Title: | A pre-calibration approach to select optimum inputs for hydrological models in data-scarce regions |
Authors: | Tarawneh E., J. Bridge, and N. Macdonald |
Year: | 2016 |
Journal: | Hydrology and Earth System Sciences |
Volume (Issue): | 70 |
Pages: | 4391-4407 |
Article ID: | |
DOI: | 10.5194/hess-20-4391-2016 |
URL (non-DOI journals): | |
Model: | SWAT |
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. |
Language: | English |
Keywords: | |