水科学进展2016，Vol.27Issue(2)：231-239,9.DOI:10.14042/j.cnki.32.1309.2016.02.008
基于田间试验的土壤水分运动模型选择
Modified unsaturated water flow model selection method and application to field experiments
摘要
Abstract
Most popular unsaturated-saturated water flow models were developed based on solving different forms of Richards′equation. Because these models all have their unique applicability and computational accuracy, it is impor-tant to select the most reasonable and efficient model for specified problems. This research used a Bayesian Model Av-eraging ( BMA) method to select the optimal one from six types of unsaturated water flow models ( Picard-h model, Picard-θ model, Picard-mix model, Ross model, Kinematic wave model, and water balance model) , using real data from field infiltration experiments. The BMA method was first implemented to estimate the model accuracy. Then a modified version of BMA for model selection was proposed to consider the model accuracy and computational cost sim-ultaneously. The results demonstrated that Ross is the optimal model with the best model accuracy and computational efficiency. The modified BMA method will increase the probability of an efficient model and can provide a more com-prehensive and reasonable model selection.关键词
土壤水分运动模型/贝叶斯模型平均方法, 改进BMA方法/Ross模型Key words
unsaturated water flow model/BMA method/modified BMA method/Ross model分类
天文与地球科学引用本文复制引用
毛威,朱焱,史良胜,刘昭,戴恒,杨金忠..基于田间试验的土壤水分运动模型选择[J].水科学进展,2016,27(2):231-239,9.基金项目
国家自然科学基金资助项目（41272270） The study is financially supported by the National Natural Science Foundation of China （ No．41272270）． （）
