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Title: Comparison of shallow water table depth algorithms used in SWAT2005

Author
item Moriasi, Daniel
item Arnold, Jeffrey
item VAZQUEZ-AMABILE, GABRIEL - UNIV BUENOS AIRES ARGENTI
item ENGEL, B - PURDUE UNIV,W LAFAYETTE
item Rossi, Colleen

Submitted to: Annual International SWAT Conference
Publication Type: Abstract Only
Publication Acceptance Date: 8/30/2008
Publication Date: N/A
Citation: N/A

Interpretive Summary: Abstract Only.

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 ground surface impacts farm machine trafficability, crop development, agricultural chemical transport, soil salinity, and drainage. Therefore, it is essential for hydrologic models to accurately simulate WTD. In this study, the performance of four water table depth algorithms, the modified DRAINMOD drainage volume – water table depth (MDV-WTD) method, the Water Balance/Drainage Volume (WB-DV) method, the antecedent climate (AC) method, and the current method used by the Soil and Water Assessment Tool model (SWAT Release 2005), a continuous-time physically-based watershed-scale hydrologic model, were tested to determine their WTD prediction accuracy performance. 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 for the four methods were compared. The average daily calibration/validation Nash-Sutcliff Efficiency (NSE) and percent bias (PBIAS) values for the three observation wells were 0.64/0.4 and -13%/-3%, respectively, for the MDV-WTD method; 0.10/-0.15 and -41%/-60%, respectively, using the WB-DV method; -2.06/-2.56 and -94%/-104%, respectively, using the AC method; and -4.55/-2.42 and -196%/-130%, respectively, using the current method. Overall, the MDV-WTD method within SWAT2005 yielded the best water table depth prediction performance. Using the most accurate water table depth prediction method increases the simulation accuracy of watershed hydrologic processes and water management components such as tile drainage.