Stockholm County is currently implementing climate change adaptation, making it essential to distinguish the priorities being made. Previous research has suggested that social dimensions of climate change adaptation in cities, especially in the Global North, are largely ignored. Therefore, this thesis aims to identify how social dimension issues of current local Climate Change Adaptation [CCA] in Stockholm County is perceived by CCA-practitioners and provide an overall understanding of how current local Climate Change Adaptation [CCA] materializes in Stockholm County. Five civil servants working as environmental planners/strategists were interviewed and part of a semi-structured interview study, which was analyzed through thematic analysis and an intersectional framework. The results suggest that current local CCA prioritizes specific climate hazards (Floods and different erosion- related hazards), certain buildings (new developments), and certain evaluations (technical). In addition, heatwaves, existing built environments, and social dimension assessments were shown to be of less focus in current local CCA. The results from the intersectional franmework showed that specific identity categories are considered in certain climate hazards, specifically in heatwaves that have clear health outcomes compared to the other hazards. It also shows that gender seems to be the least explored identity category of vulnerability in current local CCA-practice. / Stockholms län genomför för närvarande klimatanpassnings-åtgärder, vilket gör det viktigt att urskilja hur det tar sig i uttryck. Tidigare forskning har signalerat att sociala dimensioner klimatanpassning av städer, särskilt i det globala Nord, i stort sett har ignorerats. Därför syftar denna uppsats till att ge en övergripande förståelse för hur klimatanpassning inom Stockholms län tar sig i uttryck och vilka sociala perspektiv bedöms relevanta verksamma tjänstemän inom klimatanpassning. Uppsatsen hade två forskningsfrågor: 1) Enligt tjänstemän som arbetar med klimatanpassning inom Stockholms län, vad prioriteras och vad prioriteras inte inom nuvarande klimatanpassnings-praxis för en klimatrisk, och varför? 2)Enligt tjänstemän som arbetar med klimatanpassning inom Stockholms län, vem anses vara sårbar inom klimatanpassning, och var inom nuvarande klimatanpassnings-praxis tas det i åtanke? Uppsatsen har förlitats sig i stort på intersektionalitet som ett analytiskt verktyg och som vägledning i en litteraturstudie. Eftersom klimatanpassning utförs inom fysisk planering av kommunen, har fem tjänstemän som arbetar som miljöplanerare eller miljö-strateger intervjuats i en semistrukturerad intervjustudie. Materialet har analyserades genom tematisk analys. Den tematiska analysen gav tre typer av teman, där en viss prioritering kunde urskiljas. Resultaten tyder på att nuvarande klimatanpassning prioriterar specifika klimatrisker (översvämningar, ras och skred), vissa byggnader (ny bebyggelse) och vissa utvärderingar (tekniska). Dessutom visade resultatet på att värmeböljor, befintliga miljöer och bedömningar av sociala dimensioner är av mindre vikt och fokus inom klimatanpassning. Den tematiska analysen gav även ett fjärde tema kallat Sårbarheter. Under detta tema, presenterades hur sårbarheter inför klimatförändringar uppfattas av de intervjuade tjänstemännen och de angivna sårbarheterna analyserades med ett befintligt intersektionellt ramverk. Resultaten från den intersektionella analysen visar att specifika identitetskategorier beaktas mer i vissa klimatrisker, till exempel vid värmeböljor som har tydliga hälsokonsekvenser jämfört med andra extrema väderhändelser. Den visar också att kön är den minst utforskade i dagens klimatanpassnings- praxis i Stockholms Län.

In times that reveal the consequences of climate change, cities are using urban greening as a potential measure in their climate change adaptation and mitigation strategies. Greenery in the city regulates the climate and balances temperature extremes through evapotranspiration and air humidification, spending shade and increased air circulation. Many cities in Germany, such as the City of Cologne, have established funding programmes for private stakeholders to support the greening of buildings. Greened buildings contribute to a reduction of the urban heat island effect by decreasing temperatures through increased evapotranspiration, increased air circulation and air humidification and a higher reflective power (albedo). The greening of buildings also cools down the building itself forming a natural insulation layer, shading and the reflection of sun energy. However, in most cities the potential for houses that could be greened is barely utilized. This study explores variables that influence the residents’ attitudinal and behavioural acceptance towards greening their building in Cologne Deutz. Survey research was conducted based on a theoretical framework that explains how external variables form beliefs that lead to attitudinal acceptance (positive attitude) and eventually behavioural acceptance (actual behaviour). The survey was designed to examine attitudinal acceptance and behavioural intention to act, as behavioural acceptance is difficult to measure. The main variables found to influence the residents’ attitudinal acceptance and behavioural intention towards the greening of buildings were ecological aspects, such as an increase of nature in the urban environment, an improvement of the urban climate, air quality and street cooling, and climate change. Visual-aesthetic aspects also played a major role, while finances and funding possibilities had a special influence on the perceived ease of use of greening one’s building. Amongst the sample of this study attitudinal acceptance and behavioural intention were categorized as high. Reasons that could explain the low amount of greening measure implementation were a possible lack of knowledge (of funding possibilities), a low number of private property owners, and an imbalance in the distribution of tangible advantages and disadvantages amongst tenants and landlords.

