A pre-calibration approach to select optimum inputs for hydrological models in data-scarce regions

Tarawneh, Esraa, Bridge, Jonathan and Macdonald, Neil ORCID: 0000-0003-0350-7096 (2016) A pre-calibration approach to select optimum inputs for hydrological models in data-scarce regions HYDROLOGY AND EARTH SYSTEM SCIENCES, 20 (10). pp. 4391-4407. ISSN 1027-5606, 1607-7938

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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.

Item Type:	Article
Uncontrolled Keywords:	3707 Hydrology, 3709 Physical Geography and Environmental Geoscience, 37 Earth Sciences, 2 Zero Hunger
Depositing User:	Symplectic Admin
Date Deposited:	31 Oct 2016 08:48
Last Modified:	25 Sep 2026 01:20
DOI:	10.5194/hess-20-4391-2016
Open Access URL:	http://www.hydrol-earth-syst-sci.net/20/4391/2016/...
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3004200
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