Gina Cavan

Probabilistic GIS-based method for delineation of urban flooding risk hotspots

Abstract Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia.

Forecasting the outbreak of moorland wildfires in the English Peak District

Warmer, drier summers brought by climate change increase the potential risk of wildfires on the moorland of the Peak District of northern England. Fires are costly to fight, damage the ecosystem, harm water catchments, cause erosion scars and disrupt transport. Fires release carbon dioxide to the atmosphere. Accurate forecasts of the timing of fires help deployment of fire fighting resources. A probit model is used to assess the chance of fires at different times of the year, days of the week and under various weather conditions. Current and past rainfall damp fire risk. The likelihood of fire increases with maximum temperature. Dry spells or recent fire activity also signal extra fire hazard. Certain days are fire prone due to visitors and some months of the year are more risky reflecting the changing flammability of moorland vegetation. The model back-predicts earlier fires during a hot dry summer. The impact of climate change on fire incidence is not straightforward. Risks may be reduced if wetter winters and earlier onset of spring add to plant moisture content. Yet a warm spring increases biomass and potential fuel load in summer. Climate change may cause the timing of moorland wildfires to shift from a damper and more verdant spring to drought-stressed summer.

Changes to climate and visitor behaviour: implications for vulnerable landscapes in the North West region of England.

Many high quality landscapes can be found in the North West region of England, including those of international significance such as the Lake District National Park. These natural assets are recognised by the regional tourism strategy as particularly important, as they are a major determinant for visitors within, and to, the region. However, with the strategy geared towards increasing visitor numbers, there is a substantial challenge to be faced in the future: how to maintain the quality of an environment that is under combined pressure from both visitor numbers and climate change? Focusing on two landscape types considered to be the most vulnerable to a changing climate, the coastal zone and the uplands, this paper presents ‘downscaled’ climate change scenarios, and provides an assessment of how a combination of climate and non-climate factors are likely to impact these vulnerable landscapes in the future. The case study analysis is largely drawn from a series of ‘risk’ workshops held with key regional stakeholders.

XRWIS: the use of geomatics to predict winter road surface temperatures in Poland

A new method (XRWIS) to predict the minimum road surface temperature for the winter maintenance of roads, using geomatics, has been tested in Poland. A geographical database was constructed for a 200 km test route from Krakow to the Slovakian border. A GPS survey to measure sky-view factor was carried out as part of the COST 719 project. A computer energy balance model ‘IceMiser’ was run retrospectively to predict road surface temperature every 20 minutes for every 20 m along the road using hourly weather data recorded at two adjacent climate stations: at low elevation in Krakow and at high elevation in Zakopane, in March 2003. A GIS was used to visualise the predicted road surface temperatures. The IceMiser model was verified by comparing the predicted road surface temperatures with measured road surface temperatures at a number of road weather outstations along the route. The results for four road weather outstations are discussed. The best results are for Libertow (264 m) and Myslenice (304 m) close to Krakow, whereas the results for Skawa (518 m) and Piatkowa Gora (649 m) at high elevation are not as good, probably due to their distance from the Zakopane climate station. Copyright

Green Infrastructure for Climate Adaptation in African Cities

Green infrastructure is a core component of any city. The ecosystem services that it provides already make an important contribution to the health and wellbeing of urban dwellers and are considered to be vital for future urban sustainability. In the case of African cities, this argument is stronger still given that other forms of infrastructure are often lacking or seriously underperforming. This chapter discusses the potential role of urban ecosystem services for climate adaptation in African cities. It is based on an empirical assessment of the urban morphology, green structures and ecosystem services of five cities, with a particular emphasis on provisioning services from woody cover and temperature regulating services from evapotranspiring surfaces in two of them. An analysis of retrospective and prospective change helps to establish the extent of pressures to green structures – including in the context of climate change – and the prospects for using green infrastructure for achieving urban climate adaptation. The results show considerable losses in green structures and their associated ecosystem services; something set to continue under ‘business as usual’ development scenarios projected to 2025. Indeed, there is already a greater need for services than is currently satisfied, especially in the urban core. Our results suggest that, although climate change is an additional pressure to ecosystem services, it is development which poses the greatest immediate threat. It is therefore critical that green infrastructure planning is strengthened and brought into the core of urban development planning as part of climate adaptation and broader sustainability goals.

