Comparison of Local, Regional, and Scaling Models for Rainfall Intensity–Duration–Frequency Analysis
Comparison of Local, Regional, and Scaling Models for Rainfall Intensity–Duration–Frequency Analysis
复制标题
降雨强度、持续时间和频率分析的地方、区域和尺度模型比较
DOI：
10.1175/jamc-d-20-0094.1
复制
发表时间：
2020
影响因子：
3
通讯作者：
Mascaro, Giuseppe
中科院分区：
文献类型：
--
作者：
Mascaro, Giuseppe
对极端降雨的强度-持续时间-频率(IDF)分析为缓解、管理和适应城市洪水提供了关键信息。IDF分析的准确性和不确定性取决于历史降雨量记录的可获得性，这些记录在每天的分辨率下更容易获得，而且在发展中国家往往非常稀少。在这项工作中，我们量化了不同IDF模型的性能作为可用的高分辨率(Nτ)和日(N24小时)雨量计数量的函数。为此，我们应用了一个基于蒙特卡罗自举实验的交叉验证框架，该框架基于亚利桑那州中部223个高分辨率量规的记录。我们检验了5个IDF模型，这些模型基于(2)局部、(1)区域和(2)尺度频率分析的年降雨量极大值从30分钟到24小时的广义极值(GeV)分布。所有模型在模拟与长达30年的重现期相关的观测分位数方面都表现出类似的性能。当Nτ>；10时，本地和区域模型的精度最好；建议对记录长度的GeV形状参数进行偏差修正，以估计较大重现期的分位数。通过蒙特卡罗实验评估，当Nτ≤为5时，所有模型的不确定度都很大；然而，如果N24小时≥10个额外的日尺度，应用简单的尺度模型，从日尺度信息推断次日降雨量的估计，大大降低了不确定性，提高了精度。对于所有型号，性能取决于捕获其参数上的标高控制的能力。虽然我们的工作是特定地点的，但其结果为未来进行IDF分析提供了见解，特别是在数据稀少的地区。
Intensity–duration–frequency (IDF) analyses of rainfall extremes provide critical information to mitigate, manage, and adapt to urban flooding. The accuracy and uncertainty of IDF analyses depend on the availability of historical rainfall records, which are more accessible at daily resolution and, quite often, are very sparse in developing countries. In this work, we quantify performances of different IDF models as a function of the number of available high-resolution (Nτ) and daily (N24h) rain gauges. For this aim, we apply a cross-validation framework that is based on Monte Carlo bootstrapping experiments on records of 223 high-resolution gauges in central Arizona. We test five IDF models based on (two) local, (one) regional, and (two) scaling frequency analyses of annual rainfall maxima from 30-min to 24-h durations with the generalized extreme value (GEV) distribution. All models exhibit similar performances in simulating observed quantiles associated with return periods up to 30 years. WhenNτ> 10, local and regional models have the best accuracy; bias correcting the GEV shape parameter for record length is recommended to estimate quantiles for large return periods. The uncertainty of all models, evaluated via Monte Carlo experiments, is very large whenNτ≤ 5; however, ifN24h≥ 10 additional daily gauges are available, the uncertainty is greatly reduced and accuracy is increased by applying simple scaling models, which infer estimates on subdaily rainfall statistics from information at daily scale. For all models, performances depend on the ability to capture the elevation control on their parameters. Although our work is site specific, its results provide insights to conduct future IDF analyses, especially in regions with sparse data.