Robust optimization to secure urban bulk water supply against extreme drought and uncertain climate change

Urban bulk water systems supply water with high reliability and, in the event of extreme drought, must avoid catastrophic economic and social collapse. In view of the deep uncertainty about future climate change, it is vital that robust solutions be found that secure urban bulk water systems against extreme drought. To tackle this challenge an approach was developed integrating: 1) a stochastic model of multi-site streamflow conditioned on future climate change scenarios; 2) Monte Carlo simulation of the urban bulk water system incorporated into a robust optimization framework and solved using a multi-objective evolutionary algorithm; and 3) a comprehensive decision space including operating rules, investment in new sources and source substitution and a drought contingency plan with multiple actions with increasingly severe economic and social impact. A case study demonstrated the feasibility of this approach for a complex urban bulk water supply system. The primary objective was to minimize the expected present worth cost arising from infrastructure investment, system operation and the social cost of “normal” and emergency restrictions. By introducing a second objective which minimizes either the difference in present worth cost between the driest and wettest future climate change scenarios or the present worth cost for driest climate scenario, the trade-off between efficiency and robustness was identified. The results show that a significant change in investment and operating strategy can occur when the decision maker expresses a stronger preference for robustness and that this depends on the adopted robustness measure. Moreover, solutions are not only impacted by the degree of uncertainty about future climate change but also by the stress imposed on the system and the range of available options.     

An interdisciplinary modelling framework for selecting adaptation measures at the river basin scale in a global change scenario

Shaping global change adaptation strategy in water resource systems requires an interdisciplinary approach to deal with the multiple dimensions of the problem. The modelling framework presented integrates climate, economic, agronomic and hydrological scenarios to design a programme of adaptation measures at the river basin scale. Future demand scenarios, combined with a down-scaled climate scenario, provide the basis to estimate the demand and water resources in 2030. A least-cost river basin optimisation model is then applied to select adaptation measures ensuring that environmental and supply management goals are achieved. In the Orb river basin (France), the least-cost portfolio selected suggests mixing demand and supply side measures to adapt to global change. Trade-offs among the cost of the programme of measures, the deficit in agricultural water supply and the level of environmental flows are investigated. The challenges to implement such interdisciplinary approaches in the definition of adaptation strategies are finally discussed.     

Modeling climate change uncertainties in water resources management models

The impact of climate change on hydrologic design and management of hydrosystems could be one of the important challenges faced by future practicing hydrologists and water resources managers. Many water resources managers currently rely on the historical hydrological data and adaptive real-time operations without consideration of the impact of climate change on major inputs influencing the behavior of hydrologic systems and the operating rules. Issues such as risk, reliability and robustness of water resources systems under different climate change scenarios were addressed in the past. However, water resources management with the decision maker’s preferences attached to climate change has never been dealt with. This short paper discusses issues related to impacts of climate change on water resources management and application of a soft-computing approach, fuzzy set theory, for climate-sensitive management of hydrosystems. A real-life case study example is presented to illustrate the applicability of a soft-computing approach for handling the decision maker’s preferences in accepting or rejecting the magnitude and direction of climate change.     

Climate and human development impacts on municipal water demand: A spatially-explicit global modeling framework

Municipal water systems provide crucial services for human well-being, and will undergo a major transformation this century following global technological, socioeconomic and environmental changes. Future demand scenarios integrating these drivers over multi-decadal planning horizons are needed to develop effective adaptation strategies. This paper presents a new long-term scenario modeling framework that projects future daily municipal water demand at a 1/8° global spatial resolution. The methodology incorporates improved representations of important demand drivers such as urbanization and climate change. The framework is applied across multiple future socioeconomic and climate scenarios to explore municipal water demand uncertainties over the 21st century. The scenario analysis reveals that achieving a low-carbon development pathway can potentially reduce global municipal water demands in 2060 by 2–4%, although the timing and scale of impacts vary significantly with geographic location.     

Analysis of ALOS PALSAR InSAR data for mapping water level changes in Yellow River Delta wetlands

Wetlands play a key role in regional and global environments and are critically linked to many major issues such as climate change, water quality, hydrological and carbon cycles, and wildlife habitat and biodiversity. It is very important to measure water level changes and consequently water storage capacity changes in wetlands to enable wetland protection and reconstruction. In this study, HH polarization L-band synthetic aperture radar (SAR) data were used in conjunction with synchronous field measurements and investigations to investigate the potential to detect water level changes under different types of wetlands. After evaluating factors that influence interferometric coherence, the framework for measuring water level changes using interferometric synthetic aperture radar (InSAR) phase information is presented in this article. Additionally, the SAR data obtained are used to investigate InSAR-derived water level changes in Yellow River Delta wetlands. The results show that InSAR technology has great potential for application in mapping water level changes in coastal wetlands, and InSAR-derived water level changes can supply unprecedented spatial details.     

