Shengde Yu

I am Shengde Yu, an environmental data scientist and water-quality modeler specializing in global lake and reservoir systems, ecohydrology, and scalable environmental modeling. My research combines process-based models, large-scale environmental data pipelines, geospatial analysis, and machine learning to understand how reservoirs and water-management systems respond to climate change, dam operation, nutrient loading, and hydrological variability.

A central part of my work is developing reproducible modeling frameworks and data products that connect global waterbody datasets with practical water-quality modeling. These include the GlobalReservoirModel series and high-resolution depth–area–volume relationships for large-scale lake and reservoir applications. My work supports research on reservoir thermal stratification, nutrient cycling, phosphorus retention, hydrodynamic controls on biogeochemistry, and climate-sensitive water-quality assessment.

More broadly, I am interested in building transparent and transferable modeling workflows that help researchers and practitioners assess reservoir responses to environmental change and support decision-making in water-resources management.

Advisory Committee

Supervisor: Prof. Philippe Van Cappellen, University of Waterloo
Committee members: Prof. Nandita Basu, Prof. Andrea Brookfield, Dr. Chris Parsons, and Prof. Helen Jarvie