Дисертації з теми "Urban climate model"

With more than half of the world's population living in urban areas, it is important that the relationships between the urban environment and climate are better understood. The current research aims to continue the effort in assessing and understanding the urban environment through the use of a global climate model (GCM). Given the relative newness of the presence of an urban land type and model in a GCM, there are many more facets of the urban-climate relationship to be investigated. By comparing thirty-year ensembles of CAM4 coupled with CLM4 both with (U) and without (U_n) the inclusion of the urban land type, the sensitivity of the atmospheric model to urban land cover is assessed. As expected, largest differences tend to be in the Northern Hemisphere due to the location of most of the globe's densest and expansive cities. Significant differences in the basic climate variables of temperature and precipitation are present at annual, seasonal, and monthly scales in some regions. Seasonality to the urban influence also exists with the transition months of Spring and Fall having the largest difference in temperatures. Of the eleven regions defined by Oleson (2012), three were most impacted by the presence of urban land cover in the model—Europe, Central Asia, and East Asia.

Since urban attributes can vary greatly within one world continent, the sensitivity of regional climates to the urban type parameters is also explored. By setting all urban land cover to only one urban density type, the importance of city composition on climate, even within the same city, is highlighted. While preserving the distinct urban regional characteristics and the geographical distribution of urbanized areas, the model is run with homogeneous urban types: high density and tall building district. As with the default urban and excluded urban runs, a strong seasonality to the differences between the solo-high-density simulation and default urban (U_HD – U) and solo-tall-building-district-density simulation and default urban (U_TBD – U) exists. Overall, the transition and winter months are most sensitive to changes in urban density type.

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A preocupação com os chamados impactos ambientais urbanos fomentou um maior interesse nas pesquisas, principalmente aquelas voltadas para as análises climáticas, na escala urbana. A cidade por consequência de seu processo de organização e estruturação desenvolveu um clima totalmente particular, o clima urbano, isso é possível através da retirada da vegetação original e a inserção dos chamados equipamentos urbanos, como por exemplo, as vias impermeabilizadas, as construções, a verticalização, além da circulação de pessoas e veículos que irão contribuir para maior aquecimento da atmosfera local. Os materiais presentes no meio urbano vão apresentar diferentes valores de albedo, emissividade, absortividade e irradiação e consequentemente, estes condicionarão diferentes valores de temperatura de superfície e que influenciarão na temperatura do ar. O presente estudo tem por objetivo analisar o comportamento do clima urbano na cidade de Juiz de Fora- MG, onde foram trabalhadas 35 regiões urbanas, localizadas ao longo do curso do Rio Paraibuna. O estudo busca através da aplicação de um modelo geoespacial, interligar variáveis que possuem uma conexão direta com a temperatura de superfície e indireta com a temperatura do ar. Este conjunto de dados permitiu alcançar uma maior compreensão, viabilizou a espacialização e consequentemente uma visualização de como se distribuem as áreas e suas diferentes capacidades de criarem distintos campos térmicos na cidade.Além disso, para fins de validação do modelo, foi feita uma correlação estatística entre o modelo matemático proposto e a temperatura de superfície obtida na faixa do infravermelho termal. O modelo utilizado provou possuir consistência para ser adaptado a fim de ser replicado em diferentes cidades com especificidades térmicas além de ser viável a integração de outras informações e dados.
Concern about so-called urban environmental impacts has fostered greater interest in research, especially those focused on climate analysis, on the urban scale. The city as a result of its process of organization and structuring has developed a totally particular climate, the urban climate, this is possible through the removal of the original vegetation and the insertion of so-called urban equipment, such as waterproofed roads, constructions, verticalization, besides the circulation of people and vehicles that will contribute to greater warming of the local atmosphere. The materials present in the urban environment will present different values of albedo, emissivity, absorptivity and irradiation and consequently, these will condition different values of surface temperature and that will influence the air temperature. The present study aims to analyze the behavior of the urban climate in the city of Juiz de Fora- MG, where 35 urban areas were located along the course of the Paraibuna River. The study searches through the application of a geospatial model, interconnecting variables that have a direct coexistence with the surface temperature and indirect with the air temperature. This dataset allowed to reach a greater understanding, made possible the spatialization and consequently a visualization of how the areas are distributed and their different capacities to create different thermal fields in the city. In addition, for purposes of validation of the model, a statistical correlation was made between the proposed mathematical model and the surface temperature obtained in the thermal infrared range. The model used proved to have consistency to be adapted in order to be replicated in different cities with thermal specificities besides being feasible the integration of other information and data.

The objective of this work is to study the urban climate, mainly by focusing on urban temperature trends. The specific focus is to understand the reasons of increase in minimum temperature through observational and modelling techniques. For this purpose, the temperatures data from 1950 to 2004 measured on several meteorological stations of Pakistan is studied and analyzed. Daily averaged annual and seasonal minimum (Tmin) and maximum (Tmax) temperature data of 37 meteorological observatories of Pakistan (17 urban, 7 town and 13 rural) from 1950 to 2004 is first homogenized and then analyzed. The results show that after 1980s Tmin and Tmax increase faster than the period before 1980s at urban areas. During 1980-2004, the increase in Tmin at major urban stations is observed higher than the smaller towns and rural stations. To understand, the effect of the size of the city, changing land use and the building height on the evolution of minimum and maximum temperatures in urban areas has been studied by using the FVM (Finite Volume Model) model and the simulations are run for three days starting at 00:00 (GMT) on 19th day of each month and ending at 00:00 (GMT) on 22nd day of each month. For each month, 48 possible combinations of simulation scenarios are run (4*4*3) and in total, 576 simulations (48*12) are run for a year. The main results show that Tmin and Tmax increase when urban fraction u, city size r and building height h increase. But it is noticed that Tmax increases more than the Tmin when u increases, Tmin increases more than the Tmax when r increases and Tmin increases more than the Tmax when h increases. Among all urban factors (urban fraction u, city size r and building's height h), city size is the major factor that mainly contributes to increase the minimum temperature more than the maximum temperature in urban areas.

Water is the driving force in nature. We use water for washing cars, doing laundry, cooking, taking a shower, but also to generate energy and electricity. Therefore water is a necessary product in our daily lives (USGS. Howard Perlman, 2013). The model that we created is based on the urban water demand computer model from the Pacific Institute (California). With this model we will forecast the future urban water use of Emilia Romagna up to the year of 2030. We will analyze the urban water demand in Emilia Romagna that includes the 9 provinces: Bologna, Ferrara, Forli-Cesena, Modena, Parma, Piacenza, Ravenna, Reggio Emilia and Rimini. The term urban water refers to the water used in cities and suburbs and in homes in the rural areas. This will include the residential, commercial, institutional and the industrial use. In this research, we will cover the water saving technologies that can help to save water for daily use. We will project what influence these technologies have to the urban water demand, and what it can mean for future urban water demands. The ongoing climate change can reduce the snowpack, and extreme floods or droughts in Italy. The changing climate and development patterns are expected to have a significant impact on water demand in the future. We will do this by conducting different scenario analyses, by combining different population projections, climate influence and water saving technologies. In addition, we will also conduct a sensitivity analyses. The several analyses will show us how future urban water demand is likely respond to changes in water conservation technologies, population, climate, water price and consumption. I hope the research can contribute to the insight of the reader’s thoughts and opinion.

The Urban Heat Island (UHI) was investigated using satellite data, ground observations, and simulations with an Urban Canopy Parameterization in a numerical weather prediction model. Satellite-observed surface skin temperatures at Xi'an City and Oklahoma City (OKC) were analyzed to compare the UHI intensity for the two inland cities. A larger population density and larger building density in Xi'an City creates a stronger skin-level UHI effect. However, ground observed 2-m surface air temperature (Tair) data showed an urban cooling island (UCI) effect that occurred over an urban region in OKC during the daytime of July 19, 2003.

The sensitivity and accuracy of an Urban Canopy Model were evaluated by comparing simulation results between the urban and rural areas of OKC. The model reproduced skin temperature differences between the rural and urban area and reproduced a UCI effect in OKC. Furthermore, the Weather Research and Forecasting (WRF)/Noah/Single-Layer Urban Canopy Model (SLUCM) simulations were also compared with ground observations, including wind speeds, wind directions, and energy fluxes. Although the WRF/SLCUM model failed to simulate these variables accurately, it reproduced the diurnal variations of surface temperatures, wind speeds, wind directions and energy fluxes reasonably well.

This study consisted in the development of a canopy model (CIM), which could be use as an interface between meso-scale models used to simulate urban climate and micro-scale models used to evaluate building energy use. The development is based on previously proposed theories and is presented in different atmospheric conditions, with and without obstable. It has been shown, for example, that to be in coherence with the Monin-Obukhov Similarity Theory, that a correction term has to be added to the buoyancy term of the T.K.E. CIM has also been coupled with the meteorological meso-scale model WRF. A methodology was proposed to take advantage of both models (one being more resolved, the other one integrating horizontal transport terms) and to ensure a coherence of the results. Besides being more precise than the WRF model at the same resolution, this system allows, through CIM, to provide high resolved vertical profiles near the surface.

