831 resultados para Hydrologic sciences|Civil engineering|Water Resource Management


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Cover title: Teaching water conservation.

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Half a decade has passed since the objectives and benefits of autonomic computing were stated, yet even the latest system designs and deployments exhibit only limited and isolated elements of autonomic functionality. From an autonomic computing standpoint, all computing systems – old, new or under development – are legacy systems, and will continue to be so for some time to come. In this paper, we propose a generic architecture for developing fully-fledged autonomic systems out of legacy, non-autonomic components, and we investigate how existing technologies can be used to implement this architecture.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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Studies of strategic HRM have dominated HRM research over the last three decades. Focusing on the HRM-organisation performance relationship, researchers take various themes and perspectives in their approach to strategic HRM. Among these themes, two contrasting approaches of strategic HRM continue to flourish: first, the best practice approach suggests that certain HRM practices will have the same effect irrespective of context and, second, the best fit approach suggests that the choice of HRM practices should be designed in accordance with an organisations’ specific context. While there is little consensus on what constitutes strategic HRM, the most common feature agreed in this field is the notion of the strategic integration; aligning HRM practices with organisations’ overall strategic objectives (vertical fit) and with each other (horizontal fit). Utilising the best fit approach as its theoretical framework, this study examines how vertical and horizontal fit is practised in the Indonesian civil service and what factors likely influence the prevalence of vertical and horizontal fit in the Indonesian civil service context. This study is significant for two important reasons. Firstly, the literature suggests that there are limited studies examining the best fit concept in the civil sector despite its implementation in the private sector positively contributing to organisational performance improvement. Secondly, the study provides enlightenment on how the best fit approach could contribute to performance improvement in the Indonesian civil service. This is in line with the fact that negative images of the Indonesian civil service are continuously highlighted although various HRM reform initiatives have been put in place. To achieve the objectives of the study, the qualitative case study approach accompanied by semi-structured interviews was employed involving 53 senior officials and one focus group discussion from eight Indonesian government agencies, consisting of three central agencies mandated to manage human resources, the National Bureaucratic Reform Team and four line agencies from both central and local governments. Thematic analysis was employed for data analyses and NVIVO software was used to manage the data. The study suggests three main findings. First, various HRM initiatives in relation to the HRM reform have been introduced in the Indonesian civil service differentiating them from the old HRM practices. However, the findings indicate that some HRM policies are still contradicting and hinder vertical and horizontal fit. Second, despite the contradictory policies, vertical and horizontal fit can be seen in the line agencies which have been acknowledged as ‘reformed agencies’. This demonstrates that the line agencies play an important role in aligning HRM practices with the line agencies’ goals and objectives and with one another although they are bounded by HRM policies that are unlikely to support the vertical and horizontal fit concept. Third, factors influencing the prevalence of vertical and horizontal fit include knowledge of contemporary HRM in both central agencies and line agencies, commitment from the line agencies’ leaders, devolvement of HRM to the line agencies and the socio-political and economic environments of the Indonesian civil service. The findings of the study raise policy, practical and theoretical implications. In terms of policy implications, the study highlights the importance of fit in HRM policies to support the achievement of the line agencies’ goals. Therefore, when formulating an HRM policy, the central agencies need to ensure that the HRM policy is linked to line agencies’ goals and to other HRM policies. This is to ensure synchronisation among the policies and thus maximising the achievement of the line agencies’ goals. From the practical perspectives, the study highlights important points which can be learned by the central agencies in carrying out their strategic role with regard to the formulation of HRM policies; by the line agencies in maximising the contribution of HRM to the achievement of the goals and objectives of the agencies through the implementation of the best fit concept, and by the leaders of the agencies in providing continuous support to each of the involved parties in the line agencies and involving the HRM department in all agency’s strategic decision-making. In relation to the theoretical implication, it is clear that the best fit approach is not thoroughly applied due to factors discussed previously. However, this does not mean that the best fit concept cannot be implemented. As argued by McCourt & Ramgutty-Wong (2003), instead of adopting the whole concept of best fit, a modulated approach reflecting the best fit concept, such as selecting individual HRM practices and experimenting with devolution, is possible for civil service organisations which still embrace centralised HRM systems. As demonstrated in the findings, some of the line agencies being studied seem to be ready to adopt the best fit approach given that they have knowledge of the best fit concept, strong support from the top leader, less political intervention and less corruption, collusion, and nepotism practices in their HRM practices.

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Global climate change is predicted to have impacts on the frequency and severity of flood events. In this study, output from Global Circulation Models (GCMs) for a range of possible future climate scenarios was used to force hydrologic models for four case study watersheds built using the Soil and Water Assessment Tool (SWAT). GCM output was applied with either the "delta change" method or a bias correction. Potential changes in flood risk are assessed based on modeling results and possible relationships to watershed characteristics. Differences in model outputs when using the two different methods of adjusting GCM output are also compared. Preliminary results indicate that watersheds exhibiting higher proportions of runoff in streamflow are more vulnerable to changes in flood risk. The delta change method appears to be more useful when simulating extreme events as it better preserves daily climate variability as opposed to using bias corrected GCM output.

