ANALYZING THE EFFECTS OF LAND USE / COVER CHANGE (LULCC) SIMULATION ON FLOODING: A CASE STUDY IN LAS NIEVES, AGUSAN DEL NORTE, MINDANAO, PHILIPPINES
Keywords: LULCC, Prediction, Flood Simulation, SVM, MOLUSCE, Sentinel-2
Abstract. The municipality of Las Nieves, located in Agusan del Norte, Mindanao, Philippines, has experienced floods and flood-related damages in the floodplain region in recent years. Despite the best intentions of planning and implementing projects anchored in its comprehensive land use plans, recurring flooding significantly impacts its residents. Due to its growing population, changes in land cover are inevitable. The changes can result in increased overland flow and decreased infiltration rates. This study was conducted to determine and quantify the effect of changing the land use/land cover (LULC) on the flooding condition in the municipality. Base LULC map was generated using Sentinel-2 image captured in 2021. Support Vector Machine classifier was used in the classification resulting in an accuracy of 94.07%. The 2021 LULC map was the reference for predicting future LULCs for 2025 and 2029 implemented in MOLUSCE and was utilized for flood simulation. HEC-HMS and HEC-RAS were used to generate flood depth maps of different extreme rainfall scenarios. The results showed that as the rainfall event increased, the extent of affected LULC areas also increased. Based on the rainfall impact assessment results, the annual cropland was the most impacted LULC class across the various LULC classes. The class open forest is the least affected class for 2021, 2025, and 2029. However, the barren was the least affected in the scenario-based build-up increase. These assessments are especially pertinent because storm-related rains have been increasingly severe recently and will continue due to climate change. The simulations and flood mapping knowledge can inform and empower the Local Government Unit of Las Nieves. It will guide them in developing informed decision frameworks for mitigating significant land surface variabilities and adapting effective future land use plans to reduce the adverse effects of flooding.