Evaluating the Outcomes of Collaborative Modeling for Decision Support

Does collaborative modeling improve water resource management outcomes? How does collaborative modeling improve these outcomes? Does it always work? Under what conditions is collaborative modeling most appropriate? With support from the U.S. Army Corps of Engineers' Institute for Water Resources (IWR), researchers developed an evaluation framework to help address these questions. The framework links the effects of collaborative modeling on decision‐making processes with improvements in the extent to which resource management decisions, practices, and policies balance societal needs. Both practitioners' and participants' experiences suggest that under the right circumstances, collaborative modeling can generate these beneficial outcomes. Researchers developed performance measures and a survey to systematically capture these experiences and evaluate the outcomes of collaborative modeling processes. The survey 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 resource management decisions.     

Developing a New Operations Plan for the Bow River Basin Using Collaborative Modeling for Decision Support

The Bow River Basin is a cornerstone of Alberta's development. In 2010, stakeholders representing interests from agriculture, municipalities, environment, and more formed the Bow River Project Research Consortium to help determine the potential for improving the operations in the basin. At present, upstream reservoirs are operated primarily for hydropower, whereas downstream reservoirs are operated for irrigation. Through Collaborative Modeling for Decision Support the stakeholders were able to develop a new method for operating the system that would dramatically improve environmental performance. The main components of the new operating strategy called for: purchase or setting aside of a small amount of storage volume in the power reservoirs; a set of rules for releases from that storage; an agreement by the major irrigation districts with the largest water licenses to utilize their ability to shift deliveries to and from their large offstream storage reservoirs to allow for increased instream flows, and to allow junior water license holders (mainly municipal and industrial supplies) an uninterrupted water supply; limitations of reservoir fluctuations to improve inreservoir habitat for fisheries; and increased minimum flows throughout the system leading to improved environmental outcomes. Costs of this strategy were minimal, impacts on power revenue were estimated at <US$2 million/yr on average. Compensatory arrangements should be possible.     

Collaborative Modeling for Decision Support in Water Resources: Principles and Best Practices

Collaborative Modeling for Decision Support integrates collaborative modeling with participatory processes to inform natural resources decisions. Practitioners and advocates claim that the approach will lead to better water management, balancing interests more effectively and reducing 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 an effective collaborative modeling process, a task committee cosponsored by the Environmental Water Resources Institute (EWRI) of the American Society of Civil Engineers and by the U.S. Army Corps of Engineers' Institute for 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. Here, the set of eight principles is presented along with a selection of associated best practices, illustrated by two different case examples. The complete document is available at: http://www.computeraideddisputeresolution.us/bestpractices/ .     

Streamflow Depletion Modeling: Methods for an Adaptable and Conjunctive Water Management Decision Support Tool

Groundwater pumping depletes streamflow, which can have significant ecological impacts depending on the magnitude of depletion relative to environmental flow needs. Streamflow depletion estimates from groundwater pumping have been quantified using both analytical and numerical methods, but are not routinely compared to environmental flow needs or used in practical water management tools. Decision support tools that incorporate groundwater dynamics are becoming increasingly necessary for water managers as groundwater regulations become more important in environmental policy, particularly concerning the preservation of environmental flow needs. We develop and apply methods for a web‐based decision support tool for conjunctive groundwater and surface water management, demonstrated using a case study watershed in British Columbia, Canada. Open‐source data are analyzed with a combination of spatial algorithms and previously developed analytical models, such that the tool can be applied to other regions. Streamflow depletion estimates are calculated in four regions in the largely undeveloped Bulkley Valley, British Columbia. Our transparent methodology has geographic and data input flexibility which is a significant improvement on currently existing water management tool methods.     

Sustainability Criteria for Decision Support in the UK Water Industry

The incorporation of sustainability assessment into decision-making processes is a key task for water service providers in the UK and elsewhere. This paper describes the development and application of a set of sustainability criteria, which have been developed and tested with project partners in the UK and Romania. They will be used in a 'guidebook' that will set out a framework to facilitate the inclusion of sustainability in the decision-making process. This work is part of the Sustainable Water Industry Asset Resource Decisions project to develop a multi-criteria analysis decision support system to assist water service providers to assess the relative sustainability of water/wastewater system asset development decisions.     

