Research Project: Improved Agroecosystem Efficiency and Sustainability in a Changing Environment

Location: Sustainable Agricultural Water Systems Research

2024 Annual Report

Objectives
The availability of surface water and groundwater supplies for irrigated agriculture in California are adversely impacted by droughts, groundwater depletion and degradation, and increasing water demands. The overall aim of this project is to increase the efficiency and sustainability of irrigated agriculture, with a special focus on vine and tree orchard crops in the Central Valley, CA. This will be accomplished by: (i) improving irrigation efficiency; (ii) optimizing on-farm strategies for managed aquifer recharge (MAR); and (iii) assessing the long-term impacts on the sustainability of crop production, soil health, and groundwater quantity and quality. Specific objectives and subobjectives for this project are given below. Objective 1: Improve irrigation efficiency in agroecosystems by providing growers with accurate and timely estimates of spatial and temporal variations of crop ET in the field. Sub-objective 1A: Develop and validate an ET modeling framework designed to address the unique and highly structured canopy cover associated with California specialty crops. Sub-objective 1B: Improve irrigation efficiency for woody perennial crops in California by developing techniques to produce near-real-time estimates of ET from satellite data. Sub-objective 1C: Pair ET with quantified soil hydraulic and bio-meteorological properties at field-scale for better information on plant-available water within the soil column. Objective 2: Increase groundwater sustainability for irrigated agriculture by optimizing MAR strategies to capture excess surface water supplies that episodically occur during winter storms and store them into aquifers for later use. Sub-objective 2A: Quantify subsurface heterogeneity in soil properties to identify optimal locations and to better monitor and predict performance of MAR. Sub-objective 2B: Monitor and simulate the performance of MAR sites. Sub-objective 2C: Develop approaches to predict and minimize clogging and pathogen contamination at MAR sites. Sub-objective 2D: Develop and apply a computationally efficient watershed model to predict impacts of MAR on water quantity and quality. Objective 3: Assessment of the long-term impacts of irrigated agriculture on crop production, soil health, and groundwater quantity and quality under changing environmental conditions by monitoring atmospheric and subsurface fluxes and properties of soils and plants. Sub-objective 3A: Use economic analyses to assess impacts of MAR and improved irrigation efficiency on groundwater sustainability and the food-energy-water nexus.

Approach
Objective 1 will be accomplished using a combination of satellite remote sensing data, modeling, and field measurements of micrometeorological (e.g., Eddy covariance towers) and biophysical data during different phenological stages to estimate spatial and temporal variations in evapotranspiration (ET), crop stress, and irrigation requirements in vine and tree orchards crops at multiple sites in the Central Valley of California. The collected soil and bio-meteorological data will be used to validate and refine model estimates of ET from satellite imagery. Improved algorithms will be developed for near real-time ET estimates and their spatial variability in the field that can be used to improve irrigation efficiency. Objective 2 will be addressed by developing, implementing, and overcoming challenges associated with Managed Aquifer Recharge (MAR) technologies. MAR techniques that will be studied include Ag or flood MAR and drywells. Geophysical methods will be employed to identify optimal locations for MAR, to better characterize subsurface heterogeneity, and to monitoring infiltration and recharge behavior. Field sites will be characterized for soil hydraulic properties, and equipped to monitor water inputs, infiltration, recharge, and soil and water quality parameters. Complementary laboratory studies and pore-network modeling studies will be conducted to better infer underlying mechanisms controlling MAR performance, including clogging and pathogen transport and fate parameters. Collected data streams will be used in conjunction with mathematical modeling to inversely determine parameters, design improved MAR strategies that optimize water quantity and quality, and to predict long-term performance of MAR on the sustainability of groundwater and irrigated agriculture. Calibrated models will in turn be used to develop meaningful predictions of risk, management, and future performance at particular sites. A computationally efficient watershed scale model will be developed to rigorously simulate exchange of water and contaminants between surface water, the vadose zone, and groundwater. Numerical experiments will be conducted to test specific hypotheses and generalize results to other sites, water management practices, climatic conditions, and watersheds. Objective 3 involves the extension of Objectives 1 and 2 to include economic analyses to study long-term implications of remote-sensing based irrigation management tools and MAR strategies on the food-energy-water nexus, groundwater sustainability, and the long-term viability of irrigated agriculture. It also includes economic analyses of various land management practices (e.g., land fallowing), policies (e.g., the sustainable groundwater management act), and impacts on endangered species.

