Bibliography#
Full list of references cited across the HydroModPy theory documentation.
The list is generated from docs/source/theory/references.bib via the
sphinxcontrib-bibtex extension. To add a new reference, append a BibTeX
entry to that file and cite it with :cite:`<key>` from any documentation
page.
R. Abhervé, C. Roques, A. Gauvain, L. Longuevergne, S. Louaisil, L. Aquilina, and J.-R. de Dreuzy. Calibration of groundwater seepage against the spatial distribution of the stream network to assess catchment-scale hydraulic properties. Hydrology and Earth System Sciences, 27(17):3221–3239, 2023. doi:10.5194/hess-27-3221-2023.
R. Abhervé, C. Roques, J.-R. de Dreuzy, T. Datry, P. Brunner, L. Longuevergne, and L. Aquilina. Improving calibration of groundwater flow models using headwater streamflow intermittence. Hydrological Processes, 2024. doi:10.1002/hyp.15167.
R. Abhervé, C. Roques, J.-R. de Dreuzy, T. Van Der Veen, L. Dumaine, E. Chatton, P. Brunner, L. Aquilina, and L. Servière. Projected climate change impacts on groundwater-surface water connectivity in a compartmentalized mountain headwater bedrock aquifer. Water Resources Research, 2025. doi:10.1029/2025WR040083.
Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, and Masanori Koyama. Optuna: a next-generation hyperparameter optimization framework. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2623–2631. 2019. doi:10.1145/3292500.3330701.
Mary P. Anderson, William W. Woessner, and Randall J. Hunt. Applied Groundwater Modeling: Simulation of Flow and Advective Transport. Academic Press, 2 edition, 2015. ISBN 978-0-12-058103-0. doi:10.1016/C2009-0-21563-7.
Richard Barnes, Clarence Lehman, and David Mulla. Priority-flood: an optimal depression-filling and watershed-labeling algorithm for digital elevation models. Computers and Geosciences, 62:117–127, 2014. doi:10.1016/j.cageo.2013.04.024.
J. Bergstra and Y. Bengio. Random search for hyper-parameter optimization. Journal of Machine Learning Research, 13:281–305, 2012. URL: https://www.jmlr.org/papers/v13/bergstra12a.html.
J. Boussinesq. Essai sur la théorie des eaux courantes. Mémoires présentés par divers savants à l'Académie des Sciences, 23:1–680, 1877.
J. Boussinesq. Recherches théoriques sur l'écoulement des nappes d'eau infiltrées dans le sol. Journal de Mathématiques Pures et Appliquées, 10:5–78, 1904.
W. Brutsaert. Hydrology: An Introduction. Cambridge University Press, Cambridge, 2005. doi:10.1017/CBO9780511808470.
Kerry L. Callaghan, Richard Barnes, Kyle Barnhart, and Andrew D. Wickert. Coupling a groundwater model with fill-spill-merge. Geoscientific Model Development, 18:1463–1486, 2025. doi:10.5194/gmd-18-1463-2025.
J. A. Christen and C. Fox. Markov chain Monte Carlo using an approximation. Journal of Computational and Graphical Statistics, 14(4):795–810, 2005. doi:10.1198/106186005X76983.
J. Dupuit. Études théoriques et pratiques sur le mouvement des eaux dans les canaux découverts et à travers les terrains perméables. Dunod, Paris, 2nd edition, 1863.
Daniel T. Feinstein, Michael N. Fienen, Howard W. Reeves, and Christian D. Langevin. A semi-structured modflow-usg model to evaluate local water sources to wells for decision support. Groundwater, 58(4):524–534, 2020. doi:10.1111/gwat.12931.
M. G. Floriancic, R. Abhervé, C. Bouchez, J. J. Martinez, and C. Roques. Evidence of groundwater seepage and mixing at the vicinity of a knickpoint in a mountain stream. Geophysical Research Letters, 2024. doi:10.1029/2024GL111325.
Henk M. Haitjema and Sherry Mitchell-Bruker. Are water tables a subdued replica of the topography? Ground Water, 43(6):781–786, 2005. doi:10.1111/j.1745-6584.2005.00090.x.
