How Will Hydroelectric Power Generation Develop under Climate Change Scenarios?

Climate change has a large impact on water resources and thus on hydropower. Hydroelectric power generation is closely linked to the regional hydrological situation of a watershed and reacts sensitively to changes in water quantity and seasonality. The development of hydroelectric power generation in the Upper Danube basin was modelled for two future decades, namely 2021-2030 and 2051-2060, using a special hydropower module coupled with the physically-based hydrological model PROMET. To cover a possible range of uncertainties, 16 climate scenarios were taken as meteorological drivers which were defined from different ensemble outputs of a stochastic climate generator, based on the IPCC-SRES-A1B emission scenario and four regional climate trends. Depending on the trends, the results show a slight to severe decline in hydroelectric power generation. Whilst the mean summer values indicate a decrease, the mean winter values display an increase. To show past and future regional differences within the Upper Danube basin, three hydropower plants at individual locations were selected. Inter-annual differences originate predominately from unequal contributions of the runoff compartments rain, snow-and ice-melt

Flood risk modeling of urbanized estuarine areas under uncertainty: a case study for Whitesands, UK

Aims: The impacts of catastrophic flooding have steadily increased over the last few decades. This work investigated the effectiveness of flood modeling, with low dimensionality models along with a wealth of soft (qualitative) and hard (quantitative) data. In the presence of very low resolution or qualitative data this approach has the potential of assessing a plethora of different scenarios with little computational cost, without compromise in prediction accuracy. Study Design: A flood risk modeling approach was implemented for the urbanized and flood prone region of Whitesands, at the Scottish town of Dumfries. This involved collection of a wide range of data: a) topographical maps and data from field visits were used to complement existing cross-sectional data, for building the river’s geometry, b) appropriate hydrological data were employed to run the simulations, while historical information about the extent, depth and impacts of flooding were utilized for calibrating the hydraulic model, and c) a wealth of photographic data obtained during the most recent December 2013 flood, were used for the model’s validation. Place and Duration of Study: Desk study: School of Engineering, University of Glasgow; September 2013 to May 2014. Field study: Dumfries; November 2013 to January 2014. Methodology: The HEC-RAS 1D model has been used to represent the hydraulics of the system. Flood maps were produced considering the local topography and predicted inundation depths. Flood cost and risk takes further into account the type and value of inundated property as well as the extent and depth of flooding. Results: The model predictions (inundation depths and flood extents presented in the flood maps) were in fairly good agreement with the observed results along the studied section of the river. Conclusion: This study presented a flood modeling approach that utilized an appropriate range of accessible data in the absence of detailed information. As the level of performance was comparable to other inundation models the results can be used for identification of flood mitigation measures and to inform best management strategies for waterways and floodplains

Computational support for early stage architectural design

The concepts underlying 'scenario-based' design are introduced. From the analysis of a number of struc-tured interviews with practicing designers, key design scenarios are identified. These scenarios are then generalised and outline guidelines developed for structuring early stage design

Energy Modelling and Forecasting for an Underground Agricultural Farm using a Higher Order Dynamic Mode Decomposition Approach

This paper presents an approach based on higher order dynamic mode decomposition (HODMD) to model, analyse, and forecast energy behaviour in an urban agriculture farm situated in a retrofitted London underground tunnel, where observed measurements are influenced by noisy and occasionally transient conditions. HODMD is a data-driven reduced order modelling method typically used to analyse and predict highly noisy and complex flows in fluid dynamics or any type of complex data from dynamical systems. HODMD is a recent extension of the classical dynamic mode decomposition method (DMD), customised to handle scenarios where the spectral complexity underlying the measurement data is higher than its spatial complexity, such as is the environmental behaviour of the farm. HODMD decomposes temporal data as a linear expansion of physically-meaningful DMD-modes in a semi-automatic approach, using a time-delay embedded approach. We apply HODMD to three seasonal scenarios using real data measured by sensors located at at the cross-sectional centre of the the underground farm. Through the study we revealed three physically-interpretable mode pairs that govern the environmental behaviour at the centre of the farm, consistently across environmental scenarios. Subsequently, we demonstrate how we can reconstruct the fundamental structure of the observed time-series using only these modes, and forecast for three days ahead, as one, compact and interpretable reduced-order model. We find HODMD to serve as a robust, semi-automatic modelling alternative for predictive modelling in Digital Twins

