Utilizing the SAR, GIS, and Novel Hybrid Metaheuristic-GMDH Algorithm for Flood Susceptibility Mapping

On 14 March 2019, Tropical Cyclone Idai generated a devastating flood incident in Mozambique with considerable socioeconomic consequences. 1.85 million people were affected, and 602 others were killed. Generally, this region has been prone to flood disasters. Hence, preparing flood susceptibility maps can play a significant role in reducing the negative impacts of floods on lives and properties of people as well as the critical infrastructures. In this study, 10 influential factors on flood occurrence were analyzed using the geographic information system (GIS) coupled with the synthetic-aperture radar (SAR) data and the hybrid gray wolf optimizer-group method of data handling (GWO-GMDH). The results indicated that the hybrid GWO-GMDH model outperformed GMDH in mapping flood susceptibility. According to the GWO-GMDH model, 19.40% and 15.52% of the study area was found to be high and very high susceptible to flooding, respectively. The generated maps are beneficial for decision makers in mitigating flood damages and risk management.