Brief Summary of Minutes of Annual Meeting

The committee met via Zoom and gave their reports.

WERA 1022 - Meteorological and Climate Data to Support ET-Based Irrigation Scheduling, Water Conservation, and Water Resources Management

Times are Pacific Daylight Time, so Adjust according to your time zone.

Thursday

8:00 AM: Welcome and Business Meeting

8:30 AM: Revision of the Proposal

9:30 AM: Break

10:00 AM: State, Agency, and Visitor Reports

12:00 PM: Lunch

1:00 PM: State, Agency, and Visitor Reports

1:30 PM: Break

2:00 PM: State, Agency, and Visitor Reports

3:30 PM: Adjourn

WERA 1022 – Accomplishments

October 1, 2020 – September 30, 2021

Objective 1.  Coordinate the documentation of crop coefficients used in irrigation scheduling.

Colorado:  Hourly and daily crop evapotranspiration (ET_C) rates of sprinkler-irrigated dry beans and furrow-irrigated grass hay were collected from two precision weighing lysimeters at the CSU Arkansas Valley Research Center (AVRC) in Southeast Colorado during 2021. The ET_c data will be used in conjunction with ASCE Standardized reference ET to develop crop coefficients (K_c) of dry beans and grass hay appropriate for the semi-arid conditions of Southeast Colorado.

Florida:  Bayabil Water Resources Lab.  A variable rate irrigation field experiment funded by USDA/NIFA was conducted under a linear move system. The goal of the study is to develop a crop moisture stress-based irrigation scheduling method.  The first-year study (November 2020 – February 2021) was completed and several data on soil-water-plant parameters were collected. The experiment involved four irrigation treatments with four replications. Collected data will be used to estimate crop evapotranspiration/crop coefficients at plot and field levels

Kansas: As part of the Rattlesnake Creek Watershed Project, Kansas is using KanSched in at least 25 irrigated fields to track soil moisture content using ET data in the region. With the field data and frequent site visitations to check actual soil moisture, there is documentation on the performance of crop coefficients and KanSched.  For the reporting period, a couple of issues were identified and were immediately corrected.

Louisiana:  This objective was not pursued in the last year.

Minnesota: This year in Minnesota, we evaluated the interaction effects of different irrigation strategies and different N rates on grain yield, nitrate-N leaching, crop evapotranspiration, and N and water use efficiency in continuous maize to develop the best management system aimed at maximum maize production and minimum nitrate leaching. One of  the objectives of this research is to develop crop coefficients (Kc) for maize, under various irrigation and nitrogen management practices in central sands region of Minnesota. For now, ASCE manual 70 crop coefficients adjusted for Minnesota climate are being used for irrigation water management in the state. This an on-going three year research project and in 2021 we have completed the second year of the study.

Oklahoma:  The Oklahoma PI has been involved in the Crop Coefficient Task Committee of the American Society of Civil Engineers (serving as the chair), where a team of scientists, engineers, and industry representatives work on developing refereed publications and manuals on recommended documentations for measuring, estimating, and reporting crop coefficients.

USDA-ARS Texas: Short-season soybean [Glycine max (L.) Merr.] is often planted as a catch crop after cotton failure in the Texas High Plains. However, crop coefficients developed for full-season soybean are not directly applicable to irrigation scheduling of short-season varieties. Marek et al. (2021) reported crop coefficients for short-season soybean grown after cotton failure at Bushland, Texas. They found that maximum daily Kc values were not different from those published elsewhere but that season length was 24 to 29 days shorter. Due to the compressed season, crop water use was smaller than most values found in earlier studies of full-season soybean at Bushland. Crop coefficient trapezoidal functions were reported for both short-crop (grass) and tall-crop (alfalfa) reference ET and for both subsurface drip irrigation (SDI) and low-elevation spray irrigation (LESA). Mid-season crop coefficient values were larger for LESA irrigation than for SDI. Although preliminary, it appears that SDI Kc values were ~6.5% smaller than those for LESA. Water use was smaller and crop water productivity was larger for SDI compared to LESA irrigation.

Utah:  Crop coefficients for onions were developed for drip and surface irrigated onions grown in northern Utah calculated from the data based on data from 2019 and 2020. The Kc initial stage Kc is 0.2, mid stage is 1.2 for both drip and surface, but the transition for initial stage to mid-stage is about one month earlier for surface irrigation.  Irrigation depletion studies are continuing for silage corn, alfalfa, and triticale.  Data collected include soil moisture readings, climate data, including an eddy covariance tower.  Each field has recording flow meters for inflow and outflow recorded about every 15 minutes.  Crop coefficients will be developed for alfalfa, silage corn, and forage triticale for southwest Utah from the data. One objective of the research is to determine the annual water use of alfalfa compared to double cropping silage corn and fall-planted triticale.

Objective 2.  Coordinate efforts to promote adoption of improved irrigation scheduling technology, including computer models based on crop coefficients and ETref, remote sensing and instrumentation that will help producers more efficiently apply irrigation water.

California:   California: I. Groundcover irrigation management in inland southern California: Two adjacent irrigation trials were conducted by Haghverdi lab in early 2021 at the University of California, Riverside Agricultural Experiment Station in Riverside, California. The objective is to develop crop coefficient and irrigation management information for ten groundcover species representing a wide range of plant types, including woody, herbaceous, and succulent, with different growth habits and water requirements. In May 2021, four irrigation treatments (i.e., 80%, 60%, 40%, and 20% of ETo) were imposed in a randomized complete block design replicated three times. We continuously monitored the effect of irrigation on the growth and health of the plant species by measuring the NDVI values (Normalized Difference Vegetation Index, a measure of plant greenness and health) and canopy temperature (to determine the water stress in plants) for all the ten species. NDVI was measured using the handheld sensor (GreenSeeker, Trimble Inc., CA), and canopy temperature was measured using the handheld infrared temperature sensor.

