Process-based modelling offers interpretability and physical consistency in many domains of
geosciences but struggles to leverage large datasets efficiently. Machine-learning methods …

Fast and accurate identification of unknown pollution sources is a crucial and challenging
task in water resources management, in which the characteristics of unknown pollution …

The reliable assessment of hazards or risks arising from groundwater contamination
problems and the design of efficient and effective techniques to mitigate these problems …

Groundwater Age is the first book of its kind that incorporates and synthesizes the state-of-
the-art knowledge about the business of groundwater dating-including historical …

In identifying groundwater contaminant sources, given that the simulation model is
computationally inefficient, an ensemble surrogate model is proposed to improve the …

As the incidence of groundwater contamination continues to grow, a number of inverse
modeling methods have been developed to address forensic groundwater problems. In this …

The concept of vulnerability of drinking water sources is reviewed, and a quantitative
approach for assessing well vulnerability for complex three‐dimensional ground water …

Recent advances in differentiable modeling, a genre of physics-informed machine learning
that trains neural networks (NNs) together with process-based equations, have shown …

Pollution risk from the discharge of industrial waste or accidental spills during transportation
poses a considerable threat to the security of rivers. The ability to quickly identify the …

Reduction in indoor environment quality calls for effective control and improvement
measures. Accurate and prompt identification of contaminant sources ensures that they can …