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Monte Carlo simulation-aided analytical hierarchy process (AHP) for flood susceptibility mapping in Gabes Basin (southeastern Tunisia)

机译:蒙特卡罗模拟辅助的层次分析法(AHP)用于加布斯盆地(突尼斯东南部)的洪水敏感性制图

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摘要

Flash floods are among the most severe hazards which have disastrous environmental, human, and economic impacts. This study is interested in the characterization of flood hazard in Gabes Catchment (southeastern Tunisia), considered as an important step for flood management in the region. Analytical hierarchy process (AHP) and geographic information system are applied to delineate and characterize flood areas. A spatial database was developed based on geological map, digital elevation model, land use, and rainfall data in order to evaluate the different factors susceptible to affect flood analysis. However, the uncertainties that are associated with AHP techniques may significantly impact the results. Flood susceptibility is analyzed as a function of weights using Monte Carlo (MC) simulation and Global sensitivity analysis. AHP and MC-AHP models gave similar results. However, compared to AHP approach, MC-AHP confidence intervals (95%) of the overall scores had small overlaps. Results obtained were validated by remote sensing data for the zones that showed very high flood hazard during the extreme rainfall event of June 2014 that hit the study basin.
机译:暴洪是最严重的危害之一,会对环境,人类和经济造成灾难性的影响。这项研究对表征加贝斯流域(突尼斯东南部)的洪灾危险具有重要意义,被认为是该地区洪灾管理的重要步骤。应用层次分析法(AHP)和地理信息系统来描绘和表征洪水区域。基于地质图,数字高程模型,土地利用和降雨数据开发了空间数据库,以评估易受洪水分析影响的不同因素。但是,与AHP技术相关的不确定性可能会严重影响结果。使用蒙特卡洛(MC)模拟和全局敏感性分析,将洪水敏感性作为权重的函数进行分析。 AHP和MC-AHP模型给出了相似的结果。但是,与AHP方法相比,总得分的MC-AHP置信区间(95%)重叠很小。通过遥感数据验证了在2014年6月袭击该研究盆地的极端降雨事件中表现出很高洪灾危险的区域的遥感数据。

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