Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches
Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches
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DOI：
10.3390/w7073531
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发表时间：
2015-07-01
期刊：
影响因子：
3.4
通讯作者：
Venus, Valentijn
中科院分区：
文献类型：
--
作者：
Asare-Kyei, Daniel;Forkuor, Gerald;Venus, Valentijn
可靠的风险评估需要准确的洪水强度区域绘图，以便识别面临风险的人群和要素。然而，西非现有的洪水图缺乏空间变异性，而全球数据集的分辨率太粗糙，与当地规模的风险评估无关。因此，当地灾害管理人员被迫使用传统的方法，如建筑物上的水印和媒体报道，以确定洪水危险区。在这项研究中，遥感和地理信息系统（GIS）技术与水文和统计模型相结合，以划定加纳、布基纳法索和贝宁选定社区洪水危险区的空间界限。该方法包括估计不同海拔高度的峰值径流浓度，然后应用统计方法制定洪水灾害指数（FHI）。结果表明，约有一半的研究区域属于高强度洪水区。利用统计混淆矩阵和分解式GIS原理进行的经验验证表明，洪水危险区可以在77%至81%的精度范围内映射。这得到了当地专家知识的支持，这些知识准确地将79%的社区分类为高度易受洪水危害的社区。研究结果将有助于灾害管理人员在社区一级减少洪水灾害风险，因为风险结果首先体现在社区一级。
Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS) techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI). Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.