<p>Planning is what sustains an energy system. It is a process of analysis and ongoing decision making about what resources and energy technologies to use when supplying energy to society. This research focuses on integrated energy systems, i.e. systems that are comprised of several energy carriers – electricity, gas, hot water - and energy distribution networks. The planning of these kinds of systems is a complex process, influenced by many factors, among which the most important are the availability of energy resources and the competition between different energy carriers in satisfying energy demand. During the last 10-20 years significant changes have taken place on the world energy scene, which have important implications for energy planning. Two main factors have triggered these changes. The first factor is the immediate need to address environmental changes or more generally, to take measures that are sustainable in the long run. Sustainability can be defined in many ways and in relation to different issues such as economic and ecologic development, reduction of greenhouse gases, responsible use of natural resources, social equity, etc. In recent years, an increased awareness of these issues has been observed at all levels of the society. The second factor is the deregulation of national energy sectors in more than 50 countries. This process brought changes in the ownership of different parts of the formerly integrated energy systems. New business opportunities were created in power generation, wholesale power/gas trading and energy retailing, while the energy infrastructures remained state owned or/and under regulatory control. The newly created energy markets (many of them international) have attracted both new players (power, oil and gas companies and financial institutions) together with the old ones (integrated utilities). In parallel with this vertical separation of national energy sectors, recent studies have shown a tendency for horizontal integration at the regional/company level. For instance, in order to reduce their overall business risk, companies prefer to participate in several segments of the energy value chain (in both regulated and non-regulated activities), and often across more than one fuel commodity, such as gas and electricity or district heating. In this context, the competition between different energy carriers in satisfying the end-use energy demand became obvious in economic as well as in technological and environmental terms. Traditionally, in integrated planning, this competition did not play a big role, since the same state entity made decisions at both national and regional levels. However, in the post-deregulation era it is no longer obvious who the planner is. In many cases, planning decision at local levels involve at least three main interest groups: energy companies (and/or other investors), the state and the local community. This thesis is motivated by the need to help planners to cope with the changes in concepts and values concerning the planning of local energy supply systems. This thesis has two aims. The first aim is to improve the understanding of what planning of local systems implies and how such a process can be structured. The second aim is to contribute to the development of decision support methodologies and tools that can cope with the needs in planning. For this purpose, the use of energy modelling and Multi- Criteria Decision Analysis has been studied.</p>

Planning is what sustains an energy system. It is a process of analysis and ongoing decision making about what resources and energy technologies to use when supplying energy to society. This research focuses on integrated energy systems, i.e. systems that are comprised of several energy carriers – electricity, gas, hot water - and energy distribution networks. The planning of these kinds of systems is a complex process, influenced by many factors, among which the most important are the availability of energy resources and the competition between different energy carriers in satisfying energy demand. During the last 10-20 years significant changes have taken place on the world energy scene, which have important implications for energy planning. Two main factors have triggered these changes. The first factor is the immediate need to address environmental changes or more generally, to take measures that are sustainable in the long run. Sustainability can be defined in many ways and in relation to different issues such as economic and ecologic development, reduction of greenhouse gases, responsible use of natural resources, social equity, etc. In recent years, an increased awareness of these issues has been observed at all levels of the society. The second factor is the deregulation of national energy sectors in more than 50 countries. This process brought changes in the ownership of different parts of the formerly integrated energy systems. New business opportunities were created in power generation, wholesale power/gas trading and energy retailing, while the energy infrastructures remained state owned or/and under regulatory control. The newly created energy markets (many of them international) have attracted both new players (power, oil and gas companies and financial institutions) together with the old ones (integrated utilities). In parallel with this vertical separation of national energy sectors, recent studies have shown a tendency for horizontal integration at the regional/company level. For instance, in order to reduce their overall business risk, companies prefer to participate in several segments of the energy value chain (in both regulated and non-regulated activities), and often across more than one fuel commodity, such as gas and electricity or district heating. In this context, the competition between different energy carriers in satisfying the end-use energy demand became obvious in economic as well as in technological and environmental terms. Traditionally, in integrated planning, this competition did not play a big role, since the same state entity made decisions at both national and regional levels. However, in the post-deregulation era it is no longer obvious who the planner is. In many cases, planning decision at local levels involve at least three main interest groups: energy companies (and/or other investors), the state and the local community. This thesis is motivated by the need to help planners to cope with the changes in concepts and values concerning the planning of local energy supply systems. This thesis has two aims. The first aim is to improve the understanding of what planning of local systems implies and how such a process can be structured. The second aim is to contribute to the development of decision support methodologies and tools that can cope with the needs in planning. For this purpose, the use of energy modelling and Multi- Criteria Decision Analysis has been studied.

