Assessing an efficient hybrid of Monte Carlo technique (GSA-GLUE) in Uncertainty and Sensitivity Analysis of vanGenuchten Soil Moisture Characteristics Curve

Studying model uncertainty and identifying the parameter uncertainty in the modeling of water flow through the soil is useful to improve water and soil management. This research aimed to assess the uncertainty of the parameters of soil water retention curve (SWRC) models using an efficient hybrid of...

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Bibliographic Details
Published in:Computational geosciences 2021-02, Vol.25 (1), p.503-514
Main Authors: Etminan, Samaneh, Jalali, Vahidreza, Mahmoodabadi, Majid, siuki, Abbas Khashei, Bilondi, Mohsen Pourreza
Format: Article
Language:English
Subjects:
Earth and Environmental Science
Earth Sciences
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Mathematical Modeling and Industrial Mathematics
Mathematical models
Model accuracy
Moisture content
Original Paper
Parameter estimation
Parameter identification
Parameter sensitivity
Parameter uncertainty
Parameters
Resource allocation
Sensitivity analysis
Soil
Soil analysis
Soil management
Soil moisture
Soil Science & Conservation
Soil water
Statistical methods
Uncertainty
Uncertainty analysis
Water flow
Water resources
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Summary:Studying model uncertainty and identifying the parameter uncertainty in the modeling of water flow through the soil is useful to improve water and soil management. This research aimed to assess the uncertainty of the parameters of soil water retention curve (SWRC) models using an efficient hybrid of the Monte Carlo technique e.g. generalized likelihood uncertainty estimation (GLUE). GLUE estimates the parameters of vanGenuchten, vanGenuchten-Mualem, and vanGenuchten-Burdine models for four soil classes. Also, to evaluate the relative importance of the model parameters, generalized sensitivity analysis (GSA) was performed. The results of the uncertainty analysis showed that among the studied models, the vanGenuchten-Mualem model with the indices of S = 0.05, T = 0.4, d-factor  = 0.25 and, P CI  = 100 was considered as the most accurate model with the least uncertainty. Also, the results of GSA were demonstrated that alpha and n parameters were sensitive parameters in the models. Consequently, identifying the uncertainty of the SWRC model structure and its parameters, relevant models with higher accuracy can be used in the study of soil water processes, and better water resource allocation.
ISSN:1420-0597
1573-1499
DOI:10.1007/s10596-020-10019-w