基于混合似然函数的融雪径流模拟不确定性分析  

Uncertainty Analysis Based on Mixed Likelihood Function in Snowmelt Runoff Model

作　　者：吴吉天 曾献奎[1] 吴吉春[1] WU Jitian;ZENG Xiankui;WU Jichun(School of Earth Sciences and Engineering,Nanjing University,Nanjing 210023,China)

机构地区：[1]南京大学地球科学与工程学院,南京210023

出　　处：《高校地质学报》2025年第2期123-130,共8页Geological Journal of China Universities

基　　金：江苏省省级地质勘查项目(苏财资环[2021]46号);国家自然科学基金面上项目(42477082)联合资助。

摘　　要：由于模型参数及观测数据等影响,水文模型通常存在显著不确定性,开展融雪径流模拟不确定性定量分析可控制模拟结果的不确定性,提高模型的预测性能,对于寒旱山区的水资源科学管理具有重要意义。文章以新疆南部的策勒河流域为研究区,基于马尔科夫链蒙特卡洛方法(MCMC)进行融雪径流模型的参数不确定性分析。针对MCMC中似然函数的零膨胀误差(zero flatted error)及残差结构等难题,采用二项分布和正态分布组合的混合似然函数来描述残差结构,并与传统高斯似然函数的结果进行对比分析。均方根误差、决定系数和预测区间覆盖率等评价指标显示,基于混合似然函数的不确定性分析结果具有更好的预测性能。因此,混合似然函数能够更合理的刻画融雪径流模拟残差的结构,显著提升水文模型的预测性能,有利于实施科学、精准的水资源管理和保护。Due to the influence of model parameters and observational data,hydrological models usually have significant uncertainties.Quantitative analysis of the uncertainty of snowmelt runoff simulation can control the uncertainty of the simulation results and improve the predictive performance of the model,which is of great significance for the scientific management of water resources in cold and arid mountainous regions.In this study,the parameter uncertainty analysis of snowmelt runoff model based on Markov chain Monte Carlo method(MCMC)is carried out in the Cele River basin in southern Xinjiang as the study area.Aiming at the difficulties such as zero flatted error of the likelihood function and the residual structure in MCMC,a mixed likelihood function with a combination of binomial and normal distributions is used to describe the residual structure,and the results are compared and analyzed with those of the traditional Gaussian likelihood function.Model evaluation indicators such as the Root Mean Square Error,coefficient of determination and prediction interval coverage show that the uncertainty analysis results based on the mixed likelihood function have better prediction performance.Therefore,the mixed likelihood function can more reasonably portray the structure of the simulated residuals of snowmelt runoff,significantly improve the prediction performance of hydrological models,and is conducive to the implementation of scientific and accurate water resource management and protection.

关 键 词：水文模拟不确定性 混合似然函数 融雪径流模型 MCMC 零膨胀误差 

分 类 号：P333[天文地球—水文科学]