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All Journal SAINSMAT SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam
Ali, Mutmainnah
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Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Education Physics

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The Relationship of Rainfall Variability to Flood Events Using Google Earth Engine (GEE) In Makassar City Ali, Mutmainnah; Nasrul, Nasrul; Nyompa, Sukri; Arfandi, Arfandi; Maru, Rosmini
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 1 (2025): Maret
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat141709192025

Abstract

Indonesian people are most harmed by flood hydrometeorological disasters, which cause material and immaterial losses. Floods often occur in some areas of Makassar City due to high rainfall and the high density of people and buildings, especially in the rainy season. This study aims to find out: the rainfall variability in the city of Makassar for 7 years (2017-2023), a map of flood inundation areas in the city of Makassar for 7 years (2017-2023), and the relationship between rainfall variability to flood events using Google Earth Engine (GEE) in the city of Makassar.  This study is quantitative descriptive, using correlation and regression analysis between rainfall variables and flood inundation area.  A cloud-based processing approach. CHIRPS data was used for rainfall analysis in Makassar City (2017-2023), and Sentinel 1 to analyze the distribution of flood inundation. The results showed that 1) rainfall variability occurred in January, February, March, November, and March. With the highest coefficient of variance value with a value of 73% in November. 2) floods that often occur in the sub-districts of Manggala, Biringkanaya, Tamalate, Tamalanrea, and Rappocini. 3) There is a significant relationship between rainfall and events in Makassar City. Spatially there were 12 flood events, temporal flood events for 7 years (2017-2023) occurred in December, January, and February.    The parameters in this study are limited to rainfall and flood inundation, for that the next study is to add various relevant parameters based on Google Earth Engine.
The Relationship of Rainfall Variability to Flood Events Using Google Earth Engine (GEE) In Makassar City Ali, Mutmainnah; Nasrul, Nasrul; Nyompa, Sukri; Arfandi, Arfandi; Maru, Rosmini
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 1 (2025): Maret
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat141709192025

Abstract

Indonesian people are most harmed by flood hydrometeorological disasters, which cause material and immaterial losses. Floods often occur in some areas of Makassar City due to high rainfall and the high density of people and buildings, especially in the rainy season. This study aims to find out: the rainfall variability in the city of Makassar for 7 years (2017-2023), a map of flood inundation areas in the city of Makassar for 7 years (2017-2023), and the relationship between rainfall variability to flood events using Google Earth Engine (GEE) in the city of Makassar.  This study is quantitative descriptive, using correlation and regression analysis between rainfall variables and flood inundation area.  A cloud-based processing approach. CHIRPS data was used for rainfall analysis in Makassar City (2017-2023), and Sentinel 1 to analyze the distribution of flood inundation. The results showed that 1) rainfall variability occurred in January, February, March, November, and March. With the highest coefficient of variance value with a value of 73% in November. 2) floods that often occur in the sub-districts of Manggala, Biringkanaya, Tamalate, Tamalanrea, and Rappocini. 3) There is a significant relationship between rainfall and events in Makassar City. Spatially there were 12 flood events, temporal flood events for 7 years (2017-2023) occurred in December, January, and February.    The parameters in this study are limited to rainfall and flood inundation, for that the next study is to add various relevant parameters based on Google Earth Engine.
Co-Authors Arfandi Arfandi, Arfandi Nasrul Nasrul Rosmini Maru Sukri Nyompa