A decision model for selecting sustainable drinking water supply and greywater reuse systems for developing communities with a case study in Cimahi, Indonesia

Capacity Factor Analysis is a decision support system for selection of appropriate technologies for municipal sanitation services in developing communities. Developing communities are those that lack the capability to provide adequate access to one or more essential services, such as water and sanitation, to their residents. This research developed two elements of Capacity Factor Analysis: a capacity factor based classification for technologies using requirements analysis, and a matching policy for choosing technology options. First, requirements analysis is used to develop a ranking for drinking water supply and greywater reuse technologies. Second, using the Capacity Factor Analysis approach, a matching policy is developed to guide decision makers in selecting the appropriate drinking water supply or greywater reuse technology option for their community. Finally, a scenario-based informal hypothesis test is developed to assist in qualitative model validation through case study. Capacity Factor Analysis is then applied in Cimahi Indonesia as a form of validation. The completed Capacity Factor Analysis model will allow developing communities to select drinking water supply and greywater reuse systems that are safe, affordable, able to be built and managed by the community using local resources, and are amenable to expansion as the community's management capacity increases.     

Consideration of User Needs and Spatial Accuracy in Drought Mapping1

Abstract: The increasing availability of web mapping tools creates new opportunities to bridge decision‐makers’ climate information needs with technical capabilities. These new tools, however, raise familiar, unresolved issues related to cartographic representation. Using an on‐line drought mapping tool, this study seeks to understand which spatial unit best meets the desire drought managers have for “local” information, their comprehension of uncertainties introduced in mapping information at local scales, and their willingness to trade off accuracy for information at a desired unit. We found that the most useful local map information includes regional context and boundaries which present their local area of interest. Even among this experienced, well‐educated, professional group, those who had not taken a GIS or cartography class did not fully recognize the role of interpolation in creating and introducing uncertainty to some drought maps. Those who did recognize the uncertainty introduced by interpolation still strongly favored maps that provided estimated values for all areas vs. station point accuracy. Mapping poses a unique set of challenges to communicating risk and uncertainty. As more decision‐support efforts incorporate web mapping, greater attention is needed to assure that users understand the tradeoffs between accuracy and precision in creating local information, the imprecision of boundaries, as well as the limits of forecasts. Clearly conveying spatial accuracy and uncertainty is a challenge that merits greater attention in using maps to communicate drought and other environmental risk information.     

Integrating the AHP and TOPSIS decision processes for evaluating the optimal collection strategy in reverse logistic for the TPI

This study presents processes to evaluate the optimal collecting strategy (CS) in reverse logistic (RL) for the downstream part of the Taiwan photovoltaic industry (TPI). It combines the analytic hierarchy process (AHP) with the technique for ordering preference by similarity to the ideal solution (TOPSIS). The criteria and sub-criteria were initially established to assess the related benefits, opportunities, costs, and risks (BOCR). AHP was then used to obtain the weightings of the criteria and sub-criteria and TOPSIS was used to rank the optimal collection strategy in terms of its overall evaluation criteria. The AHP and TOPSIS method provides decision makers with a valuable reference for assessing the optimal collection strategy of TPI downstream. The results of the study should provide decision makers in the downstream TPI with academic support and valuable guidance for evaluating their collection program and obtain optimal strategies for administering RL practices.     

Buying price of event information in two-action decision problems

Being able to determine in advance whether certain events occur or not enables a decision maker to reduce the uncertainty of a two-action lottery, although the exact outcome of the lottery may still not be known with certainty. This paper studies the á priori value of information in such a decision making environment. Of interest to the decision maker is to compare the value of information about different events in advance of gathering the information. Using buying price as value of information, we show that when information about the occurrence of two different events are offered to a risk neutral decision maker, the event with a greater contribution in absolute value to the expected value of the lottery has higher value in terms of its buying price. For risk averse decision makers, a preference condition needs to be imposed on the set difference of two events to obtain a generic conclusion. We provide several examples that demonstrate the usefulness of these results.     

Feasibility versus sustainability in urban water management

Decision making in urban water management is exemplified by the case of Austria: Although researchers define a comprehensible concept of sustainability, practitioners emphasize feasibility and accept limitations in sustainability. Could the specification of particular methods, chosen from some decision support methodology, remedy this situation? While an integrative assessment of sustainability should not be based on prescribed or standardized criteria, or even a certain assessment method, it should force the decision makers to make their chosen premise more visible. To this end a change of the decision making process is proposed, which will allow the decision makers to adapt the decision making process to the circumstances of a specific project in a way that is accepted by the stakeholders.     

