Rozi, Hanifsyah
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Analysis of Extreme Rainfall in Padang Using GSMaP Satellite Imagery: Case Study of the July 2023 Flood : Approach Using GSMaP Satellite Data Rozi, Hanifsyah; Razi, Pakhrur; Amir, Harman; Sudiar, Nofi Yendri; Rinadi, Aulia
Georest Vol. 2 No. 2 (2024): Georest (In Press)
Publisher : EarthCare

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57265/georest.v2i2.32

Abstract

Extreme rainfall is a major cause of major flooding in coastal areas, such as Padang, Indonesia. This study analyzes the extreme rainfall event that caused the Padang flood on July 14, 2023 using rainfall data from the Global Satellite Rainfall Mapping system (GSMaP). The aim is to evaluate the spatial and temporal distribution of rainfall during the event and assess the accuracy of GSMaP satellite imagery in capturing the heavy rainfall that caused the flooding. GSMaP satellite data were processed to examine the intensity and distribution of rainfall from July 13, 2023 to July 14, 2023. The analysis showed that rainfall occurred evenly over the entire Padang area, with a peak rainfall intensity of 20-99 mm/day on July 13 and a much higher intensity of 145-434 mm/day on July 14, as recorded by ground-based rain stations. The peak rainfall on the first day occurred at 14:00 UTC, and on the second day at 00:00 UTC. Although GSMaP effectively captured the large-scale rainfall pattern, differences were seen in the local intensity. This continuous rainfall causes severe waterlogging, which then escalates into flooding, which is classified as extreme rainfall. These findings demonstrate the utility of GSMaP in monitoring extreme rainfall, especially in areas with limited ground-based observation infrastructure, and emphasize the role of satellite data in improving early warning systems and flood management strategies in flood-prone areas such as Padang.
Hanifsyah Rozi, Pakhrur Razi Identification of Extreme Rainfall in Padang Based on Weather Radar Imagery : Case Study Flood July 2023: Approach Using Weather Radar Data rozi, hanifsyah
Georest Vol. 2 No. 1 (2024): Georest
Publisher : EarthCare

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57265/georest.v2i1.27

Abstract

Extreme rainfall combined with high impact weather frequently happens in the Padang city region, resulting in flooding, damaging livelihoods, and endangering lives and the environment. Consequently, the detection of intense precipitation patterns like convective cloud development, cloud distribution patterns, as well as the time and duration of rainfall needs to be analyzed to improve disaster mitigation and research development, especially in the Padang city area. In this study we processed gematronic brand weather radar data with volumetric format to produce several weather radar products to identify extreme rainfall that causes flooding. Based on our identification, the rain on July 13 to 14, 2023 has occurred from noon to early morning, detected convective clouds with reflectivity values reaching 55-60 dBZ which indicates light rain to extreme rain, with peak rain occurring in the afternoon and evening. Identifying the pattern and duration of extreme rainfall allows for better planning and risk mitigation measures.