Development of a climate change risk and vulnerability assessment tool for urban areas

Purpose – Assessment of climate change risks and vulnerability is essential in order to inform and implement appropriate adaptation strategies. Disastrous effects of extreme weather events such as the heat waves across Europe in 2003 highlight the adaptation imperative. Regional spatial planning and urban design can help to reduce the vulnerability of communities to these risks. The purpose of this paper is to report on the development of an assessment tool, which highlights climate change risks and vulnerabilities in urban areas, and the results of pilot and user testing with the Green and Blue Space Adaptation for Urban Areas and Eco Towns (GRaBS) project partners.Design/methodology/approach – The tool follows the principles of an online public participation GIS, and is built using the Google Maps Interface. The approach is based on a risk framework, focusing on the three elements; hazard, vulnerability and exposure. Thus, the assessment tool assesses vulnerability of population and infrastructure in ur...

Climate change and the visitor economy in the uplands

This paper presents two case studies on the impact of climate change on upland landscapes in England (footpath erosion in the Lake District National Park, and moorland wildfires in the Peak District National Park) and considers the negative implications for the visitor economy in these areas. Areas of natural beauty such as the examples presented have an important role to play in attracting visitors, and sustaining the visitor economy will therefore depend on maintaining the quality of the environment in the face of both visitor pressure and the impacts of climate change.

A Combined Approach to Classifying Land Surface Cover of Urban Domestic Gardens Using Citizen Science Data and High Resolution Image Analysis

Domestic gardens are an important component of cities, contributing significantly to urban green infrastructure (GI) and its associated ecosystem services. However, domestic gardens are incredibly heterogeneous which presents challenges for quantifying their GI contribution and associated benefits for sustainable urban development. This study applies an innovative methodology that combines citizen science data with high resolution image analysis to create a garden dataset in the case study city of Manchester, UK. An online Citizen Science Survey (CSS) collected estimates of proportional coverage for 10 garden land surface types from 1031 city residents. High resolution image analysis was conducted to validate the CSS estimates, and to classify 7 land surface cover categories for all garden parcels in the city. Validation of the CSS land surface estimations revealed a mean accuracy of 76.63% (s = 15.24%), demonstrating that citizens are able to provide valid estimates of garden surface coverage proportions. An Object Based Image Analysis (OBIA) classification achieved an estimated overall accuracy of 82%, with further processing required to classify shadow objects. CSS land surface estimations were then extrapolated across the entire classification through calculation of within image class proportions, to provide the proportional coverage of 10 garden land surface types (buildings, hard impervious surfaces, hard pervious surfaces, bare soil, trees, shrubs, mown grass, rough grass, cultivated land, water) within every garden parcel in the city. The final dataset provides a better understanding of the composition of GI in domestic gardens and how this varies across the city. An average garden in Manchester has 50.23% GI, including trees (16.54%), mown grass (14.46%), shrubs (9.19%), cultivated land (7.62%), rough grass (1.97%) and water (0.45%). At the city scale, Manchester has 49.0% GI, and around one fifth (20.94%) of this GI is contained within domestic gardens. This is useful evidence to inform local urban development policies.

Introduction to the special issue on adaptive flood risk management

Societal adaptation to extreme weather events is now widely acknowledged to be a political and practical imperative. The widely recognised challenges of urban densification, a changing climate and associated intensifying weather extremes, inadequate infrastructures, and altered responsibilities for the management of risk, combine to enhance the vulnerability and exposure of natural and human systems (IPCC 2014). Against this context, flood risk is considered to pose an inevitable and significant economic and social challenge to communities across the globe, necessitating progressive and holistic approaches to adaptive flood risk management. New and innovative technologies and management systems have been identified as holding significant potential to help create resilient futures and could be highly costeffective (van Ree et al. 2011; Royas et al. 2013). Such adaptation efforts—it has been asserted—should prioritise measures that reduce the consequences of hazardous events, rather than trying to completely avoid their occurrence (Alfieri et al. 2016). The integration of adaptive ‘solutions’ requires careful consideration across traditional boundaries of practice. Recent work has identified how collaborative and interdisciplinary research has presented solutions to the manifold challenges of securing adaptation (Zevenbergen et al. 2013; Carter et al. 2015). For instance, given the high density of urban areas and increasing competition for land for transport, housing, employment, etc., there is a need to combine flood defence functions with other uses (van Ree et al. 2011). The use of green infrastructure-based approaches to enhance multifunctionality is also widely acknowledged as a ‘win–win’ solution to urban adaptation (Lindley et al. 2015). However, despite the urgency of resilience agendas, the practical integration of necessary adaptive measures is frequently frustrated and often remains elusive. Points of resistance to flood adaptation initiatives range from political and administrative