion based 2D and 3D Methodologies, Natural Hazards, 120, 11611-11640. https://doi.org/10.1007/s11069-024-06634-w. 
15. Li, J., Abukhalaf, A., Bean, E., Brisotto, C., Clark, M., Von Meding, J. K., and Otalora, A., and Barry, S. 2025. Community perception and stewardship of public coastal infrastructure in Cedar Key, Florida. Mar. Sci.. 12. DOI:10.3389/fmars.2025.1639887
16. Li, S., Y. Liu, A. H. Nguyen, Z. Wu, M. Z. Al-Farsi, T. Choi, L. Zhou, Her, F. Li, D. Ren, and X. X. Romeiko (2025), A framework for creating sustainable rainwater harvesting and reuse strategies for urban landscape irrigation in a changing climate, Journal of Environmental Management, 392, 126852. https://doi.org/10.1016/j.jenvman.2025.126852.
17. Li, S., Y. Liu, and Her (2024), Enhancing the SWAT model for creating efficient rainwater harvesting and reuse strategies to improve water resources management, Journal of Environmental Management, 798, 149336. https://doi.org/10.1016/j.scitotenv.2021.149336.
18. Liguang, C., H. Park, D. Kim, Her, and T. Jang (2025), Evaluating crop characteristics and water use efficiency of growth stages of winter wheat (Triticum aestivum L.) under various irrigation conditions, Journal of the Korean Society of Agricultural Engineers. 67(3), 17-28. https://doi.org/10.5389/KSAE.2025.67.3.017. (In Korean)
19. Loizzo, J.L. S. Hundemer, G. Spandau, S. Smidt, A. Akers, J. Bhadha, and Her (2025), An exploration of early career agricultural and natural resource scientists’ perceptions of social responsibility, International Journal of Science Education, Part B, 1-18. https://doi.org/10.1080/21548455.2024.2335673. 
20. Lusk, M. G., Bean, E. Z., Iannone, B., and Reisinger, AJ. 2025. Stormwater ponds: Unaccounted environmental challenges of a widely-adopted best management practice in urban landscapes. J. Env. Man. 374. DOI:10.1016/j.jenvman.2025.124170
21. Park, Y.S. and Her (2025), Regression-based estimation of pollutant loads from direct runoff and baseflow, Journal of Korean Society on Water Environment. 41(3), pp. 151-162. https://doi.org/10.15681/KSWE.2025.41.3.151. (In Korean)
22. Reisinger, AJ, Bean, E., Clark, M., Levine, AJ, and Wilson, PC. 2025. Fertilizer management approaches influence nutrient leaching from residential landscapes. Env. Qual. 54(1), 289-302. DOI:10.1002/jeq2.20657
23. Serrano, T., Z. Brym, L. Monserrate, Her, J. Standord, and Y.Y. Upadhyaya, W. Griffith, H. Shllenbarger, H. Singh, H. Sharma. (2025), Nitrogen fertilizer effects on hemp biomass production detected by drone-based spectral imaging, HortScience, 60(3), 353-361. https://doi.org/10.21273/HORTSCI18264-24.
24. Song, J., Her, Y. S. Park, K. Yoon, and H. Kim (2024), Investigating the applicability and assumptions of the regression relationship between flow discharge and nitrogen concentrations for load estimation, Heliyon, 10(1), e23603. https://doi.org/10.1016/j.heliyon.2023.e23603.
25. Uthman*, Q.O., R. Muñoz-Carpena, A. Ritter and D.M. Kadyampakeni. 2025. Differential water and imidacloprid transport under unsaturated Florida citrus field conditions. Vadose Zone J.doi: 10.1002/vzj2.70043.
26. Yang*, Y., Wan, Y., Chen, J., Chen, H., Li, Y., Muñoz-Carpena, R., Zheng, Y., Huang, J., Zhang, Y., Gao, B. 2025. Ball-milled spent coffee ground biochar effectively removes caffeine from water. Water17, x. doi: 10.3390/w17060881.