<p>Background and Motivation</p><p>Unlike what is common in Europe and the rest of the world, Norway has traditionally met most of its stationary energy demand (including heating) with electricity, because of abundant access to hydropower. However, after the deregulation of the Norwegian electricity market in the 1990s, the increase in the electricity generation capacity has been less than the load demand increase. This is due to the relatively low electricity prices during the period, together with the fact that Norway’s energy companies no longer have any obligations to meet the load growth. The country’s generation capacity is currently not sufficient to meet demand, and accordingly, Norway is now a net importer of electricity, even in normal hydrological years. The situation has led to an increased focus on alternative energy solutions.</p><p>It has been common that different energy infrastructures – such as electricity, district heating and natural gas networks – have been planned and commissioned by independent companies. However, such an organization of the planning means that synergistic effects of a combined energy system to a large extent are neglected. During the last decades, several traditional electricity companies have started to offer alternative energy carriers to their customers. This has led to a need for a more comprehensive and sophisticated energy-planning process, where the various energy infrastructures are planned in a coordinated way. The use of multi-criteria decision analysis (MCDA) appears to be suited for coordinated planning of energy systems with multiple energy carriers. MCDA is a generic term for different methods that help people make decisions according to their preferences in situations characterized by multiple conflicting criteria.</p><p>The thesis focuses on two important stages of a multi-criteria planning task:</p><p>- The initial structuring and modelling phase</p><p>- The decision-making phase</p><p>The Initial Structuring and Modelling Phase</p><p>It is important to spend sufficient time and resources on the problem definition and structuring, so that all disagreements among the decision-maker(s) (DM(s)) and the analyst regarding the nature of the problem and the desired goals are eliminated. After the problem has been properly identified, the next step of a multi-criteria energy-planning process is the building of an energy system model (impact model). The model is used to calculate the operational attributes necessary for the multi-criteria analysis; in other words, to determine the various alternatives’ performance values for some or all of the criteria being considered. It is important that the model accounts for both the physical characteristics of the energy system components and the complex relationships between the system parameters. However, it is not propitious to choose/build an energy system model with a greater level of detail than needed to achieve the aims of the planning project.</p><p>In my PhD research, I have chosen to use the eTransport model as the energy system model. This model is especially designed for planning of local and regional energy systems, where different energy carriers and technologies are considered simultaneously. However, eTransport can currently provide information only about costs and emissions directly connected to the energy system’s operation. Details about the investment plans’ performance on the remaining criteria must be found from other information sources. Guidelines should be identified regarding the extent to which different aspects should be accounted for, and on the ways these impacts can be assessed for each investment plan under consideration. However, it is important to realize that there is not one solution for how to do this that is valid for all kind of local energy-planning problems. It is therefore necessary for the DM(s) and the analyst to discuss these issues before entering the decision-making phase.</p><p>The Decision-Making Phase</p><p>Two case studies have been undertaken to examine to what extent the use of MCDA is suitable for local energy-planning purposes. In the two case studies, two of the most well-known MCDA methods, the Multi-Attribute Utility Theory (MAUT) and the Analytical Hierarchy Process (AHP), have been tested. Other MCDA methods, such as GP or the outranking methods, could also have been applied. However, I chose to focus on value measurement methods as AHP and MAUT, and have not tested other methods. Accordingly, my research cannot determine if value measurement methods are better suited for energy-planning purposes than GP or outranking methods are.</p><p>Although all MCDA methods are constructed to help DMs explore their ‘true values’ – which theoretically should be the same regardless of the method used to elicit them – our experiments showed that different MCDA methods do not necessarily provide the same results. Some of the differences are caused by the two methods’ different ways of asking questions, as well as the DMs’ inability to express clearly their value judgements by using one or both the methods. In particular, the MAUT preference-elicitation procedure was difficult to understand and accept for DMs without previous experience with the utility concept. An additional explanation of the differences is that the external uncertainties included in the problem formulation are better accounted for in MAUT than in AHP. There are also a number of essential weaknesses in the theoretical foundation of the AHP method that may have influenced the results using that method. However, the AHP method seems to be preferred by DMs, because the method is straightforward and easier to use and understand than the relatively complex MAUT method.