A multi-scale urban integrated assessment framework for climate change studies: A flooding application

In order to assess the potential future impacts of climate change on urban areas, tools to assist decision-makers to understand future patterns of risk are required. This paper presents a modelling framework to allow the downscaling of national- and regional-scale population and employment projections to local scale land-use changes, providing scenarios of future socio-economic change. A coupled spatial interaction population model and cellular automata land development model produces future urbanisation maps based on planning policy scenarios. The framework is demonstrated on Greater London, UK, with a set of future population and land-use scenarios being tested against flood risk under climate change. The framework is developed in Python using open-source databases and is designed to be transferable to other cities worldwide.     

Adaptive Executions of Multi-Physics Coupled Applications on Batch Grids

Long running multi-physics coupled parallel applications have gained prominence in recent years. The high computational requirements and long durations of simulations of these applications necessitate the use of multiple systems of a Grid for execution. In this paper, we have built an adaptive middleware framework for execution of long running multi-physics coupled applications across multiple batch systems of a Grid. Our framework, apart from coordinating the executions of the component jobs of an application on different batch systems, also automatically resubmits the jobs multiple times to the batch queues to continue and sustain long running executions. As the set of active batch systems available for execution changes, our framework performs migration and rescheduling of components using a robust rescheduling decision algorithm. We have used our framework for improving the application throughput of a foremost long running multi-component application for climate modeling, the Community Climate System Model (CCSM). Our real multi-site experiments with CCSM indicate that Grid executions can lead to improved application throughput for climate models.     

Supply chain ontology: Review, analysis and synthesis

In an environment where supply chains compete against supply chains, information sharing among supply chain partners using information systems is a competitive tool. Supply chain ontology has been proposed as an important medium for attaining information systems interoperability. Ontology has its origin in philosophy, and the computing community has adopted ontology in its language. This paper presents a study of state of the art research in supply chain ontology and identifies the outstanding research gaps. Six supply chain ontology models were identified from a systematic review of literature. A seven point comparison framework was developed to consider the underlying concepts as well as application of the ontology models. The comparison results were then synthesised into nine gaps to inform future supply chain ontology research. This work is a rigorous and systematic attempt to identify and synthesise the research in supply chain ontology.     

Reliable water supply system design under uncertainty

Given the natural variability and uncertainties in long-term predictions, reliability is a critical design factor for water supply systems. However, the large scale of the problem and the correlated nature of the involved uncertainties result in models that are often intractable. In this paper, we consider a municipal water supply system over a 15-year planning period with initial infrastructure and possibility of construction and expansion during the first and sixth year on the planning horizon. Correlated uncertainties in water demand and supply are applied on the form of the robust optimization approach of Bertsimas and Sim to design a reliable water supply system. Robust optimization aims to find a solution that remains feasible under data uncertainty. Such a system can be too conservative and costly. In the Bertsimas and Sim approach, it is possible to vary the degree of conservatism to allow for a decision maker to understand the tradeoff between system reliability and economic feasibility/cost. The degree of conservatism is incorporated in the probability bound for constraint violation. As a result, the total cost increases as the degree of conservatism (and reliability) is increased. In the water supply system application, a tradeoff exists between the level of conservatism and imported water purchase. It was found that the robust optimization approach addresses parameter uncertainty without excessively affecting the system. While we applied our methodology to hypothetical conditions, extensions to real-world systems with similar structure are straightforward. Therefore, our study shows that this approach is a useful tool in water supply system design that prevents system failure at a certain level of risk.     

MASCF: A generic process-centered methodological framework for analysis and design of multi-agent supply chain systems

Multi-agent systems (MAS) are becoming popular for modeling complex systems such as supply chains. However, development of multi-agent systems remain quite involved and extremely time consuming. Currently, there exist no generic methodologies for modeling supply chains using multi-agent systems. In this research, we propose a generic process-centered methodological framework, Multi-Agent Supply Chain Framework (MASCF), to simplify MAS development for supply chain (SC) applications. MASCF introduces the notion of process-centered organization metaphor, and creatively adopts Supply Chain Operations Reference (SCOR) model to a well-structured generic MAS analysis and design methodology, Gaia, for multi-agent supply chain system (MASCS) development. The popular Tamagotchi case was designed and analyzed using MASCF. The validity of the framework was established by implementing MASCF output of Tamagotchi SC using the Java Agent DEvelopment Framework (JADE).     

