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基于数据驱动的框架,研究降水的时空动态特征和水浸的原因
Feifei Han1, Xueyu Zhang2, Jingshan Yu1
1Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, College of Water Sciences, Beijing Normal University, Beijing 100875, China.
The Science of the total environment
|January 5, 2024
概括
城市化和气候变化显著改变了降雨模式,增加了城市洪水风险. 北京的分析显示,集中降雨和特定的周期性循环,突出了道路密度和地形等关键因素,导致水淹没.
科学领域:
- 环境科学 环境科学
- 水文学的水文学
- 城市规划 城市规划
背景情况:
- 城市洪水灾害因城市化和气候变化导致的降水模式变化而加剧.
- 了解这些动态降水变化对于有效的城市洪水风险管理至关重要.
研究的目的:
- 分析北京降雨的空间和时间分布.
- 为了确定城市水淹的周期性变化和驱动因素.
主要方法:
- 一个数据驱动的模型融合框架,使用多源降水数据.
- 波形分析用于周期变化和机器学习用于时空模式.
- 地理探测器和网络爬虫技术用于因素分析和数据采集.
主要成果:
- 78%的降雨发生在洪水季节,每年累积降雨周期为21,13和9年.
- 虽然大多数地区的降水趋势正在下降,但63.4%的降水度在增加,增加了水淹没的风险.
- 道路网络密度,地形和降雨强度被确定为城市水淹的主要驱动因素.
结论:
- 北京的降雨动态复杂,季节性度和周期性显著.
- 城市淹水是由气象和景观因素的结合驱动的.
- 调查结果为城市地区的洪水控制和应急管理策略提供了关键信息.
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