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Current procedures for flood risk estimation assume flood distributions are stationary over time, meaning annual maximum flood (AMF) series are not affected by climatic variation, land use/land cover (LULC) change, or management practices. Thus, changes in LULC and climate are generally not accounted for in policy and design related to flood risk/control, and historical flood events are deemed representative of future flood risk. These assumptions need to be re-evaluated, however, as climate change and anthropogenic activities have been observed to have large impacts on flood risk in many areas. In particular, understanding the effects of LULC change is essential to the study and understanding of global environmental change and the consequent hydrologic responses. The research presented herein provides possible causation for observed nonstationarity in AMF series with respect to changes in LULC, as well as a means to assess the degree to which future LULC change will impact flood risk. Four watersheds in the Midwest, Northeastern, and Central United States were studied to determine flood risk associated with historical and future projected LULC change. Historical single framed aerial images dating back to the mid-1950s were used along with Geographic Information Systems (GIS) and remote sensing models (SPRING and ERDAS) to create historical land use maps. The Forecasting Scenarios of Future Land Use Change (FORE-SCE) model was applied to generate future LULC maps annually from 2006 to 2100 for the conterminous U.S. based on the four IPCC-SRES future emission scenario conditions. These land use maps were input into previously calibrated Soil and Water Assessment Tool (SWAT) models for two case study watersheds. In order to isolate effects of LULC change, the only variable parameter was the Runoff Curve Number associated with the land use layer. All simulations were run with daily climate data from 1978-1999, consistent with the 'base' model which employed the 1992 NLCD to represent 'current' conditions. Output daily maximum flows were converted to instantaneous AMF series and were subsequently modeled using a Log-Pearson Type 3 (LP3) distribution to evaluate flood risk. Analysis of the progression of LULC change over the historic period and associated SWAT outputs revealed that AMF magnitudes tend to increase over time in response to increasing degrees of urbanization. This is consistent with positive trends in the AMF series identified in previous studies, although there are difficulties identifying correlations between LULC change and identified change points due to large time gaps in the generated historical LULC maps, mainly caused by unavailability of sufficient quality historic aerial imagery. Similarly, increases in the mean and median AMF magnitude were observed in response to future LULC change projections, with the tails of the distributions remaining reasonably constant. FORE-SCE scenario A2 was found to have the most dramatic impact on AMF series, consistent with more extreme projections of population growth, demands for growing energy sources, agricultural land, and urban expansion, while AMF outputs based on scenario B2 showed little changes for the future as the focus is on environmental conservation and regional solutions to environmental issues.

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This research is part of continued efforts to correlate the hydrology of East Fork Poplar Creek (EFPC) and Bear Creek (BC) with the long term distribution of mercury within the overland, subsurface, and river sub-domains. The main objective of this study was to add a sedimentation module (ECO Lab) capable of simulating the reactive transport mercury exchange mechanisms within sediments and porewater throughout the watershed. The enhanced model was then applied to a Total Maximum Daily Load (TMDL) mercury analysis for EFPC. That application used historical precipitation, groundwater levels, river discharges, and mercury concentrations data that were retrieved from government databases and input to the model. The model was executed to reduce computational time, predict flow discharges, total mercury concentration, flow duration and mercury mass rate curves at key monitoring stations under various hydrological and environmental conditions and scenarios. The computational results provided insight on the relationship between discharges and mercury mass rate curves at various stations throughout EFPC, which is important to best understand and support the management mercury contamination and remediation efforts within EFPC.

