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Water Management and Conservation Research

Research is proposed to develop improved methods for quantifying crop evapotranspiration (ET_c) at field to regional scales, and improved remote sensing approaches and tools for monitoring and managing spatial variability of crop water use in irrigated systems. The three primary objectives of the research are the following: 1) Determine crop coefficients, adjustment algorithms, and transfer capabilities for improving crop water use estimation of common and alternative crops in arid Southwestern U.S. climates. Basal crop coefficient (K_cb) models for cotton, wheat, and two oilseed crops, camelina and lesquerella, will be developed locally for use in the FAO-56 reference ET approach. Algorithms for adjusting standard K_cb models to account for water stress and non-standard plant densities will be tested. 2) Develop and verify remote sensing methods and techniques for predicting near real-time ET_c and plant water stress at spatial scales relevant for single fields to watersheds, including remotely sensed coefficients for use in FAO-56 applications, and surface energy balance models utilizing remote sensing for large scale ET_c and water stress assessment. 3) Develop high resolution remote sensing decision support tools for managing spatially and temporally variable water and nutrient applications to crops, including improved remote sensing indices and techniques for monitoring variable plant-canopy conditions, statistical algorithms for directing efficient sampling routines for ground-based and unmanned aerial data acquisition systems, and data assimilation techniques for combining remote sensing data and predictive capabilities of plant growth models. Six, full-season field experiments will provide new data to develop, demonstrate, and validate the methods.