Flash Floods Hazard Degrees Assessment Applying Multi-Attributes Utility Theory for Gulf of Suez Basins, Egypt

S. Abdelaziz, M. Gad, H. Ahmed
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Abstract

Good management of flash floods requires accurate estimation for both the hazard degrees and flood risk maps. Morphological parameters greatly affect the strength of flood’s hydrograph and accordingly the flash flood hazard degree. This study uses decision-making tools such as Multi Criteria Analysis (MCA) and/or Multi-Attribute Utility Theory (MAUT) to estimate the Gulf of Suez’s flash flood hazard degree, Sinai Peninsula, Egypt. The MAUT was applied successfully in estimating the hazard degrees of 56 basins in the coastal zone of the Suez Gulf. Based on the resulted correlation between all hydro-morphological parameters, only six equal weight parameters were selected and used to calculate the hazard degree. The results showed that, about 40 % of the 56 basins have high or moderately high hazard degree. Values of the correlation factors between the hydro-morphological parameters and the resulted hazard degrees are ranged between 0.813 for basin’s Sinuosity and 0.011 for Centroid Stream Slope. The weights of those parameters were non-linearly optimized to make the correlation of all chosen parameters with the hazard degree higher than or equal to the threshold value (0.6). Accordingly, percentage of basins with high or moderately high hazard degree have decreased to 32 %. Capability and validation of current model have been achieved using the damage information of some flood events in the last few decades. The comparison between current model’s scenarios and flood events showed that, all the affected basins that had high or moderated high hazard degree are highly coincide with the real cases.
基于多属性效用理论的埃及苏伊士湾流域山洪危险性评价
良好的山洪管理需要对灾害程度和洪水风险图进行准确的估计。形态参数对洪水线的强度影响很大,从而影响山洪的危害程度。本研究采用多准则分析(MCA)和/或多属性效用理论(MAUT)等决策工具对埃及西奈半岛苏伊西湾山洪灾害程度进行了评估。该方法成功地应用于苏伊士湾海岸带56个盆地的灾害程度估算。根据各水文形态参数之间的相关性,选取6个等权重参数计算灾害程度。结果表明,56个流域中约有40%的流域为高、中高危险度。水文形态参数与流域曲度的相关系数为0.813,质心河流坡度的相关系数为0.011。对各参数的权重进行非线性优化,使所选参数与危险程度的相关性均大于或等于阈值(0.6)。相应的,高、中高危险度的流域比例下降到32%。利用近几十年来一些洪涝灾害的灾情信息,验证了现有模型的能力和有效性。当前模型情景与洪水事件的对比表明,所有具有高或中度高危险度的受影响流域与实际情况高度吻合。
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