AI Models Map the Colorado River's Hard Choices

AI and machine learning tools are being deployed to model the future of the shrinking Colorado River, helping water managers make tough decisions about water allocation across seven U.S. states.

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The Colorado River, which supplies water to 40 million people across seven U.S. states, is facing a crisis as flows have declined by 20% since 2000. The U.S. Bureau of Reclamation, which manages the river's operations, is deploying advanced AI and machine learning tools to model different future scenarios and inform water allocation decisions. Streamflow forecasting models using satellite data and deep learning are now outperforming traditional methods, providing 5-7 days of advance warning on flood events compared to just 3 days previously. The scale of scenario modeling has also expanded, with millions of simulations mapping out how different operating strategies perform across a wide range of possible futures. The Colorado River Simulation System (CRSS) model, which has been the foundation for water allocation negotiations for decades, is now being enhanced with AI capabilities. This allows states, cities and tribes to run their own scenarios through CRSS, building trust in the model's assumptions. However, the challenge remains in making hard choices when the model cannot predict a single probable future for the shrinking river.