Interactive situation modelling in knowledge intensive domains

Interactive Situation Modelling (ISM) method, a semi-methodological approach, is proposed to tackle issues associated with modelling complex knowledge intensive domains, which cannot be easily modelled using traditional approaches. This paper presents the background and implementation of ISM within a complex domain, where synthesizing knowledge from various sources is critical, and is based on the principles of ethnography within a constructivist framework. Although the motivation for the reported work comes from the application presented in the paper, the actual scope of the paper covers a wide range of issues related to modelling complex systems. The author firstly reviews approaches used for modelling knowledge intensive domains, preceded by a brief discussion about two main issues: symmetry of ignorance and system behaviour, which are often confronted when applying modelling approaches to business domains. The ISM process is then characterized and critiqued with lessons from an exemplar presented to illustrate its effectiveness

A framework for developing and implementing an online learning community

Developing online learning communities is a promising pedagogical approach in online learning contexts for adult tertiary learners, but it is no easy task. Understanding how learning communities are formed and evaluating their efficacy in supporting learning involves a complex set of issues that have a bearing on the design and facilitation of successful online learning experiences. This paper describes the development of a framework for understanding and developing an online learning community for adult tertiary learners in a New Zealand tertiary institution. In accord with sociocultural views of learning and practices, the framework depicts learning as a mediated, situated, distributed, goal-directed, and participatory activity within a socially and culturally determined learning community. Evidence for the value of the framework is grounded in the findings of a case study of a semester-long fully online asynchronous graduate course. The framework informs our understanding of appropriate conditions for the development and conduct of online learning communities. Implications are presented for the design and facilitation of learning in such contexts

On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities

A model is presented in this work for simulating endogenously the evolution of the marginal costs of production of energy carriers from non-renewable resources, their consumption, depletion pathways and timescales. Such marginal costs can be used to simulate the long term average price formation of energy commodities. Drawing on previous work where a global database of energy resource economic potentials was constructed, this work uses cost distributions of non-renewable resources in order to evaluate global flows of energy commodities. A mathematical framework is given to calculate endogenous flows of energy resources given an exogenous commodity price path. This framework can be used in reverse in order to calculate an exogenous marginal cost of production of energy carriers given an exogenous carrier demand. Using rigid price inelastic assumptions independent of the economy, these two approaches generate limiting scenarios that depict extreme use of natural resources. This is useful to characterise the current state and possible uses of remaining non-renewable resources such as fossil fuels and natural uranium. The theory is however designed for use within economic or technology models that allow technology substitutions. In this work, it is implemented in the global power sector model FTT:Power. Policy implications are given.Comment: 18 pages, 7 figures, 8 pages of supplementary informatio

Case study based approach to integration of sustainable design analysis, performance and building information modelling

This paper presents a case study based research of both the method and technology for integration of sustainable design analysis (SDA) and building information modelling (BIM) within smart built environments (SBE). Level 3 BIM federation and integration challenges are recognised and improvements suggested, including issues with combining geometry and managing attribute data. The research defines SDA as rapid and quantifiable analysis of diverse sustainable alternatives and ‘what if’ scenarios posed by a design team and client during the early stages of the project, where the benefits of correct decisions can significantly exceed the actual investment required. The SDA concept and BIM integration findings are explained through a convergence from conceptualisation to calculation stages, emphasising the importance of an iterative over a linear approach. The approach allowed for a multitude of “what if” scenarios to be analysed, leading to more informed sustainable solutions at the right stages of the project development, with a generally lower level of detail (LOD) and computational/modelling effort required. In addition, the final stage of Building Regulations Part L compliance calculations was reached with a lot greater level of certainty, in terms of its requirements. Finally, a strategy for long term performance monitoring and evaluation of the building design in terms of its environmental sustainability is presented, via integration between BIM and SBE (Smart Built Environment) technologies