Abstract. The resilience of river catchments and the vital socio-ecological services they provide are threatened by the cumulative impacts of future climatic and socio-economic change. Stakeholders who manage freshwaters require tools for increasing their understanding of catchment system resilience when making strategic decisions. However, unravelling causes, effects and interactions in complex catchment systems is challenging, typically leading to different system components being considered in isolation. In this research, we tested a five-stage participatory method for developing a Bayesian network (BN) model to simulate the resilience of the Eden catchment in eastern Scotland to future pressures in a single transdisciplinary holistic framework. The five-stage participatory method involved co-developing a BN model structure by conceptually mapping the catchment system and identifying plausible climatic and socio-economic future scenarios to measure catchment system resilience. Causal relationships between drivers of future change and catchment system nodes were mapped to create the BN model structure. Appropriate baseline data to define and parameterise nodes that represent the catchment system were identified with stakeholders. The BN model measured the impact of diverse future change scenarios to a 2050 time horizon. We applied continuous nodes within the hybrid equation-based BN model to measure the uncertain impacts of both climatic and socio-economic change. The BN model enabled interactions between future change factors and implications for the state of five capitals (natural, social, manufactured, financial and intellectual) in the system to be considered, providing stakeholders with a holistic catchment-scale approach to measure the resilience of multiple capitals and their associated resources. We created a credible, salient and legitimate BN model tool for understanding the cumulative impacts of both climatic and socio-economic factors on catchment resilience based on stakeholder evaluation. BN model outputs facilitated stakeholder recognition of future risks to their primary sector of interest, alongside their interaction with other sectors and the wider system. Participatory modelling methods improved the structure of the BN through collaborative learning with stakeholders while providing stakeholders with a strategic systems-thinking approach for considering river basin catchment resilience

Abstract. The resilience of river catchments and the vital socio-ecological services they provide are threatened by the cumulative impacts of future climatic, land use and socio-economic change. Stakeholders who manage freshwaters require tools for increasing their understanding of catchment system resilience when making strategic decisions. However, unravelling causes, effects and interactions in complex catchment systems is challenging, typically leading to different system components being considered in isolation. In this research, we tested a five-stage participatory method for developing a BN model to simulate the resilience of the Eden catchment in eastern Scotland to future pressures in a single trans-disciplinary holistic framework. The five-stage participatory method involved co-developing a BN model structure by conceptually mapping the catchment system and identifying plausible climatic and socio-economic future scenarios to measure catchment system resilience. Causal relationships between drivers of future change and catchment system nodes were mapped to create the BN model structure. Appropriate baseline data to define and parameterise nodes that represent the catchment system were identified with stakeholders. The BN model measured the impact of diverse future change scenarios to a 2050 time-horizon. We applied continuous nodes within the hybrid equation-based BN model to measure the uncertain impacts of both climatic and socio-economic change. The BN model enabled interactions between future change factors and implications for the state of five capitals (natural, social, manufactured, financial and intellectual) in the system to be considered providing stakeholders with a holistic catchment scale approach to measure the resilience of multiple capitals and their associated resources. We created a credible, salient and legitimate BN model tool for understanding the cumulative impacts of both climatic and socio-economic factors on catchment resilience based on stakeholder evaluation. BN model outputs facilitated stakeholder recognition of future risks to their primary sector of interest, alongside their interaction with other sectors and the wider system. Participatory modelling methods improved the structure of the BN through collaborative learning with stakeholders, while providing stakeholders with a strategic systems-thinking approach for considering river basin catchment resilience.

No abstract

<p>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 (320km<sup>2</sup>), 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.</p>