The effect of irrigation, species, and their interaction significantly (p<0.001) affected the quality and growth of the groundcover species as measured by the NDVI index. The effect of irrigation, groundcover species and their interaction was also found significant (p<0.001) on the canopy temperature of the groundcover. For all four irrigation treatments, the species Rhagodia spinescens (Creeping Australian saltbush) showed acceptable visual growth and did not show significant signs of water stress during the experimental period. Eriogonum fasciculatum ‘Warriner Lytle’ (Buckwheat) also was not negatively affected by irrigation treatments; however, as the trial progressed, the NDVI values decreased from around 0.7 (highest) to 0.4 (lowest). Baccharis x ‘Starn’ Thompson (Coyote bush) also maintained its acceptable quality for all irrigation treatments. The lowest irrigation level of 20% ETref caused a significant decreased in the growth and quality of the remaining groundcovers species including Lantana montevidensis (Lantana), Trachelospermum jasminoides (Jasmine), Rosmarinun officinalis ‘Roman beauty’ (Rosemary), Eremphila glabra ‘Mingenew Gold’ (Gold Emu Bush), and Oenothera stubbei (Saltillo Evening Primrose). At 60- and 80-% ETref, all groundcovers showed similar growth and development.

1. Turfgrass irrigation management in Central California: Research-based information regarding the accuracy and reliability of smart irrigation controllers for autonomous landscape irrigation water conservation is limited in central California. A two-year irrigation research trial (2018–2019) was conducted in Parlier, California, to study the response of hybrid bermudagrass and tall fescue to varying irrigation scenarios (irrigation levels and irrigation frequency) autonomously applied using a Weathermatic ET-based smart controller. The response of turfgrass species to the irrigation treatments was visually assessed and rated. In addition, turfgrass water response functions (TWRFs) were developed to estimate the impact of irrigation scenarios on the turfgrass species based on long-term mean reference evapotranspiration (ET_o) data. The Weathermatic controller overestimated ET_o between 5and 7% in 2018 and between 5 and 8% in 2019 compared with California Irrigation Management Information System values. The controller closely followed programmed watering-days restrictions across treatments in 2018 and 2019 and adjusted the watering-days based on ET_o demand when no restriction was applied. The low half distribution uniformity and precipitation rate of the irrigation system were 0.78 and 28 mm h⁻¹, respectively. The catch-cans method substantially underestimated the precipitation rate of the irrigation system and caused over-irrigation by the smart controller. No water-saving and turfgrass quality improvement was observed owing to restricting irrigation frequency (watering days). For the hybrid bermudagrass, the visual rating (VR) for 101% ET_o treatment stayed above the minimum acceptable value of six during the trial. For tall fescue, the 108% ET_o level with 3 d wk⁻¹ frequency kept the VR values in the acceptable range in 2018 except for a short period in mid-trial. The TWRF provided a good fit to experimental data with r values of 0.79 and 0.75 for tall fescue and hybrid bermudagrass, respectively. The estimated VR values by TWRF suggested 70–80% ET_o as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in central California during the high water demand months (i.e., May to August) based on long-term mean ET_o data. The TWRF estimations suggest that 100% ET_o would be sufficient to maintain the tall fescue quality for only 55 days. This might be an overestimation impacted by the relatively small tall fescue VR data in 2019 owing to minimal fertilizer applications and should be further investigated in the future.

This two-year field irrigation project (2018–2019) also focused on the application of optical and thermal remote sensing for turfgrass irrigation management in central California. We monitored the response of hybrid bermudagrass and tall fescue to varying irrigation treatments, including irrigation levels (percentages of reference evapotranspiration, ET_o) and irrigation frequency. The ground-based remote sensing data included NDVI and canopy temperature, which was subsequently used to calculate the crop water stress index (CWSI). The measurements were done within two hours of solar noon under cloud-free conditions. The NDVI and canopy temperature data were collected 21 times in 2018 and 10 times in 2019. For the tall fescue, a strong relationship was observed between NDVI and visual rating (VR) values in both 2018 (r = 0.92) and 2019 (r = 0.83). For the hybrid bermudagrass, there was no correlation in 2018 and a moderate correlation (r = 0.72) in 2019. There was a moderate correlation of 0.64 and 0.88 in 2018 and 2019 between tall fescue canopy minus air temperature difference (dt) and vapor pressure deficit (VPD) for the lower CWSI baseline. The correlation between hybrid bermudagrass dt and VPD for the lower baseline was 0.69 in 2018 and 0.64 in 2019. Irrigation levels significantly impacted tall fescue canopy temperature but showed no significant effect on hybrid bermudagrass canopy temperature. For the same irrigation levels, increasing irrigation frequency slightly but consistently decreased canopy temperature without compromising the turfgrass quality. The empirical CWSI values violated the minimum expected value (of 0) 38% of the time. Our results suggest NDVI thresholds of 0.6–0.65 for tall fescue and 0.5 for hybrid bermudagrass to maintain acceptable quality in the central California region. Further investigation is needed to verify the thresholds obtained in this study, particularly for hybrid bermudagrass, as the recommendation is only based on 2019 data. No CWSI threshold was determined to maintain turf quality in the acceptable range because of the high variability of CWSI values over time and their low correlation with VR values.

Colorado:  A prototype deep learning-based (artificial intelligence) model was developed to combine high-resolution, low-frequency satellite data (Landsat) with low-resolution, high-frequency satellite data (MODIS), along with a process-based ET model (SSEBop) to generate high-resolution, high-frequency actual ET estimates (daily, 10 m resolution) for the Continental US. The deep learning model is currently being trained with Ameriflux and SSEBop ET data. The project is funded by the USDA-National Institute of Food and Agriculture (NIFA) – Food and Agriculture Cyberinformatics and Tools (FACT) program. The project is titled “A Scalable Infrastructure for High-precision Evapotranspiration Estimations and Effective Farm-level Decision Making” (2020 – 2023) and is led by Dr. Sangmi Pallickara (CSU Computer Science Department).

