Ontario Lake Digital Twin

Predictive Limnology & Eco-System Intelligence

An engineering-grade digital twin of Ontario's freshwater basins. Simulates nutrient runoff cascade, thermocline stratification, and chemical saturation indexes to manage lake metabolic stability and predict algae bloom risks.

Sensors ActiveModel v5.0Centauri Research

Modelled Lakes

12waterbodies

Ontario regional basins

Active Telemetry Nodes

42sensors

↑ Real-time field links

Dissolved O2 Target

11.2mg/L

Safe oxygen boundary

Bloom Risk Level

Lowstatus

Stochastic model secure

Platform

Analysis Modules

Methodology

Modelling Approach

Nutrient Runoff Cascade

Simulates forest sponge interception (Ia = 15mm) and landcover runoff metrics (Q = Σ Ci I Ai) to map nutrient loads delivered to basins during high-rainfall weather events.

Thermodynamics of Calcium-P

Calculates the Saturation Index (SI = log10(IAP / Ksp)) of calcium phosphate precipitation to assess the bio-availability of total phosphorus (TP) for algae consumption.

Stochastic Risk Forecasts

Executes a 1,000-trial Monte Carlo simulation to vary inputs (±10%) under weather extremes, estimating the statistical probability of Trophic State transitions and harmful blooms.

Data Sources

Primary Data

SourceScope
Ontario GeoHub Bathymetry PointRaw X, Y, Z depth markers for 3D benthic grids
Lakes Canada Volunteer NetworkCitizen science water temperature and Secchi disk depth readings
Sentinel-2 STAC Querying APIHyperspectral remote sensing chlorophyll indexes (NDCI)
MSC GeoMet OGC API v3Real-time weather station metrics and forecasted rainfall events
Dorset Environmental Science CentreBaseline nutrient datasets and chemical constants