Urban Flood Vulnerability Mapping using Analytical Hierarchy Process (AHP) for the city of Hyderabad, India

Urban flooding is one of the most recurring natural hazards, and more often it causes property damages including human losses, thereby disrupting socio-economic balance. Cities in developing countries such as in India expanded rapidly with unplanned urbanization and insufficient infrastructure, which increased the likelihood of cities getting flooded. In this regard, it is important to identify, map and predict flood vulnerable areas so that stakeholders of different types act and make decisions in a timely fashion. However, developing a model that provides information is challenging because of the difficulties in representing urban drainage information as well as urban flood processes, which are typically complex. Therefore, to this end, a data-driven model that integrates causative factors is explored. Using the advancements in Remote Sensing (RS) and Geographical Information System (GIS) in terms of finer resolution data and relatively easy access to the data, Analytical Hierarchy Process (AHP) approach is chosen. A variety of causative factors are considered, i.e., land use and land cover (LULC), elevation and slope, rainfall distribution, road network, drainage network and drainage density. AHP models for different rainfall events for a few sections of the Hyderabad city are developed, and then maps of flood vulnerable regions are generated. The maps are validated with flooded areas from different sources such as newspapers. The proposed framework showcases utilization of geospatial information including RS & GIS based, thus it offers a solution in flood management particularly, for data poor regions.