|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: Journal of the American Water Resources Association
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/9/2015
Publication Date: 1/6/2016
Citation: Marek, G.W., Gowda, P., Evett, S.R., Baumhardt, R.L., Brauer, D.K., Howell, T.A., Marek, T.H., Srininvasan, R. 2016. Estimating evapotranspiration for dryland cropping systems in the semiarid Texas High Plains using SWAT. Journal of the American Water Resources Association. 52(2):298-314.
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 simulate daily and monthly ET under dryland management practices in the semiarid Texas High Plains. Measured ET data from large lysimeter were used for model evaluation. Results indicated that the SWAT model generally underestimated both daily and monthly ET.
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 semiarid environments when ET demands exceed precipiattion. However, limited 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 a dryland managed 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 0.62 for the calibration period resulting in a "good" performance rating. A NSE of 0.70 resulted in a “very good” rating for the validation period. NSE values for simulated average monthly ET were improved at 0.87 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 during some periods of the growing season. SWAT overestimated ET during two out of three fallow years. Measured LAI input data were included for more accurate plant growth and subsequent ET simulation. However, divergences between measured and simulated ET were observed in the early growing season during three of the five years of the calibration period. These discrepancies may be the result of errors associated with LAI-based plant stress algorithms embedded in SWAT. 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 grain sorghum under dryland 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. Users should be aware of potential errors associated with using default plant database LAI values and the subsequent effects on ET estimation, particularly when evaluating water management practices for dryland/rainfed watersheds.