Research Project: A Systems Approach to Improved Water Management for Sustainable Production

Location: Sustainable Agricultural Water Systems Research

2021 Annual Report

Objectives
Objective 1: Develop technologies to enhance the sustainability of water resources for crop production that account for the processes governing movement, storage, quantity and quality of water and water re-use. Objective 2: Develop a production system decision support toolkit for water management by producers that accounts for interacting GxExMxP factors. Objective 3: Quantify and enable management of the effects of new water management strategies on crop production responses by assessing genotype x environment x limited-water and water re-use management (GxExMxP) interactions for different land use, management, and climate scenarios at field to watershed scales.

Approach
Objective 1 will be addressed by developing, implementing, and overcoming challenges associated with Managed Aquifer Recharge (MAR) technologies to store episodic excess surface water supplies in aquifers to mitigate flooding and groundwater depletion, and for later use by agriculture. Other degraded water resources may also be considered for MAR operations. Potential MAR techniques that will be studied include Ag or flood MAR, subsurface leach fields (reverse of tile drains), drywells, infiltration basins, and injection well approaches. Research will address ways to mitigate clogging, optimize treatment of source water, and operate MAR sites to ensure recharge water quality over a range of soil types and climatic conditions. 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 will be conducted to better infer underlying mechanisms controlling MAR performance. 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. These models may include conventional deterministic models, stochastic models, empirical algorithms, and/or machine learning approaches to account for groundwater-surface water interactions at various scales. Objectives 2 and 3 will be accomplished using a combination of airborne and satellite remote sensing data, field measurements of micrometeorological (e.g., Eddy covariance towers) and biophysical data during different phenological stages, and modeling to estimate spatial and temporal variations in evapotranspiration (ET), crop stress, and irrigation requirements in high-value crops like vineyards and orchards. This information is expected to improve field-scale irrigation efficiency and thereby reduce water demands and increase crop quality and productivity. These research activities will continue over the long-term and be expanded to maximize yield and/or crop quality, efficient use of water on farms, and to assess impacts of irrigation practices on groundwater recharge at different scales. Decision support toolkits will be developed for growers to improve field-scale crop and irrigation management. The wide-spread acceptance and application of such tools are critical to ensure the long-term sustainability of irrigated agriculture and groundwater resources, especially during periods of drought. Economic analyses will be employed to study long-term implications of MAR strategies and remote-sensing based irrigation management tools on the food-energy-water nexus, groundwater sustainability, and the long-term viability of irrigated agriculture. This research will support objectives 1-3.

Progress Report
In support of Objective 1, research was conducted to assess the impacts of infiltration basins (IBs), drywells (DWs), and flooding agricultural land (AgMAR) on groundwater quantity and quality. Numerical experiments were conducted on a 2D-axisymmetric (36 m wide by 60 m deep) domain using the HYDRUS (2D/3D) software to systematically study DW infiltration, recharge, and microbial water quality in homogeneous and heterogeneous soil profiles under constant head conditions. The influence of stochastic subsurface heterogeneity parameters on infiltration and recharge rates and cumulative volumes, the radius of recharge, and early and late arrival times and locations were determined. Additional simulations compared the performance of DWs with IBs under shared subsurface heterogeneity and steady-state flow conditions. Results demonstrated that five DWs could replace a 70 m diameter IB to achieve significantly higher infiltration and recharge over 20 years of operation. In addition to water quantity, groundwater quality management is an essential aspect of public health and successful managed aquifer recharge (MAR) operations. Numerical experiments were therefore conducted to quantitatively examine virus transport from a DW under various virus removal and subsurface heterogeneity conditions. Virus detachment, solid phase inactivation, and subsurface heterogeneity were critical factors in determining the risk of groundwater contamination. Ongoing research at a field site in the Central Valley, California, is exploring the independent and joint use of AgMAR and DWs for enhanced recharge and assessing impacts on groundwater quality. This research is expected to increase the widespread acceptance of various on-farm MAR technologies to increase the long-term viability of groundwater to sustain irrigated agriculture, as well as to provide government regulators with critical science-based findings and tools to manage water resources. This research was partially supported by an interagency agreement with the Environmental Protection Agency and a USDA, National Institute of Food and Agriculture (NIFA) grant. In support of Objectives 2 and 3, research continued to develop satellite remote sensing-based evapotranspiration (ET) models for the purpose of improving irrigation efficiency in specialty crops across the state of California. An open-source-based coding language for ET models was developed. This has allowed certain processes within the model structure to be completed in a faster, more straightforward manner. It has also allowed for cloud computing of satellite-based products, saving time and computing resources. ET estimates were also provided to stakeholder-owned vineyards on a weekly basis to inform irrigation management strategies. A priori parameter specification and satellite-based products specific to vineyards have improved model estimates of ET over the unique canopy structures characteristic of vineyards. We made progress on data assimilation of satellite-based information, including ET, into a soil moisture estimation model. This model is referred to as the Vineyard Data Assimilation (VIDA) model, and it has been paired with the ET model on a weekly basis to provide soil moisture estimates for stakeholder-owned vineyards. Research related to satellite-based ET model estimation has expanded to almond orchards for the purpose of improving irrigation efficiency in these cropping systems. Three study sites have been chosen with stakeholder insight. All three have flux towers installed for satellite ET validation purposes and field campaigns for ground measurements of other specific plant physiological characteristics (e.g. Leaf Area Index) are scheduled and are being used for satellite-based product validation purposes.

