SECURE- network for modelling environmental change
Lead Research Organisation:
University of Glasgow
Department Name: School of Mathematics & Statistics
Abstract
SECURE is a network of statisticians, modellers and environmental scientists and our aim is to grow a shared vision of how to describe and quantify environmental change to assist in decision making. Understanding and forecasting environmental changes are crucial to the development of strategies to mitigate against the impacts of future events. Communications and decision making around environmental change are sometimes troubled by issues concerning the weight of evidence, the nature and size of uncertainties and how both are described. Evidence for environmental change comes from a number of sources, but key to this proposal is the optimal use of data (from observational, regulatory monitoring and earth observations platforms such as satellites and mobile sensors) and models (process and statistical). A robust and reliable evidence base is key in the decision making process, informed by powerful statistical models and the best data. This proposal will deliver the statistical tools to support decision making.
Many environmental challenges related to change require statistical modelling and inferential tools to be developed to understand the drivers and system responses which may be direct or indirect and linked by feedback and lags. The character of environmental data is changing as new technologies (e.g. sensor networks offering high resolution data streams) are developed and become more widely accessible. Emerging sensor technology is able to deliver enhanced dynamic detail of environmental systems at unprecedented scale and . There is also an increasing public engagement with environmental science, through citizen science. Increasing use of citizen science observatories will present new statistical challenges, since the sampling basis of such observations will most likely be preferential and not directed, be of varying quality and collected with different effort. Fusion of the different streams of data will be challenging but essential in terms of informing society and regulators alike about change. Linkage of the different data sources, and the challenges of dealing with big data, in the environmental sphere lie in drawing together diverse, high-throughput data sources, analysing, aggregating and integrating the signals with models and then ultimately using the data-model system to address complex and shifting environmental change issues in support of decision making. Key to success lies in generating digestible outputs which can be disseminated and critiqued across academia, policy-makers and other stakeholders. In climate change, food security, ecosystem resilience, sustainable resource use, hazard warning and disaster management there are new high-volume data sources, including crowd sourced streams, which present problems and untapped opportunities around data management, synthesis, communication and real-time decision-support.
Our research will involve: improving modelling and communication tools concerning uncertainty and variability, which are ubiquitous in many environmental data sources; developing and extending modelling capabilities to deal with multi-scale issues, specifically integrating over the different spatial and temporal scales of the data streams, and the derived timescales of model outputs; exploring the power and limitations of recent statistical innovations applied to environmental change issues and finally reflecting on new technologies for visualisation and communication.
Many environmental challenges related to change require statistical modelling and inferential tools to be developed to understand the drivers and system responses which may be direct or indirect and linked by feedback and lags. The character of environmental data is changing as new technologies (e.g. sensor networks offering high resolution data streams) are developed and become more widely accessible. Emerging sensor technology is able to deliver enhanced dynamic detail of environmental systems at unprecedented scale and . There is also an increasing public engagement with environmental science, through citizen science. Increasing use of citizen science observatories will present new statistical challenges, since the sampling basis of such observations will most likely be preferential and not directed, be of varying quality and collected with different effort. Fusion of the different streams of data will be challenging but essential in terms of informing society and regulators alike about change. Linkage of the different data sources, and the challenges of dealing with big data, in the environmental sphere lie in drawing together diverse, high-throughput data sources, analysing, aggregating and integrating the signals with models and then ultimately using the data-model system to address complex and shifting environmental change issues in support of decision making. Key to success lies in generating digestible outputs which can be disseminated and critiqued across academia, policy-makers and other stakeholders. In climate change, food security, ecosystem resilience, sustainable resource use, hazard warning and disaster management there are new high-volume data sources, including crowd sourced streams, which present problems and untapped opportunities around data management, synthesis, communication and real-time decision-support.
