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Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex
Sondoss Elsawah1, Joseph H A Guillaume2, Tatiana Filatova3
1Integrated Catchment Assessment and Management (iCAM), Fenner School of Environment and Society, the Australian National University, Australia; National Centre for Groundwater Research and Training (NCGRT), School of the Environment, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia; University of New South Wales, School of Engineering and Information Technology, Australian Defence Force Academy, NorthCott Drive, Campbell, Canberra, Australia.
Abstract:
This paper aims to contribute to developing better ways for incorporating essential human elements in decision making processes for modelling of complex socio-ecological systems. It presents a step-wise methodology for integrating perceptions of stakeholders (qualitative) into formal simulation models (quantitative) with the ultimate goal of improving understanding and communication about decision making in complex socio-ecological systems. The methodology integrates cognitive mapping and agent based modelling. It cascades through a sequence of qualitative/soft and numerical methods comprising: (1) Interviews to elicit mental models; (2) Cognitive maps to represent and analyse individual and group mental models; (3) Time-sequence diagrams to chronologically structure the decision making process; (4) All-encompassing conceptual model of decision making, and (5) computational (in this case agent-based) Model. We apply the proposed methodology (labelled ICTAM) in a case study of viticulture irrigation in South Australia. Finally, we use strengths-weakness-opportunities-threats (SWOT) analysis to reflect on the methodology. Results show that the methodology leverages the use of cognitive mapping to capture the richness of decision making and mental models, and provides a combination of divergent and convergent analysis methods leading to the construction of an Agent Based Model.
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