Flash flood hazard initiated by heavy rainstorms is common in arid Jordan, and often has induced immense damage to life and infrastructures. The current study presents a flash flood assessment for Wadi Rajil (northern...Flash flood hazard initiated by heavy rainstorms is common in arid Jordan, and often has induced immense damage to life and infrastructures. The current study presents a flash flood assessment for Wadi Rajil (northern Jordan) and Wadi Wuheida (southern Jordan) watersheds using ASTER DEM, GIS, and geomorphic field observation. A total of 23 morphometric parameters of paramount relation to flash flood risk estimation were extracted and calculated using ASTER DEM, GIS, and mathematical formulae developed for this purpose. Two methods were employed to assess flash floods and to generate flooding risk susceptibility maps. The first method is El-Shamy’s approach, and the second is the morphometric hazard degree assessment method. Consequently, sub-basins with high and extreme flooding susceptibility were demarcated and displayed spatially using GIS. The maps so produced are meant to help planners and decision makers to devise appropriate plans to mitigate harmful flooding impacts, and to deal with flooding hazards.展开更多
为分析“暴雨-山洪-地质灾害”的灾变特点,利用自动化抓取技术提取了2010—2022年国内权威新闻媒体对长江中上游区域的暴雨、山洪、滑坡、泥石流等灾害的报道数据。基于自然语言处理(Natural Language Processing, NLP)技术和机器学习方...为分析“暴雨-山洪-地质灾害”的灾变特点,利用自动化抓取技术提取了2010—2022年国内权威新闻媒体对长江中上游区域的暴雨、山洪、滑坡、泥石流等灾害的报道数据。基于自然语言处理(Natural Language Processing, NLP)技术和机器学习方法,对新闻文本进行了预处理与数据清洗,实现了灾害信息的自动分类。进而,采用贝叶斯网络模型构建了灾害链的拓扑结构,推演了灾害演化过程中的各节点概率,揭示了“暴雨-山洪-地质灾害”链的情景演化规律。最后,以四川省凉山州冕宁县2020年的灾害事件为例,预测了“暴雨-山洪-地质灾害”网络中各情景节点概率,验证了贝叶斯网络模型的可靠性。结果表明,构建的“暴雨-山洪-地质灾害”的贝叶斯网络模型在山洪、泥石流、滑坡、人员伤亡、房屋倒塌等目标变量预测中,预测结果与实际数据基本一致,各目标变量的Brier检验平均结果为0.115。研究结论为“暴雨-山洪-地质灾害”的预测和情景演化分析提供了方法支撑。展开更多
文摘Flash flood hazard initiated by heavy rainstorms is common in arid Jordan, and often has induced immense damage to life and infrastructures. The current study presents a flash flood assessment for Wadi Rajil (northern Jordan) and Wadi Wuheida (southern Jordan) watersheds using ASTER DEM, GIS, and geomorphic field observation. A total of 23 morphometric parameters of paramount relation to flash flood risk estimation were extracted and calculated using ASTER DEM, GIS, and mathematical formulae developed for this purpose. Two methods were employed to assess flash floods and to generate flooding risk susceptibility maps. The first method is El-Shamy’s approach, and the second is the morphometric hazard degree assessment method. Consequently, sub-basins with high and extreme flooding susceptibility were demarcated and displayed spatially using GIS. The maps so produced are meant to help planners and decision makers to devise appropriate plans to mitigate harmful flooding impacts, and to deal with flooding hazards.
文摘为分析“暴雨-山洪-地质灾害”的灾变特点,利用自动化抓取技术提取了2010—2022年国内权威新闻媒体对长江中上游区域的暴雨、山洪、滑坡、泥石流等灾害的报道数据。基于自然语言处理(Natural Language Processing, NLP)技术和机器学习方法,对新闻文本进行了预处理与数据清洗,实现了灾害信息的自动分类。进而,采用贝叶斯网络模型构建了灾害链的拓扑结构,推演了灾害演化过程中的各节点概率,揭示了“暴雨-山洪-地质灾害”链的情景演化规律。最后,以四川省凉山州冕宁县2020年的灾害事件为例,预测了“暴雨-山洪-地质灾害”网络中各情景节点概率,验证了贝叶斯网络模型的可靠性。结果表明,构建的“暴雨-山洪-地质灾害”的贝叶斯网络模型在山洪、泥石流、滑坡、人员伤亡、房屋倒塌等目标变量预测中,预测结果与实际数据基本一致,各目标变量的Brier检验平均结果为0.115。研究结论为“暴雨-山洪-地质灾害”的预测和情景演化分析提供了方法支撑。
