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TRANSCRIPT
READ-‐AHEAD MATERIALS
for the:
Special Symposium on Collaborative Modeling as a Tool to Implement IWRM
Held at:
American Water Resources Association s
Summer Specialty Conference on Integrated Water Resources Management:
June 27-‐29, 2011 Snowbird, UT, USA
Compiled by Stacy Langsdale Institute for Water Resources, Alexandria, VA
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The papers contained within will be presented at the Special Symposium on Collaborative Modeling as a Tool to Implement IWRM. They are being provided to you in advance of the event to increase the productivity of our short time together. Please focus on the overview paper and the other papers in your session. PLEASE NOTE: This is an informal report, and should not be cited. The majority of the abstracts and papers contained here will be published in the official AWRA proceedings and should be cited as such. AWRA holds the copyright to these. Anything included here that is not published elsewhere should be considered DRAFT form, not for citation or quoting, except with permission of the author(s).
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Table of Contents Symposium Agenda ........................................................................................................................ 1
Information for Presenters and Guidelines for Case Study Papers and Presentations .................. 4
Overview Paper ............................................................................................................................... 6
THE USE OF COLLABORATIVE MODELLING IN DECISION MAKING FOR IWRM by Guillermo F Mendoza, Hal Cardwell ............................................................................................................... 7
Session 7: The Use of Collaborative Modeling for Implementing IWRM .................................... 15
COLLABORATIVE MODELING -‐ A TOOL FOR IMPLEMENTING IWRM? by Hal Cardwell, Bill Werick, Vince Tidwell, Stacy Langsdale, Mark Lorie, Brian Manwaring, Linda Manning, Lisa Bourget, Guillermo Mendoza .................................................................................................... 16
TAKING STOCK OF LESSONS FROM PARTICIPATORY MODELING EXPERIENCES FOR INTEGRATED WATER RESOURCES MANAGEMENT IN PORTUGAL by Nuno Videira, Paula Antunes, Rui Santos, Rita Lopes ............................................................................................... 17
COLLABORATIVE MODELING FOR DECISION SUPPORT IN WATER RESOURCES: PRINCIPLES AND BEST PRACTICES by Stacy Langsdale, Allyson Beall, Elizabeth Bourget, Erik Hagen, Scott Kudlas, Richard Palmer, Diane Tate and Bill Werick ................................................................. 33
EVALUATING THE OUTCOMES OF COLLABORATIVE MODELING by William Michaud ............ 37
Session 10: Case Studies in Collaborative Modeling I Convening Stakeholder-‐Based Processes....................................................................................................................................................... 43
DEVELOPING A SHARED VISION DECISION SUPPORT SYSTEM FOR THE CONNECTICUT RIVER BASIN by Richard Palmer1, Kim Lutz2, Austin Polebitski3 .......................................................... 44
COLLABORATIVE MODELING FOR DECISION SUPPORT IN THE UPPER SAN PEDRO BASIN (ARIZONA): WHAT ELSE DO WE NEED TO WALK A SUSTAINABLE PATH? by Aleix Serrat-‐Capdevila1,2, Juan B. Valdes1,2, Hoshin V. Gupta2, Anne Browning-‐Aiken4, Kevin Lansey3, Timothy L. Finan5 ...................................................................................................................... 45
THE UPS AND DOWNS OF INTEGRATED WATER RESOURCES PLANNING IN THE MURRAY-‐DARLING BASIN by Bill Young ................................................................................................... 59
Session 13: Case Studies in Collaborative Modeling II Developing Decision Support Tools .... 60
ADVANCING INTEGRATED WATER RESOURCE MANAGEMENT IN SYSTEMS WITH HIGH LEVELS OF SCIENTIFIC AND SOCIAL UNCERTAINTY: LESSONS FROM THE PALOUSE BASIN by Allyson Beall, Fritz Fiedler, Jan Boll, Barbara Cosens ............................................................................ 61
DESIGNING A SHARED VISION MODEL FOR ADAPTIVE MANAGEMENT WITH STAKEHOLDERS by Bill Werick ............................................................................................................................. 67
COLLABORATIVE, STAKEHOLDER-‐DRIVEN WATER-‐ENERGY-‐AGRICULTURE-‐ECOSYSTEMS MODELING AND PLANNING FOR LONG-‐TERM RESOURCE SUSTAINABILITY: A CASE STUDY IN THE TIGRIS EUPHRATES by Howard Passell and Vince Tidwell ................................................. 71
Session 16: Case Studies in Collaborative Modeling III Navigating Institutional Frameworks and Implementing Decisions ......................................................................................................... 74
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INTEGRATED FRESHWATER SOLUTIONS A NEW ZEALAND CASE USING MEDIATED MODELLING by Marjan van den Belt, Heike Schiele ................................................................. 75
IWRM THROUGH COLLABORATIVE MODELING FOR DECISION SUPPORT THE BOW RIVER CASE STUDY by Daniel Sheer, HydroLogics Inc., Columbia, MD ......................................................... 82
INTEGRATING COLLABORATIVE MODELING, STRUCTURED PARTICIPATION AND INTEGRATED WATER RESOURCES MANAGEMENT PLANNING IN PERU: A CASE STUDY OF A NEW WORLD BANK PROJECT by Guillermo Mendoza, Hal Cardwell, Marie-‐Laure Lajaunie .......................... 87
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Symposium Agenda Monday / June 27 / 10:30 AM 12:00 Noon Plenary Session Continued: IWRM Perspectives
The Plenary Session will feature experts discussing various aspects of IWRM including: Jerry Delli Priscoli, Institute for Water Resources, U.S. Army Corps of Engineers Collaborative Modeling Gives the Emperor His Clothes
Tuesday / June 28 / 8:30 AM 10:00 AM SESSION 7: Special Symposium Session: The Use of Collaborative Modeling for Implementing IWRM Moderator Gerald Sehlke National Idaho Laboratory, Idaho Falls, ID Collaborative Modeling - A Tool for Implementing IWRM? - Hal Cardwell, USACE Conflict Resolution & Public Participation Center, Alexandria, VA (co-authors: Bill Werick, Vince Tidwell, Stacy Langsdale, Mark Lorie, Brian Manwaring, Linda Manning, Lisa Bourget, Guillermo Mendoza) Taking Stock of Lessons from Participatory Modeling Experiences for Integrated Water Resources Management in Portugal - Nuno Videira, CENSE, FCT, Universidade Nova de Lisboa, Caparica, Portugal (co-authors: Paula Antunes, Rui Santos, Rita Lopes) Collaborative Modeling for Decision Support in Water Resources: Principles and Best Practices - Stacy Langsdale, USACE Institute for Water Resources, Alexandria, VA Evaluating the Outcomes of Collaborative Modeling - Bill Michaud, SRA International, Inc., New Hartford, CT Tuesday / June 28 / 10:30 AM 12:00 PM SESSION 10: Special Symposium Session: Case Studies in Collaborative Modeling I Convening Stakeholder Based Processes Moderator Brian Manwaring U.S. Institute for Environmental Conflict Resolution, Tucson, AZ Developing a Shared Vision Decision Support System for the Connecticut River Basin Austin Polebitski, Dept. of Civil and Environmental Engineering, University of Massachusetts, Amherst, MA (co-authors: Richard Palmer, Kim Lutz,)
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Collaborative Modeling for Decision Support in the Upper San Pedro Basin (Arizona): What Else do We Need to Walk a Sustainable Path? - Aleix Serrat-Capdevila, ICIWaRM - University of Arizona, Tucson, AZ (co-authors: Juan B. Valdes, Hoshin V. Gupta, Anne Browning-Aiken, Kevin Lansey, Timothy L. Finan) The Ups and Downs of Integrated Water Resources Planning in the Murray-Darling Basin - Bill Young, CSIRO Water for a Healthy Country National Research Flagship, Canberra, ACT, Australia Motivations, Political Support, and Impacts: A Facilitated Discussion Brian Manwaring, U.S. Institute for Environmental Conflict Resolution, Tucson, AZ Tuesday / June 28 / 1:30 PM 3:00 PM SESSION 13: Special Symposium Session: Case Studies in Collaborative Modeling II Developing Decision Support Tools Moderator Lisa Beutler MWH, Sacramento, CA Advancing Integrated Water Resource Management in Systems With High Levels of Scientific and Social Uncertainty: Lessons From the Palouse Basin - Allyson Beall, Washington State University, Pullman, WA (co-authors: Fritz Fiedler, Jan Boll, Barbara Cosens) Designing a Shared Vision Model with Stakeholders - William Werick, Werick Creative Solutions, Culpeper, VA Collaborative, Stakeholder-Driven, Water-Energy-Agriculture-Ecosystems Modeling and Planning for Long-Term Resource Sustainability - Howard Passell, Sandia National Labs, Bernalillo, NM (co-authors: Jesse Roach, Marissa Reno, Vince Tidwell) Motivations, Political Support, and Impacts: A Facilitated Discussion Lisa Beutler, MWH, Sacramento, CA Tuesday / June 28 / 3:30 PM 5:00 PM SESSION 16: Special Symposium Session: Case Studies in Collaborative Modeling III Navigating Institutional Frameworks and Implementing Decisions (Note: Session 16 continues with a Panel Discussion from 5:00 PM 6:00 PM) Moderator Linda Manning Integrated Freshwater Solutions: A Case Study of the Manawatu River, New Zealand - Marjan van den Belt, Ecological Economic Research New Zealand, Massey University, Palmerston North, New Zealand (co-author: Heike Schiele) IWRM through Collaborative Modeling for Decision Support the Bow River Case Study - Daniel Sheer, HydroLogics Inc., Columbia, MD Integrating Collaborative Modeling, Structured Participation and Integrated Water Resources Management Planning in Peru: A Case Study of a new World Bank Project - Guillermo Mendoza, International Center for Integrated Water Resources Management, Alexandria, VA (co-authors: Aleix Serrat-Capdevila, Hal Cardwell, Marie-Laure Lajaunie) Motivations, Political Support and Impacts: A Facilitated Discussion Linda Manning, The Council Oak, Annandale, VA
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Tuesday / June 28 / 5:00 PM 6:00 PM Collaborative Modeling & IWRM (Session 16 continued) Moderator Jerry Delli Priscoli Institute for Water Resources, USACE, Alexandria, VA Pancollaborative modeling is an effectively tool for achieving success in Integrated Water Resources Management. Panelists: Bill Young, CSIRO Water for a Healthy Country National Research Flagship, Canberra, ACT, Australia Elizabeth Bourget, Institute for Water Resources, Alexandria, VA Vincent Tidwell, Sandia National Labs, Bernalillo, NM Tuesday / June 28 / 6:00 PM 7:30 PM Networking Reception and Book Release Wednesday / June 29 / 8:30 AM 11:30 AM Working Meeting Agenda TBD
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Information for Presenters and Guidelines for Case Study Papers and Presentations
The purpose of this event is to explore and critically discuss the appropriateness of Collaborative Modeling as a means of doing Integrated Water Resources Management. This includes understanding how the application of the method must vary in different contexts around the world, while identifying commonalities that inform and define a set of universal best practices. The products of this symposium (papers, presentations and discussion) will be used to inform and enhance the development of UNESCO-‐IHP guidelines on the use of Shared Vision Planning for IWRM. (Note that for Decision Support, Group Model Building, or Mediated Modeling) AWRA is requesting papers for their proceedings, due May 2. Below is a template with questions to guide the content of your paper. If you choose not to write a full paper, we ask that you at least provide short answers to the questions that are relevant to your study. This template, along with the theme of your assigned session, should also guide the focus of your presentation. We are particularly interested in the Keys for Success (constraints and enabling conditions) to implement of collaborative modeling for decision making in Integrated Water Resources Management around the world. These should include technical, social, and institutional factors. If you have questions or need clarification, please contact: Hal Cardwell ([email protected]); Guillermo Mendoza ([email protected]); or Stacy Langsdale ([email protected]) Presentation and Discussion Questions I. Introduce problem description and context.
What is the purpose and location of the study? What problem were you trying to solve? Describe unique aspects of the study context. What was the catalyst or reason for using collaborative modeling / Shared Vision Planning?
II. Convening Stakeholder Based Processes
Please describe the participatory framework and how that was used to identify a distinct set of problems or opportunities. Who was involved? What role did they play (e.g. data provider, reviewer, problem definer, etc.)?
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What aspects of the participation framework enhanced or restricted IWRM planning? How did collaborative modeling support coordination of all the participants?
III. Developing Decision Support Tools
How did collaborative modeling support conceptualization of the project decision or plan (from developing objectives through formulating alternatives)
How was collaborative modeling used to coordinate and plan details (evaluate and finalize the decision or plan)?
How did collaborative modeling support implementation, monitoring and evaluation of the decision or plan?
III. Navigating Institutional Frameworks and Implementing Decisions
Describe any policies or legislation that influenced the study. How was the modeling process (both the technical modeling and stakeholder involvement)
financed? Are any of these factors included in the model?
IV. Outcome
What was the outcome or current status of the collaborative modeling process? How did the process directly or indirectly influence a decision? Describe how your effort impacted or influenced policies, strategies, laws/regulations,
future research, financing, etc in the IWRM process. What changed as a result of your effort?
V. Reflection
Please consider the most useful aspects of your project and describe why they were useful (e.g., participation, question identification, data collection, etc.) to support IWRM
What elements of the Collaborative Modeling for Decision Support approach enhanced or restricted the process of IWRM
What was surprising or unusual about your experience in this case? For example, If you have worked in different countries, describe any features of the study that would have been different if applied in a different country.
What were your lessons learned? Would you view this effort as a success? Why or why not? Would the participants would view this as a success? Why or why not?
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Overview Paper
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THE USE OF COLLABORATIVE MODELLING IN DECISION MAKING FOR IWRM by Guillermo F Mendoza, Hal Cardwell As Published in: Water Resources IMPACT. Vol 13, No. 3, May 2011. Pages 17-‐20. AWRA.
I. INTRODUCTION This short paper looks at the potential for using collaborative modeling for decision support as a tool for implementing Integrated Water Resources Management (IWRM). Shared Vision Planning
used by the Corps and others over the last twenty years to integrate systems modeling, structured participation, and traditional water resources planning into a practical forum for decision making. This collaborative modeling approach is consistent with the planning elements of IWRM (UNESCO-‐IHP 2008) and provides a pragmatic tool to incorporate systems modeling and participation in an IWRM planning process. Shared vision planning recognizes that technocratic water resources planning often fails to incorporate value systems that often ultimately drive political, cultural or social decision making priorities. The challenges to implement IWRM are often not technical issues but rather institutional drivers that are often unique to the different affected sectors, such as environment, flood management, energy, mining, municipal and industry. These sectors not only may have conflicting interests but also differing public support or understanding. Shared vision planning provides a framework for interest based negotiation that is synergistic with the recently issued
(UNESCO-‐IHP 2008). This manuscript seeks to highlight these synergies and underline how the Collaborative Modeling is a powerful, practical, and tested tool to implement IWRM at the River Basin level. II. UNESCO-‐IHP GUIDELINES FOR INTEGRATED WATER RESOURCES MANAGEMENT AT THE
RIVER BASIN LEVEL. The evolutionary, adaptive implementation of the IWRM process presented by the UNESCO-‐IHP
Figure 1). In the spiral model, water resources development in a basin, along with management principles and objectives, evolves over time as new demands and needs emerge and innovative solutions are implemented. Within an orderly IWRM process, a river basin and its management continuously adapt to those new demands and needs. At each turn of the evolutionary water management spiral, basin stakeholders must dialogue over and come to agreement on necessary tradeoffs. River basin councils or authorities often exist to provide legitimacy or institutionalize agreements (UNESCO-‐IHP 2008).
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Figure 1. IWRM Spiral (from (UNESCO-‐IHP 2008)).
Within each turn of the evolutionary water management spiral we can identify four phases, illustrated by the numbered nodes (Figure 1). Each complete turn represents the IWRM process (implementation of four phases) in response to impacts that can be social, environmental, economic, political, etc. As IWRM progresses ( ) the phases can repeat themselves to address new impacts or need for adaptive management. Often, these additional iterations represent more complex problems requiring better integration, information exchange and negotiation frameworks. Each of the four phases is described as follows: i) Recognize and identify the need for IWRM through the identification of needs and
problems. In an IWRM process this often includes public awareness and accountability efforts, and capacity building since the planning process creates new requirements from stakeholders.
ii) Conceptualize the overall structure of the problem and broad actions that might be undertaken. This phase executes a broad assessment of the river basin it conceptualizes the structure of problems and solutions, and develops a draft plan of action.
iii) Coordinate and plan with stakeholders towards reaching an agreement for appropriate actions. This phase requires that a coordinating mechanism between stakeholders exists; coordination is possible; preliminary agreements are iteratively improved; a final plan is developed; and an agreement is reached on a plan of action.
iv) Implement, monitor, and evaluate the agreed sets of actions and alternatives, such that modifications can be executed if results are not as planned. This is the critical end point of a stage of the IWRM process because it provides credibility for future planning stages, permits implementing agreement compromises, and provides an adaptive management framework to allow progress despite uncertainties in current understanding or future unknown change.
The UNESCO IHP guidelines organize case studies in the practice of IWRM under each of the phases and sub-‐ that supported their implementation. For example, a
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sub-‐
-‐phase in the Davao and Tama River case studies, as well as useful tools, (UNESCO-‐IHP
2008). III. THE PRINCIPLES OF SHARED VISION PLANNING
National Drought Study where the Corps was asked to find a better way to manage water under scarcity. After a year of collaborative study the Corps proposed a method that went further than the Federal water resources planning guidance by requiring planners to work with decision makers and stakeholders to develop metrics to evaluate drought mitigation alternatives and evaluate those alternatives using a collaboratively-‐developed, transparent computer model (Werick, 2000). This collaborative modeling method for drought preparedness eventually evolved for general application in water resources planning . Methodological descriptions and case studies of the application of Shared Vision Planning (SVP) and other Collaborative Modeling processes are described in Sheer et al. 1989, Stephenson et al. 2007, and Tidwell et al. 2007. Shared Vision Planning integrates (i) systems modeling, (ii) structured participation, and (iii) water resources planning. More specifically, it provides a framework to facilitate stakeholder and decision maker collaboration in the multi-‐disciplinary technical analysis and alternatives formulation and selection, such that compromises are possible before the end of a study or planning process. A key to success is a structured participation framework defined as the Circles of Influence (COI) with well defined rules of behavior (Figure 2).
Figure 2. Circles of Influence for Structured participation using Shared Vision Planning (adapted
from Cardwell et al. 2008)
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Using COI, SVP involves subsets and accepted leaders of stakeholders early and often during the planning and the technical analysis, rather than involving the entire public at limited, discrete instances through public notices, meetings or other forums. Participants at the inner circles are technical experts, have higher time commitments to the process and are often salaried. The participants at the outer circles have the institutional and working knowledge and values base, and through a structured process, provide the rules, directions, and validation to the technical analysis that is led by those in the inner circles. The decision makers provide directions on what they can institutionalize and what they cannot, and receive information from all their constituents (Cardwell et al. 2008). The steps to planning in SVP are based on traditional Federal water planning principles and are as follows: Step 1 Build a team with stakeholders and decision makers. Define problem-‐shed and
institutionally feasible scope of work by team, and identify problems and opportunities for the problem-‐shed.
Step 2 With stakeholder leaders develop objectives and metrics for evaluation. Step 3 status quo
using metrics from step 2. Step 4 Using collaborative model work with stakeholder representatives to formulate
alternatives. Step 5 With stakeholder leaders and decision makers evaluate alternatives and develop
recommendations. Step 6 Decision makers institutionalize the project or plan. Given stakeholder and decision
maker early involvement in technical analysis the feasible directions of solution crafting have been provided.
Step 7 Exercise the plan or project, and ensure mechanisms to adapt or update. IV. LINKING SHARED VISION PLANNING TO INTEGRATED WATER RESOURCES MANAGEMENT The parallels between the Shared Vision Planning process and IWRM are obvious (see Table 1) they are both based in traditional planning principles of identifying problems, then criteria, developing and evaluating alternatives, and moving towards implementation. They both speak to the need to involve the public and to coordinate. What Shared Vision Planning and other collaborative modeling processes bring in addition are techniques (grounded in theory and in experience) in terms of the specifics of how to successfully implement an integrated, collaborative water management planning process. To pinpoint these techniques, let us make targeted comparison between the IWRM phases and the Shared Vision Planning steps. Problem Definition: The first steps in UNESCO-‐IHP IWRM guidelines are to Recognize and Identify and then to Conceptualize the problem and potential solutions. SVP give specifics on how a team of stakeholders develop this problem definition, and how the team sets, and then iteratively refines criteria. The development of a collaborative model not only allows conceptualization of the problem, but more importantly obtains buy-‐in from stakeholders and decision early in an IWRM
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process. By including stakeholders in these first steps, IWRM plans are more likely to identify the most pressing problems and define them in ways that resonate with stakeholders (Table 1). Table 1. Comparison of the UNESCO-‐IHP phases of IWRM planning and the Steps of Shared Vision Planning per guidance of IWR-‐USACE (the sentences in bold illustrate the point in planning where an agreement is reached)
UNESCO-‐IHP Phases of IWRM The Steps of Shared Vision Planning
1. Recognize and Identify a. Recognize b. Identify problems and needs c. Create public awareness & accountability d. Develop capacity
1. Build team & Identify problems and opportunities
2. Conceptualize a. Assess b. Conceptualize c. Draft plan
2. Develop objectives and metrics for evaluation
3. Develop a collaborative model and evaluate status quo
4. Formulate Alternatives
3. Coordinate and plan details a. Build coordinating mechanism b. Coordinate c. Reach preliminary agreements d. Finalize the plan e. Reach an agreement
5. Evaluate alternatives and make recommendations
6. Institutionalize the plan or project
4. Implement, monitor and evaluate a. Implement b. Monitor & evaluate
7. Exercise and update (adapt) the plan or project
Collaboration: In the UNESCO-‐IHP IWRM guidelines, coordinating and planning details occurs at Phase 3 after resources have been spent Recognizing and Identifying, and Conceptualizing alternatives and drafting a plan. Conversely in SVP coordination starts at the beginning of the planning process and continues throughout the process of identifying problems, objectives, alternatives, and evaluation. Within SVP, collaborative modeling provides a focus for the collaborative process, the COI concept structures the collaboration, and the reliance on tested planning steps ensures progress towards development and implementation of IWRM plans. Application of these techniques allows intensive yet productive coordination throughout the planning process and increases the likelihood for agreements and institutionalization of IWRM plans. At the beginning of an SVP process, the planning team is built under the framework of the COI that designate who will develop the systems model and who will guide, conceptualize, and validate its development, i.e. who will use the model. Technical Analysis: Phase 2 of the UNESCO-‐conc
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analysis and alternative development that are necessary to identify solid solutions. By explicitly evaluating interactions in a systems model, SVP considers the multiple interests and uses that is so critical to IWRM. The SVP process provides detailed guidance on how to build collaborative models that serve to assess, conceptualize, and create draft plans to address problems and opportunities. Moreover, it integrates quantitative engineering metrics with qualitative social metrics as defined by the users, and the model is developed according to its functionality, i.e. how it will be used. Reach Agreement/Make Recommendation: Two elements of SVP support this critical stage in the IWRM process. First of all, Shared Vision Planning explicitly recognizes and uses best practices from the environmental conflict resolution from endorsing situational assessments at the beginning of a planning process, to promoting interest-‐based negotiation, to ensuring that stakeholders interests and perspectives are validated through inclusion in the analysis, to the transparent documentation of assumptions and decisions in a collaboratively developed model that functions
criteria to evaluate proposed alternatives best practices supports transparent decision making. Monitor and Evaluate: Once an agreement has been reached and implemented, SVP provides vehicle to assist with the long-‐term monitoring and evaluation process a living, collaboratively-‐developed, technical tool. The use of Shared Vision Planning provides a way to increase the likelihood of successful IWRM planning by supplementing the UNESCO guiding document with a structured planning method that integrates the technical analysis and stakeholder participation. Essentially the SVP process builds mutual understanding of the water resource systems, and builds trust between stakeholders with differences of opinion. By using a structured planning process (similar to the phases within the IWRM spiral) SVP maintains a focus on outcomes and decisions. By involving stakeholders in the analysis at the onset of planning an early understanding and possible compromises of the different points of view is achieved. Most importantly, when it is time to institutionalize an agreement, most participants understand the options for alternatives, and decision makers are not confronted with a set of options that they will not approve or validate. V. CONCLUSION Shared Vision Planning and the UNESCO-‐IHP guidelines for IWRM are not in disagreement. SVP is a toolset that integrates seamlessly into the IWRM guidelines to improve its practical and successful implementation. Although, IWRM processes can be mandated by legislative action, such as by authorizing the creation of River Basin Councils with jurisdictions over water use, social values, interest groups or certain water sectors can continue to create obstacles for integrated planning. Indeed, most countries have separate ministries that have jurisdictions over specific uses of water. Not unlike the authorization of the Tennessee Valley Authority, developing countries, in particular, seek IWRM as a mechanism for decentralized and sustainable economic growth. This often threatens the jurisdictions of other ministries (the US is more complicated as one needs to add State jurisdictions over water), which may have specific Master Plans for a given sector. SVP
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provides the framework to build the teams at the beginning of the process between difference groups at the government agency level and stakeholder groups, and establish the rules of engagement before conceptualizing problems. However, case studies that illustrate the application of Shared Vision Planning in an IWRM process are hard to come by. As a follow up on to this short paper we will be examining such international case studies to highlight Keys for Success. For example, Peru has passed a new water law that authorizes the establishment of River Basin Councils (RBC), initially tasked with developing IWRM plans at 6 pilot basins of the arid Pacific coast. To implement IWRM planning that can be validated
Authority has been working with IWR-‐USACE to implement a modified SVP approach. VI. REFERENCES Cardwell, H., Langsdale, S. and Stephenson, K. 2008. The Shared Vision Planning Primer: How to
incorporate computer aided dispute resolution in water resources planning. Institute for Water Resources, Alexandria, VA. IWR Report 08-‐R-‐2. www.iwr.usace.army.mil/docs/iwrreports/2008-‐R-‐02.pdf
Sheer, D.P., Baeck, M.L. and Wright, J.R. 1989, "The Computer as Negotiator", Management and
Operations, Journal of AWWA, vol. February, pp. 68-‐73. Stephenson, K., Shabman, L., Langsdale, S. and Cardwell, H. 2007. Computer Aided Dispute
Resolution: Proceedings from the CADRe Workshop, Sept 2007, Albuquerque, NM. Institute for Water Resources, Alexandria, VA. IWR Report 07-‐R-‐6. www.sharedvisionplanning.us/docs/SVP-‐2007-‐R-‐06.pdf
Tidwell, V.C., Sun, A., Klise, G. and Brainard, J. 2007, "Collaborative Modeling to Support the 2004
Arizona Water Settlements Act", World Environmental and Water Resources Congress 2007: Restoring our Natural Habitat.ASCE, .