Progress Report
This report documents progress for project 2032-13220-002-000D, titled, “Improved Agroecosystem Efficiency and Sustainability in a Changing Environment”, which started in March 2022. Significant progress has been made on Objective 1. Research on Sub-objective 1A aimed to enhance the evapotranspiration (ET) modeling framework through the integration of satellite products from Hydrosat, Inc. and Planet Labs. ARS researchers in Davis, California, have begun to assess and incorporate their satellite-based products that promise to refine temporal sampling and spatial resolution pertinent to crop-specific phenological markers. Hydrosat, Inc.'s development of a daily, 20 m spatial resolution land surface temperature (LST) product is particularly useful, reducing our current temporal resolution gap from 8-16 days down to daily measurements, a critical advancement for our ET model. Concurrently, ARS collaboration with Planet Labs is enhancing their ability to monitor biomass at a much finer scale (~5 m), which is pivotal in evaluating the impacts of cover crops and regenerative practices on water usage and carbon sequestration in California’s specialty crops. These partnerships are expected to yield significant scientific insights into the state's agricultural practices. In support of Sub-objective 1B, extensive unmanned aerial vehicle (UAV) campaigns across diverse crop systems provided high-resolution data crucial for evaluating and validating satellite-derived estimates of normalized difference vegetation index (NDVI), leaf area index (LAI), and Albedo. These datasets allowed for the refinement of models predicting these indices from satellite platforms, offering more accurate assessments of crop conditions across conventional and regenerative farming systems. Moreover, the installation of advanced instrumentation like radiation boards and the use of ground-based LiDAR for detailed 3D crop modeling are enabling precise diagnostics of radiation partitioning and ET retrieval from satellite data. This enhanced understanding is being directly applied to improve the algorithms used in satellite-based models, ensuring that estimates of evapotranspiration are more reliable (sub-objective 1C). Additionally, our expanded network of flux measurements, now including a new table grape vineyard, is playing a critical role in validating remote sensing products, providing invaluable real-time data to stakeholders such as E&J Gallo Wineries. This comprehensive approach not only advances our modeling capabilities but also supports the broader goal of sustainable water management in California’s agriculture. Research continued on Objective 2, which focuses on evaluating managed aquifer recharge (MAR) approaches in California’s Central Valley. In support of Sub-objective 2A, ARS researchers analyzed towed time domain electromagnetic (tTEM) data of a field site outside of Chowchilla, California. tTEM data was correlated with direct-push sediment type and water content logs to assess the viability of flood-MAR operations on recently fallowed fields. The locations of these logs were selected using a Latin hypercube sampling algorithm developed by researchers at the SAWS unit, and the analysis of the logs performed in FY24 shows that the sampling design algorithm provides superior logging sites compared to those selected using expert opinion. Additionally, the mapping and logging results were integral to understanding the local hydrogeology, helping us and the landowner understand that their land is likely not suitable for these types of recharge operations. ARS researchers are in the process of extending this general methodology to additional sites in the Central Valley to assess MAR viability. In support of Sub-objective 2B, ARS researchers in Davis, California, monitored the evolution of the wetting front and water quality at a MAR site located about 20 miles southwest of Fresno, California, that employed five drywells. Water was released from the drywells over a period of around three months in FY2023. Time-lapse electrical resistivity (ERT) was used to monitor the evolution of the wetting front and recharge to a water table located at about 220 feet below land surface over the past year. The ERT imaging was correlated with point sensors inserted into the ground that give information regarding the water saturation, pressure, electrical conductivity, and temperature down to approximately 177 feet. The results have provided valuable insights about how recharge moves through a thick, heterogeneous vadose zone, how recharge efforts can mobilize solutes in the groundwater, and how the recharge water behaves after drywell injection has ceased. Water samples in the vadose zone (at depth of 25, 55, 98, 177 feet) and at the top of the unconfined aquifer (220 feet) were periodically collected and analyzed for various contaminants. Flushing of salts and nitrate were observed in water samples, but high levels of pesticides were