Pakistan is a flood-prone country and almost every year, it is hit by floods of varying magnitudes. This study was conducted to generate a flash flood map using analytical hierarchy process (AHP) and frequency ratio (FR) models in the ArcGIS 10.6 environment. Eight flash-flood-causing physical parameters were considered for this study. Five parameters were based on the digital elevation model (DEM), Advanced Land Observation Satellite (ALOS), and Sentinel-2 satellite, including distance from the river and drainage density slope, elevation, and land cover, respectively. Two other parameters were geology and soil, consisting of different rock and soil formations, respectively, where both layers were classified based on their resistance against water percolation. One parameter was rainfall. Rainfall observation data obtained from five meteorological stations exist close to the Chitral District, Pakistan. According to its significant importance in the occurrence of a flash flood, each criterion was allotted an estimated weight with the help of AHP and FR. In the end, all the parameters were integrated using weighted overlay analysis in which the influence value of the drainage density was given the highest value. This gave the output in terms of five flood risk zones: very high risk, high risk, moderate risk, low risk, and very low risk. According to the results, 1168 km², that is, 8% of the total area, showed a very high risk of flood occurrence. Reshun, Mastuj, Booni, Colony, and some other villages were identified as high-risk zones of the study area, which have been drastically damaged many times by flash floods. This study is pioneering in its field and provides policy guidelines for risk managers, emergency and disaster response services, urban and infrastructure planners, hydrologists, and climate scientists.

中文翻译：

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巴基斯坦开伯尔 - 普赫图赫瓦省 Chitral 区使用集成的层次分析过程和频率比模型进行山洪敏感性评估和分区

巴基斯坦是一个容易发生洪水的国家，几乎每年都会遭受不同程度的洪水袭击。本研究旨在在 ArcGIS 10.6 环境中使用层次分析法 (AHP) 和频率比 (FR) 模型生成山洪地图。本研究考虑了八个引起山洪暴发的物理参数。五个参数基于数字高程模型 (DEM)、高级陆地观测卫星 (ALOS) 和 Sentinel-2 卫星，分别包括与河流的距离和排水密度坡度、高程和土地覆盖。另外两个参数是地质和土壤，分别由不同的岩石和土壤构造组成，其中两层都根据它们对水渗透的抵抗力进行分类。一个参数是降雨量。从五个气象站获得的降雨观测数据存在于巴基斯坦 Chitral 区附近。根据其在山洪暴发中的重要性，在 AHP 和 FR 的帮助下，每个标准都被分配了一个估计的权重。最后采用加权叠加分析法对所有参数进行积分，其中排水密度的影响值取最高值。这给出了五个洪水风险区的输出：非常高风险、高风险、中等风险、低风险和非常低风险。结果显示，1168公里 所有参数均采用加权叠加分析进行积分，其中排水密度的影响值被赋予最高值。这给出了五个洪水风险区的输出：非常高风险、高风险、中等风险、低风险和非常低风险。结果显示，1168公里 所有参数均采用加权叠加分析进行积分，其中排水密度的影响值被赋予最高值。这给出了五个洪水风险区的输出：非常高风险、高风险、中等风险、低风险和非常低风险。结果显示，1168公里²，即总面积的 8% ，显示出非常高的洪水发生风险。Reshun、Mastuj、Booni、Colony 和其他一些村庄被确定为研究区的高风险区，这些村庄已多次受到山洪暴发的严重破坏。这项研究是该领域的先驱，为风险管理人员、应急和灾害响应服务、城市和基础设施规划人员、水文学家和气候科学家提供政策指导。