Location: Sustainable Agricultural Water Systems Research
2022 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
This a final report for 2032-13200-001-000D (A Systems Approach to Improved Water Management for Sustainable Production) that was started on July 20, 2020, and terminated on March 16, 2022. Project 2032-13220-002-000D (Improved Agroecosystem Efficiency and Sustainability in a Changing Environment) was initiated to continue this research. For additional information, see the new project.
Field studies were initiated in support of Objective 1 to determine how drywells can be used to capture and store stormwater in aquifers in the Central Valley of California. A drywell is a vadose zone infiltration system that has a small footprint at the land surface that is installed and releases water at varying depths into the vadose zone. A farm in Helm, California, has been instrumented with sensors and infrastructure to deliver stormwater from a canal to five drywells and to monitor water flow and contaminant transport in the vadose zone and groundwater at this site. Ongoing research at this field site is exploring the independent and joint use of flooding agricultural fields and drywells for enhanced recharge and assessing impacts on groundwater quality.
Numerical experiments were also conducted in support of Objective 1 to systematically study the impact of managed aquifer recharge (MAR) approaches and designs on infiltration, recharge, and microbial water quality in homogeneous and heterogeneous soil profiles under constant head conditions. The HYDRUS (two-dimensional [2D]/three-dimensional [3D]) software program was run on a 2D-axisymmetric (36 m wide by 60 m deep) domain for this purpose. 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 drywells with infiltration basins under shared subsurface heterogeneity and steady-state flow conditions. Results demonstrated that five drywells could replace a 70 m diameter infiltration basin 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 MAR operation. Numerical experiments were therefore conducted to quantitatively examine virus transport from a drywell 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. Studies also examined designs and novel applications of drywells for agricultural settings, including their use in irrigation canal networks and repurposing dried domestic and irrigation supply wells for recharge. The use of smaller diameter and deeper drywells was determined to be the most cost-effective way to achieve large volumes of recharge, but there are still technical and regulatory challenges that need to be addressed. 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 Objective 2, satellite-based evapotranspiration (ET) models were further developed and refined to improve irrigation efficiency in specialty crops across the state of California. An open-source-based coding language for ET models was established that increased the computational efficiency of the ET model. 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 have 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. ET and soil moisture modeling activities have been expanded to additional vineyard locations throughout the Central Valley, while data transfer systems and grower-used irrigation dashboards were improved for near-real-time irrigation management during the growing season.
Objective 2-related research on satellite-based ET model estimation was expanded to almond orchards for the purpose of improving irrigation efficiency in these cropping systems as part of the Tree evapotranspiration Remote sensing EXperiment (T-REX) project. 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; LAI) are scheduled and are being used for satellite-based product validation purposes. Technical work includes progress on improving the partitioning of evaporation and transpiration in satellite-based ET modeling suites (critical due to the row/canopy-like structure of crops grown in California), fusion of ET between satellite overpass dates, acquisition of near-real-time satellite imagery for operational applications, and sensitivity analysis on inputs to satellite-based ET modeling suites. Continued technical work includes examining how vineyard management and atmospheric water stress impact irrigation efficiency, productivity, and greenhouse gas exchanges, and quantifying cover crop contributions to agroecosystem ET and carbon uptake. Established research frameworks are being expanded into new projects in pistachio, olive orchards, as well as vineyards and almonds under regenerative management. These tools are being developed to increase the likelihood of adoption of climate-smart agricultural practices and also monitor the potential of irrigated woody-perennial orchards for climate change mitigation.
In support of Objective 3, an economic optimization model was developed that can analyze adaptations to reduced water availability on croplands in California, including MAR and irrigation systems. MAR types that were considered included flood-MAR, recharge basins, drywells, and aquifer storage and recovery. Nonlinear yield functions that accounted for crop type, location, salinity, and evaporation were also included which allow different efficiency irrigation systems to predict crop yield as a function of applied water. Cost parameters for irrigation systems including furrow, flood, micro-sprinkler, sprinkler, and drip are estimated and included along with cost parameters for all MAR types. Individual watersheds’ internal spatial heterogeneity is examined so that sustainable water use can be locally targeted and accessed. Watershed specific crop mixes and appropriate irrigation methods are included as well. This modelling provides a framework upon which irrigation methods can be assessed, accounting for both their physical effects and costs of operation. It can also assess the efficiency of MAR methods and predict where in California MAR should be applied for optimal sustainability under climate change. This work is currently being used in two manuscripts—one addressing the literature gap of economics of MAR and one based on achieving sustainability under the Sustainable Groundwater Management Act.