IA – Iowa State University

1. Frankenberger, J., K. McMillan, M.R. Williams, K. Mazer, J. Ross, B. Sohngen. 2024. Drainage water management: A review of nutrient load reductions and cost effectiveness. Journal of the ASABE, Agricultural Conservation Practice Effectiveness Collection Review. https://doi.org/10.13031/ja.15549. Awarded 2024 Superior Paper award.
2. Hardaway, K.C., M. Choi, R. Nateghi, K. McMillan, Z Ma, B. Hardiman. 2024. Vegetation reduces cooling demand in low-income neighborhoods on hot days in Chicago. Environmental Research Communications. 6(7), https://doi.org/10.1088/2515-7620/ad5e3c
3. Rudko, N., 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.
4. Oelschlager P.T., Thompson A.W., Floress K., Awashra I., Barbarash D., Battista J., McMillan S. Modeling nonlinear edge-of-field buffers to enhance sediment trapping efficiency: Application of AgBufferBuilder in the Saginaw Bay basin. Journal of Soil and Water Conservation. 80(1):53-75. https://doi.org/10.1080/00224561.2024.2433922

KS – Kansas State University

1. Cheng, M., Sheshukov, A.Y., Wang, P., Tartakovsky, D.M., 2025. Data-aware forecast of harmful algal blooms with model error. Water Research 286, 124201. https://doi.org/10.1016/j.watres.2025.124201
2. Conoscenti, C., Azzara, G., Sheshukov, A.Y., 2025. Pixel-scale gully erosion susceptibility: Predictive modeling with R using gully inventory consistent with terrain variables. CATENA 257, 109091. https://doi.org/10.1016/j.catena.2025.109091
3. Soni, M., Sheshukov, A.Y., Aguilar, J., 2025. The critical role of temperature in determining optimal planting schedule for cotton: A review. Agricultural and Forest Meteorology 373, 110741. https://doi.org/10.1016/j.agrformet.2025.110741
4. Panthi, J., Moore, T., Sheshukov, A.Y., 2025. Status of Harmful Algal Blooms in Kansas Lakes and Reservoirs (No. MF3683). K-State Research and Extension, Kansas State University, Manhattan, KS. https://bookstore.ksre.ksu.edu/item/status-of-harmful-algal-blooms-in-kansas-lakes-and-reservoirs_MF3683
5. Nelson, N.O., Raugewitz, S., Kluitenberg, G.J., Sheshukov, A., Bigham, K., Hettiarachchi, G.M., Tomlinson, P.J., Presley, D.R., Roozeboom, K.L., 2025. Conservation Under Pressure: Evaluating Cover Crop Effectiveness in a Changing Climate. CANVAS 2025, ASA-CSSA-SSSA.
6. Hackenberg, S., Sheshukov, A.Y., 2024. Development of Land Use Mapping Framework at a Sub-Field Scale Using a Combination of Georeferenced Raster Layers and County-based Census Data for Kansas. Governor’s conference of the future of water in Kansas. Manhattan, KS 

KY – University of Kentucky

1. Mumbi, R., Williams, M. R., Ford, W. I., Camberato, J. J., & Penn, C. J. 2025. Identifying dissolved reactive phosphorus sources in agricultural runoff and leachate using phosphate oxygen isotopes. Journal of Contaminant Hydrology.
2. Pandit, A., Hogan, S., Mahoney, D. T., Ford, W. I., Fox, J. F., Wellen, C., & Husic, A. 2025. Establishing performance criteria for evaluating watershed-scale sediment and nutrient models at fine temporal scales. Water Research, 123156.
3. Riddle, B., Fox, J., Ford, B., Husic, A., & Pollock, E. 2025. Fourteen‐Year Fluvial Sediment Record Shows Non‐Conservativeness of Organic Tracers: Recommendations for Sediment Fingerprinting. Hydrological Processes, 39(1), e70054.
4. Ford, W., Williams, M., Mumbi, R. 2024. Subsurface sediment transport in the shallow vadose zone of fine-textured soils with heterogenous preferential flows. Hydrological Processes. 38(11):e15327. https://doi.org/10.1002/hyp.15327

