Groundwater sustainability: A review of the interactions between science and policy
Concerns over groundwater depletion and ecosystem degradation have led to the
incorporation of the concept of groundwater sustainability as a groundwater policy …
incorporation of the concept of groundwater sustainability as a groundwater policy …
Review of machine learning-based surrogate models of groundwater contaminant modeling
J Luo, X Ma, Y Ji, X Li, Z Song, W Lu - Environmental Research, 2023 - Elsevier
Heavy computational load inhibits the application of groundwater contaminant numerical
model to groundwater pollution source identification, remediation design, and uncertainty …
model to groundwater pollution source identification, remediation design, and uncertainty …
Deep convolutional encoder‐decoder networks for uncertainty quantification of dynamic multiphase flow in heterogeneous media
Surrogate strategies are used widely for uncertainty quantification of groundwater models in
order to improve computational efficiency. However, their application to dynamic multiphase …
order to improve computational efficiency. However, their application to dynamic multiphase …
Deep autoregressive neural networks for high‐dimensional inverse problems in groundwater contaminant source identification
Identification of a groundwater contaminant source simultaneously with the hydraulic
conductivity in highly heterogeneous media often results in a high‐dimensional inverse …
conductivity in highly heterogeneous media often results in a high‐dimensional inverse …
Stochastic finite element methods for partial differential equations with random input data
The quantification of probabilistic uncertainties in the outputs of physical, biological, and
social systems governed by partial differential equations with random inputs require, in …
social systems governed by partial differential equations with random inputs require, in …
Risk assessment of the Ship steering gear failures using fuzzy-Bayesian networks
Accidents caused by steering gear malfunctions, especially during port berthing maneuvers,
the strait, and canal crossings, can lead to hazardous consequences on the environment …
the strait, and canal crossings, can lead to hazardous consequences on the environment …
On uncertainty quantification in hydrogeology and hydrogeophysics
Recent advances in sensor technologies, field methodologies, numerical modeling, and
inversion approaches have contributed to unprecedented imaging of hydrogeological …
inversion approaches have contributed to unprecedented imaging of hydrogeological …
An adaptive Gaussian process‐based method for efficient Bayesian experimental design in groundwater contaminant source identification problems
Surrogate models are commonly used in Bayesian approaches such as Markov Chain
Monte Carlo (MCMC) to avoid repetitive CPU‐demanding model evaluations. However, the …
Monte Carlo (MCMC) to avoid repetitive CPU‐demanding model evaluations. However, the …
An improved tandem neural network architecture for inverse modeling of multicomponent reactive transport in porous media
Parameter estimation for reactive transport models (RTMs) is important in improving their
predictive capacity for accurately simulating subsurface hydrogeochemical processes. This …
predictive capacity for accurately simulating subsurface hydrogeochemical processes. This …
Efficient B ayesian experimental design for contaminant source identification
In this study, an efficient full Bayesian approach is developed for the optimal sampling well
location design and source parameters identification of groundwater contaminants. An …
location design and source parameters identification of groundwater contaminants. An …