N. Hansen. The CMA evolution strategy: a tutorial. 2016. URL: https://arxiv.org/abs/1604.00772, arXiv:1604.00772.
M. S. Hantush. Modification of the theory of leaky aquifers. Journal of Geophysical Research, 65(11):3713–3725, 1960. doi:10.1029/JZ065i011p03713.
A. W. Harbaugh. MODFLOW-2005, the U.S. Geological Survey modular ground-water model: the ground-water flow process. Techniques and Methods 6-A16, U.S. Geological Survey, 2005. doi:10.3133/tm6A16.
C. D. Langevin, J. D. Hughes, E. R. Banta, R. G. Niswonger, S. Panday, and A. M. Provost. Documentation for the MODFLOW 6 groundwater flow model. Techniques and Methods 6-A55, U.S. Geological Survey, 2017. doi:10.3133/tm6A55.
M. Le Mesnil, A. Gauvain, F. Gresselin, L. Aquilina, and J. de Dreuzy. Characterizing coastal aquifer heterogeneity from a single piezometer head chronicle. Journal of Hydrology, pages 131859, 2024. doi:10.1016/j.jhydrol.2024.131859.
Andrew T. Leaf and Michael N. Fienen. Modflow-setup: robust automation of groundwater model construction. Frontiers in Earth Science, 10:903965, 2022. doi:10.3389/feart.2022.903965.
John B. Lindsay. Efficient hybrid breaching-filling sink removal methods for flow path enforcement in digital elevation models. Hydrological Processes, 30(6):846–857, 2016. doi:10.1002/hyp.10648.
John B. Lindsay and Irena F. Creed. Removal of artifact depressions from digital elevation models: towards a minimum impact approach. Hydrological Processes, 19(16):3113–3126, 2005. doi:10.1002/hyp.5835.
John B. Lindsay and Irena F. Creed. Distinguishing actual and artefact depressions in digital elevation data. Computers and Geosciences, 32(8):1192–1204, 2006. doi:10.1016/j.cageo.2005.11.002.
E. Marti, S. Leray, and C. Roques. Catchment landforms predict groundwater-dependent wetland sensitivity to recharge changes. Hydrology and Earth System Sciences Discussions, 2024. doi:10.5194/HESS-2024-381.
J. A. Nelder and R. Mead. A simplex method for function minimization. The Computer Journal, 7(4):308–313, 1965. doi:10.1093/comjnl/7.4.308.
Gene-Hua Crystal Ng, Andrew D. Wickert, Lauren D. Somers, Leila Saberi, Collin Cronkite-Ratcliff, Richard G. Niswonger, and Jeffrey M. McKenzie. Gsflow-grass v1.0.0: gis-enabled hydrologic modeling of coupled groundwater-surface-water systems. Geoscientific Model Development, 11(12):4755–4777, 2018. doi:10.5194/gmd-11-4755-2018.
R. G. Niswonger, S. Panday, and M. Ibaraki. MODFLOW-NWT, a Newton formulation for MODFLOW-2005. Techniques and Methods 6-A37, U.S. Geological Survey, 2011. doi:10.3133/tm6A37.
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and É. Duchesnay. Scikit-learn: machine learning in Python. Journal of Machine Learning Research, 12:2825–2830, 2011. URL: https://www.jmlr.org/papers/v12/pedregosa11a.html.
C. E. Rasmussen and C. K. I. Williams. Gaussian Processes for Machine Learning. MIT Press, Cambridge, MA, 2006. URL: https://gaussianprocess.org/gpml/.
Thomas E. Reilly and Arlen W. Harbaugh. Guidelines for evaluating ground-water flow models. Scientific Investigations Report 2004-5038, U.S. Geological Survey, 2004. doi:10.3133/sir20045038.
C. V. Theis. The relation between the lowering of the piezometric surface and the rate and duration of discharge of a well using groundwater storage. Eos, Transactions American Geophysical Union, 16(2):519–524, 1935. doi:10.1029/TR016i002p00519.
P. Virtanen, R. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J. Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. J. Carey, İ. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R. Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, and P. van Mulbregt. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17:261–272, 2020. doi:10.1038/s41592-019-0686-2.