EGU21-7843, updated on 04 Mar 2021
https://doi.org/10.5194/egusphere-egu21-7843
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Simulating catchment scale river discharges and flood events from large scale atmospheric information: Example of the Upper Rhône River (European Alps)

Caroline Legrand, Benoît Hingray, and Bruno Wilhelm
Caroline Legrand et al.
  • Institute for Geosciences and Environmental Research, University Grenoble Alpes, CNRS, IRD, G-INP, Grenoble, France (caroline.legrand@univ-grenoble-alpes.fr)

Floods are highly destructive natural hazards causing widespread impacts on socio-ecosystems. This hazard could be further amplified with the ongoing climate change, which will likely alter magnitude and frequency of floods. Estimating how flood regimes could change in the future is however not straightforward. The classical approach is to estimate future hydrological regimes from hydrological simulations forced by time series scenarii of weather variables for different future climate scenarii. The development of relevant weather scenarii for this is often critical. To be adapted to the critical space and time scales of the considered basins, weather scenarii are thus typically produced from climate models with downscaling models (either dynamic or statistical).

In this study, we aim to evaluate the capacity of such a simulation chain to reproduce floods observed in the upper Rhône River (10900 km², European Alps) over the last century. The modeling chain is made up of (i) the atmospheric reanalysis ERA-20C (1900-2010), (ii) the statistical downscaling model Analog, and (iii) the glacio-hydrological model GSM-SOCONT (Glacier and Snowmelt SOil CONTribution model; Schaefli et al., 2005). To assess the performance of this modeling chain, the simulated scenarii of mean areal precipitation and temperature are compared to the observed time series over the common period (1961-2010), whereas the discharge scenarii are compared to the reference time series (1920-2010).

In this presentation, we will discuss (i) the results obtained by the basic Analog method, namely a flood events underestimation due to an underestimation of extreme precipitation values, in particular 3-day and 5-day extreme precipitation, and (ii) the enhanced results obtained by the improved version of Analog SCAMP (Sequential Constructive Atmospheric Analogues for Multivariate weather Predictions; Raynaud et al., 2020) combined to the Schaake Shuffle method.

References:

Schaefli, B., Hingray, B., M. Niggli, M., Musy, A. (2005). A conceptual glacio-hydrological model for high mountainous catchments. Hydrology and Earth System Sciences Discussions, European Geosciences Union, 9, 95-109.

Raynaud, D., Hingray, B., Evin, G., Favre, A.-C., Chardon, J. (2020). Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues. Hydrology and Earth System Sciences Discussions, European Geosciences Union, 24(9), 4339-4352.

How to cite: Legrand, C., Hingray, B., and Wilhelm, B.: Simulating catchment scale river discharges and flood events from large scale atmospheric information: Example of the Upper Rhône River (European Alps), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7843, https://doi.org/10.5194/egusphere-egu21-7843, 2021.

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