Causal Loop Diagrams and Automated Identification of Feedbacks in Economic Systems

<p>Current understanding is fragmented of the environmental, economic, and social processes involved in water quality issues. The fragmentation is particularly evident for coastal water quality, impacted both by local land catchment and larger-scale marine pressures and impacts. Research and policy so far has primarily addressed coastal water quality issues from either a land-based or a sea-based perspective, which does not support integrated management of the coupled land-coast-sea systems affecting coastal waters. For example, mitigation measures for improving the severe Baltic Sea eutrophication have mostly focused on land-based drivers, and not yet managed to sufficiently improve coastal or marine water quality. The strong human dimension involved in these water quality issues also highlights a need for participatory approaches to facilitate knowledge integration and drive synergistic strategic planning for sustainable management of coastal water quality. Considering the Swedish water management district of Northern Baltic Proper, including its main Norrstr&#246;m drainage basin and surrounding coastal catchment areas and waters, this study has used a participatory approach to evaluate various land-sea water quality interactions and associated management measures. A causal loop diagram has been co-created with different stakeholder groups, following a problem-oriented system thinking approach. This has been further used in fuzzy-cognitive scenario analysis to assess integrated land-coast-sea system behavior under changing human pressures and hydro-climatic conditions. Results show that synergy of several catchment measures is needed to improve coastal water quality locally, while cross-system/sector cooperation is also needed among all contributing national catchments to mitigate coastal eutrophication at the scale of the whole Baltic Sea. Furthermore, large-scale hydro-climatic changes and long-lived nutrient legacy sources also need to be accounted for in water quality management strategies and measures. System dynamics modelling, based on co-created causal loop diagrams and fuzzy-cognitive scenario analysis like those developed in this study, can support further quantification and analysis of the impacts of various mitigation strategies and measures on regional water quality problems and their possible sustainable solutions.</p>

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CHAPTER 3 – Using causal loop diagrams to understand handpump failure in sub-Saharan Africa

Systems Thinking and WASH ◽

10.3362/9781780447483.003 ◽

2019 ◽

pp. 29-58

Author(s):

Elisabeth S. Liddle ◽

Richard A. Fenner

Keyword(s):

Sub Saharan Africa ◽

Causal Loop ◽

Causal Loop Diagrams ◽

Sub Saharan

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Complexity Theory and System Dynamics for Project Risk Management

Advances in IT Personnel and Project Management - Handbook of Research on Leveraging Risk and Uncertainties for Effective Project Management ◽

10.4018/978-1-5225-1790-0.ch008 ◽

2017 ◽

pp. 152-176 ◽

Cited By ~ 1

Author(s):

Robert J. Chapman

Keyword(s):

System Dynamics ◽

Systems Thinking ◽

Complexity Theory ◽

Systems Dynamics ◽

Risk And Uncertainty ◽

Causal Loop ◽

General Systems ◽

Big Picture ◽

Causal Loop Diagrams ◽

Managing Risk

As a consequence of the consensus that projects are growing in complexity from ever ambitious goals there is a perpetual search for methods aimed at pinpointing and describing the source of complexity with the objective of subsequently reducing uncertainty, managing risk and improving project performance. An area of study that has engaged enquiring minds for over fifty years but has not yet been accepted into mainstream project management is the study and application of systems thinking and system dynamics. The purpose of this chapter is to promulgate the view that the mapping of projects as systems should be re-examined as a means of articulating and responding to complexity. The chapter examines general systems theory, systems thinking and systems dynamics with examples of causal loop diagrams as an aid to describe and respond to risk exposure. It includes simple causal loop diagrams as a means of illustrating how risks may be identified and addressed. The emphasis is on seeing the ‘big picture' to avoid gaps and omissions in the management of risk and uncertainty.

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