NERC is supporting a range of funded research projects under the Constructing a Digital Environment programme. There are two ‘waves’ of Feasibility projects, and ‘Digital Environment Demonstrator’ projects, seeking to bring together the ‘Digital Environment’ community through multi-disciplinary and interdisciplinary research and innovation to deliver increased benefit from existing and new sensor networks technology and their associated infrastructure. The funded projects are exploring the methodologies and tools for assessing, analysing, monitoring and forecasting the state of the natural environment at higher spatial and temporal resolutions than previous possible. The funded projects are listed below:
Feasibility Wave One Projects- HUGS: a Hub for UK Greenhouse gas data Science
- Engineering Transformation for the Integration of Sensor Networks: A Feasibility Study – ‘ENTRAIN’
- Digital Environment: Dynamic Ground Motion Map of the UK
Feasibility Wave Two Projects
- MOSAIC Digital Environment Feasibility Study
- Underwater large-area high resolution monitoring by Distributed Optical Fibre Acoustic Sensors
- A digital environment for water resources
- Landslide Mitigation Informatics (LIMIT): Effective decision-making for complex landslide geohazards
- Sounding out the river: a new system for monitoring bedload mobilisation and transport
- Methodologically Enhanced Virtual Labs for Early Warning of Significant or Catastrophic Change in Ecosystems: Changepoints for a Changing Planet
Digital Environment Demonstrator Projects
- PYRAMID: Platform for dYnamic, hyper-resolution, near-real time flood Risk AssessMent Integrating repurposed and novel Data sources
- DECIDE: Delivering Enhanced Biodiversity Information with Adaptive Citizen Science and Intelligent Digital Engagements
- Sentinel Treescapes for Plant Biosecurity and Risk Management – Multiple Threats
- OpenGHG: A community platform for greenhouse gas data science
- Coastal REsistance: Alerts and Monitoring Technologies (CreamT)
- SENSUM: Smart SENSing of landscapes Undergoing hazardous hydrogeological Movement
- Dynamic monitoring, reporting and verification for implementing negative emission strategies in managed ecosystems (RETINA)
Digital Environment Mini Demonstrator Projects
- Nature Positive Acoustics
- Integrating a biodiversity digital twin with a FAIR data pipeline for reproducible science
- A NERC data service for integrating NERC sensor networks
- Unlocking the potential of Sensor for our Environment: a co-creation and writing retreat
- Sustaining Environmental Data Discovery
- From photons to fish, from seconds to centuries; Generating FAIR data from high resolution sensors in the Western Channel Observatory
- The Art-Science interface: Working with artists to explore the digital environment
Feasibility Wave One projects
The projects below were supported as Feasibility Wave One.
Top of page
HUGS: a Hub for Uk Greenhouse gas data Science
Note the HUGS project here is the predecessor of the OpenGHG: A community platform for greenhouse gas data science project described below.
Abstract: Atmospheric observations of greenhouse gas (GHG) concentrations can be used to estimate emissions when combined with models of atmospheric transport and an understanding of the emission sources surrounding the observations. These top-down methods are complementary to the bottom-up, accounting-based, approaches that are currently used to create national GHG inventories. To improve the transparency and accuracy of these inventories and better evaluate progress on emissions reduction policies, scientists and policy makers have been advocating for the integration of top-down methods into the emissions reporting process. The United Nations Framework Convention on Climate Change (UNFCCC) recently acknowledged the important role that emissions quantified through atmospheric observations could have in supporting inventory evaluation (UNFCCC, COP 23, SBSTA/2017/L.21). The UK GHG science community is leading the world in this regard, with a dedicated national monitoring network, a range of regional networks and regular over-passes by various satellites. Currently, the UK is one of only three countries on Earth to include top-down estimates in its National Inventory Report to the UNFCCC. The process of inferring emissions from GHG observations is extremely data intensive. In order to understand the observed variability in GHG concentrations, scientists must combine data from diverse networks in different environments and using different instrumentation, understand the distribution of potential sources and land use types in the vicinity of the sensor and be able to accurately model the atmospheric processes that transport GHGs from sources to the measurement site. Therefore, to date, analysis of GHG data is largely carried out on a case-by-case basis for individual research papers. Here, we propose that new developments in cloud computing are required to help GHG scientists overcome some of the major obstacles for the integration of GHG networks and the production of operational, higher resolution GHG flux estimates. We will create the cloud-based framework for a UK GHG data science “hub”. This hub will allow users (GHG scientists and, eventually, the public) to: – Improve the flow of information to and from GHG data providers, because cloud services are not behind institutional firewalls – Operationalise the processing of datasets into common formats, which can then be made globally accessible to users (subject to any required usage restrictions) – Automatically trigger operations on new data, such as the running of chemical transport models, which are essential for the interpretation of GHG data – Analyse data, model output and ancillary information (maps of land use, emissions inventories, etc.) on the cloud, without the need for individual users to download datasets and run models (requiring technical expertise) – Visualise data, models and other relevant information on a web-based platform Our team is world leading in the measurement and analysis of GHGs, cloud computing and spatial mapping. This project will rely heavily on a cloud platform (built as part of the EPSRC-funded BioSimSpace project) and GHG analysis codebase that has already been developed by team members. These tools are built on top of standard tools such as Jupyter notebooks, distributed object stores, and serverless functions. It is this expertise and these open tools that will allow us to develop the framework for our data science hub that will be extensible by GHG researchers at the end of this project. We envisage that such a hub could be at the centre of the UK’s large and growing GHG science community, allowing scientists to upload, analyse and visualise their data on a single platform, enhancing data integration and sharing between groups. Ultimately, this platform could be extended to allow the public to interact with GHG data, letting them learn whether the UK’s emissions reductions efforts are reflected in atmospheric observations.
| Principal Investigator: Dr M Rigby, University of Bristol, Chemistry |
| Co-Investigator: Professor SJ O’Doherty, University of Bristol, Chemistry |
| Co-Investigator: Dr CJ Woods, University of Bristol, Chemistry |
| Co-Investigator: Dr A Ganesan, University of Bristol, Geographical Sciences |
| Co-Investigator: Professor NRP Harris, Cranfield University, School of Water, Energy and Environment |
| Held at: University of Bristol, Chemistry |
| NERC Reference: NE/S016155/1 |
| Period of Award: 4 Feb 2019 – 3 Feb 2020 |
| Value: £214,452 |
Engineering Transformation for the Integration of Sensor Networks: A Feasibility Study – ‘ENTRAIN’
Abstract: There is a need to make use of new digital data analysis techniques to improve our understanding of the environment. Data from a new generation of environmental sensors, combined with analyses based on Artificial Intelligence, has the potential to help us understand from human influences and long-term change are affecting the environment around us. Artificial Intelligence approaches enable computers to identify trends and relationships across different streams of data, often picking out patterns that would be too difficult or time-consuming for humans to identify manually. To realise these benefits, data from diverse sensor networks must combined and analysed together. Currently many sensor networks are operated individually, and data are not readily combined due to differences in the way measurements are made (e.g. between weekly river samples and sub-second measurements of gases in the atmosphere). In addition, to combine these data in an automatic way without human intervention requires much finer and more consistent descriptions of the contents of data streams, so that machines can understand the content sufficiently. Links between sensors in space are also important, and machines will need an understanding of these links, not just in the sense of coordinates, but for example how sensors are linked along rivers. We can construct a digital representation of rivers in order to enable this. We will describe the various elements of a future environmental analysis system that will be required in order to achieve these benefits, and addressing some of these currently missing components. We will look at technologies, from databases to data transfer mechanisms, to understand how a system could be built. We will use data from 3 NERC sensor networks measuring environmental variables from the atmosphere to river water quality, and show how this data can be automatically integrated in such a way that machines would be able to analyse it automatically. A significant issue when monitoring with high-resolution sensors is how to handle problems in the data, which could include missing data, and erroneous values due to sensor failure. There is too much data for humans to manually view and check, and so automated approaches are needed. Currently these are often simple checks of individual data values against expected ranges, but again there are opportunities for artificial intelligence to improve this. AI approaches can look across multiple sensors, identify relationships, and find subtle changes in data signals, and this can be used to both identify data problems and to fix them through infilling. We will enhance the 3 NERC networks by testing and applying such approaches to data quality control. We will investigate some fundamental limitations of high-resolution monitoring, the transfer of large amounts of data from the field site to the data centre, the security of such systems, and whether more processing could be done on the instruments themselves to reduce data transfer volumes. We will meet with the public, with policy-makers, with industry and with researchers to discuss where there will be most to be gained from development of AI approaches to analysing environmental sensor data. We will develop ideas for future work to realise these gains, and will promote the benefits of an integrated system for environmental monitoring. These stakeholders are likely to include the Environment Agency, SEPA, Natural Resources Wales, Defra, Water companies, sensor network developers, and public organisations with an interest in the environment, including the National Trust, the Rivers Trusts, and local community groups.
| Principal Investigator: Mr MJ Fry, NERC Centre for Ecology and Hydrology, Water Resources (Wallingford) |
| Co-Investigator: Dr SJ Cole, NERC Centre for Ecology and Hydrology, Hydro-climate Risks |
| Co-Investigator: Dr JG Evans, NERC Centre for Ecology and Hydrology, NERC CEH – Wallingford |
| Co-Investigator: Dr M Bowes, NERC Centre for Ecology and Hydrology, Water Resources (Wallingford) |
| Held at: NERC Centre for Ecology and Hydrology, Water Resources (Wallingford) |
| NERC Reference: NE/S016244/1 |
| Period of Award: 1 Apr 2019 – 30 Jun 2020 |
| Value: £251,614 |
Digital Environment: Dynamic Ground Motion Map of the UK
Abstract: The ground surface in the UK is far from stable. For example, there are more that 15,000 recorded landslides in the UK, and the average annual cost of ground movement to the insurance industry is £250M. Landslides affecting critical infrastructure, such as mainline railways or dams, can be associated with multi-million pound remediation costs even for a single slope failure event. Furthermore, there are tens of thousands of kilometres of engineered slopes in our transportation, utilities and flood defence infrastructure networks – many of which were built in Victorian times and are in poor condition. Satellite technology, specifically ESA’s Sentinel-1 constellation, has the potential to produce a dynamic, high resolution map of ground motion which can be used for monitoring and planning. The proposed feasibility study will explore whether UK expertise can be used to integrate Sentinel-1 data with sensors on the ground and embedded in the built environment to contribute to the Digital Environment. The study will leverage existing RCUK investments, map the requirements of potential stakeholders and explore cutting edge approaches to data handling, analysis, fusion and decision making. In addition to the core of InSAR experts, our team comprises a) specialists in image processing and machine learning, b) specialists in landslides, subsidence and onshore energy production and c) two knowledge exchange fellows. A wide-ranging network of potential stakeholders has already been identified, and our selected project partners (Environment Agency, Network Rail, TerraDat, Bridgeway Consulting) represent the needs of key governmental and commercial beneficiaries. The output of the feasibility study will be a peer-reviewed white paper detailing the requirements for a Sentinel-1 based UK ground motion map to be incorporated into a Digital Environment.
| Principal Investigator: Professor J Biggs, University of Bristol, Earth Sciences |
| Co-Investigator: Professor M Kendall, University of Bristol, Earth Sciences |
| Co-Investigator: Professor J Wookey, University of Bristol, Earth Sciences |
| Co-Investigator: Professor D Bull, University of Bristol, Electrical and Electronic Engineering |
| Co-Investigator: Dr JP Verdon, University of Bristol, Earth Sciences |
| Held at: University of Bristol, Earth Sciences |
| NERC Reference: NE/S016104/1 |
| Period of Award: 4 Feb 2019 – 3 Feb 2020 |
| Value: £170,405 |
Feasibility Wave Two projects
The projects below were supported as Feasibility Wave Two.
