Uncertainty plagues every effort to model subsurface processes and every decision made
on the basis of such models. Given this pervasive uncertainty, virtually all practical problems …

Sensors and sensor networks play an important role in decision-making related to water
quality, operational streamflow forecasting, flood early warning systems, and other areas. In …

This study reports on two strategies for accelerating posterior inference of a highly
parameterized and CPU‐demanding groundwater flow model. Our method builds on …

The stochastic models and deep‐learning models are the two most commonly used
methods for subsurface sedimentary structures identification. The results from the stochastic …

Ensemble Kalman filters (EnKFs) are a successful tool for estimating state variables in
atmospheric and oceanic sciences. Recent research has prepared the EnKF for parameter …

A fundamental problem in geophysical modeling is related to the identification and
approximation of causal structures among physical processes. However, resolving the …

The rational management of water resource systems requires an understanding of their
response to existing and planned schemes of exploitation, pollution prevention and/or …

Sustainable water quality management requires a profound understanding of water fluxes
(precipitation, run-off, recharge, etc.) and solute turnover such as retention, reaction …

This paper addresses the inverse problem in spatially variable fields such as hydraulic
conductivity in groundwater aquifers or rainfall intensity in hydrology. Common to all these …

Random walk particle tracking (RWPT) is a well established and efficient alternative to grid‐
based Eulerian approaches when simulating the advection‐dispersion transport problem in …