Understand catchment behaviour with transparent data, calibrated forecasts, and a clear delivery path.
This landing page introduces the platform’s workflow: from the source data used to build a forecast, to the model behind each prediction, and the commercial and legal context around usage.
Used data
The platform combines a range of hydrological and geospatial inputs to support calibration and forecasting in a practical, transparent way.
- Digital elevation models for watershed delineation and catchment boundaries.
- Hydrometeorological inputs such as precipitation, temperature and potential evapotranspiration.
- CrowdWater observations and calibration points where available.
- Catchment metadata such as area, location and timezone context.
Data quality notes
Forecast quality depends on the completeness and consistency of the input sources. Missing observations are transparently handled through fallback logic and provenance tracking.
- Calibration can run with observed or proxy-based series.
- Users can inspect model outputs and supporting evidence.
- Data layers are prepared to support both local testing and production workflows.
Model
The forecasting engine is built around a hydrological rainfall-runoff model that is calibrated for each catchment and then used to produce forecast runs.
- Calibration objectives include NSE, RMSE, KGE and bias-based criteria.
- Outputs include discharge estimates, uncertainty bands and alert-ready summaries.
- The workflow supports both Python and R-backed execution paths for comparison.
What the model helps with
It supports day-to-day decision making for water management by translating observed and forecasted conditions into actionable hydrological insight.
- Catchment-level forecasting for operational use.
- Scenario evaluation through calibration and multiple parameter sets.
- Comparison views for model diagnostics and benchmark evaluation.
Pricing
Placeholder pricing structure for planning and early onboarding.
For pilots and local testing with limited catchments.
For operational monitoring, richer calibration and shared access.
For large deployments, custom integrations and advanced support.
Support and onboarding
Contact the team for tailored onboarding, deployment support and configuration guidance for your monitoring context.
- Implementation support for new catchments.
- Assistance with model tuning and forecasting workflows.
- Custom deployment guidance for production environments.
Terms & conditions
This section is a placeholder for the final legal and usage documentation. It should be reviewed and adapted before any public rollout.
- Use of the platform is subject to the agreed data handling and access policies.
- Forecast outputs are informational and should be interpreted alongside domain expertise.
- Users remain responsible for complying with local data protection and operational requirements.