Coordination and control for energy distribution in distributed grid networks: Theory and application to power dispatch problem

This paper presents a new framework considering decentralized energy coordination and generation, and flow control for supply–demand balance in distributed grid networks. Consensus schemes using only local information are employed to produce energy coordination, generation, and flow control signals. For the supply–demand balance, it is required to determine the amount of energy needed at each distributed resource. Also, due to the different generation capacities of each energy resource, coordination of energy flows among distributed energy resources is essentially required. Thus, this paper proposes a new framework which gives decentralized energy coordination scheme, generation, and flow control method considering these constraints based on distributed consensus algorithms. The proposed framework in this paper can be nicely utilized in energy dispatch or energy flow scheduling. Furthermore, it can be applied to various engineering problems including water irrigation systems, traffic networks, and building automation systems since it deals with attributed distribution and resource allocation in large scale distributed systems. Through illustrative examples, the effectiveness of the proposed approaches is illustrated. A possible application to power dispatch problem in the IEEE-14bus is also addressed for more detailed and realistic evaluation.     

A web-based tool for the development of Intensity Duration Frequency curves under changing climate

Intensity Duration Frequency (IDF) curves are among the most common tools used in water resources management. They are derived from historical rainfall records under the assumption of stationarity. Change of climatic conditions makes the use of historical data for development of IDFs for the future unjustifiable. The IDF_CC, a web based tool, is designed, developed and implemented to allow local water professionals to quickly develop estimates related to the impact of climate change on IDF curves for almost any local rain monitoring station in Canada. The primary objective of the presented work was to standardize the IDF update process and make the results of current research on climate change impacts on IDF curves accessible to everyone. The tool is developed in the form of a decision support system (DSS) and represents an important step in increasing the capacity of Canadian water professionals to respond to the impacts of climate change.     

IRA-WDS: A GIS-based risk analysis tool for water distribution systems

This paper presents the development of a new software tool IRA-WDS. This GIS-based software predicts the risks associated with contaminated water entering water distribution systems from surrounding foul water bodies such as sewers, drains and ditches. Intermittent water distribution systems are common in developing countries and these systems are prone to contamination when empty. During the non-supply hours contaminants from pollution sources such as sewers, open drains and surface water bodies enter into the water distribution pipes through leaks and cracks. Currently there are no tools available to help engineers identify the risks associated with contaminant intrusion into intermittent water distribution systems. Hence it is anticipated that IRA-WDS will find wide application in developing countries. The paper summarises the details of the mathematical models that form the basis of IRA-WDS. It also describes the software architecture, the main modules, and the integration with GIS using a tight coupling approach. A powerful GUI has been developed that enables data for the models to be retrieved from the spatial databases and the outputs to be converted into tables and thematic maps. This is achieved seamlessly through DLL calling functions within the GIS. This paper demonstrates the application of the software to a real case study in India. The outputs from IRA-WDS are risk maps showing the risk of contaminant intrusion into various parts of the water distribution system. The outputs also give an understanding of the main factors that contribute to the risk.     

An integrated assessment approach to conduct analyses of climate change impacts on whole-farm systems

This paper argues that an integrated assessment (IA) approach, combining simulation modelling with deliberative processes involving decision makers and other stakeholders, has the potential to generate credible and relevant assessments of climate change impacts on farming systems. The justification for the approach proposed is that while simulation modelling provides an effective way of exploring the range of possible impacts of climate change and a means of testing the consequences of possible management or policy interventions, the interpretation of the outputs is highly dependent on the point of view of the stakeholder. Inevitably, whatever the responses to climate change, there will be trade-offs between the benefits and costs to a range of stakeholders. The use of a deliberative process that includes stakeholders, both in defining the topics addressed and in debating the interpretations of the outcomes, addresses many of the limitations that have been previously identified in the use of computer-based tools for agricultural decision support. The paper further argues that the concepts of resilience and adaptive capacity are useful for the assessment of climate change impacts as they provide an underpinning theory for processes of change in land use systems. The integrated modelling framework (IMF) developed for the simulation of whole-farm systems is detailed, including components for crop and soil processes, livestock systems and a tool for scheduling of resource use within management plans. The use of the IMF for assessing climate change impacts is then outlined to demonstrate the range of analyses possible. The paper concludes with a critique of the IA approach and notes that issues of quantification and communication of uncertainty are central to the success of the methodology.     

