Research Project: Advancing Water Management and Conservation in Irrigated Arid Lands

Location: Water Management and Conservation Research

2019 Annual Report

Objectives
The long-term objectives of this project are to develop decision support tools and sensing and computing technologies to support improved crop water use efficiency for irrigated agriculture in arid lands. Objective 1: Develop and integrate models, tools, and strategies to optimize water and nutrient use efficiencies under sufficient, reduced, and variable-rate irrigation strategies in arid environments. Subobjective 1A: Quantify cotton physiological development, fiber yield, fiber quality, and water use responses to variable irrigation rate and timing. Subobjective 1B: Develop end-user irrigation scheduling models for cotton and other crops. Subobjective 1C: Develop nitrogen fertilizer scheduling strategies and tools for cotton. Objective 2: Use remote and proximal sensing at regional and field scales for crop and water management and use proximal sensing for high throughput phenotyping for heat and drought tolerant cultivars. Subobjective 2A: Develop and evaluate airborne and satellite-based remote sensing methods to estimate crop evapotranspiration, ETc, at irrigation district scale. Subobjective 2B: Develop and evaluate airborne and drone-based remote sensing methods to estimate crop evapotranspiration, ETc, at field scale. Subobjective 2C: Develop and evaluate ground-based proximal sensing methods that identify crop heat and drought stress at field scale. Objective 3: Develop and evaluate crop simulation models as tools to synthesize “big” data from agricultural field studies and analyze alternative strategies for crop and water management. Subobjective 3A: Evaluate and improve Cotton2K and DSSAT-CSM models for simulation of cotton physiology, water use, and nutrient use in response to water and nutrient deficit. Subobjective 3B: Develop crop simulation modeling methodologies to analyze potential water savings and production impacts of variable-rate and deficit irrigation practices. Subobjective 3C: Develop methodologies to guide crop simulation and irrigation scheduling models using “big data” from remote and proximal sensing and crop and soil mapping equipment. Objective 4: Develop concepts, technologies, and software tools for the hydraulic analysis of surface irrigation systems. Subobjective 4A: Develop software for the hydraulic analysis of irrigation systems. Subobjective 4B: Model irrigation-induced soil erosion. Subobjective 4C: Develop field technologies for improved surface irrigation management.

Approach
Objective 1 Goal 1A: Conduct cotton field experiments using a new VRI system on a lateral move overhead sprinkler to deliver precise irrigation treatments to cotton. Goal 1B: Develop improved irrigation scheduling models and software that account for spatial water application and crop water use in irrigation management and provide guayule growers with new irrigation scheduling tools. Goal 1C: Develop improved N management scheduling models and software that will help optimize the N fertilizer application rate guidelines for cotton under lateral move overhead sprinkler and subsurface drip irrigation. Objective 2 Goal 2A: Reduce ETc estimation uncertainty and bias at irrigation district scales by integrating sensing technologies with weather-based approaches. Goal 2B: Develop a field-scale decision support system for mapping ETc using drone platforms. Goal 2C: Demonstrate that field-based high-throughput plant phenotyping with proximal sensors could be an effective approach for crop breeding. Objective 3 Goal 3A: Conduct evaluations of the Cotton2K and DSSAT-CSM cotton simulation models and identify options for model improvement. Goal 3B: Conduct simulation analyses to assess effects of variable-rate irrigation management practices on crop production and water use. Goal 3C: Develop mathematical approaches for integrating remote and proximal sensing data with irrigation scheduling models and crop simulation models. Objective 4 Goal 4A: Enhance the functionality of the WinSRFR software package by improving the design procedures to account for flow-depth dependent infiltration, developing procedures for furrow systems with return flow, and developing procedures for predicting the transverse distribution of infiltrated water in a furrow cross section based on soil textural properties. Goal 4B: Development and testing of a process-based model of sediment transport coupled to surface irrigation flow. Goal 4C: Develop a process for evaluating the field-level seasonal performance of an irrigation system and developing field technologies for acquiring irrigation evaluation data reliably and inexpensively.

