Estimasi Sebaran Banjir Menggunakan Model HEC-RAS 2D (Studi Kasus : DAS Anai, Sumatera Barat)
Abstract
Sungai Anai berpotensi menimbulkan banjir di wilayah Kabupaten Padang
Pariaman, khususnya pada ruas Jembatan Kayu Gadang sampai Jembatan Batang
Anai. Hal tersebut diakibatkan curah hujan yang tinggi, menurunnya kualitas dan
kuantitas sistem drainase, alih fungsi lahan, berkurangnya daerah resapan air di hulu
DAS, dan perilaku masyarakat. Penelitian ini bertujuan untuk mengestimasi lokasi,
kedalaman, dan luasan sebaran genangan banjir menggunakan model HEC-RAS
(2D). Estimasi sebaran banjir dimulai dari penentuan debit kejadian banjir,
pembuatan model yang terdiri dari pre-processing, running HEC-RAS, dan post
processing. Hasil model diuji dengan citra observasi (Landsat-8) menggunakan
metode Tasseled Cap Transformation untuk menentukan Wetness Index berupa
kelembapan tanah. Banjir hasil model menunjukkan wilayah terdampak banjir
mencakup 5 Nagari atau Desa. Genangan terluas dan terdalam dari empat kejadian
banjir terletak di Nagari Sungai Buluah sebesar 547,44 Ha. Nagari Buayan menjadi
Nagari dengan luas wilayah total terdampak tertinggi sebesar 20,8% dari total luas
wilayah. Akurasi keluaran model paling tinggi 72%, artinya 72% model dapat
diimplementasikan dalam estimasi banjir. The Anai River has the potential to cause flooding in the Padang Pariaman
Regency area, especially on the Kayu Gadang Bridge to Batang Anai Bridge. This
is due to high rainfall, decreased quality and quantity of drainage systems, land
conversion, reduced water catchment areas in upstream watersheds, and community
behavior. This study aims to estimate the location, depth, and distribution of flood
inundation using the HEC-RAS (2D) model. The estimation of flood distribution
starts from determining the discharge of flood events, making a model consisting
of pre-processing, running HEC RAS, and post-processing. The results of the model
were tested with observational images (Landsat-8) using the Tasseled Cap
Transformation method to determine the Wetness Index in the form of soil moisture.
The flood model results show that the flood-affected area includes 5 Nagari or
Villages. The widest and deepest inundation of the four flood events is located in
Nagari Sungai Buluah with an area of 547.44 hectares. Nagari Buayan is the Nagari
with the highest total area affected by 20.8% of the total area. The highest model
output accuracy is 72%, meaning that 72% of the model can be implemented in
flood estimation.