考虑山洪灾害影响的贝叶斯径流模拟方法

A Bayesian Runoff Simulation Method Considering the Influence of Flash Flood Disaster

摘要:

山洪灾害壅高河道水位带来的流量放大作用影响了贝叶斯径流模拟方法在山丘区流域的表现。针对这一问题，以汶川地震后山洪灾害频发的都江堰白沙河流域为研究区域，探究引发流域山洪灾害的临界雨量，引入线性放大系数修正山洪灾害对流量的放大作用，耦合一阶自回归残差模型与不同异方差转换函数构建了6种贝叶斯径流模拟方案，利用GR4J模型模拟不同方案下流域出口日径流过程。研究结果表明，临界雨量与线性放大系数能够有效识别、修正山洪灾害对径流的影响，与未考虑山洪灾害影响的贝叶斯径流模拟方案相比，白沙河流域径流模拟结果的准确性、可靠性、精确性指标分别平均提升19%、32%、62%。该方法可在山洪灾害频发流域推广应用，为山丘区流域径流预报提供更为准确的科学依据。

Abstract:

The amplification of discharge caused by flash flood disasters has affected the performance of Bayesian runoff simulation in hilly watersheds. This paper， taking the Baisha River Basin in Dujiangyan with frequent flash flood disasters after the Wenchuan earthquake as the research area， explores the critical rainfall causing flash flood disaster in the basin， introduces the linear amplification factor to correct the amplification effect of flash flood disaster on flood flow， and constructs six Bayesian flood simulation schemes by coupling the first-order autoregressive residual error model with different heteroscedastic transformation functions. The outlet daily runoff process of the basin is then simulated using the GR4J model. The results show that the critical rainfall and linear amplification factor can effectively identify and correct the impact of flash flood disasters on discharge. After considering the influence of flash flood disasters， the accuracy， reliability， and precision metrics of the daily runoff simulation results in the Baisha River Basin are increased by 19%， 32%， and 62%， respectively. This method can be widely used in the basin with frequent flash flood disasters and provide a more accurate scientific basis for runoff forecasting in hilly watersheds.