Accomplishments
1. Simulated recharge from drywells and infiltration basins compared. Infiltration basins and drywells are commonly used to capture stormwater and recharge groundwater, but their performance has not been previously compared. ARS researchers in Davis, California, employed a computer model to simulate the behavior of both recharge approaches. Results demonstrate that five drywells can replace a 70m diameter infiltration basin to achieve significantly higher infiltration and recharge over 20 years of operation. In addition, a drywell can facilitate rapid infiltration and recharge, and minimize contaminant leaching from shallow clay layers by releasing water below them. These results will be of interest to scientists, engineers, water managers, and government regulators concerned with sustainable groundwater management.

2. Impact of simulated drywell recharge on groundwater virus contamination. Drywells are increasingly used for stormwater capture and aquifer recharge, but there is a potential risk of microbial contamination. Numerical experiments were therefore conducted by ARS researchers in Davis, California, to study virus transport from a drywell under different removal and soil layering scenarios. The setback distance between the bottom of the drywell and the groundwater table to protect groundwater quality was found to be much larger than the currently recommended guideline under many instances. Virus detachment, solid phase inactivation, and subsurface heterogeneity were critical factors in determining the risk of groundwater contamination that can be mitigated by intermittent use of the drywell and in-situ soil treatment with iron compounds. These results will be of interest to scientists, engineers, water managers, government regulators, and public health officials concerned with microbial risks to groundwater during Managed Aquifer Recharge (MAR) operations.

3. Evapotranspiration retrievals capable of deciphering water use in different California vineyards. Mapping the spatial variability of evapotranspiration (ET) across vineyards is useful for optimizing irrigation scheduling and efficiency, leading to conservation of water resources and more sustainable wine grape production. ARS scientists in Davis, California, developed and refined an ET model based on satellite information to monitor ET over vineyards. This model has proven reliable over starkly different vineyards found across the diverse state of California. A reliable spatial ET product at scale has the potential to improve water allocation and conservation efforts by identifying areas of uneven water use due to variations in soil texture and composition and other environmental or anthropogenic factors. Beneficiaries of the model include growers reliant on irrigation for production, with specific, more immediate benefits to growers of crops that share similar plant physiological characteristics with vineyards.

