基于Copula函数的章水流域水沙丰枯遭遇频率研究

Frequency of water and sand abundance and desiccation encounters in Zhangshui Basin based on Copula functions

为探究章水流域内径流与输沙的相关性程度,以坝上水文站1956—2020年的月径流量及月输沙量数据为基础,采用Pettitt检验法、二维Copula函数法等,计算流域内多年径流、输沙量的变化趋势及丰枯遭遇特征。结果表明:章水流域年径流量变化平缓;年输沙量呈显著下降趋势(α<0.01),并在1994年产生显著突变(P<0.001);Lognormal分布为径流总序列的边缘分布函数;P-Ⅲ分布为输沙总序列及丰水期、枯水期、变异前、变异后序列的径流、输沙量分布函数;Clayton Copula函数为变异前后序列最优联合分布函数;Gumbel Copula函数为总序列、丰水期、枯水期序列最优联合分布函数;水沙变异前后呈现出的丰枯遭遇状态不同,遭遇频率相差较大。人类活动是章水流域水沙丰枯遭遇变化的主导因素。

To investigate the degree of correlation between runoff and sand transport in Zhangshui Basin,the monthly runoff and monthly sand transport data from 1956 to 2020 at the Bashang Hydrological Station were used as the basis for calculating the trends of runoff and sand transport and the characteristics of abundance and desiccation encounters for many years in the basin by using Pettitt's test method and two-dimensional Copula function.The results show that:(1)the annual runoff in ZhangshuiBasin changed gently without significant trend and sudden change;the annual sand transport showed a significant decreasing trend(α<0.01),and produced a significant sudden change in 1994(P<0.001);(2)the Lognormal distribution was the marginal distribution function of the total runoff sequence;the P-III distribution was the distribution function for the total sequence of sand transport as well as the abundance and desiccation of water,the runoff in dry water,and the sequence of pre-variation and post-variation,sand transport distribution function;Clayton Copula function is the optimal joint distribution function of the sequence before and after the variation;Gumbel Copula function is the optimal joint distribution function of the total sequence,the abundance and the desiccation period sequence;(3)The abundance and desiccation encounter state presented before and after the water-sand variation is different,and the encounter frequency differs greatly.Human activities are the dominant factors of water-sand abundance and desiccation encounter variation in Zhangshui Basin.