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Asian Journal of Scientific Research

Year: 2018 | Volume: 11 | Issue: 4 | Page No.: 489-497
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Authors

Heri Kuswanto

Heri Kuswanto

Kartika Fithriasari

Rosyida Inas

Keywords

Research Article

Drought Risk Mapping in East Nusa Tenggara Indonesia Based on Return Periods

Heri Kuswanto Heri Kuswanto's LiveDNA, Kartika Fithriasari and Rosyida Inas
Background and Objectives: Drought has been one of the major causes of disaster in Indonesia. The Regional Disaster Management Agency (BPBD) of East Nusa Tenggara (hereafter denoted as NTT) Province in Indonesia has reported that there were 20 districts in NTT affected by drought in 2015. This study aimed to map drought risk in NTT by using the Standardized Precipitation Index (SPI). The drought duration as well as the magnitude based on return periods of 5, 25 and 50 years were estimated as the basis of mapping. Methodology: The study were carried out by examining daily rainfall data recorded by several meteorological stations in NTT with in the period of 1999-2015. Return periods were estimated by quantifying the probability of extreme events, which thus translated into Scale-Duration-Frequency (TDF) and Time Scale Magnitude-Frequency (TMF). Results: The SPI analysis showed that NTT has experienced about 25 months of drought events within the periods of 1999 to 2015. The mapping results showed that Gewayantana is a district with the longest drought duration (reaching 30 months in 50 years) and strongest drought magnitude (11.2 SPI level) for all specified return periods. Meanwhile, Komodo and Frans Sales Lega districts are two regions with the lowest risk indicated by shortest drought duration and lowest magnitude compared to the others. The longest drought duration were mostly started in November. Conclusion: The drought risk maps derived from the magnitude and duration of the future drought in NTT clearly indicated that the severity of drought events in NTT increases over the time. However, the drought duration and magnitude for 50 years return period seems to be over-estimated.
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