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.

This diploma thesis deals with the design and implementation of a tool for network attack detection from a captured network communication. It utilises the tshark packet analyser, the meaning of which is to convert the input file with the captured communications to the PDML format. The objective of this conversion being, increasing the flexibility of input data processing. When designing the tool, emphasis has been placed on the ability to expand it to detect new network attacks and on integrating these additions with ease. For this reason, the thesis also includes the design of a complex declarative descriptions for network attacks in the YAML serialization format. This allows us to specify the key properties of the network attacks and the conditions for their detection. The resulting tool acts as an interpreter of proposed declarative descriptions allowing it to be expanded with new types of attacks.

The diploma thesis deals with experimental determination of hydrodynamic load on the overflowed bridge deck model. In the first part of the thesis the author describes the analysis of the problem together with the basic physical laws and principles that are used or assumed in the measurement itself. In the second part the author describes the measurements in the laboratory of the Faculty of Civil Engineering and its gradual processing. At the end of the work are described the results of measurement, their comparison with numerical modeling, other authors and their possible use in practice.

This doctoral thesis deals with the valuation of damage to buildings affected by floods. In its individual parts, it researches floods as a risk, focuses on the damage caused by this natural phenomenon and examines the methods used to assess the damages caused by floods. With the beginnings of human settlement, the vicinity of rivers has been inhabited for the many befits that watercourses bring. However, there are many dangers associated with this, especially the ones associated with the spillage of riverbeds – with floods. This phenomenon causes considerable damage to property, the environment or human health and lives. There are many measures to eliminate the risk of flooding, or at least mitigate its effects. This work further researches the mitigating of impacts – it examines the methods of determining the amount of damage to buildings caused by floods, looks for factors and parameters influencing the amount of damage and focuses on streamlining these methods. The aim of the thesis is to find a suitable methodology/model that can automate the calculation of the amount of damage, or in other words, to find a quick and at the same time sufficiently accurate solution to this problem. The main output of the thesis is the equation of the damage curve and a model for the amount of damage calculation based on the principle of damage curves using the hybrid genetic algorithm. Another output is a practical tool that works on the basis of the said algorithm and automatically calculates the amount of damage to the building when entering very basic information about the damaged object.

MURP / Department of Urban and Regional Planning / Disaster is posing serious threats to both human lives, infrastructure and the environment at large. Greater Tzaneen Municipality (GTM) is one of the many municipalities that suffer from flood related disasters. Lack of integration between Disaster Risk Reduction (DRR) and spatial planning has compounded the disaster risk situation in the municipality. This study sought to investigate the prospects of integrating spatial planning with disaster risk reduction in flood prone areas of GTM. The study is guided by three research objectives. First, the study sought to analyse spatial planning attributes that can be valorised for DRR in flood prone areas; Secondly, it sought to analyse spatial planning factors that define vulnerability attributes of households occupying flood prone areas. Finally, the study sought to perform a cluster analytical creation of a typology of households whose resilience to flooding could be enhanced through spatial planning. Twenty-five flood prone areas were analysed on the basis of four main flood vulnerability attributes. In order to identify such vulnerability attributes, the study borrowed critical insights from literatures on flood vulnerability, spatial planning and DRR. Such a critical review of literature was complemented by the use of pattern matching as a qualitative research instrument. Quantitative that was gathered using a structured observation checklist. Quantitative data generated was first subjected to various statistical tests that included Normality and Reliability Tests. Common measures of Normality test used included measures of skewness, kurtosis and the use of Normal Q-Q plots. To assess flood vulnerability, Hierarchical Cluster Analysis (HCA) was used. HCA was used to identify clusters of flood prone areas which had common characteristics in terms of the four main study constructs proposed by the study which included the physical/engineering, socio-economic, ecological/natural and political or governance conditions characterizing each area. HCA was then used to identify main clusters exhibiting similar characteristics and the associated level of vulnerability of such of communities occupying such clusters. Study results revealed 2 main clusters of flood prone areas whose differences lay in interactions that existed between the physical/engineering, socio-economic, ecological/natural and political or governance conditions characterizing each area. Such clusters depicted 2 levels of vulnerability that is high, and moderate. A number of opportunities and constraints were generated using the SWOT matrix strategy with the main results showing that spatial planning elements characterizing flood prone areas could be transformed into critical urban risk management options for DRR. This is because a spatial planning elements were found to have a direct influences on critical factors of DRR such as location of activities. The study concluded by recommending a number of spatial planning strategies that can be vaporized for DRR. Such strategies are systematically aligned to the unique vulnerability context conditions associated with the two flood vulnerability solution arrived at using HCA. / NRF

