Université Laval

The goal of this project is to evaluate if mesoscale (35 km) meteorological ensemble forecasts coupled to a short-range hydrological forecasting system can lead to improved forecasts, and thus help maximize hydropower production and minimize flood risks. Positive results would pave the way for a full project which would aim to design an efficient short-range hydrological ensemble forecasting system adapted to the climate and hydrology of the Great-Lakes and Saint Lawrence River basin.

This project deals with the mathematics of risk modeling and resource management. Using mathematical and statistical methods, the team develops new tools to help the financial services industry make better decisions about when to trade and at what price based on the available financial data. During the past year, the team focused on the development of statistical methods for measuring volatility and assessing asset pricing models in financial markets.

The forest industry is an extremely important sector of Canadian economic activity as it represents the largest part of Canada’s trade surplus and 3% of its GDP. Canadian forests sustain an industry that continues to support a significant number of jobs. The worldwide increase in competition and excess production capacity have considerable implications for the situation of the Canadian forest industry and threaten its position in international markets.