The Emergence of Water Resilience: An Introduction

Plummer, Ryan; Baird, Julia

doi:10.1007/978-3-030-48110-0_1

Cited by 7 publications

(4 citation statements)

References 81 publications

(93 reference statements)

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“…Water is shared between competing stakeholders and aquatic ecosystems that also rely on clean water (Falkenmark, 2003). Hence, to ensure resilient water resources, an understanding of the complexity of socio-ecological systems is required (Pahl-Wostl et al, 2011;Plummer and Baird, 2021).…”

Section: Introductionmentioning

confidence: 99%

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

Adams

Macleod

Metzger

et al. 2023

Hydrol. Earth Syst. Sci.

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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

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Section: Introductionmentioning

confidence: 99%

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

Adams

Macleod

Metzger

et al. 2023

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Approaches to scholarship on water management and governance include (but are certainly not limited to) integrated water resources management (e.g., Biswas 2008), collaborative governance (e.g., Bodin 2017), adaptive comanagement (Armitage et al 2007), adaptive water governance (e.g., Pahl-Wostl et al 2012, Cosens 2018, and water resilience (e.g., Baird and Plummer 2021). Although these approaches vary in their design and focus, shared attributes include advocacy for more diverse participation, strengthened capacity for groups to participate, and increased adaptive capacity (which is the capability to adjust processes and features to better suit present or expected social-ecological changes; Pahl- Wostl 2017, Plummer andBaird 2020). This review focuses on power dynamics that shape deliberative processes in adaptive water governance, although we also recognize that our inquiry is highly relevant to contemporary water and environmental governance research and practice more broadly.…”

Section: Introductionmentioning

confidence: 99%

Power research in adaptive water governance and beyond: a review

McIlwain¹,

Holzer²,

Baird³

et al. 2023

E&S

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Power dynamics are widely recognized as key contributors to poor outcomes of environmental governance broadly and specifically for adaptive water governance. Water governance processes are shifting, with increased emphasis on collaboration and learning. Understanding how power dynamics impact these processes in adaptive governance is hence critical to improve governance outcomes. Power dynamics in the context of adaptive water governance are complex and highly variable and so are power theories that offer potential explanations for poor governance outcomes. This study aimed to build an understanding of the use of power theory in water and environmental governance and establish a foundation for future research by identifying power foci and variables that are used by researchers in this regard. We conducted a systematic literature review using the Web of Science Core Collection and the ProQuest Political Science databases to understand how power is studied (foci, variables of interest, and methods) and which theories are being applied in the water governance field and in the environmental governance field more broadly. The resulting review can serve as a practical reference for (adaptive) water governance inquiries that seek to study power in depth or intend to integrate power considerations into their research. The identified power variables add to a much needed groundwork for research that investigates the role of power dynamics in collaboration and learning processes. Furthermore, they offer a substantive base for empirical research on power dynamics in adaptive water governance.

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“…Water is shared between competing stakeholders and, aquatic ecosystems that also rely on clean water (Falkenmark, 2003). Hence, to ensure resilient water resources, an understanding of the complexity of socio-ecological systems is required (Pahl-Wostl et al, 2011, Plummer andBaird, 2021).…”

Section: Introductionmentioning

confidence: 99%

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

Adams

Macleod

Metzger

et al. 2022

Preprint

View full text Add to dashboard Cite

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.

show abstract

The Emergence of Water Resilience: An Introduction

Cited by 7 publications

References 81 publications

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

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

Power research in adaptive water governance and beyond: a review

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

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