Progress Report
Under Sub-objective 1A, the third season of a cotton irrigation experiment in Maricopa, Arizona, was completed in 2018, irrigated by a linear move irrigation machine. These experiments were conducted to evaluate cotton yield responses to variable irrigation rates and timing during the growing season. Sixteen experimental treatments were established based on four irrigation rates (60%, 80%, 100%, and 120% of recommended amounts from an irrigation scheduler) and two timings (from squaring to peak bloom and from peak bloom to 90% open boll). Soil moisture in each plot was measured weekly. On a biweekly basis, plants in each treatment were sampled to assess crop development and measure weights of plant parts. Cotton yield and fiber quality were measured for each irrigation treatment. The experiments provide important verification of the performance of irrigation scheduling models and provide data for model improvement. Under Sub-objective 1B, substantial progress was made for the web-based interface of the programmed soil water balance irrigation scheduling tool, which will be hosted by a University of Arizona collaborator in Tucson. Evapotranspiration (ET) data from the third year (2018) cotton subsurface drip irrigation experiment was determined for the 100% and 70% irrigation levels. The measured and predicted cotton ET using remote sensing are currently being evaluated for the 2018 field data. Progress was made for guayule irrigation management by developing crop coefficients for guayule grown with subsurface irrigation. Current irrigation experiments initiated in 2018 at two Arizona sites (Eloy and Maricopa) are developing crop coefficients for guayule that was directly-seeded in plots. These data will be compared to the guayule crop coefficients developed in previous guayule studies, in which guayule seedlings were transplanted in the field. Under Sub-objective 1C, the third year of three years of Nitrogen (N) by water subsurface drip irrigation studies for cotton in Maricopa, Arizona, is complete and yielding valuable new information on management guidelines. Recovery efficiency of added liquid N fertilizer was again as high as 91%. Nitrous oxide emissions are extremely low in this system. Proximal sensing-based N management is showing N fertilizer savings without a reduction in lint yields, but in 2018 there was a reduction in seed yields. In support of Objective 2, development of remote and proximal sensing methods to monitor irrigated crop water at district, farm, and plot scales continued for farms in Yuma and Maricopa, Arizona. Private and Native American farms were visited. Crops considered included durum wheat, melon, cotton, Sudangrass, barley, spinach, broccoli, and cauliflower. Ground observations of ET were conducted at 13 sites using eddy covariance instruments and soil moisture measurements. Satellite observations in visible/near infrared wavelengths using Landsat 8, Sentinel 2, and Venus were used to create vegetation cover maps and crop coefficient curves. Thermal infrared data from Landsat, and the recently launched ECOSTRESS sensor, were used to improve ET models of crop water status. Preliminary results indicate that standardized ET estimates under-estimate water use by 20% or more. Proximal sensing of 432 elite varieties of durum wheat was conducted using multispectral and LIDAR scanning from a drone, and laser scanning from the Terraref Scanalyzer (https://terraref.org). In support of Objective 3, extensive simulations with a cotton simulation model have been conducted on the ARS SciNet cluster computer. A comprehensive analysis of temporal weather patterns and spatial soil patterns on cotton production was conducted at the Maricopa Agricultural Center in Arizona. Assessments of irrigation requirements for cotton production among the different weather and soil patterns were performed. The assessments were designed to quantify the potential for site-specific irrigation management to save water and/or improve cotton yield in central Arizona. Under Sub-objective 4A, computational procedures required to carry out the method-of-moments analysis for furrow infiltration were developed and tested. The objective of this work is to develop a tool that can be used to approximately describe the distribution of water beneath a furrow as a function of, among other factors, soil texture and furrow geometry. Procedures currently used to simulate furrow infiltration in surface irrigation models, including the WinSRFR software package developed by researchers in Maricopa, Arizona, compute only the total volume per unit length, but do not provide a measure of the transverse distribution of water, and thus potentially underestimate the volume of water stored in the root zone. The analysis consists of running infiltration simulations, utilizing a variably-saturated soil water flow model based on the two-dimensional Richards equation, under a range of soil textures, initial, and boundary conditions. Outputs from those simulations are used to calculate the mean infiltration, centroid location, and variance (the moments) of the infiltration distribution. Procedures for the moment calculations that were initially developed did not account correctly for the two-dimensional geometry of the computational domain. Those errors were resolved. The number of combinations of soils, furrow geometries, initial and boundary conditions that may be required for the analysis is potentially infinite. To reduce the scope of the analysis, initial tests were conducted comparing infiltration from one-dimensional strips to furrows of different geometries. Those initial results appear to confirm the hypothesis that the moments are similar for strips and furrows of any cross-sectional shape, but with the same wetted perimeter. Thus, it may be possible to represent all possible furrow geometric configurations simply as one-dimensional strips. Under Sub-objective 4C, furrow infiltration data collected over multiple irrigation events and three irrigation seasons are being examined in collaboration with an ARS scientist at Kimberly, Idaho. The objective is to assess the spatial and temporal variability of infiltration, and how that variability affects irrigation performance from one season to the next. The analysis also quantifies the potential effect of polyacrylamide on infiltration. An understanding of the variability of spatial and seasonal variation of infiltration is essential to the development of design guidelines and control systems for irrigation systems. Development of field sensors that can be used to evaluate surface irrigation systems by measuring depth of water in furrows is continuing. Since the systems failed to perform adequately under field conditions (unreliable data capture), modifications are being tested.