Florida: Ferrarezi Citrus Horticulture Lab

Study 1: Use of Thermal Imaging to Assess Water Status in Citrus Plants in Greenhouses

The direct examination of plant canopy temperature can assist in optimizing citrus irrigation management in greenhouses. This study aimed to develop a method to measure canopy temperature using thermal imaging in one-year-old citrus plants in a greenhouse to identify plants with water stress and verify its potential to be used as a tool to assess citrus water status. The experiment was conducted for 48 days (27 November 2019 to 13 January 2020). We evaluated the influence of five levels of irrigation on two citrus species (‘Red Ruby’ grapefruit (Citrus paradisi) and ‘Valencia’ sweet orange (Citrus sinensis (L.) Osbeck)). Images were taken using a portable thermal camera and analyzed using open-source software. We determined canopy temperature, leaf photosynthesis and transpiration, and plant biomass. The results indicated a positive relationship between the amount of water applied and the temperature response of plants exposed to different water levels. Grapefruit and sweet orange plants that received less water and were submitted to water restrictions showed higher canopy temperatures than the air (up to 6 °C). The thermal images easily identified water-stressed plants. Our proof-of-concept study allowed quickly obtaining the canopy temperature using readily available equipment and can be used as a tool to assess citrus water status in one-year-old citrus plants in greenhouses and perhaps in commercial operations with mature trees in the field after specific experimentation. This technique, coupled with an automated system, can be used for irrigation scheduling. Thus, setting up a limit temperature is necessary to start the irrigation system and set the irrigation time based on the soil water content. To use this process on a large scale, it is necessary to apply an automation routine to process the thermal images in real time and remove the weeds from the background to determine the canopy temperature.

Study 2: Pre-sprouted Sugarcane Plantlets Produced in Ebb-and-flow Subirrigation Automated by Soil Moisture Sensors

There is a growing demand for innovation in the sugarcane production chain to increase crop productivity. The recent use of sugarcane plantlets to improve planting efficiency in the field is a viable option, and nurseries are seeking for enhanced irrigation systems to accelerate the production of high-quality plantlets and optimize water and fertilizer inputs. This research aimed to determine the adequate substrate volumetric water content (VWC) to produce pre-sprouted sugarcane plantlets using ebb-and-flow subirrigation automated by soil moisture sensors and the effects on plant growth in greenhouse on acclimation stages #1 and #2. We tested three thresholds to trigger subirrigation automatically when sensor readings dropped below the setpoints: VWC 45% (v/v), VWC 35%, and VWC 25%. Plantlets were cultivated in 54-cell flat trays with 130-cm3 cone-shaped containers filled with commercial substrate in ebb-and-flow benches controlled by capacitive soil moisture sensors connected to a datalogger. The results indicated the automated subirrigation system worked properly, successfully irrigating the plantlets based on the target VWC. VWC 35% was the most efficient treatment, reducing fertilizer solution consumption in 44.78% (368.47 L and 2.41 mm d−1) in comparison with VWC 45% (667.28 L and 4.37 mm d−1) and increasing water use efficiency in 43.18% (7.62 g L−1) when compared to VWC 45% (4.33 g L−1), which produced less biomass with the same amount of water. VWC 45% treatment also resulted in the highest number of irrigation events, with the greatest electrical conductivity value in the substrate at the end of the experiment. All plant growth variables such as stem diameter, plant height, first ligule height, and shoot and root dry weight responded positively to the increase in VWC (P < 0.05). VWC 45% resulted in the highest biomass except root dry weight where VWC 35% was superior. VWC 35% was statistically the same to VWC 45% in all biometric responses (P < 0.05) and showed the best efficiency rate in fertilizer solution consumption and water use. Based on our results, we recommended VWC 35% as the setpoint for water management to produce pre-sprouted plantlets using automated ebb-and-flow subirrigation.

Study 3: Automated ebb-and-flow subirrigation conserves water and enhances citrus liner growth compared to capillary mat and overhead irrigation methods

Most citrus nurseries in Florida, USA use overhead irrigation, but subirrigation methods, including ebb-and-flow and capillary mats, have been shown to conserve water and accelerate plant growth relative to overhead irrigation for other nursery species and may be a viable alternative to overhead irrigation in citrus liner production. The objectives of this study were to (1) automate an ebb-and-flow system for citrus liner production using capacitance sensors, and (2) evaluate how subirrigation and overhead irrigation methods affect water use, plant growth parameters, and substrate chemical properties. A study was conducted from 22 May to 23 September 2018 in which liners of six commercially important rootstock cultivars in cone-shaped containers were subjected to one of the following irrigation methods: ebb-and-flow triggered at substrate volumetric water contents (θ) of 0.24, 0.36, or 0.48 m3 m−3, capillary mats, and overhead irrigation. Capacitance sensors successfully monitored irrigation throughout the study. Ebb-and-flow benches used substantially less water (~411 L) than either capillary mats (13,098 L) or overhead irrigation (3193 L). By the end of the study, rootstock cultivars propagated using subirrigation methods were approximately 22% taller with 7% more total biomass than plants subjected to overhead irrigation. Additionally, plant growth at the 0.24 m3 m−3 threshold used to trigger ebb-and-flow was as great or greater than growth at 0.36 and 0.48 m3 m−3 thresholds. During the final five weeks of the study, substrate electrical conductivity was higher using subirrigation methods (0.84–1.3 ds m−1) than under overhead irrigation (0.55–0.8 ds m−1), but there were no symptoms of salt stress observed in plants at any time. Results from this study show that ebb-and-flow is a viable alternative to overhead irrigation and is superior to capillary mats for water conservation. In automated ebb-and-flow systems in Florida, we recommend using the 0.24 m3 m−3 threshold to produce the citrus rootstock cultivars used in this study with peat: perlite substrate.

