Can Deep Learning Extract Useful Information about Energy Dissipation and Effective Hydraulic Conductivity from Gridded Conductivity Fields?

Integration of Adversarial Autoencoders With Residual Dense Convolutional Networks for Estimation of Non‐Gaussian Hydraulic Conductivities

(2020) Shaoxing Mo et al.   WATER RESOURCES RESEARCH

Seeing macro-dispersivity from hydraulic conductivity field with convolutional neural network

(2020) Zhengkun Zhou et al.   ADVANCES IN WATER RESOURCES

Deep learning of subsurface flow via theory-guided neural network

(2020) Nanzhe Wang et al.   JOURNAL OF HYDROLOGY

Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

(2020) A. M. Tartakovsky et al.   WATER RESOURCES RESEARCH

On the multiscale characterization of effective hydraulic conductivity in random heterogeneous media: A historical survey and some new perspectives

(2020) Iván Colecchio et al.   ADVANCES IN WATER RESOURCES

Parameter estimation of soil hydraulic characteristics by inverse modeling of the analytical equation for unsaturated subsurface water flow

(2020) Luiz Fernando Coutinho de Oliveira et al.   JOURNAL OF HYDROINFORMATICS

Visualizing the effects of predictor variables in black box supervised learning models

(2020) Daniel W. Apley et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

Global Intercomparison of Atmospheric Rivers Precipitation in Remote Sensing and Reanalysis Products

(2020) Alireza Arabzadeh et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

Comparative Assessment of Snowfall Retrieval from Microwave Humidity Sounders using Machine Learning Methods

(2020) Abishek Adhikari et al.   Earth and Space Science

Coupled SWAT-MODFLOW model for large-scale mixed agro-urban river basins

(2019) Fatemeh Aliyari et al.   ENVIRONMENTAL MODELLING & SOFTWARE

Towards a robust parameterization for conditioning facies models using deep variational autoencoders and ensemble smoother

(2019) Smith W.A. Canchumuni et al.   COMPUTERS & GEOSCIENCES

In-situ estimation of unsaturated hydraulic conductivity in freezing soil using improved field data and inverse numerical modeling

(2019) Qiang Cheng et al.   AGRICULTURAL AND FOREST METEOROLOGY

Groundwater Estimation from Major Physical Hydrology Components Using Artificial Neural Networks and Deep Learning

(2019) Hassan Afzaal et al.   Water

Seeing permeability from images: fast prediction with convolutional neural networks

(2018) Jinlong Wu et al.   Science Bulletin

Flow, Transport, and Reaction in Porous Media: Percolation Scaling, Critical-Path Analysis, and Effective Medium Approximation

(2017) Allen G. Hunt et al.   REVIEWS OF GEOPHYSICS

The application of inverse modeling in characterizing hydraulic conductivity beneath the city of Berlin, Germany

(2016) Alireza Hassanzadegan et al.   Environmental Earth Sciences

Estimation of effective hydraulic parameters in heterogeneous soils at field scale

(2016) Jianbin Lai et al.   GEODERMA

Estimation of the Effective Permeability of Heterogeneous Porous Media by Using Percolation Concepts

(2016) M. Masihi et al.   TRANSPORT IN POROUS MEDIA

Use of NMR logging to obtain estimates of hydraulic conductivity in the High Plains aquifer, Nebraska, USA

(2013) Katherine Dlubac et al.   WATER RESOURCES RESEARCH

Imaging of groundwater with nuclear magnetic resonance

(2008) Marian Hertrich   PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY

Inverse Modeling of Subsurface Flow and Transport Properties: A Review with New Developments

(2008) Jasper A. Vrugt et al.   VADOSE ZONE JOURNAL