UNESCO-‐IHP 2008, "Part 2-‐1: The Guidelines for IWRM Coordination" in IWRM Guidelines at River
Basin Level UNESCO, Paris, pp. 1-‐174. Werick, 2000. "History of Shared Vision Planning in the Army Corps of Engineers". Presentation for
the ASCE 2000 Joint Conference in Water Resources Engineering and Water Resources Planning and Management. Minneapolis, MN. August 2000.
Guillermo F. Mendoza Institute for Water Resources (IWR) and the International Center for Integrated Water Resources Management (ICIWaRM) under the auspices of UNESCO 7701 Telegraph Road Alexandria, VA 22315
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[email protected] Voice: 703-‐428-‐6137 Fax: 703-‐428.8171 Hal E. Cardwell [email protected] Guillermo F. Mendoza obtained his PhD from Cornell University in 2002. He worked as a modeler for New York City Department of Environmental Protection, and then in international water resources development for USAID projects in Honduras and El Salvador, and as a consultant for the World Bank. In 2007 he developed the water program of the Natural Capital Project based in Stanford University. Since 2009 he is at the Institute for Water Resources of USACE supporting the International Center for Integrated Water Resources Management, and the Center for Conflict Resolution and Public Participation.
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Session 7: The Use of Collaborative Modeling for Implementing IWRM
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COLLABORATIVE MODELING - A TOOL FOR IMPLEMENTING IWRM? by Hal Cardwell, Bill Werick, Vince Tidwell, Stacy Langsdale, Mark Lorie, Brian Manwaring, Linda Manning, Lisa Bourget, Guillermo Mendoza Abstract: This short paper looks at the potential for using collaborative modeling for decision support as a tool for implementing Integrated Water Resources Management (IWRM). Shared Vision Planning (the US Army Corps' version of Collaborative Modeling) has been used by the Corps and others over the last twenty years to integrate systems modeling, structured participation, and traditional water resources planning into a practical forum for decision making. This collaborative modeling approach is consistent with the planning elements of IWRM (GWP 2009, GWP 2000, Biswas 2005, UNESCO-‐IHP 2008) and provides a pragmatic tool to incorporate systems modeling and participation in an IWRM planning process. Shared vision planning recognizes that technocratic water resources planning often fails to incorporate value systems that often ultimately drive political, cultural or social decision making priorities. The challenges to implement IWRM are often not technical issues but rather institutional drivers that are often unique to the different affected sectors, such as environment, flood management, energy, mining, municipal and industry. These sectors not only may have conflicting interests but also differing public support or understanding. Shared vision planning provides a framework for interest based negotiation that is synergistic with the recently issued IWRM Guidelines from UNESCO's International Hydrologic Programme (UNESCO-‐IHP 2008). This manuscript seeks to highlight these synergies and underline how the Collaborative Modeling is a powerful, practical, and tested tool to implement IWRM at the River Basin level.
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TAKING STOCK OF LESSONS FROM PARTICIPATORY MODELING EXPERIENCES FOR INTEGRATED WATER RESOURCES MANAGEMENT IN PORTUGAL by Nuno Videira, Paula Antunes, Rui Santos, Rita Lopes 1
ABSTRACT
According to the meet the aim of the EU Water Framework Directive (WFD) i.e. to achieve good status by 2015 due to water scarcity, physical modifications and poor water quality (EEA, 2010). The full implementation of the integrated approach to water resource management foreseen by WFD is needed to revert these trends, which is particularly dependent upon the capacity to promote active public and stakeholder participation. Similar participatory requirements have been set by complementary policy efforts, such as the European Integrated Marine Policy and its environmental pillar, the European Marine Strategy Framework Directive that, among other objectives, requires EU Member States to d
In this paper we provide a detailed description and analysis of two case studies developed in Portugal in
which different modeling exercises with stakeholders have been tested to gain new insights on how to meet the participatory challenges presented by recent water related policy frameworks in Europe.
We start by describing an experience developed in the lower Guadiana River, where three modeling workshops were conducted to build a shared qualitative causal diagram and a scoping simulation model of
potential as a platform for integrated sustainability assessment of maritime policies. We focus on the results of a problem conceptualization workshop in which participants identified the interrelationships between different marine and coastal issues and selected leverage points for sustainable policy interventions. Finally, we take stock of lessons derived from these cases, discussing their design and evaluation features and highlighting the main weaknesses/successful outcomes fostered by the proposed participatory modeling methods and tools.
I. INTRODUCTION Integrated Water Resources Management (IWRM) has been defined as a process that promotes coordinated development and management of water (GWP, 2000) across physical, administrative, social and cognitive boundaries (Mostert et al. 2008). According to USAID (2006), participation is of central importance
-term needs for water and coastal resources while maintaining essential ecological services and economic benefits". The work presented in this paper was motivated by the calls for new approaches promoting active participation in the implementation of the Water Framework Directive (WFD) and the Integrated Maritime Policy and brings a European perspective on some of the challenges underlying the use of participatory modeling approaches in IWRM. Mediated Modeling (van den Belt, 2000; van den Belt, 2004), Group Model Building (Vennix et al. 1992; Vennix, 1996), Shared Vision Planning (USACE, 2009), Collaborative Modeling (Beall et al., 2011; Langsdale et al. 2011) are some of the designations under which these participatory platforms have been developed and implemented throughout the world. All approaches point out to learning outcomes as some of the main benefits from modeling with stakeholders while tackling complex decision-making issues. Thus,
*CENSE Center for Environmental and Sustainability Research, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal. Respectively, [email protected]; [email protected]; [email protected]; [email protected]
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promoting modeling as learning (Lane, 1992) is likely to require providing as much attention, if not more, to the participatory process as to the modeling products (van den Belt et al. 2010; Voinov and Bousquet, 2010). For implementing the cases described in this paper, we have built upon previous mediated modeling experiences developed in Portugal (Antunes et al., 2006; van den Belt, 2000; Videira et al., 2003) and followed a participatory research design. Participatory research has become a popular approach for problem-oriented scientific research aiming to address complex problems in real management situations (Hirsch et al., 2010). Within this mode of practice, researchers initiate the participatory process aiming at promoting co-production of knowledge and social learning (Mostert et al., 2008), which may subsequently facilitate the development and assessment of better-informed policies. The paper will proceed with Section II, which frames the cases within the relevant water policy context in Europe. In Section III we describe how stakeholders were convened and how the two participatory modeling processes have unfold. Section IV summarizes the main outcomes on both cases and the lessons learned regarding research and policy implications. General conclusions are presented in Section V.
II. NAVIGATING INSTITUTIONAL FRAMEWORKS AND IMPLEMENTING DECISIONS
ter bodies are at risk of failing to meet the aim of the EU WFD i.e. to achieve good status by 2015 due to water scarcity, physical modifications and poor water quality (EEA, 2010). The full implementation of the IWRM approach foreseen by the WFD is needed to revert these trends, which is particularly dependent upon the capacity to promote active public and stakeholder participation. The WFD (Directive 2000/60/EC) introduced new standards and criteria that are driving change in European water policy (CEC, 2000). It also presented significant challenges with respect to institutions, planning and evaluation processes, such as the establishment of river basin units and the development of river basin management plans (Kallis and Butler, 2001). Another innovative element of WFD was the articulation of public and stakeholder participation as a critical element for achieving the overall objective of good status for all waters in 2015 (Page and Kaika, 2003; Mostert, 2003). and stakeholders have the right to be informed before and during the planning process, the right to comment and the right to have access to the background documentation and information on River Basin Management Plans (RBMP) (CEC, 2000). Beyond these legal requirements for information and consultation, the WFD encourages more intensive deliberative processes throughout the implementation process, although these are not compulsory (Wright and Jacobsen, 2011). This brings forward some ambiguous interpretations since EU Member States need to demonstrate not only that information and
tive involvement is promoted depends on adopting a genuine, proactive and co-learning attitude by water authorities (CIS, 2003; Ker Rault and Jeffrey, 2008). Following the publication of the WFD, a Common Implementation Strategy was agreed by European Water Directors to address common challenges and promote coherent implementation among Member States. This led to the development of a set of broad guidelines for public and stakeholder involvement (ComEC, 2002). However, the general character of these guidelines has driven extensive research and experimentation with new participatory approaches to apply at different stages of river basin planning and management processes (Antunes et al., 2009; Kallis et al., 2006). Within this context, the first participatory process described in this paper was initiated and promoted by
research project, which was funded by the European Commission (FP5, EESD-RTD Program). Modelers consulted the national water and nature conservation institutes (INAG and ICN, respectively) in framing the issues and setting up the workshops. However, there was no prior commitment from water managers to the implementation of results from the participatory process (Videira et al., 2009).
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Similar participatory requirements to those of the WFD have been set by complementary policy efforts,
maritime policy-a cross-The European Marine Strategy Framework Directive (MSFD) is the environmental pillar of the IMP. It extends the scope of the WFD into the open sea and requires EU Member States to develop marine strategies
(ComEC, 2008). The European Commission published guidelines for promoting active participation by maritime stakeholders in integrated national, regional or local maritime policies, recommending governments to involve all stakeholders in the development and implementation of their own integrated maritime policies (CEC, 2008). Similarly to the WFD, challenges for participation rest in the development of the appropriate structures, methods and tools supporting stakeholder involvement in governance of maritime affairs (CEC, 2008). Considering this background, the second case study described in this paper was developed in the scope of
supported by the Portuguese Foundation for Science and Technology (PTDC/AMB/66909/2006). This multidisciplinary research project aims to explore the potential of participatory modeling based on systems thinking and system dynamics tools in conducting participatory sustainability assessments of maritime policies.
III. CONVENING STAKEHOLDER-BASED PROCESSES IN IWRM
III.1 The Baixo Guadiana Case Study The participatory modeling experience took place in the Baixo Guadiana, which corresponds to the lower section and estuary of the Guadiana River, located in the Portuguese region of the Algarve (Figure 1).
(a) (b) Figure 1 Guadiana river basin and location of the case study area. Source: a) Videira et al., 2009; b) INAG,
2009 The Guadiana is an international river shared between Portugal and Spain with a total drainage area of 6.68 million hectares (17% in Portugal). Baixo Guadiana, has a high natural, cultural and economic value. It includes important areas protected under national and international agreements, such as the Natural Reserve of the Castro Marim and Vila Real de St.º António Saltmarsh. Water plays a strategic role in the development of the local communities, providing for domestic water supply and supporting fisheries, forestry, agriculture,
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salt making industry, transportation, tourism and recreation. Castro Marim and other villages in the river basin have also important sites of cultural heritage (Videira et al., 2009). The large number of dams built upstream, both in the Portuguese and Spanish sides, affects the water quantities arriving at this southern part of the Guadiana basin. In the Natural Reserve, conflicts of interests and values occur between landowners (and other project promoters) who wish to promote economic activities and the environmental managers, who strive to preserve the ecological value of the area. Development of tourism resorts, intensive fish farming, pollution from urban areas and the decline in traditional activities are some of the main anthropogenic pressures that may lead to significant ecosystem changes in Baixo Guadiana (Videira et al., 2009). The process aimed to be a front-runner for testing innovative methods and tools for active involvement of interested parties in the planning and management processes foreseen by the WFD. This follows a model of participatory research (Barreteau et al. 2010) described in Figure 2. We identified a set of relevant policy issues for the initial stages of WFD implementation and developed a participatory modeling process accordingly.
Figure 2 Participatory modeling research framework for the Baixo Guadiana case study
The main research objective of the Baixo Guadiana case study was to develop and implement a participatory modeling methodology to support the scoping stages of river basin planning and management processes. One of the relevant policy issues selected for the research was the characterization of river basins and how to promote participation in this early stage of implementation of WFD. More specifically, the Baixo Guadiana case study aimed at (Videira et al. 2009):
Developing a causal diagram depicting a shared view of the current problems, pressures and impacts perceived by the participant group (1st workshop);
Building up a mediated model based on the causal diagram to support the analysis of alternative development scenarios (2nd and 3rd workshops);
Drafting an informal participatory action plan including objectives and measures for the sustainable management of the Baixo Guadiana river basin (3rd workshop).
The Natural Reserve of the Castro Marim and Vila Real de St.º António Saltmarsh provided the venue for the workshops and served as the local contact point. The steering group the modeling team and local
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managers from the Natural reserve met five times before the first workshop during the process set-up stage. Stakeholder analysis included several activities such as press and literature reviews and brainstorming sessions to generate a list of stakeholders to invite (Videira et al. 2009). This list was built around a broad set of sustainability issues in order to capture a high diversity in mental models and worldviews. Eighty-six stakeholders were identified related with themes such as governance structures and river basin management policies, water salinity, water flows, nature conservation conflicts, intensive tourism activities and rural development. We received a positive response from 30 organizations and 14 owners of land parcels inside the Natural Reserve (Videira et al. 2009). The number of invited stakeholders attending the three workshops was 57, 18 and 20, respectively. The participatory process had two clearly distinctive stages: the first workshop, attended by a good mix of decision-makers, technicians, scientists and local citizens; and the second and third meetings, attended by a smaller and more homogenous subgroup constituted mainly by representatives from associations, regional and local administration. Participants helped in defining the problem (i.e. significant water management pressures and impacts in the river basin), developing the conceptual models during the first and second workshops, and have also served as data providers for the quantification of the simulation model presented in the third meeting.
these roles show a progression from one of the extremes to the middle: i) the participatory modeling process first helped participants develop conceptual models to define boundaries of a poorly defined complex problem and then; ii) the simulation model helped participants to start evaluating the trade-offs between water management alternatives.
III.2 Integrated Sustainability Assessment Case Study
The challenges driven by calls for integration and active participation in maritime policy assessment
conception of policy formulation and appraisal is needed to tackle the complexity and intricacies of persistent unsustainable trends (e.g. overexploitation of marine resources, climate change, acidification of the sea and multiple conflicting sea uses) which put at risk the provision goods and services that are vital to humankind, both ecologically and economically (EEA, 2010). This rationale underlies the concept of Integrated Sustainability Assessment (ISA) (Weaver and Rotmans, 2006) that fosters a cyclical, participatory process with four main stages scoping, envisioning, experimenting and learning that support open-ended exploration of solutions to complex sustainability issues. We defend that part of the solution in improving formulation and assessment of sustainable maritime strategies lies in promoting integrated, participatory processes whereby implicated stakeholders work collaboratively to define a shared problem understanding, envision desirable future paths and evaluate alternative policy options to achieve them. To test this hypothesis we have developed within the SUSTAINAMICS research project a framework for ISA that envisages an iterative cycle where participatory modeling is the main platform for stakeholder involvement in the assessment process (Videira et al. 2010) (Figure 3).
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Figure 3 Participatory modeling research framework for the ISA case study
Figure 3 was designed and implemented, including the analysis of stakeholders invited for a problem conceptualization workshop aimed at scoping the interrelationships underlying maritime problems in Portugal.
Coastal and maritime activities have traditionally been important to the Portuguese economy and to its historical, social and cultural identity (Carneiro, 2007). In 2006, the Portuguese government already presented
better use of oceanic and coastal resources in the Portuguese Exclusive Economic Zone (Figure 4). Nevertheless, the new challenges set by the EU IMP call for a reframing and integration of this strategy with a broader framework that branches out to other policies related with environmental quality of the marine environment, maritime spatial planning, maritime research and coastal zone management.
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Figure 4 Portuguese Exclusive Economic Zone (Adapted from: http://www.igeo.pt/)
At the setup stage we have conducted five exploratory interviews with key maritime policy-makers and
scientists for the purpose of becoming familiar with the main players involved in maritime affairs in Portugal. This allowed us to develop a preliminary list of stakeholder groups to invite to the ISA process. Around 70 stakeholders were invited for a preparatory interview and for the scoping stage of the ISA experience (Videira et al. 2011), including a mix of representatives from EU organizations, Portuguese administration, Industry, Trade Unions and Staff organizations, NGO and civil society, universities and R&D centers and multi-stakeholder consultative councils. From this group, it was possible to interview 37 stakeholders before the modeling workshop, which was attended by 22 participants. There were 20 different organizations represented at the workshop, at least one from the groups indicated above, with the largest share from governmental organizations and NGO.
Similarly to the Baixo Guadiana first workshop, participants helped in defining the problem, developing a shared conceptual model of maritime issues. Stakeholders were actively involved in the construction of the causal loop diagrams, working in five heterogeneous groups after the plenary briefing about workshop objectives and methodology. Each group addressed one of the most referred maritime sustainability issues revealed in the preparatory interviews: i) R&D, awareness and dissemination of sea-related activities, ii) maritime spatial planning, iii) costal zone impacts, iv) overexploitation of oceans and seas, and v) governance (Videira et al. 2011). Stakeholders identified and wrote down variables on white paper sheets and colour cards, drawing causal relationships between causes and consequences of problems. Subsequently, they have looked for feedback loops linking consequences to causes, in a procedure similar to the group model building approach described by Vennix (1996). After a first round of the diagramming exercise, all stakeholders changed groups for an iteration of the causal maps, except for a designated rapporteur who stayed in the original group and explained progress to others. At the end of the second round, rapporteurs presented the causal loop diagrams obtained in each group to the whole audience. A plenary debriefing added to systems understanding by identifying the interrelationships between the five system maps. For e
procedure on perceived leverage points to intervene in the system (Meadows, 1999).
IV. OUTCOME AND REFLECTION
IV.1. Lessons From the Baixo Guadiana Process
IV.1.1. Research Outcomes The Baixo Guadiana experiment was conducted in 2003 when the actual river basin planning process foreseen by the WFD was still starting in Portugal. At the time, there existed several uncertainties concerning
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the way the formal participatory processes promoted by water authorities would unfold. Thus, the case study was not designed to provide direct inputs to the planning process in the Guadiana river basin. It rather aimed at exploring research questions, relevant from a policy point of view, concerning the use of participatory modeling as an approach to promote social learning and active involvement of stakeholders in river basin planning processes. The timeframe of the experiment was limited to nine months, after which a set of guidelines on methods for active involvement of public and stakeholders was made available to river basin authorities and related EU agencies for the execution of integrated evaluation of projects adopting deliberative decision platforms (Videira et al. 2009). The outputs from the process included a causal loop diagram of the perceived river basin issues, a stock-and-flow model with a total of 91 variables distributed along the 3 model sectors (water resource management, nature conservation and socio-economic activities) and a draft action plan, with strategic objectives and measures that were informed by the scenarios simulated and analyzed during the final workshop (e.g. investments in water treatment, protection of ecosystem goods and services and new licenses for economic activities). The evaluation of the participatory process from a research point of view verifies the relationship
the effectiveness of the participatory modeling process, the quality of information used, the impact that the case study produced at the individual level and the learning effects in the stakeholder group. Figures 5 and 6 provide a synthesis of the evaluation results, based on observations collected during the workshops and the final questionnaires returned by 11 participants. The values in-between brackets represent the average level of agreement to a given statement (scores ranging from 1 highly disagree to 5- highly agree) and the
Figure 5 Outcomes concerning the process and the information used (Source: Videira et al. 2009).
The participation rate declined from the first to the second workshop, which was considered one of the limitations of the process. We have argued that the reasons behind this trend may have been a combination of (Videira et al. 2009): general dissatisfaction with the approach, agenda constraints, travel costs to attend the meetings, research nature of the events and the fact that there was no commitment from river basin authorities towards the implementation of the results. Notwithstanding, the core group of stakeholders attending the three
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workshops considered that the participatory modeling methodology was open, transparent and fair in providing opportunities for each agent to contribute to the models. The majority also agreed that the sequence of events was effective, the model building stages helped in structuring the discussions, relevant management alternatives were generated and strategic objectives were synthesized. The most positive aspects of the
Figure 6 Outcomes concerning the impact at the individual and group levels (Source: Videira et al. 2009).
