Modelling asset management of railway overhead line equipment

The overhead line equipment (OLE) is a critical sub-system of the 25kV AC overhead railway electrification system. There is a need to evaluate OLE asset management strategies through a whole life cost analysis that considers degradation processes and maintenance activities of the OLE components so that the investment required to deliver the level of performance desired by railway customers and regulators can be based on evidence from modelling results. A Petri Net model is proposed to simulate the degradation, failure, inspection and maintenance of the main OLE components and to calculate various statistics associated with the cost and reliability of the system over its whole life. The Petri Net considers all the main OLE components in one model and can simulate both fixed interval and risk based maintenance regimes. To allow such processes to be modelled accurately and efficiently, High Level Petri Net features are used. The model developed is the first of its kind, in such detail, for OLE and the applicability of Petri Nets for modelling many processes on a large system, containing numerous components, is shown

Improving bank erosion modelling at catchment scale by incorporating temporal and spatial variability

Bank erosion can contribute a significant portion of the sediment budget within temperate catchments, yet few catchment scale models include an explicit representation of bank erosion processes. Furthermore, representation is often simplistic resulting in an inability to capture realistic spatial and temporal variability in simulated bank erosion. In this study, the sediment component of the catchment scale model SHETRAN is developed to incorporate key factors influencing the spatio-temporal rate of bank erosion, due to the effects of channel sinuosity and channel bank vegetation. The model is applied to the Eden catchment, north-west England, and validated using data derived from a GIS methodology. The developed model simulates magnitudes of total catchment annual bank erosion (617 - 4063 t yr-1) within the range of observed values (211 - 4426 t yr-1). Additionally the model provides both greater inter-annual and spatial variability of bank eroded sediment generation when compared with the basic model, and indicates a potential 61% increase of bank eroded sediment as a result of temporal flood clustering. The approach developed within this study can be used within a number of distributed hydrologic models and has general applicability to temperate catchments, yet further development of model representation of bank erosion processes is required

A stochastic rainfall model for the assessment of regional water resource systems under changed climatic condition

International audienceA stochastic model is developed for the synthesis of daily precipitation using conditioning by weather types. Daily precipitation statistics at multiple sites within the region of Yorkshire, UK, are linked to objective Lamb weather types (LWTs) and used to split the region into three distinct precipitation sub-regions. Using a variance minimisation criterion, the 27 LWTs are clustered into three physically realistic groups or ?states'. A semi-Markov chain model is used to synthesise long sequences of weather states, maintaining the observed persistence and transition probabilities. The Neyman-Scott Rectangular Pulses (NSRP) model is then fitted for each weather state, using a defined summer and winter period. The combined model reproduces key aspects of the historic precipitation regime at temporal resolutions down to the hourly level. Long synthetic precipitation series are useful in the sensitivity analysis of water resource systems under current and changed climatic conditions. This methodology enables investigation of the impact of variations in weather type persistence or frequency. In addition, rainfall model statistics can be altered to simulate instances of increased intensity or proportion of dry days for example, for individual weather groups. The input of such data into a water resource model, simulating potential atmospheric circulation changes, will provide a valuable tool for future planning of water resource systems. The ability of the model to operate at an hourly level also allows its use in a wider range of hydrological impact studies, e.g. variations in river flows, flood risk estimation etc. Keywords: water resources; climate change; impacts; stochastic rainfall model; Lamb weather types</p

