确定河渠纵向离散系数的分位数回归法  

Quantile regression method to determine longitudinal dispersion coefficient of river channel

作　　者：杨双[1] 杨海东[1] 王卓民[1] 肖宜[1] 邵东国[1] 

机构地区：[1]武汉大学水资源与水电工程科学国家重点实验室,武汉430072

出　　处：《南水北调与水利科技》2014年第5期63-66,76,共5页South-to-North Water Transfers and Water Science & Technology

基　　金：国家水体污染控制与治理科技重大专项(2012ZX07205005);"十二五"国家科技支撑计划项目(2012BAD08B05-3)

摘　　要：采用分位数回归的纵向离散系数研究方法和双站点浓度时间数据,对突发水污染事故中河渠的水质进行预测,并对比分析了分位数回归与最小二乘法回归效果。实例研究结果显示,运用分位数回归法确定河渠纵向离散系数效果好,第一站点的回归参数通过了97.5%置信水平下的假设检验,第二站点的预测值与实际值相关系数最高达到了0.928。同时,分位数回归法在解决偏态分布问题时较最小二乘法有明显优势。The determination method of longitudinal dispersion coefficient based on the quantile regression and the concentration-time data of two sites were used to predict the water quality in the river channel. Moreover, the results determined by the quantile regression and least squares regression methods were compared. The example results showed that the quantile regression method is feasible and effective to determine the longitudinal dispersion coefficient of river channel. The quantile regression parameters passed the hypothesis test in the 97.5% confidence level at the first site, and the highest correlation coefficient of the predicted and actual values at the second site reached up to 0.928. In addition, quantile regression method has more advantage in solving the problems with skewed distribution than the least squares regression method.

关 键 词：突发水污染 纵向离散系数 偏态分布 示踪试验 分位数回归 R软件 

分 类 号：TV131.2[水利工程—水力学及河流动力学] X143[环境科学与工程—环境科学]