MD - University of Maryland College Park

1. Mirzaei, M. and A. Shirmohammadi. 2024. Utilizing Data-Driven Approaches to Forecast Fluctuations in Groundwater Table. Water 2024, 16, 1500. https://doi.org/10.3390/w16111500.
2. Mirzaei, M., A. Shirmohammadi, A. Ruiz-Barradas, L. J. Olson, M. Negahban-Azar. 2025. Climate change effects on the spatial and temporal distribution of extreme precipitation in the Mid-Atlantic region. Urban Climate, Vol. 61(2025) 102382. pp1-17.
3. 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, https://doi.org/10.2166/ws.2024.137.
4. L. Gray, A. Rahman, M. Neghaban-Azar, and A. Shirmohammadi. 2025. Watershed-scale investigation of the net-benefit of irrigation with reclaimed water. J. of Agricultural Water Management (Under Review).

NC – North Carolina State University

1. Sauers, N., Rok, A., and Birgand, F. (2025). Evidence of nitrate removal “hot moments” during flow and nitrate pulses in a denitrification “hot spot.” Journal of the ASABE, 68(2). https://doi.org/10.13031/ja.15988.
2. Moin, S. F. Birgand, W.F. Hunt. 2025. Using Optic Sensors For Near-continuous Water Quality Monitoring Of Stormwater Runoff. J. ASABE. Accepted.
3. Nooshzadi Motlagh, M., Chapman, K., Young, S., F. Birgand. Computer vision-based measurement of stormwater discharge: proof of concept. Submitted to Journal of Hydrology.
4. Julia M. Harrison, Christopher L. Osburn, Elizabeth S. Darrow, Elise Morrison, Angela Harris, Natalie G. Nelson, Developing Predictive Models Using Sonde Data to Estimate Fecal Contamination in Estuarine Waters, ACS ES&T Water, under review
5. Natalie G. Nelson, Marcelo Ardón, Tal Ben-Horin, Eric Herbst, Whitney Knollenberg, María Menchú-Maldonado, Christopher L. Osburn (2025), See Salt: Recommendations for Engaging Oyster Growers in Community-Based Coastal Monitoring Programs, Environmental Monitoring and Assessment, in press
6. Christopher Oates, Khara Grieger, Ryan Emanuel, Natalie G. Nelson (2025), Surface waters in socially vulnerable areas are disproportionately under-monitored for nutrients in the U.S. South Atlantic Gulf Region, Nature Water, 3: 831-840
7. Christopher Oates, Hector Fajardo, Khara Grieger, Daniel R. Obenour, Rebecca L. Muenich, Natalie G. Nelson (2024), Effective nutrient management of surface waters in the U.S. requires expanded water quality monitoring in agriculturally-intensive areas, ACS Environmental Au, 5(1): 1-11
8. Qicheng Tang, Owen W. Duckworth, Daniel R. Obenour, Stephanie B. Kulesza, Nathan A. Slaton, Andrew H. Whitaker, Natalie G. Nelson (2024), Relationship between soil-test-phosphorus and agricultural surplus phosphorus, Journal of Environmental Quality, 53(6): 1127-1139
9. Julia Harrison, Christopher Osburn, Angela Harris, Natalie G. Nelson (2024), Tryptophan-like fluorescence for monitoring fecal contamination in a marsh-dominated estuary, ES&T Water, 4(12): 5633-5644

OK – Oklahoma State University

1. Edwards, J., Wagner, L. Gregory, S. Stoodley, T. Ochsner. 2025. Employing Cover Crops and No-Till in Southern Great Plains Cotton Production to Manage Runoff Water Quantity and Quality. Water 2025, 17, 2283. https://doi.org/10.3390/w17152283. 
2. Akbar, Muhammad Umar, Ali Mirchi, Arfan Arshad, Sara Alian, Mukesh Mehata, Saleh Taghvaeian, Kasra Khodkar, Jacob Kettner, Sumon Datta, Kevin Wagner. 2025. Multi-model Ensemble Mapping of Irrigated Areas Using Remote Sensing, Machine Learning, and Ground Truth Data. Agricultural Water Management Volume 312, 1 May 2025, 109416. https://doi.org/10.1016/j.agwat.2025.109416
3. Jeffus, J., Wagner, L. Goodman, T. Parker, B. Wilson, A. Foote, R. Reuter. 2025. Virtual fences are not more stressful than conventional electric fences in rotationally stocked beef cattle. Rangelands Volume 47, Issue 1, February 2025, Pages 61-71. https://doi.org/10.1016/j.rala.2024.11.002. 
4. Murray, B., Wagner, R. Reuter, L. Goodman. 2025. Use of virtual fencing to implement critical conservation practices. Rangelands Volume 47, Issue 1, February 2025, Pages 41-49. https://doi.org/10.1016/j.rala.2024.08.003.