Mining and social development: Refocusing community investment using multi-criteria decision analysis

This paper addresses the question: How can mining companies assess social investment projects so that projects create value for the company and communities in which they operate? Mining companies are still wrestling with the limits of their responsibility in relation to social development even though they accept the business case for community investment at a general level. Fully aware of the practical hazards involved in taking an active role in facilitating local development, companies increasingly avoid methods that are overly paternalistic or assume the functions of the national or local governments. Gaining senior management's commitment to long-term social projects, which are characterised by uncertainty and complexity, is made easier if projects are shown to benefit the site's strategic goals. Case study research on large global mining companies, including interviews with social investment decision makers, has assisted in developing a Social Investment Decision Analysis Tool (SIDAT), a decision model for evaluating social projects. Multi-criteria decision analysis techniques integrating business planning processes with social impact assessment have proved useful in assisting mining companies think beyond seeking reputational benefits, to how they can meet their business goals and contribute to sustainable development.     

Towards the ecotourism: A decision support model for the assessment of sustainability of mountain huts in the Alps

This paper studies mountain hut infrastructure in the Alps as an important element of ecotourism in the Alpine region. To improve the decision-making process regarding the implementation of future infrastructure and improvement of existing infrastructure in the vulnerable natural environment of mountain ecosystems, a new decision support model has been developed. The methodology is based on qualitative multi-attribute modelling supported by the DEXi software. The integrated rule-based model is hierarchical and consists of two submodels that cover the infrastructure of the mountain huts and that of the huts’ surroundings. The final goal for the designed tool is to help minimize the ecological footprint of tourists in environmentally sensitive and undeveloped mountain areas and contribute to mountain ecotourism. The model has been tested in the case study of four mountain huts in Triglav National Park in Slovenia. Study findings provide a new empirical approach to evaluating existing mountain infrastructure and predicting improvements for the future. The assessment results are of particular interest for decision makers in protected areas, such as Alpine national parks managers and administrators. In a way, this model proposes an approach to the management assessment of mountain huts with the main aim of increasing the quality of life of mountain environment visitors as well as the satisfaction of tourists who may eventually become ecotourists.     

Hierarchical modeling of seed variety yields and decision making for future planting plans

Eradicating hunger and malnutrition is a key development goal of the twenty first century. This paper addresses the problem of optimally identifying seed varieties to reliably increase crop yield within a risk-sensitive decision making framework. Specifically, a novel hierarchical machine learning mechanism for predicting crop yield (the yield of different seed varieties of the same crop) is introduced. This prediction mechanism is then integrated with a weather forecasting model and three different approaches for decision making under uncertainty to select seed varieties for planting so as to balance yield maximization and risk. The model was applied to the problem of soybean variety selection given in the 2016 Syngenta Crop Challenge. The prediction model achieved a median absolute error of 235 kg/ha and thus provides good estimates for input into the decision models. The decision models identified the selection of soybean varieties that appropriately balance yield and risk as a function of the farmer’s risk aversion level. More generally, the models can support farmers in decision making about which seed varieties to plant.     

THE CHANGING DECISION RULES IN THE POLITICS OF WATER DEVELOPMENT1

A set of decision rules have governed the traditional politics of water development. This paper identifies these rules, describes their operation, and explains the logic behind their adoption. Personal interviews with a large number of decision makers are cited to substantiate and illustrate particular rules. There are five decision rules: local support, agreement, mutual accommodation, mutual noninterference, and fairness and equity. These guidelines are intended to insure support, lessen conflict, and protect the reputation of water development as a worthwhile federal investment. Since there are current indications that the traditional decision rules are no longer followed, the paper aims to identify why and how the rules are changing.     

Focusing biodiversity research on the needs of decision makers

The project on Biodiversity Uncertainties and Research Needs (BURN) ensures the advancement of usable knowledge on biodiversity by obtaining input from decision makers on their priority information needs about biodiversity and then using this input to engage leading scientists in designing policy-relevant research. Decision makers articulated concerns related to four issues: significance of biodiversity; status and trends of biodiversity; management for biodiversity; and the linkage of social, cultural, economic, legal, and biological objectives. Leading natural and social scientists then identified the research required to address the decision makers' needs and determined the probability of success. The diverse group of experts reached consensus on several fundamental issues, helping to clarify the role of biodiversity in land and resource management. The BURN participants identified several features that should be incorporated into policy-relevant research plans and management strategies for biodiversity. Research and assessment efforts should be: multidisciplinary and integrative, participatory with stakeholder involvement, hierarchical (multiple scales), and problem- and region-specific. The activities should be focused regionally within a global perspective. Meta-analysis of existing data is needed on all fronts to assess the state of the science. More specifically, the scientists recommended six priority research areas that should be pursued to address the information needs articulated by decision makers: (1) characterization of biodiversity, (2) environmental valuation, (3) management for sustainability—for humans and the environment (adaptive management), (4) information management strategies, (5) governance and stewardship issues, and (6) communication and outreach. Broad recommendations were developed for each research area to provide direction for research planning and resource management strategies. The results will directly benefit those groups that require biodiversity research to address their needs—whether to develop policy, manage natural resources, or make other decisions affecting biodiversity.     