Les bâtiments représentent 40 pourcents de la consommation finale d'énergie. Ils sont ainsi le fer de lance des politiques de réduction des dépenses énergétiques. Récemment, des systèmes de modèles climatiques qui incluent un modèle atmosphérique régional et des paramétrisations urbaines sophistiquées ont été développés. Ils considèrent la complexité de l’îlot de chaleur urbain et ses interactions avec les besoins énergétiques des bâtiments. Dans quelle mesure ces systèmes constituent-ils des outils d’aide à la décision pour les autorités locales ? Cette étude menée sur le territoire de l'Eurodistrict (Strasbourg - Kehl) en 2010, puis en 2030, à l’aide du système de modèles de climat WRF/ARW-BEP+BEM a démontré que si le système de modèles estimait de manière fiable les besoins en chauffage des bâtiments, ces derniers étaient davantage sensibles aux caractéristiques intrinsèques des bâtiments qu'aux formes urbaines et à l'îlot de chaleur urbain induit par ces formes
Buildings represent 40 percent of the end-use energy. Thus, they constitute a key point of the energy saving policies. Recently, climate modeling systems that include a mesoscale atmospheric model, sophisticated urban parameterizations have been developed to account for the complexity of the urban climate and its interactions with the building energy loads. This study aims to assess the capability of such climate modeling systems to provide climate and energy guidelines to urban planners. For this, we used the research collaborative WRF/ARW-BEP+BEM climate modeling system and performed sensitivity tests considering the territory of the Eurodistrict in 2010, and then in 2030. The results reveal that the climate modeling system achieves estimating the building energy needs over the study area, but also indicate that the building energy needs are more sensitive to the building intrinsic properties and occupant behavior than to the urban forms and their induced urban heat island

Le influenze di natura antropica sul sistema Terra sono notevoli. Fra queste, le alterazioni dell’ambiente dovute all’urbanizzazione sono notevolmente impattanti per la vita delle persone. La comprensione dei processi atmosferici innescati dalle modifiche del suolo è ormai un importante oggetto di studi, così come l’uso di modelli a diverse scale spaziali che ne riproducono la dinamica. L’obiettivo di questo lavoro è migliorare le conoscenze relative all’isola di calore urbana di Bologna utilizzando un modello a piccola scala. In particolare, il modello Atmospheric Dispersion Modelling System – Temperature & Humidity è stato utilizzato per simulare variazioni spaziali e temporali di temperatura, con tre diverse parametrizzazioni della superficie urbana di Bologna. In letteratura sono presenti diverse metodologie per parametrizzare la superficie urbana, con vari gradi di sofisticatezza, applicabili a vari modelli. Queste parametrizzazioni tengono conto dell’uso del suolo e delle diverse caratteristiche tipiche delle superfici urbane. In particolare, in questo lavoro sono state usate tre diverse parametrizzazioni della superficie urbana. La prima prevede che la superficie urbana sia suddivisa in centro e periferia, è considerata come caso base per valutare le successive. La seconda parametrizzazione tiene conto della classificazione nota in letteratura come "Local Climate Zone" che divide l’area urbana in zone a seconda delle caratteristiche di uso del suolo. L’ultima parametrizzazione è stata sviluppata seguendo una classificazione definita "Aktas" recentemente proposta come alternativa alle classificazioni LCZ. In questa tesi, vengono presentati i risultati del modello ottenuti utilizzando le tre diverse metodologie per la parametrizzazione della superficie urbana. I risultati mostrano come una parametrizzazione più dettagliata permetta al modello di simulare una distribuzione della temperatura che tenga conto della presenza di superfici molto eterogenee tra loro.

The performance of the Integrated Urban Wastewater Systems (IUWS) including: sewer system, WWTP and river, in both operational control and design, under unavoidable future climate change and urbanisation is a concern for water engineers which still needs to be improved. Additionally, with regard to the recent attention around the world to the environment, the quality of water, as the main component of that, has received significant attention as it can have impacts on health of human life, aquatic life and so on. Hence, the necessity of improving systems performance under the future changes to maintain the quality of water is observed. The research presented in this thesis describes the development of risk-based and non-risk-based models to improve the operational control and design of the IUWS under future climate change and urbanisation aiming to maintain the quality of water in recipients. In this thesis, impacts of climate change and urbanisation on the IUWS performance in terms of the receiving water quality was investigated. In the line with this, different indicators of climate change and urbanisation were selected for evaluation. Also the performance of the IUWS under future climate change and urbanisation was improved by development of a novel non-risk-based operational control and design models aiming to maintain the quality of water in the river to meet the water quality standards in the recipient. This is initiated by applying a scenario-based approach to describe the possible features of future climate change and /or urbanisation. Additionally the performance of the IUWS under future climate change and urbanisation was improved by development of a novel risk-based operational control and design models to reduce the risk of water quality failures to maintain the health of aquatic life. This is initiated by considering the uncertainties involved with the urbanisation parameters considered. The risk concept is applied to estimate the risk of water quality breaches for the aquatic life. Also due to the complexity and time-demanding nature of the IUWS simulation models (which are called about the optimisation process), there is the concern about excessive running times in this study. The novel “MOGA-ANNβ” algorithm was developed for the optimisation process throughout the thesis to speed it up while preserving the accuracy. The meta-model developed was tested and its performance was evaluated. In this study, the results obtained from the impact analysis of the future climate change and urbanisation (on the performance of the IUWS) showed that the future conditions have potential to influence the performance of the IUWS in both quality and quantity of water. In line with this, selecting proper future conditions’ parameters is important for the system impact analysis. Also the observations demonstrated that the system improvement is required under future conditions. In line with this, the results showed that both risk-based and non-risk-based operational control optimisation of the IUWS in isolation is not good enough to cope with the future conditions and therefore the IUWS design optimisation was carried out to improve the system performance. The riskbased design improvement of the IUWS in this study showed a better potential than the non-risk-based design improvement to meet all the water quality criteria considered in this study.

The seagrass resource provides essential ecosystem functions for many marine species. This research evaluated the vulnerability and sustainability of the seagrass resource in an urbanized area to the effects of sea level rise. The assessment required analysis of information regarding the biogeography of the seagrass resource, and developing a method to model the spatial extent of the suitable habitat for seagrass, and applying the model to predict the implications of simulated sea level rise scenarios on the seagrass resource. Examining the biogeography of the seagrass resource required the development of a seagrass monitoring and assessment field survey and a comprehensive seagrass resource map (SGRM). The mesoscale field survey was designed and conducted in St. Joseph Sound (STJS) and Clearwater Harbor North (CLWN), Pinellas County, Florida from 2006-2010 to determine the seagrass species composition and spatial distribution for the resource. The seagrass species found in the study area consisted of Syringodium filiforme Kützing (Syringodium), Thalassia testudinum Banks ex König (Thalassia), and Halodule wrightii Ascherson (Halodule). These seagrass species occurred in monospecific and mixed beds in all combinations throughout the study area. Spatially, Thalassia was the dominant nearshore in STJS and Halodule in CLWN. Syringodium was most frequently found in STJS in the mid to deep depths. The SGRM was mapped from satellite remote sensing imagery with training information from the mesoscale field survey data. Landsat 5 Thematic Mapper (TM) and Earth Observing-1 Hyperion (HYP) were processed to map the seagrass resource in the study area in a nearshore shallow coastal area of Pinellas County, FL, USA. A maximum likelihood classification (MLC) was used to classify both TM and HYP imagery into three classes (seagrass estimated coverage) of the seagrass resource. The overall accuracy for the TM MLC map was 91% (kappa = 0.85) and the HYP was 95% (kappa = 0.92). Due to areas of cloud cover in the HYP image, it was necessary to composite the classification values from the TM MLC to accurately define these areas. The validation accuracy (n=72) of the composite seagrass resource map was 81% which was much more rigorous than the previous accuracy estimates. These results support the application of remote sensing methods to analyze the spatial extent of the seagrass resource. The development of a spatial habitat suitability model (HSM) for the seagrass resource provided a management tool to better understand the relationship between seagrass, water quality, and other environmental factors. The motivation to develop the spatial HSM was to provide a spatial modeling tool to simulate changes in the water quality environment and evaluate the potential impact on the seagrass resource. High resolution bathymetry and field survey water quality data were used to fit general additive models (GAM) to the STJS (Adjusted R2= 0.72, n=134) and CLWN (Adjusted R2= 0.75, n=138) seagrass resource. The final GAMs included water quality variables including salinity, chlorophyll-a concentration, total suspended solids, turbidity, and light. The only significant variable was the light metric in STJS (p-value= 0.001) and CLWN (p-value= 0.006). The light metric was the logarithmic light attenuation calculated from the water quality field survey transmittance (660nm) data and the high resolution bathymetry. The overall accuracy (OA) of the predictive GAM rasters was higher in CLWN (95%, kappa =0.88) than in STJS (82%, kappa = 0.40). The increased prediction error in STJS was spatially correlated with the areas of lower density seagrass along the deep edge of the bed. While there may be a plethora of factors contributing to the decreased density of the seagrass, this may indicate these seagrass were already living at the edge of the suitable habitat. Factors threatening the sustainability of the seagrass resource included those related to water quality and environmental changes. Knowledge of these relationships was essential to develop a predictive spatial HSM to simulate responses of the seagrass to changes in the water quality and the environment. Historically, environmental management strategies focused on water quality targets, but have not considered mitigation for climate change impacts, specifically sea level rise (SLR). This study utilized the HSM for the seagrass resource as a management tool to better understand the relationship between seagrass, water quality, and sea level rise scenarios. Based on SLR scenarios for 1ft-6ft (0.305m-1.83m) from 2010 to 2100, the potential seagrass habitat loss and gain was analyzed. From the current 60 km2 of seagrass habitat in St. Joseph Sound (STJS) and Clearwater Harbor North (CLWN), the predicted seagrass habitat loss based on the HSM which focused on light availability for photosynthesis ranged from 14 km2 (SLR 1ft) to 26 km2 (SLR 2ft) to the entire 60 km2 (SLR 6ft). The potential seagrass habitat gain based on the coastal flooding model (NOAA, 2012) ranged from 4 km2 (SLR 1ft) to 19 km2 (SLR 6ft). However, based on the spatial distribution of the seagrass and the proximity of the seagrass to the new habitat, the potential viable habitat based on the mean seagrass growth rates (horizontal rhizome elongation) only ranged from 2 km2 (SLR 1ft) to 9 km2 (SLR 6ft). An additional complexity to the gain of seagrass habitat was the effect of the anthropogenically altered shorelines, seawalls, which covered 47% of the shoreline. These seawalls potentially could impede the inundation of the seawater and the seagrass colonization of these areas by creating a vertical boundary for seagrass growth. The mitigation of the potential effects of SLR on the seagrass resource may require ecosystem level management. While management of water quality would continue to benefit the seagrass resource, additional management strategies would be necessary to mitigate for potential decrease in suitable seagrass habitat related to the effects of SLR. A discussion of potential management approaches suggested that the integration of coastal shoreline management strategies and seagrass resource management would be essential to insure the sustainability of the resource.

