DECISION SUPPORT SYSTEM FOR FLOOD RISK ASSESSMENT

Abstract

A disaster occurs when an extreme geological, meteorological, hydrological or any intolerable human event exceeds the ability of a community to cope with that event. One such disaster is flood. It is of the utmost importance to understand to understand its causes and to decision support system. For this a DSS needs. to be constructed. From a comprehensive vulnerability assessment and hazard mitigation standpoint, it is necessary to look beyond the effects of an event on a single system as it is quite complex. DSS will require more than just improved engineering and technology. A DSS requires large amount of spatial and non spatial data and disaster modelling techniques, apart from this assessment techniques. Spatial information can be derived from medium and high resolution satellite images. Sequential images can provide information on changes in flood plain. The spatial information with non spatial data can effectively integrated in GIS for modelling the natural disaster phenomenon which may be ultimately used predicting flood risk areas. The aim of this thesis to build a GIS based decision support for flood risk assessment and flash flood hazard mapping of Vinhphuc Province. To do this GIS-based DSS approach was used to build geodatabase for the selected flood hazard layers and elements at risk (land use and population density).Then the important factors were developed to a uniform raster layers and each factor is standardized and then a pair wise comparison method is used to determine the factor weights: Then weighted overlay analysis in multi criteria evaluation (MCE) is used to carry out flood hazard and risk analysis. The major findings of this thesis showed that most of the land use types in the town are within low to moderate flood hazard and flood risk level. With these Vinh phuc Province flood risk map and flash flood hazard map, Development of future land use in development policy should be done to decrease the hazard of flooding in Vinh phuc Province