The criteria used for measuring the effectiveness of the process (adapted Rouwette et al., 2002) indicate that impacts at the personal level higher than the effects in the functioning of the stakeholder group. The majority of participants agreed that the process managed to include the perspectives of the main stakeholders in the river basin, reaching medium to high impacts in the development of shared views/actions (consensus) and in the understanding of other participants (shared language) (Videira et al. 2009). Thus, the experience was successful in generating insights and facilitating learning about the river basin issues to those more actively involved. Participants declared to have learned about a new method to structure participation, which has increased their capacity to interrelate and integrate river basin pressures and impacts. IV.1.2. Policy Implications In Figure 7 we expanded the framework presented in Figure 2 to promote a comparison with the participatory processes actually implemented by the water authorities in Portugal for the characterization of river basins and identification of pressures and impacts.
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Figure 7 Participatory modeling research framework versus implemented participation framework for
Leading up to the RBMP currently under development, the National Water Institute (INAG) and the River Basin Administrations (ARH) promoted in 2009 the consultation on river basin significant water issues (QSiGA) in Portugal. The methodology, jointly developed by these organizations, included the identification of 29 pressures and impacts on water bodies and six issues of normative, organizational and economic relevance potentially applied to all river basins. The relevant QSiGA in each river basin were evaluated according to 15 criteria developed also by INAG and the ARH (INAG, 2009). The public participation procedure on QSiGA took place from February and January 2009. For each river basin a background document was made available for consultation at INAG, ARH and respective Internet websites. All interested parties were invited to send written comments on the background documents. Complementarily, an open invitation procedure was followed for public hearings in all ARH. Only one river basin authority (ARH-Algarve) used other participatory methods, namely a workshop format where participants worked more actively in small groups to discuss the QSiGA. In ARH-Alentejo, responsible for the Guadiana river basin, two public hearings of one day each took place in Évora (Portugal) and Mérida (Spain), attended by 96 and 66 participants, respectively. These sessions were advertised through the Internet, announcements in regional press, and e-mails to around 200 public and private organizations and local and regional associations (INAG, 2009). -centralized and traditional consultation approach, where authorities advanced a proposal the QSiGA list and then asked the public and stakeholders to comment on it. We argue that although there were strong efforts to promote public information and consultation these participatory events may fall short of the active
On the other hand, our modeling experience showed that it is possible to convene large stakeholder groups in a setting that fosters more active involvement and a creative atmosphere, and possibly complement the formal public hearing and written comments formats. The qualitative modeling approach and causal loop diagramming tools deployed in the Baixo Guadiana experience seemed to work well for involving stakeholders in one day workshop sessions, even if budgetary, agenda or other organizational constraints limit river basin authorities from commissioning more work-intensive mediated modeling exercises leading to computer-based simulation models. The conditions that seem to be needed for replicating the methodology in
-in, resources for conducting preliminary interviews and workshops with participants and modeling expertise. The latter may be a hindrance, as was expressed by Dores (2009) while discussing the possibilities for ARH to deploy participatory methods such as mediated modeling. Nevertheless, although ARH may not possess participatory modeling know-how, they
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can contract external consultants for this effect, if participatory budgets allow it (Dores, 2009), or develop this competences internally. With respect to substantial differences, the outcomes of the consultation approach followed in the majority of ARH differ from those achieved with the participatory modeling process. Participants in public hearings reacted to a previously defined list of QSiGA and although the collected comments were to some extent incorporated in the planning process (INAG, 2009), they did not seem to promote a thorough and holistic discussion of river basin pressures and impacts, their interconnections and respective intervention
river basin pressures and impacts were ide -interviews and modeling workshops. Figure 8 shows the conceptual diagram developed in the first modeling workshop and the relationship with QSiGA identified for the Guadiana river basin in the planning process.
Figure 8 Causal loop diagram from the participatory modeling workshop and QSiGA for the Guadiana river
basin (Adapted from Videira et al. 2009 and INAG/ARH-Alentejo, 2009)
It may be observed that the collaborative modeling process also allowed identifying some of the relevant QSiGA subsequently defined by the technical procedure established by the river basin authorities. Nevertheless, the approach also facilitated the recognition of a wider set of issues that were important for the stakeholder group. Furthermore, the causal loop diagram and the scoping model that was subsequently developed integrate these issues in a shared and holistic view of the pressures, problems and impacts in the river basin. Consequently, this led to a broader discussion of objectives and measures to implement in the river basin, which cut across many sustainability issues and arguably work in favor of deeper integration of water resources with other sectoral policies, as defended in IWRM.
IV.2. Lessons From the ISA Process
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IV.2.1. Research Outcomes With growing experimentation with methods and tools supporting ISA (de Ridder et al., 2007), we are interested in exploring the role of participatory modeling in providing a deliberative platform for conceptualizing problems and evaluating alternative policy scenarios in integrated sustainability assessment of maritime policies. The case study illustrates the use of qualitative system dynamics tools and a group modeling approach to support mapping of maritime sustainability issues. The goal was to explore how a systems perspective and causal loop diagramming may facilitate ISA scoping stages, where is it recommended to focus on the identification of interrelationships and causal structures underlying persistent problems (Videira et al. 2011). The most important outcomes concern the fact that participants were able to deliberate on the problems
between maritime issues and realization that solutions need to be planned holistically. For example, some causal relationships seem to have arisen especially due to deliberation among stakeholders, such as the need to invest in translation of scientific results to society as a pivotal link between R&D activities and promoting awareness of society regarding the value and potential of maritime resources. On the other hand, the leverage
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variables linking several of the problems that were addressed by the group (Videira et al. 2011). The evaluation of the workshop was supported by an ex-post questionnaire in which the majority of respondents agreed that the group was representative of the agents who have interests in maritime issues in Portugal and that problems were discussed in an open way, leading to a constructive exchange of ideas. Participants also agreed that the planned sequence of tasks helped to structure the discussions and created a common language for the analysis of maritime issues. On the downside, the assignment of a rapporteur to each group revealed a risk that such participant controls the discussions and mapping exercise, as commented by stakeholders in one of the small groups. Overall, respondents declared that causal loop diagrams are a useful tool for problem conceptualization and concurred that workshop results were interesting to communicate to others (Videira et al. 2011). The next steps in the implementation of the proposed ISA framework include developing a visioning workshop for the construction of a shared vision of the future for 2030 and a simulation model supporting the assessment of alternative scenarios for sustainable maritime policies. IV.2.2. Policy Implications Within the context of the EU IMP, one of the policy implications for EU Member States is the development of marine strategies for each of the identified marine regions. The Portuguese 2006 National Strategy for the Sustainable Development of the Ocean (ENM, 2006) will need to be reframed within this new policy background, and national authorities are currently implementing the MSFD leading to a marine strategy to ensure good environmental status in the marine environment by 2020. However, the MSFD lacks
effective a great risk of imbalance between the emphasis placed on scientific inputs to marine policy-making processes and the comparatively limited focus on stakeholder inputs. Hence, our ISA framework supports the investigation of new forms of complementing the traditional
-formulated policy. One of the risks that we draw attenthe problems are at the scoping stages of policy formulation and assessment. In messy and complex problem
ix, 1996). Particularly in the field of maritime policies where vast areas encompass a multitude of sustainability problems, any participatory
interviewed at the beginning of the ISA process held very different perceptions on the main maritime
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problems. It is also evident that the stakeholder group did not recognize some of the priority policy areas proposed in the ENM.
Figure 9 Perceptions of problems by interviewed stakeholders distributed according to policy areas of the
Portuguese 2005 Maritime Strategy (Source: Videira et al. 2011). Given this disparity, the conceptual exercise was very important to provide a holistic and more meaningful view of issues and their interrelationships. The preparatory interviews and conceptual mapping workshop described in this paper illustrate how systems thinking tools may facilitate such alignment between
ent and assessment of maritime policies. This step is also defended by von Korff et al. 2010 who propose a set of principles for participatory water management, including a preliminary assessment of stakeholder interests as the basis for the design of these processes.
V. CONCLUSIONS
In this paper we aimed at investigating two distinct policy frameworks in Europe that are leading change towards integrated management of inland and marine waters. Both frameworks underline the importance of encouraging active involvement of stakeholders in the policy-making and assessment processes. Nevertheless, our analysis indicates that although important progresses have been made by water authorities, formal participation processes still seem to lag best practices for active involvement. As proposed by De Stefano (2010), after reviewing participatory processes in several European countries at the beginning of implementation of WFD, improving the transparency and continued involvement of water stakeholders should be promoted by more open discussions to foster confidence in the usefulness of legal participatory provisions. The approaches described in the paper provide avenues for the ongoing planning, assessment and monitoring processes of river basin management plans and marine strategies in Europe. These cases show how more inclusive and deliberative events may be conducted in the future, as a complement of formal consultation procedures, which is not to say that participatory modeling will fit any situation nor that it is
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support, timing for participation, ethical and political reasons (De Stefano, 2010; Fletcher, 2007). Methodologically, the two participatory modeling research processes started with a qualitative approach, where stakeholder groups up to around 60 participants developed a shared system map of water issues at early problem scoping stages. This may be a straightforward and cost-effective solution for engaging larger groups and/or stakeholders who typically participate in few events (e.g. decision-makers). Such systemic view directs the modeling process toward the recognition of the main feedback loops governing water issues, while facilitating other valuable interim lessons such as the identification of leverage intervention points. Nevertheless, only the further development of mediated, computer-generated models may provide deeper insights on structure-behavior relationships, supporting the design of new policy alternatives, analysis of trade-offs between policy options, and providing strategic advice for water decision-making processes (Bots and van Daalen, 2008; van den Belt et al., 2011). The lessons presented in this paper suggest that the pdifferent governmental and non-(Mostert et al., 2008), is one of the most substantial results that may arise from collaborative modeling experiences for water management. Post-workshop evaluations revealed that participatory modeling mixes some of the ingredients essential for social learning, such as recognition of interdependence between issues and actors, interaction among stakeholders, respect for and exchange of different worldviews and co-production of potential solutions (Mostert et al., 2008). Further experimentation and monitoring of outcomes of these and other experiences are suggested for clarifying the role of participatory modeling and foster its continued application in IWRM.
VI. ACKNOWLEDGMENTS The authors acknowledge the support of the European Commission EESD-RTD Programme and the Portuguese Science Foundation to the research projects SUSTAINAMICS (PTDC/AMB/66909/2006) and ADVISOR (EVK1-CT-2000-00074), respectively. We would also like to thank the effort and enthusiasm of all stakeholders that have participated in the described case studies.
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Videira, N., Antunes, P., Santos, R., Lopes, R., 2010. A Participatory Modelling Approach to Support Integrated Sustainability Assessment Processes. Systems Research and Behavioral Science, 27(4): 446-460.
Videira, N., Lopes, R., Antunes, P., Santos, R., Casanova, J., Duarte, J., 2011. Mapping maritime sustainability issues with stakeholder groups, 5th European System Dynamics Workshop (EuSDW),
-26 2011
Voinov, A., Bousquet, F., 2010. Modelling with stakeholders, Environmental Modelling & Software, 25:1268-1281.
management and beyond, Ecology and Society, 15(3):1, http://www.ecologyandsociety.org/vol15/iss3/art1.
Weaver P, Rotmans J. 2006. Integrated Sustainability Assessment: what is it, why do it, and how? International Journal of Innovation and Sustainable Development, 1(4): 284 303.
Wright, S., Jacobsen, B., 2011. Participation in the implementation of the Water Framework Directive in Denmark: The prospects for active involvement, Water Policy, 13: 232-249.
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COLLABORATIVE MODELING FOR DECISION SUPPORT IN WATER RESOURCES: PRINCIPLES AND BEST PRACTICES by Stacy Langsdale, Allyson Beall, Elizabeth Bourget, Erik Hagen, Scott Kudlas, Richard Palmer, Diane Tate and Bill Werick1
ABSTRACT Collaborative Modeling for Decision Support, a general term for Shared Vision Planning, refers to
Practitioners and advocates claim that the approach will lead to better water management (that balances interests more effectively) and will help reduce the likelihood of costly legal delays. These claims are easy to make, but the benefits will only be realized if the process is conducted effectively. To provide guidance for how to conduct a collaborative modeling process effectively, a task committee co-sponsored by the
Water Resources developed a set of Principles and Best Practices for anyone who might convene or conduct collaborative modeling processes. The guidance is intended for both conflict resolution professionals and modelers, and our goal is to integrate these two fields in a way that will improve water resources planning and decision making. Principles will be presented along with brief case examples. The document is available at: http://www.computeraideddisputeresolution.us/bestpractices/. (KEY TERMS: Collaborative modeling; participatory modeling; stakeholder participation; best practices)
I. INTRODUCTION
As water-related professionals are well aware, water resource planning & management is characterized by multiple layers of complexity and uncertainty, sourcing from natural and human systems, conflicting interests and values, and interest groups and the public demanding involvement. Addressing these challenges requires both technical skills (understanding of system aspects such as hydrology and ecology and how they interact) and process skills (appreciation of institutional setting, ability to engage stakeholders and build their trust). Collaborative Modeling for Decision Support is one approach that combines both skill sets to manage water resources in a fair and beneficial process. Collaborative Modeling for Decision Support is
developed by different practitioners and expert communities over recent decades, such as Shared Vision Planning, Mediated Modeling, Group Model Building, Computer Aided Negotiation, and Participatory
Best Practices has been limited.
To assist in the training of new practitioners, and to provide support to ensure high standards for existing practitioners, the Environmental Water Resources Institute (EWRI) of the American Society of Civil Engineers (ASCE) and the Institute for Water Resources (IWR) of the U.S. Army Corps of Engineers (USACE) jointly sponsored a Task Committee to develop a set of Principles and Best Practices for Collaborative Modeling for Decision Support. Released in February 2011 after ample peer-review, the
case studies. The Task Committee included a range of expertise and experience, and included representatives
1 Respectively, Institute for Water Resources, USACE, 7701 Telegraph Road, Alexandria, VA 22315, PH: 703-428-7245, [email protected]; Washington State University, Pullman, WA; Institute for Water Resources, Alexandria, VA; Potomoi, LLC, The Hague, Netherlands; Virginia Department of Environmental Quality, Richmond, VA; University of Massachusetts, Amherst, MA; Denver, CO; Werick Creative Solutions, Inc., Culpeper, VA.
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of academia, federal and state government agencies, and private consulting, and developed the principles with two years of volunteer effort.
II. THE PRINCIPLES
The following set of principles focus on neither how to construct a model, nor how to lead participatory processes, but on how to do both simultaneously. Refer to the full descriptions and supporting material in the full document (Langsdale et al. 2011; available at www.computeraideddisputeresolution.us/bestpractices).
1. Collaborative modeling is appropriate for complex, conflict-laden decision making
processes where stakeholders are willing to work together. 2. All stakeholder representatives participate early and often to ensure that all their relevant
interests are included. 3. Both the model and the process remain accessible and transparent to all participants. 4. Collaborative modeling builds trust and respect among parties. 5. The model supports the decision process by easily accommodating new information and
quickly simulating alternatives. 6. The model addresses questions that are important to decision makers and stakeholders. 7. Parties share interests and clarify the facts before negotiating alternatives. 8. Collaborative modeling requires both modeling and facilitation skills.
Three themes from these principles are described in more detail in the following sections.
IV. WHEN TO USE COLLABORATIVE MODELING FOR DECISION SUPPORT
Collaborative Modeling for Decision Support does take a considerable investment of time and resources in the early planning stages, so careful consideration should be given as to when it should be utilized. Note, however, that engaging stakeholders and decision makers throughout the planning and decision process can reduce resistance to implementation, so overall project length and cost may actually be reduced (Shabman and Stephenson 2007).
Most problems in water resources planning and management are not straight-forward, but do need to consider multiple objectives, and have considerable uncertainty about hydrologic variability and trends, particularly with climate change, as well as uncertainty about human use of the watershed and resources. If potential decisions may affect stakeholders, then they should be allowed to have input up front. The saying,
it certainly will not build goodwill or trust for the agency.
Since there are many parties involved in a collaborative modeling process, all parties need to be willing and able to participate. This includes the convening agency or party, sponsors, decision makers, and stakeholders. Frequently, a convening agency or sponsor may decide that they are going to lead a collaborative modeling effort; however, if the other parties are not supportive, the process will not be very collaborative. Certain stakeholders may need resources to attend meetings, or training in computer skills, and providing these can support more balanced representation of interests. Decision makers, particularly elected officials, may be interested but unable to invest time to attend all sessions. Determine strategies to keep them
ssions, and designating a representative from their office to attend all sessions. Ensuring the process meets the needs of the decision maker is critical for ensuring the results of the process and will be supported and the investment by all parties will not be wasted.
V. WHY INVOLVING STAKEHOLDERS IS CRITICAL
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Actively involving stakeholders in a study is the best way to ensure that their interests are captured
and that the effort supports the decision at hand. A major difference between pure technical research and planning studies is that pure research
provides new insight, while planning studies support a decision to act (or to not act) in a way that will affect the relationship between humans and one or more resources. Involving stakeholders, all those who can affect, may be affected by, or who have an interest in a decision, is the best way to ensure that all interests are considered in a decision. Continuing to engage representatives of these interests throughout the process improves understanding
To be most effective, stakeholder representatives should be engaged early and often, so they have
input in the problem definition, in the performance metrics, in developing and evaluating alternatives, and in selecting a preferred alternative. Identifying all interests, and representatives of those interests, can take considerable effort, but is critical for success.
Often when building models, technical experts determine what data they have available and then put this data together to build a decision support tool that is most useful from their own perspective. In contrast, in the collaborative modeling approach, the process and model are both defined by two questions which are
leading the effort must not just ask these of each other, but of all the participants. When trying to understand complex systems it is very easy to become focused on details, so it is critical to frequently verify that the effort is relevant to the end goal. Planning-level studies typically do not need a high level of precision, so detailed information and data is not always required.
let stakeholders review it and add their own ideas how to improve it. It may be uncomfortable to show incomplete models, however, the iterative development process will be rewarding for everyone involved. In fact, the dialogue about the model at these sessions may be as valuable as, if not more than, the end model itself because this is when shared learning occurs.
VI. KEEP THE PROCESS AND MODEL ACCESSIBLE AND TRANSPARENT TO ALL
In order to effectively engage throughout the effort, both the process and the model need to remain
transparent to all parties. Include stakeholders in decisions about meeting frequency and objectives, as well as what software to use. In all communication, avoid technical jargon, acronyms, and field-specific language. Select software that is easy to learn and can be made available to all. Communicate limitations and model uncertainty to ensure that the results are interpreted appropriately. Document and distribute meeting minutes, and provide documentation in and separate from the model. Beyond doing these explicit actions, the best way to ensure the model remains transparent is to continue to ask the participants or end-users how to make it clear to them, since something that is obvious to one person is not always obvious to someone with different expertise or experience.
VII. SUMMARY
Collaborative Modeling for Decision Support can be an effective approach and rewarding experience
for all those involved. However, the parties involved need to move forward in concert from the earliest stages of deciding whether the approach is even appropriate or if resources are available to support it, to defining
ensuring that the process and model remain transparent. When conducted well, the approach can lead to decisions that effectively balance multiple interests, and are supported through implementation. The shared learning and social capital that is built through the process supports management of the resource over the long term, while provides a foundation to build upon when confronting future decisions. Therefore, collaborative modeling enables more sustainable water resources management.
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The lead authors team hopes that this set of Principles and Best Practices will be a widely-distributed resource for those who would like to convene, support, or participate in a Collaborative Modeling for Decision Support process, and thus ensure that the approach realizes the benefits that it can, as we know through experience.
VIII. ACKNOWLEDGMENTS
The Author Team is grateful to the contributors and many reviewers who provided a range of
perspectives and increased the quality of our product.
IX. REFERENCES Langsdale et. al. 2011. Collaborative Modeling for Decision Support in Water Resources: Principles and
Best Practices. Environmental Water Resources Institute, Reston, VA and Institute for Water Resources, Alexandria, VA and. [Available at: www.computeraideddisputeresolution.us/bestpractices]
Lorie, M. 2010. Computer-Aided Dispute Resolution 2nd Workshop: Summary and Strategic Plan. Institute for Water Resources, Alexandria, VA. IWR Report 2010-R-5.
Shabman, L. and K. Stephenson. 2007. Environmental Valuation and Decision Making for Water Project Investment and Operations: Lessons from the FERC Experience. Institute for Water Resources, Alexandria, VA. IWR Report 2007-VSP-01.
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EVALUATING THE OUTCOMES OF COLLABORATIVE MODELING by William Michaud1
ABSTRACT Does collaborative modeling improve the outcomes of participatory Integrated Water Resources Management (IWRM)? How does collaborative modeling improve these outcomes? Does it always work? Under what conditions is collaborative modeling most appropriate? The U.S. Army Corps of Engineers' Institute for Water Resources (IWR) developed an evaluation framework to help address these questions. The framework uses a "theory of change" to link the effects of collaborative modeling on decision-making processes with improvements in the extent to which resource management decisions, practices, and policies balance social, environmental, and economic needs. Both practitioners' and participants' experiences suggest that under the right circumstances, collaborative modeling can generate these beneficial outcomes. IWR developed performance measures and a survey tool to systematically capture these experiences and evaluate the outcomes of collaborative modeling processes. These measures and tool can provide immediate feedback during a project to determine whether collaborative modeling is having the desired effect and whether course correction is warranted. Over the longer-term, the systematic evaluation of collaborative modeling processes will help demonstrate in what ways and under what circumstances collaborative modeling is effective, inform and improve best practices, and raise awareness among water resource planners regarding the use of collaborative modeling for IWRM. Key terms: collaborative modeling, participatory modeling, evaluation, water resources planning
INTRODUCTION
A key tenet of Integrated Water Resources Management (IWRM) is the imperative for participation. The Dublin
into practice have faced and continue to face significant challenges (Allan, 2003; Gooch and Huitema, 2008; Mostert, 2003). Alternative platforms have been developed to better integrate the interests, perceptions and values of affected parties in water resources planning, including deliberative visioning, participatory modeling, and social multi-criteria evaluation (Antunes et. al., 2009). Participatory modeling involves processes in which stakeholders are involved in model development and encompasses approaches such as group model building, mediated modeling, and Shared Vision Planning (Langsdale, 2007).
The Shared Vision Planning approach was pioneered by the U.S. Army Corps of Engineers, Institute for Water Resources (IWR) in the early 1990s as a means for increasing substantive participation in water resources planning. Shared Vision Planning employs, among other elements, the use of a collaboratively-built systems model (Cardwell et. al., 2009). IWR has partnered with other U.S. government agencies and practitioners to form a community-of-practice to help establish and disseminate best practices in the field of collaborative modeling for decision support (CMDS). As conceived, CMDS includes processes referred to as collaborative modeling, participatory modeling, mediated modeling, group model building, computer-aided dispute resolution, and others. The Environmental Water Resources Institute (EWRI) and IWR have recently published set of principles and best practices for CMDS (Langsdale et. al., 2011).
A key challenge for the field is to systematically evaluate whether and to what extent collaborative modeling and similar processes result in real improvements in participation (Rouwette et. al., 2002). In 2007, IWR set out to develop an evaluation framework to address this need. The resulting framework established a theory-of-change describing how collaborative modeling processes are intended to improve water resource management decisions and a methodology for evaluating this outcome (Michaud 2009). The IWR collaborative modeling evaluation framework identifies and addresses key challenges such as defining critical end outcomes, establishing the link between the collaborative modeling activities and these outcomes, and controlling for external factors that significantly affect these outcomes. Critical challenges remain in these and other areas. The IWR evaluation framework and some of these challenges are discussed below. First, the objectives of evaluation are reviewed as a foundation for the remainder of the paper.