Top of pageMOSAIC Digital Environment Feasibility Study
Abstract: There is growing awareness of the hazards arising from space weather which are now listed on the UK National Risk Register (Cabinet Office, 2018). One significant risk is created by ‘hard’ solar particle events containing a significant flux of highly energetic particles which can lead to corruption and damage in modern microelectronic technology at ground level. In general such solar events are detectable at the earth’s surface by ground level neutron monitors and are termed ground level enhancements (GLEs): they typically have durations of some hours and the most intense ever measured was in February 1956 in the UK. Prior to the 1940s however we have only indirect measurements of GLEs from ice cores and tree rings (Miyake et al, 2012; Mekhaldi et al, 2015). Results on 10Be, 36Cl and 14C show events some 30 times larger than February 1956 in AD774 and 15 times larger in AD994. In today’s technological society GLEs present a hazard to complex systems, such as autonomous vehicles, railways, nuclear power stations and especially aircraft (including unmanned aerial platforms) which are by far the most exposed. At present the UK has no ground level neutron measurement capability as this was abandoned in the 1980s. The main objective of the Moisture Sensors for Atmospheric Ionising Collaboration (MOSAIC) project is to study dual-purposing the UK COSMOS soil moisture sensor network to provide an unprecedented, high-density, sustainable and cost-effective UK space weather measurement capability to provide real-time alerts for critical infrastructure as well as enabling new environmental science. COSMOS is a relatively new and expanding network of sensors and there are now nearly 50 detectors across the UK operated by the NERC Centre for Ecology and Hydrology (CEH). Neutrons generated by cosmic-rays high in the atmosphere can reach ground level, some of which will be reflected dependent on the soil moisture content: COSMOS stations measure the reflected neutrons to determine average soil moisture over the local area. Besides studying the prospect of operational warnings for infrastructure (including aviation) there is an opportunity to create a long term record of ground level neutron radiation in the UK which can be the basis of better environmental models and improved risk assessments for government. The study examine COSMOS sensitivity to GLEs along with the digital network feasibility issues which would arise when dual-purposing the network. An initial priority is to examine the practicality of significantly higher temporal resolution which will be needed for MOSAIC given that GLE rise times can be of the order of minutes. We will examine the feasibility of achieving very rapid communication of data from the sensors to the centre(s) where decisions are taken on the need to issue alerts and how long this might take. It is likely that the geographical diversity and distributed nature of the COSMOS digital network could offer significant benefits for robustness via the inherent redundancy compared to conventional ‘single point’ monitors. To assist this work the Met Office will act as the primary ‘user’ of the system and will advise on their data distribution and processing requirements and we will investigate how artificial intelligence can better distinguish the wanted signal and enhance decision accuracy. We will also investigate how MOSAIC can be integrated with the Surrey Smartphone Atmospheric Ionising RAdiation network or SAIRA which has already demonstrated a citizen science approach to obtain complementary radiation data from aircraft.
| Principal Investigator: Dr K Ryden, University of Surrey, Surrey Space Centre Academic |
| Co-Investigator: Dr A Hands, University of Surrey, Surrey Space Centre Academic |
| Held at: University of Surrey, Surrey Space Centre Academic |
| NERC Reference: NE/T005734/1 |
| Period of Award: 15 Nov 2019 – 14 Nov 2020 |
| Value: £134,747 |
Underwater large-area high resolution monitoring by Distributed Optical Fibre Acoustic Sensors
Abstract: A variety of problems in environmental science involve determining the location and time of origin of acoustic or seismic signals. Various marine species including whales may be tracked by triangulating their vocalisations. Active faulting and magma intrusion beneath the seabed may be located by tracking the associated seismicity. Similar approaches may be used to track gas escaping through the seabed, which is now important in the context of sub-seabed carbon capture and storage (CCS), where it is important to verify that stored gas is not escaping back to the seabed. Currently in all of these applications, sound is detected by an array comprising a relatively small number (typically a few to a few tens) of point detectors, that may be towed or (more commonly) deployed on or near the seabed. Optical-fibre Distributed Acoustic Sensing (DAS) is a new technology that allows acoustic measurements to be made at an unlimited number of locations along a fibre, with a trade-off between measurement density and sensitivity. The fibre can also be manufactured relatively cheaply and at today’s market prices telecom fibres coated with a polymer layer costs less than 1p per metre. Even with fibres are engineered with additional armouring to resist the weight of vehicles passing on them, their cost only increases to a few pounds per metre. Thus, this technology has the potential to locate and quantify sound sources in and beneath the ocean with much greater accuracy, and potentially much lower cost, than hitherto possible. Deployment of this technology in the ocean is limited by poor understanding of the coupling between acoustic waves and a DAS fibre within the water column or resting on the ocean floor. In this feasibility study, we propose to use a DAS system manufactured in Southampton, which can be specifically tailored for the monitoring of underwater acoustic signals and operate at frequencies commonly not used in commercial systems, to reconstruct a 3D map of acoustic fields in the ocean. Our approach will be to firstly determine the relationship between an acoustic signal in the ocean and the signal generated in the DAS fibre laid on the seabed. We will then determine a 3D model of the acoustic sources from the sensing enabled by the seabed fibre. Our next step is to then determine how to adapt and apply DAS technology so that it is suitable for detecting, locating and quantifying acoustic noise sources in the ocean. We will do some simple tests of the new technology in test tanks and in the marine environment (a dock within the port of Southampton). This project will build on research currently funded by NERC, EPSRC, Carbon Trust, the Royal Academy of Engineering and the Royal Society to provide a novel distributed acoustic sensor network capable of high-resolution 3D detection and analysis of underwater acoustic sources
| Principal Investigator: Professor G Brambilla, University of Southampton, Optoelectronics Research Centre (ORC) |
| Co-Investigator: Dr A Masoudi, University of Southampton, Optoelectronics Research Centre (ORC) |
| Co-Investigator: Professor J Bull, University of Southampton, Sch of Ocean and Earth Science |
| Co-Investigator: Professor T Minshull, University of Southampton, Sch of Ocean and Earth Science |
| Co-Investigator: Professor PR White, University of Southampton, School of Engineering |
| Held at: University of Southampton, Optoelectronics Research Centre (ORC) |
| NERC Reference: NE/T005890/1 |
| Period of Award: 15 Nov 2019 – 14 Nov 2020 |
| Value: £241,890 |
A digital environment for water resources
Abstract: Our proposal will develop and utilise smart sensors, test new infrastructure and approaches for data cleaning, as well as developing predictive analytics and a visualisation platform, to improve the next generation of environmental regulations for water resources. Our tools will allow businesses (e.g. the whisky and agricultural sectors) to individually assess and control their environmental interactions and ultimately enable regulators to remove the need for traditional environmental inspection and monitoring. Partners in the multi-disciplinary proposal are the Scottish Environment Protection Agency (SEPA) and the Innovation Centre for Sensor and Imaging Systems (CENSIS). Our project will scope out existing and new technology for sensing water resources in remote environments, and then in a demonstrator project, explore the practical implementation of a network of sensors across a catchment integrating data from the national river flow archive, the SEPA managed network of gauging stations, and rainfall information. The results will allow us to assess the potential of this technology to disrupt traditional approaches to environmental regulation by providing a framework for enhanced and superior information gathering while removing the extensive cost and regulatory burden associated with field officers conducting inspections and sampling. A key aspect of this proposal is the promotion and deployment of sensors and communication and analytical methods to extend a previous small scale sensor pilot into a prototype digital predictive and visualisation framework testing the communications infrastructure and integration of data streams to enhance the ability of the UK to better manage water resources (quality and availability) in the context of remote, rural environments. This links into existing networks including the national river flow archive and the SEPA supported network of river gauging stations. In this larger demonstrator project, further sensors will be deployed providing additional spatial coverage of water level sensors, while adding additional types of sensor (rainfall and soil moisture), as well as scoping using a satellite based communications solution. This study will evaluate the potential of reliable and easily deployable sensor communication infrastructure based on the low power wide area network LoRaWAN standard monitoring rural environmental areas. As well as data transmission and communication challenges we will also be attempting to address off-grid powering challenges by making use of low power devices and active duty cycle management as well as renewable energy sources (e.g. solar/wind) in a low cost sustainable format. We will use new infrastructure extending the range of environmental variables to be measured, and test different data communication technologies including satellite (IoT), daisy chaining LoRaWAN and using battery operated LoRaWAN and LoRaWAN hybrid repeater nodes. These are very leading edge and we will be working with the industry leader Semtech in not only new lower power silicon (Q319) but a roll-out of a new meshing standard (TBC). The Hybrid repeater nodes will be custom and bespoke to this project. Our proposal could lead ultimately to many new remote networks that are independent of any infrastructure requirements.
| Principal Investigator: Professor M Scott, University of Glasgow, School of Mathematics & Statistics |
| Co-Investigator: Dr CA Miller, University of Glasgow, School of Mathematics & Statistics |
| Co-Investigator: Dr S Ray, University of Glasgow, School of Mathematics & Statistics |
| Held at: University of Glasgow, School of Mathematics & Statistics |
| NERC Reference: NE/T005564/1 |
| Period of Award: 15 Nov 2019 – 14 Nov 2020 |
| Value: £228,806 |
Landslide Mitigation Informatics (LIMIT): Effective decision-making for complex landslide geohazards
Abstract: Landslides or the threat of landslides can cause significant economic disruption and pose a risk to life. Relatively small events can affect wide areas, particularly where the primary road network is sparse and there is limited scope for rerouting and diversion. Rainfall triggers the majority of landslides in the U.K. and national level 24-hr forecasts exist (for emergency response agencies), but there is uncertainty surrounding what combination(s) of duration and intensity trigger slope failures on a site specific level and why similar events do not always lead to the same event/no-event outcome. These knowledge gaps are critical where decisions must actively be made to warn users of (or close) linear infrastructure such as roads and rail in order to saves lives and costs. This lack of specificity, combined with the high costs of traditionally instrumenting known ‘at risk’ locations, hinders effective decision-making for key authorities and their partners. As a result many essential components of the environment are not monitored in advance, or on a wide-scale / high-resolution (spatial and temporal) basis. LIMIT will make use of and develop the next generation of low-cost and low-power integrated network (and networks of networks) sensors combined with edge processing and multi-threshold trigger based streaming of key data in near real-time to allow decisions underpinned by advanced theories of failure mechanics. The result is low cost, wide coverage provision of data that analyses the state of the environment and forecasts future behaviour at higher spatial and temporal resolutions than previously possible, integrated into a seamless ‘data chain’ from site to decision-makers. Data and key derivations based on fundamental process science are automatically ingested/shared into a newly constructed digital environment via an intelligent hierarchical platform. The outputs are fit for national data sets and modelling; policy makers deciding on sensor networks for monitoring evolving risk due to long-term environmental changes; operational decision-makers tasked with real-time management of acute threats to life; right though to data provision and two-way engagement with the individuals at risk. Innovative low-cost, in situ near real-time data streaming/processing sensors resiliently linked to an integrated portal with automated reporting offers a viable and transformative solution to end-user challenges. The LIMIT feasibility study will generate new field validated intelligent monitoring informatics, underpinned by advanced theories of failure mechanics, to provide critical data on the increasing likelihood and then the occurrence of slope failures in real-time.
