Comparison of Noniterative Algorithms Based on Different Forms of Richards' Equation

作     者：Zha, Yuanyuan Tso, Michael C-H. Shi, Liangsheng Yang, Jinzhong 

作者机构：Wuhan Univ State Key Lab Water Resources & Hydropower Engn S Wuhan 430072 Hubei Peoples R China Univ Arizona Dept Hydrol & Water Resources Tucson AZ 85719 USA 

出 版 物：《ENVIRONMENTAL MODELING & ASSESSMENT》 (环境模式与评估)

年 卷 期：2016年第21卷第3期

页      面：357-370页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 

基　　金：National Natural Science Foundation of China China Scholarship Council Directorate For Geosciences Division Of Earth Sciences Funding Source: National Science Foundation 

主　　题：Richards' equation Variably saturated flow Noniterative method Soil moisture 

摘      要：Through linearizing an implicit differencing scheme, several noniterative numerical solutions of Richards equation in different forms are derived here. Paniconi et al. (Water Resources Research, 27(6), 1147-1163, 1991) have developed a first-order accurate linearization of the head-based Richards equation (RE) and a second-order accurate linearization of the implicit-factored head-based RE. Considering other forms of RE, we propose a second-order accurate linearization of the moisture-based RE and a second-order accurate linearization of the mixed form RE combined with the primary variable switching technique. Extensive comparisons between the noniterative solutions are conducted through three numerical experiments. Their accuracies, efficiencies, and mass balance behaviors are analyzed. The results indicate that the first-order accurate scheme is not efficient compared to iterative models. The noniterative schemes of head-based RE suffer from the mass imbalance problem without iteration. The linearized moisture-based RE can obtain mass conservative, accurate results effectively, while it may confront numerical problems when the soil approaches saturation. Among these noniterative schemes, the linearized mixed form RE combined with the primary variable switching technique is superior in terms of accuracy, mass balance, and efficiency compared to traditional iterative methods.