</p><p>It was found that the post-interview process is essential for a good decision outcome. For example, the results from the preference aggregation may indicate that according to the DM’s preferences, a modification of one of the alternatives might be propitious. In such cases, it is important to realize that MCDA is an iterative process. The post-interview process also includes presentation and discussion of results with the DMs. Our experiments showed that the DMs might discover inconsistencies in the results; that the results do not reflect the DM’s actual preferences for some reason; or that the results simply do not feel right. In these cases, it is again essential to return to an earlier phase of the MCDA process and conduct a new analysis where these problems or discrepancies are taken into account.</p><p>The results from an MAUT analysis are usually presented to the DMs in the form of expected total utilities given on a scale from zero to one. Expected utilities are convenient for ranking and evaluation of alternatives. However, they do not have any direct physical meaning, which quite obviously is a disadvantage from an application point of view. In order to improve the understanding of the differences between the alternatives, the Equivalent Attribute Technique (EAT) can be applied. EAT was tested in the first of the two case studies. In this case study, the cost criterion was considered important by the DMs, and the utility differences were therefore converted to equivalent cost differences. In the second case study, the preference elicitation interviews showed, quite surprisingly, that cost was not considered among the most important criteria by the DMs, and none of the other attributes were suitable to be used as the equivalent attribute. Therefore, in this case study, the use of EAT could not help the DMs interpreting the differences between the alternatives.</p><p>Summarizing</p><p>For MCDA to be really useful for actual local energy planning, it is necessary to find/design an MCDA method which: (1) is easy to use and has a transparent logic; (2) presents results in a way easily understandable for the DM; (3) is able to elicit and aggregate the DMs' real preferences; and (4) can handle external uncertainties in a consistent way.</p>

Background and Motivation Unlike what is common in Europe and the rest of the world, Norway has traditionally met most of its stationary energy demand (including heating) with electricity, because of abundant access to hydropower. However, after the deregulation of the Norwegian electricity market in the 1990s, the increase in the electricity generation capacity has been less than the load demand increase. This is due to the relatively low electricity prices during the period, together with the fact that Norway’s energy companies no longer have any obligations to meet the load growth. The country’s generation capacity is currently not sufficient to meet demand, and accordingly, Norway is now a net importer of electricity, even in normal hydrological years. The situation has led to an increased focus on alternative energy solutions. It has been common that different energy infrastructures – such as electricity, district heating and natural gas networks – have been planned and commissioned by independent companies. However, such an organization of the planning means that synergistic effects of a combined energy system to a large extent are neglected. During the last decades, several traditional electricity companies have started to offer alternative energy carriers to their customers. This has led to a need for a more comprehensive and sophisticated energy-planning process, where the various energy infrastructures are planned in a coordinated way. The use of multi-criteria decision analysis (MCDA) appears to be suited for coordinated planning of energy systems with multiple energy carriers. MCDA is a generic term for different methods that help people make decisions according to their preferences in situations characterized by multiple conflicting criteria. The thesis focuses on two important stages of a multi-criteria planning task: - The initial structuring and modelling phase - The decision-making phase The Initial Structuring and Modelling Phase It is important to spend sufficient time and resources on the problem definition and structuring, so that all disagreements among the decision-maker(s) (DM(s)) and the analyst regarding the nature of the problem and the desired goals are eliminated. After the problem has been properly identified, the next step of a multi-criteria energy-planning process is the building of an energy system model (impact model). The model is used to calculate the operational attributes necessary for the multi-criteria analysis; in other words, to determine the various alternatives’ performance values for some or all of the criteria being considered. It