一种宽容的水文技术,用于从NWPM中实时选择最佳的QPF,用于洪水预警应用
Mahmoud Salah1, Ashraf El-Mostafa2, Mohamed A Gad2
1Irrigation and Hydraulics Department, Ain Shams University, Cairo, Egypt
概括
准确的定量降水预报 (QPF) 对于洪水预警至关重要. 这项研究介绍了一种新的自动化技术,它使用了...
科学领域:
- 水文和气象学
- 环境科学 环境科学
背景情况:
- 准确的定量降水预报 (QPF) 对于有效的洪水预警系统至关重要.
- 数字天气预测模型 (NWPMs) 提供QPF,但实时选择最佳模型是具有挑战性的.
- 对于洪水预警至关重要的降雨流失模拟,在很大程度上取决于QPF的准确性.
研究的目的:
- 开发一种自动化技术,用于在实时洪水预警系统中选择最适合QPF的NWPM.
- 为了应对从NWPM转移到QPF的时间转移的挑战.
- 提高洪水预警模拟的准确性和可靠性.
主要方法:
- 开发一种实时NWPM选择的自动化技术.
- 实施一种新的"耐受性"水文方法来比较QPF与测量的降雨量.
- 使用盆地规模的比较来解释预测的时间变化.
- 开发一个Python包来自动化该技术.
主要成果:
- 开发的技术成功地自动选择QPF用于洪水预警模拟.
- "宽容"的水文方法有效地消除了QPF时间变化的影响.
- 使用两个示例事件演示实时应用.
- 该技术证明能够选择合适的QPF,尽管预测时间变化.
结论:
- 采用"宽容"方法的自动化技术增强了用于洪水警告的QPF的选择.
- 这种方法通过减轻NWPMs中的时间错误来提高降雨-流水模拟的准确性.
- 开发的Python包为实时洪水预警应用程序和历史NWPM性能评估提供了一个实用的工具.
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