Study 4: Sweet Orange Orchard Architecture Design, Fertilizer, and Irrigation Management Strategies under Huanglongbing-endemic Conditions in the Indian River Citrus District

The prevalence of Huanglongbing (HLB) in Florida has forced growers to search for new management strategies to optimize fruit yield in young orchards and enable earlier economic returns given the likelihood of HLB-induced yield reductions during later years. There has been considerable interest in modifying orchard architecture design and fertilizer and irrigation management practices as strategies for increasing profitability. Our objectives were to evaluate how different combinations of horticultural practices including tree density, fertilization methods, and irrigation systems affect growth, foliar nutrient content, fruit yield, and fruit quality of young ‘Valencia’ sweet orange [Citrus sinensis (L.) Osbeck] trees during the early years of production under HLB-endemic conditions. The study was conducted in Fort Pierce, FL, from 2014 to 2020 on a 1- to 7-year-old orchard and evaluated the following treatments: standard tree density (358 trees/ha) and controlled-release fertilizer with microsprinkler irrigation (STD_dry_MS), high tree density (955 trees/ha) with fertigation and microsprinkler irrigation (HDS_fert_MS), and high tree density with fertigation and double-line drip irrigation (HDS_fert_DD). Annual foliar nutrient concentrations were usually within or higher than the recommended ranges throughout the study, with a tendency for decreases in several nutrients over time regardless of treatment, suggesting all fertilization strategies adequately met the tree nutrient demand. During fruit-bearing years, canopy volume, on a per-tree basis, was higher under STD_dry_MS (6.2–7.2 m3) than HDS_fert_MS (4.3–5.3 m3) or HDS_fert_DD (4.9–5.9 m3); however, high tree density resulted in greater canopy volume on an area basis, which explained the 86% to 300% increase in fruit yield per ha that resulted in moving from standard to high tree density. Although fruit yields per ha were generally greatest under HDS_fert_MS and HDS_fert_DD, they were lower than the 10-year Florida state average (26.5 Mg·ha−1) for standard tree density orchards, possibly due to the HLB incidence and the rootstock chosen. Although tree growth parameters and foliar nutrient concentrations varied in response to treatments, management practices that included high tree density and fertigation irrespective of irrigation systems produced the highest fruit yields and highest yield of solids. Soluble solids content (SSC) and titratable acidity (TA) were lower, and the SSC-to-TA ratio was highest under STD_dry_MS in 2016–17, with no treatment effects on quality parameters detected in other years. Both drip and microsprinkler fertigation methods sufficiently met tree nutrient demand at high tree density, but additional research is needed to determine optimal fertilization rates and better rootstock cultivars in young high-density sweet orange orchards under HLB-endemic conditions in the Indian River Citrus District.

Bayabil - During the period covered by this report, workshops and in-service trainings were were given to board audiences including extension agents, growers, and homeowners. Dates of events and topics of presentations were:

• May 21, 2021: Irrigation Scheduling Techniques.  In-Service Training lead by Bayabil’s lab. 
• Feb 02, 2021: Optimizing irrigation rates for beans and sweetcorn to improve plant health, yield and quality. Virtual Field Day. 
• September 10, 2021. Best Management Practices for Protection of Water Resources by The Green Industries. Workshop for irrigation/landscaping contractors

Kansas: Several projects are being conducted that partially addresses this objective.

In coordination with the Nature Conservancy, the Rattlesnake Creek Watershed Project promotes increased adoption of MDI, soil moisture sensors, and the KanSched irrigation scheduling mobile app, to test improvements in irrigation efficiency and irrigation water management, maintaining crop water productivity while minimizing groundwater withdrawals.  In addition, this project also aims to develop water budgets and irrigation scheduling tools, facilitate a peer-to-peer mentoring network for enhanced communication, and identify successful techniques and strategies that could be adapted to other communities trying to minimize groundwater withdrawals and sustain local aquifers. The project partnered with NRCS soil and range conservationists to develop strategies that fulfill the needs of local agricultural producers and aid in policy and procedure development.

Leveraging on this project, we have developed video tutorials for using KanSched, conduct field days and have multiple conversations with the farmers to help them better water managers.  KanSched has undergone some software and programming updates.  Most of the updates are behind the scene just trying to catch-up with technological and software development advances.  One of these relatively minor but very significant change programming update is the consolidation of our management tools under the new and shortened website, milab.ksu.edu (formerly bae.ksu.edu/mobileirrigationlab).

In cooperation with the Global Food Systems, the project Quantifying ET, water stress, and economic benefits for sustainable cotton production in Kansas has a main goal of developing strategies for economically-sound cotton production for Kansas.  It also aims to determine water use and irrigation strategies, based on crop evapotranspiration (ET) rates, water stress, and growing conditions in southwestern Kansas. We are leveraging on this project to generate the Kc for cotton on this region.

Louisiana: After completing last year’s on-farm demonstration successfully, the American Sugarcane League agreed to fund the continuation of a small on-farm research study designed to develop irrigation scheduling recommendations for sugar cane grown in central Louisiana. This field was split into four replications of two treatments: 1) irrigation based on sensor, and 2) non-irrigated. In addition to collecting yield response from irrigation, sensor placement was also considered important to the study. Thus, two Sentek Drill-and-Drop soil moisture sensors were installed in one replication of each treatment (totaling four sensor installations) with placement occurring in the top third of the field at the row center and offset from the row center. Uncharacteristic weather conditions including unprecedented rainfall amounts outside of hurricane season resulted in very little irrigation needs in 2021; only one irrigation event occurred at the end of August.  Sensor placement indicated that the edge of the row and furrow areas experience compaction that affects available water holding capacity and was independent of irrigation status. Harvest is expected to occur in November to officially assess treatment results.

Minnesota:   This year Minnesota has continued the efforts to promote efficient irrigation management practices throughout the state through research, educational and training opportunities.

In terms of research, we have used remote sensing as well as proximal sensing platforms such as UAV and crop circle phenom to develop in-season sensor based non-destructive irrigation recommendations for corn at different nitrogen levels. We have used crop circle phenom which is an integrated active canopy sensor that measures infrared temperature, relative humidity, atmospheric pressure, ambient air temperature, incident PAR, various vegetation indices etc. We are trying to correlate these parameters to in-season ground truth measured data to develop algorithms for irrigation management. In a similar way, we are using UAV that has RGB, red edge, NIR and FLIR thermal camera. By measuring these parameters and relating them to in-season soil moisture, we will develop UAV based in season irrigation mangement techniques.