Land Resource Sustainability for Urban Development: Spatial Decision Support System Prototype

Land resource sustainability for urban development characterizes the problem of decision-making with multiplicity and uncertainty. A decision support system prototype aids in the assessment of incremental land development plan proposals put forth within the long-term community priority of a sustainable growth. Facilitating this assessment is the analytic hierarchy process (AHP), a multicriteria evaluation and decision support system. The decision support system incorporates multiple sustainability criteria, weighted strategically responsive to local public policy priorities and community–specific situations and values, while gauging and directing desirable future courses of development. Furthermore, the decision support system uses a GIS, which facilitates an assessment of urban form with multiple indicators of sustainability as spatial criteria thematically. The resultant land-use sustainability scores indicate, on the ratio-scale of AHP, whether or not a desirable urban form is likely in the long run, and if so, to what degree. The two alternative modes of synthesis in AHP—ideal and distributive—provide assessments of a land development plan incrementally (short-term) and city-wide pattern comprehensively (long-term), respectively. Thus, the spatial decision support system facilitates proactive and collective public policy determination of land resource for future sustainable urban development.     

A Decision Support Framework for Science-Based, Multi-Stakeholder Deliberation: A Coral Reef Example

We present a decision support framework for science-based assessment and multi-stakeholder deliberation. The framework consists of two parts: a DPSIR (Drivers–Pressures–States–Impacts–Responses) analysis to identify the important causal relationships among anthropogenic environmental stressors, processes, and outcomes; and a Decision Landscape analysis to depict the legal, social, and institutional dimensions of environmental decisions. The Decision Landscape incorporates interactions among government agencies, regulated businesses, non-government organizations, and other stakeholders. It also identifies where scientific information regarding environmental processes is collected and transmitted to improve knowledge about elements of the DPSIR and to improve the scientific basis for decisions. Our application of the decision support framework to coral reef protection and restoration in the Florida Keys focusing on anthropogenic stressors, such as wastewater, proved to be successful and offered several insights. Using information from a management plan, it was possible to capture the current state of the science with a DPSIR analysis as well as important decision options, decision makers and applicable laws with a the Decision Landscape analysis. A structured elicitation of values and beliefs conducted at a coral reef management workshop held in Key West, Florida provided a diversity of opinion and also indicated a prioritization of several environmental stressors affecting coral reef health. The integrated DPSIR/Decision landscape framework for the Florida Keys developed based on the elicited opinion and the DPSIR analysis can be used to inform management decisions, to reveal the role that further scientific information and research might play to populate the framework, and to facilitate better-informed agreement among participants.     

Identifying Opportunities for Decision Support Systems in Support of Regional Resource Use Planning: An Approach Through Soft Systems Methodology

/ Regional resource use planning relies on key regional stakeholder groups using and having equitable access to appropriate social, economic, and environmental information and assessment tools. Decision support systems (DSS) can improve stakeholder access to such information and analysis tools. Regional resource use planning, however, is a complex process involving multiple issues, multiple assessment criteria, multiple stakeholders, and multiple values. There is a need for an approach to DSS development that can assist in understanding and modeling complex problem situations in regional resource use so that areas where DSSs could provide effective support can be identified, and the user requirements can be well established. This paper presents an approach based on the soft systems methodology for identifying DSS opportunities for regional resource use planning, taking the Central Highlands Region of Queensland, Australia, as a case study.     

Decision Support for Road System Analysis and Modification on the Tahoe National Forest

The United States Forest Service is required to analyze road systems on each of the national forests for potential environmental impacts. We have developed a novel and inexpensive way to do this using the Ecosystem Management Decision Support program (EMDS). We used EMDS to integrate a user-developed fuzzy logic knowledge base with a grid-based geographic information system to evaluate the degree of truth for assertions about a roads environmental impact. Using spatial data for natural and human processes in the Tahoc National Forest (TNF, California, USA), we evaluated the assertion the road has a high potential for impacting the environment. We found a high level of agreement between the products of this evaluation and ground observations of a TNF transportation engineer, as well as occurrences of road failures. We used the modeled potential environmental impact to negatively weight roads for a least-cost path network analysis to 1573 points of interest in the forest. The network analysis showed that out of 8233 km of road analyzed in the forest, 3483 km (42%) must be kept in a modified road network to ensure access to these points. We found that the modified network had improved patch characteristics, such as significantly fewer cherry stem roads intruding into patches, an improved area-weighted mean shape index, and larger mean patch sizes, as compared to the original network. This analysis system could be used by any public agency to analyze infrastructure for environmental or other risk and included in other mandated analyses such as risks to watersheds.     

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.     