is important that the model accounts for both the physical characteristics of the energy system components and the complex relationships between the system parameters. However, it is not propitious to choose/build an energy system model with a greater level of detail than needed to achieve the aims of the planning project. In my PhD research, I have chosen to use the eTransport model as the energy system model. This model is especially designed for planning of local and regional energy systems, where different energy carriers and technologies are considered simultaneously. However, eTransport can currently provide information only about costs and emissions directly connected to the energy system’s operation. Details about the investment plans’ performance on the remaining criteria must be found from other information sources. Guidelines should be identified regarding the extent to which different aspects should be accounted for, and on the ways these impacts can be assessed for each investment plan under consideration. However, it is important to realize that there is not one solution for how to do this that is valid for all kind of local energy-planning problems. It is therefore necessary for the DM(s) and the analyst to discuss these issues before entering the decision-making phase. The Decision-Making Phase Two case studies have been undertaken to examine to what extent the use of MCDA is suitable for local energy-planning purposes. In the two case studies, two of the most well-known MCDA methods, the Multi-Attribute Utility Theory (MAUT) and the Analytical Hierarchy Process (AHP), have been tested. Other MCDA methods, such as GP or the outranking methods, could also have been applied. However, I chose to focus on value measurement methods as AHP and MAUT, and have not tested other methods. Accordingly, my research cannot determine if value measurement methods are better suited for energy-planning purposes than GP or outranking methods are. Although all MCDA methods are constructed to help DMs explore their ‘true values’ – which theoretically should be the same regardless of the method used to elicit them – our experiments showed that different MCDA methods do not necessarily provide the same results. Some of the differences are caused by the two methods’ different ways of asking questions, as well as the DMs’ inability to express clearly their value judgements by using one or both the methods. In particular, the MAUT preference-elicitation procedure was difficult to understand and accept for DMs without previous experience with the utility concept. An additional explanation of the differences is that the external uncertainties included in the problem formulation are better accounted for in MAUT than in AHP. There are also a number of essential weaknesses in the theoretical foundation of the AHP method that may have influenced the results using that method. However, the AHP method seems to be preferred by DMs, because the method is straightforward and easier to use and understand than the relatively complex MAUT method. It was found that the post-interview process is essential for a good decision outcome. For example, the results from the preference aggregation may indicate that according to the DM’s preferences, a modification of one of the alternatives might be propitious. In such cases, it is important to realize that MCDA is an iterative process. The post-interview process also includes presentation and discussion of results with the DMs. Our experiments showed that the DMs might discover inconsistencies in the results; that the results do not reflect the DM’s actual preferences for some reason; or that the results simply do not feel right. In these cases, it is again essential to return to an earlier phase of the MCDA process and conduct a new analysis where these problems or discrepancies are taken into account. The results from an MAUT analysis are usually presented to the DMs in the form of expected total utilities given on a scale from zero to one. Expected utilities are convenient for ranking and evaluation of alternatives. However, they do not have any direct physical meaning, which quite obviously is a disadvantage from an application point of view. In order to improve the understanding of the differences between the alternatives, the Equivalent Attribute Technique (EAT) can be applied. EAT was tested in the first of the two case studies. In this case study, the cost criterion was considered important by the DMs, and the utility differences were therefore converted to equivalent cost differences. In the second case study, the preference elicitation interviews showed, quite surprisingly, that cost was not considered among the most important criteria by the DMs, and none of the other attributes were suitable to be used as the equivalent attribute. Therefore, in this case study, the use of EAT could not help the DMs interpreting the differences between the alternatives. Summarizing For MCDA to be really useful for actual local energy planning, it is necessary to find/design an MCDA method which: (1) is easy to use and has a transparent logic; (2) presents results in a way easily understandable for the DM; (3) is able to elicit and aggregate the DMs' real preferences; and (4) can handle external uncertainties in a consistent way.

