基于GLUE的土壤溶质运移参数反演及不确定性  

Parameter Estimation and Uncertainty Evaluation of a Soil Solute Transport Model Using GLUE

作　　者：闫一凡[1,2] 李晓鹏 张佳宝[1] 刘建立[1] YAN Yifan;LI Xiaopeng;ZHANG Jiabao;LIU Jianli(Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院南京土壤研究所,南京210008 [2]中国科学院大学,北京100049

出　　处：《土壤学报》2018年第5期1108-1119,共12页Acta Pedologica Sinica

基　　金：国家自然科学基金项目(41771265);国家重点研发计划课题(2016YFD0300601;2016YFD0200603);南京土壤研究所"一三五"(领域前沿)项目(ISSASIP1661)资助~~

摘　　要：溶质运移模型参数的识别结果常存在较高的不确定性,制约了模型的实际应用。以土壤中Cu2+运移过程为例,采用广义似然不确定性估计(Generalized likelihood uncertainty estimation,GLUE)并引入最大似然值(MaximumNash-Sutcliffe,MNS)等三种定量指标,探讨了数值反演估计弥散系数等参数的不确定性。结果表明,非线性最小二乘法(Nonlinear least squares,NLLS)得到的唯一"最优"参数组合对Cu2+出流曲线拟合效果很好(R2>0.937),但因"异参同效",无法刻画预测结果的不确定性。GLUE则可明确溶质运移参数及其响应界面的不确定性,MNS对应的参数组合对Cu2+出流曲线拟合R2>0.937,效果与NLLS的拟合结果高度一致。GLUE计算的95%置信区间覆盖了80%以上的观测点(NLLS为46.3%),其反演参数的取值范围也远大于NLLS的结果。在模型参数及响应界面不确定性分析两方面GLUE方法均优于NLLS方法。【Objective】Computer programs, such as CXTFIT, are commonly used to calibrate soil hydraulic and transport parameters, such as dispersion coefficient and retardation factor. CXTFIT can be used to fit observations quite well, which leave researchers in this aspect such an impression that the ＂optimum＂ parameter sets simulated with this program can be used directly for modeling prediction. However, in the process of parameter simulation, inherent uncertainties do exist and are often underestimated. The objectives of this study were to assess and even quantify the uncertainties that may occur in parameter estimation using the convection-dispersion equation（CDE） and in adoption of the parameters in modeling prediction with the non-linear least squares（NLLS） and generalized likelihood uncertainty estimation（GLUE） methods. 【Method】 In this study, with the aid of CXTFIT, NLLS and GLUE coupled with the Latin hypercube sampling strategy was used to fit concentrations of bromide and copper nitrate in transport through three oil columns different in texture（i.e. Sandy loam, loamy sand and sandy clay loam）, separately. And the parameters were optimized and analyzed to quantify the uncertainties that may occur in these processes by means of three quantitative metrics, that is, MNS（maximum coefficient determination coefficient）, P95 CI（the percentage of observations included within the 95% confidence intervals） and ARIL（average relative interval length）.【Result】Results show that the only ＂optimum＂ parameter set obtained with the NLLS technique fits the curve of solute outflow quite well with determination coefficients（R^2） all 〉0.98 for fitting Br-transport and 0.937 for fitting Cu^2＋transport, and with root mean square error lingering at the magnitude of 10-2, but it fails to cope with a large number of equivalent parameters. R^2 being high in value only indicates the ＂optimum＂ parameter set is a proper fit of observation, but it does not mean the ＂optimum＂ parame

关 键 词：溶质运移模型 参数反演 广义似然不确定性估计(GLUE)方法 不确定性分析 

分 类 号：S152[农业科学—土壤学]