WATER RESOURCES TOOLS

Hosted Research & Decision-Support Tools

Specialized computational tools for machine learning-based streamflow predictions, irrigation planning, evapotranspiration analysis, and crop simulation — built for Alberta workflows and powered by real Environment Canada weather data.

Note: while we strive for accuracy and reliability, these tools are under development and should be used with professional judgement and independent verification where appropriate. Contact us with comments or questions, or if interested in collaboration.

AqualET - ET & Irrigation Decision Tool icon

AqualET - ET & Irrigation Decision Tool

Live

A web-based evapotranspiration (ET) analysis and irrigation guidance tool designed for Alberta, BC, Saskatchewan, and Manitoba agricultural workflows. AqualET calculates crop water demand using multiple ET methods, including AquaCrop-based crop simulation, and provides forecast-based irrigation recommendations powered by real-time weather data.

water_drop

ET Calculators: Priestley-Taylor, Penman-Monteith, Hargreaves-Samani, and Maule methods

agriculture

AquaCrop crop simulation with single-year, historical range, and forecast input modes, featuring weekly result summaries and charts

cloud

Forecast-based irrigation recommendations and ET flux (W/m²) output using real-time weather data

history

Historical yield and ET prediction using AquaCrop across custom date ranges or multi-year periods

EvapotranspirationIrrigation PlanningAquaCropWestern Canada
Oldman Dam Streamflow Forecasting icon

Oldman Dam Streamflow Forecasting

Live

A web-based daily streamflow forecasting and visualization platform designed for the Oldman Dam in Alberta, Canada. The system integrates machine learning models with real-time hydrometeorological data to provide reliable 1–5 day ahead streamflow forecasts for reservoir management and water resources planning.

sensors

Real-time streamflow, weather, and inflow data integration from Environment Canada and Alberta Rivers sources

analytics

Machine learning forecasting using SVR, ANN, XGBoost, and LSTM models

bar_chart

Interactive forecast visualization, historical prediction analysis, and automated missing-data handling

Streamflow ForecastingMachine LearningHydrologyAlbertaReservoir Operations