Quantifying and Mitigating Wind‐Induced Undercatch in Rainfall Measurements

Despite the apparent simplicity, it is notoriously difficult to measure rainfall accurately because of the challenging environment within which it is measured. Systematic bias caused by wind is inherent in rainfall measurement and introduces an inconvenient unknown into hydrological science that is generally ignored. This paper examines the role of rain gauge shape and mounting height on catch efficiency (CE), where CE is defined as the ratio between nonreference and reference rainfall measurements. Using a pit gauge as a reference, we have demonstrated that rainfall measurements from an exposed upland site, recorded by an adjacent conventional cylinder rain gauge mounted at 0.5 m, were underestimated by more than 23% on average. At an exposed lowland site, with lower wind speeds on average, the equivalent mean undercatch was 9.4% for an equivalent gauge pairing. An improved-aerodynamic gauge shape enhanced CE when compared to a conventional cylinder gauge shape. For an improved-aerodynamic gauge mounted at 0.5 m above the ground, the mean undercatch was 11.2% at the upland site and 3.4% at the lowland site. The mounting height of a rain gauge above the ground also affected CE due to the vertical wind gradient near to the ground. Identical rain gauges mounted at 0.5 and 1.5 m were compared at an upland site, resulting in a mean undercatch of 11.2% and 17.5%, respectively. By selecting three large rainfall events and splitting them into shorter-duration intervals, a relationship explaining 81% of the variance was established between CE and wind speed

emerging perspectives for flood risk assessment and management

Flood estimation and flood management have traditionally been the domain of hydrologists, water resources engineers and statisticians, and disciplinary approaches abound. Dominant views have been shaped; one example is the catchment perspective: floods are formed and influenced by the interaction of local, catchment-specific characteristics, such as meteorology, topography and geology. These traditional views have been beneficial, but they have a narrow framing. In this paper we contrast traditional views with broader perspectives that are emerging from an improved understanding of the climatic context of floods. We come to the following conclusions: (1) extending the traditional system boundaries (local catchment, recent decades, hydrological/hydraulic processes) opens up exciting possibilities for better understanding and improved tools for flood risk assessment and management. (2) Statistical approaches in flood estimation need to be complemented by the search for the causal mechanisms and dominant processes in the atmosphere, catchment and river system that leave their fingerprints on flood characteristics. (3) Natural climate variability leads to time-varying flood characteristics, and this variation may be partially quantifiable and predictable, with the perspective of dynamic, climate-informed flood risk management. (4) Efforts are needed to fully account for factors that contribute to changes in all three risk components (hazard, exposure, vulnerability) and to better understand the interactions between society and floods. (5) Given the global scale and societal importance, we call for the organization of an international multidisciplinary collaboration and data-sharing initiative to further understand the links between climate and flooding and to advance flood research

Floods and climate: emerging perspectives for flood risk assessment and management

Flood estimation and flood management have traditionally been the domain of hydrologists, water resources engineers and statisticians, and disciplinary approaches abound. Dominant views have been shaped; one example is the catchment perspective: floods are formed and influenced by the interaction of local, catchment-specific characteristics, such as meteorology, topography and geology. These traditional views have been beneficial, but they have a narrow framing. In this paper we contrast traditional views with broader perspectives that are emerging from an improved understanding of the climatic context of floods. We come to the following conclusions: (1) extending the traditional system boundaries (local catchment, recent decades, hydrological/hydraulic processes) opens up exciting possibilities for better understanding and improved tools for flood risk assessment and management. (2) Statistical approaches in flood estimation need to be complemented by the search for the causal mechanisms and dominant processes in the atmosphere, catchment and river system that leave their fingerprints on flood characteristics. (3) Natural climate variability leads to time-varying flood characteristics, and this variation may be partially quantifiable and predictable, with the perspective of dynamic, climate-informed flood risk management. (4) Efforts are needed to fully account for factors that contribute to changes in all three risk components (hazard, exposure, vulnerability) and to better understand the interactions between society and floods. (5) Given the global scale and societal importance, we call for the organization of an international multidisciplinary collaboration and data-sharing initiative to further understand the links between climate and flooding and to advance flood research

Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management

Improving Supervisor Evaluations Through the Use of Self Determination Contracts

Supervisor perceptions of employee competence in areas of work, social, and personal demands of the job often determine success or failure for the supported employee. This study involved three workers with disabilities who participated in a supported employment program. After being successfully hired in a job of their choosing, problems arose that jeopardized the successful completion of the placement phase. The workers used individualized self-determination contracts to improve supervisor evaluations. Specifically, they completed daily self-determination contracts to plan their work outcomes, manage their tasks, evaluate their performance, and make adjustments for their next opportunity to work. Results indicated that all three workers used self-determination strategies to improve their performance and meet the expectations of their respective employers.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline