›› 2016, Vol. 28 ›› Issue (12): 2082-2089.DOI: 10.3969/j.issn.1004-1524.2016.12.18

• Environmental Science • Previous Articles     Next Articles

Parametric optimization of unsaturated soil hydraulic movement model

RAO Yuan1,2, XU Wen-jun1, JIANG Zhao-hui1, LAZAROVITCH Naftali2, LI Shao-wen1,*   

  1. 1. College of Information and Computer Science, Anhui Agricultural University, Hefei 230036, China;
    2. The Wyler Department of Dryland Agriculture, Ben-Gurion University of the Negev, Sede Boqer 84990, Israel
  • Received:2016-06-02 Online:2016-12-15 Published:2017-01-05

Abstract: In order to explore the suitability of parametric optimization methods, the influence of 2 typical parametric optimization methods, namely Minimizing the Objective Function (MOF), and Markov Chain Monte Carlo with DiffeRential Evolution Adaptive Metropolis algorithm (MCMC-DREAM), on numerical inversion performance was evaluated to offer suggestions for further exploring more efficient parametric optimization methods. Numerical case study showed that MOF had lower computation complexity, however, higher sensitivity to the initial solution. Therefore, MOF was suitable for conducting parametric optimization in the case of enough prior information. In contrast, MCMC-DREAM was insensitive to the initial solution, but took longer time to complete computation. As a result, MCMC-DREAM was suitable for conducting parametric optimization in the case of limited prior information. Both optimization methods suffered equifinality. However, both methods' ability to solve the practical problems could be improved by overcoming the equifinality drawback with adequate prior information and sensitivity analysis.

Key words: unsaturated soil, hydraulic movement model, numerical inversion, parametric optimization

CLC Number: