Flash Flood Early Warning and Monitoring System for Disaster Management in Al-Batina Region

Flash floods are dangerous weather-related natural disasters that can create hazardous situations for people and caused extensive damage to property. The main hydrological factors contributing to flash flooding are the size, shape, topography, and land cover of the watershed. While they are common in arid environments, their occurrence is also poorly understood. In Oman, flash floods have increased over the past decade, caused by frequent and severe rainfall within short time periods. Oman?s flash floods challenges are further compounded by recurrent cyclonic storms with devastating aftermaths. Also contributing to Oman?s flash floods problems are rapid expansion of urban areas, its non-absorptive surface areas, non-efficient drainage, clogged networks, and prolific construction in low slopes and wadis that not only increase flood related disasters but cause significant property damage, environmental destruction and tragically, loss of human lives. Despite this increase in flash flooding, Oman lacks an effective warning system able to precisely predict flash flood locations, time and size as recently evidenced during Cyclone Shaheen, which hit Al-Batina in October 2021. The purpose of the proposed research project is to propose flash flood early warning and smart monitoring system for disaster management in Al-Batina region and mainly the areas that severely affected during Shaheen cyclone. Thus, this system will incorporate Flash Flood Guidance (FFG), newly developed Artificial Intelligence (AI) techniques for monitoring during and after the events through smart monitoring network for real time monitoring and measurements of flash floods using cameras, and produce updated maps of flash flood hazard areas in the study area by using 2D-inundation modelling. These hazard maps will support the stakeholders in flood risk management and disaster in defense and emergency planning. In addition, new technologies based on remotely sensed observations and Unmanned Aerial Vehicle (UAV) will be used to observe and produce high resolution wadis? channels and floodplains geometry and elevation, land use/land cover, and vegetation cover. This proposed project will also shape new flood warning system policies to solidify an improved early flood warning system and management designed to significantly reduce Hazard from devastating flood events.

Flash floods are dangerous weather-related natural disasters that can create hazardous situations for people and caused extensive damage to property. The main hydrological factors contributing to flash flooding are the size, shape, topography, and land cover of the watershed. While they are common in arid environments, their occurrence is also poorly understood. In Oman, flash floods have increased over the past decade, caused by frequent and severe rainfall within short time periods. Oman?s flash floods challenges are further compounded by recurrent cyclonic storms with devastating aftermaths. Also contributing to Oman?s flash floods problems are rapid expansion of urban areas, its non-absorptive surface areas, non-efficient drainage, clogged networks, and prolific construction in low slopes and wadis that not only increase flood related disasters but cause significant property damage, environmental destruction and tragically, loss of human lives. Despite this increase in flash flooding, Oman lacks an effective warning system able to precisely predict flash flood locations, time and size as recently evidenced during Cyclone Shaheen, which hit Al-Batina in October 2021. The purpose of the proposed research project is to propose flash flood early warning and smart monitoring system for disaster management in Al-Batina region and mainly the areas that severely affected during Shaheen cyclone. Thus, this system will incorporate Flash Flood Guidance (FFG), newly developed Artificial Intelligence (AI) techniques for monitoring during and after the events through smart monitoring network for real time monitoring and measurements of flash floods using cameras, and produce updated maps of flash flood hazard areas in the study area by using 2D-inundation modelling. These hazard maps will support the stakeholders in flood risk management and disaster in defense and emergency planning. In addition, new technologies based on remotely sensed observations and Unmanned Aerial Vehicle (UAV) will be used to observe and produce high resolution wadis? channels and floodplains geometry and elevation, land use/land cover, and vegetation cover. This proposed project will also shape new flood warning system policies to solidify an improved early flood warning system and management designed to significantly reduce Hazard from devastating flood events.