EVALUATION OBJECTIVES
1 William Michaud, P.E., SRA International, Inc., 3434 Washington Blvd., Arlington, VA 22201, PH: 860-738-7501, [email protected]
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Evaluation of collaborative modeling processes could help address the following objectives: 1) provide mid-course feedback and help inform the effectiveness of specific process applications; 2) assess whether and how collaborative modeling results in beneficial outcomes and under what circumstances; 3) raise awareness of collaborative modeling processes and potential benefits and help ensure that this approach is appropriately considered in planning process design and development; and 4) over the long-term, contribute to the state of knowledge and improvements in collaborative modeling practice.
The first of these objectives focuses on monitoring specific collaborative modeling processes and could be accomplished on a case-by-case basis. To achieve the rest of these objectives, it will be necessary to systematically compile and evaluate information across multiple cases where collaborative modeling processes have been applied. Rouwette et. al. (2002) review existing process assessments and argue for development of a research program and standards toward this end. The CMDS community-of-practice has explored the need, practical implications, and challenges associated with compiling and evaluating information across multiple cases of collaborative modeling processes (Lorie, 2010).
LOGIC FRAMEWORK
Effective evaluation requires that a theory-of-change be developed that relates activities (e.g., collaborative modeling process decisions) to outcomes (e.g., improved participation in water resources planning). The IWR evaluation framework addresses the following questions in developing the theory of change: 1) how does collaborative modeling better integrate information and stakeholder interests; 2) how does collaborative modeling change decision dynamics; 3) how do these changes translate into improvements in the planning process; 4) how do these changes in modeling and planning processes result in higher quality recommendations; and 5) how do these processes and recommendations result in better resource management outcomes.
A logic framework was developed to map the theory linking process decisions to resource management outcomes, create a common language for dialogue among practitioners and evaluators, and help identify the process attributes and outcomes that are most critical to measure to support process-specific and cross-process evaluation.
The logic framework consisted of a logic model, describing the manner in which collaborative modeling is intended to affect participants, processes, and outcomes, and a context model, mapping the complex interactions between collaborative modeling and planning processes and the interactions of these process spheres with external factors. The context model proved particularly important for defining the boundaries between collaborative modeling processes, planning processes, and the planning setting and for identifying factors to be considered when comparing results across collaborative modeling cases. Figure 1 presents a high-level summary of the context model, showing the logical relationships and factors considered in the evaluation framework.
EVALUATION MEASURES
Building on the logic framework, IWR developed thirty-six evaluation measures designed to capture information about the planning setting, stakeholder participation, modeling and planning processes, and modeling and planning outcomes (see Figure 1). IWR developed a survey to collect information based on these evaluation measures. The survey incorporated the U.S. Insti -Agency Evaluation Study Mediation Participant questionnaire (USIECR, 2008), supplemented to include questions designed to more specifically evaluate collaborative modeling processes. The survey was tested by former participants in collaborative modeling
Figure 3 -‐ Context for Evaluating Collaborative Modeling Processes
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processes and was refined based on their feedback. The final suite of evaluation measures and the companion survey are presented in Michaud (2009). IWR and the CMDS community-of-practice have developed on-line versions of the survey.
Process setting, design, and implementation measures were developed as a means for capturing information about the specific contexts within which collaborative modeling processes are employed, design choices, and situations encountered during implementation. Examples of these measures are highlighted in Table 1. Planning setting measures are designed to capture information about the baseline conditions that existed at the outset of the process as well as information regarding the overall institutional setting within which the process took place. Measures of the stakeholder participation process address questions of not only how the process was designed but also how it occurred, recognizing that both practitioners and stakeholders make choices that influence process outcomes. These setting and process measures will allow researchers to explore relationships among process design choices, implementation, and outcomes and to control for variations in context when evaluating these relationships across different modeling processes.
Outcome measures were designed to capture the effects of the collaborative modeling process on planning and resource management outcomes. Outcome measures are defined at three levels, corresponding to their proximity to the collaborative modeling process and the extent to which the modeling process is expected to exert influence on these outcomes. Model-level outcomes are most directly influenced by the choices made by the modeling team at the outset and over the course of the model development process. Modeling process-level outcomes are influenced by not only the modeling process but also by choices made in implementing stakeholder participation. Planning-level outcomes are the farthest removed from the modeling process and can be influenced by choices made outside of the modeling process and by factors over which the planning process may have little influence. Examples of outcome measures are presented in Table 1.
An additional category of measures was included in the IWR evaluation framework: process satisfaction, cost, and duration. This category applies a different lens to collaborative modeling evaluation, focusing on investments in the process. These measures are intended to capture information needed to understand the relationships between these investments and process and resource management outcomes.
CRITICAL CHALLENGES
Defining and Evaluating End Outcomes
Ultimately, a collaborative modeling process will be judged based on the quality of the associated water resource management outcome (Werick and Palmer, 2009). Therefore, the first step and key challenge in developing a framework for evaluating collaborative modeling processes is defining the basis for judginmanagement outcomes. From an analytical perspective, if differences in the quality of resources management outcomes
Table 1 Examples of Evaluation Measures
Setting, Design, and Implementation Measures Outcome Measures
Planning setting Problem focus Level of certainty and clarity at
outset Level of conflict at outset Institutional context
Stakeholder participation process
Process design and implementation Actual stakeholder participation
Planning and modeling processes
Planning process description Model description/platform Modeling process description Integration of planning and
modeling processes
Model-level outcomes Integration of stakeholder interests Model transparency Interactive capacity of the model Confidence in the model
Modeling process-level outcome Integration of available data in model Quality of alternatives evaluation
process Planning-level outcome
Change in knowledge Change in awareness and
understanding Change in trust Change in stakeholder cooperation Change in capacity to communicate Evolution and clarity of objectives Quality of recommendations Quality of actions Institutional learning and change Adaptive management capacity
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can be measured and linked to process choices and experiences, collaborative modeling processes could be compared to one another and to alternative, non-collaborative approaches. The three pillars of sustainable development economic development, social development, and environmental protection (United Nations, 2005) provide an example of the dimensions to be considered in qualifying water resource management outcomes. However, even measures of these dimensions are elusive (OECD, 2004).
For the purposes of establishing an evaluation framework for collaborative modeling processes, IWR chose an approach that conceptually weighs the quality of a resource management outcome based on the extent to which it
the process in terms of stakeholder representation, including the extent to which stakeholders had a substantive and proportionate effect on planning outcomes. The framework assesses the extent to which the quality of stakeholder participation can be attributed to the collaborative modeling process, the extent to which the recommendations of the planning process were informed by the collaborative modeling process, and the extent to which the ultimate resource management actions were consistent with the recommendations of the planning process.
The framework represents the theory that a collaborative modeling process, by better integrating the broad range of stakeholder interests in the alternatives evaluation and planning decision processes, has the capacity to increase the extent to which interests are truly represented in resource management recommendations. To the extent that resource management actions are consistent with these recommendations, collaborative modeling has the capacity to improve the
ing needs. Note that this connection between collaborative modeling processes and resource management outcomes depends on factors that may be beyond the control of the modeling process, including the quality of the planning process (e.g., in terms of the representativeness of the stakeholders engaged) and the extent to which resource management decisions incorporate the recommendations of the planning process. These issues are addressed in the following section.
Evaluating Process-Outcome Relationships
The experience of practitioners in the collaborative modeling field is that the outcomes of a collaborative modeling process and the resource management outcomes are not always closely linked. This could result from weak links to the overall planning process or the existence of decision dynamics outside of the planning process (Werick and Palmer, 2009). The framework recognizes the importance of understanding this phenomenon as a way not only of controlling for these factors when evaluating collaborative modeling processes but also of elucidating the types of factors that should be considered when deciding whether to invest in a collaborative modeling process and when identifying critical process design elements.
The IWR evaluation framework explicitly embeds the theory that the influence that collaborative modeling processes exert on resource management outcomes decreases as decisions become increasingly removed from the process organizationally and in time and as modeling outcomes face increasing competition from external factors. This is illustrated in Figure 2. The framework includes measures of process setting, as described above, and process-from the planning process were influenced by the collaborative modeling process and consistency between planning recommendations and resource management actions. The survey questions associated with these measures ask respondents to identify the sources of inconsistency, where it exists (see questions 19A and 19B in Michaud, 2009, Appendix D), as a means of elucidating information that could be useful for investment and design decisions.
Implementation Considerations
The above sections identify key challenges associated with the evaluation of collaborative modeling processes and the approach used by the IWR evaluation framework to address these challenges. Nonetheless, significant challenges remain, both in terms of creating a robust methodological framework and implementing a cross-process evaluation program. Some of these challenges are discussed in terms of implementation considerations in Michaud (2009). Others,
Figure 4 Considering External Factors when Linking Process and Outcomes
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such as how to encourage practitioners to use the IWR survey and contribute to an evaluation database, where to house the data, how to provide researchers with access to the data, how to coordinate research efforts, and how to allow the evaluation measures to evolve, are identified in Lorie (2010).
Integral to these implementation considerations, are questions of overall evaluation design. The current survey relies on participant and practitioner observations and perceptions. While the information collected using this approach could provide useful insights by itself, it would be most useful if supplemented with information collected using other research methods. These could include follow-up interviews with survey participants, process observation, constructed counterfactual methods, expert elicitation, and other approaches. These approaches would complement the breadth enabled by the survey approach with deeper insights into the relationships between collaborative modeling processes and resource management outcomes. They could also help researchers incorporate other factors into the evaluation such as objective
Kerkhof (2004).
SUMMARY
Participation in water resources planning is a critical principle of IWRM, and implementation of this principle involves significant challenges. Experience suggests that under certain circumstances, involving stakeholders in the development of the systems model used to evaluate water resource management alternatives can be an effective approach for substantively increasing their participation. Evaluation of collaborative modeling processes will help identify the extent to which collaborative modeling improves water resource management outcomes and under what circumstances. It will also provide feedback to process implementers regarding when collaborative modeling is appropriate and regarding key considerations to include in process design and implementation.
Several challenges exist for establishing and implementing a robust collaborative modeling evaluation framework. These include methodological challenges, such as challenges associated with identifying and measuring the quality of water resources management outcomes and analyzing relationships between collaborative modeling processes and these outcomes. In the long-run, a critical review of collaborative modeling processes could help parties engaged in water resources management decisions better understand the utility of this approach and, where appropriate, employ collaborative modeling to improve participation in a way that has a real and lasting effect on water resource management decisions. This could be one more step in attaining the promise of IWRM.
ACKNOWLEDGMENTS
I would like to acknowledge Stacy Langsdale and Hal Cardwell of the U.S. Institute of Water Resources, for their thoughtful and patient efforts during the development of the IWR collaborative modeling framework and report. I would also like to acknowledge the members of the CMDS Steering Committee and for participants in the 2nd CMDS workshop for their insights into the critical elements and path forward for implementing evaluation in this field. For this group,
just a buzz word, it is a philosophy to live by.
IX. REFERENCES Allan, T., 2003. IWRM/IWRAM: a new sanctioned discourse? Occasional Paper 50, SOAS Water Issues Study Group,
School of Oriental and African Studies/King's College London, University of London. Antunes, P., G. Kallis, N. Videira and R. Santos, 2009. Participation and evaluation for sustainable river basin
governance. Ecological Economics 6, 931-939. Biswas, A.K., 2004. Integrated water resources management: a reassessment. Water International 29:2, 248 256. Cardwell, H., S. Langsdale and K. Stephenson, 2009. The Shared Vision Planning Primer: How to incorporate computer-
aided dispute resolution in water resources planning. U.S. Institute for Water Resources, Report No. 2008-R-02, Alexandria, VA.
Gooch, G.D. and D. Huitema, 2008. Participation in water management: theory and practice. In J.G. Timmerman, C. Pahl-Wostl and J. Möltgen, Eds., The adaptiveness of IWRM: analysing European IWRM research. London: IWA Publishing.
ICWE, 1992. The Dublin Statement and Report of the Conference. International conference on water and the environment: development issues for the 21st century; 26-31 January 1992, Dublin.
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Jordana, J. and D. Sancho, 2004. Regulatory designs, institutional constellations and the study of the regulatory state. The politics of regulation. Institutions and regulatory reforms for the age of governance. Ed. Jacint Jordana and David Levi-Faur. Cheltenham: Edward Elgar, 296-319.
Langsdale, S.M., 2007. Participatory model building for exploring water management and climate change futures in the Okanagan Basin, British Columbia, Canada. Thesis, University of British Columbia, April.
Langsdale et. al., 2011. Collaborative Modeling for Decision Support in Water Resources: Principles and Best Practices. Environmental Water Resources Institute, Reston, VA and Institute for Water Resources, Alexandria, VA. [Available at: www.computeraideddisputeresolution.us/bestpractices]
Lorie, M., 2010. Computer-Aided Dispute Resolution 2nd Workshop: Summary and Strategic Plan. Institute for Water Resources, Report 2010-R-5, Alexandria, VA.
Michaud, W.R., 2009. Performance Measures to Assess the Benefits of Shared Vision Planning and Other Collaborative Modeling Processes. U.S. Institute for Water Resources, Report No. 2009-R-07, Alexandria, VA.
Mostert, E., 2003. The challenge of public participation. Water Policy 5:2, 179-197. Organisation of Economic Cooperation and Development (OECD), 2004. Measuring sustainable development:
integrated environmental, economic and social frameworks. OECD, Paris. Rouwette, E.A.J.A., J.A.M. Vennix, T. van Mullekom, 2002. Group model building, a review of assessment studies.
System Dynamics Review 18:1 (Spring 2002) 5-45. United Nations, 2005. General Assembly resolution 60/1, 2005 World Summit Outcome, 24 October 2005, A/Res/60/1. U.S. Institute for Environmental Conflict Resolution (USIECR), 2008. Mediation participant evaluation (agreement
seeking). OMB No. 3320-0004. http://www.ecr.gov/pdf/MED_PartQuest.pdf Accessed May 2011. Van den Belt, M., 2004. Mediated Modeling: A System Dynamics Approach to Environmental Consensus Building.
Island Press. Van de Kerkhof, 2004. Debating Climate Change: A Study of Stakeholder Participation in an Integrated Assessment of
Long-Term Climate Policy in the Netherlands. Utrecht, The Netherlands: Lemma Publishers. Werick, W. and R. Palmer, 2009. When should shared vision planning be used.
http://www.sharedvisionplanning.us/docs/IsSharedVisionPlanningRightforYou.pdf . Accessed May 2011.
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Session 10: Case Studies in Collaborative Modeling I Convening Stakeholder-Based Processes
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DEVELOPING A SHARED VISION DECISION SUPPORT SYSTEM FOR THE CONNECTICUT RIVER BASIN by Richard Palmer1, Kim Lutz2, Austin Polebitski3
This paper presents the results of a joint effort between the Nature Conservancy, the USGS, the US Army Corps of Engineers and the University of Massachusetts Amherst to create a decision support system to minimize the conflicts that arise in the Connecticut River, identify opportunities to improve the flows in the river system to meet environmental and habitat concerns, maintain existing functions of the river, that include water supply, flood control, and hydropower production, and to engage stakeholders throughout the process. The decision support system combines both a simulation model and an optimization model to identify operational opportunities, test the feasibility of new operating procedures and to evaluate the potential impacts of climate change on the system. There is a significant need for an integrated, decision support system because the Connecticut River flows through four states (Connecticut, Massachusetts, Vermont, and New Hampshire), contains over 70 major dams (and over 1,000 documented dams), and operational changes may impact many users.
This paper begins with a characterization of the Connecticut River and its major facilities. It then describes a shared vision planning approach that was applied to defining the challenges facing the region, gathering information concerning stakeholder interest, defining current system operation and in incorporating this information into both the simulation and optimization models. The paper presents existing trade-offs between management policies that emphasize specific uses. It concludes with a discussion of likely operating alternatives that address stakeholder interests, the impacts of climate change on the system, and ways in which the shared vision planning models can be used to minimize conflicts within the basin.
1. Professor and Head, Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, MA
2. The Nature Conservancy, Director, Connecticut River Program, 25 Main Street, Suite 220, Northampton, MA 01060
3. Research Assistant Professor, Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, MA
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COLLABORATIVE MODELING FOR DECISION SUPPORT IN THE UPPER SAN PEDRO BASIN (ARIZONA): WHAT ELSE DO WE NEED TO WALK A SUSTAINABLE PATH? by Aleix Serrat-Capdevila1,2, Juan B. Valdes1,2, Hoshin V. Gupta2, Anne Browning-Aiken4, Kevin Lansey3, Timothy L. Finan5
(1) International Center for Integrated Water Resources Management (ICIWaRM-‐UNESCO) [email protected], Tel: (520) 9796438
(2) Department of Hydrology and Water Resources, The University of Arizona (3) Department of Civil Engineering and Engineering Mechanics, The University of Arizona (4) Udall Center for Studies in Public Policy, The University of Arizona (5) Department of Anthropology, The University of Arizona
ABSTRACT This presentation will analyze how the collaborative development process of a decision-support system (DSS) model can effectively contribute to increasing the resilience of regional social ecological systems. In particular, we have focused on the case study of the transboundary San Pedro Basin, in the Arizona-Sonora desert region. This is a semi-arid watershed where water is a scarce resource used to cover competing human and environmental needs. We outline the essential traits in the development of the decision support process that contributed to an improvement of water-resources management capabilities while increasing the potential for consensual problem solving. Comments and feedback from the stakeholders benefiting from the DSS in the San Pedro Basin are presented and analyzed within the regional context. We discuss how multidisciplinary collaboration between academia, stakeholders and decision-makers can be an effective step towards collaborative management. We present a simple comparison of process structure between the Rio Grande and the San Pedro cases and make the analogy with the Shared Vision Planning approach. We also stress the need for holistic integrative modeling as a requirement for effective adaptive management. These participatory planning processes provide a common arena for designing and evaluating water management policies and future scenarios.
Disclaimer: The paper below is a blend of following two publications:
Serrat-Capdevila, A., Browning-Aiken, A., Lansey, K., Finan, T. and J.B. Valdés (2009) Increasing Socio-Ecological Resilience by placing science at the decision table: The role of the San Pedro Basin Decision Support System Model (Arizona). Ecology and Society 14(1): 37. [online] URL: http://www.ecologyandsociety.org/vol14/iss1/art37/
Serrat-Capdevila, A., Valdes, J.B., Gupta, H. (2011) Decision Support Systems in Water Resources Planning and Management: Stakeholder participation and the sustainable path to science-based decision making. In the book: Efficient Decision Support Systems: Practice and Challenges From Current to Future / Book 1", ISBN 978-953-307-165-7. InTech - Open Access Publisher. (In Press)
Some writing is adapted, and some has been copy/pasted. See papers above for references. Introduction:
We analyze how the collaborative development of a decision-support system (DSS) can effectively contribute to increasing the resilience of regional Socio-Ecological Systems. We focus on the transboundary San Pedro Basin in the Arizona Sonora as a case study, and later compare it with the Rio Grande case study. The San Pedro is a semi-arid watershed where water is a scarce resource that is used to meet competing human and environmental needs. We explore the traits essential to the development of a decision- support process that contributed to an improvement of water resources management capabilities here (and advancing regional sustainability goals), while increasing the potential of consensual problem solving. Stakeholders
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(working in a partnership) who benefited from the DSS in the San Pedro Basin have provided comments and feedback on the process of model construction and use. We analyze these within regional, social, and institutional contexts.
I - The San Pedro Basin: Context and Problem Description:
The San Pedro River originates in northern Sonora, Mexico, and flows north into Arizona, eventually joining the Gila River, which flows into the Colorado River (Figure 1). The Upper San Pedro River Basin (USPB) is an area of approximately 10,660 square kilometers (4100 square miles). Arizona encompasses 74 percent of the study area and Sonora, Mexico, includes the remaining 26 percent (Steinitz et al., 2003: 11). The USPB is home to approximately 177,755 people in Arizona (Steinitz op. cit, 31) and 32,000 in Sonora (INEGI Census 2000) who live and work in seven incorporated towns and several unincorporated communities. Issues of water allocation for human and environmental uses are critical concerns and have led to divisiveness among water users and water-management entities. Agriculture, cattle grazing, mining, and recreation remain the predominant land uses, though they are being supplanted by increasing urbanization. In addition, the Upper San Pedro Basin, one of the most ecologically diverse areas in the western hemisphere, contains as many as 20 different biotic communities and supports a number of plant and animal species of special concern to both countries. The San Pedro Riparian National Conservation Area (SPRNCA), an approximately 18,200-hectare area managed by the Bureau of Land Management, is located within the U.S. portion of the USPB.
The United States Congress established the (SPRNCA) in the Arizona portion of the San Pedro Basin as a major North American migratory bird corridor in 1988, but this did not automatically assure its survival. The U.S. Bureau of Land Management has been administering the SPRNCA, with the goal of protecting the 60 km riparian corridor north of the U.S.-Mexico border. Population projections for the U.S. portion of the basin parallel those elsewhere in the Southwest--with a roughly 50 percent increase projected from 2000 to 2030--and will result in a major rise in water use to support municipal and domestic needs. In the face of continued population growth, great concern remained regarding the long-term viability of the San Pedro riparian system. Groundwater is essential for sustaining base flows within the river during dry seasons.
Most of the water demand in the basin has been for mining, municipal and domestic use, and irrigated agriculture. Recent research suggests that riparian vegetation also requires a large portion of the water budget. The basin is currently considered to be in a water deficit, with annual water withdrawals exceeding recharge by approximately 6 to 12 million cubic meters. Water use is increasing and is expected to continue to do so. A preRiver, but exacerbates the increasing competition for water resources between productive sectors such as agriculture and industry and domestic consumption (Magaña and Conde 2001: 1).
The groundwater deficit in this Basin threatens base flow in the San Pedro River which in turn threatens
the existence of the largest local economic engine, the Forth Huachuca military base whose existence is tied in part to the health of the River via legal implications from the Endangered Species Act.
In the past century, adaptation processes such as investments in infrastructure and technology dams, canals, wells, electricity, groundwater pumps and institutional arrangements such as insurance policies, have greatly reduced climate vulnerability perceptions. However, even if technological investments represent an adaptation to climate variability prompting a demographic growth in the basin they may not be sustainable over the long term, since their effects are yet to be seen (Finan el al. 2002). Indeed, if pumping extractions exceed natural recharge, the resource is being mined and the dynamics of aquifer-related ecosystems will be negatively affected. That is precisely the case in the San Pedro Basin where the river and its riparian area are closely linked to the aquifer, naturally allowing perennial flows in the desert during seasons without rainfall. When groundwater pumping is excessive, the water table is lowered and gets disconnected from the riparian area. At this point, the river goes dry and phreatophyte vegetation i.e. trees that need to access groundwater with their roots die. These linkages, its spatial nature, and its implications for sustainability are not easily understood by the general public, making it difficult to collectively address such environmental conflicts
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II - Convening Stakeholder Based Processes: In response to these water issues, stakeholder entities in the Arizona portion of the Upper San Pedro
created the Upper San Pedro Partnership (USPP, http://www.usppartnership.com/) under an interagency Memorandum of Understanding in 1998 to facilitate and implement sound water management and conservation strategies in the Sierra Vista sub watershed of the basin. The USPP is thus a consortium of 21 members including federal, state and municipal agencies, such as Fort Huachuca Military Base, Bureau of Land Management, Cochise County, The City of Sierra Vista, and non-governmental organizations such as The Nature Conservancy and the Audubon Society. The full list of member agencies, which are either land or water stakeholders in the basin or provide resources to help the Partnership accomplish its purpose, as well as their profiles can be found at http://www.usppartnership.com/about_memberagency.htm. The USPP is
-making body
provides technical and scientific advice and oversight by participating, coordinating and synthesizing research findings and information across Partnership members and other partners. In brief, the technical committee is composed of members with professional and scientific credentials from member entities, and reports to the advisory committee, so that decision-making has the best available scientific-basis.
