The use of the Raven framework will help building several semi-distributed models appropriate to the watersheds of southern Quebec. It will allow the exploration of the different algorithms to simulate snow melting and evapotranspiration.
Contribution to the prioritization of watersheds to be mapped in order to ensure public safety from flooding through the use of the results and the tool.
Once completed, the methodology developed will make it possible to estimate uncertainties in extreme flow values for different return periods for all gauged sites in southern Québec. This knowledge of uncertainty will provide a better understanding of flood events and a better estimation of flood-risk areas.
This project will determine whether assimilating snow in HYDROTEL improves hydrological simulation and forecasting, and if so, under what conditions.
In the aftermath of the events of Spring 2017, the Government of Quebec approached various players to initiate reflection on how best to manage flooding risks across the province in the context of a changing climate. This brainstorming activity culminated in a number of important realizations, including the need for comprehensive and up-to-date mapping of flood zones throughout Quebec that would foster adequate awareness of the risk inherent in land management decisions and the implementation of adaptation solutions. Following this exercise, the project INFO-Crue was launched.
This project has advanced our understanding of how heterogeneous ensemble simulations should be combined to maximize the information contained in climate projections.
Many climate change adaptation and mitigation measures involve changes in land use, including urban planning, agricultural practices, the planting of trees or crops for bioenergy or carbon capture, and the restoration of natural ecosystems.
The results of this project will provide decision-makers with a better understanding of the risks related to extreme flood events in both gauged and ungauged areas. Annual peak flow distributions for spring and summer-autumn flood periods will be used to drive the hydraulic models in the flood zone mapping process.
The project will support the development of predictive mapping adapted to user needs that will help to better equip institutions and organizations involved in flood management to ensure the safety and well-being of the population.