Der Klimawandel ist auf regionaler Ebene nachweisbar. Zudem gehen Forschungsergebnisse davon aus, dass sich Ereignisse wie Überflutung und Starkregen regional differenziert zukünftig noch intensivieren werden. Bereits heute belegen Schadensmeldungen in der Region Dresden einen sich aus den klimatischen Veränderungen ergebenden Handlungsbedarf in Form von Anpassungsmaßnahmen auf Gebäudeebene. Deshalb sind die Hauptziele der vorliegenden Arbeit das Aufzeigen der Verletzbarkeit von Wohngebäuden und die Erarbeitung von Vorschlägen für entsprechende Ertüchtigungen. Als Datenbasis dient zum einen die baukonstruktive Analyse typischer Beispielgebäude der Region Dresden, welche gleichzeitig die wichtigsten Baualtersstufen abbilden. Dadurch können die in der Region hauptsächlich anzutreffenden baukonstruktiven Durchformungen, Nutzungen und Charakteristiken von Wohngebäuden abgedeckt werden. Dies dient als Grundlage zur Beurteilung der Verletzbarkeit und Anpassungsfähigkeit der wichtigsten Baukonstruktionen gegenüber den Einwirkungen Überflutung und Starkregen. Zum anderen dient als Datenbasis die Dokumentation, Analyse und Interpretation abgelaufener Schadensereignisse in Bezug auf Schadensbilder und Schadensmechanismen an Gebäuden und Baukonstruktionen. Innerhalb der Verletzbarkeitsanalyse gegenüber Überflutung führt die Beschreibung von Schadenstypen, Schadensbildern und Schadensmechanismen in die Erläuterung einer Methodik zur Abschätzung von Hochwasserschäden an Gebäuden. Diese wird in der Arbeit dazu verwendet, die spezifische Verletzbarkeit der einzelnen Beispielgebäude gegenüber der Einwirkung Überflutung mit Hilfe von Wasserstand-Schaden-Beziehungen zu ermitteln. Darauf aufbauend können nun Bereiche, welche aufgrund ihrer hohen Verletzbarkeit angepasst werden sollten, eingegrenzt werden. In der Folge werden beispielhaft bautechnisch mögliche Anpassungsmaßnahmen vorgestellt, am baukonstruktiven Detail gezeigt und ihre positiven Auswirkungen auf die Wasserstand-Schaden-Beziehungen beziehungsweise auf die Verringerung der Verletzbarkeit der Beispielgebäude dargestellt.