The Partnership has made considerable progress on achieving its goals, but the remaining challenge of reducing groundwater use a further 40 percent during a drought is daunting. In order to help decision-makers understand the impacts and cost effectiveness of alternative water conservation measures and management policies the development of the DSS model begun (Richter, 2000).
III - The DSS model development: A collaborative process
Since its inception in 1999, the mission of the USPP was to find sustainable solutions for the management of water resources in the basin. In its commitment to do science-based decision-making, the Partnership involved scientists from the beginning. The idea of a Decision Support System Model for the Upper San Pedro Basin was first discussed around 2000/2001. The chair of the USPP Technical Committee requested different experts to come and talk about experiences with DSS models to see if the idea could be beneficial to the Partnership. Namely, a hydrologist developing a dynamic DSS model for the Middle Rio Grande Basin in a similar collaborative way, presented the potential capabilities of such tools for decision-making (Tidwell et al., 2004). Connections with the University of Arizona lead to faculty with the right expertise and interested in doing stakeholder relevant research in the area. After some visits demonstrating the capabilities of system dynamics modeling to support decision making, and because of the need of the USPP to handle large amounts of information and evaluate different options and strategies in a user-friendly way, the idea picked up.
By then, a report had already been subcontracted for a semi-quantitative analysis of potential alternatives, considering inter-basin transfers and some conservation measures. Nevertheless, a tool for decision makers was needed to easily evaluate management alternatives and the impact of their decisions. The different options and strategies outlined in the report constituted the starting point of the conservation measures packages to be built into the DSS model. From then, the DSS initiative evolved from a reconnaissance level project to a two phase modeling project. The first phase model accounted for an overall water budget with a set of conservation measures and management alternatives. Phase II of the project included linking the DSS with a detailed groundwater model developed in parallel by the US Geological Service.
Funding for model development has come from different sources during the process. Initially it was funded exclusively by SAHRA , a Science and Technology Center from the National Science Foundation at the University of Arizona, with a strong mission on stakeholder-relevant research. After approximately the first year, the Partnership provided 50% of matching funds. The project also benefited from other funding opportunities.
Discussions regarding model development are held in monthly meetings of the USPP technical committee, generally in Sierra Vista, located in the basin. The development of the model was a collaborative and open process in which any of the stakeholders of the Partnership could participate. Members find
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common ground regarding alternatives and conservation measures to be built in the model, assumptions that need to be made, the design of the user-friendly interface and any other relevant issues. In each meeting the main modeler presents advances made on the model based on previous discussions, to seek approval from members, and if need be, they are re-discussed and can be changed. As the model developed, the technical committee reported back to the PAC and the general public attending the meetings, for feedback. While stakeholders from the Mexican part of the basin did not participate in the model development process, a history of collaborative efforts exists and workshops regarding DSS modeling capabilities have taken place with Mexican water management authorities. The recent creation by the Mexican National Water Commission (CONAGUA) of a multi-stakeholder Basin Council for the Mexican portion of the basin may well be a result of the efforts mentioned previously and sets the stage for future collaborations.
While the main objective of developing the DSS model was to provide a decision-making tool and a common wavelength for communication, the development process itself is an open door for direct involvement of stakeholders and decision- the one of technical facilitators.
IV - Outcome:
Communication, Understanding, and Development of Institutional Networks and Knowledge The communication associated to the DSS development process - where stakeholders interact verbally
during meetings and express their opinions on choices to be made regarding how and what goes into the DSS model - served multiple purposes, as expressed by the individuals interviewed in this study. The development of the model forced the involved individuals to focus their communication on particular issues that ranged from processes and features represented in the model, to assumptions, conservation measures and alternative scenarios. The main sets of options containing each group of conservation measures and policies, their links and overlaps, had to be well defined and agreed upon. As the model has been developed collaboratively, every single decision embedded in it was a product of iterative communication between scientists and stakeholders during the periodical meetings of the technical committee. This required putting on the same page a range of stakeholders with different backgrounds and scientific knowledge. Preliminary findings and a better understanding as the model was being built also stimulated further discussions about improvements and updates. The model development process proved a good setting to have ongoing discussions on different
used and itemized communication was the key to a better understanding of the overall system behavior, the nature of the problem and the alternative solutions themselves.
The DSS development, along with other science processes within the USPP, contributed to a better understanding at many levels. First, it helped stakeholders such as city managers understand the physical system, especially the spatial distributions of pumping and land use management effects on the riparian corridor. The location and intensity of pumping or artificial recharge processes would have different effects on the water table adjacent to the San Pedro River. Visual tools developed by scientists were especially
US Geological Survey (USGS). Such a tool is a contour map showing in each location the percentage of pumped water if a well was drilled there that would otherwise contribute to flows in the river. In other words, it shows the areas in which pumping would have a more immediate impact on the riparian area (provided in Appendix A)
people to understand groundwater pumping impacts in the river; it allows stakeholders to realize there is this
we needed to restrict well density, especially in certain areas, and also showed the benefits of closing down alfalfa fields. The science process has been very good for land use planning and zoning.
Although changes in behavior are hard to gage, there is nevertheless a clear consensus on the fact that better common understanding of the physical riparian system - including impacts of pumping - lead to generalized acknowledgement of what may be better or worse in regards to sustainability of the riparian area.
Besides a better understanding of the natural system, the process allowed for a better understanding of what are the drivers and constraints of each stakeholder and the agency he/she represents. The complexities of
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the negotiation process can only be understoo
understand now the challenges of legislation that has to balance the needs of their constituency and the needs
conditions exist on each stakeholder range of action. Implicit to the process, the more non-technical people acknowledged the fact that they learned about the overall functioning of the models and how the groundwater model and the DSS were linked, as well as the limitations of the models. Parallel to all this understanding,
expressed by one participant.
the direction of the understanding. Participants tended to say they understood other p
This process of building understanding of individual values and perceptions on the one hand and of the complexity of the social-ecological system on the other can be regarded as a form of social capital. Putnam
tal is created as the organization members establish understanding and trust, and is part of the knowledge and understanding, norms, rules, and expectations shared by individuals participating in the collaboration (Ostrom 2007and Coleman 1988). The Resilience Alliance (2006) argues that not only must policies seek to transfer knowledge and understanding to local individuals, but must also develop institutional flexibility by encouraging the formation of networks of individuals which bridge institutional boundaries. These groups of individuals can act as agents of reform within their institutions, and the nucleus around which new institutions can crystallize. These individuals would represent the catalyzers of an adaptive complex system and benefit from institutionalized capacity building in regards to environmental knowledge about the social-ecological system. Indeed, multi-stakeholder representative public participation needs these kinds of individuals to function effectively.
More than one Partnership member, actively involved since its inception, noted that it would be hard to differentiate to what extent better understanding is due to the DSS development process exclusively or to the ensemble of previous and current working processes ongoing in the Partnership. Although the technical committee has taken the role of the science feeder into the broader Partnership, other processes may have also contributed to better understanding, social capital and institutional knowledge.
Influence of the DSS process on policy making:
The Upper San Pedro Partnership as an entity does not yet have any power to impose policies or
ndeed, as some of the interviewees have stated, the DSS development process already has influenced policy in two clear issues: (1) In Cochise County - Sierra Vista sub-watershed - limits have been established in regards to development density within two miles of the San Pedro River; (2) Regional Planning in the County Government includes the possibility of transferring development rights in areas far from the riparian corridor where pumping effects on the river are known to be more distant and spread over time. In addition, the Arizona State Legislature recently passed bill A.R.S. § 38-431.02, creating an Upper San Pedro Water District with taxing and other regulatory powers to be approved by voter referendum. Awareness, understanding and institutional knowledge raised by collaborative processes such as the DSS development have certainly contributed to such policies being implemented. Policy regulations in the San Pedro basin with aims to sustainability can be seen as a reflection of behavior changes due to better
-136) helped focus the sustainability questions in the basin and established a clear goal for the USPP, building the DSS laid out the potential strategic alternatives for achieving that goal. The 321 bill recognized a clear difference between the
kept and still kill the river, sustainable yield explicitly requires the protection of the riparian area and its ecosystems while introducing spatial and temporal concepts of impacts to the aquifer. Although the bill mandates the attainment of sustainable yield by October 1st 2011, it does not provide any associated funding
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to accomplish this task. Bill A.R.S. § 38-431.02 would give decision-makers the opportunity to rise funding locally. Putting density limits to development within two miles from the river, and transferring development rights to areas far from the river rights in southeastern Arizona. The implementation of these measures is a strong indicator of commitment to address the environmental impacts of growth in the basin. Nevertheless, it was widely manifested that the highest influence on decision and policy-making is expected to come with the use of the DSS model by managers and policy-makers. As Saliba and Jacobs (2007) have noted, a shift associated with the DSS process from a water budget approach to one with spatial management has caused land use planning to be directly influenced by water supply availability.
do have these powers within their particular jurisdiction. Thus, this is a clear example of how individuals
respective institutions. As studied by Folke et al. (2005), such networks of individuals emerging from collaborative processes can bridge institutional boundaries and be catalyzers of change within the system. In addition, the needs to involve policy people more from the beginning, expressed by the interviewees in the previous chapter, is very telling about their understanding of such processes and its influence to help bring about change. V - Reflection: Lessons Learned: What would you change?
The interviewees were asked what they would change in the DSS development process if they had to start
from scratch all over again. Overall, the collaborative process to develop the DSS model has been seen as very slow, and this seems to be the main criticism from all sides, including from the modelers themselves. Nevertheless, some of the people that have been involved in the model development feel the model is not something that needs to be finished in order to start benefiting from it. In other words, the model development process has contributed a lot to understanding and devising ways to address problems in the basin long before the model became a finished product. The interviewees were pleased with the final product, and acknowledged that it should be continually updated in its development and evolve along with the real situation, new implementations and conservation alternatives. Their answers can be grouped as follows:
Try to do it faster: One participant with a business-oriented managerial background was very critical
of the long time frames that scientific discussions took, and states that discussions about how to phrase documents or present results for the greater public can go off for months. The same participant also argued
rds like
month later he/she comes to the meeting and re-starts a discussion and changes things that were already decided. And then we have to go back and have to go through stuff again and change things. We need to go from an academic exercise to something in the engineering world. We have to go from the planning tools to
hat perhaps the modelers
should talk more in probabilistic terms. The slow pace of developing the model has taken its toll in the efforts to keep momentum, interest and belief that this initiative is worth it and that the DSS will be a useful tool. In addition, because of the slow development, some of the ideas/alternatives in the DSS may be outmoded or obsolete by the time the model is operational. At the same time, some individuals acknowledged that it also takes time to build trust and operate by consensus.
Better management of expectations: A more realistic acknowledgement of the time needed to complete the construction of the model would have reduced the feeling of frustration caused by the slow
participant stated. More clear chain of responsibility & business contract: The main modeler has been reporting back to
the technical committee during monthly meetings. There is the perception that there have been some iterations
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and changes in decisions due to two reasons: (1) member were not present when a decision was made and brought the issue back on the table in the following meeting; and (2) the technical committee often checks back with the broader USPP to seek approval for decisions made. A recently involved participant suggested that political representatives should be in the committee with insights and power to say what to put in the model. Another individual also suggested that the main modeler should report back to just one person, a
to
Another policy level participant stated that the complete absence of a business contract, where results are promised in a certain time for a certain amount of money, was a problem. When asked if he would rather have
ther hand, a technical person (not from academia) stated that the feedback loops and iterations between the main modeler and the USPP were necessary and that most of the work on how the model should have been done by a small group of
he people (including policy people) had been involved, progress would have been almost
More outreach and public input: A participant stated that a more aggressive approach to getting the understanding of the model to all the principal stakeholders and the general public is necessary, so that they trust the model upon completion. A need to keep the stakeholders and the public up to speed with the inner workings of the model.
Involve policy people from the beginning: Many individuals have stated that policy people ought to have been more involved, since the DSS is meant to be a tool for decision makers. Many state that there is a gap between the technical and the policy people. While the DSS has been in the hands of the technical
consequence of this is that there is the perception of a lag between the political realm - where things are constantly evolving - and the DSS model, which takes time to be developed by consensus. Because certain policy people were not involved in the development of the DSS, some of the options built into the DSS may not be politically feasible. However, the few sessions organized to train policy makers to use the model have become more model modification sessions.
Show examples beforehand, documentation: Many individuals had no clear idea of where the DSS model effort would lead the Partnership. They expressed it would have been helpful to see other similar models and examples at the beginning of the process in order to have a clear idea of what the model would exactly do for them, how would it look, etc. More explicitly define the purpose and goals of the DSS - as well as its limitations - , how the product is going to be used, and keep this in mind as the product is developed.
like creating something that had never been done. A really good
Feeding current, accurate and updated data into the model is a concern for the future. There is a
general consensus that the expertise of the technical people involved in the model development has ensured this up to date, but it is something to keep in mind for the future (GW data, spatial dimension, smaller grid cells, accuracy of data, from different agencies, water use estimates, projections per capita, per home, etc.).
Furthermore, capacity building of some individuals may be needed within the Partnership itself to modify the model and transform it in case the modelers in academia stopped working on the project. The point was raised that somebody within the USPP should be able to modify and update the model, the data that
modeler] leaves the state and stops working on it, nobody is able now to take care of things and move on from
will help us a lot in our planning and zoning, our municipalities and county entities, water districts, water
ow to use it yet, and my concern is how to keep it up to date with future
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science, options, and alternatives. If federal funding fails to help the BLM, the State, Fort Huachuca and the
Comparison of DSS Models in the Middle Rio Grande (NM) and Upper San Pedro River (AZ)
In the Middle Rio Grande and the Upper San Pedro River, both DSS were developed in collaboration with stakeholder groups within the setting of an open and participatory process to solve management problems.
Following a state-wide water planning process in New Mexico, a voluntary group composed of diverse stakeholder representatives from the Middle Rio Grande planning region, and called the Middle Rio Grande Water Assembly (MRGWA) was the entity responsible for the planning. Composed of five groups focusing on agriculture, environment, urban development, water management and special technical issues, the MRGWA started a public consultation process through monthly and quarterly meetings that finally produced five scenarios or tentative management plans for the region. These scenarios comprised different sets and combinations of 44 water management alternatives identified by the public during the initial consultation processes. The quantifiable alternatives were included in the Middle Rio Grande DSS model, which allowed a quantitative comparison of the water conservation alternatives. At the end, the five scenarios were combined
Council of Governments (MRGCOG), representing the local governments that would be responsible for implementing the final plan. Besides helping planners (MRGWA) and decision-makers (MRGCOG) to compare and evaluate alternatives proposed by the public, the model was instrumental to familiarize and engage the public itself in the planning process (Passell et al., 2003).
In the case of the Upper San Pedro basin, the Upper San Pedro Partnership was created to solve the management challenge in the basin and close the gap between human demand, natural availability and environmental needs. The USPP is also an organization composed by stakeholder representatives from 21 state and federal agencies as well as other entities and user groups, functioning at a voluntary basis. It is structured in three main committees: the Partnership Advisory Committee (PAC), the Executive Committee (EC) and the Technical Committee (TC). The PAC is the decision making body representing all entities; the EC represents the member entities that finance projects and operations; and the TC coordinates technical and scientific advice and oversight. Composed by representatives with technical and scientific profiles from the member entities of the USPP and the modelers from the University of Arizona, the TC reports to the PAC, so that decision-making can be science-based. The DSS model was developed through monthly open meetings with the Technical Committee, where other stakeholders and the public could participate. Representatives in the TC had to agree and decide on alternatives and conservation measures to be included in the model, as well as underlying assumptions, how to deal with uncertain parameters and how model results should be displayed
DSS model, review them with the group and discuss the next steps of model construction, making it a collaborative, participatory and transparent endeavor (Serrat-Capdevila et al., 2009).
The Cooperative Modeling Group in the Upper Rio Grande is the equivalent to the Technical Committee in the Upper San Pedro. In both settings, these technical groups were in charge of developing and synthesizing the technical and scientific information that would be the basis of the planning process, working with the DSS model development, and other related tasks. In both cases, there was an effort to build public confidence and trust in the planning model (it properly addressed the issues at hand) as well as a sense of
Although the planning processes in the Rio Grande and the San Pedro River are the result of different
institutional drivers (Statewide planning initiative in NM vs. basin initiative to meet a federal mandate in the San Pedro), the planning is structured around parallel organizations with similar roles. Although neither the MRGWA nor the USPP have any powers to impose policies or have any decision-making status, their individual member entities may have such powers within their particular jurisdictions. The understanding that comes from having to work together within a collaborative terms of what actions are or are not sustainable or convenient. Most importantly, these planning and decision-support processes provide the opportunity to engage both the public and the actual decision-makers well
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before decisions need to be made. Thus the process itself, even long before the completion of the DSS product, will likely have significant positive contributions, and the way it is conducted will have important implications. The understanding of the physical system, of what is or not convenient for the common good,
competing needs. For the interested reader, Serrat-Capdevila et al. (2009) provides an analysis of the lessons learned and the
contributions of the participatory process by which the DSS model in the San Pedro basin was developed. Cockerill et al. (2006) presents the feedbacks from the Cooperative Modeling Team in the Upper Rio Grande.
Shared Vision Planning
There have been many efforts from varying perspectives to establish a methodological framework for science-based collaborative planning and decision-making. Liu et al. (2008) present an excellent study of integrated modeling to support natural resource management. Their work is presented from an academic perspective and a desire to improve the credibility, legitimacy and saliency of scientific information so that decision-makers use it. They frame their work within the setting of participatory processes but focus their efforts on the contributions of an integrative modeling approach. Mahmoud et al. (2009) has a broader scope, placing integrative modeling approaches as a tool to support scenario development for decision making. They emphasize the need for stakeholder input in order for the scenario analysis to be useful to decision-making.
Perhaps the most widely used participatory planning methodology in the US has been Shared Vision Planning (SVP). The main difference with respect to Liu et al. (2008) and Mahmoud et al. (2009) is that SVP was developed and refined by planning practitioners that needed to solve planning challenges in their professional life. Authorized by the US Congress and motivated by the 1988 drought, the method initially appeared as the Drought Preparedness Study (Werrick and Whipple, 1994) with the goal of finding better ways to manage water during drought. The report is based on the joint effort of over 100 practitioners and researchers on how to approach water management issues in many case studies across the country during
people understanding their role, and knowing how their actions fit in a larger respoplanning will be much more effective if it benefits from collaboration between government agencies and stakeholders. This will provide easy access to insights and knowledge from the stakeholders (integrative plans), they will learn about the broader picture (social learning, understanding), thus being less vulnerable themselves, and will ensure public support for any potential water management plans (credibility and trust). The Drought Preparedness Study presented a methodology to set up a functional and integrated multi-stakeholder process to find planning solutions in the face of droughts, but can be used in any water management issues. The full report is available online at: http://www.iwr.usace.army.mil/docs/iwrreports/94nds8.pdf
Since its initial development, the method has been adopted by the US Army Corps of Engineers in many conflict resolution efforts in US water management regional disputes, and is commonly known now as Shared Vision Planning (SVP). SVP is based on three principles: (1) traditional and time tested planning methods and techniques (such as described in chapter 2); (2) structured public participation; and (3) use of computer models collaboratively developed in order to support the participatory planning process (Cardwell et al., 2009).
To efficiently benefit from stakeholder participation, SVP uses Circles of Influence as a way to structure involvement and engage stakeholders depending on their role in the process. As shown in Figure 1, participants can fall in Circles A, B, C or D, ideally representing the following:
Circle A: Planners and model developers. Their task is to integrate the work of others to develop planning alternatives and modeling tools to help decision-making. They form the core planning team that facilitates communication across the different circles.
Circle B: Stakeholder representatives and technical experts. Sometimes organized around working groups on specific issues, they provide information, insights and advice. They validate the work of Circle A and can evaluate proposed plans.
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Circle C: The general public, whose members should have representatives in Circle B. A mechanism should exist to inform them and allow their feedback regarding the work of Circles A and B.
Circle D: The decision makers. Those who will ultimately decide what decisions are taken and what plans are implemented. They should be identified and actively engaged along the planning process, so they can provide feedback and guidance to the process.
These circles of influence are relatively natural, and they can be well illustrated by the case studies in the Rio Grande and the San Pedro basin, with slight differences. The Cooperative Modeling Team in the Middle Rio Grande and the Technical Committee of the Upper San Pedro Partnership would compose Circle A, the hands-on planners, in each basin. The Middle Rio Grande Water Assembly and the Upper San Pedro Partnership as stakeholder consortiums as a whole would compose Circle B, providing information to Circle A and validating its progress. Circle C is the general public in both cases. Finally, the Middle Rio Grande Council of Governments and the Partnership Advisory Committee would compose the cores of Circle D in each basin, with the possibility of other decision-making agents existing beyond those groups.
Figure 1: The concept of the Circles of Influence (from Cardwell et al., 2009). Table 1 summarizes the seven steps of Shared Vision Planning and compares the process with the
proposed frameworks of Liu et al. (2008) and Mahmoud et al. (2009) to show the similarities despite the different perspectives from academics and practitioners.
Integrated Modeling Approach
Liu et al. (2008)
Scenario Analysis Mahmoud et a.l (2009)
Shared Vision Planning Werrick and Whipple (1994)
-- --
(1) Build a team: identify circles of influence: planners, stakeholder representatives, agency leads, advocacy groups & decision-makers.
Identify Problems and Opportunities
(1) Identify and formulate the important focus questions, using science and stakeholder input
-- (2) Develop Objectives and Metrics for Evaluation
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(2) Define scenarios based on focus questions based on key external forcings, important and highly uncertain
Scenario Definition
(3) Describe current status quo: what happens if we do nothing?
(4) Formulate Alternatives to the status quo, through broad participation
(3) Develop conceptual basis for numerical models to be built and generate data for scenarios
Scenario Construction
(5) Evaluate alternatives and develop study team recommendations (Compare alternatives against the status quo, and evaluate them with the metrics and indicators previously developed.)
(4) Develop modeling system, calibration and validation. Adjust conceptual model
(5) Construct scenarios by deriving model inputs and collecting outputs from model runs
Scenario Analysis
(6) Perform indicator analysis on scenario outputs: sensitivity analysis to understand main controls and uncertainty sources. Compare scenarios
Scenario Assessment
-- --
(6) Institutionalize Plan (ensure recommendations will be acted upon, requires written agreement to act according to the findings regardless of political and administrative leaderships)
(7)Informed Decision-making
Risk Management (7) Implement and update the
Plan (~adaptive mgmt.) (8) Monitoring & post-audit
Monitoring
(1) Repeat, new cycle Repeat Table 1: Comparison of the approaches from Liu et al. (2008), Mahmoud et al. (2009) and Werrick and
Whipple (1994).
