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Designing a Hydro-Economic Collaborative DSS Model David E. Rosenberg December 19, 2008 AGU Fall Conference http://www.engr.usu.edu/cee/faculty/derosenberg/
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So what is a collaborative DSS model? Model lifecycle Key design decisions Best practices Future directions Conclusions Outline 2
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So what is a collaborative DSS? A model that is developed, used, and applied through a stakeholder-driven planning process 3 Collaborative DSS Data Facilitation Economics Water Management Modeling Stakeholders IndividualCollaborative My vs. your model Our model My vs. your experts We are / become experts Your [bad] data / asummptions Our (agreed) data / assumptions Individual goalIndividual & collective goals Win-lose; zero- sum Win-win; expand the pie
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The model lifecycle End Points: –Consensus reached –Exhaust interest, time, $$, etc. –Remove / change over-arching motivator –Computer model can not accommodate stakeholders’ needs 4 1.Identify participants 2.Define problems and goals 3.Define performance objectives 4.Identify potential solutions 5.Evaluate solutions against performance objectives Need flexible, adaptive models and tools!!
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Key decisions 1.Who constitutes a stakeholder? 2.Use a facilitator? 3.Model choice? General platform Existing hydrologic software Custom-developed 4.Who builds, tests, runs, and modifies the model? 5 Stakeholders Contracted 3 rd Party
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Key decisions (continued) 5.Centralized or decentralized model? 6.Time between specify scenario and obtain model results? 7.How to communicate + share results? 6 ? ? ? ? ? ? ? ?
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Some recommended best practices 7 1. Develop in modules Data Input Store Manipulate Analyze Present results Data aware 2. Track meta data Data source? Who acquired it? When? Gaps Modifications / transformations 3. Document Data inputs; model assumptions & calculations Stakeholder use Reproducible by outside observer? TimeSpatialSectorParameterData type Hourly Daily Weekly Monthly Seasonal Annual Surface water Groundwater Storage Demand site District Conveyance Urban Agricultural Industrial Tourist Price Elasticity Capacity Availability Cost Capital cost Point value Time-series Paired data 4. Object-oriented software Encourages modular development Use + customize existing tools Share your tools
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Future directions Spatial (map-based) input, display, and analysis Real time operations Internet based –Access –Share information –Support chat, discussion, wiki, voice/video conference –Record and make more transparent the who, what, when, and why of the collaboration process 8
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Conclusions Pay attention to: –Model lifecycle, Key design decisions –Best practices, Future directions Need flexible, adaptive models Reduce time on logistical support Increase ability to meet user needs Enhance communication, understanding, learning Decrease barriers to participate 9
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?? Questions ?? David E. Rosenberg david.rosenberg@usu.edu http://www.engr.usu.edu/cee/faculty/derosenberg/ 10
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