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Collaborative Modeling for Decision Support in Water Resources: Principals and Best Practices 1. Context

Water Resources Planning and the Role of Collaborative Modeling

Today, those who support water resources planning and management decision-making processes face conditions of complexity, conflict, and lack of trust. These are not new problems on their own, but they have been exacerbated over the past several decades by increasing demands on the resource, an increased concern for the environment, and an increase in expertise among the public. Guidance provided in past decades such as the Principles and Standards (Water Resources Council, 1973) and the Economic and Environmental Principles and Guidelines for Water and Related Land Resources Implementation Studies (Water Resources Council, 1983) is no longer adequate for either the problems nor planning processes we face today.


Complex, multi-objective problems are not new. However, interest in and understanding of complex hydrologic, ecological, economic, and social processes—their interactions, as well as internal linkages and relationships—have deepened. At the same time, stakeholder expertise and involvement has increased. Thus, most decisions require analysis of complex sets of cause and effect relationships that give rise to multiple outcomes and impacts. Understanding and analyzing outcomes for different alternatives requires multiple professional disciplines as well as an appreciation for the political climate in which planning takes place.


Conflicts over allocation to multiple uses are common in developed watersheds, particularly in areas where populations are increasing, and where greater values have been placed on supporting or improving ecosystems. However, conflict can be over facts, interests, or values, and collaborative modeling serves each type in different ways. Conflict can be over facts (e.g., how a rivers’ flow affects a fish population). Conflict might also arise on questions of what stream flow should be (i.e., conflicting values and interests). Stakeholders may all agree that a certain river flow pattern is good for a non-native recreational fishery but vehemently disagree on whether this species should be in the river in the first place.

Technical analysis is often only partially successful in resolving conflicts. Conflict over facts may or may not be resolvable given project resources and schedules, and their resolution can be hampered if stakeholders doubt the skill or neutrality of the experts involved. Technical studies can provide valuable insight into the trade-offs between objectives and can provide a framework in which values can be incorporated, but they do not address how stakeholders with different values can come to agreements. Today’s analytical and planning strategies need to have both analytical tools (scientific and engineering techniques) and process tools (process design, facilitation and public involvement techniques), as well as a way to link both in order to guide a multi-stakeholder process to a successful conclusion.

Lack of Trust

Communication and personal relationships in public decision-making processes play a vital role in the negotiation process. Getting people with different agendas to work toward a mutually satisfactory outcome is much more difficult in an atmosphere of mistrust. Unfortunately, mistrust and suspicions often exist in many decisions involving water resources. When trust exists among decision participants (even in the face of disagreement or conflict), people will be more honest in revealing what is important to them, more likely to help others meet their goals, and less likely to sabotage a process. If relationships between diverse groups of people can be strengthened during the course of a decision, the resulting outcomes will likely be less costly and more satisfactory to a larger number of people. Anyone leading a project must earn the trust of the stakeholders and create a process that builds trust among them.

Any of these challenges on their own can hinder a water resources decision-making process, and their combination can cause crises. Techniques that address these challenges can help avoid big controversies.

Purposes of Collaborative Modeling

Collaborative modeling is one method that can help to address the modern challenges associated with resource management. Collaborative modeling helps stakeholders with differing perspectives to integrate their interests into the model. The model enables them to see “the problem” from their own perspective as well as from others’ perspectives. The process of working together on a model keeps the focus on “getting the model right” which reduced focus on personal conflicts. The experience helps to reconcile the facts and to clarify assumptions, while building trust in the process. Collaborative modeling helps the participants to build a shared language and to identify and define areas of agreement and disagreement.

Collaborative modeling can be used for many different purposes (Table 1). The most common purpose for water resources problems is to design and recommend a management or operational plan. An example of this is determining how to operate a dam in a way that meets multiple purposes over a range of hydrologic conditions. Collaborative modeling is also an appropriate tool forresearching and analyzing (technical or scientific information) and for clarifying arguments and values among various parties. These two may be end-goals on their own, or intermediate goals on the way to designing a plan. Similarly, the collaborative modeling approach may help to democratize a process or mediate conflict. Frequently, several of these goals are present within one project, to various extents.

Table 1. Range of policy contexts and their applicability of collaborative modeling.

Policy context
(Mayer et al. 2004)

Example application

Applicability of Collaborative Modeling
Research and analysis Is climate changing? Partial
Design and recommendation How should we operate this reservoir system? High
Clarification of arguments and values What drives the deep division between coastal property owners and environmentalists? Partial
Provision of strategic advice What strategic initiative should an individual client pursue? Low
Democratization How can citizens make an informed decision on health care or reservoir management? Partial
Mediation How can disputants deal with conflicting scientific findings on their dispute? Partial


Addressing Challenges through Collaborative Modeling

This document presents Principles and Best Practices to build relationships and trust, foster both shared understanding and shared vision, and expand the array of alternatives to increase the chances of finding appropriate and often hard-fought solutions. These principles are illustrated through vignettes from real cases or projects that vary with respect to their purpose, level of conflict, project type, spatial scale, and number and type of parties involved. The vignettes range from visioning exercises to legally binding planning processes that use models to support decisions. The recommended Best Practices can improve planning and management for situations or planning processes where conflicts are minor or significant. Early application of these practices can help practitioners avoid or minimize conflict, conserve time, money, relationships, and community integrity as well as resources.

Experience suggests that the time and money spent building trust and collaborating will avoid the time and money spent later on additional studies or litigation. Recent American water management history is replete with examples of 20- and 30-year efforts that produced no decision, or one that cannot be implemented. Collaborative processes, including collaborative modeling, can help better identify and address concerns, explore a wide range of options, and create and implement a supportable and lasting solution. Proponents point not only to the decision outcome, but to other benefits such as improved relationships and perceptions of a fairer process. Work has been undertaken to clarify various measures of success (Michaud and Langsdale 2009) that, with future application, can provide quantitative information in support of the qualitative assessments now available.



revised 18 Feb 2011