SD – South Dakota State University

1. Lamichhane, M., Mehan, S., & Mankin, K. R. (2025a). Soil Moisture Prediction Using Remote Sensing and Machine Learning Algorithms: A Review on Progress, Challenges, and Opportunities. Remote Sensing, 17(14), 2397. https://doi.org/10.3390/rs17142397
2. Lamichhane, M., Mehan, S., & Mankin, K. R. (2025b). Surface Soil Moisture Prediction Using Multimodal Remote Sensing Data Fusion and Machine Learning Algorithms in a Semi-Arid Agricultural Region. Science of Remote Sensing, 100255. https://doi.org/10.1016/j.srs.2025.100255
3. Shrestha, E., Poudyal, S., Ghimire, A., Maharjan, S., Lamichhane, M., & Mehan, S. (2025). Evaluating Empirical and Machine Learning Approaches for Reference Evapotranspiration Estimation Using Limited Climatic Variables in Nepal. Results in Engineering, 104254. https://doi.org/10.1016/j.rineng.2025.104254
4. Lamichhane, M., Chapagain, A. R., Mehan, S., Ames, D. P., & Kafle, S. (2024). 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, 36, 101371. https://doi.org/10.1016/j.rsase.2024.101371
5. Mehan, S., Lamichhane, M., & Jha, A. (2025). Shift in Streamflow Regime in Headwater Catchments: Causes and Impacts. In A. Nanda, P. K. Gupta, V. Gupta, P. K. Jha, & S. K. Dubey (Eds.), Navigating the Nexus: Hydrology, Agriculture, Pollution and Climate Change, Volume 1 (pp. 3–32). Water Science and Technology Library, vol 102. Springer, Cham. https://doi.org/10.1007/978-3-031-76532-2_1
6. Mehan, S. (2024). Drainage Water Management: Fundamentals, Opportunities and Challenges for South Dakota. Presented at the Agronomy Conference organized by the South Dakota Agri-Business Association (SDABA), Sioux Falls, SD.
7. Hafner, J., Antequera, L. A., Prasad, L., Thompson, A., King, K., Osterholz, W., Shedekar, V., Mehan, S., Radatz, A., & Kalcic, M. (2025). Simulating Winter Hydrology: Validating an Improved Soil Heat Transfer Equation Against Measured In-field and Edge-of-field Observations in SWAT. Presented at the UCOWR/NIWR Annual Water Resources Conference, Minneapolis, MN.
8. Manna, A., Mehan, S., & Amatya, D. M. (2024). Development of a Statistical Predictive Model for Daily Water Table Depth and Important Variables Selection for Inference. arXiv preprint arXiv:2410.01001. https://arxiv.org/abs/2410.01001
9. Macdonald, J. A., Barnard, D. M., Mankin, K. R., Miner, G. L., Erskine, R. H., Poss, D. J., Mehan, S., Mahood, A. L., & Mikha, M. M. (2025). Topographic Position Index Predicts Within-Field Yield Variation in a Dryland Cereal Production System. Agronomy, 15(6), 1304. https://doi.org/10.3390/agronomy15061304