Transformations of the various agricultural systems have been taking place in the coastal zone of Bangladesh. While some farmers continue to follow traditional practices, in recent years, others have become involved in massive shrimp cultivation, shrimp-rice cultivation, a rice-based improved agricultural system or a shrimp-rice-vegetable integrated system. All these types of agriculture are being practiced under highly vulnerable environmental conditions. The long-term livelihood, food security and adaptation of the coastal people largely depend on the sustainability of these agricultural practices. In this context, assessing the level of sustainability is extremely important and will be essential for developing future policy options in Bangladesh. This study attempts to examine the sustainability of agricultural practices in the coastal region of Bangladesh. A field study was carried out in 2011 in five villages of five upazilas in the mature and active delta areas of the country. The data were collected through in-depth questionnaire surveys, focus groups discussions, field observation, key informants and secondary materials. A comprehensive suite of indicators was developed considering productivity, efficiency, stability, durability, compatibility and equity of the coastal agriculture. The categories and the indicators were weighted using Multi-Criteria Decision Analysis (MCDA) to measure the sustainability level of five study sites. The integrated agricultural system (shrimp-rice-vegetable) of Dumuria appeared to be the most sustainable system among agricultural practices, and other integrated systems (rice-based improved agricultural system) of Kalaroa were also found to show a good level of sustainability. The massive shrimp cultivation system of Shyamnagar and Kaliganj appears to be least sustainable. A traditional agriculture system with some improved methods followed in Bhola Sadar also performed in a satisfactory manner, but there were limitations in terms of its location in the active delta. The level of the sustainability measured in this study allows for a comparison among agricultural practices of the five study sites. The information generated from the study may be used in formulating policies for this part of the country. Measuring agricultural sustainability in this way produces a useful summary of sustainability issues and also provides some vital learning experiences. A holistic and interdisciplinary approach is attempted in this study for assessing and comparing the sustainability level of coastal agricultural systems. It has the potential to become useful as one of the frameworks for sustainability assessment. / Thesis (Master, Environmental Studies) -- Queen's University, 2012-09-28 15:08:18.847

Municipalities increasingly have less financial resources to spend on implementation of transport strategies and plans. This situation is putting pressure on transport professionals to minimize wasteful expenditure on projects that do not deliver high transport service improvements. As such, the need for efficient, pragmatic decision making on policy direction, infrastructure expenditure, or any transport interventions is becoming very critical. Thus, transport professionals are increasingly in need of tools to help them predict with increased accuracy the outcomes of their intended transport interventions. The City of Cape Town has a Bus Rapid Transport system called MyCiTi. Current MyCiTi operations are incurring losses. The service is kept running on the back of subsidies from the federal government. There is a need for rationalization of the system. However, with strained resources, the interventions on the system have to guarantee improvements. Overemphasis on the ability of MyCiTi BRT service to support transportation during the 2010 soccer world cup event heavily influenced the design of the network. As a result, network appraisal is one area that can be done on the system to identify areas of improvement. In this thesis, decision making support will be demonstrated using a network design appraisal process for the MyCiTi BRT system in Cape Town. The existing MyCiTi network will undergo network improvement using heuristic node insertion technique leading to multiple network scenarios in a modeling environment. Agent-Based demand mobility behavior simulation will be used on each of the network scenarios to come up with network performance indicators. These network performance indicators will be used in the multi-criteria decision analysis (MCDA) model to come up with a ranking of the network scenarios and help in deciding on the optimum network improvement intervention. Overall, findings of this research show the importance of weighting of the performance indicators. Where networks that score well in the performance indicator with the high weights also rank high. In conclusion, the study has demonstrated the importance of decision making support in interventions on complex systems like bus systems. Recommendations on the possible avenues of research stemming from this thesis have also been outlined.

