Location: Soil and Water Management ResearchTitle: Calibration and validation of the SWAT model for predicting daily ET over irrigated crops in the Texas High Plains using lysimetric data Author
|Evett, Steven - Steve|
|Baumhardt, Roland - Louis|
|Brauer, David - Dave|
|Howell, Terry - Retired ARS Employee|
|Marek, Thomas - Texas Agrilife Research|
|Srininvasan, R - Texas A&M University|
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/30/2015
Publication Date: 4/27/2016
Citation: Marek, G.W., Gowda, P., Evett, S.R., Baumhardt, R.L., Brauer, D.K., Howell, T.A., Marek, T.H., Srininvasan, R. 2016. Calibration and validation of the SWAT model for predicting daily ET over irrigated crops in the Texas High Plains using lysimetric data. Transactions of the ASABE. 59(2):611-622 doi:10.1303/trans.59.10926.
Interpretive Summary: Freshwater resources are finite and becoming increasingly scarce. Effective water management strategies are required 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 simulate and evaluate water management strategies for extending water resources. The Soil and Water Assessment Tool (SWAT) is one of the most widely used hydrologic models used for this purpose. However, limited studies have been done to evaluate the ability of SWAT to simulate daily ET in these regions. In this study, scientists from ARS (Bushland, TX) and Texas A&M AgriLife compared simulated SWAT ET values to measured values from a lysimeter located in the semiarid Texas High Plains. Results indicated that the SWAT model generally underestimated both daily and monthly ET. Further evaluation is required to evaluate its ability to estimate ET under water-limited conditions.
Technical Abstract: The Soil Water Assessment Tool (SWAT) is a widely used watershed model for simulating stream flow, overland flow, sediment, pesticide, and bacterial loading in response to management practices. All SWAT processes are directly dependent upon the accurate representation of hydrology. Evapotranspiration (ET) is commonly the most significant portion of the hydrologic cycle, especially for irrigated lands in semiarid environments when ET demands are met or exceeded. However, no studies using long-term data to evaluate the SWAT model’s capacity to estimate daily, monthly, and seasonal ET have been performed. In this study, daily and monthly ET values were simulated using ArcSWAT 2012 for an irrigated lysimeter field at the USDA-ARS CPRL at Bushland, TX and compared to measured ET values from 2001-2010. A one year warm-up (2000) and equal division of the remaining years were used for the calibration (2001-2005) and validation (2006-2010) periods. SWAT achieved a Nash Sutcliffe Efficiency (NSE) of 0.67 for the calibration period resulting in a “good” performance rating. A NSE of 0.78 resulted in a “very good” rating for the validation period. NSE values for simulated average monthly ET were improved at 0.77 and 0.85 for the calibration and validation periods respectively. Analysis of simulated versus measured ET values both during and outside of the growing season revealed better agreement during the former than the latter. The SWAT model generally underestimated ET at both the daily and monthly levels but overestimated for cotton years due to over estimation of leaf area index during the senescing stage. Overall, SWAT was able to predict daily and average monthly ET reasonably well for major summer crops grown in the semiarid Texas High Plains. These results should reinforce confidence in the SWAT model’s capacity to accurately simulate ET in fully irrigated watersheds. However, limitations in accuracy do appear to exist for certain crops such as cotton and sunflower and particularly under limited irrigation conditions. These deficiencies are suspected to be related to issues with generic irrigation algorithms, crop production function or plant parameter values in the embedded crop database in SWAT.