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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 #320363

Research Project: IMPROVING WATER PRODUCTIVITY AND NEW WATER MANAGEMENT TECHNOLOGIES TO SUSTAIN RURAL ECONOMIES

Location: Soil and Water Management Research

Title: Evaluation of SWAT for estimating ET in irrigated and dryland cropping systems in the Texas High Plains

Author
item Marek, Gary
item Gowda, Prasanna
item Evett, Steven - Steve
item Baumhardt, Roland - Louis
item Brauer, David - Dave
item Howell, Terry - Retired ARS Employee
item Marek, Thomas - Texas Agrilife Research
item Srinivasan, R - Texas A&M University

Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: 5/22/2015
Publication Date: 11/10/2015
Citation: Marek, G.W., Gowda, P., Evett, S.R., Baumhardt, R.L., Brauer, D.K., Howell, T.A., Marek, T.H., Srinivasan, R. 2015. Evaluation of SWAT for estimating ET in irrigated and dryland cropping systems in the Texas High Plains. ASABE Annual International Meeting. CDROM: Paper#152141855.

Interpretive Summary: Groundwater resources are finite and becoming increasingly scarce. Effective water and crop management strategies are needed to maximize and extend the use of these limited resources. In agriculture, crop water use (ET) is the major use of rain and irrigation water. Models are commonly used to evaluate alternative water management strategies for their potential to maximize water use efficiency. In this study, we used the Soil and Water Assessment Tool (SWAT), one of the most widely used hydrologic models, to compare model performance for estimating daily ET under both dryland and irrigated management in the semiarid Texas High Plains. Simulated values were compared to measured ET values from large weighing lysimeters. Results indicated that the SWAT model generally underestimated both daily and monthly ET.

Technical Abstract: Hydrologic models such as SWAT are used extensively for predicting water availability and water quality responses to alternative management practices. Modeling results have been used by regulatory agencies for developing remedial measures for impaired water bodies and for water planning purposes. However, comprehensive calibration and testing of these models for predicting daily ET are noticeably absent from most modeling efforts. This is largely due to the limited number of quality, long-term ET and related management datasets. Consequently, more readily available and easily measured components of the water balance, including runoff and stream flow, are often used as calibration targets. ET is often simply ignored or adjusted by manipulating sensitive ET model parameters in order to match other simulated water balance components to measured values. This approach can provide a false sense of confidence that the model is performing properly although significant errors in modeled ET may exist. In essence, the model may provide the right answer for the wrong reasons. This condition may go unnoticed until the calibrated model is used to simulate other components of the water balance such as ET and compared with measured data. Additionally, model errors in ET simulation may vary considerably under irrigated and dryland management practices. The application of default crop database and production functions embedded in the SWAT model appears to be inadequate for accurately simulating the water budget, including ET and irrigation demand and consequent water quality and crop yield. Improper or incomplete calibration and testing of water balance components and the use of uncalibrated crop database parameters can be problematic and lead to improper evaluation of management strategies. In this presentation, we discuss calibration and testing efforts of SWAT simulated ET under both irrigated and dryland cropping systems of the semi-arid Texas Panhandle using lysimetric data from the USDA-ARS Conservation and Production Research Laboratory in Bushland, Texas.