| Split award |
| Principal Investigator: Dr SA Dunning, Newcastle University, Sch of of Geog, Politics and Sociology |
| Team: Dr R. Bainbridge, Dr A. Diaz Moreno |
| Held at: Newcastle University, School of Geography, Politics and Sociology |
| NERC Reference: NE/T00567X/1 |
| Period of Award: 1 Nov 2019 – 31 Oct 2020 |
| Value: £120,043 |
| Split award |
| Principal Investigator: Dr M Lim, Northumbria University, Faculty of Engineering and Environment |
| Co-Investigator: Dr N Jin, Northumbria University, Faculty of Engineering and Environment |
| Co-Investigator: Dr H Torun, Northumbria University, Faculty of Engineering and Environment |
| Co-Investigator: Professor J E Martin, Northumbria University, Faculty of Engineering and Environment |
| Team: Dr M.W. Khan |
| Held at: Northumbria University, Faculty of Engineering and Environment |
| NERC Reference: NE/T005653/1 |
| Period of Award: 14 Feb 2020 – 13 Feb 2021 |
| Value: £121,852 |
Sounding out the river: a new system for monitoring bedload mobilisation and transport
Abstract: The mobilisation and transport of coarse sediment, referred to as bedload, has a profound impact on the evolution of mountain rivers, the surrounding basins they feed, and the communities that live within their catchments. However, we have few effective methods to routinely monitor bedload transport in near real-time because it is such a high energy and erosive environment under peak flow conditions. Hence, bedload monitoring can be considered a missing component of real-time environmental monitoring. In ‘Sounding Out the River’ we take advantage of low cost seismic sensor systems that have become available because of the rise of technology such as the Raspberry Pi computer and the ease to which these systems can be telemetered. We will demonstrate this system for monitoring the mobilisation and transport of bedload along the River Feshie in Scotland, which is catchment already monitored for a range of scientific projects. In order to ensure that the system is useful, usable and used we will co-produce the design with a range of stakeholders including SEPA, CEH, Practical Action Nepal and cbec eco-engineering UK Ltd. Beyond this proposal, we will then be able to address a range of environmental challenges, for example: – In Nepal the supply of coarse bedload to the mountain front has resulted in successive channel avulsion events on the Kosi River. This has caused the displacement of vulnerable people and the deposition of gravels across agricultural land has devastated communities. Through near real-time monitoring of bedload transport, we can better understand the dynamics of such systems and have the potential to develop early warning. – When rivers carry bedload, their erosive capacity increases; and when the bedload is deposited the beds become armoured. This poses a clear challenge for managing critical infrastructure. – Forecasting of flood hazard requires knowledge of the shape of the river bed. However, when flood waters mobilise the bedload, the shape of the bed changes which poses a problem for flood modelling. Our near-real time monitoring system has the potential to inform where and when we would expect flood models to start breaking down. – Bedload transport is an important process that cascades in the wake of other hazards, such as the monsoonal mobilisation of coarse sediment derived landslides triggered by the 2015 Nepal earthquake. It is often the case that these secondary processes (bedload transport) do not receive the same attention as the primary hazard (earthquake induced landsliding) because the uncertainty is often described as cascading, implying growing uncertainty. We believe that through the effective use of the monitoring proposed in this project, we have an opportunity to constrain the uncertainty and manage this cascading hazard.
| Principal Investigator: Dr M Naylor, University of Edinburgh, School of Geosciences |
| Co-Investigator: Professor H Sinclair, University of Edinburgh, School of Geosciences |
| Co-Investigator: Dr R Williams, University of Glasgow, School of Geographical and Earth Sciences |
| Co-Investigator: Dr AR Black, University of Dundee, Geography and Environmental Science |
| Co-Investigator: Dr W Buytaert, Imperial College London, Civil & Environmental Engineering |
| Held at: University of Edinburgh, School of Geosciences |
| NERC Reference: NE/T005920/1 |
| Period of Award: 15 Nov 2019 – 14 Nov 2020 |
| Value: £272,098 |
Methodologically Enhanced Virtual Labs for Early Warning of Significant or Catastrophic Change in Ecosystems: Changepoints for a Changing Planet
Abstract: Virtual labs are emerging as a key component in the construction of future digital environments, particularly to abstract over the complexities of the underlying distributed networks of sensors and associated computational infrastructure. We define a virtual lab as a transdisciplinary collaboration space hosted in the cloud (public/private/hybrid) that allows stakeholders to access a range of data, analytical methods and assessment tools (e.g. visualisation tools and/or statistical tools), and to execute these analyses using the elastic capacity of a cloud. In the environmental science community, most existing virtual labs focus on the problem of integrating often complex and heterogeneous data. We seek to significantly advance the state-of-the-art by enhancing virtual labs with sophisticated methodological capability, embracing state-of-the-art data science techniques to assist in the societally-relevant interpretation of these data. This is a bold and broad vision and, to make this feasible in a year, we elect to work with a particular family of data science techniques, that is, changepoint detection methods, designed to identify fundamental changes and anomalous behaviour in data, typically within time-series, but also applicable across space and time and to complex, multivariate problems. This feasibility study will therefore bring together a cross-disciplinary team working on virtual labs, changepoint methods and evidence for impacts of global environmental change on ecosystem structure and function. Our approach will foster a deep, cross-disciplinary dialogue through workshops, enhanced by rapid prototyping of virtual labs to stimulate thinking about what is possible/desirable w.r.t. ecosystem early warning methods. The project will build on the rich, complex, multi-faceted data available from the Environmental Change Network (ECN), that offers detailed multivariate 25-year long data sets for a range of ecosystems in the UK. We seek to understand the role of data science, including, but not limited to changepoint detection, in the construction of environmental early warning alert systems capable of operating at a variety of scales, from catchments to global planetary level systems.
| Principal Investigator: Professor G Blair, Lancaster University, Computing and Communications |
| Co-Investigator: Professor IA Eckley, Lancaster University, Mathematics and Statistics |
| Co-Investigator: Dr R Killick, Lancaster University, Mathematics and Statistics |
| Held at: Lancaster University, Computing and Communications |
| NERC Reference: NE/T006102/1 |
| Period of Award: 15 Nov 2019 – 14 Nov 2020 |
| Value: £203,419 |
Demonstrator projects
Top of pagePYRAMID: Platform for dYnamic, hyper-resolution, near-real time flood Risk AssessMent Integrating repurposed and novel Data sources
Abstract: Flooding has been identified by the government as the number one priority and risk to the UK. Flooding already causes millions of pounds worth of damage to people’s homes, infrastructure and the economy every year, and is projected to become even more severe under climate change. Being able to plan for, respond to and manage flooding effectively is therefore essential. We are lucky to have a tradition of flood management in the UK led by the Environment Agency. Operational flood models use meteorological data combined with elevation data to show us where flooding will occur. These models produce flood risk maps for planning and forecasting purposes and have helped us design flood defences for many areas. However, flooding is not only dependent on the topography of an area. There are many other factors at play that evolve over time: culverts can get blocked, flood gates are left open and flood walls can fall into disrepair. This can dramatically alter the extent and depth of a flood. Not only that, but our exposure to flood risk changes too. Far less disruption occurs from a flood overnight than during rush hour traffic. A prime example of this is the flooding of Boscastle in 2004. During the event, 116 cars parked in a carpark were washed downstream, blocking a bridge, causing water to back up and flood unexpected areas. If the rain had fallen in the evening, the cars would not have been in the carpark and the impact of the flood would have been smaller. Could we have predicted this? Can we reduce the impact of flooding for similar future events? We think that with the right data and tools, we can. We will build a tool that will change how we respond to flood risks as they evolve. The tool will allow flood risk managers to deploy just-in-time maintenance and alleviation measures, such as clearing critical blocked culverts or setting up mobile flood defences. To achieve this, the tool will incorporate brand new types of data and cutting edge flood models into an easy-to-use online platform that allows users to visualise evolving flood risks. The platform (called PYRAMID) will be developed in conjunction with the Environment Agency, local authorities and community groups to ensure that it delivers relevant information for critical decision-making in near-real time. The platform will have toolkits to make it easy for communities to incorporate their data, providing essential local information. The new data driving this modelling will be key. The data that we need are available but sit fragmented across a range of organisations in difficult-to-use formats. We will use artificial intelligence to extract this useful information from hidden datasets, such as old reports, flood asset registers and various types of satellite imagery. In addition, we want to incorporate brand new information from novel sensors that are being deployed as part of Newcastle University’s Urban Observatory. These sensors monitor things like soil moisture and rainfall at very high resolutions, as well as other factors like traffic and congestion. We can also monitor the condition of specific factors affecting flood risk, such as whether particular culverts are blocked or whether certain flood walls are in poor condition. These factors can be monitored by looking at a combination of satellite remote sensing and sensors deployed on lorries and other vehicles. We will also harness data collected communities and citizens. All of this information will be put into our flood models. We have a hyper-resolution hydrodynamic flood model that can accurately simulate the movement of debris in flood flows at a centimetre scale. This model will work in conjunction with a broader catchment model, which will provide information on the hydrological conditions in the wider area. The platform will be trialled in Newcastle to take advantage of existing government investments in the Urban Observatory and a legacy of flood research conducted here.