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Climate resilience is increasingly an attribute of competitive global cities. Cities that are most responsive to change will continue to prosper. To achieve this, governance structures and decision-making approaches that promote flexible and/or robust adaptation action are required. This thesis introduces a framework for urban adaptation planning that links medium-term risk management with the development and appraisal of long-term adaptation pathways. A long-term plan informed by the appraisal of a range of plausible pathways provides the opportunity to retain the flexibility to respond to future uncertainties, whilst also demonstrating how a city could manage future climate risk. This provides stakeholders with confidence that long-term risk is adequately considered, even if there is not a need to act immediately. To demonstrate how adaptation pathways can support adaptation decision-making in an urban system, the approach and methods developed as part of this thesis are applied in London. Adaptation pathways in response to water scarcity, surface water flood and heat risk were developed, and their appraisal presented as pathways diagrams. These diagrams provide a visual representation of the sequencing of decision points and plausible adaptation actions that may be implemented in the future. Pathways diagrams present climate risk and adaptation information for decision-makers in a salient and actionable manner. The pathways responding to individual risks in London are then brought together to demonstrate how an integrated assessment framework may be used to appraise city-scale adaptation pathways that respond to multiple climate risks. The growing emphasis within adaptation planning on approaches that can react flexibly to change increases the need to better understand the dynamics of climate risk and embed learning about the effectiveness of adaptation actions. To complement the pathways and adaptation decision-making research presented in this thesis, a framework that links adaptation monitoring and evaluation (M&E), risk assessment and decision-making is presented and explored to highlight the potential benefits of, and mechanisms for, adaptation M&E to inform and strengthen iterative risk-based adaptation planning. Demonstrated for the Thames Estuary, where concepts of adaptation planning have been pioneered but the opportunities of linking to monitoring and evaluation have not been extensively explored, we show how the framework can highlight actions and factors that are contributing to improving adaptation outcomes and those that require strengthening. This thesis contributes to the literature on urban climate change adaptation planning under conditions of uncertainty. This thesis also contributes to the evidence base needed to justify long-term planning and realise the benefits of climate risk reduction through the implementation of flexible, long-term integrated urban adaptation plans.

Increasing global mean temperature or global warming has the potential to affect the hydrologic cycle. In the 21st century, according to the UN Intergovernmental Panel on Climate Change (IPCC), alterations in the frequency and magnitude of high intensity rainfall events are very likely. Increasing trend of urbanization across the globe is also noticeable, simultaneously. These changes will have a great impact on water infrastructure as well as environment in urban areas. One of the impacts may be the increase in frequency and extent of flooding. India, in the recent years, has witnessed a number of urban floods that have resulted in huge economic losses, an instance being the flooding of Mumbai in July, 2005. To prevent catastrophic damages due to floods, it has become increasingly important to understand the likely changes in extreme rainfall in future, its effect on the urban drainage system, and the measures that can be taken to prevent or reduce the damage due to floods. Reliable estimation of future design rainfall intensity accounting for uncertainties due to climate change is an important research issue. In this context, rainfall intensity-duration-frequency (IDF) relationships are one of the most extensively used hydrologic tools in planning, design and operation of various drainage related infrastructures in urban areas. There is, thus, a need for a study that investigates the potential effects of climate change on IDF relationships. The main aim of the research reported in this thesis is to investigate the effect of climate change on Intensity-Duration-Frequency relationship in an urban area. The rainfall in Bangalore City is used as a case study to demonstrate the applications of the methodologies developed in the research Ahead of studying the future changes, it is essential to investigate the signature of changes in the observed hydrological and climatological data series. Initially, the yearly mean temperature records are studied to find out the signature of global warming. It is observed that the temperature of Bangalore City shows an evidence of warming trend at a statistical confidence level of 99.9 %, and that warming effect is visible in terms of increase of minimum temperature at a rate higher than that of maximum temperature. Interdependence studies between temperature and extreme rainfall reveal that up to a certain range, increase in temperature intensifies short term rainfall intensities at a rate more than the average rainfall. From these two findings, it is clear that short duration rainfall intensities may intensify in the future due to global warming and urban heat island effect. The possible urbanization signatures in the extreme rainfall in terms of intensification in the evening and weekends are also inferred, although inconclusively. The IDF relationships are developed with historical data and changes in the long term daily rainfall extreme characteristics are studied. Multidecedal oscillations in the daily rainfall extreme series are also examined. Further, non-parametric trend analyses of various indices of extreme rainfall are carried out to confirm that there is a trend of increase in extreme rainfall amount and frequency, and therefore it is essential to the study the effects of climate change on the IDF relationships of the Bangalore City. Estimation of future changes in rainfall at hydrological scale generally relies on simulations of future climate provided by Global Climate Models (GCMs). Due to spatial and temporal