Improvement of hydrological forecasting of inflows to the St. Lawrence watershed
Hydrological forecasting provides predictions of water levels and flows on rivers and streams several days in advance. It is a very useful tool for ensuring public safety as it can predict, for instance, when a river is about to overflow its banks, thereby allowing residents along the river to take the necessary measures.
In their effort to improve hydrological forecasting for the St. Lawrence River and its tributaries, Environment and Climate Change Canada (ECCC) and the Department of Sustainable Development, Environment and the Fight Against Climate Change (MDDELCC) must address the challenge of ensuring alignment between the hydrological forecast models and the computer tools they use so that they can share their meteorological and hydrological data. The St. Lawrence Action Plan (SLAP) is the mechanism for increased collaboration.
The purpose of this project is to improve the available hydrological forecasting tools for the St. Lawrence watershed by leveraging the expertise of the two teams. To this end, a common data assimilation method will be developed, common hydrological modelling tools will be assessed and forecasting approaches based on these advances will be tested on St. Lawrence River tributary watersheds.
The tools developed may be integrated by ECCC and MDDELCC into their forecasting activities as a function of their respective operational mandates. In doing so, it will be possible to improve real-time decision-making capabilities for the St. Lawrence and its tributaries as we will be better equipped to predict their behaviour and to respond quickly.
Figure 1: The St. Lawrence River watershed; modelling by the Numerical Environmental Prediction Program
Enhanced use of the meteorological data from the St. Lawrence watershed
Snow measurements are important to hydrological forecasting, which involves predicting flows and water levels of rivers and streams. Snowfall amounts at a particular location are difficult to predict, and they have a significant impact on streamflow. A number of tools are currently used to measure snowfall amounts, but they generate different data for a given site, which creates measurement uncertainties. In the face of this issue, ECCC and MDDELCC wish to enhance the sharing of snow-related data between the two governments and to work together to reduce uncertainties.
The objective of this project, which will be carried out in partnership with Université Laval, is to develop a common technique for measuring and locating snow for the St. Lawrence watershed. A shared database for recent observations and an optimized procedure for locating snow will be developed. The project will allow for adoption of best practices and the enhancement of tools, thus contributing to improving snowfall amount forecasts at a given location.
Photo : Amandine Pierre @ Université Laval
The Montmorency forest, which is managed by Université Laval, receives over 600 mm of solid precipitation (snow, hail, sleet) annually, making it an ideal location for scientific research. Various instruments have been installed in the forest to collect hydrometeorological data—i.e., meteorological data related to the hydrological cycle—including no fewer than 13 snow measurement devices. Given its natural physical features and its history as a site for hydrometeorological measurements, the Montmorency Forest was selected as the location for the experimental meteorological station. Sophisticated measuring devices have been installed at the site, including a Double Fence Intercomparison Reference or DFIR (ECCC) gauge and a Nipher shield precipitation gauge (MDDELCC).
Photo: Amandine Pierre @ Université Laval
Description : The Double Fence Intercomparison Reference (DFIR) gauge at the Montmorency Forest experimental meteorological station on April 28, 2016. 63 cm of snow.
Modelling of the hydrology and hydraulics of the Richelieu River watershed
The 2011 Richelieu River floods were one of Quebec’s worst natural disasters. Forecasting water levels and flows is critical to anticipating and preparing for such a threat. Although the International Joint Commission determined that a forecast model is required for the Richelieu River watershed, its geography and the complex issues affecting the watershed pose major challenges for the modelling of its hydrology and hydraulics. The watershed contains a major lake (Lake Champlain), a mountainous, forested region upstream and gently sloping agricultural lands downstream. The Richelieu River is also a major tributary of the St. Lawrence River. For these reasons, the watershed was selected for a pilot study combining hydrology and hydraulics.
More specifically, the project is designed to combine observed data, forecasts and existing hydrological (streamflow) and hydraulic (depth, velocity and flooded areas) models to create and populate a model combining hydrology and hydraulics that will provide a more comprehensive picture of the watershed. The model will improve flow forecasts on Lake Champlain and the Richelieu River, thus helping better anticipate and prepare for major changes.
Assessment of climate change impacts on St. Lawrence River water levels and flows
According to regional climate models, precipitation and temperature changes in the St. Lawrence watershed are predicted by the years 2050 and 2100, as compared to data recorded between 1961 and 1990. Water level fluctuations are anticipated that could have their share of inconveniences for riverside communities and users of the St. Lawrence. The purpose of this project is to assess the impacts of climate change on the river’s water levels and flows in order to be able to better adapt to them.
The first part of the study involves using outputs from climate models as inputs for hydrological models for this watershed to forecast flows on Lake Ontario and on rivers flowing into the St. Lawrence. The forecasts will then be used to feed a hydraulic model of the St. Lawrence River that will provide future water levels and flows.
Water level simulations will provide valuable information for anticipating changes in the St. Lawrence. They will be used to assess potential risks to the public and the environment and to implement adaptation measures to prepare for such risks.