The impact of climate change is increasingly important to the design of urban water infrastructure like stormwater systems, sewage systems and drinking water systems. Growing evidence indicates that the water sector will not only be affected by climate change, but it will reflect and deliver many of its impacts through floods, droughts, or extreme rainfall events. Water resources will change in both quantity and quality, and the infrastructure of stormwater and wastewater facilities may face greater risk of damage caused by storms, floods and droughts. The effect of the climate change will put more difficulties on operations to disrupted services and increased cost of the water and wastewater services. Governments, urban planners, and water managers should therefore re-examine development processes for municipal water and wastewater services and are adapt strategies to incorporate climate change into infrastructure design, capital investment projects, service provision planning, and operation and maintenance. According to the Intergovernmental Panel on Climate Change, the global mean temperature has increased by 0,7 °C during the last 100 years and, as a consequence, the hydrological cycle has intensified with, for example, more acute rainfall events. As urban drainage systems have been developed over a long period of time and design criteria are based upon climatic characteristics, these changes will affect the systems and the city accordingly. The overall objective of this thesis is to increase the knowledge about the climate change impacts on the stormwater system in Al Hillah city/Iraq. In more detail, the objective is to investigate how climate change could affect urban drainage systems specifically stormwater infrastructure, and also to suggest an adaptation plan for these changes using adaptation plans examples from international case studies. Three stochastic weather generators have been investigated in order to understand the climate and climate change in Al Hillah. The stochastic weather generators have been used in different kind of researches and studies; for example in hydrology, floods management, urban water design and analysis, and environmental protection. To make such studies efficient, it is important to have long data records (typically daily data) so the weather generator can generate synthetic daily weather data based on a sound statistical background. Some weather generators can produce the climate change scenarios for different kind of global climate models. They can be used also to produce synthetic data for a site that does not have enough data by using interpolation methods. To ensure that the weather generator is fitting the climate of the region properly, it should be tested against observed data, whether the synthetic data are sufficiently similar. At the same time, the accuracy of the weather generator is different from region to region and depends on the respective climate properties. Testing three weather generators GEM6, ClimGen and LARS-WG at eight climate stations in the region of Babylon governorate/Iraq, where Al Hillah is located, is one of the purposes of the first part of this study. LARS-WG uses a semi-parametric distribution (developed distribution), whereas GEM6 and ClimGen use a parametric distribution (less complicated distribution). Different statistical tests have been selected to compare observed and synthetic weather data for the same kind, for instance, the precipitation and temperature distribution (wet and dry season). The result shows that LARS-WG represents the observed data for Babylon region in a better way than ClimGen, whereas GEM6 seems to misfit the observed data. The synthetic data will be used for a first simulation of urban run-off during the wet season and the consequences of climate change for the design and re-design of the urban drainage system in Al Hillah. The stochastic weather generator LARS is then used to generate ensembles of future weather data using five Global Climate Models (GCMs) that best captured the full range of uncertainty. These Global Climate Models are used to construct future climate scenarios of temperature and precipitation over the region of Babylon Governorate in Iraq. The results show an increase in monthly temperatures and a decrease in the total amount of rain, yet the extreme rain events will be more intense in a shorter time. Changes in the amount, timing, and intensity of rain events can affect the amount of stormwater runoff that needs to be controlled. The climate change calculated projections may make existing stormwater-related flooding worse. Different districts in Al Hillah city may face more frequent stormwater floods than before due to the climate change projections. All the results that have been taken from the Global Climate Models are in a daily resolution format and in order to run the Storm Water Management Model it is important to have all data in a minimum of one hour resolution. In order to fulfill this condition a disaggregation model has been used. Some hourly precipitation data were required to calibrate the temporal disaggregation model; however none of the climate stations and rain gauges in the area of interest have hourly resolution data, so the hourly data from Baghdad airport station have been used for that calibration. The changes in the flood return periods have been seen in the projected climate change results, and a return period will only remain valid over time if environmental conditions do not change. This means that return periods used for planning purposes may need to be updated more often than previously, because values calculated based on the past 30 years of data may become unrepresentative within a relatively short time span. While return periods provide useful guidance for planning the effects of flooding and related impacts, they need to be used with care, and allowances have to be made for extremes that may occur more often than may be expected. In the study area with separated stormwater systems, the Storm Water Management Model simulation shows that the number of surface floods as well as of the floods increases in the future time periods 2050s and 2080s. Future precipitation will also increase both the flooding frequency and the duration of floods; therefore the need to handle future situations in urban drainage systems and to have a well-planned strategy to cope with future conditions is evident. The overall impacts on urban drainage systems due to the increase of intensive precipitation events need to be adapted. For that reason, recommendations for climate change adaptation in the city of Al Hillah have been suggested. This has been accomplished by merging information from the review of five study cases, selected based on the amount and quality of information available. The cities reviewed are Seattle (USA), Odense (Denmark), Tehran (Iran), and Khulna (Bangladesh)
Die Auswirkungen des Klimawandels auf die Gestaltung der städtischen Wasserinfrastruktur wie Regenwasser, Kanalisation und Trinkwassersysteme werden immer wichtiger. Eine wachsende Anzahl von Belegen zeigt, dass der Wassersektor nicht nur durch den Klimawandel beeinflusst werden wird, aber er wird zu reflektieren und liefern viele seiner Auswirkungen durch Überschwemmungen, Dürren oder extreme Niederschlagsereignisse. Die Wasserressourcen werden sich in Quantität und Qualität verändern, und die Infrastruktur von Regen-und Abwasseranlagen kann einer größeren Gefahr von Schäden durch Stürme, Überschwemmungen und Dürren ausgesetzt sein. Die Auswirkungen des Klimawandels werden zu mehr Schwierigkeiten im Betrieb gestörter Dienstleistungen und zu erhöhten Kosten für Wasser-und Abwasserdienstleistungen führen. Regierungen, Stadtplaner, und Wasser-Manager sollten daher die Entwicklungsprozesse für kommunale Wasser-und Abwasserdienstleistungen erneut überprüfen und Strategien anpassen, um den Klimawandel in Infrastruktur-Design, Investitionsprojekte, Planung von Leistungserbringung, sowie Betrieb und Wartung einzuarbeiten. Nach Angaben des Intergovernmental Panel on Climate Change hat die globale Mitteltemperatur in den letzten 100 Jahren um 0,7 °C zugenommen, und in der Folge hat sich der hydrologische Zyklus intensiviert mit, zum Beispiel, stärkeren Niederschlagsereignisse. Da die städtischen Entwässerungssysteme über einen langen Zeitraum entwickelt wurden und Design-Kriterien auf klimatischen Eigenschaften beruhen, werden diese Veränderungen die Systeme und die Stadt entsprechend beeinflussen. Das übergeordnete Ziel dieser Arbeit ist es, das Wissen über die Auswirkungen des Klimawandels auf das Regenwasser-System in der Stadt Hilla / Irak zu bereichern. Im Detail ist das Ziel, zu untersuchen, wie der Klimawandel die Siedlungsentwässerung und insbesondere die Regenwasser-Infrastruktur betreffen könnte. Desweiteren soll ein Anpassungsplan für diese Änderungen auf der Grundlage von beispielhaften Anpassungsplänen aus internationalen Fallstudienvorgeschlagen werden. Drei stochastische Wettergeneratoren wurden untersucht, um das Klima und den Klimawandel in Hilla zu verstehen. Stochastische Wettergeneratoren wurden in verschiedenen Untersuchungen und Studien zum Beispiel in der Hydrologie sowie im Hochwasser-Management, Siedlungswasser-Design- und Analyse, und Umweltschutz eingesetzt. Damit solche Studien effizient sind, ist es wichtig, lange Datensätze (in der Regel Tageswerte) haben, so dass der Wettergenerator synthetische tägliche Wetterdaten erzeugen kann, dieauf einem soliden statistischen Hintergrund basieren. Einige Wettergeneratoren können Klimaszenarien für verschiedene Arten von globalen Klimamodellen erzeugen. Sie können unter Verwendung von Interpolationsverfahren auch synthetische Daten für einen Standort generieren, für den nicht genügend Daten vorliegen. Um sicherzustellen, dass der Wettergenerator dem Klima der Region optimal entspricht, sollte gegen die beobachteten Daten geprüft werden, ob die synthetischen Daten ausreichend ähnlich sind. Gleichzeitig unterscheidet sich die Genauigkeit des Wettergenerator von Region zu Region und abhängig von den jeweiligen Klimaeigenschaften. Der Zweck des ersten Teils dieser Studie ist es daher, drei Wettergeneratoren, namentlich GEM6, ClimGen und LARS-WG, an acht Klimastationen in der Region des Gouvernements Babylon / Irak zu testen. LARS-WG verwendet eine semi-parametrische Verteilung (entwickelte Verteilung), wohingegen GEM6 und ClimGen eine parametrische Verteilung (weniger komplizierte Verteilung) verwenden. Verschiedene statistische Tests wurden ausgewählt, um die beobachteten und synthetischen Wetterdaten für identische Parameter zu vergleichen, zum Beispiel die Niederschlags- und Temperaturverteilung (Nass-und Trockenzeit). Das Ergebnis zeigt, dass LARS-WG die beobachteten Daten für die Region Babylon akkurater abzeichnet, als ClimGen, wobei GEM6 die beobachteten Daten zu verfehlen scheint. Die synthetischen Daten werden für eine erste Simulation des städtischen Run-offs in der Regenzeit sowie der Folgen des Klimawandels für das Design und Re-Design des städtischen Entwässerungssystems in Hilla verwendet. Der stochastische Wettergenerator LARS wird dann verwendet, um Gruppen zukünftiger Wetterdaten unter Verwendung von fünf globalen Klimamodellen (GCM), die das gesamte Spektrum der Unsicherheit am besten abdecken, zu generieren. Diese globalen Klimamodelle werden verwendet, um zukünftige Klimaszenarien der Temperatur und des Niederschlags für die Region Babylon zu konstruieren. Die Ergebnisse zeigen, eine Steigerung der monatlichen Temperaturen und eine Abnahme der Gesamtmenge der Regen, wobei es jedoch extremere Regenereignissen mit höherer Intensivität in kürzerer Zeit geben wird. Veränderungen der Höhe, des Zeitpunkt und der Intensität der Regenereignisse können die Menge des Abflusses von Regenwasser, die kontrolliert werden muss, beeinflussen. Die Klimawandel-Prognosen können bestehende regenwasserbedingte Überschwemmungen verschlimmern. Verschiedene Bezirke in Hilla können stärker von Regenfluten betroffen werden als bisher aufgrund der Prognosen. Alle Ergebnisse, die von den globalen Klimamodellen übernommen wurden, sind in täglicher Auflösung und um das Regenwasser-Management-Modell anzuwenden, ist es wichtig, dass alle Daten in einer Mindestauflösung von einer Stunde vorliegen. Zur Erfüllung dieser Bedingung wurde ein eine Aufschlüsselungs-Modell verwendet. Einige Stunden-Niederschlagsdaten waren erforderlich, um das zeitliche Aufschlüsselungs-Modell zu kalibrieren. Da weder die Klimastationen noch die Regen-Messgeräte im Interessenbereich über stundenauflösende Daten verfügt, wurden die Stundendaten von Flughäfen in Bagdad verwendet. Die Veränderungen in den Hochwasserrückkehrperioden sind in den projizierten Ergebnissen des Klimawandels ersichtlich, und eine Rückkehrperiode wird nur dann über Zeit gültig bleiben, wenn sich die Umweltbedingungen nicht ändern. Dies bedeutet, dass Wiederkehrperioden, die für Planungszwecke verwendet werden, öfter als bisher aktualisiert werden müssen, da die auf Grundlage von Daten der letzten 30 Jahre berechneten Werte innerhalb einer relativ kurzen Zeitspanneunrepräsentativ werden können. Während Wiederkehrperioden bieten nützliche Hinweise für die Planung die Effekte von Überschwemmungen und die damit verbundenen Auswirkungen, müssen aber mit Vorsicht verwendet werden, und Extreme, die öfter eintreten könnten als erwartet, sollten berücksichtigt werden. Im Studienbereich mit getrennten Regenwassersystemen zeigt die Simulation des Regenwasser-Management-Modells, dass sich die Anzahl der Oberflächenhochwasser sowie der Überschwemmungen im Zeitraum 2050e-2080 erhöhen wird. Zukünftige Niederschläge werdensowohl die Hochwasser-Frequenz als auch die Dauer von Überschwemmungen erhöhen. Daher ist die Notwendigkeit offensichtlich, zukünftige Situationen in städtischen Entwässerungssystemen zu berücksichtigen und eine gut geplante Strategie zu haben, um zukünftige Bedingungen zu bewältigen. Die gesamten Auswirkungen auf die Siedlungsentwässerungssyteme aufgrund der Zunahme von intensiven Niederschlagsereignissen müssen angepasst werden. Aus diesem Grund wurden Empfehlungen für die Anpassung an den Klimawandel in der Stadt Hilla vorgeschlagen. Diese wurden durch die Zusammenführung von Informationen aus der Prüfung von fünf Fallstudien, ausgewählt aufgrund der Menge und Qualität der verfügbaren Informationen, erarbeitet,. Die bewerteten Städte sind Seattle (USA), Odense (Dänemark), Teheran (Iran), und Khulna (Bangladesch)

