The future of drought monitoring in Canada with machine learning and AI

Machine Learning


Canada’s Drought Monitor is taking steps to improve accuracy in 2026.

“We’re actively looking at new models, and we’re developing our own model that leverages some of the power of artificial intelligence and machine learning. This will help us get a first look at droughts across the country and pull the right indicators in the right areas and at the right time,” said Trevor Hadwen, an agro-climate expert at Agriculture Canada who co-leads drought monitoring with David Lee.

“Droughts are different in the spring and summer and fall. There’s so much data available to us and so many different combinations of that data. Machine learning and AI are ideal sources for us to look at to simplify that and help us make those assessments a little bit more precise.”

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Why it’s important: Parts of Canada have been experiencing years of drought, and having the most accurate tool for predicting drought would help farmers with both long-term and short-term planning.

This information includes approximately 1,500 data points across the country with climate observatories.

By next spring, the program aims to move to more gridded data, which will display specific values ​​for a 10-kilometer grid across the country.

“We’re always battling with what we can offer on the map across the country and how small we can go, because for some farms in areas where there’s a lot of data, it’s really great,” Hadwen said.

“Going north, there’s not as much data. Gridded datasets will solve some of this problem.”

The origins of drought monitors began small in prairie regions focused solely on agriculture and eventually spread throughout the country except Nunavut and the Arctic.

This is a team effort. Agriculture Canada draws information from Environment Canada, climate and hydrometry data for each province, Natural Resources Canada’s Forest Fire Network, Agriculture and Water Boards, and satellite-based plant health indices.

“That last part is the important one,” Hadwen said.

“You can model drought all you want, but what’s hard to really find out is what the effects are. You might get a lot of rain in a particular area, but all that water rushes off into rivers and doesn’t really benefit soil moisture, at least not at depth.”

He said the monitor was accessing farmers at the ground level.

“When you look at drought from an agricultural perspective, you need to know what the impacts are. You need to know where there are problems, where there are problems with feed, where there are problems with canola, where there are problems with water supply.”

There are different types of drought in Canada, which can affect regions differently.

In regions like British Columbia, drought is not just about soil moisture, but also the availability of water from river flows and winter snowmelt.

This type of information is useful to producers.

Farmers in central Manitoba are well aware of the drought in front of them, but knowing what their neighbors are doing can help them plan for the short and long term.

“It’s not always necessary to know where you are,” Hadwen said.

“It’s about knowing where your neighbors are, where your customers are, where the dealers who are trying to send seeds, chemicals, etc. to that area are. That’s information that helps them plan, knowing the market and knowing where they are relative to the rest of Canada.”

He added that the drought outlook map is built on monthly monitoring and also uses historical trends.

“Will the drought really change? Will it get better?”

Agriculture officials strive to have monthly drought monitors ready for agricultural producers and water managers by the 10th of each month.

Drought is considered from many angles, including hydraulics, meteorology, environmental landscape impacts, and sustainability.

Hadwen said he and his team are proud of how much the Drought Monitor is being used by farmers, policy makers, local government planners and the media.

“They use it in different ways,” he said.

“They may not know for sure how it’s made, but the question is how do they trust this? How accurate is it? What are they using?”



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