Our research will involve: improving modelling and communication tools concerning uncertainty and variability, which are ubiquitous in many environmental data sources; developing and extending modelling capabilities to deal with multi-scale issues, specifically integrating over the different spatial and temporal scales of the data streams, and the derived timescales of model outputs; exploring the power and limitations of recent statistical innovations applied to environmental change issues and finally reflecting on new technologies for visualisation and communication.
Planned Impact
Beneficiaries of the research will include the network members and their organisations, which include
academia (both mathematical and environmental sciences)
the international scientific communities (such as IPCC, UNEP, EEA)
the main environmental agencies within the UK;
utility companies such as Scottish Water
local government
environmental consultancy firms such as Ricardo AEA.
The wider public will also benefit from the research.
Benefits will include improved modelling and communication tools concerning uncertainty and variability, which are ubiquitous in many environmental data sources; new developments and extensions to modelling capabilities to deal with multi-scale issues, specifically integrating over the different spatial and temporal scales of the data streams, and the derived timescales of model outputs; improved understanding of the power and limitations of recent statistical innovations applied to environmental change issues and finally greater reflection and understanding of the impact of new technologies for visualisation and communication.
Our network and its research has the potential to:
(1) improve the scientific knowledge base for decision making in the face of environmental change (whether in terms of mitigation or adaptation), thus contributing to delivery of public services and environmental policy. This is achievable over the lifetime of the network, but also in the short term. Our research will inform on the scale of environmental changes (both temporally and spatially).
(2) better quantify risks due to climate and environmental change and thus resulting in improved management. Economic and societal impacts of environmental change are potentially very large, probabilistic based, and thus lend themselves to statistical modelling.
(3) better inform citizens concerning environmental change issues, to encourage reflection and debate. Through our outreach programme, we will attempt to ensure that our communications are fit for purpose and timely.
(4) encourage the development of much stronger multi-disciplinary connections. This will be immediate.
(5) better inform policy development.
Staff engaged in the network will develop strong team working skills, certainly management skills and will also acquire communication (not simply scientific, but also knowledge transfer) skills. Everyone engaged in the network will acquire deeper understanding the environmental and statistical challenges.
academia (both mathematical and environmental sciences)
the international scientific communities (such as IPCC, UNEP, EEA)
the main environmental agencies within the UK;
utility companies such as Scottish Water
local government
environmental consultancy firms such as Ricardo AEA.
The wider public will also benefit from the research.
Benefits will include improved modelling and communication tools concerning uncertainty and variability, which are ubiquitous in many environmental data sources; new developments and extensions to modelling capabilities to deal with multi-scale issues, specifically integrating over the different spatial and temporal scales of the data streams, and the derived timescales of model outputs; improved understanding of the power and limitations of recent statistical innovations applied to environmental change issues and finally greater reflection and understanding of the impact of new technologies for visualisation and communication.
Our network and its research has the potential to:
(1) improve the scientific knowledge base for decision making in the face of environmental change (whether in terms of mitigation or adaptation), thus contributing to delivery of public services and environmental policy. This is achievable over the lifetime of the network, but also in the short term. Our research will inform on the scale of environmental changes (both temporally and spatially).
(2) better quantify risks due to climate and environmental change and thus resulting in improved management. Economic and societal impacts of environmental change are potentially very large, probabilistic based, and thus lend themselves to statistical modelling.
(3) better inform citizens concerning environmental change issues, to encourage reflection and debate. Through our outreach programme, we will attempt to ensure that our communications are fit for purpose and timely.
(4) encourage the development of much stronger multi-disciplinary connections. This will be immediate.
(5) better inform policy development.
Staff engaged in the network will develop strong team working skills, certainly management skills and will also acquire communication (not simply scientific, but also knowledge transfer) skills. Everyone engaged in the network will acquire deeper understanding the environmental and statistical challenges.
