MODFLOW

MODFLOW is the USGS’s three-dimensional (3D) finite-difference groundwater model. MODFLOW is considered an international standard for simulating and predicting groundwater conditions and groundwater/surface-water interactions. Originally developed and released solely as a groundwater-flow simulation code when first published in 1984, MODFLOW’s modular structure has provided a robust framework for integration of additional simulation capabilities that build on and enhance its original scope. The family of MODFLOW-related programs now includes capabilities to simulate coupled groundwater/surface-water systems, solute transport, variable-density flow (including saltwater), aquifer-system compaction and land subsidence, parameter estimation, and groundwater management.


References in zbMATH (referenced in 63 articles )

Showing results 1 to 20 of 63.
Sorted by year (citations)

1 2 3 4 next

  1. Kyas, Svetlana; Volpatto, Diego; Saar, Martin O.; Leal, Allan M. M.: Accelerated reactive transport simulations in heterogeneous porous media using Reaktoro and Firedrake (2022)
  2. Blank, Laura; Meneses Rioseco, Ernesto; Caiazzo, Alfonso; Wilbrandt, Ulrich: Modeling, simulation, and optimization of geothermal energy production from hot sedimentary aquifers (2021)
  3. Chen, Shang-Ying; Hsu, Kuo-Chin; Fan, Chia-Ming: Improvement of generalized finite difference method for stochastic subsurface flow modeling (2021)
  4. Chen, Yuntian; Huang, Dou; Zhang, Dongxiao; Zeng, Junsheng; Wang, Nanzhe; Zhang, Haoran; Yan, Jinyue: Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method (2021)
  5. Koch, Timo; Gläser, Dennis; Weishaupt, Kilian; Ackermann, Sina; Beck, Martin; Becker, Beatrix; Burbulla, Samuel; Class, Holger; Coltman, Edward; Emmert, Simon; Fetzer, Thomas; Grüninger, Christoph; Heck, Katharina; Hommel, Johannes; Kurz, Theresa; Lipp, Melanie; Mohammadi, Farid; Scherrer, Samuel; Schneider, Martin; Seitz, Gabriele; Stadler, Leopold; Utz, Martin; Weinhardt, Felix; Flemisch, Bernd: DuMu(^\textx 3) -- an open-source simulator for solving flow and transport problems in porous media with a focus on model coupling (2021)
  6. Kuhlman, Kristopher L.; Malama, Bwalya: Uncoupling electrokinetic flow solutions (2021)
  7. Lykkegaard, Mikkel B.; Dodwell, Tim J.; Moxey, David: Accelerating uncertainty quantification of groundwater flow modelling using a deep neural network proxy (2021)
  8. Travis Thurber, Chris R. Vernon, Ning Sun, Sean W. D. Turner, Jim Yoon, Nathalie Voisin: mosartwmpy: A Python implementation of the MOSART-WM coupled hydrologic routing and water management model (2021) not zbMATH
  9. Wang, Nanzhe; Chang, Haibin; Zhang, Dongxiao: Theory-guided auto-encoder for surrogate construction and inverse modeling (2021)
  10. Xu, Rui; Zhang, Dongxiao; Rong, Miao; Wang, Nanzhe: Weak form theory-guided neural network (TgNN-wf) for deep learning of subsurface single- and two-phase flow (2021)
  11. Egidi, N.; Gioia, E.; Maponi, P.; Spadoni, L.: A numerical solution of Richards equation: a simple method adaptable in parallel computing (2020)
  12. Pathania, Tinesh; Eldho, T. I.; Bottacin-Busolin, Andrea: Coupled simulation of groundwater flow and multispecies reactive transport in an unconfined aquifer using the element-free Galerkin method (2020)
  13. Pedretti, Daniele: Heterogeneity-controlled uncertain optimization of pump-and-treat systems explained through geological entropy (2020)
  14. Piret, Cécile; Dissanayake, Nadun; Gierke, John S.; Fornberg, Bengt: The radial basis functions method for improved numerical approximations of geological processes in heterogeneous systems (2020)
  15. Vassilevski, Yuri; Terekhov, Kirill; Nikitin, Kirill; Kapyrin, Ivan: Parallel finite volume computation on general meshes (2020)
  16. Zanini, Andrea; D’Oria, Marco; Tanda, Maria Giovanna; Woodbury, Allan D.: Coupling empirical Bayes and Akaike’s Bayesian information criterion to estimate aquifer transmissivity fields (2020)
  17. Zheng, Qiang; Zeng, Lingzao; Karniadakis, George Em: Physics-informed semantic inpainting: application to geostatistical modeling (2020)
  18. Zhang, Yong; Sun, HongGuang; Zheng, Chunmiao: Lagrangian solver for vector fractional diffusion in bounded anisotropic aquifers: development and application (2019)
  19. Anuprienko, D. V.; Kapyrin, I. V.: Modeling groundwater flow in unconfined conditions: numerical model and solvers’ efficiency (2018)
  20. D’Oria, Marco; Zanini, Andrea; Cupola, Fausto: Oscillatory pumping test to estimate aquifer hydraulic parameters in a Bayesian geostatistical framework (2018)

1 2 3 4 next