[Runoff] VITCaM: Virtual Inventory Toolkit for Catchment Management

The aim of the VITCaM project is to explore new capability for enhanced decision-making in catchment management using innovative visualisation technologies to exploit existing data in novel ways. Recent advances in high resolution mapping from drones has enabled fine resolution 3D catchment models to be built that represent environmental variables, hydrological pathways and risk sources with much greater clarity and detail than ever before. These rich datasets provide the opportunity to visualise catchments in new and novel ways, and can transform a decision-maker's understanding of the sources of diffuse pollution risk to the wider environment and how different catchment pressures interact. We propose a need to move beyond 2D web-based GIS tools and 3D web visualisation to deliver a step-change in decision-making; we will investigate the potential for Augmented-Reality/ Virtual Reality (AR/VR) immersive decision-making experiences whereby physical and digital objects co-exist and interact in real time to aid exploration of adaptable solutions for better catchment management. We will use a process of participatory co-design (via a workshop format, hosted at Hartree to explore available technologies) and work with relevant stakeholders & end-users (e.g. farm advisor communities, STFC, environmental regulators, water company land management teams, large land owners, NERC, EPSRC, ESRI, Agri-tech centres, CEH, cloud computing providers etc) to ensure relevant knowledge and end-user needs for functionality are integrated into our recommendations for taking forward a new collaborative approach to data visualisation for diffuse pollution management. The vision is to represent complex catchment systems using Building Information Management (BIM) and use immersive visualisation tools to interrogate an inventory of geospatial data layers using AR/VR capability. BIM is the process of designing, constructing and operating a building with the use of electronic object-orientated information, and in our case the 'building' will be a catchment system.

Why is this important?: Open data access is the trend in research, an obligation from many funding agencies and an increasing practice from both governmental agencies and private companies. The paradigm is changing from data collection to data analysis in the era of Big Data. In turn, visualisations of environmental risks (e.g. agricultural runoff and diffuse pollution) provide a new dimension to decision-making for catchment managers by virtually placing the end-user within the landscape or environment of immediate concern. Often, due to logistics and practical barriers, decision-making is undertaken in a location far removed from the site of interest, or by personnel lacking up-to-date knowledge. The use of BIM coupled to AR/VR to visualise how risks are generated from the landscape will help to remove the barriers, but will also provide opportunities for (i) a collaborative decision-making environment; (ii) enhanced communication with stakeholders and communities around catchment issues and (iii) visualisations of 'what-if' scenarios for catchment managers to test in order to guide future decision-making and thus increase resilience to future extreme wet weather events.

There are four main categories of organisations that will benefit from the proposed research:

1. Government agencies with a statutory role to manage the landscape. Examples include the Environment Agency, Natural England, SEPA and Natural Resources Wales.
2. Commercial companies that use water-based ecosystem services but do not own the land. Examples include most water companies.
3. Large landowners who wish to improve their environmental management. Examples include bodies such as the National Trust and the large land estates, such as the Duchy of Lancaster or Duchy of Cornwall.
4. Communities and environmental NGOs (eNGOs): examples include the Rivers Trust and local action groups.

Government agencies have an obligation to improve the water environment to meet the requirements of the The Water Environment Regulations 2017 and to achieve the goals of the 25 Year Plan for the Environment. This environmental improvement needs to be achieved in a cost-effective way to ensure that maximum public goods for public money. Since the required changes to the landscape, such as changes to land use and management, will impact on farm businesses, it is important that they are based on access to and visualisation of solid science and evidence.

Commercial companies who depend upon water provisioning ecosystem services have a key interest in maintaining or improving the water quality. Also, many water companies are looking to offset waste water treatment costs by investing the catchment to improve the upstream water quality. For these actions to be cost effective, they need to be robustly spatially targeted. This research will provide the framework to explore new methods required to ensure that the investments in catchment-based approaches are effective and that their associated uncertainties are understood.

Many large landowners are recognising the role that land management has on the wider environment and are looking to change the land management to reduce their impact. A good example of this is the RiverLands project by the National Trust. This project is working to improve water quality and reduce flooding in a set of catchments. They need to balance the range of ecosystem services that they gain from the land, including the cultural services, to ensure that they are able to deliver a range of services that their membership requires. This proposed research project will provide an innovative framework for bodies, like the National Trust, to consider where in the landscape to change how they are managing the land using scenario-based visualisation approaches.

Many communities and eNGO groups are working to improve the water quality and runoff within catchments. Due to their size and funding, they often have limited resources to engage with landowners and to undertake mitigation projects. Therefore, they need high confidence in the predictions of the key areas for flood and water quality sources in the catchment to effectively target their resources. These groups need tools that are cost effective and applicable by their teams. The proposed research will provide an improved method to make these spatial targeting decisions and hence enable them to achieve their environmental management aims.