In addition, in collaboration with other University of Minnesota researchers, we are expanding the geographic coverage of the irrigation management assistant (IMA) tool which is an ET based online irrigation scheduling tool, to the entire state of Minnesota; expanding and improving the input data and crop models of the IMA tool so it is more useful for farmers, covering a wider array of irrigation approaches, including recycled drainage water and increasing tool adoption by engaging farmers, SWCD staff, and crop consultants through extension and outreach. This project aims to reduce the groundwater use to levels that are sustainable over the long run and improve water quality in Minnesota.

In terms of extension and outreach, various field days and workshops were organized attended by farmers, county agents, and soil water conservation districts (SWCD). Through various educational events, farmers and agency personals were introduced to different methods of irrigation scheduling including soil moisture sensors, Irrigation Management Assistant (IMA) tool (http://ima.respec.com/), ET based irrigation scheduling and how to utilize these methods in their practices to enhance crop water use efficiency and reduce irrigation-induced environmental pollution and encourage the adoption of best irrigation management practices.

Oklahoma:  Oklahoma continued efforts toward promoting the use of sensor-based technologies to improve irrigation scheduling:

1. The use of soil moisture probes in estimating and updating crop ET and crop coefficients was evaluated by conducting a field experiment in west-central Oklahoma, where soil moisture probes, rain gauges, and canopy temperature sensors were installed at irrigated cotton plots (two varieties). Besides using sensor readings to estimating ET and crop coefficients, the effectiveness of sensors to be used for sensor-based irrigation scheduling is evaluated.
2. A new commercial irrigation scheduling product developed for irrigated cotton in Australia was installed at over 22 collaborating farms in southwestern Oklahoma to assess the performance of this product in achieving irrigation water conservation. This product relies on three technologies of remotely sensed crop coefficients, in-situ soil water content, and in-situ canopy temperature to provide information on cotton water stress and irrigation requirement.

USDA-ARS Texas:  Since 2002, ARS has been developing a center pivot variable rate irrigation (VRI) decision support system based on proximal sensing of plant and soil water stress indices. This Irrigation Scheduling Supervisory Control And Data Acquisition (ISSCADA) system, patented in 2014, was licensed by Valmont Industries in 2018. The ARS team at Bushland, Texas, coordinated ISSCADA field trials with ARS and university partners in Alberta, Missouri, Mississippi, South Carolina and Texas in 2019-2021, continuing multi-state field trials that began in 2016. Several journal articles reporting on the ISSCADA system were reported in last year’s report to WERA 1022 and will not be reiterated here. However, comparable articles are expected in the proceedings of the Decennial Irrigation Symposium, which was postponed from 2020 to 2021.

Researchers from Texas A&M AgriLife, TAMU, and ARS Bushland recently developed a center pivot automation and control system (CPACS) that integrates innovative hardware, software, and logic technologies. The system combines GPS guided location and speed control, real-time soil water monitoring, and precipitation forecasting with distributed crop models to generate and perform targeted irrigation prescriptions. Field studies have demonstrated the effectiveness of CPACS’s water-saving technologies and can be used to optimize equipment currently available on the market. The system has U.S. and international patents pending, and the developers are ready to work with industry licensing partners. The CPAC team was recently honored with the Texas Water Development Board’s Blue Legacy Award in the agriculture category and awarded a Texas A&M AgriLife Research Director’s Award.

In 2021, Evett et al. (2021) reported on the ability of a solar-powered, wireless node and gateway system to withstand the long-term subfreezing and subzero (F) temperatures, snow and cloudiness brought on by the February polar vortex outbreak that covered the central US, also known as Winter Storm Uri. The node and gateway system, developed by ARS in cooperation with Acclima, Inc., interfaces with SDI-12 sensor systems such as those for soil water, canopy temperature, and weather, which makes it useful for irrigation and environmental management. It is being integrated into the ISSCADA system. A separate paper reported development of the node and gateway system and improvements in its capabilities (Thompson et al., 2021).

Kutikoff et al. (2021) reported on differences in water vapor density and turbulent fluxes from three generations of fast-response infrared gas analyzers that were deployed over an irrigated maize field at Bushland, Texas. There were differences in mean and variance values, although the former did not influence flux magnitudes. Although the three different analyzers produced different results, most differences in fluxes could be corrected using the energy balance ratio to estimate systematic bias.

Marek et al. (2021) reported on maize grown under full and deficit irrigation on a Pullman silty clay loam near Bushland, TX in 2018 to compare seasonal water use of two sprinkler irrigation management approaches. The USDA-ARS CPRL weighing lysimeter fields were generally irrigated twice weekly using irrigation depths ranging from 19 to 32 mm. The Texas A&M AgriLife Research Emeny field was irrigated only once per week using greater application depths ranging from 35 to 42 mm. Yield and crop water productivity (CWP) values for the 100 and 75% lysimeter field irrigation treatments were greater than corresponding values for the Emeny field. Results suggested evaporative losses associated with the more frequent, smaller irrigations on the lysimeter fields did not contribute to appreciably smaller CWP values. One reason may be that losses were likely mitigated by the rapid development of the corn canopy. Another reason may be that evaporative loss from the Pullman soil continues for several days after irrigation on the soil surface and continues longer after larger irrigations (Tolk et al., 2015), reducing the difference in losses between once-a-week and twice-a-week irrigation scheduling. These findings suggest that corn yield on the Pullman soil is principally dependent upon seasonal water inputs. and that, outside of incomplete canopy conditions, losses from frequent, smaller irrigation are comparable to those from larger, once-a-week irrigations.

