Bibliography#
Léon Bottou. Stochastic gradient descent tricks. Neural Networks: Tricks of the Trade: Second Edition, pages 421–436, 2012.
Ven Te Chow, David R. Maidment, and Larry W. Mays. Applied Hydrology. McGraw-Hill Series in Water Resources and Environmental Engineering, 1998.
Marcos Duarte and Renato Naville Watanabe. Notes on Scientific Computing for Biomechanics and Motor Control. March 2021. URL: https://doi.org/10.5281/zenodo.4599319, doi:10.5281/zenodo.4599319.
John Duchi, Elad Hazan, and Yoram Singer. Adaptive subgradient methods for online learning and stochastic optimization. Journal of machine learning research, 2011.
I. Emmanuel, H. Andrieu, E. Leblois, N. Janey, and O. Payrastre. Influence of rainfall spatial variability on rainfall–runoff modelling: benefit of a simulation approach? Journal of Hydrology, 531:337–348, 2015. Hydrologic Applications of Weather Radar. URL: https://www.sciencedirect.com/science/article/pii/S0022169415003170, doi:https://doi.org/10.1016/j.jhydrol.2015.04.058.
Nathalie Folton and Patrick Arnaud. Indicateurs sur la ressource en eau estimés par une modélisation pluie-débit regionalisée : la base de donnees web loieau. La Houille Blanche, 3:22 – 29, 2020. doi:https://doi.org/10.1051/lhb/2020034.
Federico Garavaglia, Matthieu Le Lay, Frèderic Gottardi, Rèmy Garçon, Joèl Gailhard, Emmanuel Paquet, and Thibault Mathevet. Impact of model structure on flow simulation and hydrological realism: from a lumped to a semi-distributed approach. Hydrology & Earth System Sciences, 2017.
Alex Graves. Generating sequences with recurrent neural networks. arXiv preprint arXiv:1308.0850, 2013.
Laurent Hascoet and Valérie Pascual. The tapenade automatic differentiation tool: principles, model, and specification. ACM Transactions on Mathematical Software (TOMS), 39(3):1–43, 2013.
Maxime Jay-Allemand, Pierre Javelle, Igor Gejadze, Patrick Arnaud, Pierre-Olivier Malaterre, Jean-Alain Fine, and Didier Organde. On the potential of variational calibration for a fully distributed hydrological model: application on a mediterranean catchment. Hydrology and Earth System Sciences, pages 1–24, 2020. doi:10.5194/hess-24-5519-2020.
James R Kermode. F90wrap: an automated tool for constructing deep python interfaces to modern fortran codes. J. Phys. Condens. Matter, March 2020. doi:10.1088/1361-648X/ab82d2.
Diederik P Kingma and Jimmy Ba. Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980, 2014.
Vit Klemeš. Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31(1):13–24, 1986.
N. Le Moine. Le bassin versant de surface vu par le souterrain : une voie d'amélioration des performances et du réalisme des modles pluie-débit ? PhD thesis, Cemagref (UR HBAN, Antony, 2008.
Xu Liang, Dennis P. Lettenmaier, Eric F. Wood, and Stephen J. Burges. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. Journal of Geophysical Research: Atmospheres, 99(D7):14415–14428, 1994. URL: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/94JD00483, arXiv:https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/94JD00483, doi:https://doi.org/10.1029/94JD00483.
V Lyne and M Hollick. Stochastic time-variable rainfall-runoff modelling. In Institute of Engineers Australia National Conference, volume 79, 89–93. Institute of Engineers Australia Barton, Australia, 1979.
C Michel. Hydrologie appliquée aux petits bassins ruraux. Hydrology handbook (in French), Cemagref, Antony, France, 1989.
Jerome Monnier. Data Assimilation - Inverse Problems, Assimilation, Control, Learning. INSA Toulouse, 2024. URL: https://www.math.univ-toulouse.fr/~jmonnie/Enseignement/CourseVDA.pdf.
Rory J Nathan and Thomas A McMahon. Evaluation of automated techniques for base flow and recession analyses. Water resources research, 26(7):1465–1473, 1990.
Charles Perrin, Claude Michel, and Vazken Andrèassian. Improvement of a parsimonious model for streamflow simulation. Journal of hydrology, 279(1-4):275–289, 2003.
E. Todini. The arno rainfall—runoff model. Journal of Hydrology, 175(1):339–382, 1996. URL: https://www.sciencedirect.com/science/article/pii/S0022169496800163, doi:https://doi.org/10.1016/S0022-1694(96)80016-3.
IK Westerberg and Hilary K McMillan. Uncertainty in hydrological signatures. Hydrology and Earth System Sciences, 19(9):3951–3968, 2015.
C Zhu, RH Byrd, P Lu, and J Nocedal. L-bfgs-b: a limited memory fortran code for solving bound constrained optimization problems: eecs department, northwestern university, evanston. Technical Report, IL, Technical Report No. NAM–11, 1994.
D. Zoccatelli, M. Borga, A. Viglione, G. B. Chirico, and G. Blöschl. Spatial moments of catchment rainfall: rainfall spatial organisation, basin morphology, and flood response. Hydrology and Earth System Sciences, 15(12):3767–3783, 2011. URL: https://hess.copernicus.org/articles/15/3767/2011/, doi:10.5194/hess-15-3767-2011.