Estimating the value of foresight: aggregate analysis of natural hazard mitigation benefits and costs

Hazard mitigation planners claim that foresighted present actions and investments produce significant future benefits. However, they have difficulty in supporting their claims, since previously their evidence typically was derived from individual case studies. Constituents and decision makers are often sceptical, believing that individual cases are either inapplicable to their situation or non-randomly selected to support a particular view. Planners need objective evidence based on a large body of experience to support the case for mitigation. Such is the unique contribution of a recent U.S. study that found that each dollar spent in three federal natural hazard mitigation grant programs (the Hazard Mitigation Grant Program, Project Impact, and the Flood Mitigation Assistance Program) saves society an average of $4 in future avoided losses. Complementing the aggregate benefit-cost analysis with community-based evaluations, the study yielded insights on how planners can improve long-term community resilience in the face of extreme events. Valuable lessons for mitigation planners and policy makers emerged: the need to consider a wide variety of losses, the importance of mixing qualitative with quantitative analysis, the value of averaging results over a large number of projects, and the need to more explicitly address social issues and data collection in order to reduce vulnerability and enhance resilience to cope with twenty-first century hazards.     

Informing the development of decision support tools for risk management: the case of electrical and magnetic fields

This paper describes tools developed through a community consultative process to help decision makers manage electrical and magnetic fields (EMF) health risk. The process involved in‐depth interviews with experts (N=12) and focus group discussions with seven different stakeholder groups. The results reveal commonly held intense public concerns about the long‐term health effects of EMF. These concerns were further reinforced by the lack of public trust in both government and industry with regards to EMF risk management. Overall, the participants wanted tools that can be used to manage EMF information, scientific uncertainty about EMF and the complex environment in which EMF issues are embedded. The findings contributed to a mapping out of response formats to address public concerns related to risk, hazard, trust, accountability and fairness across a range of stakeholder groups. These tools and their roles in the management of complex and variable risks, involving new circumstances (e.g. privatization) and information (e.g. new scientific studies) are presented. The importance of recognizing and working with uncertainty through adaptive management strategies, using qualitative approaches, is also discussed.     

DEVELOPING AND IMPLEMENTING DECISION SUPPORT SYSTEMS: A CRITIQUE AND A CHALLENGE1

ABSTRACT: Computer-based models together with their interactive interfaces are typically called decision support systems. DSSs are interactive computer-based information providers. The common objective of all DSSs, regardless of the frameworks, methodologies, or techniques used, is to provide timely information that supports human decision makers - at whatever level of decision making. The informational needs of the decision making process are the key considerations that motivate the development of DSSs. The growth of DSS development and use has been substantial. In spite of this impressive growth, computer-aided decision support systems can still be improved and made more useful to those they are intended to support. Researchers and practitioners, and indeed the computer industry, continue to identify ways of doing this. This paper reviews some of these needs and opportunities by focusing on the process of successful DDS development and implementation. The paper outlines an approach and some guidelines for developing DSSs. The approach emphasizes and requires considerable interaction between the DSS developers (analysts) and the DSS users (decision makers). This interaction and feedback is required throughout the entire DSS building, testing and evaluation (debugging), and implementation processes. The paper concludes by identifying some research needs and opportunities affecting DSS development and effective use.     

Design and evaluation of a local analytic-deliberative process for climate adaptation planning

In the midst of rapidly proliferating engagement efforts around climate adaptation, attention to the design and evaluation of decision support processes and products is warranted. We report on the development and evaluation of a process framework called the Vulnerability, Consequences, and Adaptation Planning Scenarios (VCAPS) process. VCAPS is a systematic approach to integrate local knowledge with scientific understanding by providing opportunities for facilitated, deliberative learning-based activities with local decision makers about climate change vulnerability and adaptation. We introduce the conceptual basis of the process in analytic-deliberation, hazard management, and vulnerability. Our evaluations from eight coastal communities where the approach was applied point to four assets of VCAPS: it promotes synthesis of local and scientific knowledge; it stimulates systems thinking and learning; it facilitates governance by producing action plans with transparent justifications; and it accommodates participant time constraints and preferences.     

