- 31st May 2018
- Posted by: Sophie Bunker
- Category: Blog
Following our involvement with the Working with Natural Processes (WwNP) Evidence Directory, and the production of the national WwNP Potential maps, we are working with the Environment Agency on a Natural Flood Management (NFM) modelling project across Yorkshire.
Extending beyond a traditional fluvial flooding and modelling project, the study incorporates NFM and wider knowledge transfer. Through site visits and workshops, Environment Agency staff and wider project stakeholders will be directly involved in the modelling process to increase their confidence to deliver NFM projects on the ground. This project is therefore implementing and expanding on the national WwNP Evidence Directory.
- Learn about the WwNP Evidence Directory, and how to use the evidence base
- Understand and help evolve the NFM modelling methodology
- Incorporate their own learning outcomes
- Incorporate their own local knowledge and provide links to other studies
- Appreciate how NFM modelling differs from the well-defined fluvial modelling approach
- Shape the NFM modelling process for each case study site so that it focusses on areas and scenarios of interest, and ensure it aligns with their expectations.
Throughout the last month we have facilitated the first set of workshops and have more scheduled as the modelling process progresses. We have also led site visits to investigate flood risk (and wider catchment) issues, and explore the wider landscape.
Throughout the works we will utilise GISmapp and JFlow®. The GISmapp app has been used to collect georeferenced photographs and notes whilst out on site. Important for this NFM project, GISmapp has allowed us to explore and characterise the wider landscape where datasets are often scarce and outputs have also been easily shared with the client and site visit attendees.
JFlow® enables us to model a baseline scenario for each case study site. The model is being edited to include potential NFM measures, and outputs will be used to quantify and assess the benefits of different NFM scenarios.