L’urbanisation engendre, par l’imperméabilisation des surfaces et la présence de bâtiments, une modification locale du climat et, plus spécifiquement, le phénomène d’îlot de chaleur urbain (ICU). Ce phénomène se traduit par l’augmentation de la température en ville la nuit. Lors des vagues de chaleur ce phénomène peut causer un inconfort voire une surmortalité. Dans le contexte du changement climatique et d’une dynamique démographique importante, la thèse est réalisée sur le territoire de Rennes Métropole. Au cours de cette thèse, plusieurs objectifs sont poursuivis. Dans un premier temps, l’étude porte sur l’analyse de la variabilité spatiale de l’ICU selon l’occupation du sol et des formes urbaines. Afin d’observer ce phénomène sur le territoire de Rennes Métropole, plusieurs réseaux de mesuressont mis en place. Le premier réseau concerne l’échelle de l’agglomération avec 22 stations météorologiques. Le second réseau est établi à l’échelle intra-urbaine avec l’installation de 20 capteurs de température. Enfin, le troisième réseau de mesures vise à observer la variabilité de l’ICU au sein de deux quartiers rennais et d’une petite ville, Vezin-le-Coquet. Dans un second temps, des modèles de spatialisation de l’ICU sont construits à l’échelle de l’agglomération, puis, à l’échelle intra-urbaine. Ces modèles permettent de réaliser des cartes de l’ICU pour ces deux échelles emboitées. Dans un troisième temps, l’analyse temporelle est établie par la relation entre les types de temps et l’ICU. Cette analyse permet de construire un modèle de prévision de l’ICU quotidien. A partir de ce modèle, l’ICU quotidien est projeté par les sorties régionalisées des modèles du changement climatique. Plusieurs outils d’aide à la décision sont proposés à partir des modèles développés de l’ICU. L’exposition de l’agglomération rennaise au changement climatique est évaluée à partir des cartes de l’ICU et de plusieurs indices projetés par les sorties régionalisées des modèles du changement climatique
Urban development, characterized by the presence of buildings and impervious surfaces, modify the local climate and in particular, enhance the urban heat island (UHI). This phenomenon raises temperatures in cities at night, which could cause discomfort and over-mortality during heat waves. In the context of climate change and important population dynamics, this thesis is carried out in the Rennes Metropolitan area (in Brittany). Firstly, this thesis focuses on the spatial analysis of UHI variability according to land use and urban forms. To observe UHI in the Rennes Metropolitan area, a network of multiple measurement types were implemented at various scale. 1) a network of 22 permanents weather stations located in urban/rural sites; 2) a network of 20 temperature sensors placed in intra-urban area; and 3) a network of temperature measurements in two neighborhoods of Rennes and a small town, Vezin-le-Coquet. Secondly, spatial models of UHI were designed in this thesis at both the urban agglomeration and intra-urban scale. This multi-scale approach produced UHI map for these nesting-scales. Thirdly, this thesis determined the temporal variability of UHI by looking at the interaction between weather types and UHI. This analysis produced a statistical model of daily UHI magnitude according to meteorological observations. This model combined with data from downscaled climate change scenarios provided future projections of UHI. Lastly, this study deals with tools for town planning to prevent intensive UHI. UHI maps and downscaled climate change scenarios defined the risk assessment in the Rennes Metropolitan area

This thesis presents a research on quantitative assessment of temperature in urban residential settings and its influence on extreme temperature exposure to humans, energy usage and indoor air pollution in households, which is of significance at the time when climate change mitigation approaches are being considered. The work aimed to quantify indoor temperature profile; indoor-outdoor temperature relationship; indoor temperature occupant experience; and the association between temperature (indoor and outdoor) and air quality in houses. A temperature relationship model was developed applying advanced statistical methods to over one-year empirical temperature (indoor and outdoor) data sets of 90 houses in Brisbane, Australia.