What else do we need to walk a sustainable path? An Evolving System: Uncertainty, DSS and Adaptive Management
Living in a changing world, it is evident that even if planning and management are implemented as particular actions, they are an ongoing process over the long-term. Consequently, Integrated Water Resources Management is portrayed as a spiral where the implementation of past plans is monitored and the process is re-evaluated and re-directed based upon our most current, new information. In other words, we have to plan for an uncertain future, then deal with it when it becomes the present, and learn from it when it becomes the past. Such an acknowledgement is the basis of adaptive management.
Everyone knows the future is uncertain, but how do Decision Support System Models deal with uncertainty? To what extent and how is uncertainty incorporated into DSS and how is it communicated? The truth is that uncertainty is a difficult concept to work with and is often not well represented in models and decision support tools. Many systems dynamics models state as a disclaimer that the specific values provided
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by the model are to be interpreted as a relative measure in comparison to other alternatives, but never as absolute numbers. This is well accepted because it still allows the comparison of different management alternatives and an overall view of their impacts in the entire system. While uncertainty can be accounted for in specific model components (physical land surface and hydrologic models) once the intention to do so is there, it may be harder to represent it accurately in systems dynamics models, perhaps due to the inability to accurately represent and blend uncertainties from many different model components of the system (i.e. behavioral and socio-economic components).
There are many sources of uncertainty in simulations: uncertainty contained in the input data (climate change projections), in the model structure formulation (recharge, runoff and evaporation transformations), and arising from issues related to boundaries and scales (e.g., regionalizing soil parameters).
Uncertainty inherent to structural representations of the physical world reflects the lack of proper understanding of physical processes or our inability to represent them properly, much less crossing boundaries of scale. As an example, in basins in Arizona that constitute some of the most instrumented and studied watersheds in the world, the quantification and the spatio-temporal characterization of natural recharge into the regional aquifer remains a formidable challenge. The estimates currently used in hydrologic models are based on empirical relationships aggregated at the basin scale that were developed 20 years ago (Anderson, 1992).
When developing a DSS model, different sources of uncertainty can be represented in different ways. During a collaborative process, stakeholders and decision-makers can decide on what sources and measures of uncertainty need to be explicitly represented in the model and which ones may better be addressed through other means. For example, climate change projections are very uncertain but a multi-model envelope of uncertainty can easily be represented using the wettest and driest models (or hottest and coldest) as the extreme cases, and assuming that future rainfall (or temperature) will fall somewhere in between these extreme cases. All the projections of climate models falling within the wettest and driest models can be averaged, providing what can be used as the highest-likelihood possibility (Hagedorn et al. 2005). Such envelopes of uncertainty in inputs that drive land-surface and hydrologic models can easily be propagated or transmitted from the input variables to the output variables (Serrat-Capdevila et al. 2007). On the other hand, there are uncertainties regarding issues that are difficult to quantify but still have important impacts on decision-making, such as changes in economic drivers, land use cover, institutions and policies. These uncertainties may be better handled through scenario development, where alternative futures independent of our decision-making process can be accounted for. On the other hand, information gaps identified during model development can help identify areas of uncertainty and consequently direct research and monitoring activities.
In some cases, uncertainty can be constrained and minimized to a certain extent with studies and research, but it will always be there, especially when trying to assess the future. Acknowledging uncertainty, the concept and practice of adaptive management presents a framework for natural resource management under uncertainty that aims at reducing uncertainty through observation during and after management interventions. In other words, adaptive management is a decision-making process that attempts to manage systems in order to maximize both the short-term benefits of management; and the gaining of new understanding to improve management over the longer term. To accomplish the second goal learning about the system adaptive management relies on a few basic steps:
(a) Characterizing the sources of uncertainty in the system. What are the poorly understood processes in our system and where does the uncertainty arise from?
(b) System observation and monitoring of system response to management actions, during their implementation and afterwards. Is the system responding to management interventions as it was expected?
(c) If the system is not responding as was expected, different potential explanations can be developed and tested in future management implementations. Such explanations of why the system behaved as it did can either be consistent with our previous understanding of the system, but can also question it. Information and data gathered in future management interventions could be used to validate or invalidate such explanations. This is also known as testing assumptions and hypothesis.
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(d) Including and assimilating new data and information in a conceptual and numerical representation of the system, embodying the current understanding of how it functions.
(e) Management can be specifically geared towards tackling domains of the system where less is known about its functioning or where major uncertainties lie. This can conflict with management goals to maximize beneficial use of the resource in the short term, but is considered a benefit for the long-term as it is likely to reduce uncertainties on the system.
Flexibility is an important aspect of a good adaptive management practice. Institutions should be able to change past policies based on the observed impacts such policies had on the system. The key to this essential feedback linking the latest observations with the next decision-making steps is that it requires close collaboration between those who monitor, study and interpret the behavior of the system with those who do the decision-making. Traditionally, these groups of people belong to different institutions, the communication among which is not necessarily fluid. It is for this reason that a true adaptive management mechanism must also foster new organisms and institutional strategies that will be able to put new knowledge to use at a practical level. For management to be adaptive, the policies must be flexible, not just the institutions.
As real-world systems are often very complex, adaptive management must make use of modeling tools to properly simulate and understand how the system functions. Ideally, as previously mentioned, this forces decision-makers, scientists and model developers to work collaboratively in a cycle of management decisions, implementation, monitoring, interpretation of new data, and inclusion in conceptual and numerical models of the system to help validate past interpretations and/or provide new working hypothesis of how the system behaves.
To the present date, DSS models have mostly been viewed as a product that can be developed to help answer management and planning questions at a given time. It is only very recently that DSS models are starting to be perceived as evolving tools. Rather than developing and using them once, they offer greater benefits when they are dynamically changed over time to represent the evolving present, becoming a working tool that may never be a finished product but a product to work along the years. In participatory planning processes this allows the model to be a common representation of the system and the DSS model and
management practice, a DSS model will have to be updated as ongoing policies and management actions are implemented. Model updates will reflect modifications in the engineered system layer (canals, pipes, wells, dams, water re-allocations, changes in use efficiencies, changes in land use cover, etc.) as well as new or modified understanding gained through adaptive management on how the system works.
The issues of model updates and institutional flexibility can be well illustrated by the worries of many stakeholders in the San Pedro Basin, collected in a study to evaluate the contributions of the collaborative process in the basin. Being able to feed current, accurate and updated data into the model was a concern for the future that relates well with institutional limitations. A modeling team from the University of Arizona had ensured model and data accuracy, along with technical people from different government and state agencies involved in the process. The point was raised that if the modeling team left the collaboration, no human
inue the modeling work. Local capacity building to update and modify the model was necessary: Otherwise, if [the main modeler] leaves the State and stops working on it, nobody is able now to take care of things and move on from here. A comment by one top level policy person illustrates the precarious institutional integration and
our municipalities and county entities, water districts, water planning, etc. [...] my concern is how to keep it
-Capdevila et al., 2008). The final important point to make here is that an integrative modeling approach in adaptive management
institutions will be essential in these types of contexts for many reasons. Decision makers usually use (or benefit from the use of) medium or coarse resolution models in system dynamics platforms (DSS models) that incorporate findings of more refined models in a simplified but still accurate manner. As new information and understanding becomes available, these DSS models are likely to be unsuited to the assimilation of such information. Instead, the more detailed physical models that support and inform system dynamics simulations,
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are more likely to accommodate new data properly and help improve the understanding of that particular component of the system. Once this is accomplished, the DSS model can be modified accordingly to accurately represent new findings in a simplified way. The full potential of adaptive management can only be reached when it is coupled with an integrative decision support systems modeling approach and with continued research and observation.
6. Conclusion
Decision Support Systems have transitioned from engineering tools to systems that provide frameworks for stakeholder participation to guide, inform and support decision making in a transparent and more sustainable way. The research and past experiences presented in this chapter have shown that participatory planning and management processes can greatly benefit from an integrative and holistic modeling approach. Models of different resolution and complexity that serve different purposes can be used to inform each other through feedbacks. While high-resolution Land Surface Models are necessary when there is a need to accommodate in detail the processes in the physical environment (such as the land-atmosphere partitioning of water and energy, the role of vegetation and the interactions between surface and groundwater hydrology), medium- and coarse-resolution models are typically better suited to modeling human interventions on the environment (such as land-use management, engineering infrastructure). Medium resolution models allow us to represent water allocation and re-distribution within the system and across uses, while coarse resolution models are used to properly describe socio-economic and institutional aspects of water management over the natural and engineered system, with a resolution at the scale of the sub-watershed. In addition to providing an efficient way to represent the coupled natural-human system, a major benefit of multiple resolution modeling is that information and findings can be readily transferred across models and used for model refinement. Information regarding natural processes, climate change impacts and feedbacks in the natural system can be up-scaled to higher level models, while behavioral and policy feedbacks from the socio-economic and institutional models can be used to drive lower resolution models and assess impacts on the natural system.
This integrated modeling approach can be the scientific foundation for participatory planning processes and the collaborative development of decision support tools. The combination of structured stakeholder participation and the use of integrative modeling will allow the proper identification of problems and management objectives in the basin, as well as a better shared understanding of the system functioning, and the development of future scenarios and management alternatives. Based on conflict resolution concepts, this methodology will not only lead to agreed-upon management solutions, but also to a well informed and educated stakeholder community in the basin. Sustainable learning comes with a better understanding of the system as a whole; and problem-solving, over the long term, can benefit from the human capital among individuals involved in participatory processes and the groups they represent. Past studies have pointed out the importance of human capital in society over economic welfare, as well as the mechanisms for ensuring it (education, research, health care, social investments), as the key quality required to address environmental and sustainability challenges. The reinvestment of resources towards human capital (knowledge) in a higher priority over economic capital can be in itself a definition of a sustainable system.
This resonates well with the learning goal of adaptive management. In the present time of rapid economic and environmental change, the future now seems to be more uncertain than ever. With the influence of climate change, the premise of a stationary state on which much of water resources planning and management are based, is now compromised. It is likely that we will have to change the ways in which we extract and use information from the past to predict the future. The implementation of efficient adaptive management mechanisms combined with integrative multi-resolution modeling capabilities will have to balance the search for new understanding and the short-term economic benefits of management.
Currently, the main challenge to achieving efficient adaptive management remains to provide within existing institutional arrangements, sufficient flexibility and the capacity to close the feedback loop between system monitoring, modeling and scientific analysis, stakeholder participation and iterative decision-making. As this is accomplished, it will enable water resources management to shine through the lenses of economic efficiency, social equity and environmental sustainability.
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THE UPS AND DOWNS OF INTEGRATED WATER RESOURCES PLANNING IN THE MURRAY-DARLING BASIN by Bill Young Director, CSIRO Water for a Healthy Country National Research Flagship ABSTRACT
-‐Darling Basin was show-‐cased around the world as an example of best practice in integrated catchment management. However, continued growth in water resources development coupled with a severe decade-‐long drought led to a water management crisis characterised by widespread ecological degradation and significant economical and social impacts on irrigation communities. This was in spite of ongoing national water reforms including an increasingly active water market, which helped to buffer the impacts for water users. The crisis led to the suspension of many existing water management arrangements and ultimately new legislation and governance arrangements for water planning and management across the Basin. Centrally, these arrangements require the Australian Government to put in place for the first time a Basin Plan for the sustainable management by state governments of the water resources of the Basin in the national interest. Major investments in water information and modelling have provided a strong technical basis for the required reforms and have begun to improve the transparency and accessibility of water information. However, the uncertainties still inherent in climate change projections and ecological responses to environmental water regimes mean water planning reforms are risk-‐based decisions balancing risk between environmental, economic and social outcomes. This complex and highly contested situation calls for strong participatory approaches to water planning, which while a feature of Murray-‐Darling history, have arguably been absent in recent years. This paper will outline key elements of the problem and consider the prospects for a rational resolution informed by robust science and wide consultation in the rapidly shrinking politically determined window of opportunity.
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Session 13: Case Studies in Collaborative Modeling II Developing Decision Support Tools
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ADVANCING INTEGRATED WATER RESOURCE MANAGEMENT IN SYSTEMS WITH HIGH LEVELS OF SCIENTIFIC AND SOCIAL UNCERTAINTY: LESSONS FROM THE PALOUSE BASIN by Allyson Beall, Fritz Fiedler, Jan Boll, Barbara Cosens1
ABSTRACT The Palouse Basin Participatory Modeling Project was designed to assist with conceptualization of social and physical components of the Palouse Basin from a system wide perspective and in doing so help managers recognize and identify potential management and outreach strategies. This process is part of an effort to evaluate the use of participatory modeling in situations with high levels of uncertainty regarding the resource and resulting disagreement on the nature, scope and even existence of a problem. The basin is located on the border of northwest central Idaho and southeastern Washington with each state having its own system for water allocation. Two confined aquifers located in heterogeneous basalt formations are the sole source of domestic water supply for approximately 60,000 people. The primary aquifer has little or no recharge. The physical properties of the aquifers are highly uncertain, including basin area, volume and degree of decline directly attributable to pumping. The combination of long-term decline in aquifer levels with scientific and regulatory uncertainty create the potential for conflict, although currently there is no immediate supply crisis. This participatory project has been designed to determine if it is useful in assuring that a crisis does not develop. Results suggest that the tool and process are useful to help people understand the effects of uncertainty, focus the dialogue on specific problems rather than positions, and to facilitate discussion across multiple jurisdictions. This specific application also provided lessons on when to use the approach, how to initiate the process, and who to involve. Keywords: participatory modeling; collaborative modeling; system dynamics; ground water
I. INTRODUCTION
The Palouse basin is located on the border of northwest-central Idaho and southeastern Washington (figure 1). The basin contains two confined aquifers, the Grande Ronde and the Wanapum, which are located in heterogeneous basalt formations of the same name (figure 2). These aquifers are the sole source of domestic water supply for approximately 60,000 people. The primary aquifer, the Grande Ronde has high quality water with little evidence of significant recharge. The Wanapum has limited recharge yet a high mineral content making it much lower quality. Due to the geologic complexity of the basalt flows the physical properties of the aquifers are highly uncertain. Researchers have not come to consensus as to the total basin area, much less the volume of the aquifers or the degree of aquifer decline that can be directly attributable to pumping. Well data from the Grande Ronde aquifer has been collected for over 70 years and has recorded an almost continuous 1.5 foot drop per year in aquifer level with a several fold increase in pumping rates. The level of decline may be tapering off to approximately 1 foot per year however the reason for the change is highly speculative and it is too early to assume that this is a new trend. While some residents and decision makers point to slow and possibly slowing declines to argue that there is little or no problem, others argue that consistent declines are inherently unsustainable and require immediate action. In addition to scientific uncertainty there is a high level of regulatory uncertainty because the Grande Ronde straddles the Idaho-Washington border. Each state has its own system for water allocation and as there is no agreement on aquifer extent and connectivity, and direction of flow, there is no upstream-downstream context. The combination of long-term decline in aquifer levels with scientific and regulatory uncertainty create the potential for conflict, although currently
*Respectively, School of Earth and Environmental Sciences, P.O. Box 642812, Washington State University, Pullman, WA. 99164-2812, USA. 1-509-335-4037. [email protected]. Waters of the West, P.O. Box 443002, University of Idaho, Moscow, ID. 83844-3002, USA.
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there is no immediate supply crisis. In order to facilitate a precautionary rather than reactionary approach, the participatory project has been designed to determine if it is useful in assuring that a crisis does not develop (for a complete description please see Beall et al. 2011). Application of participatory modeling to the Palouse Basin suggests that the tool and process is useful to help people understand the effects of high levels of uncertainty, focus the dialogue on specific problems rather than positions, and to facilitate discussion across multiple jurisdictions. The specific application also provided lessons on when to use the approach, how to initiate the process, and who to involve. While the outreach element was embraced, it is too early to assess whether the decision support element will result in bi-state integrated water resource management over the long term.
Figure 1. Working boundary for the Palouse Ground Water Basin. The state line is indicated by the north-south dashed line between Pullman and Moscow. (Robischon 2011).
Figure 2. Cross-section of area between Pullman and Moscow. Including major wells, of the Grande Ronde (multiple flows in different shades of green) and Wanapum (blue) basalt formations, Latah formation sediments in represented in beige (Bush and Garwood 2005) .
II. CONVENING STAKEHOLDER-BASED PROCESSES IN IWRM
As noted above the basin is not in an immediate crisis but many in the area feel strongly that we need to have the conversation about long-term integrated management with the understanding that scientific or regulatory uncertainty is
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not a reason to delay. An annual Water Summ -term plan for sustainable
in Moscow began exploring the use of system dynamics modeling as a decision support tool in 2006. After describing the potential at the 2007 Water Summit discussion inspired us to explore the utilization of system dynamics in a participatory fashion with water managers. Initial stakeholder outreach and identification began with the local aquifer committee. The Palouse Basin Aquifer Committee (PBAC) was formed in 1988 in response to declining well levels and has representatives from the cities, counties, universities and state water resource agencies. The largesof Moscow, ID and Pullman WA and the two universities, University of Idaho and Washington State. PBAC is a multi-jurisdictional, cooperative group that operates under a non-binding Resolution of Understanding between the water management agencies of Washington and Idaho. The committee itself is made up of public works and facilities managers from the two cities and two universities who are not elected officials. For the smaller communities and the counties, elected officials participate. As noted in Beall et al. (2011), some basin residents are concerned that there is no legally binding agreement across the state line for bi-state management of this water resource while others support the status
BAC is purposely and proudly a voluntarily- -standing relationship with the universities in part because of their representation on the committee but also because PBAC relies on university researchers for ground water and geologic assessments. When initially approached about the potential of participating in a collaborative modeling exercise PBAC expressed significant reservation. There were, and perhaps still are, concerns about the non-traditional modeling platform (system
discomfort with a decision support tool in general. Some explicitly stated that they did not want a model to be used to
science dimension of hydrogeology to including the human dimension. We felt very strongly that once participants became involved in the project that many of these concerns could be overcome through process and model transparency. After a great deal of discussion both in meetings and with individual PBAC members, somewhat reluctantly, PBAC decided to participate and invited their Citizen Advisory Group (CAG) to join them. Upon reflection we speculate that their decision to participate was influenced by the concern that we would have undertaken the project with or without them. Our position was that even without PBAC we could invite local policy makers, citizens, and NGOs to help us with the social side of the model. We had already assumed that hydrogeologic experts (and their respective data) would be included and indeed would be essential to development of the physical side of the model. Our final stakeholder group was limited to PBAC and CAG representatives, hydrogeologic experts and our group. Though in hindsight a push to include policy makers not on PBAC could have helped the project progress to another level, we did not because at the time establishing trust with PBAC was vital. Our hope was that PBAC representatives would discuss the project well beyond the aquifer committee through report backs to their respective jurisdictions. The project lasted two years, a first year pilot and then a second year with financial buy-in from PBAC. During the first year attendance ranged from 11-17 participants representing PBAC, the CAG, Washington Department of Ecology, Idaho Department of Water Resources and local scientists with expertise in hydrology and geology. The second year meetings included 6-9 participants with participation primarily PBAC representatives of the major pumpers who reported back to PBAC during their regular meetings, and one member of the CAG who also reported back to those interests. State agencies could not attend due to budget issues but were kept apprised of the model and process progress. Participants worked together to determine the model scope, important parameters, and they helped frame model outputs and the design of the interface. Between workshops modelers worked individually with hydrologic experts on the specific design and parameterization of the ground water sector. The original invitee list of 34 (and anyone they invited) was included in an online vetting process of the final model and interface. The model includes hypothesized aquifer volume, historic pumping data, population growth, potential conservation measures and potential new sources. Simulation results are presented in graphs of well levels, total volume of available water, and demand. An online simulation model has been made available to the public through PBAC and other local water centric websites.
III. USING DECISION SUPPORT TOOLS IN IWRM The major pumpers in the basin have individual plans as to how they will keep their pumping below the level
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with good maintenance protocol and conservation technology. This has occurred in the face of ~1% population growth and has kept pumping rates constant for about 20 years. Aquifer levels however have continued to decline and there is a point of diminishing returns with respect to maintenance and technology; there are only so many high flow fixtures left to replace. Though we are not sure when it will happen, pumping levels will begin to follow population growth at some point in time. At that point the likelihood for conflict is significant. Although there is apparently a large volume of water in the aquifers there have already been heated skirmishes over both water and development as it relates to water. This process was designed to reduce the potential for conflict in the future and to set a framework for transparent discussions about aquifer behavior and water planning. With respect to advancing this process to support on the ground decisions, PBAC understands both the potential and value of the model that they helped produce. Due to the flexibility of the model framework adapting it to include impacts from land use decisions or changes in water rates is a potential next step. Even if these decisions are not basin wide and individual pumper could use the model to understand their individual impact on the aquifers.
here. First, some people theory have elements that cannon be modeled. Third, people were concerned that parameters with a high degree of
was helpful and instead framed our work as an educational tool. In doing so we enabled the group to embrace the participatory process as a learning exercise for them and as a way for them to explain the system to others. Furthermore through the use of system dynamics theory we dealt with the uncertain physical parameters of the aquifer upfront. At one
now with this uncertainty, how
IV. NAVIGATING INSTITUTIONAL FRAMEWORKS AND IMPLEMENTING DECISIONS The need for a tool that provides transparency to the various scientific models of the aquifers and easily displays the level of uncertainty in that knowledge was the result of differing policies and laws governing groundwater development between the two states sharing the aquifer. Water allocation is a matter of state law and there are no rules governing coordination between states in the absence of a formal agreement or judicial opinion. Prior to the project, the degree of uncertainty in understanding of the aquifer had been used to polarize the debate and to characterize it as a debate between pro- and anti-development interests. Thus the tool and participatory method of development were designed specifically to help water managers on both sides of the state line understand, agree upon, and communicate the degree of uncertainty and its impact on decisions. Utilizing a precautionary rather than reactionary approach this participatory project has been designed to determine if it is useful in assuring that a crisis does not develop. Perhaps in the long term we will be unable to measure how much
indirectly test our hypothesis. As part of the larger effort for collaborative water management area decision makers were invited to roundtable a few months after the culmination of model building. The model and various scenarios were
and the potential for integrating technology or additional sources. Thus, the model was being used to discuss the relative merit of competing management options, informing and supporting the decision making process. During the next portion of the roundtable conversation did lead to heated discussion about the potential for a bi-state regulatory framework for water management and the group perspective this was both positive and negative. It was positive because it indicated confidence in a group that collaborates quite well. It is negative in the connotation that collaboration at a higher level is not necessary.
V. OUTCOME
outreach element was embraced, it is too early to assess whether the decision support element will be integrated over the long term. That said PBAC has confidence in the product and in the understanding that it is adaptable to new data and
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that it has the potential to be modified for uses beyond outreach. When asked if the modeling process could include policy makers as a next step there was a mixed response from PBAC members, some of which are city council members
in
that is, in part the result of conflicting values concerning water and development that have been exacerbated by scientific and regulatory uncertainty. At this point in time the lack of decision maker participation may be limiting the usefulness of the model. Specific land use options and economics were not included in the model because the stakeholders still needed to develop the components for these parameters. However when having one on one discussions with a few key decision makers they seem to trust the model and have been very willing to volunteer that they felt that it is neutral.
