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Restricted water allocations: Landscape-scale energy balance simulations and adjustments in agricultural water applications

Ramesh Dhungel, Robert Aiken, Xiaomao Lin, Shannon Kenyon, Paul D. Colaizzi, Ray Luhman, R. Louis Baumhardt, Dan O’Brien, Seth Kutikoff, David K. Brauer
Agricultural water management 2020 v.227 pp. 105854
algorithms, aquifers, automation, biophysics, crops, deficit irrigation, dry environmental conditions, energy balance, evapotranspiration, groundwater, irrigation rates, irrigation scheduling, irrigation water, landscapes, meteorological data, satellites, simulation models, surface temperature, vegetation index, water supply, Kansas
Research that incorporates information from satellites into conventional biophysical models has great importance and interest. Comprehensive crop water algorithms can help track crop stress, schedule irrigation, and acquire water right information for effective water management and increased productivity in semi-arid and arid environments. Overall objective was to utilize the automated biophysical surface energy balance model BAITSSS (Backward‐Averaged Iterative Two‐Source Surface temperature and energy balance Solution) to understand critical agricultural water management issues. BAITSSS served as an advanced digital landscape crop water tracker and irrigation scheduler to simulate hourly landscape evapotranspiration (ET) at 30 m spatial resolution. North American Land Data Assimilation System (NLDAS) weather data and Landsat-based vegetation indices were inputs of BAITSSS to simulate surface energy balance components along with irrigation (Iᵣᵣ). Two agricultural-dominated groundwater regions of northwest Kansas, USA within a section of the Ogallala aquifer were studied during a five-year period (2013–2017). We compared model-simulated irrigation to reported within water right management units (WRMU). The sum of reported irrigation and precipitation (P), representing in-season water supply, was also compared to model simulated ET as an indicator of well-watered ET. The model was able to simulate reasonably ET values, and irrigation quantities, and to differentiate various spatial distribution patterns of crops within WRMU. However, unknown water management, within WRMU, constrained explicit inference of actual ET and irrigation amounts. The model appears suitable for quantifying the upper bound of in-season water supply (irrigation plus P) expected for well-watered crops in the U.S. Central High Plains. A WRMU exhibiting significantly different in-season water supply than the simulated ET may present opportunities to modify irrigation rates or to gain inference about deficit irrigation.