RESEARCH HIGHLIGHT – Spatial Datasets of 30-year (1991-2020) Average Monthly Total Precipitation and Minimum/Maximum Temperature for Canada and the United States
This study, led by researchers utilizing thin plate smoothing spline models, examines 30-year (1991-2020) average monthly total precipitation and minimum/maximum temperature datasets for Canada and the United States.
CANADIAN WATER RESOURCES ASSOCIATION, Water News Volume 42, No 4 – Fall 2023: Eliminating the unknowns: Canada1Water reveals the country’s water future with a new continental-scale model.
The Canadian Water Resources Association has included a feature article on the Canada1Water project in the latest issue of Water News CWRA's official magazine.
"Few decisions are more crucial to our future than how we manage freshwater resources. Wise choices require a clear understanding of conditions today and how they are likely to change over time. That’s exactly what the Canada1Water project aims to provide by giving Canadian decision-makers an all-new continental-scale model of groundwater, surface water and climate interactions that looks out to the end of this century".
Agriculture Canada highlights C1W - Researchers protect environment, human and animal health with natural capital
Agriculture Canada has spotlighed the Canada1Water project in their latest "Scientific achievements in agriculture" feature article, and the ways that the C1W project continues to benefit (and benefit from) the "Environmental Change One Health Observatory" (ECO2) initiative at AAFC.
New York Times - A Tangle of Rules to Protect America’s Water Is Falling Short
“AMERICA’S STEWARDSHIP of one of its most precious resources, groundwater, relies on a patchwork of state and local rules so lax and outdated that in many places oversight is all but nonexistent, a New York Times analysis has found.”
NRCan’s Simply Science highlights C1W - The science of seeing into the future: Canada’s groundwater
“With scientists predicting major water shortages in less than 10 years, we need to make smart choices today about how to use and protect our water resources. The Canada1Water project aims to help. Co-led by Natural Resources Canada’s Groundwater Geoscience Program and Aquanty Inc., it will give Canadians powerful new tools to understand the country’s water future.” - Simply Science
The Conversation - Understanding the dynamics of snow cover in forests can help us predict flood risks
An piece in The Conversation highlights the important role that winter snowpack plays on hydrology, and how a better understanding of snow depth in forested catchments can help us better predict flood risks during the spring freshet.
Canada1Water: 2023 Progress Report
The Canada1Water continues to make steady progress toward our goal of providing Canadians with a comprehensive data/modelling framework and decision support system to evaluate the sustainability of water resources under a changing climate. The 2023 Progress Meeting and Summary Report provides a comprehensive overview of project progress up to June 2023.
New York Times - America Is Using Up Its Groundwater Like There’s No Tomorrow
The NY Times performed comprehensive analysis of decades worth groundwater level data across America, and the findings indicate that there is a national groundwater crisis (that has been growing in severity for quite some time).
The Water Institute - Baseflow trends across Canada: The impact of climate change
This recent article in The Water Institute’s newsletter - WaterResearch - highlights a statistical analysis of baseflow trends to streams and rivers across Canada. The results of this work can inform water resources management by identifying the direction of change in groundwater availability across Canada and regions where interventions may be necessary.
Canada1Water: 2022 Progress Report
The Canada1Water project has reached the midpoint of its three-year project . This progress report covers model development updates as well as a review on engagement and outreach with project stakeholders.
CMOS BULLETIN - Bias Correcting Surface Snow Water Equivalent Estimates using Machine Learning
Snow is a critical contributor to Ontario's water-energy budget, with impacts on water resource management and flood forecasting. Snowmelt-derived flooding has become increasingly problematic across much of Canada in recent decades as global temperatures continue to rise. This article discusses a snow-melt bias correction method developed by Dr. Fraser King and other C1W collaborators.