Forest Naturalness: Criterion for Decision Support in Designation and Management of Protected Forest Areas

The article analyses the possibilities of developing an integrated indicator and a model of the assessment of forests naturalness using the data from the database of mountainous spruce forests situated in the Western Carpathians of Slovakia. The article presents two variants of such a model, one based on discriminant analysis, while the second one using an additive approach. The analysis of the data from mountainous spruce forests revealed significant indicators of forest naturalness degree: the arithmetic mean of the ratio between crown length and tree height, the deadwood volume, the coverage of grasses, the coverage of mosses and lichens, and the aggregation index. In addition, the coefficient of variation of tree diameters was included in the final model, since its presence in the model had a positive influence on the correctness of the classification of the forest naturalness degree. The correctness of the classification of the proposed discriminant model was 74.5%. For the additive model, the ranges of the values of the integrated indicator were defined for every degree of forest naturalness by taking into account the error ranges of the arithmetic mean values and the percentiles of the values in individual degrees of forest naturalness. The overall correctness of the classification with the additive model was 63.4%. In the second step, the scheme how to apply the classification model of the forest naturalness degree in the decision-making process of designating as a forest protected areas was proposed. In this scheme, the degree of forest naturalness is considered as a basic criterion for the determination of nature-conservation value of forest ecosystems. As further decision-making criteria we identified the possibility to restore, or the possibility to improve the naturalness of less natural forest ecosystems, which are designated as protected; the occurrence of the endangered species; and the occurrence of other natural values.     

Benefits of Collaborative Learning for Environmental Management: Applying the Integrated Systems for Knowledge Management Approach to Support Animal Pest Control

Resource management issues continually change over time in response to coevolving social, economic, and ecological systems. Under these conditions adaptive management, or “learning by doing,” offers an opportunity for more proactive and collaborative approaches to resolving environmental problems. In turn, this will require the implementation of learning-based extension approaches alongside more traditional linear technology transfer approaches within the area of environmental extension. In this paper the Integrated Systems for Knowledge Management (ISKM) approach is presented to illustrate how such learning-based approaches can be used to help communities develop, apply, and refine technical information within a larger context of shared understanding. To outline how this works in practice, we use a case study involving pest management. Particular attention is paid to the issues that emerge as a result of multiple stakeholder involvement within environmental problem situations. Finally, the potential role of the Internet in supporting and disseminating the experience gained through ongoing adaptive management processes is examined.     

A Hierarchical Fuzzy Decision Support System for the Environmental Rehabilitation of Lake Koronia,Greece

This article presents the design of a fuzzy decision support system (DSS) for the assessment of alternative strategies proposed for the restoration of Lake Koronia, Greece. Fuzzy estimates for the critical characteristics of the possible strategies, such as feasibility, environmental impact, implementation time, and costs are evaluated and supplied to the fuzzy DSS. Different weighting factors are assigned to the critical characteristics and the proposed strategies are ordered with respect to the system responses. The best strategies are selected and their expected impact on the ecosystem is evaluated with the aid of a fuzzy model of the lake. Sensitivity analysis and simulation results have shown that the proposed fuzzy DSS can serve as a valuable tool for the selection and evaluation of appropriate management actions. Note: This version was published online in June 2005 with the cover date of August 2004.     

Decision Support for Mitigating the Risk of Tree Induced Transmission Line Failure in Utility Rights-of-Way

Vegetation management is a critical component of rights-of-way (ROW) maintenance for preventing electrical outages and safety hazards resulting from tree contact with conductors during storms. Northeast Utility’s (NU) transmission lines are a critical element of the nation’s power grid; NU is therefore under scrutiny from federal agencies charged with protecting the electrical transmission infrastructure of the United States. We developed a decision support system to focus right-of-way maintenance and minimize the potential for a tree fall episode that disables transmission capacity across the state of Connecticut. We used field data on tree characteristics to develop a system for identifying hazard trees (HTs) in the field using limited equipment to manage Connecticut power line ROW. Results from this study indicated that the tree height-to-diameter ratio, total tree height, and live crown ratio were the key characteristics that differentiated potential risk trees (danger trees) from trees with a high probability of tree fall (HTs). Products from this research can be transferred to adaptive right-of-way management, and the methods we used have great potential for future application to other regions of the United States and elsewhere where tree failure can disrupt electrical power.     

Local IWRM organizations for groundwater regulation: The experiences of the Aquifer Management Councils (COTAS) in Guanajuato, Mexico

Evidence of groundwater management by aquifer users emerging under Integrated Water Resources Management (IWRM) initiatives is presented, by analyzing the Consejos Técnicos de Aguas (COTAS; Technical Water Councils or Aquifer Management Councils) in the state of Guanajuato, Mexico, established between 1998 and 2000 by the Guanajuato State Water Commission (CEAG). Two contrasting models influenced this attempt to promote user self-regulation of groundwater extractions: locally autonomous aquifer organizations with powers to regulate groundwater extractions versus aquifer organizations with advisory powers only. The COTAS were conceived as locally autonomous IWRM organizations consisting of all aquifer users that would work together to reduce groundwater over-extraction and stabilize aquifer levels, at a later stage. CEAG followed an expedient IWRM approach to develop the COTAS, setting achievable targets for their development and explicitly focusing on active stakeholder participation. The article shows that, due to struggles between the state and federal levels, the COTAS have become advisory bodies that have not led to reductions in groundwater extractions. It concludes that achieving user self-regulation of groundwater extractions requires a fuller delegation of responsibilities to the COTAS which would not be possible without addressing the institutional struggles over water governance at the state and federal levels.     

