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Flood Inundation Potential Analysis in Denpasar City Using Topographic Wetness Index from Digital Elevation Model
Sari
ABSTRAK
Banjir genangan sering terjadi di wilayah perkotaan, termasuk Kota Denpasar, akibat topografi, karakteristik daerah aliran sungai (DAS), dan perubahan penggunaan lahan. Penelitian ini bertujuan mengidentifikasi potensi genangan banjir menggunakan algoritma Topographic Wetness Index (TWI) berbasis Digital Elevation Model (DEM) multiresolusi serta mengevaluasi pengaruh resolusi spasial terhadap akurasi hasil pada skala perkotaan. Kebaruan penelitian terletak pada perbandingan kinerja DEM SRTM (30 m) dan ALOS PALSAR (12,5 m) untuk TWI pada DAS kecil perkotaan yang masih terbatas dikaji. Kedua DEM diseragamkan pada datum vertikal EGM 2008 dan dianalisis pada sembilan DAS sekitar Kota Denpasar. Hasil TWI diklasifikasikan menjadi lima kelas potensi genangan dan divalidasi menggunakan 33 titik kejadian banjir periode September–Desember 2025 menggunakan analisis sensitivitas berbasis confusion matrix kejadian. Hasil menunjukkan ALOS PALSAR memiliki tingkat sensivitas kesesuaian lebih tinggi (30,30%) dibanding SRTM (24,24%). Resolusi DEM lebih tinggi terbukti meningkatkan sensitivitas TWI dalam mendeteksi potensi genangan perkotaan dan mendukung perencanaan mitigasi banjir.
Kata kunci: ALOS PALSAR, banjir, digital elevation model, SRTM, topographic wetness index
ABSTRACT
Flood inundation frequently occurs in urban areas, including Denpasar City, due to topography, watershed characteristics, and land-use changes. This study aims to identify flood inundation potential using the Topographic Wetness Index (TWI) derived from multiresolution Digital Elevation Models (DEM) and to evaluate the effect of spatial resolution on model accuracy at the urban scale. The novelty lies in comparing SRTM (30 m) and ALOS PALSAR (12.5 m) DEM performance for TWI modelling in small urban watersheds. Both DEMs were standardized to the EGM 2008 vertical datum and analyzed across nine watersheds surrounding Denpasar. TWI outputs were classified into five inundation-potential classes and validated using 33 flood event points (September–December 2025) through event-based confusion matrix sensitivity analysis. Results indicate that ALOS PALSAR achieved higher sensitivity (30.30%) than SRTM (24.24%). Higher DEM resolution improves TWI sensitivity in detecting urban flood potential and provides more reliable information for flood mitigation planning.
Keywords: ALOS PALSAR, digital elevation model, flood, SRTM, topographic wetness index
Kata Kunci
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DOI: https://doi.org/10.26760/jrh.v10i1.37-50
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