Environmental management using a digital twin

Durden, Jennifer M. ORCID: https://orcid.org/0000-0002-6529-9109. 2025 Environmental management using a digital twin. Environmental Science & Policy, 164, 104018. 1, pp. 10.1016/j.envsci.2025.104018

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Official URL: https://doi.org/10.1016/j.envsci.2025.104018

Abstract/Summary

Robust environmental management is based on evidence of ecosystem health and anthropogenic harms gleaned from successful environmental monitoring. Successful monitoring involves the synthesis of observations from a variety of sources to represent a site in its current and past states, the anticipation of future conditions, and communicate the findings to decision-makers for environmental management and other stakeholders; a lack of such synthesis and communication has been identified as a shortcoming in Environmental Impact Assessment. However, a suitable digital platform for this synthesis and communication has not yet been developed. Digital twins, an approach from engineering, may offer a solution with advantages over other approaches traditionally employed in ecosystem monitoring. Here a process and considerations for conducting the use case analysis of a digital twin for environmental monitoring is presented, including identifying users, establishing their requirements, refining use cases based on data practicalities, planning analyses and data/model integrations, and developing the user interface. The process is demonstrated using a case study, developing use cases for an ecological digital twin of a UK Marine Protected Area, which could be generalised as use cases for a digital twin for ecosystem monitoring of a conservation area. Considerations for constructing a digital twin based on these use cases are discussed, including the practicalities of using remotely-sensed biological data; gaps in the scientific, technological and data management capabilities; the role of expertise in adding value beyond simple data collation data; and federation of digital twins. Finally, challenges and benefits to using a digital twin approach to informing conservation management are summarised.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1016/j.envsci.2025.104018
ISSN:	14629011
Additional Keywords:	Evidence-based, Conservation, Protected areas, Environmental impact assessment, Big data, Biodiversity
Date made live:	05 Feb 2025 12:04 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/538857

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1016/j.envsci.2025.104018

ISSN:

14629011

Additional Keywords:

Evidence-based, Conservation, Protected areas, Environmental impact assessment, Big data, Biodiversity

Date made live:

05 Feb 2025 12:04 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/538857