Objective 1: Evaluate the effects of degraded irrigation waters on crop water use and yield at commercial production scales. Subobjective 1A: Evaluate the impact of salinity on crop water use and productivity by observing evapotranspiration and carbon fluxes in commercial almond and pistachio orchards exhibiting a range of salinities. Subobjective 1B: Develop quantitative relationships between remotely-sensed plant canopy observations and measured crop water use and productivity. Objective 2: Develop an innovative, open informatics platform for disseminating information, tools, and recommendations for the management of marginal quality irrigation and artificial recharge waters. Subobjective 2A: Develop a web-based platform for disseminating information, tools, and recommendations for evaluating and managing saline irrigation waters. Subobjective 2B: Develop improved models to support managed aquifer recharge (MAR) treatment of alternative water resources for irrigation. Objective 3: Develop a set of sensing technologies that measure soil and solution properties relevant to the use of low quality waters for irrigation, including salinity, sodicity, clay content, aluminum, iron oxides, organic matter, and soil solution boron concentration. Sensor technologies will include near-infrared (NIR), mid-infrared (MIR), and x-ray fluorescence (XRF) spectroscopy. Objective 4: Develop and evaluate an integrated system of tools for site-specific irrigation management to control soil salinity and related adverse conditions when using degraded waters. The integrated multiple-sensor system will combine the use of geospatial apparent soil electrical conductivity (ECa), y-ray spectrometry, and multi-spectral imagery. Subobjective 4A: Develop and evaluate an integrated multiple-sensor system (1) to delineate matric and osmotic stress patterns at field scale and (2) to enhance the robustness of regional-scale salinity assessment modeling. Subobjective 4B: Develop a set of integrated tools to diagnose and manage infiltration problems due to sodic conditions by modeling the chemical effects on infiltration reduction and quantifying soil sodicity.
Drought, climate change, and competition for resources are reducing the availability of irrigation water and farmland in arid and semi-arid regions. One strategy for maintaining or enhancing productivity in the face of diminished resource availability is to make greater use of marginal lands and alternative water sources, both for irrigation and for recharging depleted aquifers. Sustainable use of low-quality waters requires soil, water, and crop management practices that optimize crop production and aquifer recharge while minimizing the degradation of natural resources by salts and other contaminants. Advanced multi-sensor technologies, models, and decision-support tools are needed to evaluate alternative management practices and to assist growers and water managers in satisfying increasingly stringent regulations. In this project, we propose a combination of field studies and laboratory experiments designed to develop knowledge and technologies needed to enable optimal use of fresh, degraded, and recycled waters for irrigation and recharge. In the laboratory, we undertake a series of experiments to test the hypothesis that portable near-infrared (NIR), mid-infrared (MIR), and x-ray fluorescence (XRF) sensors can be calibrated to measure soil chemical properties, and ultimately can be used in the field to observe changes in soil properties and guide management. The influences of soil texture, mineralogy, EC, pH, ESP, water content, and surface roughness on sensor calibration and performance will be assessed. A second group of experiments will evaluate the effects of irrigation water quality (SAR, pH, EC) on the long-term impact of irrigation and rainfall on the infiltration capacity of soils of varying textures. Two major field campaigns are planned. In the first, we field-test a multi-sensor platform for delineating field-scale spatial variations in soil salinity and texture and identifying associated matric and osmotic stress patterns. The platform consists of gamma ray (y-ray) and electromagnetic induction (EMI) instrumentation in combination with Landsat 7 multi-spectral imagery. In the second campaign, we use micro-meteorological methods to evaluate field-scale crop productivity and water-use across a network of research sites in commercial orchards exhibiting a range of soil salinities and irrigation water qualities. Finally, we develop modeling tools focusing on two problems associated with alternative waters and managed aquifer recharge operations: (i.) decreasing infiltration due to soil clogging by colloids; and (ii.) infiltration depths and setback distances required to ensure microbial safety at groundwater extraction points. And lastly we develop an open, web-based informatics platform for disseminating information, models, and decision-support for the use of saline irrigation waters. The project should lead to improved recommendations for managing alternative water resources for irrigation and recharge, and produce new capabilities for predicting the effects of management decisions on crop yields and on soil and water quality.
