Researchers at the University of Minnesota Twin Cities have developed artificial intelligence models that improve flood forecasting accuracy compared to current methods. The studies, published in Water Resources Research and the Proceedings of the IEEE International Conference on Data Mining, demonstrate how "knowledge-guided" artificial intelligence can assist forecasters as extreme weather events become more frequent.
Separately, a Penn State study analyzing more than three decades of data suggests that economic growth can occur without increasing greenhouse gas emissions, but only under strict conditions and primarily in wealthy nations. The research examined how climate policies affect the relationship between economic expansion and emissions using data from the Organisation for Economic Co-operation and Development's Climate Actions and Policies Measurement Framework.
The flood forecasting research comes as communities worldwide face increasing risks from extreme weather events linked to climate change. The AI-powered prediction systems could help save lives and protect critical infrastructure by providing more accurate advance warnings of flooding events.
These developments highlight the dual challenge of climate adaptation and mitigation. While improved forecasting helps communities prepare for climate impacts, the economic growth study suggests policy interventions may allow continued prosperity while reducing emissions in developed countries.