USDA ARS scientists gave 45-minute presentations followed by Q&A in the ICARDA/FAO Webinar Series on the “Measurement of Evapotranspiration: Basic principles, and measurement methods.” One presentation was titled, “Comparison of ET estimates from a surface layer scintillometer and a large weighing lysimeter”, while the other was titled, “ET by Soil Water Balance: Weighing lysimetry and soil water sensing approaches.” The webinar series ran from 2021-09-15 through 2021-11-24. Gary Marek presented results from an evaluation of a SLS scintillometer to estimate hourly and daily ET (Moorhead et al, 2017) as part of the 2021 ICARDA/FAO webinar series on measuring ET. A Surface Layer Scintillometer (SLS) was evaluated for accuracy in determining ETsls, as well as sensible and latent heat fluxes, by comparison with values obtained from a large weighing lysimeter field at ARS bushland. The SLS was positioned over irrigated grain sorghum (Sorghum bicolor (L.) Moench) from July 29 – August 17 in 2015 and over grain corn (Zea mays L.) from June 23 – October 2 in 2016. Results showed poor correlation for sensible heat flux, but much better correlation with ET, with r² values of 0.83 and 0.87 for hourly and daily ETsls, respectively.  The accuracy of the SLS was comparable to other ET sensing instruments with an RMSE of 0.13 mm h^-1 (31%) for hourly ETsls. However, summing hourly data to daily values reduced the ETsls error to 14% (0.75 mm d^-1). The reduction in error was likely due to over- and underestimations in hourly values canceling out upon summation. With error rates as small as 14%, the SLS exhibits potential for use in water management activities such as developing crop coefficients or irrigation scheduling when daily data can be used. However, for shorter time steps, error rates are larger and comparable to error rates from other instruments such as eddy covariance systems. Additional research is needed to identify the cause(s) of discrepancies in the hourly data which may lead to improvements in accuracy of the method. Evaluating data from scenarios having larger sensible heat values, such as dryland conditions, may provide more information regarding discrepancies in sensible heat values.

Utah: Grower meetings and field days were held with growers to share information on yield impacts from replacing and updating pivot sprinklers/nozzles and of decreasing as section nozzle flowrates by 10 percent. As part of the research, we used Washington State’s Irrigation Scheduling application (Kc based) to schedule a portion of each field to schedule irrigations, another portion of each field was scheduled using soil moisture sensors, and the balance of each field was irrigated based on irrigators preference.  While the yield differences were small and inconsistent, the research showed that irrigation amount could be decreased without significantly impacting yield. Possible salinity impacts will be evaluated after a few years.

Objective 3.  Coordinate the development of quality control (QC) procedures for weather data used for irrigation scheduling.

Colorado:  Short-term weather forecasts (up to 7 days) during the 2021 growing season have been downloaded via the aWhere (http://www.awhere.com/) Weather Info API. The 2021 weather forecasts will be added to archived 2020 forecast data and compared to selected Colorado Agricultural Meteorological Network (CoAgMet) station data in a historical (hindsight) analysis that will assess the accuracy and usability of the information in forecasting irrigation requirements.

Florida:  Bayabil - A study was conducted to investigate the reliability of the DarkSky (©Apple inc.) weather forecast data based on eight-months observations at 124 weather stations distributed across Florida and Georgia. A manuscript is submitted to the Journal of American Water Resources Association (JAWRA) and is currently under review.

Kansas: This year Kansas did not engage in Objective 3.

Louisiana:  The LSU AgCenter provides access to weather data through the Louisiana Agriclimatic Information System (LAIS). In 2019, LAIS was transitioned onto the LSU AgCenter’s new website using a similar format to what was used prior to the update. As a result, high quality weather data is now available (beginning May 2019) for each of eight weather stations located across the state. However, work continues in providing reference evapotranspiration estimations for use in irrigation scheduling.  Also, the data has some limited usefulness until station information is specified (i.e. sensor type, sensor height, units listed for each parameter, maintenance logs, etc.).  LSU AgCenter IT was directed toward comparable resources for review such as University of Florida’s FAWN, California’s CIMIS, and Bureau of Reclamation’s AgriMet.

Minnesota: This year Minnesota did not engage in Objective 3.

Oklahoma:  Our efforts on investigating the quality of reference ET estimates as impacted by non-reference condition continued in the reporting period. A large number of Oklahoma Mesonet stations in the western half of the state, where close to 90% of irrigated land is located, suffer from non-reference conditions and as such the reference ET values are overestimated. At some sites, the percentage of time when the maximum relative humidity is less than 80% (an indicator of station aridity) reached 36%.

USDA-ARS Texas:  The Bushland large weighing lysimeter ET and corresponding weather data sets are widely used for model development. The USDA-ARS team at Bushland, Texas, previously developed quality assurance (QA) and QC procedures for weighing lysimeter data from the four large weighing lysimeters at Bushland, as well as for research weather data compiled from a grassed research weather station, four large weighing lysimeters and a U.S. Weather Service station at Bushland. In FY2021, we applied these procedures to produce four years of quality 15-minute, 365-day weather and lysimeter ET data that were shared with alfalfa ET modelers. Work is underway to apply these procedures to 30+ years of Bushland weighing lysimeter and weather data for sharing on the USDA National Agriculture Library Ag Data Commons, similar to that already posted there.

Utah: No new development on Object 3.  The ongoing quality control procedures are developed and implemented by the Utah Climate Center.

California

Haghverdi, A., Singh, A., Sapkota, A., Ghodsi, S., Reiter, M. (2021). Developing Irrigation Water Conservation Strategies For Hybrid Bermudagrass Using An Evapotranspiration-Based Smart Irrigation Controller In Inland Southern California. Agricultural Water Management.

Haghverdi, A., Reiter, M., Singh, A., Sapkota, A. (2021). Hybrid Bermudagrass and Tall fescue Turfgrass Irrigation in Central California: II. Assessment of NDVI, CWSI and Canopy Temperature Dynamics. Agronomy. Agronomy 2021, 11, 1733. https://doi.org/10.3390/agronomy11091733.

Haghverdi, A.; Reiter, M.; Sapkota, A.; Singh, A. (2021). Hybrid Bermudagrass and Tall Fescue Turfgrass Irrigation in Central California: I. Assessment of Visual Quality, Soil Moisture and Performance of an ET-based Smart Controller. Agronomy, 11, 1666. https://doi.org/10.3390/agronomy 11081666.

