Densely Connected Squeeze‐and‐Excitation Convolutional Encoder‐Decoder Networks for Identifying Preferential Channels in Highly Heterogeneous Porous Media

Improving the computational efficiency of first arrival time uncertainty estimation using a connectivity-based ranking Monte Carlo method

(2021) Maria Morvillo et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

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

A near real-time deep learning approach for detecting rice phenology based on UAV images

(2020) Qi Yang et al.   AGRICULTURAL AND FOREST METEOROLOGY

Real-time detection of rice phenology through convolutional neural network using handheld camera images

(2020) Jingye Han et al.   PRECISION AGRICULTURE

A comprehensive review of deep learning applications in hydrology and water resources

(2020) Muhammed Sit et al.   WATER SCIENCE AND TECHNOLOGY

Deep autoregressive neural networks for high‐dimensional inverse problems in groundwater contaminant source identification

(2019) Shaoxing Mo et al.   WATER RESOURCES RESEARCH

Deep convolutional neural networks for rice grain yield estimation at the ripening stage using UAV-based remotely sensed images

(2019) Qi Yang et al.   FIELD CROPS RESEARCH

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

(2019) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Mechanisms, upscaling and prediction of anomalous dispersion in heterogeneous porous media

(2019) Alessandro Comolli et al.   WATER RESOURCES RESEARCH

Efficient identification of preferential flow path in heterogeneous media based on stream function

(2019) Tongchao Nan et al.   JOURNAL OF HYDROLOGY

Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification

(2018) Yinhao Zhu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

An Entrogram-Based Approach to Describe Spatial Heterogeneity With Applications to Solute Transport in Porous Media

(2018) Marco Bianchi et al.   WATER RESOURCES RESEARCH

A trans-disciplinary review of deep learning research and its relevance for water resources scientists

(2018) Chaopeng Shen   WATER RESOURCES RESEARCH

Minimum Hydraulic Resistance and Least Resistance Path in Heterogeneous Porous Media

(2017) Calogero B. Rizzo et al.   WATER RESOURCES RESEARCH

Effects of the hydraulic conductivity microstructure on macrodispersivity

(2016) Mariaines Di Dato et al.   WATER RESOURCES RESEARCH

Stochastic modeling of solute transport in aquifers: From heterogeneity characterization to risk analysis

(2015) A. Fiori et al.   WATER RESOURCES RESEARCH

Is unique scaling of aquifer macrodispersivity supported by field data?

(2015) A. Zech et al.   WATER RESOURCES RESEARCH

Solute transport in aquifers of arbitrary variability: A time-domain random walk formulation

(2014) Vladimir Cvetkovic et al.   WATER RESOURCES RESEARCH

The plume spreading in the MADE transport experiment: Could it be predicted by stochastic models?

(2013) A. Fiori et al.   WATER RESOURCES RESEARCH

On Preferential Flow, Channeling and Connectivity in Heterogeneous Porous Formations

(2011) A. Fiori et al.   Mathematical Geosciences

Spatial connectivity in a highly heterogeneous aquifer: From cores to preferential flow paths

(2011) Marco Bianchi et al.   WATER RESOURCES RESEARCH