| Principal Investigator: Professor H Fowler, Newcastle University, Sch of Engineering |
| Co-Investigator: Dr LS Smith, Newcastle University, Sch of Engineering |
| Co-Investigator: Dr E Lewis, Newcastle University, Sch of Engineering |
| Co-Investigator: Professor JP Mills, Newcastle University, Sch of Engineering |
| Co-Investigator: Dr C Walsh, Newcastle University, Sch of Engineering |
| Held at: Newcastle University, Sch of Engineering |
| NERC Reference: NE/V002538/1 |
| Period of Award: 1 Aug 2020 – 31 Jul 2022 |
| Value: £787,200 |
| Principal Investigator: Professor Q Liang, Loughborough University, Architecture, Building and Civil Eng |
| Held at: Loughborough University, Architecture, Building and Civil Eng |
| NERC Reference: NE/V003321/1 |
| Period of Award: 1 Aug 2020 – 31 Jul 2022 |
| Value: £182,839 |
DECIDE – Delivering Enhanced Biodiversity Information with Adaptive Citizen Science and Intelligent Digital Engagements
Abstract: Biodiversity is under increasing pressure, with consequent impacts on the benefits people gain from nature. This means that it is vital to include biodiversity in our decision-making and for this we need high quality, fine-resolution, spatial biodiversity information. With this information we can better value nature, and this can be done formally through a process called ‘natural capital’ assessment, such as by government agencies or local economic partnerships. We also need this information to develop better plans for protecting nature, undertaking ecological restoration to develop resilient ecological networks, and make good decisions about infrastructure development (to achieve net biodiversity gain, as is the ambition in Defra’s 25 Year Environment Plan). Much of our existing biodiversity information comes from volunteer-collected species records (a process often called ‘citizen science’). However, in many cases, people record where and when they want – leading to large spatial unevenness in recording, both at a national scale and at a local scale. The people and organisations who need to use biodiversity information don’t simply require more records: they require better information. This requires us to construct good biodiversity models generated from the available data, communicate these models well, and preferentially target effort to add records from times and places that optimally improve the model outputs. This project seeks to achieve all of this by addressing three important questions. Firstly, can we enhance existing biodiversity information through near real-time, fine resolution, species distribution models? Secondly, can we make biodiversity information more accessible and useful to end users through data flows and automated data communication? Thirdly, can we encourage adaptive sampling behaviour in recorders, by using intelligent digital engagements, so that they re-deploy a portion of their effort to optimally improve biodiversity models? Our team is expertly placed to address these questions because we are a multidisciplinary team (environmental, computer, social and data scientists), and we will use a service design approach that actively engages data users (from national to local levels) and biodiversity recorders alongside the research team. In this project we will produce fine-resolution distribution models for about 1000 insect species across the UK (in this study focusing on butterflies, moths and grasshoppers) using earth observation sensor data, and a data lab (an online analysis platform) to automatically update outputs as new data are available. It is important to communicate these results and their uncertainty so, in collaboration, with data end users we will develop interactive and automatically-generated visualisations and text to do this effectively. We will also develop ways of assessing when and where new data will be most valuable in improving the model outputs. This, when combined with constraints (such as land access or people’s recording preferences) will be communicated to recorders as bespoke recommendations via a web app. This will be developed for recording butterflies and grasshoppers (a sunny day activity), and recording moths (supported by our provision of portable, low cost light traps). We will engage recorders through established recording projects across the UK, including with partners in London (many people, but relatively few biodiversity data) and North and East Yorkshire (fewer people, and a wide variety of land uses). Throughout this project our work flows will be implemented in an data lab, so they will be flexible for use with any species and indeed could be adapted for any environmental data. The outcome of this project will be a process for enhancing biodiversity information that can be incorporated into existing recording projects and data streams, so that the outputs will be accessible and useful, for the benefit of nature and people.
| Principal Investigator: Dr M Pocock, UK Centre for Ecology and Hydrology, Biodiversity (Wallingford) |
| Co-Investigator: Dr S G Jarvis, UK Centre for Ecology and Hydrology, Soils and Land Use (Lancaster) |
| Co-Investigator: Dr T August, UK Centre for Ecology and Hydrology, Biodiversity (Wallingford) |
| Co-Investigator: Dr M S Botham, UK Centre for Ecology and Hydrology, Biodiversity (Wallingford) |
| Held at: UK Centre for Ecology and Hydrology , Biodiversity (Wallingford) |
| NERC Reference: NE/V003054/1 |
| Period of Award: 10 Aug 2020 – 9 Aug 2022 |
| Value: £661,269 |
| Principal Investigator: Dr S West, University of York, Stockholm Environment Institute |
| Held at: University of York, Stockholm Environment Institute |
| NERC Reference: NE/V002856/1 |
| Period of Award: 10 Aug 2020 – 9 Aug 2022 |
| Value: £137,205 |
| Principal Investigator: Dr GJ McInerny, University of Warwick, Centre for Interdisc. Methodologies |
| Co-Investigator: Dr C Turkay, University of Warwick, Centre for Interdisc. Methodologies |
| Held at: University of Warwick, Centre for Interdisc. Methodologies |
| NERC Reference: NE/V002856/1 |
| Period of Award: 10 Aug 2020 – 9 Aug 2022 |
| Value: £96,631 |
| Principal Investigator: Dr A Siddharthan, Open University, Faculty of Sci, Tech, Eng & Maths (STEM) |
| Co-Investigator: Dr M Dodd, Open University, Faculty of Sci, Tech, Eng & Maths (STEM) |
| Co-Investigator: Ms J Ansine, Open University, Faculty of Sci, Tech, Eng & Maths (STEM) |
| Held at: Open University, Faculty of Sci, Tech, Eng & Maths (STEM) |
| NERC Reference: NE/V002856/1 |
| Period of Award: 10 Aug 2020 – 9 Aug 2022 |
| Value: £94,283 |
Sentinel Treescapes for Plant Biosecurity and Risk Management – Multiple Threats
Abstract: Trees play an essential role in sustaining life, providing wildlife habitats and timber and storing carbon, helping to reduce climate change. Tree cover accounts for around 17% of the land area of Great Britain, but trees across the UK landscape, in both woodlands and urban or agricultural environments (the ‘treescape’), are currently at risk due to a range of pests and diseases, many of which result in eventual tree death or cause safety hazards due to dead hanging branches or increased risk of tree fall. For example, ash dieback, a disease which arrived in the UK in 2012, could lead to the loss of 90% of the UK’s ash trees, currently one of the most common broadleaf species. This project will work with key partners with responsibility for managing trees or ensuring public safety, including the Department for Environment, Food and Rural Affairs (Defra), Network Rail and Norfolk County Council, to develop a monitoring system, which can ultimately be established across the UK treescape, in locations likely to provide an early warning of pest and disease spread (such as near ports or along roads and railways), or of importance for conservation, cultural reasons or public safety, to provide a ‘sentinel’ system of changes in the health of trees. The monitoring system, to be deployed in Norfolk, UK, will combine observations from sensors attached to individual trees in the landscape (measuring the condition of the tree canopy, movement of water, tree growth and the motion of the trunk as an indicator of risk of tree fall) with visual observations of tree health made by networks of voluntary ‘citizen scientists’, including current Tree Council Tree Wardens. Images obtained from cameras on drones and satellites will be used to expand the observations across a wider area and modelling methods will be used to combine the data from these different sources to estimate tree health and detect changes. A web-based interface will be developed to provide both volunteers and partners with accessible and easily interpreted information from sensors and models, and the experiences of volunteers of working with the technology will be explored through workshops. Models will also be developed to explore the efficiency and cost-effectiveness of different designs of sensor networks and to identify the ideal combinations of and distribution of sensors and observations for future use in monitoring larger areas and more locations. Workshops with partners and other interested stakeholders (e.g. forestry industry representatives or conservation organisations) will be used to examine the best ways in which sensor technology and model outputs can be communicated and the role such data can play in the decision-making processes. The demonstration network, representing a digital environment for tree health assessment and monitoring, will provide a blueprint for future deployment throughout the UK, leading to improved understanding of the spread of pests and diseases and better management of trees.
| Principal Investigator: Mr P A Brown, Fera Science Limited, Plant Pest & Disease |
| Held at: Fera Science Limited, Plant Pest & Disease |
| NERC Reference: NE/V003429/1 |
| Period of Award: 14 Aug 2020 – 13 Aug 2022 |
| Value: £385,876 |
| Principal Investigator: Dr R Gaulton, Newcastle University, Sch of Natural & Environmental Sciences |
| Co-Investigator: Dr GD Jones, Newcastle University, Sch of Natural & Environmental Sciences |
| Held at: Newcastle University, Sch of Natural & Environmental Sciences |
| NERC Reference: NE/V003755/1 |
| Period of Award: 14 Aug 2020 – 13 Aug 2022 |
| Value: £98,075 |
| Principal Investigator: Professor A Kleczkowski, University of Strathclyde, Mathematics and Statistics |
| Held at: University of Strathclyde, Mathematics and Statistics |
| NERC Reference: NE/V003755/1 |
| Period of Award: 14 Aug 2020 – 13 Aug 2022 |
| Value: £123,504 |
OpenGHG: A community platform for greenhouse gas data science
Note the OpenGHG project here is the successor of the HUGS: a Hub for UK Greenhouse gas data Science project described above.
Abstract: With numerous governments, cities, and organisations declaring climate emergencies and net-zero emissions targets, greenhouse gases (GHGs) are now the focus of international geopolitics and UK domestic policies. Furthermore, with the recent identification of violations of the Montreal Protocol, ozone depleting substances (ODS), are receiving renewed attention. It is therefore critically important to be able to analyse GHG and ODS emissions trends, examine spatial patterns, estimate future trajectories, and explore mitigation options in an open, transparent and publicly accessible way. Our proposed project will enable this, using state-of-the-art computing technology to create a platform, “OpenGHG”. The estimation of GHG and ODS emissions requires close collaboration between a diverse group of scientists and stakeholders: “bottom-up” methods rely on statistical information collected by governments and industries, combined with scientific studies of the emissions intensity of particular activities, or the development of computer models that describe how human or natural processes produce or absorb GHGs. Complementary “top-down” techniques rely on instruments developed by spectroscopists and analytical chemists, the data from which are analysed along with outputs from meteorological models using advanced statistical methods. The data that is being generated by these diverse research and stakeholder communities is growing rapidly. However, the development of computational tools to help researchers aggregate data from such a wide range of sources and carry out and share analyses has not kept pace. Furthermore, given the sensitive nature of, for example, the inference of national GHG or ODS emissions, these communities must urgently take steps to make their analyses more transparent and reproducible. OpenGHG meets these needs, by providing an open, cloud-based, platform for researchers to share data and analysis methods and publish workflows. Furthermore, we have co-designed with our stakeholders, a range of tools that will facilitate the sharing of research outputs with governments, private companies and the public. The OpenGHG platform will: – Continuously incorporate and standardise up to date GHG and ODS measurements, bottom-up emission estimates, and a range of ancillary information related to GHG and ODS emissions. This data will be pulled automatically, or on demand, from a range of public archives, or pushed to the platform by data providers seeking to analyse or share their own data – Provide a wide range of analysis options, including the ability to design, publish and share custom workflows – Allow production of new top-down and bottom-up emissions estimates by accessing pre-existing and newly developed models and methods incorporated into the platform – Provide users with lower levels of computational expertise an easy-to-use interface for the most useful data analysis and visualisation. This will include comparisons of top-down and bottom-up estimates of emissions from different sectors of the economy, and potential future warming from different emissions scenarios.
