Abstract
ABSTRACTCollaborative, holistic, and proactive planning for basin-wide water management solutions addressing multiple water-related hazards is challenging. Shared vision planning (SVP) and decision support systems (DSSs) are two approaches that have been used to address the challenges described. SVP is a participatory planning process. DSSs can efficiently support the integration of multiple and vast amounts of information and interactively illustrate the trade-offs between alternative mitigation plans. While SVP and DSS have been previously used to help stakeholders to better understand watershed processes and how to arrive at collaborative basin-wide decisions, coupling these tools with serious gaming is an emerging effort. The multi-hazard tournament (MHT) framework is an example of the integration of serious gaming, DSS and SVP. The MHT is based on the premise that almost all cultures and individuals understand and enjoy sports, teams and structured games. This paper first introduces a new approach called the MHT which couples serious gaming via the use of DSS with the traditional SVP concepts of (1) collaborative computer modelling, (2) traditional water resources planning, and (3) structured public participation through a case study of the Cedar Rapids, Iowa MHT. Second, it examines and discusses the effectiveness of this combined approach in achieving objectives often established in collaborative, watershed scale: decision-making, social learning, and relationship building. An analysis of the Cedar Rapids MHT survey results show that the integration of the Iowa watershed decision support system, SVP, and serious gaming framework served as a valuable tool for examining trade-offs between mitigation options and their impacts. The Cedar Rapids MHT survey results indicated this was also an adequate means of capacity building, social learning, and meaningfully engaging the community in mitigating hazards posed in their watersheds. The paper also explores how the integration of SVP, DSS, and serious gaming with some refinements could be used to practically support watershed scale planning and decision-making processes.
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