4. Sharpening land surface temperature using harmonized Landsat-Sentinel surface reflectance. Land surface temperature (LST) is a key diagnostic indicator of agricultural water use and crop stress. However, LST data tends to have coarser spatial resolution than surface reflectance (SR) data. Spatial sharpening of LST data using higher resolution SR data provides an important path to improve agricultural monitoring at sub-field scales. ARS scientists in Davis, California, modified a Data Mining Sharpening (DMS) approach to sharpen LST from ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Visible Infrared Imaging Radiometer Suite (VIIRS) platforms. Modifications improved sharpening accuracy over the standard DMS. This work facilitates the development of a prototype system that generates high spatiotemporal resolution LST products for improved agricultural water use monitoring by synthesizing multi-source remote sensing data. An improved agricultural water use monitoring system via high spatiotemporal resolution LST will benefit growers that rely on irrigation for production, as it will lead to water and cost savings through efficiencies in application.

Review Publications
Sasidharan, S., Bradford, S.A., Simunek, J., Kraemer, S.R. 2020. Comparison of simulated recharge from drywells and infiltration basins: a modeling study. Journal of Hydrology. 594. Article 125720. https://doi.org/10.1016/j.jhydrol.2020.125720.
Sasidharan, S., Bradford, S.A., Simunek, J., Gerba, C.P., Kraemer, S.R. 2021. Virus transport from drywells under constant head conditions: a modeling study. Water Research. 197. Article 117040. https://doi.org/10.1016/j.watres.2021.117040.
Liang, Y., Luo, Y., Lu, Z., Klumpp, E., Shen, C., Bradford, S.A. 2021. Evidence on enhanced transport and release of silver nanoparticles by colloids in soil due to modification of grain surface morphology and co-transport. Environmental Pollution. 276. Article 116661. https://doi.org/10.1016/j.envpol.2021.116661.
Zhang, M., Bradford, S.A., Klumpp, E., Šimunek, J., Jin, C., Qiu, R. 2020. Non-monotonic contribution of nonionic surfactant on the retention of functionalized multi-walled carbon nanotubes in porous media. Journal of Hazardous Materials. 407. Article 124874. https://doi.org/10.1016/j.jhazmat.2020.124874.
Shen, C., Bradford, S.A. 2021. Why are viruses spiked? mSphere. 6(1). Article e01339-20. https://doi.org/10.1128/mSphere.01339-20.
Lin, D., Hu, L., Bradford, S.A., Zhang, X., Lo, I.M. 2021. Simulation of colloid transport and retention using a pore-network model with roughness and chemical heterogeneity on pore surfaces. Water Resources Research. 57(2). Article e2020WR028571. https://doi.org/10.1029/2020WR028571.
Wendroth, O., Bradford, S.A., Harter, T. 2021. Transdisciplinary contributions and opportunities in soil physical hydrology. Vadose Zone Journal. 20(2). Article e20114. https://doi.org/10.1002/vzj2.20114.
Knipper, K.R., Kustas, W.P., Anderson, M.C., Nieto, H., Alfieri, J.G., Prueger, J.H., Hain, C.R., Gao, F.N., McKee, L.G., Mar Alsina, M., Sanchez, L. 2020. Using high-spatiotemporal thermal satellite ET retrievals to monitor water use over California vineyards of different climate, vine variety and trellis design. Agricultural Water Management. 241. Article 106361. https://doi.org/10.1016/j.agwat.2020.106361.
Anderson, M.C., Yang, Y., Xue, J., Knipper, K.R., Yang, Y., Gao, F.N., Hain, C., Kustas, W.P., Cawse-Nicholson, K., Hulley, G., Fisher, J., Alfieri, J.G., Meyers, T., Prueger, J.H., Baldocchi, D., Sanchez, C. 2020. Interoperability of ECOSTRESS and Landsat for mapping evapotranspiration time series at sub-field scales. Remote Sensing of Environment. 252. Article 112189. https://doi.org/10.1016/j.rse.2020.112189.
Xue, J., Anderson, M.C., Gao, F.N., Hain, C., Sun, L., Yang, Y., Knipper, K.R., Kustas, W.P., Torres, A., Schull, M. 2020. Sharpening ECOSTRESS and VIIRS land surface temperature using harmonized Landsat-Sentinel surface reflectances. Remote Sensing of Environment. 251. Article 112055. https://doi.org/10.1016/j.rse.2020.112055.