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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 #371731

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

Location: Soil and Water Management Research

Title: Evaluation of SWAT soil water estimation accuracy using data from Indiana, Colorado, and Texas

item HASHEM, AHMED - Arkansas State University
item ENGEL, BERNARD - Purdue University
item Marek, Gary
item MOORHEAD, JERRY - Xcel Energy
item Flanagan, Dennis
item RASHAD, MOHAMED - Suez Canal University
item RADWAN, SHERIF - Suez Canal University
item BRALTS, VINCENT - Purdue University
item Gowda, Prasanna

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/23/2020
Publication Date: 12/1/2020
Citation: Hashem, A.A., Engel, B.A., Marek, G.W., Moorhead, J.E., Flanagan, D.C., Rashad, M., Radwan, S., Bralts, V.F., Gowda, P.H. 2020. Evaluation of SWAT soil water estimation accuracy using data from Indiana, Colorado, and Texas. Transactions of the ASABE. 63(6):1827-1843.

Interpretive Summary: Hydrologic models at accurately predict various parameters of agricultural ecosystems are useful for water policy development and irrigation scheduling. The Soil and Water Assessment Tool (SWAT) is a watershed-scale model widely used to simulate the effects of management and land use change on hydrologic processes. Meaningful simulations are dependent upon accurate representation of the water balance. However, many have raised concerns about the efficacy of SWAT to simulate realistic soil water profile values. Researchers from USDA-ARS Bushland, TX and El Reno, OK and cooperating universities (Arkansas State University, Purdue University and Suez Canal University, Egypt) compared simulated soil water values with measured data from Indiana, Texas, and Colorado. Results indicated that although simulations approximated stream flow reasonably well following calibration, simulated values for soil water content by layer and profile were not useful for irrigation scheduling purposes. These results suggest that improvements to the soil water simulation algorithms in SWAT may be needed for accurate simulations of irrigation management.

Technical Abstract: Soil water estimation is a challenging measurement at field, watershed and regional scales. The Soil and Water Assessment Tool (SWAT) soil water estimates were evaluated at three locations: 1) St. Joseph River Watershed (SJRW) located in northeast Indiana, 2) the USDA-ARS Conservation and Production Research Laboratory (CPRL) at Bushland, Texas, and 3) the USDA-ARS Limited Irrigation Research Farm (LIFR) at Greeley, Colorado. The soil water estimates were evaluated under two scenarios: 1) for the entire soil profile, and 2) layer by layer. Each site’s soil moisture assessment was performed based on the existing management conditions during each experiment, whether dryland or irrigated, and for various periods depending on soil water measurement availability at each site. The SWAT model soil water results were evaluated as follows: Indiana site under dryland conditions using daily soil moisture observations for one year. The Texas site was evaluated for a ten-year period under irrigated and dryland conditions using weekly soil water observations for four lysimeters. The Colorado site was evaluated under irrigated conditions for a four-year period. The soil water estimates were evaluated by comparing the model estimates with observed daily and weekly soil water measurements at the three sites. Based on the results, all the SWAT models were considered to perform as good models following calibration (streamflow, ET, etc). However, the soil water estimates were unacceptable for the entire soil profile and for separate layers for the three sites. Deeper soil layers showed observations outside the field capacity threshold indicating poor soil parameters. The dryland model showed greater water content compared to the irrigated model, contradicting the soil water measurements. This higher soil water with the dryland model is a result of SWAT model uncertainties with ET reduction under dryland conditions due to water stress. This paper indicates that using the default SWAT soil moisture equations is not appropriate for real-time irrigation management practices, and more modification/development to the SWAT soil moisture routines is required to improve overall soil water estimation accuracy for irrigation water management purposes.