Assessing an efficient hybrid of Monte Carlo technique (GSA-GLUE) in Uncertainty and Sensitivity Analysis of vanGenuchte
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ORIGINAL PAPER
Assessing an efficient hybrid of Monte Carlo technique (GSA-GLUE) in Uncertainty and Sensitivity Analysis of vanGenuchten Soil Moisture Characteristics Curve Samaneh Etminan 1 & Vahidreza Jalali 1,2
3
4
& Majid Mahmoodabadi & Abbas Khashei siuki & Mohsen Pourreza Bilondi
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Received: 23 July 2019 / Accepted: 9 November 2020 # Springer Nature Switzerland AG 2020
Abstract 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 tshe parameters 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, PCI = 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. Keywords Predictively uncertainty . GLUE method . vanGenuchten model . Generalized sensitivity analysis (GSA)
Highlights • The GLUE method is an appropriate method to evaluate parameters uncertainty of soil water retention curves. • S and T indices have more performance than confidence interval criteria to evaluate the models uncertainty. • the GSA method was able to determine the sensitivity of the model parameters in each studied soil texture class. • “n” parameter is the most sensitive parameter in three models. * Vahidreza Jalali [email protected] Samaneh Etminan [email protected] Majid Mahmoodabadi [email protected] Abbas Khashei siuki [email protected] Mohsen Pourreza Bilondi [email protected]
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Department of Soil Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
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Department of Rangeland and watershed management, Higher Education Complex of Shirvan, Birjand, Iran
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Department of Soil Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
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Associate Professor, Department of Water Engineering, Faculty of Agriculture, University of Birjand, Southern Khorasan, Iran
Comput Geosci
1 Introduction Soil moisture is a key state property of soil that has a determining role in calculation of irrigation water requirement and the plantwater consumption. In addition, many environmental and agricultural processes such as soil-water resource management, flo
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