Catchment Management Modelling Platform

Case Study 7

Interpolation of model outputs and data from catchment to national scales and monitored to non-monitored sites

Participants

Jack Cosby1; Bridget Emmett1; Amy Thomas1.

1Centre for Ecology and Hydrology, Bangor;

Stakeholder Representatives

Murray Hart, Defra; Nick Paling, Rivers Trust.

Forum issues addressed by case study

How can I know if land management will be effective?

  • Can I transfer these measures or approaches to other catchments? Will they be less or more effective?
  • Can I transfer conclusions on how well land management works from the catchment to the national scale?
What did we find?

This case study uses a Dynamic Typology Tool (DTT) to combine spatially explicit datasets describing landscape character and management and identify homologous areas of agricultural potential, natural environment quality and risk.  The DTT provides national coverage and local output suitable for stakeholder engagement in study areas. Application of the tool can aid identification, targeting and prioritisation of land-use opportunities for management of water quality.

How did we do it? (Synopsis)

Results Available Soon.

How did we do it? (Full)

Results Available Soon.

What did this case study show? (Synopsis)

Results Available Soon.

What did this case study show? (Full)

Results Available Soon.

What were the benefits of using more than one model?

Results Available Soon.

What were the lessons learned about how to apply the models?

Results Available Soon.

What pre- and post-processing was done on the input and output data?

Results Available Soon.

W​hat datasets were used in the case study?

Results Available Soon.

Videos
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Project view
Stakeholder view
Location

Conwy Catchment, North Wales and England

Issues
  • Transferability
Pollutants
  • Water Quality
Scale
  • National
 Models
  • DTT
CaMMP

Improved access to and integration among data and models to address key questions in catchment management for water quality and wider ecosystem services, providing a more holistic view to inform scientific understanding and policy development.

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