A comprehensive Analysis of the Application of GIS and RS Technologies in Flood Prediction and Risk Assessment, with a Focus on Wadi Baysh Dam in the Jazan region. KSA

Abstract

This study uses GIS spatial analysis and open-source data based on flood hazards formulas to provide a thorough analysis and forecast of floods using Geographic Information Systems (GIS) and Remote Sensing (RS). The Wadi Baysh Dam overflowed with water in 2016 as a result of the torrential downpour that hit the dam, its streams, and the surrounding surroundings results the increasing the storage capacity. In terms of water reserves, it is the dam that is thought to be the biggest in the Kingdom. Some settlements in Baysh, which are under siege since their highways are blocked off, suffered greatly as a result of flooding. However the storage capacity of Wadi Baysh Dam around 200 million cubic meters of water. In order to identify the actual Wadi Baysh flood-vulnerable area, this study combined data from remote sensing, the Geographic Information System (GIS) technique, and an Analytical Hierarchy Process (AHP) computation. The investigation was carried out to determine the viability of using remote sensing open-source data,basemap of the study area andArcGIS10.4 software in Wadi Baysh risk management. Slope (10%), height (15%), drainage density (20%), distance to stream (20%), rainfall intensity (25%), and land cover (10%) all have a proportion of relative weight that determines how flooding is analyzed. As a result of the most recent GIS analysis (weighted overlay approach), five zones are identified within the extracted flood region based on the categories of hazard. There are ten blocks in all—five in a high-risk area and five in a moderately dangerous one. The paper looks at the flood risk in Wadi Baysh using a combination and integration betweenremote sensing opensources data and GIS models. High precipitation and runoff in the dam’s downstream sections will be the main cause of difficulties, causing a great deal of death and destruction to agricultural and urban areas. Eventually, a control room connected to the GIS model and remote sensing devices will be needed in this valley to implement an efficient warning system and flood hazard management system.