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Many infrastructure and necessity systems such as electricity and telecommunication in Europe and the Northern America were used to be operated as monopolies, if not state-owned. However, they have now been disintegrated into a group of smaller companies managed by different stakeholders. Railways are no exceptions. Since the early 1980s, there have been reforms in the shape of restructuring of the national railways in different parts of the world. Continuous refinements are still conducted to allow better utilisation of railway resources and quality of service. There has been a growing interest for the industry to understand the impacts of these reforms on the operation efficiency and constraints. A number of post-evaluations have been conducted by analysing the performance of the stakeholders on their profits (Crompton and Jupe 2003), quality of train service (Shaw 2001) and engineering operations (Watson 2001). Results from these studies are valuable for future improvement in the system, followed by a new cycle of post-evaluations. However, direct implementation of these changes is often costly and the consequences take a long period of time (e.g. years) to surface. With the advance of fast computing technologies, computer simulation is a cost-effective means to evaluate a hypothetical change in a system prior to actual implementation. For example, simulation suites have been developed to study a variety of traffic control strategies according to sophisticated models of train dynamics, traction and power systems (Goodman, Siu and Ho 1998, Ho and Yeung 2001). Unfortunately, under the restructured railway environment, it is by no means easy to model the complex behaviour of the stakeholders and the interactions between them. Multi-agent system (MAS) is a recently developed modelling technique which may be useful in assisting the railway industry to conduct simulations on the restructured railway system. In MAS, a real-world entity is modelled as a software agent that is autonomous, reactive to changes, able to initiate proactive actions and social communicative acts. It has been applied in the areas of supply-chain management processes (García-Flores, Wang and Goltz 2000, Jennings et al. 2000a, b) and e-commerce activities (Au, Ngai and Parameswaran 2003, Liu and You 2003), in which the objectives and behaviour of the buyers and sellers are captured by software agents. It is therefore beneficial to investigate the suitability or feasibility of applying agent modelling in railways and the extent to which it might help in developing better resource management strategies. This paper sets out to examine the benefits of using MAS to model the resource management process in railways. Section 2 first describes the business environment after the railway 2 Modelling issues on the railway resource management process using MAS reforms. Then the problems emerge from the restructuring process are identified in section 3. Section 4 describes the realisation of a MAS for railway resource management under the restructured scheme and the feasible studies expected from the model.

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As a result of rapid urbanisation, population growth, changes in lifestyle, pollution and the impacts of climate change, water provision has become a critical challenge for planners and policy-makers. In the wake of increasingly difficult water provision and drought, the notion that freshwater is a finite and vulnerable resource is increasingly being realised. Many city administrations around the world are struggling to provide water security for their residents to maintain lifestyle and economic growth. This chapter reviews the global challenge of providing freshwater to sustain lifestyles and economic growth, and the contributing challenges of climate change, urbanisation, population growth and problems in rainfall distribution. The chapter proceeds to evaluate major alternatives to current water sources such as conservation, recycling and reclamation, and desalination. Integrated water resource management is briefly looked at to explore its role in complementing water provision. A comparative study on alternative resources is undertaken to evaluate their strengths, weaknesses, opportunities and constraints, and the results are discussed.

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Water Sensitive Urban Design (WSUD) practices such as wetlands, bioretention systems and swales are widely implemented in Australia’s urban areas for the mitigation of stormwater pollution and to enhance its reuse potential. In-depth research undertaken has confirmed that these systems do not always perform according to design expectations due to a diversity of reasons. To deliver anticipated benefits, it is critical that they are designed in conformity with catchment and rainfall characteristics and pollutant processes. This in turn entails an in-depth understanding of key pollutant processes. This paper presents the outcomes of extensive research investigations on pollutant characterisation and stormwater pollutant processes on urban catchment surfaces. Outcomes from the research studies revealed the complexities in physical and chemical characteristics of pollutants originating from urban catchments which are strongly influenced by rainfall and catchment characteristics. Based on the research outcomes, recommendations are provided to enhance stormwater treatment performance and to enhance its reuse potential.

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Many of the teaching elements in Civil and Environmental Engineering and Spatial Science/Surveying are strongly related to multidisciplinary real-world situations. Professionals in each discipline commonly work collaboratively, knowing each other’s professional and technical limitations and requirements. Replication of such real-world situations allows students to gain an insight and acquire knowledge of professional practice for both civil engineering and spatial science disciplines. However, replication of an authentic design project is not always possible in a single unit basis where empirical project situations are often created with controlled sets of constraints, inputs and outputs. A cross-disciplinary design-based project that is designed to promote active student learning, engagement and professional integration would be the preferred option. The central aim of this collaborative project was to create positive and inclusive environments to promote engaging learning opportunities that cater for a range of learning styles with a two-way linkage involving third-year civil engineering and spatial science (surveying) students. This paper describes the cross-disciplinary project developed and delivered in 2010 and 2011. A survey was conducted at completion of the project to assess the degree of improvement in student engagement and their learning experiences. Improvements were assessed in a range of dimensions including student motivation, learning by cross-disciplinary collaboration and learning by authentic design project experiences. In this specific cross-disciplinary linkage project, the study findings showed that teaching approaches utilised have been effective in promoting active student learning and increasing engagement.

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Carbon taxation governance is becoming increasingly popular, further evolving the polluter pays concept already well established in the built environment as a mechanism to controlling and licensing waste generation. This paper presents an explanation of property asset ‘regeneration reuse’ principles following deconstruction, which reduce waste generation associated with the process of demolition, construction and operation. An analysis is made of strategies in Australia and the United Kingdom, comparing jurisdiction targets pertaining to construction and demolition waste that encourage ‘regeneration reuse’. From examination of applicable Australian and United Kingdom legislation, strategic, fiscal and policy that influence on the 'regeneration reuse' of property assets, an evaluation to the variety of issues relevant to waste and resource management practices is reached. The paper concludes that a systematic evaluation framework to selecting building components and structures suitable for reuse after deconstruction must be considered in legislation.

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Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.