not found. Arsenic, uranium, and chromium were found to be mobilized from in situ soils. Arsenic and chromium were mainly associated with iron oxide colloids in soil solution. The presence of clays in source water used for MAR can hamper performance by clogging the infiltrating surface. In support of Sub-objective 2C, studies were initiated to better understand and mitigate clogging in packed sand columns. Clogging was found to be sensitive to the input clay concentration, with high input clay concentrations producing greater clogging due to hydrodynamic bridging. Various best management practices to mitigate clogging were explored, including using source water below a specific turbidity threshold, implementing flow reversals, and periodically removing the top layer of sand. A pore-network model was also employed to study factors that influence clogging when straining, attachment, and blocking occurred. Results provide insight on the roles of boundary conditions, colloid size, and water velocity. In support of Sub-objective 2C, a theoretical model was developed to predict the influence of physicochemical conditions on the transport, attachment, detachment, and blocking of colloids such as pathogenic microorganisms. To accomplish Sub-objective 2D, ARS researchers are working towards developing a fully integrated coupling of KINEROS2 (K2), HYDRUS-1D (H1D), and MODFLOW models within a computationally efficient framework to simulate water flow and the transport of sediment and contaminants. The model development process is divided into two major phases: initiating the coupling strategy at a hillslope scale and then expanding this strategy to a watershed scale. Researchers made significant progress in coupling the models at the hillslope scale and upscaling them to a watershed scale for simulating water flow, sediment rate, solute, and reactive transport, paving the way for a new, computationally efficient hydrologic model. Currently, there are two completed versions of the coupled models: the H1D-K2 coupled model at the hillslope scale for water, sediment, and solute, and the H1D-K2 coupled model at the watershed scale for water flow which showed excellent accuracy, compared to benchmark simulations and experimental watershed data observations. The models were also tested to be reproducible with improved computational times. Additionally, three versions of the model are in progress: the hillslope scale reactive transport H1D-K2 model, the watershed scale H1D-K2 for water flow, sediment, and solute, and the hillslope scale coupling of the three models (KINEROS2, HYDRUS-1D, and MODFLOW). In addition, ARS researchers continued developing a high-resolution, integrated hydrologic model to enhance understanding of groundwater dynamics, recharge processes, and potential sustainable management strategies in the Turlock, Modesto, and Merced, California, groundwater subbasins. This region faces critical groundwater sustainability challenges exacerbated by historical overdraft and recurrent droughts. The model integrates spatially distributed unsaturated flow processes using HYDRUS-1D and 3D groundwater flow simulation with MODFLOW-2005 at 300 m by 300 m resolution. The steady state version of this model has been applied to compute spatially distributed recharge, transit time for infiltrated water to reach the groundwater table, understand the distribution and drivers of groundwater depletion, and estimate groundwater residence time in the model domain. Expanding the transient flow simulation is in progress to enhance the understanding of groundwater dynamics in Turlock-Modesto-Merced subbasin crucial for formulating effective management strategies and impacts of changes under the Sustainable Groundwater Management Act (SGMA). ARS researchers continue to develop their economic optimization models, designed to evaluate reduced water adaptations, including MAR and irrigation systems, per Sub-objective 3A. They have expanded the models to include the Central Valley of California, as well agricultural regions in Southern California. These models can evaluate adaptations to changing water availability, due to overuse, policy, and/or climate change on croplands in California. ARS researchers continue to examine MAR, including an assessment of the costs and benefits of different MAR types (e.g., flood-MAR, recharge basins, drywells, and aquifer storage and recovery) including in the California San Joaquin Valley. ARS researchers generated a nonlinear optimization model for irrigated croplands in the Ogallala aquifer, another arid region with over-pumping of groundwater, and assessed various scenarios for sustainable groundwater management; results which are applicable to California and other arid regions. ARS reearchers also developed The Water Adaptation Techniques Atlas (WATA), a web-based tool that organizes and presents geo-referenced case studies of climate adaption for agriculture, including irrigation systems and MAR.

