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

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posted on 2017-07-05, 14:16 authored by Peshawa M. Najmaddin, Mick J. Whelan, Heiko Balzter
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.

Funding

This research was funded via a scholarship from the Higher Committee for Education Development in Iraq (HCED) with support from the NERC National Centre for Earth Observation. We are grateful to the Hydrology Department of the Dukan Dam Directorate for providing river discharge data and to the Directorate of Meteorology in Sulaimanyiah for providing meteorological data. HB was supported by a Royal Society Wolfson Research Merit Award (2011/R3) and MW benefitted from Study Leave granted by the University of Leicester

History

Citation

Climate, 2017, 5 (2), pp. 32-32

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Geography/GIS and Remote Sensing

Version

  • VoR (Version of Record)

Published in

Climate

Publisher

MDPI

issn

2225-1154

eissn

2225-1154

Acceptance date

2017-03-30

Copyright date

2017

Available date

2017-07-05

Publisher version

http://www.mdpi.com/2225-1154/5/2/32

Notes

Supplementary Materials: The following are available online at www.mdpi.com/2225-1154/5/2/32/s1.

Language

en

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