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.