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All Journal JTSL (Jurnal Tanah dan Sumberdaya Lahan) MAKILA: Jurnal Penelitian Kehutanan
Talakua, Silwanus M
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Environmental Science

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Kajian Meteorologis dari Fenomena Hujan Ekstrim terhadap Kejadian Banjir di Kota Ambon Makaruku, Eunike L; Talakua, Silwanus M; Kunu, Pieter J
MAKILA Vol 19 No 1 (2025): MAKILA: Jurnal Penelitian Kehutanan
Publisher : Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/makila.v19i1.13711

Abstract

This study investigates the meteorological factors contributing to extreme rainfall events and their relationship with flood occurrences in Ambon City. Based on a comprehensive global analysis of several atmospheric parameters, the results reveal: (1) a closed circulation pattern (streamline) over the Karimata Strait and Cenderawasih Bay, leading to the convergence and deceleration of easterly winds; (2) high atmospheric humidity ranging from 80% to 100%, coupled with warm sea surface temperatures (26–30°C), which significantly increase water vapor availability for cloud formation and development; and (3) a Southern Oscillation Index (SOI) of +10.39 and a Niño Index of -0.8, indicating the presence of a weak La Niña phenomenon that contributes to increased rainfall across Ambon City and the Maluku region. These atmospheric conditions collectively elevate the potential for hydrometeorological disasters, including severe flooding (BMKG, 2024). Ambon City, located within the Maluku Islands, exhibits a distinct local rainfall pattern that contrasts with Indonesia’s monsoonal climate, with its peak rainy season occurring from June to August, coinciding with the national dry season. This study aims to analyze the physical atmospheric conditions during extreme rainfall events and their influence on flood occurrences in Ambon City. Utilizing a descriptive-analytic approach, the research focuses on real field events to explore the underlying mechanisms driving these phenomena. The findings demonstrate a significant correlation between extreme rainfall and flood events, with atmospheric indices confirming conditions that favor intense convective activity, prolonged heavy rainfall, and subsequent flooding.
UJI VALIDASI  SISTEM  PREDIKSI PERINGATAN DINI BERBASIS DAMPAK UNTUK BENCANA BANJIR DI KOTA AMBON Iriyanto, Suaif; Kunu, Pieter J; Puturuhu, Ferad; Talakua, Silwanus M
JTSL (Jurnal Tanah dan Sumberdaya Lahan) Vol. 13 No. 2 (2026)
Publisher : Departemen Tanah, Fakultas Bio-industri Pertanian dan Kehutanan, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtsl.2026.013.2.10

Abstract

Ambon City a high level of vulnerability to floods due to steep topography, extreme rainfall, and land use that exceeds land capability. Floods pose a serious threat to community safety and cause damage to infrastructure. Risk reduction requires an accurate and well-implemented early warning system. This study aims to analyze the spatial level of flood disaster risk, examine the distribution of extreme rainfall during rainfall events, and assess the accuracy of the Impact-Based Forecast and Warning Services System (IBFWS). The research method includes spatial analysis using a Geographic Information System (GIS) through an overlay approach of three risk components: hazard, vulnerability, and capacity. The study also applies Inverse Distance Weighting (IDW) methods for spatial interpolation of 24-hour rainfall data from the events on May 11 and May 30, 2023, and conducts spatial validation of the IBFWS prediction results against actual landslide occurrences. The results show that 75.6% of Ambon City falls into the high-risk category for floods. Multiple linear regression analysis indicates that slope gradient is the most significant variable influencing floods hazard, with an R² value of 90.6% and an S value of 0.120. Spatial validation and field verification demonstrate that the accuracy of the IBFWS reached 94% for the floods event on May 11 and 100% for the event on May 30, 2023. These findings indicate that the IBFWS functions as a reliable early warning system to support floods disaster risk reduction in Ambon City.
Co-Authors Ferad Puturuhu Iriyanto, Suaif Makaruku, Eunike L Pieter J Kunu