| Principal Investigator: Dr M Rigby, University of Bristol, Chemistry |
| Co-Investigator: Mr PJ Kershaw, STFC – Laboratories, RAL Space |
| Co-Investigator: Dr CJ Woods, University of Bristol, Chemistry |
| Co-Investigator: Professor SJ O’Doherty, University of Bristol, Chemistry |
| Co-Investigator: Dr A Ganesan, University of Bristol, Geographical Sciences |
| Held at: University of Bristol, Chemistry |
| NERC Reference: NE/V002538/1 |
| Period of Award: 1 Aug 2020 – 31 Jul 2022 |
| Value: £548,115 |
| Principal Investigator: Professor NRP Harris, Cranfield University, School of Water, Energy and Environment |
| Co-Investigator: Dr M Cain, Cranfield University, School of Water, Energy and Environment |
| Held at: Cranfield University, School of Water, Energy and Environment |
| NERC Reference: NE/V003224/1 |
| Period of Award: 1 Aug 2020 – 31 Jul 2022 |
| Value: £134,459 |
| Principal Investigator: Dr P Levy, UK Centre for Ecology and Hydrology, Atmospheric Chemistry and Effects |
| Co-Investigator: Dr DR Cameron, UK Centre for Ecology and Hydrology, Atmospheric Chemistry and Effects |
| Held at: UK Centre for Ecology and Hydrology, Atmospheric Chemistry and Effects |
| NERC Reference: NE/V002821/1 |
| Period of Award: 1 Aug 2020 – 31 Jul 2022 |
| Value: £117,715 |
Coastal REsistance: Alerts and Monitoring Technologies (CreamT)
Abstract: A 1 m sea level rise is almost certain in the next century and it is estimated that 20% of England’s coastal defences could fail under just half this rise. Ambitious climate mitigation and adaptation plans may protect 400,000 – 500,000 people, but flood and coastal erosion risks cannot be fully eliminated – we cannot build infinitely high sea walls. Worldwide 150 million people could be affected by sea level rise in the next 30 years. Better ways to measure, forecast, warn of and respond to coastal flooding are thus required. Using Penzance and Dawlish we will demonstrate a new monitoring system able to issue vital real-time hazard alerts and flood data to national government agencies. Working with the Environment Agency (EA), Met. Office, Channel Coastal Observatory (CCO), Cornwall Council, Teignbridge District Council, Capgenimi and National Trust, we will build on previous research using digital communication, data networking and citizen science. Our recent project (WireWall) created a unique overtopping sensor that we will develop into a low-cost hazard monitoring system for long-term deployments using telemetry to transfer data. Another project (SWEEP) created a south west regional computer simulation that updates daily to forecast coastal hazard 3 days in advance. The CCO hosts both projects online alongside the Regional Coastal Monitoring Programmes (RCMP) across England. This project will incorporate our new hazard data into the SWEEP service through a new web-accessible, open source data staging web service, thus linking models and new monitoring to validate current hazard services. The new web service will expose existing, coastal, river and weather data, while the new system will include: 1) a novel wave overtopping sensor to measure water levels and waves just before they impact a sea wall in addition to the depth, volume and speed of the water as it overtops onto public access areas behind the sea defence; 2) cameras to validate wave conditions and confirm the occurrence of overtopping events; 3) laser measurements of the pre- and post-storm beach levels during an event; and 4) an international citizen science programme, CoastSnap, that monitors beach conditions over time through photographs. The system will use the UK’s tide gauge network to trigger the measurement of potentially hazardous conditions when water levels reach the sea walls and return real-time alerts when flooding is detected. This information will allow validation of the SWEEP computer alert service. With the EA’s flood forecast team we will use this information to refine their local hazard thresholds and to understand the uncertainty in local conditions at the sea wall sites due to their large (many km’s) distance from national monitoring stations. The measured, visual and audio data will be used in an interactive coastal walk, and made accessible through an Augmented Reality (AR) phone application, available for IOS and Android devices. The AR walk will guide people to CoastSnap photo posts, encouraging participation in the RCMP beach monitoring. Promotion of the walk through the Tourist Information Centres and Twitter will raise community awareness of changing coastal hazards and shoreline management initiatives such as #floodaware and #CoastSafe. The team of oceanographers, engineers, data managers, a digital artist, a poet and a software developer will apply their expertise in different disciplines to significantly improve the accuracy and effectiveness of existing coastal hazard warning services. They will engage the public through an easily accessible phone app and participation in citizen science monitoring. Information will be archived at BODC and made available under the NERC Data Policy. This online catalogue is designed to be easily found by the Google dataset search engine and ensures our data are FAIR (Findable, Accessible, Interpretable and Re-usable).
Keywords: Hazard monitoring; Coastal forecasting; Flood aware; Hazard warning
| Principal Investigator: Dr JM Brown, National Oceanography Centre, Science and Technology |
| Co-Investigator: Dr MJ Yelland, National Oceanography Centre, Science and Technology |
| Co-Investigator: Mr D Jones, National Oceanography Centre, National Oceanography Centre Liverpool |
| Co-Investigator: Mr CL Cardwell, National Oceanography Centre, Science and Technology |
| Co-Investigator: Dr L Darroch, National Oceanography Centre, National Oceanography Centre Liverpool |
| Co-Investigator: Mr RW Pascal, National Oceanography Centre, Science and Technology |
| Held at: National Oceanography Centre, Science and Technology |
| NERC Reference: NE/V002538/1 |
| Period of Award: 3 Aug 2020 – 2 Aug 2022 |
| Value: £734,812 |
| Principal Investigator: Professor G Masselink, University of Plymouth, Sch of Biological and Marine Sciences |
| Co-Investigator: Dr T Poate, University of Plymouth, Sch of Biological and Marine Sciences |
| Co-Investigator: Dr C Stokes, University of Plymouth, Sch of Biological and Marine Sciences |
| Held at: University of Plymouth, Sch of Biological and Marine Sciences |
| NERC Reference: NE/V002589/1 |
| Period of Award: 3 Aug 2020 – 2 Aug 2022 |
| Value: £177,672 |
SENSUM: Smart SENSing of landscapes Undergoing hazardous hydrogeological Movement
Abstract: Floods and landslides affect the UK every year, both inland and along the coast, causing disruption, occasional fatalities and severe economic loss. An increase in storminess under climate change and population pressure are resulting in an increase in landslide and flood hazards in the UK and globally and threatening the defences put in place to manage these hazards. Monitoring of unstable hillslopes and flood-prone rivers as well as defences designed to manage these is increasingly vital. Landslides and floods are both triggered by heavy rainfall, often occur at the same time, and may interact to generate a chain reaction of knock-on hazardous effects. SENSUM proposes a new integrated way to tackle these ‘hydrogeological’ hazards, taking advantage of advances in Wireless Sensor Network (WSN) and Internet of Things (IoT) technologies, microelectronics and machine learning. Those exciting new tools will be used to monitor the stability of defences, provide warnings of hazard events, and improve mathematical models and visualisation of hazardous phenomena. Landslides and floods have traditionally been monitored using a combination of satellite-based remote-sensing techniques and wired ground-based instruments to measure factors that control the related hazard, such as river flow level, displacement and soil moisture. Wireless sensor networks (WSNs) show great potential for monitoring and early warning of these hazards. Their main advantage is their use of easily deployable, low-power sensors enabling continuous, long-term, low-cost monitoring of the environment. For landslides and floods, which occur infrequently and unpredictably, this is an important technological advance. SENSUM proposes to develop innovative smart tracking devices, embedded in boulders and woody debris on hillslopes and in rivers to give real-time warning of movement related to landslide and flood processes. Collaborating closely with external partners, the team of experts in the SENSUM project will develop and test the tracking devices both in dedicated laboratory experiments and in the field, with the deployment of trial networks of smart boulders and woody debris in different localities in the UK and abroad. The large set of data obtained from sites and experiments will be used to improve mathematical models, to develop innovative early warning systems and in 3D digital visualisations. This integrated approach will enable us to establish a comprehensive understanding of landslide and flood processes which will significantly reduce risk to society. The SENSUM team is a diverse, interdisciplinary and multinational team made up of a range of environmental scientists and engineers, computer scientists and science communication specialists from three leading UK universities: University of Exeter, University of East Anglia and University of Plymouth and will involve several project partners including the Environment Agency, Forest England, Natural England and AECOM. It will work closely with these project partners to design an effective digital environment for monitoring and managing landslide and flood hazards in the UK, and to target applied risk management challenges. For example, in the UK, the Environment Agency is tasked with giving a 2-hour warning to the population affected by floods. However, these warnings are lacking in the upland areas of the UK’s landscape due to a lack of instruments to monitor river flow. The smart tracking devices embedded within boulder and woody debris in landslides and river channels proposed by SENSUM will help address that limitation, and therefore will significantly improve early warning of movement and consequently the assessment of potential high-risk natural events. The team will also engage stakeholders and the general public through the creation of compelling visualizations of landslide and flood hazards and through project workshops and outreach activities.
| Principal Investigator: Dr GL Bennett, University of Exeter, Geography |
| Co-Investigator: Professor IS Stewart, University of Plymouth, Sch of Geog Earth & Environ Sciences |
| Co-Investigator: Dr C Luo, University of Exeter, Computer Science |
| Co-Investigator: Dr I Manzella, University of Plymouth, Sch of Geog Earth & Environ Sciences |
| Co-Investigator: Professor RE Brazier, University of Exeter, Geography |
| Co-Investigator: Professor AC Raby, University of Plymouth, Sch of Eng, Comp and Math (SECaM) |
| Co-Investigator: Professor G Min, University of Exeter, Computer Science |
| Co-Investigator: Dr SJ Boulton, University of Plymouth, Sch of Geog Earth & Environ Sciences |
| Co-Investigator: Dr A Franco, University of East Anglia, Environmental Sciences |
| Held at: University of Exeter, Geography |
| NERC Reference: NE/V003402/1 |
| Period of Award: 14 Aug 2020 – 13 Aug 2022 |
| Value: £969,482 |
Dynamic monitoring, reporting and verification for implementing negative emission strategies in managed ecosystems (RETINA)
Abstract: Carbon sequestration in soil is one of the most promising biological negative emission (BNE) technologies to mitigate climate change. Soil carbon sequestration relies on the adoption of best management practices to increase the amount of carbon stored in soil. An advantage of soil carbon sequestration in agriculture is that carbon stocks are most depleted in cropland systems, so there is great potential to capture atmospheric carbon without land use conversion and competition for land resources. The successful implementation of land based negative emission technologies will require continuous monitoring, reporting and verification of soil storage changes and greenhouse gas (GHG) emissions to estimate net carbon sequestration in soils. Currently, a lack of cost effective, robust, consistent, transparent and accurate methods limits large-scale implementation of these technologies. Monitoring, reporting and verification of carbon sequestration and GHG emissions from soils could be achieved by combining information from novel cost-effective technological developments in field-based sensors, remote sensing, and/or smartphone apps and integration of models on cloud platforms to confirm management practice effectiveness. The process of detecting and inferring soil carbon changes and GHG emissions is extremely data intensive. In order to understand the variability in soil carbon and GHG emissions there is a need to combine information from diverse sensor networks in different environments and to accurately model soil carbon changes and GHG emissions from various management practices. Here we propose a cloud-based platform that combines new development in sensor-based technologies with cloud-based model simulations to overcome major obstacles for implementing a monitoring, reporting and verification (MRV) system for land based negative emission technologies. To operationalize the MRV system, we will collect and process sensor information from the field, land scape level sensors and national scale (Satellite data) and harmonize data feeds to cloud-based models. This setup allows near time simulations on carbon changes and GHG emissions on the cloud without the need for individual user inputs. This project offers the quality data and confidence required for visualising a future, rising to the demands of a net zero carbon UK by 2050. This project will undertake transdisciplinary research to harness recent advances in digital technology combined with novel approaches in stakeholder engagement to make a step change in delivering integrated management options, co-produced with stakeholders, which can help to mitigate climate change. There are several groups who will benefit from the outcomes of this research. We identify various stakeholders and interested groups; UK Farmers will benefit from a freely available mobile-App to help plan various management options to increase/maintain soil organic matter in soil while also accounting for GHG emissions from soil. For policy makers, web-based decision support tool developed in this project will forecast regional estimates of net soil carbon sequestration and GHG emissions. This project could help in designing strategies to monitor and improve environmental quality and reduce GHG emissions from managed ecosystems to meet net zero Britain by 2050. We anticipate wide interest from academia in the GHG budgets and various environmental data sources this project will generate.
