Results 71 to 80 of about 2,287 (214)

An Efficient Quasi‐Monte Carlo Method for Concurrent Estimation of First‐Order and Total‐Effect Process Sensitivity Indices

open access: yesWater Resources Research, Volume 61, Issue 12, December 2025.
Abstract Developing and improving process‐based models requires identifying the importance and/or influence of various processes driving system behavior. In our recent studies, important processes are identified using first‐order process sensitivity index PSK (Dai et al., 2017, https://doi.org/10.1002/2016wr019715), and non‐influential processes are ...
Jing Yang   +4 more
wiley   +1 more source

Relieve the Demand for Labeled Data of Deep Learning Models for Hydraulic Conductivity Field Tasks in Groundwater Through Self‐Supervised Learning

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 4, December 2025.
Abstract Deep learning (DL) has shown great potential in solving groundwater problems but often requires large labeled data sets, which are expensive and time‐consuming to obtain. In this study, we introduce a self‐supervised learning approach based on a masked autoencoder (MAE)—an encoder‐decoder architecture that reconstructs randomly masked input ...
Kai Ji   +4 more
wiley   +1 more source

Modeling the Effect of Rainfall Recharge on Denitrification in Intertidal Mixing Zones of Coastal Aquifers

open access: yesWater Resources Research, Volume 61, Issue 12, December 2025.
Abstract Tidally driven saltwater‐freshwater mixing in coastal aquifers can promote denitrification, a key process facilitating attenuation of terrestrially derived nitrate prior to groundwater discharge into coastal waters. However, to date the effect of rainfall recharge, which can greatly alter flow and mixing in intertidal zones, on this mixing ...
Huiqiang Wu   +3 more
wiley   +1 more source

Optimal Water Resources Management and Operation Based on Social Choice Procedures [PDF]

open access: yesمهندسی منابع آب, 2015
Optimal management and operation of groundwater resources need to attract a great attention according to their special characteristics. Groundwater resources exploitation operation involves important issues such as conflicting and complex objectives, a ...
محمدرضا علیزاده   +3 more
doaj  

An Adaptive SPH Method (ADP‐SPH) for Simulating Solute Transport in Heterogeneous Aquifers

open access: yesWater Resources Research, Volume 61, Issue 12, December 2025.
Abstract Smoothed Particle Hydrodynamics (SPH) is a meshfree, Lagrangian‐based approach used to solve the advection‐dispersion equation (ADE) of groundwater solute transport. It is well known that the accuracy of SPH deteriorates significantly when particles become irregularly distributed, often occurring in heterogeneous aquifers.
Tian Jiao   +4 more
wiley   +1 more source

Groundwater Modeling by MODFLOW Model in Toyserkan Aquifer and Evaluation of Hydrogeological State under Present and Future Conditions [PDF]

open access: yesمهندسی منابع آب, 2017
Groundwater resources are one of the most valuable natural resources. Therefore, in the recent years, the groundwater modeling is a powerful tool in management procedures, optimization and predicting of groundwater resources in future.
Abdullah Taheri Tizro, Morteza Kamali
doaj  

A Fully Coupled Numerical Model for Radial Collector Well Intake Simulation Incorporating Comprehensive Head Loss Mechanisms

open access: yesWater Resources Research, Volume 61, Issue 12, December 2025.
Abstract This study presents a physically based numerical framework for accurately simulating the intake performance of radial collector wells (RCWs) by explicitly accounting for internal flow dynamics and all major head loss mechanisms. Unlike conventional models that often simplify RCW hydraulics, the proposed approach integrates aquifer, filter ...
Seonmin Lee, Min‐Ho Koo
wiley   +1 more source

MODFLOW as a Configurable Multi‐Model Hydrologic Simulator [PDF]

open access: bronze, 2023
Christian D. Langevin   +4 more
openalex   +1 more source

Generative Subsurface Flow Modeling With Pretrained Diffusion Model and Training‐Free Knowledge Alignment

open access: yesGeophysical Research Letters, Volume 52, Issue 22, 28 November 2025.
Abstract We introduce a versatile generative learning framework that integrates probabilistic diffusion models, observational data, and domain knowledge for stochastic modeling of flow in porous media. The framework begins by pretraining an unconditional diffusion model to approximate the joint distribution of subsurface parameters and state variables,
Zhongzheng Wang   +4 more
wiley   +1 more source

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