利用长期格式降雨数据和微观地形洞察力来描述地表水泛滥的风险
Kriti Mukherjee1, Mónica Rivas Casado1, Rakhee Ramachandran1
1School of Water, Energy and Environment, Cranfield University, Bedford, United Kingdom.
PloS one
|September 24, 2024
概括
随着气候变化,地表水泛滥 (SWF) 的风险增加. 本研究使用降雨数据和高分辨率地形识别了英国脆弱的地点和物业,从而实现了针对性的洪水风险管理.
科学领域:
- 环境科学 环境科学
- 水文学的水文学
- 适应气候变化 适应气候变化
背景情况:
- 根据UKCP18的气候预测,英国的气候将变得更加温暖,更加潮湿,表面水淹没 (SWF) 风险也将增加.
- 由局部对流降雨驱动的SWF,由于其高时空分辨率要求,难以预测.
- 现有的SWF模型是计算密集的,限制了分辨率和预测的交付时间.
研究的目的:
- 开发一个框架来量化SWF危险和暴露在像素和属性级别.
- 确定局部区域和特定物业最容易受到SWF的影响.
- 为制定有针对性的洪水风险管理策略提供信息,包括财产抗洪能力 (PFR) 措施.
主要方法:
- 利用长期格式降雨数据来评估SWF危险在1公里×1公里像素分辨率.
- 集成的高分辨率 (10厘米摄影,25厘米LiDAR) 数字海拔模型 (DEMs) 用于微观地形分析.
- 集成了一个物业抗洪和弹性 (PFR) 数据库,以量化物业级SWF暴露.
主要成果:
- 在1公里×1公里像素级别成功量化了SWF危险,识别了脆弱的局部区域.
- 通过整合微观地形和PFR数据,在物业层面量化SWF暴露.
- 展示了一种方法来精确确定特定位置和物业的SWF高风险.
结论:
- 开发的框架有效地确定了在不断变化的气候条件下易受SWF影响的区域和物业.
- 这种方法为实施有效的SWF风险管理和PFR策略提供了关键数据.
- 针对性干预,例如PFR装置,可以优先考虑被确定为最脆弱的物业.
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