EGU22-12136, updated on 23 May 2022
https://doi.org/10.5194/egusphere-egu22-12136
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Assessing parsimonious hydrological model structures with distributed adjoint-based calibration in SMASH Python-Fortran platform on large sample of French catchments and flash floods

François Colleoni1, Pierre-André Garambois1, Maxime Jay-Allemand2, Pierre Javelle1, Patrick Arnaud1, Catherine Fouchier, and Igor Gejadze3
François Colleoni et al.
  • 1Aix-Marseille University, INRAE, RECOVER - rhax team, Aix-en-Provence, France (pierre-andre.garambois@inrae.fr)
  • 2Hydris Hydrologie corp.
  • 3INRAE, Montpellier Univ., GEAU

This contribution presents improvements of conceptual models in SMASH (Spatially distributed Modelling and ASsimilation for Hydrology) platform, underlying the French national flash flood forecasting system Vigicrues Flash [1], based on: (i) the 3-parameters model formulation and variational data assimilation algorithm of [2] that showed promising results (i) hypothesis testing on a large sample of catchments and flash floods; (ii) comparison of the SMASH model performances in uniform and distributed calibration to GR models; (iii) a new wrapped Python interface automatically generated by the f90wrap library [3]. Multiple tests have allowed us to converge on two parsimonious distributed model structures that have comparable performances to the GR models in spatially uniform calibration. These two structures, mainly based on GR operators at the pixel scale, differ in the production operator, with the 6-parameters structure being GR production and the 7-parameters structure being VIC production. Furthermore, the use of distributed calibration applied to these formulations via adjoint model resolution shows significantly better calibration performances without being less robust in spatio-temporal validation. Immediate work deals with improving the regional calibration scheme by tayloring the global search of semi-distributed prior parameter sets, with multi-gauge constrains, improving physiographic regularizations in the forward-inverse SMASH assimilation chain, using Python librairies.

References
[1] P. Javelle, et al. Flash flood warnings: Recent achievements in france with the national vigicrues flash system UNDRR GAR, 2019.
[2] M. Jay-Allemand, et al.. On the potential of variational calibration for a fully distributed hydrological model: application on a mediterranean catchment. HESS, 2020, https://doi.org/10.5194/hess-24-5519-2020
[3] J. R. Kermode. f90wrap: an automated tool for constructing deep python interfaces to modern fortran codes. 2020. https://doi.org/10.1088/1361-648X/ab82d2

How to cite: Colleoni, F., Garambois, P.-A., Jay-Allemand, M., Javelle, P., Arnaud, P., Fouchier, C., and Gejadze, I.: Assessing parsimonious hydrological model structures with distributed adjoint-based calibration in SMASH Python-Fortran platform on large sample of French catchments and flash floods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12136, https://doi.org/10.5194/egusphere-egu22-12136, 2022.

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