Coupled rainfall model and discharge model for flood frequency estimation
Coupled rainfall model and discharge model for flood frequency estimation
复制标题
用于洪水频率估计的耦合降雨模型和流量模型
DOI：
10.1029/2001wr000474
复制
发表时间：
2002
影响因子：
5.4
通讯作者：
J. Lavabre
中科院分区：
文献类型：
--
作者：
P. Arnaud;J. Lavabre
设计了一种将逐时降雨随机模型与降雨转化为流量的一般概念模型相结合的水文变量（降雨和流量）频率分布研究方法。该模型在给定的模拟周期内生成许多不同的洪水事件，以评估水文风险。模拟洪水概率估算（SHYPRE）方法是利用观测资料描述现象并进行统计再现的方法。水文变量的频率分布是根据模拟的降雨和洪水事件经验建立的。这些频率分布向稀有频率的外推是通过在很长的模拟周期内产生非常不同的事件来实现的，而不是通过直接拟合观测值的理论概率分布。这种方法产生了从常见频率到罕见频率的洪水分位数的原始估计，并提供了这些洪水的完整时间数据。此外，该方法提供的洪水分位数估计值比根据观测值拟合的统计分布更稳定，即使对于频繁事件也是如此。这是由于更好地整合了降雨数据和两个模型（降雨模型和降雨-流量模型）的参数化设计稳定性。
A method was designed to study frequency distributions of hydrologic variables (rainfall and discharge) which combined a stochastic model for hourly rainfall with a general conceptual model for transforming rainfall into discharge. The model generates many different flood events over a given simulation period to evaluate hydrologic risks. The Simulated Hydrographs for flood Probability Estimation (SHYPRE) method was based on the use of observations to describe phenomena and statistically reproduce them. Frequency distributions of hydrological variables are built empirically from simulated rainfall and flood events. Extrapolation of these frequency distributions toward rare frequencies is performed by generating very different events over a long simulation period rather than by directly fitting a theoretical probability distribution on observed values. This method yields an original estimation of flood quantiles from common to rare frequencies and provides complete temporal data about these floods. In addition, the approach supplies more stable estimates of flood quantiles than statistical distributions fitted on observed values, even for frequent events. This is due to a better integration of rainfall data and the parametric design stability of the two models (rainfall model and rainfall‐discharge model).