Accomplishments
1. Innovative designs and applications for drywells. Drywells have been primarily used in urban environments to capture and store stormwater into soils. A computer model was employed by ARS researchers in Davis, California, to study the influence of drywell designs (diameters, depths, and screen intervals) on water infiltration and flow towards groundwater. Infiltration was found to increase with the drywell diameter, depth, and screening interval. However, economic analyses revealed that smaller diameter and deeper drywells were more cost effective at infiltrating a given volume of water. Repurposing of failed wells and use of drywells in irrigation canal networks are being explored as ways to infiltrate very large volumes in rural environments, but technical and regulatory challenges still need to be overcome.
2. Improving temporal resolution of evapotranspiration (ET) estimates in vineyards. Landsat satellites, which provide optimal spatial and spectral information for monitoring evapotranspiration (ET) at field scale, have low temporal revisit frequency that can be exacerbated by cloud cover. Therefore, improving the temporal frequency of field-scale estimates of ET is critical for improved irrigation management. Recent work by ARS researchers in Davis, California, has addressed this limitation by combining information from many satellite platforms and ET models, and fusing with thermal-proxies. Refined satellite predictions of ET are being used by growers to determine irrigation requirements for specialty crops across fields and throughout the growing season.
Review Publications
Lin, D., Hu, L., Bradford, S.A., Zhang, X., Lo, I.M. 2021. Pore-network modeling of colloid transport and retention considering surface deposition, hydrodynamic bridging, and straining. Journal of Hydrology. 603 Part B. Article 127020. https://doi.org/10.1016/j.jhydrol.2021.127020.
Lin, D., Hu, L., Bradford, S.A., Zhang, X., Lo, I.M. 2022. Prediction of collector contact efficiency for colloid transport in porous media using Pore-Network and Neural-Network models. Separation and Purification Technology. 290. Article 120846. https://doi.org/10.1016/j.seppur.2022.120846.
Du, Y., Bradford, S.A., Shen, C., Li, T., Bi, X., Liu, D., Huang, Y. 2021. Novel analytical expressions for determining van der Waals interaction between a particle and air-water interface: Unexpected stronger van der Waals force than capillary force. Journal of Colloid and Interface Science. 610:982-993. https://doi.org/10.1016/j.jcis.2021.11.157.
Bradford, S.A., Shen, C., Kim, H., Letcher, R.J., Rinklebe, J., Ok, Y., Ma, L. 2021. Environmental applications and risks of nanomaterials: An introduction to CREST publications during 2018–2021. Critical Reviews in Environmental Science Technology. https://doi.org/10.1080/10643389.2021.2020425.
Ohana-Levi, N., Gao, F.N., Knipper, K.R., Kustas, W.P., Anderson, M.C., Alsina, M., Sanchez, L., Kameli, A. 2021. Time-series clustering of remote-sensing retrievals for defining management zones in a vineyard. Irrigation Science. https://doi.org/10.1007/s00271-021-00752-0.
Davitt, A., Tesser, D., Gamarro, H., Anderson, M.C., Knipper, K.R., Xue, J., Kustas, W.P., Alsina, M., Podest, E., McDonald, K. 2022. The complementary uses of Sentinel1A SAR and ECOSTRESS datasets to identify vineyard growth and conditions: a case study in Sonoma County, California. Irrigation Science. https://doi.org/10.1007/s00271-022-00781-3.
Bhattarai, N., D'Urso, G., Kustas, W.P., Bambach, N., Anderson, M.C., McElrone, A.J., Knipper, K.R., Gao, F.N., Alsina, M., Aboutalebi, M., McKee, L.G., Alfieri, J.G., Prueger, J.H., Belfiore, O. 2022. Influence of modeling domain and meteorological forcing data on daily evapotranspiration estimates from a Shuttleworth-Wallace model using Sentinel-2 surface reflectance data. Irrigation Science. 40:497-513. https://doi.org/10.1007/s00271-022-00768-0.
