Skip to main content
ARS Home » Research » Publications at this Location » Publication #227285

Title: Incorporation of a new shallow water table depth algorithm into SWAT 2005

Author
item Moriasi, Daniel
item Arnold, Jeffrey
item VAZQUEZ-AMABILE, GABRIEL - UNIV. LA PLATA, ARGENTINA
item ENGEL, BERNARD - PURDUE UNIV., INDIANA
item Rossi, Colleen

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/30/2009
Publication Date: 7/1/2009
Citation: Moriasi, D.N., Arnold, J.G., Vazquez-Amabile, G.G., Engel, B.A., Rossi, C.G. 2009. Incorporation of a new shallow water table depth algorithm into SWAT 2005. Transactions of the ASABE. 52(3):771-784.

Interpretive Summary: Shallow water table depth (WTD) fluctuation over time is an important issue for planning drainage systems at the plot-, field- and watershed-scale. The proximity of the WTD to the soil surface impacts farm machine trafficability, crop development, agricultural chemical transport, soil salinity, and drainage. It is, therefore, essential for hydrologic models to accurately simulate WTD. The methods presently used by the Soil and Water Assessment Tool model (SWAT Release 2005), a continuous-time physically-based watershed-scale hydrologic model, to compute water table depth tend to give somewhat erratic water table depth profile fluctuations during relatively short dry periods followed by short wet periods. The main objectives of this study were to: 1) develop and incorporate into SWAT a new water table depth algorithm, the modified DRAINMOD drainage volume – water table depth method, in order to improve the prediction of the WTD; 2) evaluate the new method within SWAT2005 using measured water table depth data for three soils located with Muscatatuck River basin in southeast Indiana; and 3) compare the water table depth predictions using the new method with, those previously implemented within SWAT, to determine the effect of the new method on the water table depth routine predictions. Based on the model outputs, the new method within SWAT2005 improved the prediction of water table depth by 66% to 98% on average. Enhanced water table depth prediction is expected to increase the simulation accuracy of watershed hydrologic processes and water management components such as tile drainage.

Technical Abstract: The fluctuation of the shallow water table depth (WTD) is important for planning drainage systems at the plot-, field-, and watershed-scale because its proximity to the surface impacts farm machine trafficability, crop development, agricultural chemical transport, soil salinity, and drainage. Therefore, it is important for hydrologic models to accurately simulate WTD. In this study, a new water table depth algorithm, the modified DRAINMOD drainage volume – water table depth (MDV-WTD) method, was developed and incorporated into the Soil and Water Assessment Tool model (SWAT Release 2005), a continuous-time physically-based watershed-scale hydrologic model, in order to improve the prediction of the WTD. SWAT was calibrated and validated for WTD for three observation wells located within the Muscatatuck River basin in southeast Indiana and the water table depth prediction performance of the MDV-WTD method was compared to those of three other WTD routines used by SWAT. The average daily calibration/validation model performance efficiency (NSE), percent bias (PBIAS), root mean square error (RMSE), and correlation coefficient (R) values for the three observation wells were 0.64/0.41, -13%/-3%, 0.41 m/0.59 m, and 0.81/0.65, respectively, for the newly implemented MDV-WTD method, 0.10/-0.15, -41%/-60%, 0.65 m/0.80 m, and 0.63/0.58, respectively, using the Water Balance/Drainage Volume (WB-DV) method, -2.06/-2.56, -94%/-104%, 1.18 m/1.46 m, and 0.52/0.13, respectively, using the Antecedent Climate method, and -4.55/-2.42, -196%/-130%, 1.49 m/1.31 m, and 0.54/0.45, respectively, using the Current method. Overall, implementation of the MDV-WTD method within SWAT2005 improved the prediction of water table depth. Enhanced water table depth prediction is anticipated to increase the simulation accuracy of watershed hydrologic processes and water management components such as tile drainage.