Keywords: Climate change, soils, carbon sequestration, Greenhouse gas emissions, cloud-based modelling
| Principal Investigator: Dr J Yeluripati, The James Hutton Institute, Information & Computational Sciences |
| Co-Investigator: Dr K Macleod, The James Hutton Institute, Information & Computational Sciences |
| Co-Investigator: Dr MJ Aitkenhead, The James Hutton Institute, Information & Computational Sciences |
| Held at: The James Hutton Institute, Information & Computational Sciences |
| NERC Reference: NE/V003259/1 |
| Period of Award: 1 Aug 2020 – 31 Jul 2022 |
| Value: £587,420 |
| Principal Investigator: Dr DR Cameron, UK Centre for Ecology and Hydrology, Atmospheric Chemistry and Effects |
| Held at: UK Centre for Ecology and Hydrology, Atmospheric Chemistry and Effects |
| NERC Reference: NE/V003232/1 |
| Period of Award: 1 Aug 2020 – 31 Jul 2022 |
| Value: £58,307 |
| Principal Investigator: Professor P Smith, University of Aberdeen, Inst of Biological and Environmental Sci |
| Held at: University of Aberdeen, Inst of Biological and Environmental Sci |
| NERC Reference: NE/V003240/1 |
| Period of Award: 1 Aug 2020 – 31 Jul 2022 |
| Value: £202,176 |
Mini-Demonstrator projects
A series of smaller demonstration projects were supported directly through the constructing a digital environment program, each of which were selected to showcase particular facets of digital environmental science. These ‘mini-demonstrator’ projects are described below.
Top of pageNature Positive Acoustics
Need
The 2021 Environment Act sees the operationalisation of various biodiversity metrics into public policy. Operating at the scale of individual developments, the Environment Act makes it mandatory for all new developments in England from late 2023 onwards regulated via the Town and Country Planning Act to demonstrate they will result in a 10% improvement in biodiversity. This is termed “Biodiversity Net Gain” (BNG). The same legislation will apply to all Nationally Significant Infrastructure Projects from 2025 onwards. Biodiversity is measured using the Government’s “Biodiversity Metric”; a simple composite indicator reflecting the area, ecological condition, and distinctiveness (a proxy for the degree of conservation value) of each patch of habitat within the development boundary. Measuring biodiversity in this way has significant implications for the kind of nature that will be delivered by the policy. Other sections of the act that target improvements in wildlife abundances, wildlife-rich habitats, and a reduction to the number of species at risk of extinction are not addressed by the Metric. In addition, the Act requires developers to provide evidence that their BNG obligations have been met, and this will extend for 30 years as part of the agreements made with planning authorities and relevant offset providers. As a result, there is a recognized need to define standards for monitoring design, data collection, storage and analysis that would reliably demonstrate support for net gain outcomes; and for those standards to be sustainable and cost-efficient over long timescales.
One such technology that we believe is likely to help serve this demand is ecoacoustic monitoring. Ecoacoustic monitoring is increasingly undertaken using unattended “passive” automated recorders which minimises human involvement in fieldwork, and enables surveying in otherwise remote and harsh environments (Gillespie et al. 2009; Marques et al. 2013; Stowell and Sueur 2020). Passive acoustic monitoring can record large volumes of sound data over long time periods, thereby following standardised reproducible protocols independent of observer biases (Hill et al. 2018; Stowell and Sueur 2020). While research and development are still active, developments in ecoacoustics have progressed to such a point that good practices for survey and monitoring can begin to be identified (Furumo and Mitchell Aide 2019, Bradfer-Lawrence et al. 2020). Nonetheless, the synergy between the policy requirements of BNG, and between the calculation of Metric scores and ecoacoustic indices is unknown.
This project aims to build consensus amongst researchers and policy makers on the minimum data and reporting standards for ecoacoustics that would reliably support Biodiversity Net Gain assessments. To do this will require consideration of all stages in the ecoacoustics workflow: data collection, management, communication, analysis, and reporting. Where possible the network will identify organisations with existing data workflows that can be adapted to suit a public accessible ecoacoustics portal, and where further work would be required to allow ecoacoustics to be adopted by regulatory authorities. Finally, it is worth noting that ecoacoustics is only one of several sensing systems (e.g. camera traps, RADAR, eDNA) in ecology that could be supported by an emerging digital infrastructure. Nonetheless, at this stage it would be too complex to consider the integration of all possible techniques, which is why we have decided to focus on ecoacoustics as it has the most immediate potential to support BNG monitoring.
Project objectives
This project will critically address the value of ecoacoustics for assessment of BNG in the UK through the following four deliverables:
- A workshop to review the current state of knowledge and develop a white paper on ecoacoustics for BNG.
In this, 12-15 attendees from academic and private sectors would be invited with expertise in ecoacoustics and data management (NERC EDS), alongside decision makers in regional and national government (Local Nature Partnerships, Natural England, JNCC, DEFRA). We have contacts within most of these organisations who we can approach to identify interested attendees.
Questions we aim to address include:
- Which metrics derived from ecoacoustics are suitable for BNG assessment?
- Which changes in ecoacoustic metrics are comparable to scores based on habitat assessment?
- What monitoring design and metadata provides developers and regulators with greatest statistical power to support their assessment?
- What factors will influence storage and reuse of ecoacoustic data?
- How could ecoacoustic results be reported and visualized to suit a wider audience of stakeholders?
- Pilot field project illustrating principle of white paper in practise
Previous reviews have suggested the greatest uncertainty is currently how acoustic indices vary within and between habitats and how changes relate to scores indicated by the BNG Metric v3.1 (NE 2021). Preliminary conversations with government colleagues have therefore indicated that a pilot that demonstrate how we can reduce and quantify those types of variations would be valuable in understanding the technical pathways to national assessment.
This pilot will ask six partners to select sites that represent a specific terrestrial habitat type in three different levels of condition. Partners will also receive an additional recorder that can be rotated among sites so that we can estimate the degree of variability within-, as opposed to among-sites. Differences in condition will illustrate when metrics based on ecoacoustics align with perceived differences in condition based on vegetation assessment. For reference, partners will be asked to score each site using the BNG Metric v3.1 vegetation classification system. For each site the partners will be provided with a SongMeter MiniBat and a schedule for recording both acoustic (birds) and ultrasonic (bats) calls over a period of several months prior to the workshop. The acoustic data from these surveys will be analysed using the open source BirdNet classifier, and the bats will be identified using commercially available software (Kaleidoscope Pro or BTO portal). We will also calculate a variety of indices to describe the complete soundscape. - A journal article that covers the white paper and evaluates the field pilot.
Dissemination
In addition to the members of the agencies attending the workshop, a public-facing summary will be distributed alongside the journal article and white paper to all organisations in the UK involved in natural environmental planning through the Local Nature Partnerships (and who thereby are involved in administering BNG policy). The Eden Project expressed interest in hosting a pilot project and we will seek opportunities to build on their experience supporting outreach and engagement with the public. Additionally, we will present our initial findings at the CDE conference 2023.
The PIs on this application are well placed to lead this project as we are each actively exploring the use of ecoacoustics for evidencing ecological gains in other applied fields such as forest restoration and agri-environment subsidies, as well as assessing impacts from development. In addition to A. Bush’s and T. August’s time (included in the allowances as expert network members) we are also able to offer some resources in-kind to help with the pilot, including additional recorders, software licence costs, and where possible student time.
| Principal Investigators |
|---|
| Alex Bush, Lancaster University alex.bush@lancaster.ac.uk |
| Tom August, UKCEH tomaug@ceh.ac.uk |
| Carlos Abrahams, Baker Consultants c.abrahams@bakerconsultants.co.uk |
| Value: £41,957 |
Integrating a biodiversity digital twin with a FAIR data pipeline for reproducible science
Overview
We live in a time of Big Data, big environmental and social challenges, and associated complex models and high computational needs. As data and software dependencies for research projects become ever more complex, it’s increasingly important that we have correspondingly powerful and flexible frameworks to ensure that science carried out to address these challenges can be seen to be trusted. The FAIR Data Pipeline (FDP) was created during the pandemic for managing workflows involving FAIR (Findable, Accessible, Interoperable and Reusable) data to trace data and software use while computational analyses are carried out. We currently lack an exemplar for Open environmental science and so this project proposed to integrate the FDP into a digital twin of the UK plant biodiversity. This EcoSISTEM (Ecosystem Simulation through Integrated Species Trait–Environment Modelling) simulation framework integrates complex environmental and ecological data to predict the impact of landscape decisions and climate change on UK biodiversity. As part of this project, we used case studies from Harris’ work with UK plant biodiversity and Welsh peatlands to both test the integration of the two systems and provide examples for other researchers and environmental scientists. As part of this project, we ran a stream of the Hackathon at the 2023 NERC Digital Gathering in Cambridge to provide other researchers with the opportunity to integrate their own work with the FDP.
Further information
EcoSISTEM is a digital twin designed for dynamic plant simulation at various scales, spanning individual sites to entire continents. It incorporates competition among diverse plant species for resources like sunlight and water, as well as land management choices. Plant species are distributed across a gridded environment, competing, reproducing, and dispersing seeds based on local conditions. Initially funded by EPSRC, EcoSISTEM scales from laptops to high-performance computing platforms, enabling simulations of trillions of plants across thousands of species against century-long climate records. Through a series of NERC Landscape Decisions grants, the system was applied to the UK, achieving higher-resolution plant biodiversity modelling and focusing on a highly detailed simulation of a Welsh peatland site. The project amassed diverse climatic, soil, hydrological, and ecological data, and associated codebases
The FAIR Data Pipeline was developed as a response to concerns about data and code management and the transparency and provenance of scientific, especially modelling, policy advice during the early stages of the COVID-19 crisis, and a recognition that while standards for the format and storage of metadata existed, no tools were available for end users to easily manage FAIR data using these standards as it was generated and consumed in analyses. Researchers in the Scottish COVID-19 Research Consortium identified this need for a data management pipeline that could track data provenance through the modelling process from initial data collection to results presented to policy makers. Development of the pipeline was a collaboration across several major research institutions with considerable expertise in the FAIR principles and in Research Software Engineering as well as industrial partners.
| Principal Investigators |
|---|
| Richard Reeve, University of Glasgow richard.reeve@glasgow.ac.uk |
| Claire Harris, Biomathematics and Statistics Scotland, James Hutton Institute claire.harris@bioss.ac.uk |
| Value: £39,971 |
A NERC data service for integrating NERC sensor networks
Motivation
Sensors are everywhere. Increasing numbers of sensors and sensor networks within emerging technologies – such as the Internet of Things (IoT), autonomy and robotics – are being used to capture NERC environmental data, expanding and offering new opportunities to understand our natural world. Yet much of this data is captured in near real-time and often from distributed networks, with limited consideration for long term archiving, where the data is captured in varying size and complexity over different temporal and spatial scales. This makes it challenging to integrate and optimise the data for analysis, modelling and simulation over large-scales as well as providing any ‘right-time insight’ for decision-making. With a rapid growth in the global sensor market expected over the coming years, the use of sensors in environmental science is also expected to become more significant. Thus, common ways to access and integrate the data from these sensors will be required. As part of its ambition to increase integration and interoperability across the NERC environmental data centres, the Environmental Data Service (EDS) has identified the need to support sensor technologies through digital infrastructure that connects distributed networks of NERC sensors, ensuring that they are optimised and accessible in the long term for use to address critical environmental challenges within a NERC-enabled digital ecosystem. Using this momentum, our proposal aims to conduct a scoping study for a new NERC service hosted by the EDS for integrating NERC sensor networks within NERC data centres, enhancing the interoperability and accessibility of NERC sensors and sensor networks across existing and broadening user communities.
