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Climate 2017, 5(2), 32; doi:10.3390/cli5020032

Application of Satellite-Based Precipitation Estimates to Rainfall-Runoff Modelling in a Data-Scarce Semi-Arid Catchment

1
Department of Geography, Centre for Landscape and Climate Research, University of Leicester, Leicester LE1 7RH, UK
2
Department of Soil and Water Science, Faculty of Agricultural Sciences, University of Sulaimani, Iraq-Kurdistan Region-Sulaimani-Bekrajo 46011, Iraq
3
National Centre for Earth Observation, University of Leicester, Leicester LE1 7RH, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Zhong Liu
Received: 7 March 2017 / Revised: 29 March 2017 / Accepted: 30 March 2017 / Published: 11 April 2017
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Abstract

Rainfall-runoff modelling is a useful tool for water resources management. This study presents a simple daily rainfall-runoff model, based on the water balance equation, which we apply to the 11,630 km2 Lesser Zab catchment in northeast Iraq. The model was forced by either observed daily rain gauge data from four stations in the catchment or satellite-derived rainfall estimates from two TRMM Multi-satellite Precipitation Analysis (TMPA) data products (TMPA-3B42 and 3B42RT) based on the Tropical Rainfall Measuring Mission (TRMM) from 2003 to 2014. As well as using raw TMPA data, we used a bias-correction method to adjust TMPA values based on rain gauge data. The uncorrected TMPA data products underestimated observed mean catchment rainfall by −10.1% and −10.7%. Corrected data also slightly underestimated gauged rainfall by −0.7% and −1.6%, respectively. Nash-Sutcliffe Efficiency (NSE) and Pearson’s Correlation Coefficient (r) for the model fit with the observed hydrograph were 0.75 and 0.87, respectively, for a calibration period (2010–2011) using gauged rainfall data. Model validation performance (2012–2014) was best (highest NSE and r; lowest RMSE and bias) using the corrected 3B42 data product and poorest when driven by uncorrected 3B42RT data. Uncertainty and equifinality were also explored. Our results suggest that TRMM data can be used to drive rainfall-runoff modelling in semi-arid catchments, particularly when corrected using rain gauge data. View Full-Text
Keywords: rainfall-runoff modelling; remote sensing; TRMM; semi-arid catchment rainfall-runoff modelling; remote sensing; TRMM; semi-arid catchment
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Najmaddin, P.M.; Whelan, M.J.; Balzter, H. Application of Satellite-Based Precipitation Estimates to Rainfall-Runoff Modelling in a Data-Scarce Semi-Arid Catchment. Climate 2017, 5, 32.

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