The approach to water management worldwide is currently in transition, with a shift from centralised infrastructures to greater consideration of decentralised technologies, such as rainwater harvesting (RWH). Initiated by recognition of drivers, including water demand, increasing risk of ground-water pollution and flooding, the value of RWH is filtering across the academic-policy boundary. However, in Nigeria, implementation of sustainable water management (SWM), such as RWH systems, is inefficient social, environmental and technical barriers, concerns and knowledge gaps exist, which currently restrict its widespread utilisation. This inefficiency contributes to water scarcity, water-borne diseases, and loss of lives and property due to flooding. Meanwhile, several RWH technologies have been developed to improve SWM through both demand and storm-water management. Such technologies involve the use of storage tanks, surface water reservoirs and ground-water recharge pits as storage systems. A framework was developed to assess the significance and extent of water management problems, match the problems with existing RWH-based solutions and develop a robust ready-to-use multi-criteria analysis tool that can quantify the costs and benefits of implementing several RWH-based storage systems. The methodology adopted was the mixed method approach, involving a detailed literature review, followed by a questionnaire survey of 1067 household respondents, 135 Nigerian Architects and Civil Engineers and focus group discussion with Stakeholders. A total of 1042 sets of data were collected through a questionnaire survey and analysed using SPSS, Excel and selected statistical methods to derive weightings of the attributes for the tool. Following this, three case studies were selected to collect data for hydrological modelling using the RainCycle model. From the results it is found that the most important barrier constraining sustainable RWH regime in Ibadan was obsolete and insufficient operational equipment, followed by poor renumeration of water corporation staff and misuse of available funds. In addition, the measure of importance of storage capacity was established, with the highest score of 4.5 which reflects the general inadequacy of storage as a major barrier to the adoption of RWH as a sustainable water management method. Further, respondents’ major health hazards associated with drinking contaminated water was established. A larger proportion (61.2%) of respondents chose prevalence of typhoid fever; some have a prevalence of diarrhea (19.4%), while few of respondents’ water sources is free from water-borne diseases (2.3%). The tool developed is an integrated platform of related evaluation techniques, including Whole Life Cycle Cost Analysis and Multi-Attribute Utility Theory. The tool uses data including cost and quantities of materials for building a RWH storage system and quantifies the cost and benefits of alternative RWH-based systems that can improve project management. This tool is novel, given its integration of the analytical techniques mentioned above and application for selecting the most appropriate RWH-based SWM systems. The implementation of the tool is envisaged to provide an objective platform for the quantification of the costs and benefits of RWH-based systems prior to implementation.

Sustainable transport is now a popular goal of transport planning. As with any aspiration, systems and mechanisms are required to assess and gauge success in achieving this policy goal. There is increasing reliance on sustainable transport indicators as appropriate tools for this purpose. The usefulness and credibility of any indicator-based assessment will undoubtedly depend on the specific indicators utilised. As such, indicators must be selected carefully to maximise their contribution to the sustainable transport decision making process. A review of current applications of sustainable transport indicators has revealed however, that they are typically selected in an ad hoc and arbitrary fashion. Development of a framework that facilitates transparent and systematic indicator selection would therefore represent a significant advance in transport research. In that regard, this thesis presents the Evaluative and Logical Approach to Sustainable Transport Indicator Compilation (ELASTIC), a methodological framework which provides a flexible, participatory and systematic mechanism for identifying and selecting key sustainable transport indicators. The output of ELASTIC is the Transport Sustainability Profile (TSP), a small un-aggregated suite of sustainable transport indicators which together can provide a snapshot of the sustainability of a transport system. Using various multi-criteria and statistical techniques, ELASTIC applies a robust process to evaluate and select indicators based on their analytical soundness and their relevance to key objectives of sustainable transport. A generic and transferable tool, ELASTIC is capable of application at different geographical scales as well as to non-transport sustainability assessment. For the purpose of this research, the framework is demonstrated through application to England, UK where the judgements of relevant Academics and Transport Planners are elicited and entered into the ELASTIC framework to systematically select a subset of 15 indicators from an initial set of 200. By disaggregating the sample of stakeholders into regional groupings, different context-specific suites of indicators for the regional groupings were also derived. The demonstration confirms ELASTIC to be an inclusive and practical approach to compiling a suite of sustainable transport indicators specific to context and which reflects the unique values of key stakeholders.

