模拟极端降雨使用一般化极端价值分布和超值分析在墨西哥科利马,墨西哥
Raúl Renteria1, Raúl Aquino2, Mayrén Polanco3
1Facultad de Ingeniería Civil, Universidad de Colima, Coquimatlán 28400, Mexico.
Sensors (Basel, Switzerland)
|January 28, 2026
概括
墨西哥科利马的极端降雨情况使用统计建模和空间可视化进行分析. 北部和西部地区的强降雨事件频率最高,有助于评估洪水风险.
科学领域:
- 环境科学 环境科学
- 水文学 水文学
- 数据科学数据科学数据科学
背景情况:
- 极端降雨事件给墨西哥科利马带来了重大风险,需要强大的分析框架.
- 准确评估降水模式对于有效的洪水风险管理和领土规划至关重要.
研究的目的:
- 开发一个统计和技术框架来分析墨西哥科利马的极端降雨情况.
- 为了识别高强度降雨事件,并为洪水风险评估建模其复发情况.
主要方法:
- 利用来自CONAGUA气象站的历史降水数据.
- 应用通用极值 (GEV) 分布用于降雨复发和回归周期的概率模型.
- 在Python (3.13版本) 和QGIS (3.38版本) 中使用空间插值来创建超值图.
主要成果:
- 确定了科利马极端降雨事件的关键回归期.
- 空间可视化显示了整个州降雨强度的地理差异.
- 科利马北部和西部地区出现极端降雨事件的频率最高.
结论:
- 开发的框架有效地支持科利马的洪水风险评估和领土规划.
- 超标地图突出了针对水灾减缓战略的关键区域.
- 实时传感器技术和卫星观测的整合可以增强未来的洪水监测和风险管理.
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