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All Journal INTERNATIONAL JOURNAL OF ENVIRONMENT AND GEOSCIENCES
Kakuji Ogawara
Graduate School of Sciences and Technology for Innovation, Yamaguchi University, 2-16-1 Tokiwadai, Ube, Yamaguchi 755-8611, Japan
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Environmental Science

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Application of GSMaP Product and Rain Gauge Data for Monitoring Rainfall Condition of Flood Events in Indonesia Nyoman Sugiartha; Kakuji Ogawara; Tasuku Tanaka; Made Sudiana Mahendra
International Journal of Environment and Geosciences Vol 1 No 1 (2017)
Publisher : Graduate Study of Environmental Sciences, Postgraduate Program of Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/ijeg.2017.v01.i01.p05

Abstract

Rainfall is one of main causes of floods. Monitoring of the rainfall is essential for understanding flood mechanism and early warning. Ground-based rain gauge is a conventional device to measure rainfall amount and considered as a point measurement. Satellite-based rainfall estimates provides complement measurement over wide area having few or even no in situ data. This study evaluates rainfall intensity variation and patterns preceding flood events in Indonesia for the period of 2003-2010 using the GSMaP_MVK satellite-based rainfall product with one hour and 0.1o x 0.1o resolutions and rain gauge station data as a benchmark. The analysed data are 3-hourly average and daily accumulation time steps. The chosen research locations were Medan City, Pekanbaru City, Indragiri Hulu Regency, Samarinda City and Manado City. Graphical comparisons of the GSMaP_MVK with the rain gauge data show discrepancies in capturing rainfall events and intensity. The GSMaP_MVK performs underestimation for the most areas, except Samarinda City, which is overestimated. Short-term period rainfall pattern is the most frequent occurred preceding flood events for the entire study areas which indicate that the areas are more susceptible to flash floods and river overflows. Overall, the GSMaP_MVK product provides promising potentiality for the application of monitoring rainfall conditions preceding flood events over the research locations. Statistical verifications reveal that on average, correlation coefficients are (0.22-0.54) and (0.65-0.83) for 3-hourly and daily scale, respectively. While, probability of rain detections (PODs) are (0.57-0.75) and (0.93-0.99), accordingly.
Co-Authors M. Sudiana Mahendra Nyoman Sugiartha Tasuku Tanaka