Local Community Tools

EVO is being developed to meet the needs of a wide range of potential users. At the local community scale we are focussing on the Eden, Tarland and Dyfi Catchments, where a number of tools for visualising and analysing environmental data are being developed to allow people to find out about the environment in their local area.

Users can access environmental data from a range of sources and the tools within the EVO portal will support the visualisation, analysis and interpretation of the data outputs. The portal has been designed with extensive help facilities and guides to allow non-experts to learn about the different kinds of analysis options open to them and how to interpret the results. An overview of some of the tools available is provided below. To find out about environmental data in your area, access the EVOp portal.

Visualising live data
The use of new technologies in environmental sensors is allowing researchers to measure environmental variables at increasingly higher frequencies using automatic monitoring systems. These systems provide a stream of data which can be sent via a telemetered link and viewed in near to real time. The types of data currently available to view in this way are:

  • River level data
  • Rainfall data
  • Weather data
  • Webcam images of river conditions
  • Water quality information

Some examples of the live data available in the catchments can be found at:

Modelling
Models are used to process data, identify patterns and help to predict how the environment might respond under specified conditions or management scenarios. These responses can then be used to inform the decisions we make. Using the EVO portal, it will be possible for users to run models and explore their predictions. Currently, the following models are available:

  • Using a simple rainfall-runoff model called TOPMODEL, it is possible to examine how different land uses or land management strategies might alter flood risk, whilst also considering the uncertainties associated with the model predictions.