Nicolas Gasset


2021

DOI bib
Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E)
Juliane Mai, Bryan A. Tolson, Helen C. Shen, Étienne Gaborit, Vincent Fortin, Nicolas Gasset, Hervé Awoye, Tricia A. Stadnyk, Lauren M. Fry, Emily A. Bradley, Frank Seglenieks, André Guy Tranquille Temgoua, Daniel Princz, Shervan Gharari, Amin Haghnegahdar, Mohamed Elshamy, Saman Razavi, Martin Gauch, Jimmy Lin, Xiaojing Ni, Yongping Yuan, Meghan McLeod, N. B. Basu, Rohini Kumar, Oldřich Rakovec, Luis Samaniego, Sabine Attinger, Narayan Kumar Shrestha, Prasad Daggupati, Tirthankar Roy, Sungwook Wi, Timothy Hunter, James R. Craig, Alain Pietroniro
Journal of Hydrologic Engineering, Volume 26, Issue 9

AbstractHydrologic model intercomparison studies help to evaluate the agility of models to simulate variables such as streamflow, evaporation, and soil moisture. This study is the third in a sequen...

2020

DOI bib
Assessing the factors governing the ability to predict late-spring flooding in cold-region mountain basins
Vincent Vionnet, Vincent Fortin, Étienne Gaborit, Guy Roy, Maria Abrahamowicz, Nicolas Gasset, John W. Pomeroy
Hydrology and Earth System Sciences, Volume 24, Issue 4

Abstract. From 19 to 22 June 2013, intense rainfall and concurrent snowmelt led to devastating floods in the Canadian Rockies, foothills and downstream areas of southern Alberta and southeastern British Columbia, Canada. Such an event is typical of late-spring floods in cold-region mountain headwater, combining intense precipitation with rapid melting of late-lying snowpack, and represents a challenge for hydrological forecasting systems. This study investigated the factors governing the ability to predict such an event. Three sources of uncertainty, other than the hydrological model processes and parameters, were considered: (i) the resolution of the atmospheric forcings, (ii) the snow and soil moisture initial conditions (ICs) and (iii) the representation of the soil texture. The Global Environmental Multiscale hydrological modeling platform (GEM-Hydro), running at a 1 km grid spacing, was used to simulate hydrometeorological conditions in the main headwater basins of southern Alberta during this event. The GEM atmospheric model and the Canadian Precipitation Analysis (CaPA) system were combined to generate atmospheric forcing at 10, 2.5 and 1 km over southern Alberta. Gridded estimates of snow water equivalent (SWE) from the Snow Data Assimilation System (SNODAS) were used to replace the model SWE at peak snow accumulation and generate alternative snow and soil moisture ICs before the event. Two global soil texture datasets were also used. Overall 12 simulations of the flooding event were carried out. Results show that the resolution of the atmospheric forcing affected primarily the flood volume and peak flow in all river basins due to a more accurate estimation of intensity and total amount of precipitation during the flooding event provided by CaPA analysis at convection-permitting scales (2.5 and 1 km). Basin-averaged snowmelt also changed with the resolution due to changes in near-surface wind and resulting turbulent fluxes contributing to snowmelt. Snow ICs were the main sources of uncertainty for half of the headwater basins. Finally, the soil texture had less impact and only affected peak flow magnitude and timing for some stations. These results highlight the need to combine atmospheric forcing at convection-permitting scales with high-quality snow ICs to provide accurate streamflow predictions during late-spring floods in cold-region mountain river basins. The predictive improvement by inclusion of high-elevation weather stations in the precipitation analysis and the need for accurate mountain snow information suggest the necessity of integrated observation and prediction systems for forecasting extreme events in mountain river basins.