Améliorer l'efficacité énergétique des bâtiments et limiter l'ilot de chaleur urbain est une priorité, en particulier dans les centres-villes historiques, composés de bâtiments peu isolés. Un des leviers d’action envisagés est l'isolation des parois. Cependant, la rénovation des parois anciennes rencontre de nombreux obstacles (technologiques, architecturaux, urbains). Ces parois ont notamment un comportement hygrothermique spécifique, qu’il convient de prendre en compte pour éviter l’apparition de pathologies et estimer correctement les déperditions énergétiques. Il est donc primordial d’intégrer les transferts hygrothermiques à travers les parois pour simuler efficacement le bâti ancien. Néanmoins, la plupart des modèles à l’échelle urbaine négligent les transferts hydriques à travers les parois.Cette thèse propose une nouvelle méthode de résolution numérique pour les transferts hygrothermiques, qui est adaptée aux différentes contraintes de la modélisation à l’échelle urbaine (résolutions spatio-temporelles, méthode numérique etc.). La validation est réalisée en deux temps : une partie numérique et une partie expérimentale. La validation numérique est effectuée par une comparaison inter-modèle, en s’appuyant sur quinze compositions de parois et trois climats. La validation expérimentale utilise les données enregistrées dans plusieurs bâtiments rénovés à partir de matériaux biosourcés et instrumentés dans le centre médiéval de la ville de Cahors.Ensuite, les transferts couplés de masse et de chaleur dans les parois sont intégrés dans le modèle de climat urbain TEB (Town Energy Balance), en utilisant la méthode développée et validée. La pertinence de cette nouvelle version de TEB pour représenter le centre-ville médiéval de Cahors est évaluée par comparaison avec des mesures in-situ. Une amélioration significative est constatée pour la simulation de l’humidité relative intérieure. L’impact des transferts d’humidité est discuté à plusieurs échelles.Finalement, la réhabilitation des parois anciennes des bâtiments du centre-ville de Cahors est étudiée à partir de plusieurs types d’isolant thermique positionnés à l’intérieur ou à l’extérieur. Ces scénarios de réhabilitation sont simulés en utilisant la version modifiée de TEB incluant les transferts d’humidité à travers les parois. Leur pertinence est comparée, vis-à-vis des enjeux énergétiques, du confort intérieur et extérieur, de la conservation du patrimoine et de la durabilité des parois. Des recommandations sont formulées en fonction du type de parois
Improving the energy efficiency of buildings and mitigating the urban heat island is a priority, particularly in historical city centres, which are composed of poorly insulated buildings. One of the levers of action envisaged is wall insulation. However, the retrofit of old walls faces numerous obstacles (technological, architectural, urban). In particular, these walls have a specific hygrothermal behavior, which needs to be taken into account to avoid the appearance of pathologies and to correctly estimate energy losses. It is therefore essential to integrate hygrothermal transfers through the walls to effectively simulate old buildings. However, most urban-scale models neglect moisture transfer through walls.This thesis proposes a new numerical method for solving hygrothermal transfers, which is adapted to the various constraints of urban-scale modeling (spatio-temporal resolutions, numerical method, etc.). Validation is carried out in two steps: a numerical part and an experimental part. Numerical validation is based on an inter-model comparison, using fifteen wall compositions and three climates. Experimental validation uses data recorded in several buildings retrofitted with bio-based materials and instrumented in the medieval city centre of Cahors.Then, coupled heat and mass transfer through walls are integrated into the TEB (Town Energy Balance) urban climate model, using the developed and validated method. The suitability of this new version of TEB to represent the medieval town center of Cahors is assessed by comparison with in-situ measurement. A significant improvement is observed when simulating indoor relative humidity. The impact of moisture transfer is discussed at several scales.Finally, the retrofit of the old walls of buildings in the city center of Cahors is studied using several types of thermal insulation positioned inside or outside. These retrofitting scenarios are simulated with the modified version of TEB, including moisture transfer through the walls. Their relevance is compared with regard to energy issues, indoor and outoor comfort, heritage conservation and wall durability. Recommendations are given according to the type of wall

O planejamento ou a readequação urbana de espaços abertos são capazes de promover a melhoria das condições térmicas exteriores, e assim, influenciar qualitativamente o uso de espaços abertos. Neste contexto, esta pesquisa tem como objetivo analisar a sensação térmica da população de Curitiba e propor um modelo de predição de sensação térmica adequado às condições climáticas locais. Os locais de estudo são ruas de pedestres da Rua XV de Novembro e cercanias. Foram realizados 15 levantamentos de campo, sendo 14 dias no período entre janeiro e agosto de 2009 e um dia em junho de 2010, totalizando 15 situações urbanas distintas. Os levantamentos ocorreram entre 10h00 e 15h00 em dias de semana e foram monitorados dados climáticos e levantados dados pessoais, com o uso de questionários. A metodologia utilizada compreendeu quatro etapas: análise da relação entre as características urbanas e a sensação térmica; análise da sensação térmica real, a partir dos dados coletados; análise da sensação térmica por meio dos índices PMV, PET e UTCI; e proposição de um modelo preditivo de sensação térmica para Curitiba. Da análise dos atributos urbanos e sua relação com as variáveis climáticas e a sensação térmica, concluiu-se que a orientação do cânion e o perfil vertical das fachadas são importantes para compreender o comportamento das variáveis climáticas e para propor sugestões que melhorem o conforto térmico no ambiente urbano. A análise dos índices PMV, PET e UTCI mostrou a necessidade de calibração destes índices para a avaliação da sensação térmica da população de Curitiba. Ao analisar as respostas de sensação térmica e as variáveis climáticas verificou-se que as três categorias de sensação térmica se misturam entre si, não havendo clara distinção entre o grupo de conforto e os de desconforto para o frio e para o calor, o que dificulta a definição de faixas climáticas de conforto térmico para Curitiba. Em relação aos dois métodos estatísticos utilizados para a definição do modelo de predição, a Função Discriminante Linear (FDL) apresentou melhor desempenho que o Modelo de Regressão Logístico (MRL), tendo taxa total de acerto de 53%, se mostrando adequada para a avaliação da sensação térmica da população analisada.
Urban planning and modifications in open spaces are able to promote the improvement of outdoor thermal conditions and thus qualitatively influence the use of open spaces. In this context, this research aims to analyze the thermal sensation of the population of Curitiba and propose a model for predicting thermal sensation suited to local climatic conditions. The study was carried out at the pedestrian street Rua XV de November and adjacent streets. As a whole, fifteen monitoring campaigns were carried out (14 days in the period between January and August 2009 and one day in June 2010), encompassing fifteen different urban situations. The surveys took place between 10h00 and 15h00 on week days and weather data were monitored and personal data collected, using questionnaires. The method comprised four steps: analysis of the relationship between urban characteristics and thermal sensation; analysis of observed thermal sensation vote; analysis of calculated thermal sensation expressed by the indeces PMV, PET and UTCI and proposal of a thermal sensation predictive model for Curitiba. From the analysis of urban attributes and their relationship with climatic variables and thermal sensation, it was concluded that the canyon orientation and the vertical profile of the facades are important to understand the behavior of the climatic variables and to propose suggestions to improve the thermal comfort in urban environment. The analysis of PMV, PET and UTCI indeces showed the need for calibration to evaluate the thermal sensation of the population of Curitiba. The analysis between the observed thermal sensation and the climatic variables showed that the three categories of thermal sensation are mixed among themselves, with no clear distinction between the group of comfort and cold/heat discomfort, making difficult the definition of climatic zones of thermal comfort for Curitiba. Regarding both statistical methods used to develop the thermal sensation predictive model, the Linear Discriminant Function performed better than the Logistic Regression Model and the total success rate of 53% is adequate for the thermal sensation evaluation of the population analyzed.