Singh, A., Haghverdi, A., Nemati, M., Hartin, J. (2020). Efficient Urban Water Management: II. Weather-based Smart Irrigation Controllers. UCANR Publications.

Florida

Kadyampakeni, D.; Morgan, K.; Zekri, M.; Ferrarezi, R. S.; Schumann, A. W.; Obreza, T.A. 2021. Irrigation management of citrus trees (2021-2022 Citrus Production Guide). UF/IFAS Extension, Agronomy Department, #CPG12. EDIS Publication, URL: org/10.32473/edis-cg093-2021

Vieira, G. H. S.; Ferrarezi, R. S. Use of thermal imaging to assess water status in citrus plants in greenhouses. Horticulturae. 7(8): 249. DOI: 10.3390/horticulturae7080249

Da Silva, T. P. C. T. (g); Soares, F. T.; Matsura, E. E.; Xavier, M. A.; Ohashi, A. Y. P.; Macan, N. P. F.; Ferrarezi, R. S. Pre-Sprouted sugarcane plantlets produced in ebb-and-flow subirrigation automated by soil moisture sensors. Sugar Tech. 25(5): 974-985. DOI: 10.1007/s12355-020-00913-z

Jani, A. D.; Meadows, T. D.; Eckman, M. A.; Ferrarezi, R. S. Automated ebb-and-flow subirrigation conserves water and enhances citrus liner growth compared to capillary mat and overhead irrigation methods. Agricultural Water Management 246(106711): 1-12. DOI: 10.1016/j.agwat.2020.106711

Ferrarezi, R. S.; Jani, A. D.; James, H. T.; Gil, C.; Ritenour, M. A.; Wright, A. L. 2020. Sweet orange orchard architecture design, fertilizer and irrigation management strategies under Huanglongbing-endemic conditions in the Indian River Citrus District. HortScience. 55(12): 2028-2036. DOI: 21273/HORTSCI15390-20

Bayabil, H.K., L. Vasquez, L. Lomeli, and P. Martin. 2021. Lessons from a Landscape Irrigation Rebate Program in Miami Dade County. Journal of Extension. Journal of Extension. 59(2) 12. 10.34068/joe.59.02.13

Bayabil, H.K., J.H. Crane, K.W. Migliaccio, Y. Li, F.H. Ballen, and S. Guzman.  Programación de Riego Basado en el Método de Evapotranspiración Para Papaya (Carica papaya) en Florida. University of Florida IFAS Extension Publication #AE547. 2020/6: https://edis.ifas.ufl.edu/ae547

Bayabil, H.K., K.W. Migliaccio, M.D. Dukes, L. Vasquez, and y C. Balerdi. Consejos Basicos para Diseñar Sistemas Eficientes de Riego. University of Florida IFAS Extension. Publication #AE549.  https://edis.ifas.ufl.edu/ae539

Getachew, F., K. Bayabil, G. Hoogenboom, F.T. Teshome, and E. Zewdu. 2021. Irrigation and shifting planting date as climate change adaptation strategies for sorghum. Agricultural Water Management. 255:106988. https://doi.org/10.1016/j.agwat.2021.106988.

Kansas:

Oker, T.E., Sheshukov, A.Y., Aguilar, J., Rogers, D.H. and Kisekka, I., 2021. Evaluating Soil Water Redistribution under Mobile Drip Irrigation, Low-Elevation Spray Application, and Low-Energy Precision Application Using HYDRUS. Journal of Irrigation and Drainage Engineering, 147(6), p.04021016.

Koudahe, K., Sheshukov, A.Y., Aguilar, J. and Djaman, K., 2021. Irrigation-Water Management and Productivity of Cotton: A Review. Sustainability 2021, 131, 70.

Aguilar, J., Currie, R.S., Tomsicek, D., Haag, L. and Duncan, S., 2021. Testing Irrigated Cotton Production. Kansas Agricultural Experiment Station Research Reports, 7(7), p.6.

Aguilar, J., A. Sheshukov, C. Redmond, J. Thompson. 2021. Accessing ET for Kansas Irrigation Scheduling. K-State Research & Extension. MF2850. 2 pgs.

Louisiana

Sohoulande Djebou, C. D., S. L. D. Conger, A. A. Szogi, K C. Stone, and J. H. Martin. (2021). Seasonal precipitation pattern analysis for decision support of agricultural irrigation management in Louisiana, USA. Agric. Water Manage., 254(2021) 106970. https://doi.org/10.1016/j.agwat.2021.106970

Conger, S. L. D., R. L. Frazier, B. Garner, D. Burns, D. R. Lee, and K. Miller. (2020). On-farm furrow irrigation technology demonstrations in Louisiana. J. NACAA, 13(2).  Available at: https://www.nacaa.com/journal/index.php?jid=1149. Accessed on 19 Jan 2021.

Minnesota

Sharma, V. (2021). Crop water use and irrigation timing. University of Minnesota Extension. https://blog-crop-news.extension.umn.edu/2021/07/crop-water-use-and-irrigation-timing.html [Non-Refereed]

Sharma, V., & Fernandez, F. (2021). How to calculate a nitrogen credit from irrigation water. University of Minnesota Extension. https://blog-crop-news.extension.umn.edu/2021/07/how-to-calculate-nitrogen-credit-from.html [Non-Refereed]

Sharma*, V., Naeve*, S., & Coulter*, J. (2021). Early season drought effects on corn and soybean. University of Minnesota Extension. https://blog-crop-news.extension.umn.edu/2021/06/early-season-drought-effects-on-corn.html [Non-Refereed]

Sharma, V., & Becker*, T. (2021). It’s time to start thinking about your irrigation water management. University of Minnesota Extension. https://blog-crop-news.extension.umn.edu/2021/05/its-time-to-start-thinking-about-your.html [Non-Refereed]

Sharma, V. (2020). Checklist for winterizing your irrigation system. University of Minnesota Extension. https://blog-crop-news.extension.umn.edu/2020/10/checklist-for-winterizing-your.html [Non-Refereed]

Sharma, V., Naeve, S. N., & Coulter, J. (2021). Early season crop water use and drought stress. University of Minnesota Extension. https://strategicfarming.transistor.fm/episodes/early-season-crop-water-use-and-drought-stress [Non-Refereed]

Sharma*, V., Fernandez*, F., Becker*, T., & Nelson*, A. (2021). Irrigation and nutrient management: What to know. University of Minnesota Extension. https://blog-crop-news.extension.umn.edu/2021/06/irrigation-and-nutrient-management-what.html [Non-Refereed] Author

Oklahoma

Datta, S., Mehata, M., Taghvaeian, S., Moriasi, D., & Starks, P. J. (2021). Quantifying Water Fluxes of Irrigated Fields in an Agricultural Watershed in Oklahoma. Journal of Irrigation and Drainage Engineering, 147(7), 04021026.

