Comparative Analysis of Observed and Empirical Rainfall Distribution for Flood Hydrograph Modeling

Flood disasters in Indonesia are persistent challenges during the rainy season, primarily due to intense rainfall and inadequate flood control. This study evaluates hourly rainfall to characterize hydrology and predict flood discharge more accurately, benefiting water infrastructure planning. The research used modified Mononobe methods, observational data, and rainfall-runoff modeling, including HEC-HMS simulations with the SCS-CN unit hydrograph. Observed rainfall simulated a flood discharge of 779.7 m³/s, while empirical rainfall yielded 3623 m³/s, showing a 79.12% deviation. Comparing flood hydrographs, recorded rainfall data closely matched previous studies (R² = 0.94), unlike empirical rainfall (R² = 0.88). The study concludes that observed rainfall is highly effective for estimating flood runoff, accurately representing local characteristics. This method significantly aids planning and design of water resource infrastructure like dams, weirs, and bridges at the study site.

Authors

Institutions

Publication Details

Journal
Advance Sustainable Science Engineering and Technology
Published
2025-08-22
DOI
https://doi.org/10.26877/asset.v7i3.2142
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative Analysis of Observed and Empirical Rainfall Distribution for Flood Hydrograph Modeling

Sri Sangkawati, Suripin, Risdiana Cholifatul Afifah, Dyah Ari Wulandari
Advance Sustainable Science Engineering and Technology
Hydrology and Watershed Management Studies
article

Comparative Analysis of Observed and Empirical Rainfall Distribution for Flood Hydrograph Modeling

Sri Sangkawati, Suripin, Risdiana Cholifatul Afifah, Dyah Ari Wulandari
article en

Abstract

Flood disasters in Indonesia are persistent challenges during the rainy season, primarily due to intense rainfall and inadequate flood control. This study evaluates hourly rainfall to characterize hydrology and predict flood discharge more accurately, benefiting water infrastructure planning. The research used modified Mononobe methods, observational data, and rainfall-runoff modeling, including HEC-HMS simulations with the SCS-CN unit hydrograph. Observed rainfall simulated a flood discharge of 779.7 m³/s, while empirical rainfall yielded 3623 m³/s, showing a 79.12% deviation. Comparing flood hydrographs, recorded rainfall data closely matched previous studies (R² = 0.94), unlike empirical rainfall (R² = 0.88). The study concludes that observed rainfall is highly effective for estimating flood runoff, accurately representing local characteristics. This method significantly aids planning and design of water resource infrastructure like dams, weirs, and bridges at the study site.

Advance Sustainable Science Engineering and TechnologyVol. 7(3)
Diponegoro University (ID)
Openalex Percentile: Top 79%
Hydrology and Watershed Management Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.