Identifying and testing adaptive management options to increase river catchment system resilience using a Bayesian Network model

Kerr j. Adams, Marc j. Metzger, Rachel c. Helliwell, Nicola Melville, Christopher j. a. Macleod, Jim Pritchard, Katie Edwards, Miriam Glendell

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

The cumulative impacts of future climatic and socioeconomic change threaten the ability of freshwater catchments to provide essential ecosystem services. Stakeholders who manage freshwaters require decision-support tools that increase their understanding of catchment system resilience and support the appraisal of adaptive management options to inform decision-making. Our research aims to test the ability of a Bayesian Network model to identify adaptive management scenarios and test their effectiveness across future pathways to 2050. Using the predominantly arable river Eden catchment (320 km2) in eastern Scotland as a case study, we invited stakeholders from multiple sectors to participate in a series of workshops aimed at addressing water quality issues and achieving good ecological status in the catchment both now and in the future. Our participatory methods helped stakeholders overcome multiple layers of complexity and uncertainty associated with future-focused water management. Outputs of a Bayesian Network model simulated both current and future catchment resilience to inform the identification of six management scenarios. The effectiveness of each management scenario was tested using the Bayesian Network model. Two adaptive management scenarios increased catchment resilience and helped achieve good ecological status; a ‘Best Available Technology’ scenario, including aerobic granular sludge treatment, and a management scenario focused on ‘Resource Centre’, including phosphorus recovery from wastewater treatment works and constructed lagoons for crop irrigation. Stakeholders were interested in a 'Nature Based' management scenario including options such as wetland wastewater treatment methods and rural sustainable drainage systems, which improved water quality in the catchment, but had lower certainty in achieving desired outcome. Findings led to a recognition that innovative and collaborative action was required to improve current and future freshwater conditions.
Original languageEnglish
Article number62
JournalDiscover Geoscience
Volume2
Issue number1
DOIs
Publication statusPublished - 30 Sept 2024

Fingerprint

Dive into the research topics of 'Identifying and testing adaptive management options to increase river catchment system resilience using a Bayesian Network model'. Together they form a unique fingerprint.

Cite this