Location: Sustainable Agricultural Water Systems Research
2022 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 (Improved Agroecosystem Efficiency and Sustainability in a Changing Environment) which started March 17, 2022, and continues research from project 2032-13200-001-000D (A Systems Approach to Improved Water Management for Sustainable Production). For additional information, see the report for project 2032-13220-001-000D.
A base-fund increase occurred for research activities related to Objective 1 on using satellite remote sensing, mathematical modeling, and micrometeorological measurements to improve prediction of evapotranspiration (ET) and irrigation management in olive crops. We are currently in the process of coordinating field and modeling activities with stakeholders in the olive industry.
The following research activities were also conducted in support of Objective 2. Towed time-domain electromagnetic (tTEM) datasets were analyzed to identify optimum sampling locations to characterize subsurface heterogeneity at field sites. Various statistical approaches were evaluated for this purpose, including response surface sampling designs (RSSDs). Preliminary results indicate that RSSDs can be used to identify ideal sites to ground truth subsurface resistivity measurements and to relate to hydraulic properties.
A novel approach was developed as part of Objective 2 to couple one-dimensional (1D) models of overland flow and variably-saturated flow in the vadose zone. Application of these coupled 1D models to a range of scenarios (rainstorm events, soil properties, and surface slopes) showed good agreement with a more complex two-dimensional model but ran faster and can account for other processes that are usually neglected. This simplified model therefore shows great promise for computationally intensive watershed applications.
Accomplishments
Review Publications
Liang, Y., Luo, Y., Shen, C., Bradford, S.A. 2022. Micro- and nanoplastics retention in porous media exhibits different dependence on grain surface roughness and clay coating with particle size. Water Research. 221. Article 118717. https://doi.org/10.1016/j.watres.2022.118717.
Xue, J., Anderson, M.C., Gao, F.N., Hain, C., Knipper, K.R., Yang, Y., Kustas, W.P., Yang, Y., Bambach, N., McElrone, A.J., Castro, S., Alfieri, J.G., Prueger, J.H., McKee, L.G., Hipps, L., Alsina, M. 2022. Improving the spatiotemporal resolution of remotely sensed ET information for water management through Landsat, Sentinel-2, ECOSTRESS and VIIRS data fusion. Irrigation Science. 40:609-634. https://doi.org/10.1007/s00271-022-00799-7.