Improvements for environmental monitoring and assessment were achieved to advance our understanding of sea-land interactions and nutrient cycling in a coastal bay.; The comprehensive assessment techniques for monitoring of water quality of a coastal bay can be diversified via an extensive investigation of the spatiotemporal nutrient patterns and the associated eco-hydrological trends in a coastal urban region. With this work, it is intended to thoroughly investigate the spatiotemporal nutrient patterns and associated eco-hydrological trends via a two part inquiry of the watershed and its adjacent coastal bay. The findings show that the onset of drought lags the crest of the evapotranspiration and precipitation curve during each year of drought. During the transition year, ET and precipitation appears to start to shift back into the analogous temporal pattern as the 2005 wet year. NDVI shows a flat receding tail for the September crest in 2005 due to the hurricane impact signifying that the hurricane event in October dampening the severity of the winter dry season in which alludes to relative system memory. The k-means model with 8 clusters is the optimal choice, in which cluster 2 at Lower Tampa Bay had the minimum values of total nitrogen (TN) concentrations, chlorophyll a (Chl-a) concentrations, and ocean color values in every season as well as the minimum concentration of total phosphorus (TP) in three consecutive seasons in 2008. Cluster 5, located in Middle Tampa Bay, displayed elevated TN concentrations, ocean color values, and Chl-a concentrations, suggesting that high colored dissolved organic matter values are linked with some nutrient sources. The data presented by the gravity modeling analysis indicate that the Alafia River Basin is the major contributor of nutrients in terms of both TP and TN values in all seasons. Such ecohydrological evaluation can be applied for supporting the LULC management of climatic vulnerable regions as well as further enrich the comprehensive assessment techniques for estimating and examining the multi-temporal impacts and dynamic influence of urban land use and land cover.
B.S.C.E.
Bachelors
Engineering and Computer Science
Civil Engineering

This thesis looks at the practice of climate modelling at the urban scale in relation to projections of future climate. It responds to the question of how climate models perform in a policy context, and how these models are translated in order to have agency at the urban scale. It considers the means and circumstances through which models are constructed to selectively represent urban realities and potential realities in order to explore and reshape the built environment in response to a changing climate. This thesis is concerned with an interdisciplinary area of research and practice, while at the same time it is based on methodologies originating in science and technology studies which were later applied to architecture and planning, geography, and urban studies. Fieldwork consisted of participant-observation and interviews with three groups of practitioners: firstly, climate impacts modellers forming part of the Adaptation and Resilience in a Changing Climate (ARCC) programme; secondly, planners and adaptation policymakers in the cities of Manchester and London; and thirdly, boundary organisations such as the UK Climate Impacts Programme (UKCIP). Project and climate policy material pertinent to these projects and the case study cities were also analysed in tandem. Of particular interest was the common space shared to researchers and stakeholders where modelling results were explained, contextualised, and interrogated for policy-relevant results. This took the form of stakeholder meetings in which the limits of the models in relation to policy demands could be articulated and mediated. In considering the agency of models in relation to uncertainties, it was found that although generated in a context of applied science, models had a limited effect on policy. As such, the salience of urban climatic risk-based assessment for urban planning is restrained, because it presupposes a quantitative understanding of climate impacts that is only slowly forming due to societal and governmental pressures. This can be related both to the nature of models as sites of exploration and experimentation, and to the distribution of expertise in the climate adaptation community. Although both the research and policy communities operate partly in a common space, models and their associated tools operate at a level of sophistication that policy-makers have difficulty comprehending and integrating into planning policy beyond the level of simple guidance and messages. Adaptation in practice is constrained by a limited understanding of climate uncertainties and urban climatology, evident through the present emphasis on catch-all solutions like green infrastructure and win-win solutions rather than the empowerment of actors and a corresponding distribution of adequate resources. An analysis is provided on the means by which models and maps can shape climate adaptation at scales relevant for cities, based on considerations of how models gain agency through forms of encoded expertise like maps and the types of interaction between science and policy that they imply.

Thesis (S.M. in Building Technology)--Massachusetts Institute of Technology, Dept. of Architecture, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 127-131).
Thermal simulation of buildings is a requisite tool in the design of low-energy buildings, yet, definition of weather boundary conditions during simulation of urban buildings suffers from a lack of data that accounts for the UHI effect. To overcome barriers preventing the use of more representative climate data in building thermal simulations, this thesis evaluates two recently developed methods for generating urban weather files from a rural station. The two methods examined are computationally inexpensive. The first method is the urban weather generator (UWG) a model developed by Bueno et al. and the second is a temperature alteration algorithm developed by Crawley 2008. Actual weather data is used to validate the modeled urban data. Actual and modeled weather data is then used in simulation of a typical single-family and small office building to quantify normalized energy use metrics of urban buildings. Applying the UWG to appropriate rural weather data reduces the error associated with energy prediction of an urban single-family building by nearly half (21% to 13%). If the Crawley algorithm is applied to rural data, the resulting weather data will produce simulation results that are lower (- 8%) and upper limits (+ 11%) to the actual urban energy simulation results. For applications that either require feedback with the urban design or have extensive data on the urban morphology we recommend the use of the UWG with a radius of 500 m. For applications that lack urban site data and are order of magnitude estimations, the Crawley algorithm generally is able to provide extremes of the predicted EUI.
by Michael A. Street.
S.M.in Building Technology

Le GIEC (groupe d’expert Intergouvernemental sur l’Evolution du Climat) dans leur 4 ème rapport souligne que les villes européennes seront impactées par des épisodes caniculaires plus fréquents et plus intenses dû aux modifications climatiques ayant lieu au cours du XXI ème siècle. La ville, espace climatique particulier, sensiblement plus chaud que son espace environnant amplifie le phénomène de l’îlot de chaleur urbain (ICU). Pour la ville de Paris, les îlots de chaleur urbains peuvent dépasser de 8 à 10°C les températures relevées quelques kilomètres plus loin. Cet effet est d’autant plus néfaste lors de période caniculaire comme a connu la France en 2003, 2006, 2010 ou bien même en 2015. La connaissance sur le phénomène de la canicule nécessite de mettre en relation des données autant spatiales que temporelles afin de définir des zones à risques .Pour pouvoir simuler une canicule, le modèle SURFEX-TEB, conçu par Météo-France, CNRS, a été choisi. Il permet d’estimer la température en ville à partir de conditions climatiques des plus hautes atmosphères. Ces prévisions sont importantes notamment en période de canicule où les écarts de température entre la ville et sa banlieue peuvent dépasser 8C°. Le risque caniculaire, induit par les ICU, est complexe à appréhender et à représenter.Pour caractériser, appréhender et représenter la canicule, avec l’aide du modèle SURFEX-TEB, nous avons effectué une assimilation avec des mesures réalisées pendant la canicule de 2015 sur Paris. Cette assimilation met en évidence par exemple les phénomènes d’accumulation et l’impact des configurations des appartements sur les températures intérieures et extérieures. Nos différentes configurations ont permis de confirmer l’importance de considérer les températures intérieures lors de périodes caniculaires.Ce travail de recherche propose donc un éclairage spécifique et technique de la représentation des canicules. Son objectif est une meilleure représentation des canicules et l’estimation de leur dangerosité en fonction de la durée du phénomène, de son intensité et des caractéristiques urbaines et humaines. Des cartes décrivant la canicule et sa dangerosité sont mises en valeur grâce à l’élaboration d’un site web grand public.Les résultats de cette recherche soulèvent une interrogation sur les seuils de canicule. Ils soulignent l’importance d’introduire un seuil de canicule intérieur et démontrent le rôle de la configuration urbaine et en particulier des types d’habitation pour mieux prendre en compte la dangerosité des canicules et espérer mieux atténuer leurs effets
The IPCC (Intergovernmental Panel on Climate Change) in its 4th report underlines that the European cities will be impacted by more frequent and more intense scorching episodes due to the climatic modifications taking place during the XXIth century. Peculiar climatic areas, significantly hotter than their surroundings, cities amplify the phenomenon of the urban heat island (UHI). In the example of Paris, the urban islands of heat can exceed by 8°C to 10°C the temperatures measured a few kilometers away. This effect is all the more fatal as heat wave periods become more and more regular (2003, 2006, 2010, 2015). The knowledge on the heat wave phenomenon requires to put in relation spatial and temporal data so as to define high-risk areas.To be able to simulate a heat wave, the SURFEX-TEB model, designed by Météo-France, and CNRS, was chosen. It allows to estimate the temperature in town from weather conditions of the highest atmospheres. These forecasts are particularly important in heat wave periods where temperature differences between cities and suburban areas can exceed 8°C. The heat wave risk, resulting from the UHI, is complex to both understand and represent.To characterize, understand and represent the heat wave by the means of the SURFEX-TEB model, we made a data fusion with measures realized during the 2015 heat wave in Paris. This assimilation highlights, for instance, the accumulation phenomena and the impact of the apartments configuration on the inside and outside temperatures. Our various configurations allowed to confirm the importance of taking into account the internal temperatures during heat waves periods.This research thus proposes a specific and technical perspective of the heat waves representation. Its objectives are a better representation of heat waves and a sharper estimation of their dangerousness according to the phenomenon duration, its intensity and the urban and human features. Maps describing the heat wave and its dangerousness are highlighted thanks to the elaboration of a public Web site.The results of this research rise an interrogation on the thresholds of heat wave. They underline the importance to introduce an internal threshold of heat wave and demonstrate the role of the urban configuration, particularly the types of house. This should contribute to better take into account the dangerousness of heat waves and to improve the mitigation of their effects

