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Hydrology 2017, 4(2), 22; doi:10.3390/hydrology4020022

Evaluation of Satellite-Derived Rainfall Estimates for an Extreme Rainfall Event over Uttarakhand, Western Himalayas

1
Centre for Land Resource Management (CLRM), School of Natural Resource & Management, Central University of Jharkhand, Ranchi 835205, Jharkhand, India
2
Department of Civil Engineering, Center for Environmental Science & Engineering (CESE), Shiv Nadar University, Greater Noida 201314, U.P., India
3
Department of Civil Engineering, National Institute of Technology, Imphal 795001, Manipur, India
4
Centre for Glaciology, Wadia Institute of Himalayan Geology, Dehradun 248001, Uttarakhand, India
*
Author to whom correspondence should be addressed.
Academic Editor: Jai Vaze
Received: 8 February 2017 / Revised: 17 March 2017 / Accepted: 23 March 2017 / Published: 30 March 2017
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Abstract

The extreme rainfall event during June 2013 in the Western Himalayas caused widespread flash floods, which triggered landslides, a lake-outburst, and debris flow. For the hydrological study of such an unexpected extreme event, it is essential to have reliable and accurate rainfall predictions based on satellite observations. The mountainous state of Uttarakhand is covered by complex topography, and this state has few, unevenly distributed, rain gauge networks. This unique study was conducted to evaluate three satellite based rainfall products (i.e., TMPA-3B42, Global Satellite Mapping of Precipitation (GSMaP), and NOAA CPC Morphing Technique (CMORPH)) against the observed rain gauge-based India Meteorological Department (IMD) gridded dataset for this rainfall episode. The results from this comprehensive study confirmed that the magnitude of precipitation and peak rainfall intensity were underestimated in TMPA-3B42 and CMORPH against gauge-based IMD data, while GSMaP showed dual trends with under- and over-predictions. From the results of the statistical approach on the determination of error statistic metrics (MAE (mean absolute error), NRMSE (normalized root mean square error), PBIAS (percent bias), and NSE (Nash-Sutcliffe efficiency)) of respective satellite products, it was revealed that TMPA-3B42 predictions were more relevant and accurate compared to predictions from the other two satellite products for this major event. The TMPA-3B42-based rainfall was negatively biased by 18%. Despite these caveats, this study concludes that TMPA-3B42 rainfall was useful for monitoring extreme rainfall event in the region, where rain-gauges are sparse. View Full-Text
Keywords: extreme rainfall event; Kedarnath disaster; satellite rainfall products; IMD; TRMM; TMPA; GSMaP; mass curve and hyetograph; Mandakini valley extreme rainfall event; Kedarnath disaster; satellite rainfall products; IMD; TRMM; TMPA; GSMaP; mass curve and hyetograph; Mandakini valley
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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

Parida, B.R.; Behera, S.N.; Bakimchandra, O.; Pandey, A.C.; Singh, N. Evaluation of Satellite-Derived Rainfall Estimates for an Extreme Rainfall Event over Uttarakhand, Western Himalayas. Hydrology 2017, 4, 22.

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