水利学报2018，Vol.49Issue(4)：428-438,11.DOI:10.13243/j.cnki.slxb.2017099
基于Bayes理论的田间层状土壤水分运动参数识别及不确定性分析
Parameter identification and uncertainty analysis of soil water movement model in field layered soils based on Bayes Theory
摘要
Abstract
Soil water movement parameters are the core parameters of water and pollutant migration in unsaturated zone.However,water movement parameters obtained from the indoor steady-state test of the soil samples at the point scale can't accurately reflect the soil water movement characteristics at the field scale under the natural occurring boundary conditions.A Bayesian inference for inversion of soil water retention and hydraulic parameters,based approach DREAMZS (Differential Evolution Adaptive Metropolis algorithm),was combined with Hydrus_1d to implement model optimization and uncertainty analysis on the data of soil moisture content in field observation (2013 for calibration and 2014 for validation).In order to get the prior information of the parameters in the van Genuchten-Mualem (VGM) model of the soil hydraulic functions,the ROSETTA pedotransfer functions was used.The posterior distribution of the water characteristic parameters was obtained,and modelling performance using the best estimated parameter set and the 95％ prediction confidence interval of the model prediction were analyzed.The results show that the Bayes method based on DREAMZS sampling can be used to identify the soil water characteristic parameters and predict the soil water dynamics at the field scale.The parameter identification results show that the saturated conductivity Ks is the least sensitive,and saturated water content θs is the most sensitive and easily identified.The parameter θs estimated from the laboratory experiment can be used for the modeling at the field scale.With the increase of soil depth,the higher the PUCI (Percentage of observations bracketed by the Unit Confidence Interval) value,the higher the performance of the model (reliability and accuracy).The prediction uncertainty is mainly caused by model structural uncertainty,and this implies that the effort to improve model prediction credibility in future should focus on diagnosis of model structure.关键词
层状土壤/Bayes理论/不确定性分析/参数后验分布/自适应差分演化Key words
layered soil/Bayes Theory/uncertainty analysis/posterior distribution/DREAMZS分类
农业科技引用本文复制引用
林青,徐绍辉..基于Bayes理论的田间层状土壤水分运动参数识别及不确定性分析[J].水利学报,2018,49(4):428-438,11.基金项目
国家自然科学基金项目(41571214) （41571214）
国家重点研发计划课题(2016YFC0402807) （2016YFC0402807）
山东省自然科学基金项目(ZR2014DQ021) （ZR2014DQ021）