VI. REFLECTION
As we reflect back on this project there are successes and lessons learned. Facilitators, modelers and participants all felt very good with the last iteration of the model especially with respect to the aquifer module. We had found that by modeling the aquifer as a dual storativity system, that we were able to simulate generalized water levels using parameters that were consistent with groundwater age dates of ~20,000 years (see Beall et al 2011). The approach to date had been the use of a single storativity to describe system water storage, which most of the local hydrogeologic experts agreed did not make sense numerically if there is little to no recharge. We do not know if the dual storativity parameterization is
-term behavior to be storage-dominated, rather than recharge dominated. Our hope is that future research will confirm or deny this concept, and until then management options are explored with dual storativity in mind. With respect to dealing with scientific uncertainty our participants are now even more familiar with the difficulties researchers face when trying to accurately characterize complex groundwater systems with limited information. At the same time this was sobering because the process brought up the point that just because there is potential water in this system it does not necessarily mean it can be accessed at will. The model also helps to illustrate to users just how effective PBAC pumpers have been, by quietly doing what they do; managers have kept pumping rates constant in spite of growth. However the model makes it very clear that when we have maximized efficiency pumping rates will grow unless human water use behavior changes or population growth stops. In the long-term (i.e., 100+ years), even low population growth dominates all other considerations. Unfortunately, rather than leading to a dialogue on decision making under uncertainty, PBAC has continued to focus its time and effort on data identifying gaps and prioritizing efforts to close those gaps. A lesson learned is to have full buy in from decision makers (i.e., elected officials) at the start of the participatory
re hopeful that this was one of many steps that the community must go through to get decision makers to the table. The issues surrounding the difficulty of modeling the physical side of the system were enormous. Our sense is that even if the decision makers were there initially they would have told us to work it out with the experts and to let them know when the model was to the point that we could talk about potential policies. At the same time, we believe that greater effort to assess the situation upfront to better target the tool and to encourage key people to participate may have led to a better outcome. We are currently performing a situation assessment through interviews of basin leadership and water managers. Re-visiting the modeling process in light of that assessment may shed light on a process for use of the approach in other water basins. The complexities of designing a bi-when one considers other bi-state situations concerning water this basin is relatively simple. And although in the US
that rely on these aquifers we will continue to promote a precautionary, rather than reactionary approach to integrated water resource management.
VII. ACKNOWLEDGMENTS
We would like to acknowledge the Palouse Basin Aquifer Committee (PBAC) and its Citizen Advisory Group for their collaboration on this project.
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VIII. REFERENCES Beall, A., Fiedler, F. Boll, J., and Cosens, B. 2011 Sustainable Water Resource Management and Participatory System
Dynamics. Case study: Developing the Palouse Basin Participatory Model. Sustainability 3(5), 720-742. Bush, J.H.; Garwood, D.L., 2005. Geologic Cross Section of the Moscow-Pullman area Idaho.
http://www.webs.uidaho.edu/pbac/GeologicMaps/E_W_regional.pdf Accessed September 2010. Palouse Basin Aquifer Committee (PBAC), 2011. Available online: http://www.webs.uidaho.edu/pbac/. Accessed April
2011. Palouse Water Summit http://www.palousewatersummit.org/2006.html. Accessed May 2011 Robischon, S., 2011. Idaho Water Resource Research. Institute University of Idaho, Moscow, ID. Personal
communication January 2011.
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DESIGNING A SHARED VISION MODEL FOR ADAPTIVE MANAGEMENT WITH STAKEHOLDERS by Bill Werick1
ABSTRACT The International Joint Commission (IJC) regulates the shared waters of the U.S. and Canada. The IJC appointed an international study board in 2000 to develop new operating rules for the release of water from Lake Ontario. A Shared Vision Model was developed during the study and used by the Board to develop 3 preferred regulation plan options for the IJC to select from. Six years after the end of that study, the U.S. and Canada are negotiating final details of the new plan, still using the Shared Vision Model. The Shared Vision Planning process always included management with the model after a collaborative decision, but there were few practical examples. How should planners design models so they have an "afterlife" for such negotiations and for adaptive management? This paper introduces the basic concepts for doing that; it will be applied in a second IJC study of the Upper Great Lakes. The protocol involves the creation of an information management map that shows the route back from study decisions to study research, passing through decision criteria, plan formulation and evaluation and risk and uncertainty analysis. The map would allow users to track, after the study was long over, the reasoning of the Board so that adaptive modifications to the decision could be made as if the Board were still sitting and had just received the new post-study information. This paper essentially follows the format proposed by Hal Cardwell, Guillermo Mendoza and Stacy Langsdale (IWR) but without the questions enumerated explicitly.
I. INTRODUCTION
The International Joint Commission (IJC) regulates the release of water from Lake Superior into the St. Marys River. In 2005, it appointed an international study board to develop new regulation rules as part of a five year International Upper Great Lakes Study (IUGLS). The Board decided to use the shared vision planning (SVP) approach that had also been used by another internation -2005 Lake Ontario-St. Lawrence River (LOSL) regulation study. Each board found that the SVP approach provided a complete, practical way to thoroughly investigate regulation plan alternatives in an open collaborative manner. SVP made it easier to involve stakeholders, create greater trust in the overall process, and assure that technical studies were tailored to the needs of decision makers. The choice of SVP took considerable debate on the LOSL study; much less so on IUGSL because of its success on the LOSL study and the general trend towards collaborative modeling.
II. CONVENING STAKEHOLDER-BASED PROCESSES
SVP is a particular sort of systems analysis, an evolution of the iterative planning process described in the Federal Principles and Standards (U.S. Water Resources Council, 1973). The first step in SVP is to identify problems and begin building the problem solving team, which always includes stakeholders, decision makers and experts. The IJC has its own history of stakeholder involvement that had already supported a network of all three kinds of participants, and study funds were allocated for a Public Interest Advisory Group (PIAG). Two Board members served on PIAG, and PIAG appointed representatives to work with experts on six Technical Working Groups (TWGs) developing water level impact studies for hydropower, coastal development, commercial navigation, ecosystems, recreational boating, and municipal and industrial water supply. The strong support and predetermined PIAG framework generally made it easy to do participatory planning. The SVM in this case was a large, fancy Excel spreadsheet, so it was relatively easy to use and share. Each of the TWGs (and by extension, stakeholders) are now involved in a review of the SVM that extends the
represents the impacts on each TWG sector from any new regulation plan. From the very beginning of the study, stakeholders have been able to work with experts to create measures within the SVM that they will use in deciding which plans are best. The fact that the model is easily shared and is the vehicle for the integration of the various scientific studies to support the decision has led to a much more thorough model review than a peer review typically would. This 1 14508 Chesterfield Lane Culpeper, VA 22701. [email protected]
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is customary for SVMs because the models are instrumental in the decision and stakeholders are keen to make sure the model makes their case well. This creates a usefully critical tension among experts and stakeholders, sometimes including stakeholders with conflicting self-interest. Circles of Influence are being used to help develop the input and win the trust of team members who because of lim
experts and leaders they trust.
Comparing LOSL and IUGLS
There are many similarities between the two studies, but three defining differences. First, the effect of regulation on Lake Ontario is much more pronounced and the planned changes are more significant. For sixty years, Lake Ontario regulation has compressed the lake level range, while Lake Superior regulation has a much more muted effect. The ecological response portion of the Ontario shared vision model showed this compression reduced the diversity of wetland plants, but the flood and erosion part of the model showed that range compression also helped reduce damages to coastal homes.
Figure 1 shows Lake Ontario levels under a variety of regulation plans considered during the LOSL study, all based on 20th century water supplies. Elevations are in meters, IGLD 1985. The unregulated condition, preproject, would have allowed levels as high as 76.16 meters, whereas the current regulation plan, 1958DD, kept the lake nearly half a meter lower. The difference between the regulated and unregulated levels on Lake Superior (Figure 2), however, amount to a few centimeters and the differences on Lake Michigan and Huron are even less.
The second difference is that the Lake Superior study uses a more evolved assessment of climate uncertainty
and has invested more into the use of adaptive management to address that uncertainty. Briefly, the climate assessment does not put downscaled climate model results at the center of the analysis. Instead, the assessment begins with the definition of the most worrisome impacts, then asks what water supply condition could create those impacts, and finally, determines whether those water supplies are plausible. Plausibility is a judgment based on a wide variety of technical analysis including the results from downscaled global circulation models, regional climate models, paleohydrology, and stochastic analysis. The study team will attempt to design regulation plans that are robust that is, plans that perform about as well as any other no matter the supplies. Adaptive management will be used improve the plan as the true future climate unfolds and the uncertainties underlying the plan selection are reduced. The third difference between the two studies is that there is a conscious effort on the Upper Great Lakes study to create an information management plan for adaptive management. An interactive information management map is being developed that shows the route back from study decisions to study research, passing through decision criteria, plan formulation and evaluation and risk and uncertainty analysis. The online map will have links to the associated reports and data. The map would allow users to track, after the study was long over, the reasoning of the Board so that adaptive
Figure 6 Lake Ontario levels (red bar is average and range is blue) using historic supplies, several plans
Figure 5 Lake Superior maximum, average and minimum levels for the current regulation plan (77A) a proposed plan (122) and no regulation (PP), based on historic (HI) supplies
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modifications to the decision could be made as if the Board were still sitting and had just received the new post-study information. Jacob Bruxer, Environment Canada, is reviewing the SVM and will document the linkages, working with web designers to create the online presentation. This work is discu
III. USING DECISION SUPPORT TOOLS IN IWRM
Iterative planning
from previous studies, including water level statistics from the LOSL study and crude benefit transfer estimates of boating, hydropower and navigation benefits. Fencepost plans were designed to address one stakeholder group no matter the impact on other stakeholders. As a group these plans corralled the possible outcomes; for example, a plan that compressed Lake Michigan levels to avoid coastal damages created very damaging high and low water levels on Lake Superior, but it showed the maximum impact Lake Superior regulation could have on Lake Michigan flooding, and so became a valuable tool for managing stakeholder expectations.
The practice decisions were held at Board meetings and the results were widely distributed among study participants. Plan formulators relied on these decisions to sharpen their design criteria, while stakeholders and decision makers used them to develop desired outcomes and to criticize the performance indicators and other metrics used in the practice decision.
Plan ranking and selection
As of May 2011, the study is about ten months from completion, so the final plan selection has not been made.
for the final plan ranking. Those metrics will be programmed into the SVM so that Board members and others can see the rationale for plan ranking.
IV. NAVIGATING INSTITUTIONAL FRAMEWORKS
The choice of a regulation plan is driven by the Boundary Waters Treaty of 1909 between Canada and the United States. The SVM preserves treaty requirements where necessary in the allocation of water (for example, the equal division of flow at Soo hydropower plants). The study has been financed by line item funding in U.S. and Canadian appropriation bills for the U.S. State Department and the Canadian Foreign Affairs.
V. OUTCOME
The Study is in its last year. After the study is over, the IJC will hold public hearings on the study recommendations and will probably select a new plan within the next few years.
The decision has not been made but will be organically connected to the shared vision planning process. Stakeholders, experts and decision makers use the SVM to decide which regulation plans to champion. The LOSL study shows that the SVM will be used by a new set of decision makers after the study to weigh competing plan outcomes.
VI. REFLECTION Unlike the Lake Ontario study, the Upper Great Lakes study will not produce a substantially different regulation plan nor will it resolve deep seated conflicts among stakeholders. The most significant issues on the Upper Lakes study have all surrounded future uncertainty and the development of an adaptive management plan to address water levels above and below those in the historic record. The planning, modeling, participation and decision making elements of shared vision planning have all been important in addressing these challenges:
The systems planning principles of shared vision planning encourage study participants to think about objectives rather than preferred alternatives. Traditionally, this has been the foundation for interest based
- method has always helped local experts inform the basinwide
decisions which were the subject of the SVP study, but in this case, they were also a good forum for local flood and coastal zone managers to access the climate risk information developed by IUGSL to improve local decision making.
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The Shared Vision Model and decision support are useful in making decisions but never before have both the model and decision process been so explicitly designed and documented for adaptive management.
Most participants in IUGLS support the use of SVP, and that acceptance came much more easily than on the LOSL study and certainly more easily than the first SVP studies in the 1990s. The lack of controversy (with the exception of the two issues described below) was due in part to its successful application on LOSL, but may in part be due to general public expectations that electronic processing should change everything from the way one finds a place to eat to the way one arranges travel.
There were two issues, hopefully overcome now. First, some study participa
conflict, and from the beginning (U.S. Army Corps of Engineers), it has been acknowledged that at best, SVP can create
differing values or self-interest is to facilitate the development of solutions that satisfy those values or interests. A few stakeholders also took umbrage at the circles of influence concept because it seemed to duplicate or compete
with public meetings, which were being run by the Public Interest Advisory Group. It seems that people are comfortable with the idea now, as experience showed that the two approaches can co-exist and that the Circles approach has merit.
Using these methods outside North America
We are beginning SVP studies in Peru and the immediately obvious difference is that North American stakeholders are far wealthier and better equipped to participate. Participatory studies place a premium on communicating precisely but in ways that can be more commonly understood, a challenge when English is the principal language of all involved, much more difficult when it is not and the culture has less experience with collaborative planning.
Will this study be successful?
Success in SVP is defined as the creation of benefits that would not otherwise have occurred. It is clear that SVP will have been helpful in producing benefits from the new Superior regulation plan, but those benefits will be modest compared to the benefits that should accrue from the new Ontario regulation plan. The greatest and most uncertain successes of SVP on the Upper Lakes will be the creation of an online knowledge system that helps others adapt to changing water levels beyond IJCs control, and the demonstration of a new and more sound approach to managing climate uncertainty.
VII. REFERENCES U.S. Water Resources Council, 1973. Principles and Standards for Planning Water and Related Land Resources. Washington, D.C. U.S. Army Corps of Engineers (1994). Managing Water for Drought. Institute for Water Resources, 7701 Telegraph Road, Alexandria, VA 22315. (IWR Report 94-NDS-8) U.S. Water Resources Council, 1983. Economic and Environmental Principles and Guidelines for Water and Related Land Resources Implementation Studies. Washington, D.C.
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COLLABORATIVE, STAKEHOLDER-DRIVEN WATER-ENERGY-AGRICULTURE-ECOSYSTEMS MODELING AND PLANNING FOR LONG-TERM RESOURCE SUSTAINABILITY: A CASE STUDY IN THE TIGRIS EUPHRATES by Howard Passell and Vince Tidwell I. Introduce problem description and context.
What is the purpose and location of the study? What problem were you trying to solve? The location was the Tigris-‐Euphrates Basin. We were working with the Iraqi Ministry of Water, the US Dept. of State, and UNESCO, to build a model of water-‐energy-‐ag resources in Iraq. The model was intended to inform long term decision making in the government.
Describe unique aspects of the study context. What was the catalyst or reason for using collaborative modeling / Shared Vision Planning?
The catalyst for using the approach was that we felt it was the most effective. The catalyst for the work in general was the Iraqi concern that the country will become more water scarce in the decades to come. II. Convening Stakeholder Based Processes
Please describe the participatory framework and how that was used to identify a distinct set of problems or opportunities. Who was involved? What role did they play (e.g. data provider, reviewer, problem definer, etc.)?
The framework was made by the scientists and engineers from the partner institutions named above. Over a period of 16 months we held 5 meetings in the Middle East, each time for 1 week. A total of 8 engineers and scientists from the Iraqi Ministry of Water Resources (MoWR), 2 staff from the US Embassy, and a UNESCO water program director. Not all were present at every meeting. The Iraqi partners role was to provide expertise on the structure of water-‐energy-‐ag systems in Iraq, to provide data, to receive our training in the modeling and to learn it, and to do some of the modeling, and ultimately to transmit the results of the modeling and even a demo of the model
input into structural issues. He also helped provide meeting space for some meetings at the United Nations University in Amman, and he was a general supporter. One staffer from the embassy was the director of a program that funded us, and the other was a very committed and very nice Egyptian-‐American hydrologist who was very closely involved in the project in every way, and who was killed by a roadside explosion during one of his trips outside Baghdad aimed at improving water resource availability for Iraqis.
What aspects of the participation framework enhanced or restricted IWRM planning?
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Trust and good will among the partners enhanced the planning process.
How did collaborative modeling support coordination of all the participants? It helped take some of the guesswork out of how to manage resources in the future for all of them. III. Developing Decision Support Tools
How did collaborative modeling support conceptualization of the project decision or plan (from developing objectives through formulating alternatives)
How was collaborative modeling used to coordinate and plan details (evaluate and finalize the decision or plan)?
How did collaborative modeling support implementation, monitoring and evaluation of the decision or plan?
III. Navigating Institutional Frameworks and Implementing Decisions
Describe any policies or legislation that influenced the study. The MoWR is carrying on with its long range planning, and as a result of our work we have been invited to continue with the modeling, again with MoWR engineers and scientists, but this time also with other participants from a consortium of companies involved in the long range planning effort.
range effort.
How was the modeling process (both the technical modeling and stakeholder involvement) financed?
The first phase of the work was financed by the US Dept. of State. The current work is being financed by the Gov. of Iraq. IV. Outcome
What was the outcome or current status of the collaborative modeling process? How did the process directly or indirectly influence a decision? Describe how your effort impacted or influenced policies, strategies, laws/regulations,
future research, financing, etc in the IWRM process. What changed as a result of your effort?
See comments in previous section. V. Reflection
Please consider the most useful aspects of your project and describe why they were useful (e.g., participation, question identification, data collection, etc.) to support IWRM
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One of the most useful aspects was the participation by the Iraqi engineers and scientists, the UNESCO participant, and the DOS participants, without whom of course we would not have had the subject matter expertise nor the data to build a good model. Another of the most useful aspects was the excellent modeling skill among our own team members, which allowed us to focus sufficiently on the subject matter in creative and expansive ways.
What elements of the Collaborative Modeling for Decision Support approach enhanced or restricted the process of IWRM
The collaboration enhanced IWRM. The proprietary nature of water data in the Tigris Euphrates basin restricted the process. We were missing some data on some transboundary dynamics.
What was surprising or unusual about your experience in this case? For example, If you have worked in different countries, describe any features of the study that would have been different if applied in a different country.
The international experience creates a whole level of challenges, including primarily linguistic and communications challenges, but also cultural challenges.
What were your lessons learned? One lesson learned is that stakeholder involvement is crucial to building a good model that will be used. No one but the stakeholders fully understand the system dynamics, and they must convey that understanding to the modelers. Also, we think it is important to build into the scope of the project a road show in which project partners take the model out into the wider community and make demonstrations of it, and explain results. All these models stand the risk of being put on a shelf once completed, so any extra effort expended on developing an advocacy for the modeling or for more firmly establishing it is well spent.
Would you view this effort as a success? Why or why not? I conclude that was a successful project because we built a good model that offered valuable insight, and our Iraqi colleagues found it sufficiently useful to want to continue with more modeling.
Would the participants would view this as a success? Why or why not? See above.
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Session 16: Case Studies in Collaborative Modeling III Navigating Institutional Frameworks and Implementing Decisions
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INTEGRATED FRESHWATER SOLUTIONS A NEW ZEALAND CASE USING MEDIATED MODELLING by Marjan van den Belt, Heike Schiele*
ABSTRACT
This paper presents preliminary results from the Integrated Freshwater Solutions (IFS www.ifs.org.nz) action
researcZealand (NZ). diverse stakeholder groups representing industry & farming, local and regional authorities, environmental groups, and
-tribe) groups. We are using Mediated Modelling (MM) as a tool to integrate economic, ecological, social and cultural interests.
iver consists of 9 sub-catchments. The key issues are: sedimentation, eutrophication and habitat
Accord in July 2010 to improve the quality of th The IFS project is funded by the Ministry for Science and Innovation (MSI) to run from 2010 to 2013 and is commissioned to Ecological Economics Research NZ (EERNZ), Massey University.
In this paper we describe the context setting in which the Mediated Modelling (MM) tool is used. We evaluate the availability and the role of data and the process and facilitation choices that were made from a MM perspective to support the Forum in achieving its goal of developing an action plan by March 2011. We also examine the roles of
Key Words: Mediated Modelling Adaptive Management Capacity Process and Facilitation Indigenous Stakeholders
I. INTRODUCTION
Over the past 40 years the quality o10 years. In addition, the pressure to store and allocate more water is increasing due to intensification of farming.
As pressure on quality and availability of freshwater increases, so does the tension between economic (Western) The
river is healthy the land and the people are
to claim the rights to water as it is identified as one of their taonga (treasures). The Resource Management Act (RMA) 1991
d catchments. The river runs East to West over a distance of 200km in the lower North Island traversing a fault line and mountain range. It has 9 sub-catchments with varying degrees from sedimentation, eutrophication and habitat loss. arly features at the bottom of national water quality league tables for nitrate, phosphate, turbidity, E-Coli, Dissolved Oxygen, and Macro-invertebrate Community Index to name a few. Around 60% of native fish, shellfish and crayfish are endangered (Ministry for the Environment, 2010; Joy, 2010).
body responsible for freshwater management under the RMA. Forum members were recruited from HRC, local auth In July 2010 the leaders signed an Accord, committing to develop an action plan by March 2011 that would help to meet the following agreed goals by 2030:
- a source of reg ).
* Associate Professor, Director of Ecological Economics Research New Zealand at Massey University, Landcare Research Building, Private Bag 11222, Palmerston North 4442, New Zealand. Email: [email protected] http://eernz.massey.ac.nz/ Phone: 64(0)6-356 9099 ext 81512PhD Researcher, Ecological Economics Research New Zealand at Massey University, Email:[email protected] Phone: 64(0)6-356 909 ext 81518
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- resources.
- n. - omic
prosperity of the region. In parallel, EERNZ received funding from MSI in July 2010 for a three year period (October 2010 September 2013). IFS is an end-and environmental stakeholders. The project is action research, aiming at developing a blueprint for other regional authorities to manage freshwater in a more integrated, adaptive manner. It uses and tests two synergistic modelling approaches MM and Bayesian Belief Network (BBN) modelling.
MM is a tool to help stakeholders develop a common understanding of complex systems, in this case to explore natural capital, providing ecosystems services and their relation to Catchment. Through the MM process, we explore solutions and their potential impact on natural capital and ecosystem services, aiming to support a cycle of continuous improvement. (Fig. 1) Figure 1: Freshwater Ecosystem Service Evaluation
Natural Capital of Freshwater Systems Rivers and Streams Aquifers Riparian Zones Wetlands Aquatic Life
Ecosystems Services of Freshwater Food Water Provision Habitat Nutrient Cycling Climate Regulation & Carbon Cycling Recreation
Governance, Institutions, Solutions Enforcement of existing rules Anticipated Policies Adaptive Management Co-management Moratorium on Harvest Conservation Education & Communication Monitoring
(E) Valuation of Estuaries & Coasts Perceived or Non Perceived Benefits
from Ecosystem Services Potential costs for stakeholders. Market, Non Market Prices New funding sources and spending
efficiency Stakeholder Participation Tradeoffs Cultural & Spiritual Values
Source: Adapted from van den Belt, 2011 in press STELLA software is used to scope a dynamic model showing causes, effects and unintended consequences simulating a 50 year period comprising the 20 years of historic data as well as future projections for 30 year goals and pathways. It provides a system dynamics framework to evaluate some action plans and monitor data requirements to assess the overall outcomes of proposed actions and their tradeoffs, thus creating the platform for adaptive management. In IFS, MM will be complemented by BBN, a spatially explicit model using GIS data. BBN connects land use and land cover
Given the strong overlap in objectives and participating s
August 2010 to join forces and work jointly on developing the first action plan by March 2011. It was agreed that the -facilitate the process.
