17 citations as recorded by crossref.

1. Groundwater modelling for decision-support in practice: Insights from Sweden N. Höglund et al. https://doi.org/10.1007/s13280-024-02068-7
2. Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system I. Qurban et al. https://doi.org/10.1016/j.scitotenv.2025.179861
3. Modeling a geologically complex volcanic watershed for integrated water resources management in Mt. Fuji, Japan S. Musy et al. https://doi.org/10.1038/s41597-025-06380-z
4. Influence of aquifer properties on optimal location and duration of groundwater level monitoring to predict aquifer recovery after mine closure L. Suescun et al. https://doi.org/10.1016/j.jhydrol.2025.133686
5. ArchPy and MODFLOW: Toward a General Integration of Heterogeneity into Groundwater Models L. Schorpp et al. https://doi.org/10.1111/gwat.70028
6. HGS-PDAF (version 1.0): a modular data assimilation framework for an integrated surface and subsurface hydrological model Q. Tang et al. https://doi.org/10.5194/gmd-17-3559-2024
7. Exploring the use of new data assimilation technologies to map groundwater quality vulnerability in a large alluvial aquifer W. Kitlasten et al. https://doi.org/10.3389/feart.2025.1609778
8. Explicit simulation of microbial transport with a dual-permeability, two-site kinetic deposition formulation using the integrated surface–subsurface hydrological model HydroGeoSphere F. Currle et al. https://doi.org/10.5194/hess-29-5383-2025
9. Data Space Inversion for efficient and uncertainty-informed contaminant source identification in aquifers G. Formentin et al. https://doi.org/10.1016/j.watres.2026.126176
10. Quantifying urban groundwater complexity: A high parameterization modelling approach K. Hayley & E. White https://doi.org/10.1016/j.jhydrol.2024.131416
11. Runoff spatiotemporal variability driven by climate change and human activity for the Nianchu River Basin in Southwestern Tibet Z. Yuan et al. https://doi.org/10.1016/j.ejrh.2025.102301
12. A Null Space Sensitivity Analysis for Hydrological Data Assimilation with Ensemble Methods N. Martin et al. https://doi.org/10.3390/hydrology12050106
13. Advancing Machine Learning-Based Streamflow Prediction Through Event Greedy Selection, Asymmetric Loss Function, and Rainfall Forecasting Uncertainty S. Tofighi et al. https://doi.org/10.3390/app152111656
14. Evaluating a data space inversion surrogate model for predictive uncertainty quantification in a coupled SWAT + gwflow model E. Qasemipour et al. https://doi.org/10.1016/j.jhydrol.2026.135028
15. DarcyWarp: A graphics processing unit (GPU)-accelerated multigrid solver for repeated 2D fixed-transmissivity groundwater solves validated against reference solvers P. Durney & J. Fourie https://doi.org/10.1016/j.envsoft.2026.107081
16. Translating pumping test data into groundwater model parameters: a workflow to reveal aquifer heterogeneities and implications in regional model parameterization N. Manewell et al. https://doi.org/10.3389/frwa.2023.1334022
17. Model simplification to simulate groundwater recharge from a perched gravel-bed river A. Di Ciacca et al. https://doi.org/10.1016/j.jhydrol.2024.132016