Research

This work develops and applies hydrologic models for urban stormwater management, flood analysis, and climate adaptation. Recent emphasis has been on how model inputs, scale, and sparse observations affect the reliability of flow predictions, and on how modelling workflows can be made faster and more reproducible.

• Hydrologic modelling: Use of PCSWMM, SWMM, and related tools for urban drainage analysis
• Spatial uncertainty: Fuzzy-entropy approaches for watershed-scale uncertainty in flowrate and runoff modelling
• Infiltration model-form uncertainty: Entropy-based methods for comparing how infiltration formulations affect prediction
• Reproducible workflows: Agentic and scripted pipelines for rapid stormwater modelling

Key applications:

• Low Impact Development (LID) performance assessment
• Urban flood forecasting and peak-flow prediction
• Climate scenario analysis for infrastructure planning
• Model comparison under uncertain or incomplete inputs

This area focuses on the design, monitoring, and evaluation of green infrastructure for stormwater management in cold climates, with recent work linking LID performance to climate adaptation, runoff control, and treatment design.

• Permeable pavement systems: Long-term hydraulic performance, clogging mechanisms, and maintenance needs
• Bioretention cells and rain gardens: Water quality treatment, media-plant interactions, nutrient dynamics, and amendments
• Rainwater tree trenches (RTTs): Integration of urban forestry, stormwater management, and urban heat mitigation
• Porous asphalt and treatment media: Heavy metal removal and cyclic wetting-drying performance

Research focus:

• Performance metrics for Canadian climate zones
• LID performance under changing rainfall and temperature conditions
• Scale effects in LID implementation and drainage response
• Design guidance for cold-climate applications

This research examines pollutant fate and transport in urban water systems, with recent emphasis on treatment processes inside green infrastructure and stormwater media:

• Heavy metal removal: Performance of porous asphalt, oyster shell media, and bioretention media for lead, zinc, copper, and cadmium
• Nutrient dynamics: Phosphorus and nitrogen leaching, retention, and treatment behaviour in amended and non-amended bioretention systems
• Vegetation and media interactions: How plants, roots, senescence, and media influence treatment performance
• Microbial water quality: Bacterial occurrence, sources, and virulence potential in stormwater systems and ponds

Collaborative projects:

• Treatment studies for permeable and bioretentive stormwater systems
• Integration of water quality sensing into green infrastructure monitoring
• Microbial and nutrient studies in urban stormwater systems

This work explores how data-driven methods can support water resources engineering, especially when available observations are sparse or uncertain:

• Predictive modelling: Data-driven approaches for rainfall-runoff prediction and flood forecasting
• Pattern recognition: Analysis of sensor data from LID installations and treatment systems
• LLM comparison studies: Recent work comparing fuzzy-based hydrologic methods with ChatGPT outputs for peak-flow prediction
• Agentic modelling pipelines: Workflow automation for reproducible rapid stormwater modelling
• Digital twins: Integration of data-driven models with real-time monitoring

Current directions:

• Large language models for technical synthesis and model comparison
• Workflow automation for stormwater analysis and scenario generation
• Learning-based tools for real-time control of urban drainage systems

This area covers the development and deployment of sensor systems for urban water research, including recent work on vegetation, tree, and biomass monitoring in green infrastructure:

• Custom velocity meters: Low-cost flow measurement devices for shallow urban runoff and open-water applications
• Multi-parameter monitoring: Integration of water level, flow velocity, temperature, and water quality sensors
• Biomass monitoring: Optical, impedance, and electrochemical sensing approaches for vegetated green infrastructure
• Tree and canopy studies: Monitoring approaches relevant to structural soils, energy-water balance, and urban heat mitigation
• Data management pipelines: Automated data collection, quality control, and visualization platforms

Technical areas:

• Open-source hardware designs for hydrological monitoring
• Wireless sensor networks for distributed monitoring
• Integration with IoT platforms for real-time data access
• Power management solutions for remote field sites