As global weather events become more extreme, scientists are developing innovative solutions for forecasting and facing droughts.
One university student is enhancing drought predictions with artificial intelligence. Andrew Watford, a fourth-year Faculty of Science student at the University of Waterloo in Canada, is working on an AI tool that accurately predicts droughts in Kenya.
Watford, along with two supervising professors, published a paper detailing the findings in the Ecological Informatics journal. Though the research is still in the early stages, it offers a viable stepping stone for future prediction tools.
"Our goal was to bring together mathematics and machine learning to develop new methodologies and push the field forward to predict drought," Watford said. "We are still far off from predicting drought five years in the future with certainty, but it's a step towards trying to find the best way to do that."
Predicting extreme weather events, such as droughts, is vital, especially amid a shifting climate. By using AI models to forecast droughts, researchers could better prepare and safeguard communities.
"The research doesn't end with being able to predict drought," Watford said. "It is an evolving tool that will help people and save lives."
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Human-caused global heating has seen droughts become much more prevalent. Hotter temperatures have led to more intense droughts across Eastern Africa, threatening crops and wildlife in countries including Kenya and Ethiopia, as World Weather Attribution reported.
"Drought is a naturally occurring phenomenon that affects millions of people and results in billions of dollars in damages each year, with impacts expected to worsen due to climate change," stated Watford's paper, shared by Science Direct.
This paper examined the effectiveness of three different models for predicting droughts in regions of Kenya, including two that involve machine learning. The researchers found that the models performed best in a particular farming zone since rain in this area followed a more significant and consistent yearly pattern.
Moving forward, Watford hopes his research serves as a foundation for improving extreme weather prediction tools.
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