II. CONVENING STAKEHOLDER-BASED PROCESSES
The decision to join forces was followed by a period of planning for a series of 6 workshops to run monthly between October 2010 and March 2011. The purpose of the workshops was to develop an acwould address its four stated goals, while delivering the first iteration of a scoping model showing historic and anticipated cause and effect interdependencies.
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It was recognised early on in the project that risks and benefits in this first phase were different for the Forum and IFS even though some goals overlapped. The Forum was very much driven by the need to deliver an action plan by March 2011, whereas IFS was more focused on understanding the underlying system and capacity building, from which an action plan was to eventuate. Risks and benefits were identified prior to starting the collaboration and set the context for tradeoffs made later in the organization of the project (Table 1).
Table 1: Pre-collaboration Assessment of Risks and Benefits Risks Benefits Compression of IFS research time frame for the initial MM and BBN models from 2 years to 6 months.
2011
Real time application of research. Opportunity to build, measure and monitor adaptive capacity throughout two additional planning cycles. Political process aided by neutral team and focus on facts.
Data gathering effort - Resource availability and access to data in general - Translation and interpretation of scientific data to
create a common knowledge base for stakeholders
Opportunity to feed into regional and local annual and 10-year planning cycles.
Leader IFS) with distinct facilitation methods and process approaches
with the University and the use of a transparent process.
Political dynamics in local government elections November 2010) during project set up. Out of scope are treaty play a role in the background.
Potential for buy-in and implementation of findings.
or meet predominantly in contentious situations.
Stakeholder selection w
IFS project. There were 5 distinct actively participating stakeholder groups in total: Regional Council, local authorities, industry and farming, environmental intere Each group was asked to nominate up to 4 representatives who would participate in the six workshops. Only named representatives would be allowed to actively participate in the workshops. It was possible to nominate in lieu representatives and to invite observers to the sessions.
Workshops were open to members of the general public to observe in order to increase transparency and openness. The IFS team consisted of a Science Leader/ Mediated Modeller, a modeller, a research officer and a PhD student. Figure 2: Stakeholder Selection & Communication High Interest
Low Decision Making
Represented stakeholder organisations Engaged Public Scientists Regular 2 way communication
Direct Participants in Mediated Modelling
High Decision Making
Power
Other sectors Disengaged public Media updates
Stakeholders not wanting to be involved Regular 2 way communication
Power
Low Interest
Source: Adapted from van den Belt, 2004
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With the risks and benefits in mind and a clear understanding of the participating stakeholder groups the six
workshops were set out to flow as follows:
Workshop 1 Introductions, qualitative model, from goals to indicators, some solutions brainstorming. Workshop 2 Solutions and targets, towards a draft action plan. Workshop 3 Economics, time frame, equity, draft action plan. Workshop 4 Land use, water quality/quantity, indicators & monitoring, review model, draft action plan. Workshop 5 Social, cultural and ownership aspects, review model and action plan. Workshop 6 Overall simulation and final action plan.
The presentation material and summaries and model updates from each workshop can be found on the website. Data gathering and continuous fine tuning of the model as well as engagement with individual stakeholders on a one on one basis was planned for the time between workshops to accelerate progress, to familiarize interested stakeholders with the model and allow in-depth engagement.
The first two workshops resulted in the development of the base model in STELLA leading to a clearer understanding of the interdependencies of land use changes, river engineering and demographics on levels of sedimentation, eutrophication and habitat loss for native and introduced (trout) fish. There was general agreement that due to reasonable levels of rainfall in the catchment, 90% of the issue was around water quality and only 10% around water quantity. It was established that ca. 50% of sediment come from accelerated erosion from hill country farms and 50% from river engineering. Ca 86 98% of nutrient problems stem from farming and 14 2% from point source dischargers at low and high water flows respectively. It was obvious from the beginning that actual data to populate all aspects of the model was difficult to source which meant that the model would have limited reference trends for calibration.
Workshop 3 was about developing the economic cause and effect links for the model. This did not eventuate due to a number of reasons which will be discussed later and led to some members/decision makers in the group concerned that the agreed deadline for an action plan by March 2011would not be met. As a consequence it was decided to revert to a more traditional, linear facilitation process conducted by the chairman of the Leaders Forum, with subgroups working up action plans in-between workshops and consolidation of sub-group action plans during the remaining three workshops. IFS continued to source data and improve the model outside of workshops working with individual participants and reporting back at each of the remaining workshops. IFS supported the changed process but took a step back in facilitation and driving the agenda toward a politically acceptable action plan.
III. USING DECISION SUPPORT TOOLS
MM helped the stakeholders around the table early on in the process to develop a shared and more integrated understanding of causes and effects as well as a sense of order of magnitude of problems and the impact proposed solutions might have. In the course of the discussions it came as a surprise to the participants just how much scientific data was available from HRC and how much activity was already underway. Through the discussions it became evident that the data available was not always presented in a way that made it intuitive for the layperson. As a result HRC put a lot of effort into regrouping and consolidating data on a sub-catchment level to make the challenges and related solutions more accessible.
The original plan had been to simulate some of the solutions in the model to give participants a better understanding of their potential benefits as well as unintended consequences. Due to the difficulties in obtaining relevant data in the given timeframe this exercise had to be deferred to the next round of workshops which will commence in June 2011. However, the shared understanding of key issues provided a sufficiently robust base for the first, incremental action plan.
IV. OUTCOME
Forbes, M., 2011). By the end of May 2011 IFS will have populated and documented the scoping model, this will be15 months ahead of the original research plan submitted to the funders. Initial results from the post-workshop surveys indicate a strong support to continue with solution-oriented workshops, fostering adaptive capacity building among stakeholders.
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IFS funding will be covered through the original research project until September 2013. The accelerated approach to action planning has given the project team an opportunity to build more adaptive capacity with stakeholders by conducting workshops during two additional planning rounds. The outcomes from the next series of three workshops will have the potential to inform the 10-year planning process which takes place in regional and local authorities during 2011/12.
east on an annual basis to monitor progress and adapt the action plan. There is recognition amongst leaders that future action plans can be enhanced through prioritisation of actions and the addition of more specific targets and timelines. The current action plan in incremental and its strengths is in communicating more coherently what is already happening.
V. REFLECTION Political Context Changes in Sponsorship
In order to understand some of the dynamics within the project, one also needs to understand the dynamics around the project. Local Government elections in November 2010 saw the Chairman of the Regional Council and original
Furthermore the makeup of the council changed, with more councillors representing farming interests being voted in. This drove a level of uncertainty into the project, the commitment to resources and the continuity in approach. In the end, IFS did not receive the level of support in data gathering that had been indicated under the previous sponsor.
However, throughout the changes in sponsorship the project continued, and had a very public profile. Science Content The need for science translation and communication
The multitude of data sets available appeared to be more confusing rather than helpful to individuals. There was at times
drivers of water quality in the catchment and those who took more of a local approach to river quality. MM helped to establish the relativity of problems across the whole region and showed systemic interconnections and flow on effects. At the same time HRC catered to the interest in more localised information by preparing factsheets for the 9 sub-catchments.
The second area of intense discussion was around the desire to move from the goals stated in the Accord to measurable improvement targets. The multitude of individual physico-chemical measurements e.g. for nitrogen, phosphate, dissolved oxygen, temperature and turbidity, biodiversity and cultural indicators, had to be brought together in a framework that could be accepted by all.
Last but not least different stakeholders had different perceptions of what science was actually telling them. Whereas in most cases consensus could be reached by the group through dialogue, in some cases the group was looking for guidance from independent scientists outside the project. This guidance was in the end provided by a panel of scientists from various Crown Research Institutes who met on one occasion to clarify outstanding questions for the participants. Participants had agreed upfront to accept the outcome from the science panel. Time Quality Resource Trade off
Most projects are likely to experience some tension between available time, resources and the quality of outcomes. Due to the high
public interest, and a publicly made commitment, this timeline was not negotiable. The six months period available included the Christmas holiday period. As previously mentioned, the 3rd workshop on 13 December did not lead to the expected outcomes around modelling the economic drivers in the system. In hindsight we believe this was due to a combination of several factors. The absence of some of the key players from industry and farming, who had been particularly interested in discussing Economics, combined with the introduction of some new players, who had not been sufficiently briefed, changed group dynamics on the day considerably funding sources, costs for stakeholders and benefits from an ecosystem service perspective. The latter was a new concept for most participants and too big to take on under the time pressure to produce an action plan.
At the same time the usefulness of the MM process at this stage of the project was questioned by some participants (mainly decision makers), as the model could not be populated with data due to a lack of resources available for data gathering. They, therefore, felt that too much precious time was spent on a model that could only show causes and effects in principle, but not provide precise baselines for the catchment. A mid-point survey of the participants indicated
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that model reflect their inputs and the linking of causal effects. The process also suited their approach to developing relationships and talking through issues upfront. change the approach for the last three workshops to a more traditional, linear process of mediated action planning with subgroups developing actions in-between workshops and the workshops providing the platform to integrate the emerging plans. The revised workshops were facilitated by the Chairman of the Forum. Stakeholder interests and dynamics Figure 3 Stakeholder Dynamics Revisiting Quadrant 1 from Figure 2 High Interest
Low Decision Making Power
Environmental groups Scientists Observers
Regional Council
High Decision Making Power
Industry/Farming
Local Authorities
Low Interest Source: Adaptation of Figure 2 based on van den Belt, 2004
In the course of the six workshops it became increasingly apparent that the participants as identified in the high interest/high decision making power quadrant in Figure 2 were not a homogeneous group. Applying the stakeholder quadrant model to them as a group in Figure 3 identifies HRC as the group with the highest interest and decision making power due to their role as regulator; industry and local authority stakeholder groups had high decision making power within the boundaries of their organisations, but a lesser interest, which was possibly reflected in their patchy attendance of the workshops. The environment and power. Their attendance in the workshops was the most consistent amongst all groups. Action Plan
In the end compromises had to be made around the action plan. Few actions have got clear timelines, targets and costs associated. Overall the plan has an incremental nature. But all actions are steps in the right direction and have the support from all participants. As one participant put it, the mere fact that actions were discussed during the workshops and are highly visible to the general public, has made collaborating organisations focus on the actions.
IFS supported the change in approach in the interest of adaptive capacity building and in expectation to be able to contribute to the 10-year planning process in 2011/12 using a populated model to simulate the likely impact of the key actions.
VI. ACKNOWLEDGMENTS This programme is funded by the New Zealand Ministry for Science and Innovation (MSI) under grant number MAUX 1002. This project could not happen without the in-kind contributions from the various participants involved. Names and affiliations are included on the website.
VII. REFERENCES Forbes, M., 2011, Polluters approve to clean up dirty river, Dominion Post Wellington, A2 Joy, M, 2010, Before the Manawatu Wanganui Rgional council, speaking Notes $ Supplementary Statement of Evidence
on behalf of Wellington fish & Game & The New Zealand Royal Forest & bird Protection society, section 214
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Ministry for the Environment, Nutrient river water quality league table: nitrate, total nitrogen, dissolved reactive phosphorus, total phosphorus, http://www.mfe.govt.nz/environmental-reporting/freshwater/river/league-table/nutrient, accessed 11/01/2011
van den Belt, M, in press 2011, Ecological Economics of Estuaries and Coasts. Chapter 1 in Volume 12 (Eds M.van den Belt and R. Costanza).of Treatise on Estuaries and Coasts. Eds. E. Wolanski and D. McLusky, Elsevier.
Van den Belt, M. 2004, Mediated Modeling; a system dynamics approach to environmental consensus building, Island Press, Washington D.C
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IWRM THROUGH COLLABORATIVE MODELING FOR DECISION SUPPORT THE BOW RIVER CASE STUDY by Daniel Sheer, HydroLogics Inc., Columbia, MD ABSTRACT Integrated Water Management often involves achieving multiple management objectives for multiple stakeholders. Collaborative Modeling for Decision Support (CMDS) can be extraordinarily effective in developing implementable, consensus based IWRM plans. A CMDS process on the Bow River in Alberta, concluded in December 2010, has developed an IWRM strategy and recommended government action to implement the strategy. The strategy includes integrated management of water supply withdrawals, hydropower reservoirs, and large off-stream reservoirs that serve irrigation demands. The benefits include improved recreational fisheries, improved instream flow, more reliable supply, and the identification of additional water to be made available for continuing development in the Basin. The CDMS focus on developing performance measures and on collaborative modeling allowed the process to leverage stakeholder expertise concerning alternative operating strategies and their impacts. It also paved the way for a consensus request to the Government of Alberta to consider the agreed upon IWRM plan. This will undoubtedly increase the likelihood of implementation. This presentation will present the results of the CDMS process, focusing on how CMDS can help to: * define the objectives for IWRM, * develop creative alternatives for IWRM * leverage stakeholder expertise, and * assist in implementing IWRM CASE STUDY Q & A
I. INTRODUCTION
Introduce the problem and describe the context. What is the purpose and location of the study? What problem were you trying to solve?
The Bow River Basin in Alberta rises in the Canadian Rocky Mountains and flows out onto the irrigated prairie passing through the cities of Banff and Calgary. Several of the mountainous tributaries are impounded for hydropower production, and the hydropower storage is the only sizeable on-‐stream storage (with one smallish exception) in the basin. The irrigation districts on the prairie have large offstream storage reservoirs which primarily support irrigation
e of the water licenses (Canadian version of US water rights) in the basin. A severe drought in 2001, coupled with a desire to preserve instream flows and an interprovincial requirement to deliver half of the water in the South Saskatchewan Basin (the Bow is most developed tributary) to the province of Saskatchewan led to the Government of Alberta closing the basin to new water licenses in 2009. Rapid urban and industrial development, fueled in part by the development of the oil sands in northern Alberta, has created increasing demands for new municipal and industrial supply. There is no clear precedent for transfer of water from existing licenses to new users, nor for compensating the hydro utility for making directed releases from
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their reservoirs for other purposes. There was a widely held perception that coordinated management of the hydropower and irrigation reservoirs could greatly increase the reliability of flows. The problem at hand was to establish that coordinated operations could, in fact, provide substantial benefits for all water uses and to reach consensus among the stakeholders on an operational scheme that could be recommended to the government.
Describe unique aspects of the study context.
In addition to the description above,
The irrigation districts in the basin have an informal coordination of their withdrawals based on the priority of their water rights and the desire to ensure adequate water to all farmers, especially those vulnerable to daily fluctuations in streamflow. Canadian water licenses are at the whim of the crown, and can be legally cancelled at any time without compensation. There is not the political will to do so, however, but that could change. As a result, the stakes in the negotiation are somewhat different than they would be in the US. The hydropower utility faces license renewal in 2020, and the need to make capital expenditures for rehab and perhaps expansion in the near future. The utility has expressed its desire to negotiate operational changes with a single party, the government, rather than individual water users. This placed a severe time constraint about 9 months, on the collaborative process. There was widely held skepticism that consensus could be reached in that short a time period. Most of the stakeholders had little experience with models prior to the process. Critical data was difficult to obtain through the Environment department of the Alberta government. Much of the modeling work was done by foreigners. The models were made generally available on a server, over the internet, and local staff was trained to carry on modeling when the process was complete.
What was the catalyst or reason for using collaborative modeling / Shared Vision Planning? Dave Hill, the director of the Alberta Water Research Institute was aware of collaborative modeling efforts and their success in the US. He had arranged for a mock process for the entire South Saskatchewan Basin with funding from the Canadian Government, the State of Israel, and others. The mock process convinced many in the Basin that a collaborative process could succeed. Finally, Kim Sturgiss, a pre-‐eminent Canadian engineer, and Mike Kelly, an influential former executive of the hydro utility became convinced that such a process was worth trying and championed the effort.
II. CONVENING STAKEHOLDER-‐BASED PROCESSES IN IWRM
Please describe the participatory framework and how that was used to identify a distinct set of problems or opportunities. Who was involved? What role did they play (e.g. data provider, reviewer, problem definer, etc.)?
The Government of Alberta requested assistance from the Alberta Water Research Institute to investigate potential benefits of integrating hydro operations with downstream basin management. Dave Hill, Mike Kelly, and Kim Sturgiss used their connections and influence to bring the stakeholders to a meeting. At the meeting HydroLogics described the
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CAN (Computer Aided Negotiation Process). The stakeholders agreed to attempt the process. The stakeholders agreed to participate and some provided modest funding. The bulk of the funding came from AWRI and from the Alberta Water Environment Hub, and umbrella organization for managing water science and data in the province.
-‐profit organization) provided logistical, administrative and facilitation support. HydroLogics provided modeling and facilitation support. The stakeholder group contributed substantial time and effort in meetings, and between meeting efforts. The process was modeled on HydroLogics CAN process:
1. Identify performance measures. 2. Identify data and scientific methods to be used. 3. Create a fairly comprehensive list of alternatives. 4. Develop analytical tools, including but not limited to models, to evaluate the alternatives in terms of the
performance measures using the identified data and methods. 5. Conduct CAN sessions to facilitate consensus building.
The CAN sessions were generally two day affairs, with multiple teams each supported by one or more modelers. The teams evaluated and modified alternatives on the list and created new alternatives to be tested on-‐the-‐fly. Between meetings the alternatives were refined, model bugs were addressed, and new suggestions were put forward and evaluated. After consensus was reached, a final report was prepared and reviewed line by line at the last meeting of the stakeholders prior to submission to the government.
What aspects of the participation framework enhanced or restricted IWRM planning? The entire effort was collaborative IWRM planning.
How did collaborative modeling support coordination of all the participants? Did the collaborative model support stakeholder participation throughout the process, from problem definition through implementation?
The integrated CAN process and modeling efforts focused discussions on practical alternatives by forcing participants to consider how their suggestions could be implemented. The model provided the opportunity to weed out alternatives that seemed initially beneficial, but simply did not pan out. Counterintuitive modeling results led either to corrections to the model or a better shared understanding of the capabilities and limitations of management alternatives.
How did participation influence public awareness of the problem and/or increase accountability? The process built broad based support for the consensus alternative, and provided each stakeholder community with access to trusted resources that could explain what works and why.
What were the capacity development needs and limitations of stakeholders? The stakeholders faced a steep learning curve, first and foremost in providing definition of their actual interests in the management of the river (defining performance measures). They then had to understand how the models represented reality, and, as a by-‐product, learned the actual reality associated with managing the resource for all the different uses. The stakeholders needed to learn new language to communicate between themselves, the facilitators helped this along. Finally, the stakeholders had to learn what was important and what was less important to other stakeholders in order to collaboratively craft a consensus solution.
III. USING DECISION SUPPORT TOOLS IN IWRM
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How did collaborative modeling support conceptualization of the project decision or plan (from developing
objectives through formulating alternatives)? The CAN process, as described above is targeted at providing this support
How was collaborative modeling used to coordinate and plan details (evaluate and final ize the decision or plan)?
Potential difficulties in implementation are largely identified and resolved in describing the alternatives to the modelers prior to coding. The choice of level of detail and time-‐step for the model are critical in this regard.
How did collaborative modeling support implementation, monitoring and evaluation of the decision or plan?
The plan has been presented to the Government of Alberta, which will negotiate with the hydropower utility and issue the necessary regulations (and recommend legislation, if needed).
IV. NAVIGATING INSTITUTIONAL FRAMEWORKS AND IMPLEMENTING DECISIONS
Describe any policies or legislation that influenced the study. See above. How was the modeling process (both the technical modeling and stakeholder involvement) financed? See
above. Did any challenges slow or block implementation of the decision? Were any challenges avoided or overcome
by use of the collaborative modeling process? See above. Are any of these institutional factors included in the model? See above.
V. OUTCOME
What was the outcome or current status of the collaborative modeling process? See above. How did the process directly or indirectly influence a decision? See above. Describe how your effort impacted or influenced policies, strategies, laws/regulations, future research,
financing, etc in the IWRM process. What changed as a result of your effort? See above.
VI. REFLECTION
Please consider the most critical aspects of your project and describe why they were useful (e.g., participation, question identification, data collection, etc.) to support IWRM
The CAN process, with its emphasis on performance measures, is entirely commensurate with IWRM. IWRM suffers only if the scope of the process was limited. This was not the case on the Bow.
What elements of the Collaborative Modeling for Decision Support approach enhanced or restricted the process of IWRM? See above.
What was surprising or unusual about your experience in this case? If your case was conducted in a different country (ie, in a developing country if it was in a developed country or vice versa), what would have changed? What would you have done differently? See above.
What were your lessons learned?
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With committed stakeholders and sufficient modeling support, collaborative processes can achieve consensus relatively quickly.
Would you view this effort as a success?
The process met or exceeded all expectations.
Would the participants view this as a success? Why or why not?
Yes, indeed a success. The process built a communal reality-‐based appreciation of the capabilities and limitations of the system, and a shared appreciation of the merits of a wide range of management objectives.
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INTEGRATING COLLABORATIVE MODELING, STRUCTURED PARTICIPATION AND INTEGRATED WATER RESOURCES MANAGEMENT PLANNING IN PERU: A CASE STUDY OF A NEW WORLD BANK PROJECT by Guillermo Mendoza, Hal Cardwell, Marie-Laure Lajaunie
Although Peru had the world's highest rate of GDP growth in 2008, and continues to be a regional leader in economic growth, most of this growth occurs along the arid Pacific coast which accounts for 1.8% of Peruvian renewable fresh water supply, and where 70% of the population lives. 80% of the total use in this arid area satisfies agriculture, mostly for export. Shortages in water due to inefficient use; competing uses; lack of infrastructure, droughts; and deteriorating water quality due to unregulated effluents from mining, industries, municipalities and uncontrolled use of agrochemicals, is creating increased social conflicts and limiting economic development. In a country where 50% of the population is poor, addressing social conflicts and sustaining economic growth is central to a national strategy for development and for enabling democracy to continue to flourish.
To address increasing conflicts due to water shortages on the arid Pacific coast, Peru is undergoing a fundamental shift in the way water resources are managed. In March 2009, its new water law was passed authorizing the creation of a National Water Authority (ANA) and River Basin Councils (RBC) to implement Integrated Water Resources Management (IWRM) planning at a river basin level. The new law establishes a clear mandate for basin-scale water resources planning, integration of sectoral policies, participation of stakeholders, decentralization of management to the river basin level, and recognition of water as a social and economic good. To support this new national directive, the World Bank and Inter-American Development Bank are providing loans to strengthen ANA at the national level and implement pilots in 6 basins of the arid Peruvian coast, Chancay-Lambayeque, Chili, Ica-Huancavelica, Santa, Tacna-Puno and Chira-Piura River basins.
To execute this effort for participatory IWRM planning at the river basin scale, ANA has been working with the International Center for Integrated Water Resources Management
methodology for Shared Vision Planning, which integrates collaborative modeling, water resources planning, and structured participation. This seminar will share our experiences of this collaborative effort with stakeholders, ANA and the World Bank, provide insight on challenges, current status of this project, and hopefully generate a round of discussion for pragmatic incorporation of shared vision planning in IWRM efforts. This presentation is an ongoing project meant to raise questions and background to for the session of collaborative modeling in IWRM.