Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Teknik Sipil
Triono, Reno
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture

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

Found 1 Documents
Search

 1 
Comparative Analysis of Rainfall Estimation Methods Using Observation Data and Satellite Data in Coastal Areas of Kalimantan Barat Province Triono, Reno; Utomo, Kiki Prio; Jati, Dian Rahayu
Jurnal Teknik Sipil Vol 24, No 4 (2024): Vol 24, No 4 (2024): JURNAL TEKNIK SIPIL EDISI NOVEMBER 2024
Publisher : Fakultas Teknik Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jts.v24i4.80879

Abstract

This study analyzes the accuracy of satellite rainfall data compared to observed data at several stations in West Kalimantan from 1998 to 2019. Three methods"”Normal Ratio, Algebraic Mean, and Inverse Square Distance"”were employed to address missing rainfall data. Among these, the Inverse Square Distance method provided the highest coefficient of determination (R ²), with values nearing one at Ketapang, Tebas, and Singkawang stations. Evaluation using RMSE and Relative Bias revealed variations in data accuracy across stations. Satellite data showed high accuracy at Sukadana and Ketapang but lower accuracy at Singkawang, highlighting the need for location-specific calibration. Graphical analyses showed consistent annual rainfall patterns between satellite and observed data despite differences in magnitude during specific years. Comparative studies of three data sources"”observational, satellite, and BMKG"”demonstrated similar trends, with satellite data exhibiting fewer fluctuations and higher stability. Satellite rainfall data is a reliable alternative for estimating rainfall patterns in areas with limited observational data. However, further adjustments are required to enhance its accuracy in specific locations. This study underscores the importance of refining satellite data models for better hydrological management and prediction accuracy.
Co-Authors Jati, Dian Rahayu Utomo, Kiki Prio