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Data Products and Interpolation

Oak Ridges Moraine Groundwater Program


Delft-FEWS (Flood Early Warning System)

Delft-FEWS is an industry-standard “platform for real time forecasting and water resources management” (Delft-FEWS brochure, 2015). Its strength is that it, as a stand-alone product, can i) fetch forecast data from 3rd party APIs, ii) interpolate data to/from points, grids and shapes, iii) aggregate and re-generate data from their source to any time scale, all with the ability to operate using a GIS-like platform. FEWS is a fully-generalized water data management tool.

In addition, FEWS has the ability to run scripts from command line, which, among other purposes, means that FEWS can even integrate with, say, any hydrological model—by creating input data, running the model (via command), importing the resulting model output and providing alerts should any threshold be met.


The ORMGP-FEWS system operates using version 2019.02.

The “ORMGP-FEWS” system is used to organize data collected from a variety of sources (international, federal, provincial and municipal agencies, academia and private organizations) and consolidates them to a single spatially-distributed, temporally-aggregated data product we offer to our partners and utilized internally.

End Product

In support of our mapping, waterbalance and partners, we maintain two long-term climatological datasets updated nightly: at a daily timescale since 1901, and a 6-hourly dataset since 2001. The data, infilled and distributed at a 10km² resolution across our jurisdiction, include:

  1. Rainfall
  2. Snowfall, snowmelt and snow equivalent (SWE)
  3. Air temperature and pressure
  4. Wind speed and direction
  5. Potential evaporation

The data support a wide variety of web services the ORMGP offers where knowledge of past climactic conditions have a direct causal link to other monitored phenomena. All data sources can be found here.

Data types

The types of time-series data hosted in FEWS are described as such:

  1. Scalar data — These are data most common to environmental databases. They are data collected at stations, and represent phenomena measured at a point. These data require spatial interpolation to convert them to a distributed field.
  2. Vector data — There data come in a distributed (i.e., raster) form, and thus may not require further interpolation. This data format is relatively new given reduced technological constraints and have yet to make significant gains in practice. More and more open international sources offer such data, free of charge. Difficulties with the data are it’s management, as they do not lend themselves well to standard “normalized” database schemas. FEWS, on the other hand, is especially tailored to handle and manipulate vector data.


Example “vector” data: 6-hourly ORMGP-interpolated precipitation (CaPA-RDPA) animated in FEWS