Accomplishments
1. Satellite remote sensing quantifies irrigated crop water use in Arizona. Persistent drought and declared water shortages are threatening the sustainability of farms in Central Arizona. Known methods to conserve crop water resources, such as land leveling and use of pressurized irrigation, can be effective management tools; however, accurate water use amounts are lacking, meaning that policy planning and on-farm decision making are difficult. ARS researchers in Maricopa, Arizona, used satellite remote sensing images and water balance models to quantify water use by cotton, wheat, and alfalfa in the Central Arizona Irrigation District. The methods and the values derived from them provide important tools and baseline data for farmers and district managers to assess their current and future irrigation needs.

2. Development of WinSRFR 5 completed. Surface irrigation systems still account for nearly 40% of the irrigated surface in the U.S. Many of those systems are inadequately designed, and as a result, produce large water losses. Performance of those systems can be improved with the assistance of hydraulic analysis tools. ARS researchers in Maricopa, Arizona, completed the development of Version 5 of WinSRFR, a software package for the analysis of surface irrigation systems that is being released to National Resources Conservation Service (NRCS), the primary user of the software, and to the general public. Key software enhancements include the addition of procedures for modeling furrow infiltration based on physical principles, a module for modeling fertigation events (solute transport), new design options for furrows, and a new module for the estimation of infiltration and hydraulic resistance parameters (inverse solution). Simulation and field studies have validated the usefulness of this infiltration modeling approach.

Review Publications
Kothari, K., Ale, S., Bordovsky, J.P., Thorp, K.R., Porter, D.O., Munster, C.L. 2019. Simulation of efficient irrigation management strategies for grain sorghum production over different climate variability classes. Agricultural and Forest Meteorology. 170:49-62. https://doi.org/10.1016/j.agsy.2018.12.011.
Thorp, K.R., Thompson, A.L., Harders, S.J., French, A.N., Ward, R.W. 2018. High-throughput phenotyping of crop water use efficiency via multispectral drone imagery and a daily soil water balance model. Remote Sensing. 10(11):1682. https://doi.org/10.3390/rs10111682.
Chen, X., Thorp, K.R., Ouyang, Z., Hou, Y., Li, Y. 2019. Energy consumption due to groundwater pumping for irrigation in the North China Plain. Science of the Total Environment. 669:1033-1042.
Thompson, A.L., Thorp, K.R., Andrade-Sanchez, P., Conley, M.M., Heun, J.T., Dyer, J.M., White, J.W. 2018. Deploying a proximal sensing cart to identify drought-adaptive traits in upland cotton for high-throughput phenotyping. Frontiers in Plant Science. 9:507. https://doi.org/10.3389/fpls.2018.00507.
Lamsal, A., Welch, S.M., White, J.W., Thorp, K.R., Bello, N. 2018. Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics. PLoS One. 13(4):e0195841. https://doi.org/10.1371/journal.pone.0195841.
Thompson, A.L., Thorp, K.R., Conley, M.M., French, A.N., Andrade-Sanchez, P., Pauli, D. 2019. Comparing nadir and multi-angle view sensor technologies for measuring in-field plant height of upland cotton. Remote Sensing of Environment. 11:700-719. https://doi.org/10.3390/rs11060700.
Kimball, B., Boote, K., Hatfield, J.L., Ahuja, L.R., Stockle, C., Archontoulis, S., Caron, C., Basso, B., Bertuzzi, P., Constantin, J., Deryng, D., Dumont, B., Durand, J., Ewert, F., Gaiser, T., Gayler, S., Hoffmann, M.P., Jiang, Q., Kim, S., Lizaso, J., Moulin, S., Nednel, C., Parker, P., Palosuo, T., Priesack, E., Qi, Z., Srivastava, A., Tommaso, S., Tau, F., Thorp, K.R., Timlin, D.J., Twine, T.E., Webber, H., Willaume, M., Williams, K. 2019. Simulation of maize evapotranspiration: an inter-comparison among 29 maize models. Agricultural and Forest Meteorology. 271:264-284.
Bronson, K.F., Hunsaker, D.J., Thorp, K.R. 2019. Nitrogen fertilizer and irrigation effects on seed yield and oil in camelina. Agronomy Journal. 111(4):1712-1719. https://doi.org/10.2134/agronj2018.10.0644.
Hunsaker, D.J., Elshikha, D.M., Bronson, K.F. 2019. High guayule rubber production with subsurface drip irrigation in the US desert southwest. Agricultural Water Management. 220:1-12. https://doi.org/10.1016/j.agwat.2019.04.016.
French, A.N., Hunsaker, D.J., Bounoua, L., Karnieli, A., Luckett, W., Strand, B. 2018. Remote sensing of evapotranspiration over the central Arizona irrigation and drainage district, U.S.A. Agronomy Journal. 8(12):278.
Guzman-Rojo, D.P., Bautista, E., Gonzalez-Trinidad, J., Bronson, K.F. 2018. Variability of furrow infiltration and estimated infiltration parameters in a macroporous soil. Journal of Irrigation and Drainage Engineering. 145(2):04018041. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001366.