Accomplishments
1. A model to predict the influence of physicochemical conditions on colloid transport in soil. The fate of colloids (such as pathogens, clays, dissolved organic matter, nanoparticles, and colloid associated contaminants) in soils and sediments needs to be quantified for many industrial and environmental applications. However, existing models cannot forecast the observed sensitivity of colloid transport to many physicochemical factors. ARS researchers in Davis, California, developed a model to predict the fate of colloids in soils by accounting for underlying removal processes for different colloid and grain sizes, water velocities, solution and solid phase chemistries, and various amounts and types of heterogeneities on grain surfaces. This model will aid in risk assessment for colloidal contaminants and in the design of processes that are influenced by colloids such as water treatment, managed aquifer recharge, petroleum recovery, and cleaning of surfaces.

Review Publications
Bambach, N., Knipper, K.R., McElrone, A.J., Nocco, M., Torres-Rua, A., Kustas, W.P., Anderson, M.C., Castro, S., Edwards, E., Duran-Gomez, M., Gal, A., Tolentino, P., Wright, I., Roby, M.C., Gao, F.N., Alfieri, J.G., Prueger, J.H., Hipps, L., Saa, S. 2023. The Tree-Crop Remote Sensing of Evapotranspiration Experiment (T-REX): A science-based path for sustainable water management and climate resilience. Bulletin of the American Meteorological Society. 105(1):E257-E284. https://doi.org/10.1175/BAMS-D-22-0118.1.
Osterman, G.K., Lesch, S., Bradford, S.A. 2024. A conditioned Latin hypercube sampling design methodology for ground-truthing transient EM resistivity models. Computers and Geosciences. 187. Article 105582. https://doi.org/10.1016/j.cageo.2024.105582.
Chen, L., Šimunek, J., Bradford, S.A., Ajami, H., Meles, M.B. 2023. Coupling water, solute, and sediment transport into a new computationally efficient hydrologic model. Journal of Hydrology. 628. Article 130495. https://doi.org/10.1016/j.jhydrol.2023.130495.
Silber-Coats, N., Elias, E.H., Steele, C., Fernald, K., Gagliardi, M., Hrozencik, A., Levers, L.R., Ostoja, S.M., Parker, L., Williamson, J.C., Yao, Y. 2024. The water adaptation techniques atlas: A new geospatial library of solutions to water scarcity in the U.S. Southwest. PLOS Water. 3(6). Article e0000246. https://doi.org/10.1371/journal.pwat.0000246.
Liang, Y., Liu, J., Dong, P., Qin, Y., Zhang, R., Bradford, S.A. 2023. Retention and release of black phosphorus nanoparticles in porous media under various physicochemical conditions. Chemosphere. 339. Article 139604. https://doi.org/10.1016/j.chemosphere.2023.139604.
Saeedimoghaddam, M., Nearing, G., Goodrich, D.C., Hernandez, M., Guertin, D., Metz, L., Wei, H., Ponce-Campos, G., Burns, I., McCord, S.E., Nearing, M., Williams, C.J., Houdeshell, C., Rahman, M., Meles, M.B., Barker, S. 2024. An artificial neural network to estimate the foliar and ground cover input variables of the Rangeland Hydrology and Erosion Model. Journal of Hydrology. 631. Article 130835. https://doi.org/10.1016/j.jhydrol.2024.130835.
Fullhart, A.T., Ponce-Campos, G., Meles, M.B., McGehee, R., Armendariz, G.A., Oliveira, P., Almeida, C., de Araujo, J., Nel, W., Goodrich, D.C. 2022. Gridded 20-year climate parameterization of Africa and South America for a stochastic weather generator (CLIGEN). Big Earth Data. 7(2):349-374. https://doi.org/10.1080/20964471.2022.2136610.
Anderson, M.C., Kustas, W.P., Norman, J., Diak, G., Hain, C., Gao, F.N., Yang, Y., Knipper, K.R., Xue, J., Yang, Y., Crow, W.T., Holmes, T., Nieto, H., Guzinski, R., Otkin, J., Mecikalski, J., Cammalleri, C., Torres-Rua, A., Zhan, X., Fang, L., Colaizzi, P.D., Agam, N. 2024. A brief history of the thermal IR-based Two-Source Energy Balance (TSEB) model – diagnosing water and energy fluxes from plant to global scales. Agricultural and Forest Meteorology. 350. Article e109951. https://doi.org/10.1016/j.agrformet.2024.109951.
Meles, M.B., Bradford, S.A., Casillas-Trasvina, J.A., Chen, L., Osterman, G.K., Hatch, T., Ajami, H., Crompton, O.V., Levers, L.R., Kisekka, I. 2024. Uncovering the gaps in managed aquifer recharge for sustainable groundwater management: A focus on hillslopes and mountains. Journal of Hydrology. 639. Article 131615. https://doi.org/10.1016/j.jhydrol.2024.131615.
Meles, M.B., Chen, L., Unkrich, C.L., Ajami, H., Bradford, S.A., Simunek, J., Goodrich, D.C. 2024. Computationally efficient watershed-scale hydrological modeling: Integrating HYDRUS-1D and KINEROS2 for coupled surface-subsurface analysis. Journal of Hydrology. 640. Article 131621. https://doi.org/10.1016/j.jhydrol.2024.131621.
Dong, P., Liang, Y., Shen, C., Jiang, E., Bradford, S.A. 2024. Dual roles of goethite coating on the transport of plastic nanoparticles in heterogeneous porous media: The significance of collector surface roughness. Journal of Hazardous Materials. 470. Article 134153. https://doi.org/10.1016/j.jhazmat.2024.134153.
Knipper, K.R., Anderson, M.C., Bambach, N., Melton, F., Ellis, Z., Yang, Y., Volk, J., McElrone, A.J., Kustas, W.P., Roby, M.C., Carrara, W., Castro, S., Kilic, A., Fisher, J., Ruhoff, A., Senay, G.B., Morton, C., Saa, S., Allen, R. 2024. A comparative analysis of OpenET for evaluating evapotranspiration in California almond orchards. Agricultural and Forest Meteorology. 355. Article 110146. https://doi.org/10.1016/j.agrformet.2024.110146.
Lapidus, D., Milliken, C., Knipper, K.R., Saa, S., Devol, T., Kustas, W.P., McElrone, A.J., Gallaher, M., Bambach, N., Anderson, M.C. 2024. Estimating the value of satellite-derived measurements of evapotranspiration to inform irrigation scheduling in California almond orchards. The Journal of Technology Transfer. 50:209-226. https://doi.org/10.1007/s10961-024-10093-7.