Joint Special Issue on Good Modelling Practice

Collaborating Journals: Socio-Environmental Systems Modelling (SESMO), Environmental Modelling and Software (EMS), and Ecological Modelling (ECOMOD)

Modelling, computational, conceptual or otherwise, has become an indispensable tool for dealing with complex socio-environmental systems (SES), whether the purpose be system understanding, prediction or social learning. It is crucial therefore that any modelling undertaken be adequate in its practices for the purposes. But despite early advances this century, guidance and protocols for good modelling practice (GMP) in different settings have been lacking.

This joint special issue intends to provide a platform for visible and ongoing attention to what ought to be the current standard(s) for an appropriate modelling protocol that considers uncertainty in all its facets and promotes transparency in the quest for robust and reliable results. It aims to bring together and highlight work that develops, applies, or evaluates procedures for a trustworthy modelling workflow or that investigates good modelling practices for particular aspects of the workflow. We invite research that aims to improve the scientific basis of the entire modelling chain and places good modelling practice in focus. Particular aspects of GMP might include (but are not limited to) contributions on:

  1. Developing modelling conceptual maps, protocols and workflows
  2. Benchmarking model results
  3. Developing robust parameterization, calibration and evaluation frameworks
  4. Going beyond common metrics in assessing model performance and realism, including qualitative methods
  5. Conducting controlled model comparison studies
  6. Investigating subjectivity and reflexivity along the modelling chain, and addressing model fitness for purpose
  7. Identifying and prioritising sources of uncertainty and/or investigating uncertainty propagation along the modelling chain, and data acquisition planning for reducing uncertainty
  8. Communicating model results and their uncertainty to end users of model results
  9. Evaluating implications of model limitations and identifying priorities for future model development
  10. Examples of developing FAIR principles for digital assets in the modelling chain (Findable, Accessible, Interoperable and Reusable – see https://www.comses.net/education/responsible-practices/)

Note that interpretation of what is an SES is considered widely. Systems for example may include ecological, hydrological, energy, policy, health and social sectors, often a combination of these or others. An aim is to share experiences of GMP across sectors and disciplines.

Which journal to publish in?

Authors can submit to one of the three journals but only one must be chosen. It is envisaged that manuscripts will be reviewed and assessed by the relevant journal selected by the author(s) and Guest Editors will be across all manuscript processes.

Guest editors: Hsiao-Hsuan (Rose) Wang,  Sondoss Elsawah, and Tony Jakeman

Manuscript submission information:

Deadlines for submission

Enquiries and Abstracts of 500 words as soon as possible to any of the three Guest Editors above. Full papers by February 28, 2024

For any queries in submitting your manuscript please contact Tony Jakeman (tony.jakeman@anu.edu.au) for SESMO, Sondoss Elsawah (s.elsawah@adfa.edu.au) for EMS, and Hsiao-Hsuan (Rose) Wang (Hsiaohsuan.Wang@ag.tamu.edu) for ECOMOD, respectively.

All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.

Please ensure you read the Guide for Authors before writing your manuscript: SESMO submission guidelines 

Keywords:

Modelling practices; Integrated assessment and modelling; Socio-ecological systems; Decision support; uncertainty; scaling