Developing and Evaluating Remote Sensing Based Direct Evapo-Transpiration (ET) Models to Improve Water Accounting Efficiency

Project ID: 282
Principal Investigator: Ronald Miller
Research Topic: Water Supply Forecasting
Funded Fiscal Years: 2008, 2009 and 2010
Keywords: None

Research Question

* Can remote sensing based energy balance models based on the Surface Energy Balance Algorithm for Land standard (SEBAL, Bastiannsen et al. 1998) be used in operation as a replacement for crop coefficient based irrigation water use formulas?

Crop-based water-use accounting systems are costly and time-consuming to produce due to the agriculture classification input requirements. Recently, new ground and remote sensing tools have increased the ability to measure ET locally and scale it to larger natural and agricultural regions. Tools have been developed by university and government research that are now available and can be used with minimal modification for new remote sensing sources to produce enhanced ET statistics at lower costs as a replacement to expensive crop specific irrigation withdrawal estimates.

Need and Benefit

Conventional methods used to estimate irrigation withdrawals involve applying crop specific consumptive use coefficients to acreages estimated for each crop category. Local climate, application rates, soil conditions and other factors are used to estimate ET rates to determine water needs of districts for irrigation scheduling. Return flows and conveyance losses are subtracted in irrigation use formulas. Crop classifications have been produced using remote sensing and image processing of terrestrial or satellite imagery. Additionally, ground verification of crop conditions, historical patterns, and other field data are used. These processes are time consuming and costly. Accuracy assessments are usually estimated in the range of 75-85 percent. If alternate methods can be developed to estimate ET rates at equal or better accuracies without the need for costly crop classifications, then costs and times to schedule could be reduced while increasing efficiency.

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Last Updated: 6/22/20