Organisations
- University of Glasgow (Lead Research Organisation)
- UNIVERSITY OF EXETER (Collaboration)
- Engineering and Physical Sciences Research Council (EPSRC) (Collaboration)
- Past Earth Network (Collaboration)
- NatureScot (Scottish Natural Heritage) (Project Partner)
- Scottish Environment Protection Agency (Project Partner)
- Met Office (Project Partner)
- Agri Food and Biosciences Institute (Project Partner)
- BioSS (Biomaths and Stats Scotland) (Project Partner)
- Environment Agency (Project Partner)
- Scottish Water (United Kingdom) (Project Partner)
- British Geological Survey (Project Partner)
- NERC CEH (Up to 30.11.2019) (Project Partner)
- Ricardo AEA (United Kingdom) (Project Partner)
People |
ORCID iD |
Marian Scott (Principal Investigator) | |
Susan Waldron (Co-Investigator) |
Publications
Beaulieu C
(2018)
Distinguishing Trends and Shifts from Memory in Climate Data
in Journal of Climate
Lee D
(2019)
Estimating the health impact of air pollution in Scotland, and the resulting benefits of reducing concentrations in city centres.
in Spatial and spatio-temporal epidemiology
Leeson A
(2018)
Extreme temperature events on Greenland in observations and the MAR regional climate model
in The Cryosphere
Gallacher K
(2017)
Flow-directed PCA for monitoring networks.
in Environmetrics
Young DM
(2018)
Spatial models with covariates improve estimates of peat depth in blanket peatlands.
in PloS one
Description | Each feasibility project has allowed a small team of academics and others (agencies,etc) to work together on a specific project, implementing new statistical methods, or in knowledge exchange with the other organisations, thereby demonstrating the value of the project and the network in delivering new statistical methodology. |
Exploitation Route | a number of full grant applications have been developed, workshops held. |
Sectors | Aerospace Defence and Marine Agriculture Food and Drink Energy Environment |
URL | http://www.gla.ac.uk/research/az/secure/ |
Description | our network developed a series of use cases involving non academic partners, and at least two led to REF 2021 impact case studies- including on water and air quality. |
First Year Of Impact | 2021 |
Sector | Agriculture, Food and Drink,Digital/Communication/Information Technologies (including Software),Energy,Environment,Healthcare |
Impact Types | Economic Policy & public services |
Description | advice on air quality modelling |
Geographic Reach | Local/Municipal/Regional |
Policy Influence Type | Influenced training of practitioners or researchers |
Impact | our advice is being used in the creation of environmental indicators and the creation of low emission zones |
Description | design of optimal river network design |
Geographic Reach | National |
Policy Influence Type | Influenced training of practitioners or researchers |
Impact | the EA are now beginning to use the software tools developed to explore impacts of changes to network monitoring designs. |
Description | river network design |
Geographic Reach | National |
Policy Influence Type | Influenced training of practitioners or researchers |
Impact | this network design issue is critical to allow that less resources may be used but which still delivers the same environmental protection |
Description | A digital environment for water resources |
Amount | £228,806 (GBP) |
Funding ID | NE/T005564/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 11/2019 |
End | 05/2021 |
Description | Delivering a Climate Resilient City through City-University Partnership: Glasgow as a Living Lab Accelerating Novel Transformation (GALLANT) |
Amount | £10,370,235 (GBP) |
Funding ID | NE/W005042/1 |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 01/2022 |
End | 01/2027 |
Description | Developing statistical downscaling to improve water quality understanding and management in the Ramganga sub-basin |
Amount | £461,314 (GBP) |
Funding ID | EP/T003669/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2019 |
End | 06/2022 |
Description | GCU studentship |
Amount | £20,000 (GBP) |
Organisation | Glasgow Caledonian University |
Sector | Academic/University |
Country | United Kingdom |
Start | 08/2018 |
End | 09/2019 |
Description | GU IAA |
Amount | £25,000 (GBP) |
Organisation | University of Glasgow |
Sector | Academic/University |
Country | United Kingdom |
Start | 07/2017 |
End | 02/2018 |
Description | Glasgow Caledonian University studentship fund |
Amount | £80,000 (GBP) |
Organisation | Glasgow Caledonian University |
Sector | Academic/University |
Country | United Kingdom |
Start | 08/2018 |
End | 09/2021 |
Description | training funds |
Amount | £10,000 (GBP) |
Organisation | Scottish Environment Protection Agency |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2015 |
End | 03/2016 |