Intense but short-term cloudbursts may cause severe flooding in urban areas. Such short-term cloudbursts mostly are of convective character, where the rain intensity may vary considerably within relatively small areas. Using uniform design rains where maximum intensity is assumed over the whole catchment is common practice in Sweden, though. This risks overestimating the hydraulic responses, and hence lead to overdimensioning of stormwater systems. The objective of this study was to determine how the hydraulic response to cloudbursts is affected by the spatial variation of the rain in relation to the catchment size, aiming to enable improved cloudburst mapping in Sweden. Initially, the spatial variation of heavy rains in Sweden was investigated by studying radar data provided by SMHI. The distribution of rainfall accumulated over two hours from heavy raincells was investigated, based on the assumption that the intensity of convective raincells can be approximated as spatially Gaussian distributed. Based on the results, three Gaussian test rains, whose spatial variation was deemed a representative selection of the radar study, were created. In order to investigate how the hydraulic peak responses differed between the Gaussian test rains and uniform reference rains, both test and reference rains were modeled in MIKE21 Flow model. The modelling was performed on an idealised urban model fitted to Swedish urban conditions, consisting of four nested square catchments of different sizes. The investigated hydraulic peak responses were maximum outflow, proportion flooded area and average maximum water depth. In comparison with spatially varied Gaussian rains centered at the outlets, the uniform design rain with maximum rain volume overestimated the peak hydraulic response with 1-8%, independent of catchment size. Uniform design rains scaled with an area reduction factor (ARF), which is averaging the rainfall of the Gaussian rain over the catchment, instead underestimated the peak response, in comparison with the Gaussian rains. The underestimation of ARF-rains increased heavily with catchment size, from less than 5 % for a catchment area of 4 km2 to 13 - 69 % for a catchment area of 36 km2. The conclusion can be drawn that catchment size ceases to affect the hydraulic peak response when the time it takes for the whole catchment to contribute to the peak response exceeds the time it takes for the peak to be reached. How much the rain varies over the area which is able to contribute to the peak response during the rain event, can be assumed to decide how much a design rain without ARF overestimates the peak responses. If the catchment exceeds this size, an ARF-scaled rain will underestimate the peak responses. This underestimation is amplified with larger catchments. The strong pointiness of the CDS-hyetograph used in the study risks underestimating the differences in hydraulic peak responses between the test rains and a uniform rain without ARF, while the difference between test rains and uniform rains with ARF risks being overestimated. / Intensiva men kortvariga skyfall kan orsaka omfattande översvämningsproblematik i urbana områden. Trots att sådana kortvariga skyfall oftast är av konvektiv karaktär, där regnintensiteten kan variera avsevärt inom relativt små områden, används idag uniforma designregn där maxintensitet antas över hela avrinningsområdet. Detta riskerar att leda till en överskattning av hydrauliska responser, och följaktligen överdimensionering av dagvattensystem. Denna studie syftar till att utreda hur den hydrauliska responsen av skyfall påverkas av regnets spatiala variation, i relation till avrinningsområdets storlek. Ytterst handlar det om att möjliggöra förbättrad skyfallskartering i Sverige. Initialt undersöktes den spatiala variationen hos kraftiga regn i Sverige, genom en studie av radardata tillhandahållen av SMHI. Utbredningen av regnmängd ackumulerad över två timmar från kraftiga regnceller undersöktes utifrån antagandet att intensiteten hos konvektiva regnceller kan approximeras som spatialt gaussfördelad. Baserat på resultatet skapades tre gaussfördelade testregn vars spatiala variation ansågs utgöra ett representativt urval från radarstudien. För att undersöka hur de hydrauliska responserna skiljer sig åt mellan de gaussfördelade testregnen och uniforma referensregn, modellerades såväl test- som referensregn i MIKE 21 Flow model. Modelleringen utfördes på en idealiserad stadsmodell anpassad efter svenska urbana förhållanden, bestående av fyra nästlade kvadratiska avrinningsområden av olika storlekar. De hydrauliska responser som undersöktes var maximalt utflöde, maximal andel översvämmad yta samt medelvärdesbildat maximalvattendjup, alltså toppresponser. Jämfört med spatialt varierade gaussregn centrerade kring utloppen överskattade ett uniformt designregn med testregnens maximala volym de hydrauliska toppresponserna med 1-8 %, oberoende av avrinningsområdets storlek. Uniforma designregn skalade med area reduction factor (ARF), vilken medelvärdesbildar gaussregnets nederbörd över avrinningsområdet, underskattade istället toppresponsen jämfört med gaussregnen. ARF-regnets underskattning ökade kraftigt med avrinningsområdets storlek, från mindre än 5 % för ett avrinningsområde på 4 km2, till 13 - 69 % för ett avrinningsområde på 36 km2. Slutsatsen kan dras att avrinningsområdets storlek upphör att påverka den hydrauliska toppresponsen, då tiden det tar för hela avrinningsområdet att samverka till toppresponsen överstiger tiden till denna respons. Hur mycket regnet varierar över det område som under regnhändelsen hinner samverka till toppresponsen, kan antas avgöra hur mycket ett designregn utan ARF överskattar toppresponserna. Överstiger avrinningsområdet denna storlek kommer ett ARF-regn att underskatta toppresponserna, och underskattningen förstärks med ökande avrinningsområdesstorlek. Den kraftiga temporala toppigheten hos den CDS-hyetograf som användes i studien riskerar att underskatta skillnaderna i hydraulisk topprespons mellan testregnen och ett uniformt regn utan ARF, medan skillnaden mellan testregn och uniforma regn med ARF istället riskerar att överskattas.

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Flooding is a worldwide problem that every year causes substantial damage for the environment and stakeholders nearby, and this impact relates to several of the United Nations Sustainable Development Goals. Colombia is specially prone to flooding as 17% of its surface area is at risk of extreme flooding. In addition, there is something called a POT (plan de ordenamiento territorial) for every municipality in Colombia, which states how the territory should be managed. For this project the rivers were of particular interest, and the POT states that no temporary or permanent constructions are allowed within 30 meters on either side of a river. The purpose of this report was to investigate and analyze the possibilities of using UAV (unmanned aerial vehicle) -based photogrammetry and UAV-based LiDAR (light detection and ranging) technology to gather sufficient data for a model that could simulate different flooding scenarios in the examined area. Data from the UAV-based photogrammetry resulted in a complete visual overview of the examined area. The data gathered from the UAV-based light detection and ranging resulted in an accurate point cloud that could be processed into a DTM (digital terrain model) where three different flooding scenarios were simulated. The simulations and the visual model showed that majority of people in theexamined area were disobeying the POT and the 30 meter rule, therefore being in risk of flooding and impacting the natural diversity of the body of water. The simulation also showed that stakeholders close to the body of water were affected for each of the three different water level scenarios. In some cases, it was only vegetation and crops that got affected by the flooding scenario, while in other cases entire structures and buildings were damaged due to the increase of water level. To complement the flooding scenarios, interviews were conducted with people that have good knowledge of the area and of ecology, resulting in a stakeholder analysis. This provided an additional depth to the analysis and showed the complexity in the management of flooding in the area.