TN – University of Tennessee

1. Momm, H.G., R.R. Wells, R. ElKadri, T. Seever, Yoder, R.P. McGehee, R.L. Bingner, and C.J.G. Darnault. 2025. Isoerodent surfaces of the continental US for conservation planning with the RUSLE2 water erosion model. Catena 253 108879. https://doi.org/10.1016/j.catena.2025.108879. Role: developing data manipulation sequence, error checking of results, contributing to and editing resulting report
2. San Martin, R., P. Das, T. Xue, M.R. Brown, R.D. Reis Marques, E. Essington, A. Gonzalez, and R.P. McCord. 2025. Amorphous calcium phosphate-coated surfaces as a model for bone microenvironment in prostate cancer. HELIYON 11 https://doi.org/10.1016/j.heliyon.2025.e41929
3. Anuo, C.O., S. Rakshit, E. Essington, and M. Kaiser. 2025. Effect of oxytetracycline on molybdenum adsorption at the hematite-water interface: insights from macroscopic and in situ ATR-FTIR study. J. Plant Nutrition Soil Sci. https://doi.org/10.1002/jln.202400395
4. Maheen, M., S. Rakshit, E. Essington, and A. Taheri. 2025. In-situ ATR-FTIR spectroscopic study of metformin adsorption on gibbsite and Loring soil. Agric. Environ. Letters. Accepted 
5. Fidan, E.N., B. Reich, R. Emanuel, A. Harris, S. Kathariou, N.G. Nelson (2025) Spatiotemporal Dynamics and Drivers of Microbial Contaminants in Hurricane Florence Floodwaters. Environmental Science & Technology Water, 5 (5). https://doi.org/10.1021/acsestwater.4c01180

