A SWAT model validation of nested-scale contemporaneous streamflow, suspended sediment and nutrients from a multiple-land-use watershed of the central USA

作者：Zeiger Sean J^*; Hubbart Jason A

来源：Science of the Total Environment, 2016, 572: 232-243.

DOI：10.1016/j.scitotenv.2016.07.178

• SWAT
• Hydrologic modeling
• Water quality
• Stream flow
• Suspended sediment
• Nutrients

There is an ongoing need to validate the accuracy of predictive model simulated pollutant yields, particularly from multiple-land-use (i.e. forested, agricultural, and urban) watersheds. However, there are seldom sufficient observed data sets available that supply requisite spatial and temporal resolution and coupled multi-parameter constituents for rigorous model performance assessment. Four years of hydroclimate and water quality data were used to validate SWAT model estimates of monthly stream flow, suspended sediment, total phosphorus, nitrate, nitrite, ammonium, and total inorganic nitrogen from 5 nested-scale gauging sites located in a multiple-land-use watershed of the central USA. The uncalibrated SWAT model satisfactorily simulated monthly stream flow with Nash-Sutcliffe efficiency (NSE) values ranging from 0.50 near the headwaters, to 0.75 near the watershed outlet. However, the uncalibrated model did not accurately simulate monthly sediment, total phosphorus, nitrate, nitrite, ammonium, and total inorganic nitrogen with NSE values <0.05. Calibrating the SWAT model to multiple gauging sites within the watershed improved estimates of monthly stream flow (NSE = 0.83), sediment (NSE = 0.78), total phosphorus (NSE = 0.81), nitrate (NSE = 0.90), and total inorganic nitrogen (NSE = 0.86). However, NSE values were <-0.16 for nitrite and ammonium estimates. Additionally, model performance decreased for sediment, nitrate, and total inorganic nitrogen during the validation period with NSE values < 0.62, 0.52, and 0.36, respectively. Results highlight the benefits of calibrating the SWAT model to multiple gauging sites and provide guidance to SWAT model (or similar models) users wishing to improve model performance at multiple scales.

• 出版日期2016-12-1