Research excellence and fit to strategy
The NERC Digital strategy seeks to support the development of novel environmental sensors and measuring techniques as part of an ecosystem of digital infrastructures. However, as more environmental sensors are deployed, the volume and complexity of this data will also grow. Data services must evolve to meet these demands. Our proposal seeks to align with this strategy, proposing a digital infrastructure that will enhance the accessibility and interoperability of this growing pot of data. In doing so, we can help to close the gap between data collection, data analysis, through careful data stewardship within the NERC digital ecosystem. The project also meets the scope of CDE by managing digital data streams from sensors, and the transmission and utilisation of this across the technology arc.
The careful data stewardship of this data through fundamental data management practices will be key to maximising the value of these NERC assets. The digital infrastructure must demonstrate trustworthiness and resilience in its ability to curate data long-term (TRUST).
Transparency and robust data exchange can be achieved through the findability, accessibility, interoperability and reusability (FAIR) of these assets. As such, new environmental understanding could be realised from the integration of this data with other sources of information such as remote sensing (e.g. Met Office rain radar data: NIMROD), or at the intersections of environmental disciplines, for example between the ocean and atmosphere.
Optimising and making this data available for powerful new tools such as data analytics and visualisation, or models and simulations (e.g. Artificial Intelligence and digital twining), will increase the potential to significantly improve our understanding of the environment. It may become a key driver for the NERC IMFe[5], a framework for multidisciplinary environmental digital twins that support decision-making for key environmental policies.
Figure 1 presents a notional overview of core elements in the infrastructure that connects distributed networks of NERC sensors. Key factors in the success of this service will be the ability to consume sensor data and transfer sensor contextual information without human intervention. This will be necessary in scenarios where sensors are required to inform ‘right-time insights’. The service will likely need to support multiple communication protocols (e.g. CoAP, MQTT). Contextual information, such as identifiers, capabilities, calibrations and interfacing, will be needed by connected systems to effectively use the signal from sensors. IEEE Transducer Electronic Data Sheets (TEDS) were developed to embed contextual information in sensor memory in industrial applications. More recently, the Research Data Alliance endorsed the use of globally unique persistent identifiers that identify a sensor and resolve to contextual information over the internet, thereby saving memory and transmission volumes.
Widely used standards could also be considered to further integrate sensors. The OGC SensorThings API provides an open, unified way to interconnect sensors, data, and applications over the Web. Semantic interoperability could be adopted to enable connected systems to exchange information unambiguously using controlled vocabularies and ontologies. The W3C Semantic Sensor Network (SSN) ontology is used to annotate sensors, their procedures and their observations using serialisation formats that arecompatible with the web (e.g. Resource Data Framework), enabling machines to not only read but understand metadata and data. The ENTRAIN CDE project assessed the potential use of these standards for describing data from terrestrial monitoring networks. Other elements that may be key factors in a digital infrastructure might include: enabling automated transmission of data from both in- and out-of-sight sensor network (e.g. NCAS FAAM Airborne Laboratory); feedback to sensor networks in support of decision making; processing and event handling to clean or validate sensor data in event order; Edge processing layers where sensor networks are resource-constrained; appropriate hardware for big data storage and scalability (e.g. NERC CEDA JASMIN).
Figure 1. A conjectural overview of elements for a NERC data service for NERC sensor networks.Click image to enlarge
Benefits to wider environmental science NERC-focused community: Through an ecosystem of tools, the digital infrastructure will make the management, visualisation, analysis and archiving of sensor data more efficient for the wider research community. In addition, they will support the actors and standards involved in sensor workflows. For example, the NCAS Data Project engages instrument operators, data archivists, software developers and end-user communities to collaborate on common standards-driven data and metadata flows, so sensor data can meet the needs of the wider community. Through providing the capability to easily access or integrate sensor data, the service can also support collaborative interdisciplinary activities, such as with other sensor networks or data facilities. This could be within NERC (e.g. NERC Floods and Droughts Research Infrastructure (FDRI)), across the UKRI (e.g. UK Geoenergy Observatories (UKGEOS), EPSRC Energy Demand Observatory and Laboratory) as well as the wider UK environmental community (e.g. Environment Agency).
Aim
Our vision is to develop a new digital infrastructure that connects distributed networks of NERC sensors, enhancing the interoperability and accessibility of NERC sensors and sensor networks to support research and environmental understanding across existing and broadening user communities.
Approach
To make the initial steps towards realising this vision we will conduct a scoping study that engages the EDS and wider environmental science NERC-focused community (see above). It will aim to understand:
- Enabling technologies and management procedures from sensor networks, identifying commonalities.
- Core infrastructure elements.
- The application of FAIR and TRUST principles.
- Requirements enabling the service to integrate into the NERC Digital ecosystem.
- Requirements enabling the service to integrate with the wider environmental science NERC-focused community.
Given the timeframe of the project, we will use a combination of anonymous online surveys (this project) and one-to-one interviews (as part of concurrent survey activities supported by FDRI time in-kind) to gather responses from a cross-section of representatives from the EDS and wider environmental science NERC-focused community. We will also gather and summarise evidence from two scoping studies that have been conducted by the FDRI and UKGEOS sensor networks, and further elaborate these requirements where required.
Objectives
O1. Survey and gather responses from EDS and wider environmental science NERC-focused representatives using online surveys and one-to-one interviews.O2. Summarise scoping studies from wider environmental science NERC-focused sensor communities.
O3. Deliver a visioning document for a NERC data service for integrating NERC sensor networks.
| Principal Investigators |
|---|
| Lou Darroch (National Oceanography Centre, CDE Expert member lorr@noc.ac.uk |
| Matt Fry (UK Centre for Ecology & Hydrology, CDE Expert member mfry@ceh.ac.uk |
| Carl Watson (British Geological Survey, CDE Expert member cats@bgs.ac.uk |
| Graham Parton (Centre for Environmental Data Analysis graham.parton@stfc.ac.uk |
| Value: £49,949 |
Unlocking the potential of Sensor for our Environment: a co-creation and writing retreat
Project description
The project fits under the Sensor Networks (SNs) objective but also has intended outcomes that will impact other CDE objectives, and further contribute to the network’s legacy.
The retreat aims to:
- synthesize advances to date in environmental sensing and sensor networks as deployed and used by practitioners, communities and other stakeholder groups;
- identify best techno-social practice in the development and field deployment of environmental sensor systems
- identify gaps in knowledge, articulate research and development needs and possibly the need for new methods for co-creation of sensing and actuation feedback loops and systems;
- shape the role of sensing, through its outputs, with regards to policy making, strategic investment in the sector and investment uptake of research challenges.
The output of the retreat will be in the form of a briefing paper that complements and further builds upon and expands the scope of the UKRI’s (soon to be released) report “Low cost environmental monitoring sensors: landscaping review, UK and India”. (Both Co-PIs have had the honour of attending the December sandpit on defining the direction of travel for UKRI/India efforts in water and air pollution sensing in particular.)
The retreat will be held at Coventry University campus over 2 days – dates to be determined, in the period May/June 2023, with the briefing paper aimed to be delivered before the onset of the new academic year.
The administration of the retreat, invitations, preparation and venue costs will be fully covered by the grant, as will the accommodation and subsistence for the attendees (except attendees travel to and from retreat).
The attendees will be selected to ensure coverage of the CDE network interests and objectives while also ensuring multi-disciplinarity, cross-field fertilization and learning especially from the engineering/computer science sensing community and the social science participatory methods community. We aim for a transdisciplinary setting that fully considers people, places and ethics. It is intended that the invitations and attendees confirmation process will take place shortly upon award and all 30 funded places will be confirmed 6 weeks prior to the retreat date.
The preparation stages (opening 4 weeks prior to the retreat and continuing up to the event) will see attendees working individually or in small teams to cover set challenge categories (to be fully specified by the Co-PIs in conjunction with the CDE Network leadership, upon award) and use the digital space to springboard discussion, bring to bear relevant materials and experiences and contribute to emerging debates.
The retreat will offer a structured experience that covers the stated aims and produces the raw material for the briefing paper. The delivery method builds on participatory sandpit approaches to co-creation of convergent outcomes. The retreat will offers participants a platform to interact, network, exchange ideas and share into the common knowledge and lived experiences pool on the themes pursued. It is intended that, along with the briefing paper, the value of the retreat will also be of experiential nature for the individual attendees. Participants will collaborate on the action-based call for future research foci and it is hoped that natural partnerships emerge towards new projects and proposals.
Upon the retreat, the briefing paper draft will be produced by the Coventry team and agreed with the participants before delivery to CDE Network leadership. It is hoped that the co-created set s of best practice and articulated future challenges will be of use and importance to the key stakeholders in the environmental sensing eco-systems, from researchers to funders and others.
While as described above, the sub-themes and challenge categories will be themselves co-created with the CDE Network leadership, we offer below some questions that may be considered of interest:
- What is the greatest valued (economic, social, political and other dimensions) identified to date, from Environmental Sensing (ES) in various domains (air, water, etc?)
- What are the best lessons learned from design and deployment, usage and exploitation of ES? Are there cross-domain common lessons? Are there common pitfalls of the ES technologies that cross domains? Are we learning enough from failure?
- What are remaining barriers to unlocking value from ENs in particular in the Digital Environment context?
- What would you change about the EN eco-system, the to better unlock their value? (considering a whole society approach to the design, implementation, use and exploitation of SNs)
- Would tools for bringing together technologies, techniques, sponsors, governmental parties help ease the productization of ENs and associated data -to-knowledge pipelines? (for example but not limited to tools like https://coped.coventry.ac.uk/ that bring together the Digital Energy community of research and enterprise).
| Principal Investigators |
|---|
| Prof. Elena Gaura, Coventry University e.gaura@coventry.ac.uk |
| Dr. Liz Bagshaw, Cardiff University/University of Bristol bagshawe@cardiff.ac.uk |
| Value: £19,394 |
Sustaining Environmental Data Discovery
Abstract: A 1 m sea level rise is almost certain in the next century and it is estimated that 20% of England’s coastal defences could fail under just half this rise. Ambitious climate mitigation and adaptation plans may protect 400,000 – 500,000 people, but flood and coastal erosion risks cannot be fully eliminated – we cannot build infinitely high sea walls. Worldwide 150 million people could be affected by sea level rise in the next 30 years. Better ways to measure, forecast, warn of and respond to coastal flooding are thus required. Using Penzance and Dawlish we have demonstrated a new monitoring system able to issue vital real-time wave overtopping hazard alerts to national government agencies. Working with the Environment Agency (EA), Network Rail, Met. Office, SW Coastal Monitoring, the National Network of Regional Coastal Monitoring Programmes (NNRCMP), Cornwall Council, Teignbridge District Council, Capgenimi and National Trust, we have built on previous research using digital communication, data networking and citizen science. Our previous project (WireWall) created a unique overtopping sensor that we developed into a low-cost hazard monitoring system for long-term deployments using telemetry to transfer data. Another project (SWEEP) created a southwest regional computer simulation that updates daily to forecast coastal hazard 3 days in advance.
