Point-Based Rainfall Intensity Information System in Mt. Merapi Area by X-Band Radar
Santosa Sandy Putra*1,*2,, Banata Wachid Ridwan*1, Kazuki Yamanoi*3, Makoto Shimomura*4, Sulistiyani*5, and Dicky Hadiyuwono*6
*1Balai Sabo, Ministry of Public Works and Housing
Balai Sabo, Sopalan, Maguwoharjo, Yogyakarta 55282, Indonesia
*2School of Geography, Faculty of Environment, University of Leeds, Leeds, United Kingdom
*3RIKEN Center for Computational Science, Kobe, Japan
*4Sakurajima Volcano Research Center, Kyoto University, Kagoshima, Japan
*5Balai Penyelidikan dan Pengembangan Teknologi Kebencanaan Geologi, Ministry of Energy and Mineral Resources, Yogyakarta, Indonesia
*6Department of Civil and Environmental Engineering, Universitas Gadjah Mada, Yogyakarta, Indonesia
An X-band radar was installed in 2014 at Merapi Museum, Yogyakarta, Indonesia, to monitor pyroclastic and rainfall events around Mt. Merapi. This research aims to perform a reliability analysis of the point extracted rainfall data from the aforementioned newly installed radar to improve the performance of the warning system in the future. The radar data was compared with the monitored rain gauge data from Balai Sabo and the IMERG satellite data from NASA and JAXA (The Integrated Multi-satellitE Retrievals for GPM), which had not been done before. All of the rainfall data was compared on an hourly interval. The comparisons were conducted based on 11 locations that correspond to the ground rainfall measurement stations. The locations of the rain gauges are spread around Mt. Merapi area. The point rainfall information was extracted from the radar data grid and the satellite data grid, which were compared with the rain gauge data. The data were then calibrated and adjusted up to the optimum state. Based on January 2017–March 2018 data, it was obtained that the optimum state has a NSF value of 0.41 and R2 value of 0.56. As a result, it was determined that the radar can capture around 79% of the hourly rainfall occurrence around Mt. Merapi area during the chosen calibration period, in comparison with the rain gauge data. The radar was also able to capture nearby 40–50% of the heavy rainfall events that pose risks of lahar. In contrast, the radar data performance in detecting drizzling and light rain types were quite precise (55% of cases), although the satellite data could detect slightly better (60% of cases). These results indicate that the radar sensitivity in detecting the extreme rainfall events must receive higher priority in future developments, especially for applications to the existing Mt. Merapi lahar early warning systems.
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