Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam (JURRIMIPA)
Hamida Nasution
Unknown Affiliation
Mathematics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Estimasi Volume Air Hujan Menggunakan Metode Riemann untuk Mitigasi Banjir Musiman Adinda Saputri; Asni Al Amini; Alvi Sahri Nasution; Hamida Nasution; Livia Mutianda; Juanda Arif Darmawan Damanik; Mhd.Fachrizal
JURNAL RISET RUMPUN MATEMATIKA DAN ILMU PENGETAHUAN ALAM Vol. 4 No. 3 (2025): Desember : JURRIMIPA: Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrimipa.v4i3.7763

Abstract

Rainfall plays a crucial role in determining flood risk, particularly in regions with high precipitation intensity and limited drainage capacity. Langkat Regency in North Sumatra is one of the areas frequently affected by seasonal flooding. This study aims to model the spatial distribution of rainfall and estimate the rainwater volume using the double integral approach as a basis for flood mitigation planning. Monthly rainfall data from various observation stations in 2024 were processed to obtain the average rainfall intensity, which was then converted into meters and multiplied by the total area of Langkat Regency to compute the rainwater volume. The results indicate that the total estimated rainwater volume throughout 2024 reached 16,409,819,800 m³, with peak precipitation occurring from September to November, contributing significantly to the increasing flood risk in low‐lying zones and riverine areas. These findings demonstrate that the use of double integrals is an effective quantitative method for predicting potential flood volume based on rainfall distribution. The outcomes of this study are expected to serve as a scientific reference for local governments in developing data-driven flood mitigation strategies, such as improving drainage capacity, constructing retention basins, and strengthening watershed management.
Co-Authors Adinda Saputri Alvi Sahri Nasution Asni Al Amini Juanda Arif Darmawan Damanik Livia Mutianda Mhd.Fachrizal