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Satellite-derived rainfall thresholds for landslide early warning in Bogowonto Catchment,Central Java,Indonesia
Institution:1. Ndata School of Climate and Earth Sciences, Malawi University of Science and Technology, Limbe, P.O. Box 5196, Malawi;2. Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, 7500 AA, Netherlands;3. Department of Civil Engineering, Universitas Muhammadiyah Yogyakarta (UMY), Yogyakarta, Indonesia;4. Balai Litbang Sabo (BALAI SABO), Research Center for Water Resources, Min. of Works and housing, Yogyakarta, Indonesia
Abstract:Satellite rainfall products for landslide early warning prediction have been spotlighted by several researchers, in the last couple of decades. This study investigates the use of TRMM and ERA-Interim data, for the determination of rainfall thresholds and the prediction of precipitation, respectively, to be used for landslide early warning purposes at the Bogowonto catchment, Central Java, Indonesia. A landslide inventory of 218 landslides for the period of 2003–2016 was compiled, and rainfall data were retrieved for the landslide locations, as given by 6 ground stations, TRMM, and ERA-Interim data. First, rainfall data from the three different sources was compared in terms of correlation and extreme precipitation indices. Second, a procedure for the calculation of rainfall thresholds for landslide occurrence was followed consisting of four steps: i) the TRMM-based rainfall data was reconstructed for selected dates and locations characterized by landslide occurrence and non-occurrence; ii) the antecedent daily rainfall was calculated for 3, 5, 10, 15, 20 and 30 days for the selected dates and locations; iii) two-parameter daily rainfall-antecedent rainfall thresholds were calculated for the aforementioned dates; after analysis of the curves the optimum number of antecedent rainfall days was selected; and (iv) empirical rainfall thresholds for landslide occurrence were determined. The procedure was repeated for the entire landslide dataset, differentiating between forested and built-up areas, and between landslide occurrence in four temporal periods, in relation to the monsoon. The results indicated that TRMM performs well for the detection of very heavy precipitation and can be used to indicate the extreme rainfall events that trigger landslides. On the contrary, as ERA-Interim failed to detect those events, its applicability for LEWS remains limited. The 15-day antecedent rainfall was indicated to mostly affect the landslide occurrence in the area. The rainfall thresholds vary for forested and built-up areas, as well as for the beginning, middle and end of the rainy season.
Keywords:Landslides  Early warning systems  Satellite rainfall products  TRMM  Rainfall thresholds  Antecedent rainfall
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