An interdisciplinary approach to resolving conflict in the water domain
Integrated Water Management (IWM) in line with the European Union Water Framework Directive (WFD) promotes a collaborative-oriented approach to tackle water management issues. This requires the participation of various government departments and stakeholder groups along with scientists and experts from different scientific disciplines. Conflict, arising from the diversity of perspectives, beliefs and benefits among those interest groups is a common characteristic of integrated water management. In order to benefit from stakeholder participations in supporting and accepting any results obtained in stakeholder meetings etc, the conflict of interests must be addressed.
Examining the essence of the conflict, the Integrated Sustainability Assessment (ISA) is a form of knowledge co-production aiming at gathering and synthesizing diverse perceptions of persisting problems. ISA is a cyclical process of scoping, envisioning, experimenting and learning to provide the stakeholder with a deeper understanding of causalities behind the water issues.
Following the visionary process of ISA, we particularly focus on agent based modeling as an essential method to understand and visualize the complexity of water resource management. Agent Based Models (ABM) complements traditional analytic methods and is a useful approach to depict not only the roots of conflict, but also potential resolutions based on stakeholders viewpoints. Nevertheless, ABM and designing and implementing the computer applications, which are supposed to reflect the ideas shaped during the ISA process, is very challenging. There are few examples of computer models, if any, embedding multiple disciplines to capture the interactions among stakeholders related to water issues. As a result of these challenges, many developed models detach from the initial goals and cannot be used effectively to address the problem.
We strive to address some of these challenges by recognizing the need for an analytical (conceptual) framework along with empirical evidence from case studies as well as utilizing appropriate methodologies and tools for the implementation phase. Respectively, first, we explore the role of the Agent Modeling Language (AML) to develop the conceptual model upon which the computer models should be built up. AML provides a rich set of modeling constructs for modeling applications that substantiates and/or shows characteristics of multi-agent systems such as a river basin with all its stakeholders. Second, we propose to apply eXtreme Programming (XP) methodology to implement agent-based models. XP is based on short-time software delivery providing the developers with the opportunity of fixing the applications’ errors, and changing the direction of development in the early stages. We use an example to illustrate the process of developing an agent-based model and how to deal with the complications of converging different perspectives in the model.
KeywordsConflic Agent Integrated Water Managemen Integrated Sustainability Assessmen Agent Based Modeling Extreme Programming
Unable to display preview. Download preview PDF.
- Axelrod R (1997) The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton University PressGoogle Scholar
- Beck K, Andres C (2004) Extreme Programming Explained: Embrace Change, 2nd Edition. Addison-Wesley ProfessionalGoogle Scholar
- Bellifemine FL, Caire G, Greenwood D (2007) Developing Multi-Agent Systems with JADE, John Wiley & Sons, LtdGoogle Scholar
- Castle C, Crooks A (2006) Principles and concepts of agent-based modeling for developing geospatial simulations. UCL Centre for Advanced Spatial Analysis Working Papers Series. Available from: http://www.casa.ucl.ac.uk/working_papers/paper110.pdf
- Cervenka R, Trencansky I (2007) The Agent Modeling Language - AML: A Comprehensive Approach to Modeling Multi-Agent Systems, Birkhäuser BaselGoogle Scholar
- Darmofal DL, Soderholm DH, Brodeur, DR (2006) Using concept maps and concept questions to enhance conceptual understanding. Frontiers In Education, 2002, 32nd Annual, 1, T3A-1-T3A- 6Google Scholar
- Hipel KW, Obeidi A, Fang G, Kilgour DM (2008) Adaptive Systems Thinking in Integrated Water Resources Management with Insights into Conflicts over Water Exports. INFOR, 46:1:51-69Google Scholar
- Miller JH, Page, SE (2007) Complex Adaptive Systems: An Introduction to Computational Models of Social Life. Princeton University PressGoogle Scholar
- Nastar M (2008) Synergy of Disciplines for Sustainability - Analysis of agent interactions in the transition management cycle to tackle the water scarcity issue. Master’s Thesis, Lund University, Center for Sustainability Studies. Available from: http://www.lumes.lu.se/database/alumni/06.08/thesis/Maryam_Nastar.pdf
- OMG (2008) Catalog of OMG Modeling and Metadata Specifications. Object Management Group. Available from: http://www.omg.org/technology/documents/modeling_spec_catalog.htm
- Renger M, Kolfschoten GL, Vreede GD (2008) Challenges in Collaborative Modeling: A Literature Review. In: Dietz JLG, Albani A,Barjis J (eds) Advances in Enterprise Engineering I, Springer Heidelberg, Berlin, Ch 4Google Scholar
- Schweitzer F, Farmer JD (2007) Browning Agents and Active Particles; Collective Dynamics in the Natural and Social Sciences, Springer Berlin HeidelbergGoogle Scholar
- Van der Brugge R, De Haan J (2005) Complexity and Transition Theory, paper for the conference Lof der Verwarring, RotterdamGoogle Scholar
- WFD (2007) Introduction to the new EU Water Framework Directive. European Water Policy. Available from: http://ec.europa.eu/environment/water/waterframework/info/intro_en.htm