Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

360-2 Improving SWAT Auto-Irrigation Functions for Simulating Irrigation Management Using Lysimeter Field Data.

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Climatology and Modeling Oral General II

Wednesday, October 25, 2017: 9:50 AM
Marriott Tampa Waterside, Florida Salon V

Gary W. Marek1, Yong Chen2, Thomas H. Marek3, David K. Brauer1 and Raghavan Srinivasan2, (1)USDA-ARS Conservation and Production Research Laboratory, Bushland, TX
(2)Department of Ecosystem Science and Management, Texas A&M University, College Station, TX
(3)Texas A&M AgriLife Research, Amarillo, TX
Abstract:
The Texas High Plains is one of the most productive U.S. agricultural regions. However, decreasing groundwater availability has resulted in the adoption of limited irrigation strategies such as the management allowed depletion (MAD) concept of plant available water. Simulation models such as the Soil and Water Assessment Tool are a cost-effective and time saving method commonly used to evaluate best management practices and their effect on water balance. However, some studies have suggested that the irrigation algorithms in SWAT are inadequate for evaluation of representative irrigation practices. Consequently, auto-irrigation algorithms were developed based on a 1) single season MAD level and 2) growth stage-specific MAD levels for seasonal crop growth partitioning based on both scheduled date and accumulated heat units. Comparisons with observed data from an irrigated lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas resulted in improved representation and simulation of irrigation.

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Climatology and Modeling Oral General II