Identifying and testing adaptive management options to increase catchment resilience using a Bayesian Network.

The cumulative impacts of future climatic and socio-economic change threaten the ability of freshwater catchments to provide valuable socio-ecological services. Stakeholders who manage freshwater resources require decision-support tools that increase their understanding of catchment system resilience and support the appraisal of adaptive management options. Our research aims to address the following question: Can a Bayesian Network (BN) model support stakeholders in the identification and testing of adaptive management options that help increase catchment system resilience to the impacts of cumulative future change? Using the predominantly arable Eden catchment (320km²), in eastern Scotland as a case study, we invited stakeholders from multiple sectors to participate in a series of workshops aimed at addressing water resource issues and achieving good ecological status in the catchment both now and in the future. Outputs of a BN model that simulates both current and future catchment resilience were presented to stakeholders. Outputs informed the identification of adaptive management options which were grouped into five management scenarios. The effectiveness of each management scenario in increasing catchment system resilience was tested using the BN model to support the appraisal of each management scenario by participating stakeholders. Two optimal adaptive management scenarios were identified; the first optimal management scenario focussed on predominantly nature-based management options such as wetland wastewater treatment methods and rural sustainable drainage systems. The second optimal scenario focussed on resource recovery, including phosphorus recovery from wastewater treatment works and constructed lagoons for crop irrigation. Outputs of the model describing the resilience of the catchment initiated conversations about feasible management options that could be applied across sectors to reduce risk and increase catchment resilience. The ability of the BN model to test and compare adaptive management scenarios in a time-effective manner was seen as an advantage in comparison to conventional methods.