Investigating the impact of temporal resolution on a snow model used for hydrological modelling

Real-time flood forecasting and other hydrological applications in mountainous areas require a good understanding and accounting of snow accumulation and melt. The CemaNeige snow model is currently used with the GRP hydrological model by most regional operational services in France to produce floods forecasts with lead times varying from a few hours to a few days. The snow model is based on a degree-day approach and needs limited inputs (precipitation and air temperature) spatialized on altitude bands over the catchment. It was initially developed on snow-dominated catchments by Valéry et al. (2014) using only streamflow series as calibration information. The model was then adapted by Riboust et al. (2019) to better simulate snow-covered areas as estimated by MODIS satellite images. These data were used as a secondary source of information for parameter calibration. All these developments were made at the daily time step. However, for real-time purposes, the outputs from the snow model are often needed at a finer time step, typically hourly or sub-hourly.

Here the transposability and the consistency of the CemaNeige model were studied across a range of time steps, from hourly to daily, on a set of snow-influenced catchments. This follows previous works on the hydrological model to improve its consistency across time scales (see e.g. Viatgé et al., 2019). Several questions were addressed:

• To which extent are the outputs of the snow model and its parameters consistent across various time steps?
• Is the current snow model complexity (structure and parameters) sufficient to simulate the snow influence at the catchment scale at sub-daily time steps?
• Can we expect better results by running the snow model at sub-daily time steps than by disaggregating the outputs of the snow model run at the daily time?

The answers to these questions will be presented based on a comprehensive testing scheme and a set of numerical criteria. Perspectives in terms of operational use will be discussed.