La question de la conception urbaine du futur est à la une des questions importantes et critiques de notre société. On peut citer comme exemples : le réchauffement de la planète, la biodiversité en péril, les transitions économiques/sociales/culturelles, les prévisions d’une augmentation considérable de la population citadine, les mutations des transports et le changement des formes urbaines, pour ne citer que ceux-là. Toutes ces questions sont au cœur des problématiques actuelles et font partie des contraintes auxquelles nous devons faire face dans la conception urbaine de demain...Ce travail entend reconsidérer l’approche classique de conception et aménagement urbain et développer une approche globale assistée par ce que l’on nommera ici une maquette numérique procédurale. Car la ville en tant que système complexe est constituée de sous-systèmes très variés ; physique et perceptible ; exemple : [bâti, réseaux routiers, infrastructure, verdure] et non-physique ; sans forme visible, exemple : [mobilité des citadins, activités interactives liées à la temporalité…]. Un respect des liens de ses sous-systèmes : sociaux, techniques est nécessaire dans ce travail. Des recherches dans le domaine urbain dévoilent l’importance du besoin d’études globales approfondies dans l’aspect comportemental et social du citadin ainsi que son interaction spatio-temporelle dans la ville, un aspect très important, mais souvent pris à la légère dans la conception urbaine. Pourtant, les activités répétitives quotidiennes du citadin représentent un aspect essentiel devant alimenter toute intervention urbaine. Cette orchestration de milliers de citadins comporte une dimension socio-temporel-interactive, décisive et vitale permettant de mesurer le « succès » ou non d’une ville. Cet aspect invisible de vie urbaine constitue un phénomène essentiel de réussite urbaine que Jan Gehl qualifie d’« inter-Play (l’entrejeu) entre l’utilisat-eur(rice) [agent dynamique vivant] et l’objet [physique statique]. D’après Jan Gehl , le succès d’une ville se mesure par sa capacité à attirer l’utilisateur(rice) à passer plus de temps dans ses places et ses rues. Sans ce jeu dynamique vivant entre l’utilisateur(rice) et l’objet, la ville est sans âme. Ce travail essaye en même temps de célébrer la puissance technologique en soulignant la nécessité et supériorité du pouvoir de décision humaine sur celui de la machine. De manière à montrer que l’intelligence humaine reste indispensable à la pensée, l’observation, la synthèse et le pilotage du projet. Ceci redonne à l’homme sa place de leader et dirigeant pour atteindre des résultats plus flexibles et adaptables à des schémas généraux à grande échelle ou refocalisés sur l’expérience singulière individuelle à l’échelle de l’utilisat-eur(rice). Cette capacité et flexibilité permet d’intégrer des nouveaux éléments ou de nouvelles performances qui surgissent avec le développement soit des applications utilisées soit de nouvelles découvertes sur le terrain
The question of urban design of the future is one of the important and critical issues of our society. The global warming, the biodiversity at risk, the economic/social/cultural transitions, the predictions of a significant increase in the urban population, the changes in transportation patterns, and changes in urban forms, to quote only a few... All these questions are at the heart of current issues and are part of the constraints we must face in the urban design of tomorrow. Faced with such a situation, it seems risky today to continue to think of the city with approaches or design processes that are based on yesterday’s realities. As Albert Einstein puts it, "we cannot solve our problems using the same way of thinking that we had when we created them". The environmental issues (global warming, biodiversity, etc ...) are factors of vulnerability in the current city in such a way that it is generally accepted (ScienceNet) that built environments must now , more than in the past, be designed in a way that is "respectful of the environment ". We are encouraged to develop a socially responsible and "environmentally friendly" mentality, an approach that looks beyond the immediate and individual interest to achieving stable, long-term common goals. This is only possible if we use and intelligently and fairly all the resources at our disposal, in this case our knowledge, the natural resources, the socio-economic, the geographical as well as the technological advancements. Because, if technology and digital have become of common daily used by the citizens, urban design and architectural disciplines seems however to have a hard time integrating it completely in an intelligent and systemic way as do today other disciplines such as medicine and aeronautics...This work tries to develop a methodology of urban design based on a combination of digital applications, the effort of a collective intelligence as well as ideas, concepts and techniques proposed by a handful of philosophers, historians, psychologists, architects, town planners above mentioned who marked the history of cities. It is therefore from this heterogeneous marriage of techniques and thoughts augmented by recent geospatial technologies that this research intends to base its point of view on the study of urban complexity in order to try to cope with urban problems in constant form. evolution

The purpose of this study is to develop an improved human radiation exchange model for use by planners and researchers. Although applicable for all environments, emphasis will be on urban areas. All processes of radiation exchange between the human body surface and surrounding environments were investigated through human body area factors (effective radiation area factor, feff, and projected area factor, fp), existing human thermal exchange models and three-dimensional (3D) computer simulation models with collected microclimatic data. For new body area factors, a sample of standing contemporary Canadian adults in normal-weight (male: 31 persons, female: 40) and over-weight (male: 48, female: 20) body mass index (BMI) categories were analyzed. A 3D mean body model was created for each category. Only very small differences in feff and fp were found between genders and BMI categories. Differences in feff and fp values between this study and previous studies were very large, up to 0.101 and 0.173, respectively. Another common body posture, walking, was also studied for the normal-weight male and female BMI categories. 3D computer walking body models at four stride positions were created. The directionless fp values for walking posture had minor differences between genders and positions in a stride. However, the differences of mean directional fp values between azimuth angles were great enough (up to 0.072) to create important differences in modeled radiation receipt. When both standing and walking postures are considered, the mean feff value of standing (0.826) and walking (0.846), 0.836, could be used. However, fp values should be selected carefully because differences between directional and directionless fp values were large enough that they could influence the estimated level of human thermal sensation. A new human radiation exchange model was developed using the new body area factors and compared with five existing models and one method (Burt, COMFA, MENEX, OUT_SET* and RayMan models and the six-directional method) using collected microclimatic data observed in Guelph, Ontario, Canada. Most differences between models came from absorbed solar radiation, especially absorbed direct beam solar radiation because of differences in fp* (=fp×feff) and feff or some missing components (feff or view factors). The lowest differences between the new model and the RayMan model alter the net all-wave radiation estimate up to 29 Wm-2, which can be significant in the human thermal exchange model. For 3D computer estimation, a new human-urban radiation exchange simulation model was developed combining the new human radiation exchange model and improved urban area factors (i.e., albedos and view factors of sunny and shaded building, ground and vegetation surfaces). The results of the new computer model were compared with microclimatic data collected in Nanaimo, B.C., Canada and Changwon, Republic of Korea as well as with two other 3D computer simulation programs, RayMan Pro and ENVI-met 3.1. The differences between the collected data and the new model were very small. Their correlation was very strong, over 0.99 for total radiation. RayMan Pro and ENVI-met 3.1 programs had larger differences, and their correlations with measured data were weaker than the new model’s. Accurate meteorological and urban setting data should be obtained for better results. The new model will give planners and researchers a simple tool to estimate accurate radiation effects in complex urban areas.
Graduate

Heatwaves are among the most dangerous extreme weather events, and their occurrence is projected to significantly increase over Europe in a climate change scenario. Densely urbanized regions as cities, are more vulnerable to extreme hot weather events, than rural areas, due to pre-existing UHI effect. The present work evaluates the WRF model sensitivity to landuse and Urban Canopy Model (UCM) parametrizations, during a heat wave event occurring in Stockholm region. The landuse sensitivity test compares the model results produced with three different landuse datasets, showing that using a more updated and high-resolution dataset increases the model skill simulating wind and temperature fields. The UCM sensitivity, compared the model performance coupled with two UCMs, SLUCM and BEP model, using a high resolution landuse dataset with three different urban categories. The simulated results showed that these models are strongly dependent on the parameters used by each model to describe the city geometry and proprieties, besides this, using the BEP model increased the model skill simulating the u and v wind components, but the differences found for the temperature field were insignificant.
As ondas de calor estão entre os mais perigosos fenómenos de tempo extremo, sendo que num cenário de alterações climáticas, a frequência da sua ocorrência está projetada para aumentar significativamente na Europa. Zonas densamente urbanizadas, como as cidades, estão mais vulneráveis a eventos de temperaturas extremas do que as zonas rurais envolventes devido ao efeito de ilha de calor urbano pré-existente. O presente trabalho pretende avaliar a sensibilidade do modelo WRF aos dados do uso do solo e à parametrização da canópia urbana, durante um evento de ilha de calor, na região de Estocolmo. Para o teste de sensibilidade ao uso do solo foram utilizadas três base de dados diferentes. Os resultados mostraram que uma base de dados mais atualizada e com uma maior resolução aumentam a performance do modelo nos campos do vento e da temperatura. Para o teste de sensibilidade às parametrizações da canópia urbana, foram comparadas duas simulações produzidas com o acoplamento de dois modelos de parametrização da canópia urbana (UCM) diferentes, o Single Layer Urban Canopy Model (SLUCM) e o Building Effect Parametrization Model (BEP), utilizando uma base de dados de uso do solo de alta resolução, com três categorias urbanas diferentes. Os resultados mostraram que estes modelos dependem significativamente dos parâmetros utilizados para descrever a geometria e as propriedades da cidade, contudo, o uso do modelo BEP permitiu melhorar a simulação das componentes u e v, enquanto que para o campo da temperatura, os resultados não apresentaram diferenças significativas.
Mestrado em Ciências do Mar e da Atmosfera

