As part of the Water Institute's WaterTalks lecture series, Dr. Cayelan Carey, Professor of Biological Sciences, Virginia Tech, will present: Advancing our understanding and management of freshwaters with near-term forecasting.
This event is in person in DC 1302 with a lunch reception to follow in DC 1301 (The Fishbowl).
More Information
Water quality in lakes and reservoirs around the globe is increasingly variable due to human activities, preventing managers from using historical baselines to predict tomorrow’s conditions. In response, our team is developing near-term, iterative water quality forecasts in which we predict future water quality conditions with fully-quantified uncertainty. We have created an open-source forecasting system that wirelessly transfers water quality sensor data to the cloud to run ensemble models via automated cyberinfrastructure, delivering daily, real-time forecasts of water quality conditions 1 to 35 days in the future to managers. To date, we have deployed this system in 12 lakes globally, enabling managers to anticipate and preemptively mitigate water quality impairment before it starts. Moreover, we can use forecasting to begin to identify the drivers of freshwater predictability among waterbodies. For example, we observed significant positive relationships between the accuracy of water temperature forecasts and lake characteristics (e.g., water clarity, depth), expanding our understanding on the controls of lake ecosystem functioning. Our team seeks to galvanize the freshwater research community to join the forecasting effort by creating easy-to-use teaching modules through the Macrosystems EDDIE program and leading initiatives such as the U.S. National Ecological Observatory Network (NEON) Ecological Forecasting Challenge. Together, we aim to lower the barrier to forecasting, engage a broad and diverse community of forecast developers and users, and use forecasts to improve our management of freshwater ecosystems in a changing world.
Speaker Bio