Using participatory rapid appraisal and DPSIR approaches for participatory modelling: A case study for groundwater management in South Australia

S. El Sawah, H.A. Guillaume, Michael Mitchell

Research output: Book chapter/Published conference paperConference paper

3 Citations (Scopus)
40 Downloads (Pure)

Abstract

Groundwater management faces a growing number of complexities and uncertainties including: the impacts of climate change, increasing demand, and socio-economic and ecological outcomes of management policies. To help deal with these issues, social learning is an interactive process which brings together scientists, policy makers, and stakeholder groups in order to share their views and develop a common framework for managing the system. This project aims to use a participatory modelling approach to support social learning about the future of groundwater management in South Australia. This paper reports on the data collection and analysis methods used in the scoping phase of the study. The central focus is on the process undertaken rather than the content of the results.
Original languageEnglish
Title of host publicationMODSIM 2011
Subtitle of host publicationSustaining our future: Understanding and living with uncertainty
EditorsD Marinova F Chan, R S Anderssen R S S Anderssen
Place of PublicationAustralia
PublisherModelling and Simulation Society of Australia and New Zealand
Pages2873-2879
Number of pages7
ISBN (Electronic)9780987214317
Publication statusPublished - 2011
EventInternational Congress on Modelling and Simulation - Perth, Australia
Duration: 12 Dec 201116 Dec 2011

Conference

ConferenceInternational Congress on Modelling and Simulation
CountryAustralia
Period12/12/1116/12/11

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    El Sawah, S., Guillaume, H. A., & Mitchell, M. (2011). Using participatory rapid appraisal and DPSIR approaches for participatory modelling: A case study for groundwater management in South Australia. In D. M. F. Chan, & R. S. A. R. S. S Anderssen (Eds.), MODSIM 2011: Sustaining our future: Understanding and living with uncertainty (pp. 2873-2879). Modelling and Simulation Society of Australia and New Zealand.