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All Journal Jurnal Teknik Sipil
Fikri, Rijal Muhammad
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Civil Engineering, Building, Construction & Architecture

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Flood Inundation Mapping in the Cimanceuri River through Integration of HEC-HMS and HEC-RAS as A Basis for Flood Risk Management Fikri, Rijal Muhammad; Herawati, Henny; Pranoto, Wati Asriningsih
Jurnal Teknik Sipil Vol 25, No 4 (2025): Jurnal Teknik Sipil: Vol 25, No. 4, November 2025
Publisher : Fakultas Teknik Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jts.v25i4.97772

Abstract

Flooding has become a recurring hazard in parts of Tangerang Regency, particularly in the Cimanceuri River Basin, where communities are increasingly vulnerable to inundation. Repeated flood events recorded over recent years highlight the urgent need for data-driven approaches in flood risk mitigation and management. This study aims to model the basin's hydrological characteristics and hydraulic regime using the eventual inundation map to support flood risk management planning in Tangerang Regency. To do so, HEC-HMS was used to compute flood discharge during the March 3, 2025, event in Pagedangan Subdistrict. The computed discharge was used as input to generate the inundation map using HEC-RAS 2D, supported by LiDAR-derived digital elevation model data. This area imagery of flood inundation served as the basis for model calibration. The results showed that the developed model accurately mapped the inundation, yielding a simulated total inundation area of 6.705 hectares.
Intercomparison of Gauge, Satellite (GPM), And ARR Rainfall Data Using Extended Triple Collocation Analysis Fikri, Rijal Muhammad; Herawati, Henny; Pranoto, Wati Asriningsih
Jurnal Teknik Sipil Vol. 26 No. 2 (2026): Vol 26, No 2 (2026): Vol 26, No 2 (2026): Jurnal Teknik Sipil (JTS) Universita
Publisher : Fakultas Teknik Universitas Tanjungpura

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Abstract

Accurate rainfall data are essential for reliable hydrological analysis, yet different measurement methods can yield varying estimates, and the true areal precipitation cannot be directly observed. This study evaluates three rainfall datasets—BMKG observations, Global Precipitation Measurement (GPM), and Automatic Rainfall Recorder (ARR)—using the Extended Triple Collocation (ETC) method in the Cimanceuri Watershed, Indonesia. Daily rainfall data from two representative locations were temporally and spatially collocated for comparative analysis. The results demonstrate location-dependent differences in dataset performance. At Budiarto–Curug, GPM produced the lowest estimated error (RMSE = 7.62 mm), whereas ARR achieved the highest correlation with the unknown rainfall signal (r² = 0.83). At Tangerang–Kresek, ARR showed the best overall performance, with the lowest RMSE (7.26 mm) and highest r² (0.65), while BMKG exhibited the highest error (RMSE = 15.94 mm). Ground-based datasets captured greater rainfall variability, whereas GPM provided smoother estimates. These findings indicate that rainfall dataset performance is influenced by location, spatial variability, and measurement characteristics. ETC offers an objective framework for evaluating rainfall datasets in the absence of a known reference and supports data selection for hydrological modeling and water resources management.
Co-Authors Herawati, Henny Pranoto, Wati Asriningsih