Flood vulnerability analysis for inland medium-sized cities: Guang’an as an example

University essay from KTH/Geoinformatik

Abstract: Vulnerability studies look into the impact of hazard events on socio-ecological systems. Socio-ecological vulnerability is a very complex subject because it is not only a technical matter but also a social problem. Precise assessment of socio-ecological vulnerability can help people successfully reduce potential losses caused by disasters as well as provide decision support for decision makers to take different urban planning strategies in areas of different vulnerability levels when making development and construction.   In previous studies, the definition of vulnerability is vague, which leads to diverse vulnerability framework. Vulnerability assessment is hazard-specific, most vulnerability studies are centered on a certain hazard, such as floods. To evaluate vulnerability, previous literatures combined qualitative and quantitative methods, such as narrative interviews, uniform vulnerability level ranking systems, statistical methods, GIS methods, etc. GIS methods are especially widely used in vulnerability studies. However, because of the complexity and vagueness of vulnerability, previous studies did not reach a consensus, even on the framework. The most focuses of flood vulnerability researches at city level are put on big coastal cities, while small & medium inland cities which also suffer severe flood disasters are usually ignored. A flood vulnerability map with vulnerability level from high to low is usually created in previous flood vulnerability assessment studies. However, this kind of flood vulnerability map can only tell the general flood risk states, ignoring the inherent details, which may confuse decision makers.   Considering these problems, the objective of this research is to put forward a socio-ecological vulnerability assessment framework. As most previous researches suggested, the socio-ecological vulnerability is a function of exposure, sensitivity, and adaptation. In this research, the vulnerability is classified into 27 situations. The exposure, sensitivity, and adaptation are grading into three levels respectively. Of course, more levels can be used, but a three-level system, including high, medium, and low, is sufficient enough to describe the state of a place. Each vulnerability situation is a combination of a state of exposure, sensitivity, and adaptation. In this case, the vulnerability map makes it easier for decision makers to understand the inner structure of vulnerability level. This framework is applied to Guang’an, an inland medium-sized Chinese city which has suffered severe flood disasters. Flood is considered as the hazard. The assessment parts of exposure, sensitivity, and adaptation involve different data sets and methodologies. By an overlay analysis of these assessment results, the flood vulnerability map is derived. According to different situations in the flood vulnerability map, different coping strategies are given. Finally, a flood vulnerability assessments tool based on python script and model builder in ArcGIS10.2 and a GIS app based on ArcGIS Engine 10.2 are created. This ArcGIS tool can be applied to other cities, making the vulnerability framework and methodologies proposed in this research be widely used. The GIS app is used to store some useful information of Guang’an and show the vulnerability results, which can be used directly by decision makers.

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