Impact of climate change on sea level rise in Lagos,Nigeria

Sea level rise and ocean surge are the major potential impacts of climate change in the rapidly growing urban Lagos in Nigeria. Coastal inundation is, however, expected to increase problems of flooding and intrusion of sea water into freshwater sources and ecosystems, thereby heightening the social conflict already prevalent in this area. This article examines the historical trend in the coastal extent of one of the most populous coastal cities in the tropics and projects the potential impact on coastline change using geographic information system (GIS) techniques coupled with scenario-based climate change predictions from three different general circulation models (GCMs). This study aims, therefore, to provide empirical reasoning for the development of sea defence policies which would help in the reduction of possible loss of life or capital asset damage by suggesting adequate and cost-effective flood warning systems as well as by discouraging inappropriate infrastructural development in areas at risk from flooding and coastal erosion.     

Standard Principles for Installing a Social Media Control Framework for Supply Chain Risk Management

The use of social media platforms for inter-company employee interactions of suppliers and acquirers in the supply chain is an effective and efficient tool. The social media application related to Supply Chain Risk Management (SCRM) has potential risks with the transmission of proprietary information between organizations. Currently there are not published recommendations for Social Media Supply Chain Risk Management (SM-SCRM). The paper takes the first step in providing a risk management framework for organizations to implement inter-communication access controls within the supply chain based on NIST IR 7622 Notional Supply Chain Risk Management for employee interaction.     

Development of an oil palm cropping systems model: Lessons learned and future directions

Oil palm has become one of the most important crops in the world with questions being raised about its economic and environmental sustainability. Agricultural systems models are regularly employed in studying sustainable crop management but no detailed model is currently available for oil palm systems.We developed a production systems model for oil palm within the Agricultural Production Systems Simulator (APSIM) framework and tested it using data across a range of environments within Papua New Guinea (PNG). The model captured key growth responses to climate and management. This demonstrates that modern modelling frameworks do allow for rapid model development for new agricultural systems.However, whilst application of the model is promising, the availability of key data is likely to restrict its use. Local soil and weather data are not available in adequate detail for many of the major oil palm production areas, although some methods exist to address this.     

A biophysical and economic model of agriculture and water in the Murray-Darling Basin,Australia

Economic analysis of climate scenarios and alternative water policies is critical for development and implementation of appropriate water policies and programs. Mathematical models have been developed to assess water resources policies due to their ability to explicitly represent the biophysical dynamics of natural systems while integrating these within social and economic constraints. These models have been criticised, however, due to the problems of simplification, overspecialisation, plausibility and lack of empirical validation. This paper introduces a mathematical programming model which uses positive mathematical programming method to calibrate and model agriculture and water use in the Murray-Darling Basin of Australia. This paper reviews the theoretical and technical details of the model development including the key steps taken in collating and scaling the biophysical and economic data, and to address model parameterisation issues. The paper summarises results of an application of the model for assessing climate change impacts in the form of reduced rainfall and water allocations and increased crop water use for agricultural production. The results show the degree of variability in gross values under different climate scenarios compared to the base case scenario, especially in very dry years. The results also show how on-farm adaptation options and water markets can mitigate these losses.     

Development and application of a geospatial wildfire exposure and risk calculation tool

Applying wildfire risk assessment models can inform investments in loss mitigation and landscape restoration, and can be used to monitor spatiotemporal trends in risk. Assessing wildfire risk entails the integration of fire modeling outputs, maps of highly valued resources and assets (HVRAs), characterization of fire effects, and articulation of relative importance across HVRAs. Quantifying and geo-processing wildfire risk can be a complex and time-intensive task, often requiring expertise in geospatial analysis. Researchers and land managers alike would benefit from a standardized and streamlined ability to estimate wildfire risk. In this paper we present the development and application of a geospatial wildfire risk calculation tool, FireNVC. We describe the major components of the tool and how they align with a geospatial wildfire risk assessment framework, detail a recent application of the tool to inform federal wildfire management and planning, and offer suggestions for future improvements and uses of the tool.     

The Climate for Transformation: Lessons for Leaders

This article reports insights for organizational leaders based on a series of case studies describing the use of the Situational Outlook Questionnaire as a tool to assist them with their transformation efforts. Leaders often assert the need to change their organizational cultures. This article seeks to clarify and differentiate culture from climate, and then focus on what leaders can do to transform their climate by applying a deliberate assessment tool. As the case studies illustrate, making organizational transformation happen is best approached through a systemic or ecological approach. This approach includes considering the people involved, the methods deployed, the desired outcome of the change as well as the context within which the transformation occurs. The broadest concept within this framework is context, which includes both culture and climate, among other things. Since context is key to initiating and sustaining transformation, emphasis on the leader's role in climate creation will be provided.