SWAT Literature Database for Peer-Reviewed Journal Articles

Title:A pre-calibration approach to select optimum inputs for hydrological models in data-scarce regions 
Authors:Tarawneh E., J. Bridge, and N. Macdonald 
Journal:Hydrology and Earth System Sciences 
Volume (Issue):70 
Article ID: 
URL (non-DOI journals): 
Broad Application Category:hydrologic and pollutant 
Primary Application Category:input data effects 
Secondary Application Category:calibration, sensitivity, and/or uncertainty analysis 
Watershed Description:1,743 km^2 Wala River, (up to Wala Dam), which drains to the Dead Sea in northwest Jordan. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:This study uses the Soil and Water Assessment Tool (SWAT) model to quantitatively compare available input datasets in a data-poor dryland environment (Wala catchment, Jordan; 1743 km2). Eighteen scenarios combining best available land-use, soil and weather datasets (1979–2002) are considered to construct SWAT models. Data include local observations and global reanalysis data products. Uncalibrated model outputs assess the variability in model performance derived from input data sources only. Model performance against discharge and sediment load data are compared using r2, Nash–Sutcliffe efficiency (NSE), root mean square error standard deviation ratio (RSR) and percent bias (PBIAS). NSE statistic varies from 0.56 to -12 and 0.79 to -85 for best- and poorest-performing scenarios against observed discharge and sediment data respectively. Global weather inputs yield considerable improvements on discontinuous local datasets, whilst local soil inputs perform considerably better than global-scale mapping. The methodology provides a rapid, transparent and transferable approach to aid selection of the most robust suite of input data.