In a paper published in the journal Chemical Geology, Wenkai Qiu and co-authors present new geochemical data on porewaters extracted from unconsolidated argillaceous sediments collected in the Jianghan Plain, central China.
Ecohydrology Research Group MSc student Christina Lam successfully defended her thesis on April 29, 2025 in a virtual defence.
The week of 27 April–2 May 2025, Ecohydrology Research Group members will present their research at the 2025 European Geosciences Union (EGU) Conference.
The second annual meeting of the “Adaptive management of green stormwater infrastructure to reduce greenhouse gas emissions from urban watersheds” project was held on Wednesday April 16, 2025, at the University of Waterloo. The aim of the annual meeting was to review the progress of the work completed over the last year, and exchange ideas about further integration among the different work packages, while deepening collaborations with the external partners.
Philippe and Shengde participated in the 5th International Symposium on Surface Earth System Science, held by Tianjin University from April 10–13, 2025.
ERG member Jovana Radosavljevic recently returned from a month-long academic visit to the China University of Geosciences (CUG) in Wuhan.
This afternoon, Philippe presented a talk entitled "Putting microbes in reactive transport modeling - Some of the things I learned over the years" as part of the Ecohydrology Seminar Series. Thank you to Philippe for the excellent talk! We all had a great time.
Philippe participated in the São Paulo International Groundwater Week, which took place from March 19-22, 2025, in Buaru, São Paulo State, Brazil.
A new paper entitled “Functionalized Microwave Biosensor for Rapid, Reagent-Free Detection of E. coli in Water Samples” was published in the journal Biosensors and Bioelectronics. It is the result of a collaboration between researchers at the University of Waterloo.
In a recent article in Scientific Reports, Amir Reshadi and coauthors present a machine learning model for the prediction of microplastic (MP) concentration in urban stormwater using an original dataset with a broad array of environmental and socioeconomic variables.