During FY19, this project merged with project 2036-61000-017-00D. Objectives 3 and 4 of the current project came from 2036-61000-017-00D. For a progress report on those objectives and associated milestones, see the FY19 (final) report of 2036-61000-017-00D. Objective 1 of this project involves monitoring and modeling water use and crop productivity in five commercial almond and pistachio orchards using irrigation waters of varying quality. During FY19, operation of the monitoring sites established in FY17 continued (Sub-objective 1A). The monitoring sites consist of eddy covariance (ECV) towers and instrumentation, plus soil monitoring instrumentation. Data analysis for ECV sites has begun, and infrastructure has been established on an established repository (Ameriflux) for eventual data archiving. A cooperating graduate student from University of California, Riverside, (project 2036-61000-018-02S) has continued incorporating the soil water content and electrical conductivity observations in her modeling research. Analysis of priority soil samples was completed in FY19 along with site specific soil sensor calibrations and evaluation of irrigation amounts and timing based on system information and sensor data. Preliminary remote sensing work has been done to relate satellite data to measured crop water use and productivity. The focus of Objective 2 is the development of informatics and modeling tools for salt-affected irrigated agricultural systems and for managed aquifer recharge operations. In FY19, under Objective 2A, we released Fluxpart (version 0.2), a computer program that processes data from eddy covariance monitoring systems to determine water vapor and carbon dioxide fluxes in agricultural fields and other landscapes. Water and carbon dioxide flux data provide information about plant growth and water use that is essential in many kinds of agronomic and climate research, including our field work under Objective 1. The new version of the code has significantly improved capabilities for handling large volumes of data (big data) and a refined flux partitioning algorithm. Also in FY19, coding began on a web implementation of RETC. The RETC software is the industry standard for analyzing and modeling the water retention and hydraulic conductivity of properties of unsaturated soils. Under Objective 2B, research was directed to improve our understanding of various Managed Aquifer Recharge strategies. New and old drywells at the National Training Center in Fort Irwin, California, were instrumented with water level and turbidity sensors to monitor their infiltration behavior and clogging over time. Analysis of collected particle size distributions during the new drywell installation and inverse simulations have been performed to determine temporal and spatial changes in soil hydraulic properties at this site. Numerical experiments have been conducted to quantify the influence of subsurface heterogeneity and soil type on the amount, timing, and extent of recharge from a drywell. This information is needed to assess the impact of drywells on groundwater quantity and quality. Numerical experiments have also been conducted to assess factors that influence the fate of viruses at an Aquifer Storage and Recovery (ASR) site in Australia, including virus retention and inactivation, storage time, and subsurface soil heterogeneity. An improved understanding of these factors can be used to optimize the performance of ASR to remove pathogens, minimize the risks to human health, and reduce the need for expensive pre- or post-treatments. This research was partially supported by an interagency agreement with the Environmental Protection Agency.
1. Assessment of future water availability for agriculture. California has high variability in water availability, and the potential for extended future droughts with changes in climate is widely perceived to be a substantial risk. However, models have high uncertainty with respect to future precipitation climatology, with some models showing substantially drier future climates while others show increasing precipitation. An ARS scientist in Riverside, California, and collaborators tested climate models based on their ability to reproduce El Niño, which has a major impact on the likelihood of a wet winter in California and high agricultural water availability. Models that did a better job of simulating El Niño showed a significantly lower risk of drought. However, precipitation was increasingly concentrated in core winter months (December, January, and February) and in major rain storms that can produce floods that flow directly to the ocean. These results suggest that added agricultural water storage capacity will be needed to effectively mitigate against warmer and drier summer periods and to maintain the same relative agricultural water availability.
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