An Evaluation of Multiple Objective Decision Support Weighting Techniques in Natural Resource Management

Multiple objective decision support (MODS) is a structured framework for evaluating decision alternatives against multiple, and often conflicting, criteria. Its ability to handle complex trade-offs in a variety of quantitative and qualitative units gives it much potential in the field of natural resource management (NRM). A key component of MODS is the process used to obtain information from decision makers on the relative importance of evaluative criteria. Ranking algorithms then use this information to determine the relative value of each decision alternative. This paper explores how practising community based NRM decision makers respond to five generic methods for weighting the criteria. It presents a study in which 55 decision makers throughout five regions in Queensland, Australia, applied MODS to evaluate environmental projects seeking funding under the Australian Natural Heritage Trust. Weighting methods applied include fixed point scoring, rating, ordinal ranking, a graphical method and paired comparisons. Decision makers evaluated each weighting method in terms of ease of use and of how much it helped clarify the decision problem. Results show that decision makers felt uncomfortable applying fixed point scoring and generally preferred to express their preferences through ordinal ranking. This has implications for the types of ranking algorithms that can be applied to evaluate the decision alternatives.     

Finding Common Ground: How Advocacy Coalitions Succeed in Protecting Environmental Flows1

Abstract: This paper reviews several recent case studies in which states or countries have strengthened their protection of environmental flows to explore the key policy, stakeholder, and scientific elements that contributed to these advances in water management. A conceptual framework is developed to describe the actions of interest groups and individuals, how environmental flow issues get onto the formal agenda of decision makers, the events and conditions which precipitate this attention, the role of science and scientific uncertainty, and how interactions and dialog among individuals and groups with different interests lead to changes in state and national statutes. In general, the review found that changing policies is a result of actions of informed groups of interested parties using science and information to inform both the public and decision makers about the need for action and about the specific action needed. In almost all cases, environmental flow issues make it onto the formal agenda of institutions through one or more precipitating events, often legal challenges that call into question the existing legal framework for water management. Significantly, in almost all cases the engagement between advocacy coalitions with different and often opposing views results in reframing the issues to provide a common approach or solution upon which the competing coalitions can agree.     

A fuzzy knowledge-based decision support system for groundwater pollution risk evaluation

In this paper we propose a decision support system that can provide information on the environmental impact of anthropic activities by examining their effects on groundwater quality. We use the combined value of both intrinsic vulnerability of a specific local aquifer, obtained by implementing a parametric managerial model (SINTACS), and a degree of hazard value, which takes into account specific human activities. Incomplete information is notoriously common in environmental planning. To overcome this deficiency we apply an algorithmic and a qualitative approach, based on expert judgment incorporated into the system's knowledge base. The decision support system takes into account the uncertainty of the environmental domain by using fuzzy logic and evaluates the reliability of the results according to information availability.     

A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making

The choice among alternative water supply sources is generally based on the fundamental objective of maximising the ratio of benefits to costs. There is, however, a need to consider sustainability, the environment and social implications in regional water resources planning, in addition to economics. In order to achieve this, multi-criteria decision analysis (MCDA) techniques can be used. Various sources of uncertainty exist in the application of MCDA methods, including the selection of the MCDA method, elicitation of criteria weights and assignment of criteria performance values. The focus of this paper is on the uncertainty in the criteria weights. Sensitivity analysis can be used to analyse the effects of uncertainties associated with the criteria weights. Two existing sensitivity methods are described in this paper and a new distance-based approach is proposed which overcomes limitations of these methods. The benefits of the proposed approach are the concurrent alteration of the criteria weights, the applicability of the method to a range of MCDA techniques and the identification of the most critical criteria weights. The existing and proposed methods are applied to three case studies and the results indicate that simultaneous consideration of the uncertainty in the criteria weights should be an integral part of the decision making process.     

Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk

In the Wasatch Range Metropolitan Area of Northern Utah, water management decision makers confront multiple forms of uncertainty and risk. Adapting to these uncertainties and risks is critical for maintaining the long‐term sustainability of the region's water supply. This study draws on interview data to assess the major challenges climatic and social changes pose to Utah's water future, as well as potential solutions. The study identifies the water management adaptation decision‐making space shaped by the interacting institutional, social, economic, political, and biophysical processes that enable and constrain sustainable water management. The study finds water managers and other water actors see challenges related to reallocating water, including equitable water transfers and stakeholder cooperation, addressing population growth, and locating additional water supplies, as more problematic than the challenges posed by climate change. Furthermore, there is significant disagreement between water actors over how to best adapt to both climatic and social changes. This study concludes with a discussion of the path dependencies that present challenges to adaptive water management decision making, as well as opportunities for the pursuit of a new water management paradigm based on soft‐path solutions. Such knowledge is useful for understanding the institutional and social adaptations needed for water management to successfully address future uncertainties and risks.