Joel Trubilowicz is a hydrologist and engineer with 11 years of experience applying regional-scale hydrologic modeling, GIS, and remote sensing to floodplain mapping, hydrologic prediction, and transboundary water issues. Currently at Environment and Climate Change Canada’s Water Survey of Canada, he blends operational forecasting needs with research-grade uncertainty assessment developed during PhD work on freshwater inputs to the Gulf of Alaska. He has a strong track record of building open-source tools and automated pipelines—Python-based systems for assimilating MODIS snowcover into operational forecasts and real-time hydrometric QA/visualization consoles. Joel’s background spans academia, consulting, and utilities (BC Hydro, UBC, Northwest Hydraulic Consultants), giving him practical skill translating complex earth-science data into decision-ready products. He pairs statistical and machine-learning approaches to classify watershed regimes with hands-on experience in hydrometric network data management. Notably, he has merged remote sensing, Bayesian methods, and custom modeling to improve forecasting during rain-on-snow and climate-driven regime shifts.
11 years of coding experience
10 years of employment as a software developer
Bachelor of Science (B.Sc.), Environmental Engineering, Magna Cum Laude, Bachelor of Science (B.Sc.), Environmental Engineering, Magna Cum Laude at Michigan Technological University
Doctor of Philosophy (PhD), Physical Geography (Hydrology), Doctor of Philosophy (PhD), Physical Geography (Hydrology) at The University of British Columbia
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