Title | network design |
Description | as an example in one of the funded feasibility projects, an R tool and training material have been developed to model river networks and also to consider the effect of re-design of such networks. In another feasibility project, a new R library has been developed for the identification of changepoints in environmental time series. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2016 |
Provided To Others? | Yes |
Impact | the R packages are widely available and free to use. |
Title | Spatial models with covariates improve estimates of peat depth in blanket peatlands |
Description | Dataset to underpin the associated publication. |
Type Of Material | Database/Collection of data |
Year Produced | 2018 |
Provided To Others? | Yes |
Title | Using river network structure to improve estimation of common temporal patterns |
Description | |
Type Of Material | Database/Collection of data |
Year Produced | 2016 |
Provided To Others? | Yes |
Description | Maths Foresees |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Country | United Kingdom |
Sector | Public |
PI Contribution | we are working together for a final all network meeting, to showcase the work supported by the networks and the impacts the feasibility projects have had. |
Collaborator Contribution | jointly publishing calls for funding, jointly supporting national events, helping to organise joint events |
Impact | shared workshops, regular cross-workshop PI and co-I teleconferences. |
Start Year | 2015 |
Description | Past Earth network |
Organisation | Past Earth Network |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | we have shared information about events and feasibility projects, and most recently held a joint conference in january 2018 |
Collaborator Contribution | we have shared information about events and feasibility projects, and most recently held a joint conference in january 2018 |
Impact | we have held a joint conference in January 2018, with REcover |
Start Year | 2016 |
Description | RECOVER |
Organisation | University of Exeter |
Department | Department of Mathematics |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | RECOVER is an EPSRC funded network and I have been invited to join the advisory board |
Collaborator Contribution | none |
Impact | we have supported a workshop to be held in February 2016. |
Start Year | 2015 |
Title | stpca |
Description | the R package stpca is freely available and used to identify common spatiotemporal patterns in river network nutrient levels |
Type Of Technology | Software |
Year Produced | 2017 |
Impact | n/a |
Description | Parliamentary conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | I attended and presented at Brexit: an academic conference and was able to showcase the work being done in WEFWEBs and other projects to parliamentarians, as a result there will be an outreach event held in Glasgow in March 2017. |
Year(s) Of Engagement Activity | 2016 |
Description | TIES2017 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | the network organised an invited session with 3 speakers from those who had received feasibility funds from SECURE. the event was the annual conference of the International Environmetrics society. |
Year(s) Of Engagement Activity | 2017 |
URL | http://www.environmetrics.org/tiesmeetings.html |
Description | conference (Glasgow) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | opening event for the SECURE network to launch the network and publicise its activities. |
Year(s) Of Engagement Activity | 2015 |
URL | http://www.gla.ac.uk/research/az/secure/ |
Description | grand challenge workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | this workshop was intended to bring the SECURE network non academic stakeholders together to set some challenges for the network members, we had 5 challenges identified in the areas of aquaculture, land use, air pollution and catchment management. |
Year(s) Of Engagement Activity | 2017 |
URL | https://www.gla.ac.uk/research/az/secure/news/headline_528531_en.html |
Description | secure sponsored workshops |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Study participants or study members |
Results and Impact | the SECURE sponsored workshops (there have now been 6) have been intended to reach out from the statistical community to a wider audience and to scope out new challenges while forming new partnerships |
Year(s) Of Engagement Activity | 2016 |
URL | http://www.gla.ac.uk/research/az/secure/events/archive/ |
Description | workshop (Glasgow) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Study participants or study members |
Results and Impact | a focused workshop on environment and health, the goal is to identify key research challenges |
Year(s) Of Engagement Activity | 2016 |