Associate Professor of Civil & Environmental Engineering University of Wisconsin - Madison
Recent and ongoing advances in subseasonal-to-seasonal scale predictions of climate and hydrology variables provide prospects for sectoral management, particularly in water quantityfocused areas (e.g., streamflow, reservoir management, agriculture). However, significantly less attention has been devoted to prediction of water quality factors that impact aquatic habitat conditions, affecting fish stress and leading to fish kills. In response, predictions of lake water quality were developed, leveraging global and local hydro-climate features, to predict fish stress and vulnerability. We used direct (summertime fish counts) and indirect (e.g., summertime air and water temperature, dissolved oxygen, and other variables) prediction models, leveraging existing datasets to assess a variety of freshwater metrics to predict fish stress and fish kills. Additionally, climate change datasets were utilized to understand how summertime conditions may evolve and how predictability may change in the future; specifically, whether pre-summer season large-scale climate teleconnections and local hydrologic conditions may become more or less certain. Modeling and predicting changes on subseasonal-to-seasonal time scales can inform actionable resource decisions, and compliment long-term climate change adaptation strategies, specifically early warning management strategies developed by Departments of Natural Resources. Future research may explore the transferability of models and method to lakes exhibiting different characteristics.
