Articles | Volume 27, issue 11
Research article
14 Jun 2023
Research article |  | 14 Jun 2023

Developing a Bayesian network model for understanding river catchment resilience under future change scenarios

Kerr J. Adams, Christopher A. J. Macleod, Marc J. Metzger, Nicola Melville, Rachel C. Helliwell, Jim Pritchard, and Miriam Glendell


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-617', Laura Uusitalo, 27 Jul 2022
    • AC1: 'Reply on RC1', Kerr Adams, 09 Sep 2022
    • AC3: 'Reply on RC1', Kerr Adams, 27 Mar 2023
  • RC2: 'Comment on egusphere-2022-617', Ibrahim Alameddine, 12 Feb 2023
    • AC4: 'Comment on egusphere-2022-617', Kerr Adams, 05 Apr 2023
  • AC2: 'Comment on egusphere-2022-617', Kerr Adams, 27 Mar 2023
  • AC4: 'Comment on egusphere-2022-617', Kerr Adams, 05 Apr 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish as is (20 Apr 2023) by Ibrahim Alameddine
AR by Kerr Adams on behalf of the Authors (30 Apr 2023)  Author's response   Manuscript 
Short summary
We applied participatory methods to create a hybrid equation-based Bayesian network (BN) model to increase stakeholder understanding of catchment-scale resilience to the impacts of both climatic and socio-economic stressors to a 2050 time horizon. Our holistic systems-thinking approach enabled stakeholders to gain new perspectives on how future scenarios may influence their specific sectors and how their sector impacted other sectors and environmental conditions within the catchment system.