Integrasi Fusi Spasial Lidar Airborne dan Survei Terestris Untuk Pemodelan Hidraulik 2D Kali Kamal Jakarta

Akbar Ramadhan; Endah  Kurniyaningrum; Bagus  Handyastono

doi:10.70716/reswara.v4i4.764

Authors

Akbar Ramadhan Program Studi Magister Teknik Sipil, Fakultas Teknik Sipil dan Perencanaan, Universitas Trisakti, Jakarta, Indonesia Author
Endah Kurniyaningrum Program Studi Magister Teknik Sipil, Fakultas Teknik Sipil dan Perencanaan, Universitas Trisakti, Jakarta, Indonesia Author
Bagus Handyastono PT. Inakko Internasional Konsulindo Author

DOI:

https://doi.org/10.70716/reswara.v4i4.764

Keywords:

HEC-RAS 2D, Spatial Fusion, Airborne LiDAR, Terrestrial Survey

Abstract

Flooding in the Kali Kamal Watershed, Tegal Alur Village, West Jakarta, occurred repeatedly during 2020–2025, with inundation depths of 20–50 cm or more due to extreme rainfall, river overflow, sedimentation, and tidal effects. Accurate hydraulic modeling is essential for effective flood mitigation. However, secondary Airborne LiDAR data in DWG format may have limitations in spatial representation and riverbed characterization. This study integrates secondary Airborne LiDAR DWG data with terrestrial cross-section surveys using a total station to improve wet-channel representation in HEC-RAS 2D modeling. Three elevation models were evaluated: Model A, combining DWG LiDAR and terrestrial survey data; Model B, combining satellite DEM and terrestrial survey data; and Model C, using satellite DEM alone. Model performance was assessed using vertical Root Mean Square Error (RMSE), Linear Error 90% (LE90), and Nash-Sutcliffe Efficiency (NSE), with simulation results validated against historical flood data from 2020–2025. Model A achieved the highest accuracy, with an RMSE of 0.090 m, LE90 of 0.148 m, and NSE of 0.942. It met the geometric accuracy standards of the Geospatial Information Agency (BIG) and reduced false flood estimates by up to 25.00%. The HEC-RAS 2D simulation based on Model A also showed good agreement with historical inundation patterns. These findings demonstrate that spatial fusion of secondary LiDAR and terrestrial survey data can improve elevation representation and support more reliable urban flood modeling and mitigation planning.

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