NI: DEPICTION - DEveloPing an International CollaboraTIon to advance community-based, Open and FAIR eNvironmental modelling
Lead Research Organisation:
UK CENTRE FOR ECOLOGY & HYDROLOGY
Department Name: Pollution (Lancaster)
Abstract
Addressing the broadest and most pressing issues facing the natural world requires a holistic understanding of the complex interactions that govern it. This requires the use of models - mathematical descriptions of the world - to explain observed trends, answer "what if?" questions and predict future trajectories. As these models evolve to match our increasing understanding of the natural world, so must the research software infrastructure that underpins them. Amongst other things, this software infrastructure is responsible for helping us link models together to assess the bigger picture, promoting trust in scientific results by making model results reproducible, letting us easily use models on the latest high-performance computers, providing a consistent computational environment and access to data to help developers collaborate, and providing interactive visualisations and apps of model results to a broader audience.
To use an analogy - just as analytical scientists require access to laboratories full of high-tech equipment to perform scientific experiments, computational scientists require access to virtual laboratories full of the latest software infrastructure to perform computational experiments.
Software infrastructure and communities have developed to begin to meet these challenges across the globe, and partners in this project have been leading these developments for several decades. However, these software and communities are currently independent and constrained, either by geography or to particular scientific domains. The goal of this project is to unite this infrastructure around an international community of practice, providing much needed international cohesion across environment modelling software infrastructure. United, this software has the potential to be truly transformative, enabling collaborative innovation where, for example: models can be readily deployed to and dynamically linked within the cloud; physics-based, statistical and data science models can work seamlessly together to provide a step change in how realistically our models predict the natural world, and; results can be shared easily to non-developers via interactive apps.
We will showcase this transformative potential through a case study, which will predict the transport of microplastics in the environment from their release, through waterways and the terrestrial environment, out to the ocean. Plastic pollution is widespread and global, with plastic debris present in all parts of the environment, from deep ocean trenches to remote mountains. It poses a potentially significant risk to both the environment and ourselves. Despite this, the modelling of microplastic transport in the environment is in its infancy, and whilst models of individual compartments (rivers, oceans) exist, there are no frameworks capable of predicting high-resolution microplastic transport from source to sea. Our case study will solve this, at the same time as demonstrating the benefits yielded by our united software infrastructure. This infrastructure will underpin the case study, providing the tools needed to link together the hydrological, microplastic transport and coastal ocean models of which it comprises, and providing a collaborative virtual environment to power it. The result will be a modelling framework that not only offers a step change in our ability to predict microplastic transport from source to sea, but that is flexible enough to be adapted to different chemical classes, thereby making a significant contribution to our efforts towards a zero pollution society.
We are a new partnership who collectively unites world-leading expertise in software infrastructure development, community building, hydrology, chemical fate modelling and oceanography. All partners are committed to securing a long-term, self-sustaining collaboration that will ultimately help advance environmental modelling far beyond the scope of this project.
To use an analogy - just as analytical scientists require access to laboratories full of high-tech equipment to perform scientific experiments, computational scientists require access to virtual laboratories full of the latest software infrastructure to perform computational experiments.
Software infrastructure and communities have developed to begin to meet these challenges across the globe, and partners in this project have been leading these developments for several decades. However, these software and communities are currently independent and constrained, either by geography or to particular scientific domains. The goal of this project is to unite this infrastructure around an international community of practice, providing much needed international cohesion across environment modelling software infrastructure. United, this software has the potential to be truly transformative, enabling collaborative innovation where, for example: models can be readily deployed to and dynamically linked within the cloud; physics-based, statistical and data science models can work seamlessly together to provide a step change in how realistically our models predict the natural world, and; results can be shared easily to non-developers via interactive apps.
We will showcase this transformative potential through a case study, which will predict the transport of microplastics in the environment from their release, through waterways and the terrestrial environment, out to the ocean. Plastic pollution is widespread and global, with plastic debris present in all parts of the environment, from deep ocean trenches to remote mountains. It poses a potentially significant risk to both the environment and ourselves. Despite this, the modelling of microplastic transport in the environment is in its infancy, and whilst models of individual compartments (rivers, oceans) exist, there are no frameworks capable of predicting high-resolution microplastic transport from source to sea. Our case study will solve this, at the same time as demonstrating the benefits yielded by our united software infrastructure. This infrastructure will underpin the case study, providing the tools needed to link together the hydrological, microplastic transport and coastal ocean models of which it comprises, and providing a collaborative virtual environment to power it. The result will be a modelling framework that not only offers a step change in our ability to predict microplastic transport from source to sea, but that is flexible enough to be adapted to different chemical classes, thereby making a significant contribution to our efforts towards a zero pollution society.
