Towards evaluation design for smart city development

Smart city developments integrate digital, human, and physical systems in the built environment. With growing urbanization and widespread developments, identifying suitable evaluation methodologies is important. Case-study research across five UK cities - Birmingham, Bristol, Manchester, Milton Keynes and Peterborough - revealed that city evaluation approaches were principally project-focused with city-level evaluation plans at early stages. Key challenges centred on selecting suitable evaluation methodologies to evidence urban value and outcomes, addressing city authority requirements. Recommendations for evaluation design draw on urban studies and measurement frameworks, capitalizing on big data opportunities and developing appropriate, valid, credible integrative approaches across projects, programmes and city-level developments

Probabilistic soil moisture projections to assess Great Britain's future clay-related subsidence hazard

Clay-related subsidence is Great Britain’s (GB) most damaging soil-related geohazard, costing the economy up to £500 million per annum. Soil-related geohazard models based on mineralogy and potential soil moisture deficit (PSMD) derived from historic weather data have been used in risk management since the 1990s. United Kingdom Climate Projections (UKCP09) suggest that regions of GB will experience hotter, drier summers and warmer, wetter winters through to 2050. As a result, PSMD fluctuations are expected to increase, exacerbating the shrinkage and swelling of clay soils. A forward-looking approach is now required to mitigate the impacts of future climate on GB’s built environment. We present a framework for incorporating probabilistic projections of PSMD, derived from a version of the UKCP09 stochastic weather generator, into a clay subsidence model. This provides a novel, national-scale thematic model of the likelihood of clay-related subsidence, related to the top 1-1.5m soil layer, for three time periods; baseline (1961-1990), 2030 (2020-2049) and 2050 (2040-2069). Results indicate that much of GB, with the exception of upland areas, will witness significantly higher PSMDs through to the 2050’s. As a result, areas with swelling clay soils will be subject to proportionately increased subsidence hazard. South-east England will likely incur the highest hazard exposure to clay-related subsidence through to 2050. Potential impacts include increased incidence of property foundation subsidence, alongside deterioration and increased failure rates of GB’s infrastructure networks. Future clay-subsidence hazard scenarios provide benefit to many sectors, including: finance, central and local government, residential property markets, utilities and infrastructure operators.EPSR

Soil geohazard mapping for improved asset management of UK local roads

Unclassified roads comprise 60% of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be “at risk” and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink–swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any, structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence

Enhanced visualization of the flat landscape of the Cambridgeshire Fenlands

The Fenlands of East Anglia, England, represent a subtle landscape, where topographic highs rarely exceed 30 m above sea level. However, the fens represent an almost full sequence of Quaternary deposits which, together with islands of Cretaceous and Jurassic outcrops, make the area of geological importance. This feature discusses the advantages of using 3D visualization coupled with high-resolution topographical data, over traditional 2D techniques, when undertaking an analysis of the landscape. Conclusions suggest that the use of 3D visualization will result in a higher level of engagement, particularly when communicating geological information to a wider public

Opening up the coast

Coastal zones attract human settlement, business and industry, and are instrumental to the functioning of societies both in coastal states and the wider global community. However, the oceans and coasts are under growing pressure as human practices change, populations rise and climate change impacts increase. In managing coastal regions, high quality data forms the basis of rational decision-making. Large volumes of ‘triple bottom line’ data exists representing a wide variety of environmental, social, and economic themes in coastal regions. Such data is especially crucial to development of environmental risk evaluations for the coast. The momentum driving the Open Source data movement across the world is accelerating and consequently, huge quantities of data are becoming freely available to the public. This presents a valuable opportunity for coastal managers, policy makers and land planners, who need to evaluate the full implications of their choices. Decision-makers frequently need to draw on many disparate datasets. However, this can be complicated by many factors, including a lack of awareness of the full range of datasets available. This paper seeks to explore this area, taking the UK as an example, to reveal how currently available open data sources relate to coastal management decision-making. Environmental risk management is a cross-cutting theme, relevant to all areas of coastal management. As such, this topic is discussed and addressed within a case study focusing on the vulnerable coastal region of East Anglia. In collation and analysis of coastal data Geographical Information Systems (GIS) can play an important role, in line with this GIS approaches were utilised within the case study. The case study led to development of a conceptual framework which can be applied to future coastal risk assessments, using Open Source data. The UK is currently at the forefront of the Open Source data movement and as such it is used as an example within this paper, however the issues addressed have international relevance, and the UK perspective is used to illustrate wider opportunities, resulting from freely available data sources, extending to management of coastal regions globally