Uncertainty associated with the potential impact of climate change on supply availability, varied success with demand-side interventions such as water efficiency and changes in priority relating to hydrometric data collection and ownership, have resulted in challenges for water resources system management particularly in data-sparse regions. Consequently, the aim of this thesis is to assess the reliability, resilience and sustainability of water resources systems in both data-rich and data-sparse regions with an emphasis on robust decision-making in data-sparse regions. To achieve this aim, new resilience indicators that capture water resources system failure duration and extent of failure (i.e. failure magnitude) from a social and environmental perspective were developed. These performance indicators enabled a comprehensive assessment of a number of performance enhancing interventions, which resulted in the identification of a set of intervention strategies that showed potential to improve reliability, resilience and sustainability in the case studies examined. Finally, a multi-criteria decision analysis supported trade-off decision making when the reliability, resilience and sustainability indicators were considered in combination. Two case studies were considered in this research: Kingston and St. Andrew in Jamaica and Anyplace in the UK. The Kingston and St. Andrew case study represents the main data-sparse case study where many assumptions were introduced to fill data gaps. The intervention strategy that showed great potential to improve reliability, resilience and sustainability identified from Kingston and St. Andrew water resources assessment was the ‘Site A-east’ desalination scheme. To ameliorate uncertainty and lack of confidence associated with results, a methodology was developed that transformed a key proportion of the Anyplace water resources system from a data-rich environment to a data-sparse environment. The Anyplace water resources system was then assessed in a data-sparse environment and the performance trade-offs of the intervention strategies were analysed using four multi-criteria decision analysis (MCDA) weighting combinations. The MCDA facilitated a robust comparison of the interventions’ performances in the data-rich and data-sparse case studies. Comparisons showed consistency in the performances of the interventions across data-rich and data-sparse hydrological conditions and serve to demonstrate to decision makers a novel approach to addressing uncertainty when many assumptions have been introduced in the water resources management process due to data sparsity.

For many decisions validation of their outcomes is invariably problematic to objectively assess. Therefore to aid analysis and validation of decision outcomes, approaches which provide improved traceability and more semantically meaningful measurements of the decision process are required. Hence, this research investigates traceability, transparency, interactivity and auditability to improve the decision making process. Approaches and evaluation measures are proposed to facilitate a richer decision making experience. Multi-Criteria Decision Analysis (MCDA) seeks to determine the suitability of alternatives of a goal with respect to multiple criteria. A key component of prominent MCDA methods is the concept of pairwise comparison. For a set of elements, pairwise comparison enables an accurate and transparent extraction and codification of a decision maker’s preferences, though facilitating a separation of concerns. From a set of pairwise comparisons, a ranking of the elements under consideration can be calculated. There are scenarios when a set of pairwise comparisons undergo alteration, both for individual and multiple decision makers. A set of measures of compromise are proposed to quantify the alteration that a set of pairwise comparisons undergo in such scenarios. The measures seek to provide a decision maker with meaningful knowledge regarding how their views have altered. A set of pairwise comparisons may be inconsistent. When inconsistency is present it adversely affects a ranking of the elements derived from the comparisons. Moreover inconsistency within pairwise comparisons used for consideration of more than a handful of elements is almost inevitable. Existing approaches that seek to alter a set of comparisons to reduce inconsistency lack traceability, flexibility, and specific consideration of alteration to the judgments in a way that is meaningful to a decision maker. An approach to inconsistency reduction is proposed that seeks to address these issues. For many decisions the opinions of multiple decision makers are utilized, either to avail of their combined expertise or to incorporate conflicting views. Aggregation of multiple decision makers’ pairwise companions seek to combine the views of the group into a single representation of views. An approach to group aggregation of pairwise comparisons is proposed that models compromise between the decision makers, facilitates decision maker constraints, considers inconsistency reduction during aggregation and dynamically incorporates decision maker weights of importance. With internet access becoming widespread being able to garner the views of a large group of decision makers’ views has become feasible. An approach to the aggregation of a large group of decision makers’ preferences is proposed. The approach facilitates understanding regarding both the agreement and conflict within the group during calculation of an overall group consensus. A Multi-Objective Optimisation Decision Software (MOODS) prototype tool has been developed that implements both the new measures of compromise and the proposed approaches to inconsistency reduction and group aggregation.