The NNRCMP hosts both projects online alongside regional coastal monitoring across England. CreamT incorporated the new beach level data into the SWEEP service, thus linking models and new monitoring to access uncertainty in the hazard service. A new wave overtopping hazard dashboard was also released online visualising overtopping hazard alongside existing coastal met-ocean data. Together the concurrent coastal observations include: 1) a novel wave overtopping sensor to measure the frequency and duration of wave overtopping; 2) cameras to validate wave conditions and confirm the occurrence of overtopping events; 3) laser measurements of the pre- and post-storm beach levels during an event; and 4) an international citizen science programme, CoastSnap, that monitors beach conditions over time through photographs. This information has allowed the validation of the SWEEP computer alert service. We continue to work with the EA’s flood forecast team we will use this information to refine their local hazard thresholds and to understand the uncertainty in local conditions at the sea wall sites due to their large (many km’s) distance from national monitoring stations. The visual data were used in an interactive coastal walk and made accessible through an Augmented Reality (AR) phone application, available for IOS and Android devices. The AR walk guides people to CoastSnap photo posts, encouraging participation in the beach monitoring. Promotion of the walk through the Tourist Information Centres, Newlyn Art Gallery and Twitter has raised community awareness of changing coastal hazards and shoreline management initiatives. Information is archived with the BODC and made available under the NERC Data Policy. This online catalogue is designed to be easily found by the Google dataset search engine and ensures our data are FAIR (Findable, Accessible, Interpretable and Re-usable).
| Principal Investigator: Jenny Brown, National Oceanography Centre, Marine Physics and Ocean Climate |
| Co-Investigator: Louise Darroch,, National Oceanography Centre, British Oceanographic Data Centre |
| Co-Investigator: Adrian Hines, , Science and Technology Facilities Council (UKRI) |
| Held at: National Oceanography Centre, Marine Physics and Ocean Climate |
| Period of Award: 1 Jan 2023 – 31 Jul 2023 |
| Value: £50,000 |
From photons to fish, from seconds to centuries; Generating FAIR data from high resolution sensors in the Western Channel Observatory
Abstract: The Western Channel Observatory (WCO) is an oceanographic time-series and marine biodiversity reference site that provides a valuable source of data to a wide range of UK research, policymaker, public and businesses communities. Recently, emerging and innovative sensor and platform technologies have proven their abilities to increase both the spatial and time resolution of these data. While this additional data will allow current applications to evolve and improve their capabilities, a new generation of innovative digital solutions such as digital twins or higher level artificial intelligence (AI) and machine learning (ML) applications require the creation of new, scalable, robust and mature data pipelines that focus on the need to make data truly findable, accessible, interoperable and reusable (FAIR).
This mini-demonstrator project has allowed a collaboration among data providers, data users and data archiving centres to investigate and trial approaches to increase the FAIR-ness of marine observation data. From the perspective of data findability (FAIR), this project has implemented intuitive and interactive tools that allow users to find, visualise and explore data and metadata within complex and long-running data series. The developed webpages provide visual, intuitive and interactive toolsets, that allow all data users to search data, interact with enriched metadata, discover and identify data of interest. To improve data access (FAIR), this project has implemented a common interface allows data users to seamlessly access both the British Oceanographic Data Centre’s (BODC’s) data archive and WCO’s near-real time data within a single, intuitive interface. Prototypical tools have been developed within this project that prove the concept of a combined data access ticketing system that guides users though the process of accessing archived and near real-time data through a single, structured and auditable data and metadata access process.
To increase data interoperability (FAIR), scientist-centred approaches that encourage the elicitation and use of commonly used community metadata vocabularies that follow FAIR principles have been developed. These approaches focus on the implementation of the UK Marin Environmental Data Information Network (MEDIN) discovery metadata standard, increased use of standardised vocabularies from the NERC vocabulary services improved metadata richness. Approaches to identify and capture data quality via automated quality checking and crowd-sources approaches were also trailed within the developed toolsets, providing a building block towards improved data provenance. Finally, to increase data reusability (FAIR), multi-community approach to enhancing the visibility of metadata and increasing its quality early in the data lifecycle. Data reusability has been enhanced by clarifying and improving the quality of discovery metadata, with an emphasis on increasing the clarity of licencing and open data usage policies.
Focussing on the observatory’s CTD (conductivity, temperature, depth) data, this work provides an important step towards enabling a new generation of sensors and platforms to generate scalable, FAIR data sets. In addition, the lessons learned from this development have been shared within a reusable reference architecture framework to provide foundations that allow near real-time environmental data to drive the development of digital twins, machine-to-machine (M2M) data discovery, artificial intelligence (AI) and machine learning (ML) approaches, These foundations are vital to unlocking the potential of data among environmental digital sciences while supporting several NERC Digital Strategy areas, including enhanced data services, facilitating confidence and trust and developing people and skills.
| Principal Investigator: Thomas Mansfield, Plymouth Marine Laboratory, Digital Innovation and Marine Autonomy |
| Co-Investigator: Ben O’Driscoll,, Plymouth Marine Laboratory, Digital Innovation and Marine Autonomy |
| Co-Investigator: James Ayliffe, , National Oceanography Centre (NOC), British Oceanographic Data Centre |
| Co-Investigator: Tim Smyth, , Plymouth Marine Laboratory, Marine Biogeochemistry and Observations |
| Held at: Plymouth Marine Laboratory |
| Period of Award: 1 Jan 2023 – 31 Jul 2023 |
| Value: £41,000 |
The Art-Science interface: Working with artists to explore the digital environment
Description
Public engagement with research in the digital environment is key for creating a greater awareness of the challenges facing both the environment, and researchers in our domain. Improving the public understanding of digital tools, methods, and the ‘digital environment’ is key to both NERCs digital strategy and the aims of the CDE programme. Working with artists is not only a fantastic way to create engaging and informative experiences for a wider audience, but is also a powerful tool for scientists to reflect on the nature of their own research through the eyes of creative individuals. Both objectives are especially valuable when considering the novel ‘digital environment’ technologies and tools being promoted through CDE and the NERC Digital Strategy. This project will demonstrate the value of artist-scientist collaborations regarding the remit of the CDE and the NERC Digital Strategy through an installation in the North of England and will build capacity through two training events for scientists.
We will build on the “Dataset’s Dream”, an art-science collaboration undertaken through DECIDE (a CDE demonstration project, run by Michael Pocock and Tom August), and existing art-science collaborations initiated by Gordon Blair in the ENSEMBLE project. The “Dataset’s Dream” is an art installation that explores what happens when nature becomes digital – what is gained and what is lost – and how becoming digital affects the ‘agency’ of nature. Working with a visual artist and a poet, this collaboration with data scientists has had a successful public run in London in December 2022; from this we have written on the nature and value of environmental data in a national magazine (currently in prep.). Through the ENSEMBLE project (EPSRC Senior Fellowship related to digital technology and environmental change) Prof Blair explored the role of art-science interface, looking at how art can communicate science concepts around a changing environment, and also how art can inspire citizens to engage more with their natural landscape.
Firstly, we will further develop the installation, through lighting and sound design, and host the installation in the North of England, which is traditionally underserved by art. Inspiration for developing the lighting has come from a visit of the artists and scientists to the JASMIN data centre. This installation will demonstrate how art can be used to communicate themes of the digital environment to the public including the process of modelling and forecasting, the value of data, and the importance of addressing data gaps. Instead communicating these themes through traditional means (i.e. talks/maps), in the installation we use poetry to discuss these challenges. We have found that this has been an effective we for people to engage with these issues, with engaging conversations striking up between scientists and visitors as they reflect on what they have experienced. Through the event, we will conduct an evaluation to evidence its impact on participants.
Testimonials from first exhibition
“As someone who works with datasets it was such a new and thought-provoking perspective…It is a bit weird and arty, and as scientists we could easily dismiss it as a bit silly. But being there in the woods, listening to the dataset was such an immersive experience. It explores some great themes that will really stick with me.”
“I was thrilled by the poem, how powerful it was to animate a database and make it so likeable – and the wider message was vital and useful. I had no idea that citizen recording was useful and I will start doing this.”
Dataset’s Dream has exhibited in London and combines painted glass sculpture, spoken word poetry and lights to explore the nature of data.
Screenshot of an animated artistic reflection by Daksha Patel about ‘digital twins’ to model Morecombe Bay, as part of the ENSEMBLE project.
Secondly, alongside the installation we will run a training workshop for UKRI researchers, developed and delivered by artists and scientists, to build capacity to work with artists and develop creative engagements. The trainers will include scientists with experience working with artists (Gordon, Tom and Michael), and artists experienced working with scientists on the DECIDE and ENSEMBLE projects (we have confirmed the artists Bryony Benge-Abbot, and Rob and Harriet Fraser want to be involved). The training will begin one evening during which attendees explore the “Dataset’s Dream” installation and have discussions with the artists and scientists involved. The following day, the course will cover the benefits that art-science collaborations can bring, the creative process, as well as practical considerations such as budgeting and funding. We will also provide time for artists to work with attendees to identify and develop art-science concepts around the attendees’ own research. The value of combining the training with the installation is the opportunity for immersive engagement and reflection, rather than solely ‘theoretical’ training. Attendees will leave confident in how to create their own art-science collaborations and aware of the next steps they can take.
Thirdly, we run a second training event at the CDE conference 2023 as a 1.5 hour workshop. The first half will be a condensed version of the one-day workshop, giving an overview of the value of art-science collaborations, and how they work in practise. The second half of the workshop will be a panel discussion exploring scientists’ and artists’ experiences of these collaborations, the benefits and the challenges. The panel discussion will be curated, with time for audience questions at the end. This session will be recorded and shared openly online.
Across all of these activities we will be maximising impact and reach through complimentary activities. These activities will highlight themes of ‘digital environment’ themes, as per CDE and the NERC Digital Strategy, including what is gained and what is lost as the environment is digitised, which is vital in public support for this work. The installation will be supported by professional PR and marketing to maximise footfall and to maximise the potential for articles in the media about the exhibition. We will also collect images of the event that will be used to compliment all our communications. We already have a film created that includes interviews with the artists and the scientists involved in the project which we will also promote during this phase of the project. We will write a blog piece that summarises the work around the installation, giving a reflection on this project from a scientist’s point of view. This will be shared via the CDE blog, with the option to additionally share it as a blog on the CEEDS site (with both Gordon and Tom being in the leadership team). All staff involved will use their social media channels to promote the events, making use of the professional images and videos. The impact of the training activities will be amplified by recording the session at DG23. This session will be an abridged version of the full 1-day training event with a panel discussion. This will be made available on the CDE website, as well as Youtube, alongside any materials from the 1-day workshop that may be of interest.
| Principal Investigators |
|---|
| Dr Tom August (UK Centre for Ecology & Hydrology, CDE Expert member tomaug@ceh.ac.uk |
| Michael Pocock (UK Centre for Ecology & Hydrology michael.pocock@ceh.ac.uk |
| Prof. Gordon Blair (UK Centre for Ecology & Hydrology, CDE Expert member GBlair@ceh.ac.uk |
| Value: £21,175 |
Top of page