Data collected in a participatory manner can be fed into models in order to define the flood zones and the alert levels for populations and infrastructure, in particular for the rivers where more traditional data collection is not possible.
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.
This project will determine whether assimilating snow in HYDROTEL improves hydrological simulation and forecasting, and if so, under what conditions.
By estimating water levels in ungauged areas, virtual stations contribute to the improvement of these essential tools. Based on free, easily accessible images, the approach will provide data on multiple sectors at an almost daily frequency and at little cost.
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.
Public safety officials, hydrological system managers and hydroclimatology researchers will be able to better assess the impacts of climate change on water resources based on changes in vegetation cover.
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.