Development of a Decision Support System for Assessing Farm Animal Welfare in Relation to Husbandry Systems: Strategy and Prototype

Due to increasing empiricalinformation on farm animal welfare since the1960s, the prospects for sound decisionmakingconcerning welfare have improved. This paperdescribes a strategy to develop adecision-making aid, a decision support system,for assessment of farm-animal welfare based onavailable scientific knowledge. Such a decisionsupport system allows many factors to be takeninto account. It is to be developed accordingto the Evolutionary Prototyping Method, inwhich an initial prototype is improved inreiterative updating cycles. This initialprototype has been constructed. It useshierarchical representations to analysescientific statements and statements describingthe housing system. Welfare is assessed fromwhat is known about the biological needs of theanimals, using a welfare model in the form of atree that contains these needs as welfarecomponents. Each state of need is assessedusing welfare relevant attributes of thehousing system and weighting factors.Attributes are measurable properties of thehousing system. Weighting factors are assignedaccording to heuristic rules based on theprinciple of weighting all components(attributes and needs) equally, unless thereare strong reasons to do otherwise. Preliminarytests of the prototype indicate that it may bepossible to perform assessment of farm-animalwelfare in an explicit way and based onempirical findings. The procedure needs to berefined, but its prospects are promising.     

Degradation Model: A Quantitative EIA Instrument,Acting as a Decision Support System (DSS) for Environmental Management

Environmental assessment of alternative development plans, programs, and policies may bring conflict among decision-makers, particularly when some quantitative measures for decision-making are needed and where cumulative impacts are neglected. Environmental impact assessment (EIA) and environmental economics theories, despite their usefulness, are not capable of addressing those issues and problems alone. In recent years, the decision support system (DSS) has provided some solutions, but mathematical analysis of the system to show the internal structure of the problem is not always possible. To addres the above shortcomings and ongoing problems of decision-making in Iran, a degradation model (DM) was introduced as an instrument of EIA, to act as a DSS for managers. The model is a compromise between knowledge-based decision support systems, detailed models, digested information models, and the basic theorem of environmental economics. In the present study (1996–2000), the model was applied in three provinces of Iran, representing three of four biogeographical regions of Iran. The study area was divided into a set of grids (100 km²). The degradation coefficient (H) was computed for all grids (1333), representing the degree of degradation in the grid. It is obvious that the higher the coefficient the more area is degraded and less prone to further development, and vice versa. In order to provide decision-makers with a set of quantitative measures to observe impacted areas (critical and noncritical) for resource allocation and further development, the degradation coefficients of all grids were classified into categories and criteria, using a fuzzy set theoretic approach. Accordingly, only 24% of study areas are prone to further development. The degradation model as a knowledge-based decision support system has its strengths and weaknesses, but it has solved managers' ongoing problems in Iran and it could be used elsewhere.     

Modeling Nitrate-Nitrogen Load Reduction Strategies for the Des Moines River,Iowa Using SWAT

The Des Moines River that drains a watershed of 16,175 km² in portions of Iowa and Minnesota is impaired for nitrate-nitrogen (nitrate) due to concentrations that exceed regulatory limits for public water supplies. The Soil Water Assessment Tool (SWAT) model was used to model streamflow and nitrate loads and evaluate a suite of basin-wide changes and targeting configurations to potentially reduce nitrate loads in the river. The SWAT model comprised 173 subbasins and 2,516 hydrologic response units and included point and nonpoint nitrogen sources. The model was calibrated for an 11-year period and three basin-wide and four targeting strategies were evaluated. Results indicated that nonpoint sources accounted for 95% of the total nitrate export. Reduction in fertilizer applications from 170 to 50 kg/ha achieved the 38% reduction in nitrate loads, exceeding the 34% reduction required. In terms of targeting, the most efficient load reductions occurred when fertilizer applications were reduced in subbasins nearest the watershed outlet. The greatest load reduction for the area of land treated was associated with reducing loads from 55 subbasins with the highest nitrate loads, achieving a 14% reduction in nitrate loads achieved by reducing applications on 30% of the land area. SWAT model results provide much needed guidance on how to begin implementing load reduction strategies most efficiently in the Des Moines River watershed.