We are a new partnership who collectively unites world-leading expertise in software infrastructure development, community building, hydrology, chemical fate modelling and oceanography. All partners are committed to securing a long-term, self-sustaining collaboration that will ultimately help advance environmental modelling far beyond the scope of this project.
Organisations
- UK CENTRE FOR ECOLOGY & HYDROLOGY (Lead Research Organisation)
- University of Colorado Boulder (Collaboration)
- Netherlands eScience Center (Collaboration, Project Partner)
- Delft University of Technology (TU Delft) (Collaboration)
- Community Surface Dynamics Modeling Sys. (Project Partner)
- Delft University of Technology (Project Partner)
- University of Massachusetts Dartmouth (Project Partner)
Publications

MacLeod M
(2023)
Computational models to confront the complex pollution footprint of plastic in the environment.
in Nature computational science
Title | Software tools to faciliate integrated environmental modelling |
Description | The DEPICTION project has brought together communities working on software tools to faciliate environmental modelling. We are showcasing the combined use of these software tools, such as the use of CSDMS Workbench tools in DataLabs. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2024 |
Provided To Others? | Yes |
Impact | Research impacts: Expedites environmental model development and facilitates model integration, thereby reducing "time to science". Societal impacts: Broadly impactful to any sector requiring environmental models. |
Description | DEPICTION |
Organisation | Delft University of Technology (TU Delft) |
Country | Netherlands |
Sector | Academic/University |
PI Contribution | Software tools that enable integrated environmental modelling, such as UKCEH-developed DataLabs (https://datalab.datalabs.ceh.ac.uk/). Chairing of webinars in the CSDMS webinars series. |
Collaborator Contribution | Software tools that enable integrated environmental modelling, such as the CSDMS Workbench tools (https://csdms.colorado.edu/wiki/Workbench). Access to CSDMS community for disseminating research, including opportunity to chair CSDMS webinars. |
Impact | UKCEH has hosted four CSDMS webinars as "Euro-CSDMS" webinars, helping to strengthen the international reach of respective communities from project partners, such as the CSDMS community and CEEDS (Centre of Excellence in Environmental Data Science). |
Start Year | 2022 |
Description | DEPICTION |
Organisation | Netherlands eScience Center |
Country | Netherlands |
Sector | Charity/Non Profit |
PI Contribution | Software tools that enable integrated environmental modelling, such as UKCEH-developed DataLabs (https://datalab.datalabs.ceh.ac.uk/). Chairing of webinars in the CSDMS webinars series. |
Collaborator Contribution | Software tools that enable integrated environmental modelling, such as the CSDMS Workbench tools (https://csdms.colorado.edu/wiki/Workbench). Access to CSDMS community for disseminating research, including opportunity to chair CSDMS webinars. |
Impact | UKCEH has hosted four CSDMS webinars as "Euro-CSDMS" webinars, helping to strengthen the international reach of respective communities from project partners, such as the CSDMS community and CEEDS (Centre of Excellence in Environmental Data Science). |
Start Year | 2022 |
Description | DEPICTION |
Organisation | University of Colorado Boulder |
Department | Institute of Arctic and Alpine Research |
Country | United States |
Sector | Academic/University |
PI Contribution | Software tools that enable integrated environmental modelling, such as UKCEH-developed DataLabs (https://datalab.datalabs.ceh.ac.uk/). Chairing of webinars in the CSDMS webinars series. |
Collaborator Contribution | Software tools that enable integrated environmental modelling, such as the CSDMS Workbench tools (https://csdms.colorado.edu/wiki/Workbench). Access to CSDMS community for disseminating research, including opportunity to chair CSDMS webinars. |
Impact | UKCEH has hosted four CSDMS webinars as "Euro-CSDMS" webinars, helping to strengthen the international reach of respective communities from project partners, such as the CSDMS community and CEEDS (Centre of Excellence in Environmental Data Science). |
Start Year | 2022 |
Description | CSDMS Webinars |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | UKCEH has hosted three CSDMS webinars as part of this project (with a fourth scheduled for April 2024, and more in Autumn 2024). Approximately 150 attendees with more watching publically available recordings of the webinars. Recordings available here: https://csdms.colorado.edu/wiki/Webinars |
Year(s) Of Engagement Activity | 2023,2024 |
URL | https://csdms.colorado.edu/wiki/Webinars |