TX – Texas A&M AgriLife

1. Aadhi, N., Bharadwaj, R., Naik, M. G., Gupta, H., Jaber, F. H., & Ale, S. (2025). Optimization of parameters for the HEC-HMS model based on real-time flow monitoring data: a case study of Hyderabad metropolitan area, India. Modeling Earth Systems and Environment, 11(5), 351. https://doi.org/10.1007/s40808-025-02547-0
2. Niu, H., Murray, S., Jaber, F., Heidari, B., & Duffield, N. (2025). Tail-Aware Forecasting of Precipitation Extremes Using STL-GEV and LSTM Neural Networks. Hydrology, 12(11), 284. https://doi.org/10.3390/hydrology12110284
3. Zhang, Y., & Jaber, F. H. (2024). An Upgraded GIS-based Multi-criteria Decision Making Approach for Flood Susceptibility Mapping. AGU Fall Meeting Abstracts, 2024, NH32C-06.
4. Shubham Jain, Arun Bawa, Katie Mendoza, Raghavan Srinivasan, Rajbir Parmar, Deron Smith, Kurt Wolfe, and John M. Johnston. "Enhancing Prediction and Inference of Daily in-Stream Nutrient and Sediment Concentrations Using an Extreme Gradient Boosting Based Water Quality Estimation Tool - Xgbest." Science of The Total Environment963 (2025/02/01/ 2025): 178517.
5. Arun Bawa, Katie Mendoza, Raghavan Srinivasan, Fearghal O'Donchha, Deron Smith, Kurt Wolfe, Rajbir Parmar, John M. Johnston, and Joel Corona. "Enhancing Hydrological Modeling of Ungauged Watersheds through Machine Learning and Physical Similarity-Based Regionalization of Calibration Parameters." Environmental Modelling & Software186 (2025/03/01/ 2025): 106335. 
6. Jain, Shubham, Raghavan Srinivasan, Thomas J. Helton, and Raghupathy Karthikeyan. "TXSELECT: a web-based decision support system for regional assessment of potential E. coli loads using a spatially explicit approach." Journal of Environmental Science and Health, Part A59, no. 10 (2024): 550-561.
7. Valeriy Osypov, Arun Bawa, Nataliia Osadcha, Volodymyr Osadchyi, Oleksii Shevchenko, Andrii Bonchkovskyi, Oleksandr Kostetskyi, et al. "A High-Resolution Hydrological Dataset for Ukrainian River Basins with an Interactive Web Interface." Geoscience Data Journal 12, no. 4 (2025): e70027. 
8. Chengcheng Yuan, Xinlin Li, Yufeng Wu, Gary W. Marek, Srinivasulu Ale, Raghavan Srinivasan, and Yong Chen. "Impacts of Change in Multiple Cropping Index of Rice on Hydrological Components and Grain Production in the Zishui River Basin, Southern China." Agricultural Water Management 316 (2025/07/01/ 2025): 109572.
9. David de Andrade Costa, Yared Bayissa, Mariana Dias Villas-Boas, Shreedhar Maskey, Jader Lugon Junior, Antônio José da Silva Neto, Raghavan Srinivasan, 2024. "Water availability and extreme events under climate change scenarios in an experimental watershed of the Brazilian Atlantic Forest",
   Science of The Total Environment, Volume 946.
10. David Costa, Yared Bayissa, Kargean Vianna Barbosa, Mariana Dias Villas-Boas, Arun Bawa, Jader Lugon Junior, Antônio J. Silva Neto, and Raghavan Srinivasan. "Water Quality Estimates Using Machine Learning Techniques in an Experimental Watershed." Journal of Hydroinformatics 26, no. 11 (2024): 2798-814.
11. Xiaoyu Zhang,  Yingqi Zhang, Junyu Qi, Gary W. Marek, Raghavan Srinivasan, Puyu Feng, Kelin Hu, De Li Liu, and Yong Chen. "Effects of Changes in Freeze-Thaw Cycles on Soil Hydrothermal Dynamics and Erosion Degradation under Global Warming in the Black Soil Region." Water Resources Research 61, no. 3 (2025): e2024WR038318.
12. Jain, S., Kathuria, D., Srinivasan, R., Schramm, M., Bawa, A., Ale, S., Jeong, J., White M. (2024). Deriving Hydrological Inferences from a Machine Learning Model to Explore the Physical Drivers of Flow Duration Curves. Under review: Journal of Hydrology [1^st round of review submitted]
13. Dayal, D., Palmate, S. S., Luera, E. D., Ganjegunte, G. K., & Kumar, S. (2025). A Spatially Aware Bayesian Deep Learning Framework for UAV-Based Soil Salinity Prediction. Smart Agricultural Technology, 101359.
14. Shrestha, R., Xue, Q., Soto, A. L., Ganjegunte, G., Palmate, S. S., Chaganti, V. N., ... & Zapata, S. (2025). Plant Traits in Spring and Winter Canola Genotypes Under Salinity. Agronomy, 15(7), 1657. 
15. Shrestha, R., Xue, Q., Soto, A.L., Ganjegunte, G., Palmate, S.S., Chaganti, V.N., Kumar, S., Ulery, A.L., Flynn, R.P., & Zapata, S. (2025). Seedling Emergence in Winter and Spring Canola Genotypes under Salinity Stress. Crop Science. 
16. Ebrahimi, S., Khorram, M., Neri Barranco, R., Sanchez, R., Talchabhadel, R., Palmate, S. S., … & Kumar, S. (2025). 30 Years of simultaneous crop & land cover land use maps for Middle Rio Grande from 1994 to 2024. Scientific Data, 12(1), 1462.
17. Arheimer, B., Cudennec, C., Castellarin, A., Grimaldi, S., ... Palmate, S.S., … & Xia, J. (2024). The IAHS Science for Solutions decade, with Hydrology Engaging Local People IN one Global world (HELPING). Hydrological Sciences J., 69(11), 1417-1435.
18. Bahita, T. A., Swain, S., Jha, P. K., Palmate, S. S., & Pandey, A. (2024). Numerical modelling of pollutant dispersion affecting water quality of Upper Ganga Canal (Roorkee City, India). International Journal of Environmental Science and Technology, 1-12.
19. Amrit, K., Soni, A. R., & Palmate, S. S. (2024) Exploring relationships between drought characteristics and environmental flow conditions in Indian catchments. Earth Sci. 
20. Kumar, S., Imen, S., Sridharan, V. K., Gupta, A., McDonald, W., Ramirez-Avila, J. J., Abdul-Aziz, O.I., Talchabhadel, R., Gao, H., Quinn, N.W.T., Weiss, W.J., Poulose, T., Palmate, S.S., Lee, C.M., & Baskaran, L. (2024). Perceived barriers and advances in integrating earth observations with water resources modeling. Remote Sensing Applications: Society and Environment, 33,
21. Palmate, S. S. (2025). Machine learning-based estimation of blue water footprints for transboundary water management in the Rio Grande River watershed. In Water Footprints: Achieving Sustainable Development Goals (pp. 19-31). Elsevier.