Forward-looking climatic scenarios of UK clay-related subsidence risk

An award drawing upon the Cranfield University EPSRC-funded Impact Acceleration Account (IAA) was awarded to staff in the University’s School of Energy, Environment and Agrifood (SEEA) (Hallett, Farewell, Pritchard), to undertake processing of UKCP09 climate projections for the United Kingdom (UK) in support of assessments of future geohazards and societal impact. This report identifies the technical outcomes from this work and presents the resultant climate change cartography and related data. Spatially coherent national data ensembles are generated for the UKCP09 ‘Baseline’ period, for ‘2030’ and ‘2050’. Maps of Potential Soil Moisture Deficit (PSMD) are produced for each to exemplify its application. The findings suggest that the extremes in PSMD observed at the current time in the UK are likely to become the norm by 2030 and 2050. The data produced has a range of potential applications, from geohazard assessments to the built environment and infrastructure, to agri-informatic modelling of agricultural crops, as well as modelling for 'future-proofing' of buildings against predicted climate change by example. It is anticipated that the datasets presented from this IAA will be of benefit to a range of end-user stakeholders. One example is in the insurance, reinsurance and water utility sectors, where modelling of future impacts of climate change are conducted. Recent research has suggested this data will likely prove of use for County Councils and municipal authorities, for example in the allocation of targeted road maintenance funding, particularly on local-authority owned highways. Rail network operators, having faced a number of embankment failures, and track undulations as a result of shrink/swell activity are also likely to benefit from this research. The soil moisture deficit scenarios produced could help such organisations better manage geotechnical assets and vegetation management of susceptible slopes and soils. Cranfield’s School of Energy, Environment and Agrifood (SEEA) manage and operate the Natural Perils Directory (NPD). The NPD is a widely used geohazard thematic dataset portraying vulnerabilities arising from soil-climate responses to long-term climate change. NPD will incorporate directly the datasets produced and described here

Leveraging big data tools and technologies: Addressing the challenges of the water quality sector

The water utility sector is subject to stringent legislation, seeking to address both the evolution of practices within the chemical/pharmaceutical industry, and the safeguarding of environmental protection, and which is informed by stakeholder views. Growing public environmental awareness is balanced by fair apportionment of liability within-sector. This highly complex and dynamic context poses challenges for water utilities seeking to manage the diverse chemicals arising from disparate sources reaching Wastewater Treatment Plants, including residential, commercial, and industrial points of origin, and diffuse sources including agricultural and hard surface water run-off. Effluents contain broad ranges of organic and inorganic compounds, herbicides, pesticides, phosphorus, pharmaceuticals, and chemicals of emerging concern. These potential pollutants can be in dissolved form, or arise in association with organic matter, the associated risks posing significant environmental challenges. This paper examines how the adoption of new Big Data tools and computational technologies can offer great advantage to the water utility sector in addressing this challenge. Big Data approaches facilitate improved understanding and insight of these challenges, by industry, regulator, and public alike. We discuss how Big Data approaches can be used to improve the outputs of tools currently in use by the water industry, such as SAGIS (Source Apportionment GIS system), helping to reveal new relationships between chemicals, the environment, and human health, and in turn provide better understanding of contaminants in wastewater (origin, pathways, and persistence). We highlight how the sector can draw upon Big Data tools to add value to legacy datasets, such as the Chemicals Investigation Programme in the UK, combined with contemporary data sources, extending the lifespan of data, focusing monitoring strategies, and helping users adapt and plan more efficiently. Despite the relative maturity of the Big Data technology and adoption in many wider sectors, uptake within the water utility sector remains limited to date. By contrast with the extensive range of applications of Big Data in in other sectors, highlight is drawn to how improvements are required to achieve the full potential of this technology in the water utility industry

Coastal risk adaptation: the potential role of accessible geospatial Big Data

Increasing numbers of people are living in and using coastal areas. Combined with the presence of pervasive coastal threats, such as flooding and erosion, this is having widespread impacts on coastal populations, infrastructure and ecosystems. For the right adaptive strategies to be adopted, and planning decisions to be made, rigorous evaluation of the available options is required. This evaluation hinges on the availability and use of suitable datasets. For knowledge to be derived from coastal datasets, such data needs to be combined and analysed in an effective manner. This paper reviews a wide range of literature relating to data-driven approaches to coastal risk evaluation, revealing how limitations have been imposed on many of these methods, due to restrictions in computing power and access to data. The rapidly emerging field of ‘Big Data’ can help overcome many of these hurdles. ‘Big Data’ involves powerful computer infrastructures, enabling storage, processing and real-time analysis of large volumes and varieties of data, in a fast and reliable manner. Through consideration of examples of how ‘Big Data’ technologies are being applied to fields related to coastal risk, it becomes apparent that geospatial Big Data solutions hold clear potential to improve the process of risk based decision making on the coast. ‘Big Data’ does not provide a stand-alone solution to the issues and gaps outlined in this paper, yet these technological methods hold the potential to optimise data-driven approaches, enabling robust risk profiles to be generated for coastal regions