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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #369840

Research Project: Precipitation and Irrigation Management to Optimize Profits from Crop Production

Location: Soil and Water Management Research

Title: Watershed scale evaluation of an improved SWAT auto-irrigation function

item CHEN, YONG - Texas A&M University
item Marek, Gary
item MAREK, THOMAS - Texas A&M Agrilife
item PORTER, DANA - Texas A&M Agrilife
item MOORHEAD, JERRY - Xcel Energy
item HEFLIN, KEVIN - Texas A&M Agrilife
item Brauer, David
item SRINIVASAN, RAGHAVAN - Texas A&M University

Submitted to: Journal of Environmental Modeling and Software
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/22/2020
Publication Date: 6/30/2020
Citation: Chen, Y., Marek, G.W., Marek, T.H., Porter, D.O., Moorhead, J.E., Heflin, K., Brauer, D.K., Srinivasan, R. 2020. Watershed scale evaluation of an improved SWAT auto-irrigation function. Journal of Environmental Modeling and Software. 131. Article 104789.

Interpretive Summary: Water scarcity due to drought and groundwater depletion has led to increased interest of irrigation strategies for extending limited water resources. The Soil and Water Assessment Tool (SWAT), a widely used hydrologic model, is increasingly being used to evaluate the impacts of irrigation strategies. The efficacy of an alternative Management Allowed Depletion (MAD) auto-irrigation algorithm for SWAT was recently demonstrated by comparing simulated irrigation, crop water use (ET), plant growth, and yield with measured values for corn grown at multiple research sites across the Southern Great Plains. However, the MAD algorithm has not been evaluated at the watershed scale. Scientists from ARS Bushland and Texas A&M University evaluated simulated stream flow with gauged data for an irrigated watershed located in the Texas High Plains. Results indicated that the alternative MAD function outperformed the default auto-irrigation algorithms in SWAT.

Technical Abstract: The Soil and Water Assessment Tool (SWAT) model is a well-documented hydrologic model. However, some studies report the existing SWAT auto-irrigation methods are unable to represent actual producer irrigation management, particularly in intensively irrigated regions. In the U.S. Great Plains, the SWAT model does not reproduce the management allowed depletion (MAD) irrigation scheduling commonly used by researchers and producers. Therefore, the SWAT source code was modified to include the MAD auto-irrigation function. This study evaluated the performance of the MAD method in streamflow and irrigation simulations at a watershed scale by comparison with existing SWAT auto-irrigation methods. All auto-irrigation methods resulted in satisfactory simulation of monthly streamflow. However, the MAD method performed the best with NSE greater than 0.65 and PBIAS within plus or minus 10 percent. Comparisons of simulated irrigation with the field irrigation also indicated the MAD method outperformed other methods with the NSE and PBIAS of 0.77 and -8.2 percent, respectively.