RI – University of Rhode Island

1. Panthi, J., Boving, T., Pradhanang, S.M. and Ismail, M., 2024. Time‐Lapse Geophysical Measurements for Monitoring Coastal Groundwater Dynamics in an Unconfined Aquifer. Groundwater, 62(4), pp.513-526.
2. Adhikari, T.R., Baniya, B., Tang, Q., Chen, D., Talchabhadel, R., Li, H., Shrestha, S., Sigdel, M., Budhathoki, B.R., Pradhanang, S.M. and Pradhananga, D., 2024. Identification precipitation threshold and resulting river discharge: an IDF-based approach in the Central Himalaya, Nepal. Geografiska Annaler: Series A, Physical Geography, pp.1-16.
3. Paul, S., Pradhanang, S.M., and Boving, T., 2024 Assessing the Hydrologic Response of a Major Drinking Water Reservoir during Extreme Flood. Water 6(18), p.2572
4. Ismail, M.; Pradhanang, S.M.; Boving, T.; Motta, S.; McCarron, B.; Volk, A. 2024 Review of Modeling Approaches at the Freshwater and Saltwater interface in Coastal Aquifers. Land, 13, 1332
5. Panthi, J., Boving, T., Pradhanang, S.M., Russoniello, C.J., and Kang, S. 2024. The Contraction of Freshwater Lenses in Barrier Island: A Combined Geophysical and Numerical Analysis, Journal of Hydrology, 637, 131371
6. Paul*, S., Pradhanang, S. M., and Boving, T. 2024. Simulation of Reservoir Inflow in a Forest Dominated Watershed through Multi-site Parameterization and Calibration. NEWWA, March 2024, 46- 57.
7. Singh, R., Sharma, A., Goswami, P., Pradhananga, D., Aryal, D., Pradhanang, S.M. and Kumar, R., 2023. Phytoremediation of organic contaminants: An eco-friendly approach-based application of aquatic macrophytes. In Aquatic macrophytes: Ecology, functions and services (pp. 175-205). Singapore: Springer Nature Singapore.

VA – Virginia Tech

1. Easton, Z.M. Linking runoff source areas and nitrogen fluxes across topographic and landuse gradients. Transactions of the ASABE. (In Review).
2. Asfaw, B.^,R. Fuka, A.S. Collick, R.R. White, Z.M. Easton. 2025. Characterizing the topographic index as a tool to represent spatial soil moisture: The effect of classification approach, digital elevation model type and resolution. Vadose Zone Journal. https://doi.org/10.1002/vzj2.70031.
3. Easton, Z.M., J. Hanson, E. Bock, B. Asfaw. 2025. A systematic review of Chesapeake Bay climate change impacts: Watershed processes and pollutant delivery. Journal of the American Water Resources Association. https://doi.org/10.1111/1752-1688.70030.
4. Easton, Z.M., K. Stephenson, B. Benham, J.K. Böhlke, A. Buda, A. Collick, L. Fowler, E. Gilinsky, A. Miller, G. Noe, L. Palm-Forster, L. Shabman, T. Wynn-Thompson. 2025. The nonpoint source challenge: Obstacles and opportunities for meeting nutrient reduction goals in the Chesapeake Bay watershed. Journal of the American Water Resources Association. https://doi.org/10.1111/1752-1688.70034
5. dos Reis, B.R., S. Sujani, D.R. Fuka, M. Easton, R.R. White. 2025. Comparison among grazing animal behavior classification algorithms for use with open-source wearable sensors. Smart Agricultural Technology. https://doi.org/10.1016/j.atech.2025.101133.
6. Garna, R., Maksud, S., D.R. Fuka, R.R. White, J.W. Faulkner, A.S. Collick, M. Easton. 2025. Development of a dairy model for the Soil and Water Assessment Tool (SWAT) to direct water quality management of livestock. (In Review).