High-tech Limnology

Can we use new technologies and knowledge-guided machine learning to better monitor, model, and manage lakes?

 

We are investing in the development and application of environmental sensors to understand and manage lakes and rivers. We build and deploy sensors on lakes (buoys) to provide continuous real-time monitoring of lake water quality. We’ve also developed the Fast Limnological Automated Measurements (FLAMe) platform which measures spatial patterns of water quality. With this vast amounts of data comes the need to manage and analyze the data. The CFL leads the Environmental Data Initiative (EDI) – a leading ecological data repository comprised of tens of thousands of datasets. In addition, CFL researchers are collaborating with computer scientists and pioneering the application of knowledge-guided machine learning (KGML) in aquatic ecology. High-tech limnology is revolutionizing how we study and manage lakes. See also LAGOS open-access research platform and Global Lake Ecological Observatory Network (GLEON).

Recent publications:

Buelo, C., M.E. Pace, S.R. Carpenter, E.H. Stanley, D. Ortiz, and D. Ha. 2022. Evaluating the performance of temporal and spatial early warning statistics of algal blooms. Ecological Applications 32:e2616. DOI

Gries C.P.C. HansonM. O’BrienM. ServillaK. VanderbiltR. Waide. 2023. The Environmental Data Initiative: Connecting the past to the future through data reuse. Ecology and Evolution. Vol 3, Issue 1. DOI

Hanson, P., A.B. Stillman, X. Jia, A. Karpatne, H. Dugan, C.C. Carey, J. Stachelek, N.K. Ward, Y. Zhang, J.S. Read, V. Kumar. 2020. Predicting lake surface water phosphorus dynamics using process-guided machine learning. Ecological Modelling. Volume 430, 15. DOI

Read J.S.X. JiaJ. WillardA.P. ApplingJ.A. ZwartS.K. OliverA. KarpatneG. J. A. HansenP.C. HansonW. WatkinsM. SteinbachV.  Kumar. 2019. Process-Guided Deep Learning Predictions of Lake Water Temperature. Advancing Earth and Space Sciences. DOI

 

High-tech Limnology Researchers

Hilary Dugan

Position title: Associate Professor

Website

Paul Hanson

Paul Hanson

Position title: Research Professor

Noah Lottig

Position title: Research Scientist

Website

Emily Stanley

Emily Stanley

Position title: Professor

Website