resolution mismatch, GCM results need to be downscaled to get the information at station scale and at time resolutions necessary in the context of urban flooding. The downscaling of extreme rainfall characteristics in an urban station scale pose the following challenges: (1) downscaling methodology should be efficient enough to simulate rainfall at the tail of rainfall distribution (e.g., annual maximum rainfall), (2) downscaling at hourly or up to a few minutes temporal resolution is required, and (3) various uncertainties such as GCM uncertainties, future scenario uncertainties and uncertainties due to various statistical methodologies need to be addressed. For overcoming the first challenge, a stochastic rainfall generator is developed for spatial downscaling of GCM precipitation flux information to station scale to get the daily annual maximum rainfall series (AMRS). Although Regional Climate Models (RCMs) are meant to simulate precipitation at regional scales, they fail to simulate extreme events accurately. Transfer function based methods and weather typing techniques are also generally inefficient in simulating the extreme events. Due to its stochastic nature, rainfall generator is better suited for extreme event generation. An algorithm for stochastic simulation of rainfall, which simulates both the mean and extreme rainfall satisfactorily, is developed in the thesis and used for future projection of rainfall by perturbing the parameters of the rainfall generator for the future time periods. In this study, instead of using the customary two states (rain/dry) Markov chain, a three state hybrid Markov chain is developed. The three states used in the Markov chain are: dry day, moderate rain day and heavy rain day. The model first decides whether a day is dry or rainy, like the traditional weather generator (WGEN) using two transition probabilities, probabilities of a rain day following a dry day (P01), and a rain day following a rain day (P11). Then, the state of a rain day is further classified as a moderate rain day or a heavy rain day. For this purpose, rainfall above 90th percentile value of the non-zero precipitation distribution is termed as a heavy rain day. The state of a day is assigned based on transition probabilities (probabilities of a rain day following a dry day (P01), and a rain day following a rain day (P11)) and a uniform random number. The rainfall amount is generated by Monte Carlo method for the moderate and heavy rain days separately. Two different gamma distributions are fitted for the moderate and heavy rain days. Segregating the rain days into two different classes improves the process of generation of extreme rainfall. For overcoming the second challenge, i.e. requirement of temporal scales, the daily scale IDF ordinates are disaggregated into hourly and sub-hourly durations. Disaggregating continuous rainfall time series at sub-hourly scale requires continuous rainfall data at a fine scale (15 minute), which is not available for most of the Indian rain gauge stations. Hence, scale invariance properties of extreme rainfall time series over various rainfall durations are investigated through scaling behavior of the non-central moments (NCMs) of generalized extreme value (GEV) distribution. The scale invariance properties of extreme rainfall time series are then used to disaggregate the distributional properties of daily rainfall to hourly and sub-hourly scale. Assuming the scaling relationships as stationary, future sub-hourly and hourly IDF relationships are developed. Uncertainties associated with the climate change impacts arise due to existence of several GCMs developed by different institutes across the globe, climate simulations available for different representative concentration pathway (RCP) scenarios, and the diverse statistical techniques available for downscaling. Downscaled output from a single GCM with a single emission scenario represents only a single trajectory of all possible future climate realizations and cannot be representative of the full extent of climate change. Therefore, a comprehensive assessment of future projections should use the collective information from an ensemble of GCM simulations. In this study, 26 different GCMs and 4 RCP scenarios are taken into account to come up with a range of IDF curves at different future time periods. Reliability ensemble averaging (REA) method is used for obtaining weighted average from the ensemble of projections. Scenario uncertainty is not addressed in this study. Two different downscaling techniques (viz., delta change and stochastic rainfall generator) are used to assess the uncertainty due to downscaling techniques. From the results, it can be concluded that the delta change method under-estimated the extreme rainfall compared to the rainfall generator approach. This study also confirms that the delta change method is not suitable for impact studies related to changes in extreme events, similar to some earlier studies. Thus, mean IDF relationships for three different future extreme events, similar to some earlier studies. Thus, mean IDF relationships for three different future periods and four RCP scenarios are simulated using rainfall generator, scaling GEV method, and REA method. The results suggest that the shorter duration rainfall will invigorate more due to climate change. The change is likely to be in the range of 20% to 80%, in the rainfall intensities across all durations. Finally, future projected rainfall intensities are used to investigate the possible impact of climate change in the existing drainage system of the Challaghatta valley in the Bangalore City by running the Storm Water Management Model (SWMM) for historical period, and the best and the worst case scenario for three future time period of 2021–2050, 2051–2080 and 2071–2100. The results indicate that the existing drainage is inadequate for current condition as well as for future scenarios. The number of nodes flooded will increase as the time period increases, and a huge change in runoff volume is projected. The modifications of the drainage system are suggested by providing storage pond for storing the excess high speed runoff in order to restrict the width of the drain The main research contribution of this thesis thus comes from an analysis of trends of extreme rainfall in an urban area followed by projecting changes in the IDF relationships under climate change scenarios and quantifying uncertainties in the projections.