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用概率密度函数和随机天气发生器对洪水分析进行比较.
Israel García-Ledesma1, Jaime Madrigal1, Jesús Pardo-Loaiza1
1Faculty of Civil Engineering, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán, Mexico.
PeerJ
|May 9, 2025
概括
墨西哥莫雷利亚的洪水预测通过比较理论分布函数和随机天气发生器来改进. 先进的建模和高分辨率数据显示,不受管制的城市增长显著加剧了洪水影响,需要进行战略干预.
科学领域:
- 水文和水资源管理 水文和水资源管理
- 适应气候变化 适应气候变化
- 城市规划和自然灾害管理
背景情况:
- 由于气候变化,极端水文事件的频率和严重程度越来越高,需要改进洪水预测.
- 有效的洪水风险管理对于城市地区至关重要,特别是在墨西哥莫雷利亚等地区.
- 准确的洪水淹没地图对于城市规划和减轻灾害影响至关重要.
研究的目的:
- 为了比较两个不同的方法来预测墨西哥莫雷利亚的洪水事件:理论分布函数和随机天气发生器.
- 将排水预测集成到液压模型中,用于模拟洪水淹没区域.
- 评估城市增长对洪水风险的影响,并为决策提供工具.
主要方法:
- 采用土壤保护服务曲线数 (SCS-CN) 方法和多变量随机模型 (MASVC) 来进行排水估计.
- 使用HEC-RAS进行水力动力学建模,使用二维浅水方程模拟洪水淹没.
- 整合了高分辨率的数字海拔模型 (DEM) 和土地利用数据,以提高液压模拟的准确性.
主要成果:
- 理论分布函数和随机天气发生器都类似地复制了系统行为,但由于流量变化,产生了不同的水位.
- 与理论分布函数相比,随机模型倾向于产生更高的最大水位.
- 高分辨率的DEM (5米城市,0.5米排水) 和土地使用数据显著提高了液压模拟的准确性.
结论:
- 洪水易发生地区的不受管制的城市增长大大放大了洪水的影响,强调了战略城市规划的必要性.
- 生成的洪水危险地图和模拟为洪水风险管理决策提供了宝贵的工具.
- 整合先进的建模技术对于提高水文学洪水预测的精度和可靠性至关重要.
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