Khand, K., Bhattarai, N., Taghvaeian, S., Wagle, P., Gowda, P. H., & Alderman, P. D. (2021). Modeling Evapotranspiration of Winter Wheat Using Contextual and Pixel-Based Surface Energy Balance Models. Transactions of the ASABE, 64(2), 507-519.

Taghvaeian, S., Andales, A. A., Allen, L. N., Kisekka, I., O’Shaughnessy, S. A., Porter, D. O., ... & Aguilar, J. (2020). Irrigation scheduling for agriculture in the United States: The progress made and the path forward. Transactions of the ASABE, 63(5), 1603-1618.

USDA-ARS Texas

Evett, S.R., A.I. Thompson, H.H. Schomberg, and J. Anderson. 2021. Solar node and gateway wireless system functions in record breaking polar vortex outbreak of February 2021. Accepted July 2021 by Agrosystems, Geosciences and Environment. https://doi.org/10.1002/agg2.20193. 2021.

Kutikoff, S., Z. Lin, S.R. Evett, P. Gowda, D. Brauer, J. Moorhead, G. Marek, P. Colaizzi, R. Aiken, L. Xu, and C. Owensby. 2021. Water vapor density and turbulent fluxes from three generations of infrared gas analyzers. Atmos. Meas. Tech., 14, 1253–1266, 2021. https://doi.org/10.5194/amt-14-1253-2021

Marek, G. W., Marek, T. H., Evett, S. R., Chen, Y., Heflin, K. R., Moorhead, J. E., & Brauer, D. K. 2021. Irrigation management effects on crop water productivity for maize production in the Texas High Plains. Water Conserv Sci Eng, 6(1), 37-43. https://doi.org/10.1007/s41101-020-00100-x

Marek, G.W., S.R. Evett, P.D. Colaizzi, and D.K. Brauer. 2021. Preliminary crop coefficients for late planted short-seasonsoybean: Texas High Plains. Agrosyst Geosci Environ. 2021;4:e20177. https://doi.org/10.1002/agg2.20177.

Thompson, A.I., H.H. Schomberg, S.R. Evett, D.K. Fisher, S.B. Mirsky, and S.C. Reberg-Horton. 2021. Gateway-node wireless data collection system for environmental sensing. Accepted by Agrosystems, Geosciences and Environment, 2021.

Moorehead, J.E., G.W. Marek, P.D. Colaizzi, P.H. Gowda, S.R. Evett, D.K. Brauer, T.H. Marek and D.O. Porter. 2017. Evaluation of sensible heat flux and evapotranspiration estimates using a surface layer scintillometer and a large weighing lysimeter. Sensors 2017, 17, 2350. https://doi.org/10.3390/s17102350

Tolk, J.A., S.R. Evett and R.C. Schwartz. 2015. Field-measured, hourly soil water evaporation stages in relation to reference evapotranspiration rate and soil to air temperature ratio. Vadose Zone J. http://doi.org/10.2136/vzj2014.07.0079.

https://agrilifetoday.tamu.edu/2020/01/09/amarillo-water-management-team-earns-agrilife-research-honors/

https://agrilifetoday.tamu.edu/2021/03/25/water-management-research-earns-blue-legacy-award/

Utah

Effects of Short Season Irrigation on Pasture Yield and Predicting Yield with Sentinel-2 Satellite, MS Thesis by Ihsan Bugra Bugdayci, Utah State University, December 2020

Fruit Tree Responses to Water Stress: Automated Physiological Measurements and Rootstock Responses, Ph.D. Dissertation by William D. Wheeler, Utah State University, December 2020

Development and Application of a Decision Framework to Support Improved River Basin Water Management, Ph.D. dissertation by Leah Meeks, Utah State University, August 2021

TRENDS IN US CROP YIELDS & WATER USE by Britta L. Schumacher, MS thesis, Utah State University, June 2021.

Innovative Water Management Using Advanced Irrigation Systems and Biochar by Jonathan A. Holt, MS thesis, Utah State University, May 2021.

Irrigation Water Use – Drip v. Surface Irrigation of Onions Report Utah Agricultural Water Optimization by L. Niel Allen, Alfonso Torres-Rua, Anastasia Thayer Hassett, Ryan Larsen, Matt Yost

Utah State University, July 2021.

References

USDA-ARS Texas

Moorehead, J.E., G.W. Marek, P.D. Colaizzi, P.H. Gowda, S.R. Evett, D.K. Brauer, T.H. Marek and D.O. Porter. 2017. Evaluation of sensible heat flux and evapotranspiration estimates using a surface layer scintillometer and a large weighing lysimeter. Sensors 2017, 17, 2350. https://doi.org/10.3390/s17102350

Tolk, J.A., S.R. Evett and R.C. Schwartz. 2015. Field-measured, hourly soil water evaporation stages in relation to reference evapotranspiration rate and soil to air temperature ratio. Vadose Zone J. http://doi.org/10.2136/vzj2014.07.0079.

https://agrilifetoday.tamu.edu/2020/01/09/amarillo-water-management-team-earns-agrilife-research-honors/

https://agrilifetoday.tamu.edu/2021/03/25/water-management-research-earns-blue-legacy-award/