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首页> 外文期刊>Stochastic environmental research and risk assessment >Delineation of flooding risk hotspots based on digital elevation model, calculated and historical flooding extents: the case of Ouagadougou
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Delineation of flooding risk hotspots based on digital elevation model, calculated and historical flooding extents: the case of Ouagadougou

机译：基于数字高程模型，洪水泛滥程度和历史洪水泛滥程度的洪灾风险热点区划：以瓦加杜古为例

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Delineation of flood risk hotspots can be considered as one of the first steps in an integrated methodology for urban flood risk management and mitigation. This paper presents a step-by-step methodology in a GIS-based framework for identifying flooding risk hotspots for residential buildings. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. The novelty of this paper consists in the fact that the flood-prone areas (the TWI thresholds) are identified through a maximum likelihood method (MLE) based both on inundation profiles calculated for a specific return period (T~(R)), and on information about the extent of historical flooding in the area of interest. Furthermore, Bayesian parameter updating is employed in order to estimate the TWI threshold by employing the historical extent as prior information and the inundation map for calculating the likelihood function. For different statistics of the TWI threshold, the map of potentially flood-prone areas is overlaid with the map of residential urban morphology units in order to delineate the residential flooding risk urban hotspots. Overlaying the delineated urban hotspots with geo-spatial census datasets, the number of people affected by flooding is estimated. These kind of screening procedures are particularly useful for locations where there is a lack of detailed data or where it is difficult to perform accurate flood risk assessment. In fact, an application of the proposed procedure is demonstrated for the identification of urban flooding risk hotspots in the city of Ouagadougou, capital of Burkina Faso, a city for which the observed spatial extent of a major flood event in 2009 and a calculated inundation map for a return period of 300 years are both available.
机译：在城市洪水风险管理和缓解的综合方法中，洪水风险热点区的划定可被视为第一步。本文介绍了基于GIS的框架中的分步方法，用于识别住宅建筑物的洪水风险热点。这是通过叠加潜在易发洪水区域的地图[通过地形湿度指数（TWI）估算]，居住区域的地图[从全市范围内的城市形态类型评估（UMT）中提取]和地理空间人口普查数据集。本文的新颖性在于，通过最大似然法（MLE）来识别易发洪水区域（TWI阈值），这两种方法都基于针对特定返回期（T〜（R））计算的淹没剖面，以及有关感兴趣地区历史洪水泛滥程度的信息。此外，采用贝叶斯参数更新以便通过将历史范围用作先验信息和淹没图来计算似然函数来估计TWI阈值。对于TWI阈值的不同统计，将潜在易发洪水区域的地图与住宅城市形态单位的地图重叠，以描绘出住宅洪灾风险城市热点地区。用地理空间普查数据集覆盖划定的城市热点，估计受洪水影响的人数。对于缺乏详细数据或难以进行准确的洪水风险评估的地点，此类筛选程序特别有用。实际上，已经证明了所建议程序的应用，可用于确定布基纳法索首都瓦加杜古市的城市洪灾风险热点，该城市观测到了2009年重大洪灾事件的空间范围并计算了淹没图都有300年的回报期。

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