基于贝叶斯方法的流量数据的不确定性分析

用贝叶斯方法估计水位流量幂律关系式中参数,并计算东江流域平均低流量、中流量和高流量的不确定性,并分析影响流量不确定性的因素。结果表明:①东江流域流量不确定性总体水平在中等偏上水平,其中高流量不确定性最大,中、低流量次之;②人类活动比如兴建水库、河道整治、围堰筑坝以及大规模的河道采沙对流量不确定性的大小及趋势有着显著的影响;大量级的洪水对河道水力特性以及几何形状的影响比较复杂,变化没有明显统一的趋势。

Uncertainty Analysis of Flow Data Based on Bayesian Methods

In this paper, Bayesian methods are used to estimate parameters of the stage discharge power law model in the Dongjiang River, the average low flow, medium flow and high flow uncertainty are calculated and factors affecting the flow uncertainty are analyzed. The results show that: (1) The overall uncertainty of flow data is at a middle-high level, in which high flow uncertainty is maximum, followed by medium and low flow. (2) Human activities, such as construction of reservoirs, river regulation, cofferdams damming, and large-scale mining river sand, have a significant impact on the size and trends of flow uncertainty; the impact of large river floods on hydraulic characteristics and geometric shape is complex, without obvious change in uniform trend.