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Pakhrur Razi
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Center of Disaster Monitoring and Earth Observation Jl. Prof. Dr. Hamka Air Tawar Padang West Sumatra, Indonesia 25131
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Georest: Geoscience, Remote Sensing, and Technology
Published by Earthcare
ISSN : 29637767     EISSN : 29637767     DOI : https://doi.org/10.57265/georest.v1i1
Core Subject : Science,
Astronomy Earth & Planetary Sciences Physics
Georest: Geoscience, Remote Sensing and Technology is an international peer-reviewed open-access journal dedicated to interchange for the results of high-quality research in all aspect of Sciences, Geoscience, Geophysics, Remote Sensing, Drone, Radar SAR, Optical Satellite, LiDAR, Radar Antenna, Computer Science, Computer Engineering, Engineering, Information Technology, and Visualization.
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Geofisika
Articles 1 Documents
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Search results for , issue "Vol. 2 No. 2 (2024): Georest (In Press)" : 1 Documents clear
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.

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