干旱区生态环境知识资源中心(Arid): Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation

Arid

DOI	10.1007/s12665-023-11264-9
	Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation
	Khorshidi, Mohammad Sadegh; Izady, Azizallah; Al-Maktoumi, Ali; Chen, Mingjie; Nikoo, Mohammad Reza; Gandomi, Amir H.
通讯作者	Izady, A
来源期刊	ENVIRONMENTAL EARTH SCIENCES
ISSN	1866-6280
EISSN	1866-6299
出版年	2023
卷号	82 期号:23
英文摘要	This paper presents a novel approach to analyzing uncertainty in complex groundwater models based on the approximate Bayesian computation (ABC) framework and information-theoretic summary statistics. Two summary statistics using the concepts of mutual information and variation of information are formulated as distance function measures of the ABC. These signatures are utilized within an ABC rejection (ABC-REJ) algorithm to measure the similarity and dissimilarity of the generated samples to the true posterior distribution of the groundwater model parameters. This method was applied to groundwater model calibration and uncertainty analysis in an arid region of Oman with a complex hydrogeological setting and a hardrock-alluvial aquifer system. MODFLOW unstructured-grid was used for modelling groundwater dynamics. A three-dimensional stratigraphic model was developed based on borehole data, and five-layer grid cells were defined according to the material and elevations of the stratigraphic model. Results show that the model reproduces the observed data behaviour very well, including peaks and abrupt declines in the head, as well as the trend of fluctuations in the observation wells. A notable match between the observed and simulated heads indicates the accuracy of the ABC-REJ algorithm based on summary statistics for calibrating and analyzing groundwater models.
英文关键词	Diagnostic model calibration Uncertainty analysis Approximate Bayesian computation Information-theoretic summary statistics Rejection algorithm
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001101141300002
WOS关键词	UNCERTAINTY ; ERROR ; FLOW
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/396138
推荐引用方式 GB/T 7714	Khorshidi, Mohammad Sadegh,Izady, Azizallah,Al-Maktoumi, Ali,et al. Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation[J],2023,82(23).
APA	Khorshidi, Mohammad Sadegh,Izady, Azizallah,Al-Maktoumi, Ali,Chen, Mingjie,Nikoo, Mohammad Reza,&Gandomi, Amir H..(2023).Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation.ENVIRONMENTAL EARTH SCIENCES,82(23).
MLA	Khorshidi, Mohammad Sadegh,et al."Information-theoretic summary statistics for diagnostic calibration of the groundwater models using approximate Bayesian computation".ENVIRONMENTAL EARTH SCIENCES 82.23(2023).