气候变化领域集成服务门户(CCPortal): Seeing macro-dispersivity from hydraulic conductivity field with convolutional neural network

CCPortal

DOI	10.1016/j.advwatres.2020.103545
	Seeing macro-dispersivity from hydraulic conductivity field with convolutional neural network
	Zhou Z.; Shi L.; Zha Y.
发表日期	2020
ISSN	0309-1708
卷号	138
英文摘要	Building a quantitative relation between the spatial heterogeneity of the hydraulic conductivity fields and the macroscale behavior of solute transport is fundamental for groundwater environment problem. In this work, the deep learning technique is explored to build the functional mapping between the hydraulic conductivity field and the longitudinal macro-dispersivity. We examine the capability of the deep neural network in estimating macro-dispersivities of conductivity fields with different variances. The universality of the trained deep neural network is investigated. Comparisons of the neural network results and the reference values (macro-dispersivities from transport simulation) suggest the promising potential of deep learning technique in porous media with moderate heterogeneity. For a given size of training datasets, the deep neural network produces better macro-dispersivity estimation for the conductivity field with smaller variance. The trained neural network by conductivity fields with larger variance has stronger universality for macro-dispersivity estimation. This study demonstrates that deep neural network can be an effective alternative for estimating macroscale behavior of solute transport by directly interpreting hydraulic conductivity fields. © 2020 Elsevier Ltd
关键词	Convolution Deep learning Deep neural networks Groundwater Groundwater pollution Hydraulic conductivity Learning algorithms Learning systems Porous materials Solute transport Contaminant transport Convolutional neural work Groundwater environment Heterogeneity Macrodispersivity Quantitative relations Spatial heterogeneity Trained neural networks Convolutional neural networks algorithm artificial neural network computer simulation groundwater heterogeneity hydraulic conductivity machine learning
语种	英语
来源机构	Advances in Water Resources
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/131834
推荐引用方式 GB/T 7714	Zhou Z.,Shi L.,Zha Y.. Seeing macro-dispersivity from hydraulic conductivity field with convolutional neural network[J]. Advances in Water Resources,2020,138.
APA	Zhou Z.,Shi L.,&Zha Y..(2020).Seeing macro-dispersivity from hydraulic conductivity field with convolutional neural network.,138.
MLA	Zhou Z.,et al."Seeing macro-dispersivity from hydraulic conductivity field with convolutional neural network".138(2020).