Urban heat island (UHI) is a region of increased air temperature in the canopy layer and boundary layer of the atmosphere above the town or industrial agglomeration in comparison with rural surroundings. The difference in temperature increases with the size of the city. This study describes the dependence of the intensity UHI Central European cities on their size and position of their weather station. It uses a multiple linear regression model. The dependent variable Y entering the model (data from 40 cities) are UHImean and UHImax. They are calculated as difference in air temperature between the urban and the relevant rural weather station. The average intensity of the urban heat island (UHImean) is the average value of the UHI of all available data in the analyzed period (hourly measurements of air temperature [řC] for the years 1994-2012). The data are only taken from night times records between 21:00 and 4:00 UTC and on days with the average total cloud cover at the city weather station less than 0,5. The maximum intensity of the urban heat island (UHImax) is the average maximum value of the UHI per night. The data are taken under the same conditions as in the case of UHImean. Independent variables X are the size of built-up area (X1) and the position of the weather station calculated using the...

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.

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.

Modelling solar radiation data at a high spatiotemporal resolution for an urban environment can inform many different applications related to climate action, such as urban agriculture, forest, building, and renewable energy studies. However, the complexity of urban form, vastness of city-wide coverage, and general dearth of climatological information pose unique challenges doing so. To address some climate action goals related to reducing building emissions in the City of Victoria, British Columbia, Canada, applied geomatics and climatology were used to model solar radiation data suitable for informing renewable energy feasibility studies, including photovoltaic system sizing, costing, carbon offsets, and financial payback. The research presents a comprehensive review of solar radiation attenuates, as well as methods of accounting for them, specifically in urban environments. A novel methodology is derived from the review and integrates existing models, data, and tools – those typically available to a local government. Using Light Detection and Ranging (LiDAR), a solar climatology, Esri’s ArcGIS Solar Analyst tool, and Python scripting, daily insolation (kWh/m2) maps are produced for the city of Victoria. Particular attention is paid to the derivation of daily diffuse fraction from atmospheric clearness indices, as well as LiDAR classification and generation of a Digital Surface Model (DSM). Novel and significant improvements in computation time are realized through parallel processing. Model results exhibit strong correlation with empirical data and support the use of Solar Analyst for urban solar assessments when great care is taken to accurately and consistently represent model inputs and outputs integrated in a methodological approach.
Graduate

The impact of climate change is increasingly important to the design of urban water infrastructure like stormwater systems, sewage systems and drinking water systems. Growing evidence indicates that the water sector will not only be affected by climate change, but it will reflect and deliver many of its impacts through floods, droughts, or extreme rainfall events. Water resources will change in both quantity and quality, and the infrastructure of stormwater and wastewater facilities may face greater risk of damage caused by storms, floods and droughts. The effect of the climate change will put more difficulties on operations to disrupted services and increased cost of the water and wastewater services. Governments, urban planners, and water managers should therefore re-examine development processes for municipal water and wastewater services and are adapt strategies to incorporate climate change into infrastructure design, capital investment projects, service provision planning, and operation and maintenance. According to the Intergovernmental Panel on Climate Change, the global mean temperature has increased by 0,7 °C during the last 100 years and, as a consequence, the hydrological cycle has intensified with, for example, more acute rainfall events. As urban drainage systems have been developed over a long period of time and design criteria are based upon climatic characteristics, these changes will affect the systems and the city accordingly. The overall objective of this thesis is to increase the knowledge about the climate change impacts on the stormwater system in Al Hillah city/Iraq. In more detail, the objective is to investigate how climate change could affect urban drainage systems specifically stormwater infrastructure, and also to suggest an adaptation plan for these changes using adaptation plans examples from international case studies. Three stochastic weather generators have been investigated in order to understand the climate and climate change in Al Hillah. The stochastic weather generators have been used in different kind of researches and studies; for example in hydrology, floods management, urban water design and analysis, and environmental protection. To make such studies efficient, it is important to have long data records (typically daily data) so the weather generator can generate synthetic daily weather data based on a sound statistical background. Some weather generators can produce the climate change scenarios for different kind of global climate models. They can be used also to produce synthetic data for a site that does not have enough data by using interpolation methods. To ensure that the weather generator is fitting the climate of the region properly, it should be tested against observed data, whether the synthetic data are sufficiently similar. At the same time, the accuracy of the weather generator is different from region to region and depends on the respective climate properties. Testing three weather generators GEM6, ClimGen and LARS-WG at eight climate stations in the region of Babylon governorate/Iraq, where Al Hillah is located, is one of the purposes of the first part of this study. LARS-WG uses a semi-parametric distribution (developed distribution), whereas GEM6 and ClimGen use a parametric distribution (less complicated distribution). Different statistical tests have been selected to compare observed and synthetic weather data for the same kind, for instance, the precipitation and temperature distribution (wet and dry season). The result shows that LARS-WG represents the observed data for Babylon region in a better way than ClimGen, whereas GEM6 seems to misfit the observed data. The synthetic data will be used for a first simulation of urban run-off during the wet season and the consequences of climate change for the design and re-design of the urban drainage system in Al Hillah. The stochastic weather generator LARS is then used to generate ensembles of future weather data using five Global Climate Models (GCMs) that best captured the full range of uncertainty. These Global Climate Models are used to construct future climate scenarios of temperature and precipitation over the region of Babylon Governorate in Iraq. The results show an increase in monthly temperatures and a decrease in the total amount of rain, yet the extreme rain events will be more intense in a shorter time. Changes in the amount, timing, and intensity of rain events can affect the amount of stormwater runoff that needs to be controlled. The climate change calculated projections may make existing stormwater-related flooding worse. Different districts in Al Hillah city may face more frequent stormwater floods than before due to the climate change projections. All the results that have been taken from the Global Climate Models are in a daily resolution format and in order to run the Storm Water Management Model it is important to have all data in a minimum of one hour resolution. In order to fulfill this condition a disaggregation model has been used. Some hourly precipitation data were required to calibrate the temporal disaggregation model; however none of the climate stations and rain gauges in the area of interest have hourly resolution data, so the hourly data from Baghdad airport station have been used for that calibration. The changes in the flood return periods have been seen in the projected climate change results, and a return period will only remain valid over time if environmental conditions do not change. This means that return periods used for planning purposes may need to be updated more often than previously, because values calculated based on the past 30 years of data may become unrepresentative within a relatively short time span. While return periods provide useful guidance for planning the effects of flooding and related impacts, they need to be used with care, and allowances have to be made for extremes that may occur more often than may be expected. In the study area with separated stormwater systems, the Storm Water Management Model simulation shows that the number of surface floods as well as of the floods increases in the future time periods 2050s and 2080s. Future precipitation will also increase both the flooding frequency and the duration of floods; therefore the need to handle future situations in urban drainage systems and to have a well-planned strategy to cope with future conditions is evident. The overall impacts on urban drainage systems due to the increase of intensive precipitation events need to be adapted. For that reason, recommendations for climate change adaptation in the city of Al Hillah have been suggested. This has been accomplished by merging information from the review of five study cases, selected based on the amount and quality of information available. The cities reviewed are Seattle (USA), Odense (Denmark), Tehran (Iran), and Khulna (Bangladesh).:Preface Acknowledgment Abstract Kurzfassung Contents List of Figures List of Tables List of Listing List of Abbreviation Introduction 1.1. Background of The Research 1.2. The Climate Change Challenge 1.3. Urban Water Systems and Climate Change 1.4. Climate Change and Urban Drainage Adaptation Plan 1.5. Objectives of the Research 1.6. Research Problems and Hypothesis 1.7. Dissertation Structure 1.8. Delimitations Climate History and Climate Change Projections in Al Hillah City Chapter One: State of the Art on Climate Change 2.1.1. The Earth’s Climate System 2.1.2. Climate Change 2.1.3. Emission Scenarios 2.1.4. Global Climate Change 2.1.5. Climate Models 2.1.6. Downscaling Chapter Two: Topography and Climate of the Study Area 2.2.1. Location 2.2.2. Topography 2.2.3. Climate Chapter Three: Climate Change - Methodology and Data 2.3.1. Methodology 2.3.1.1. Stochastic Weather Generators 2.3.1.2. Description of Generators Used in the Comparison 2.3.1.3. Statistical Analysis Comparison Test 2.3.2. Data 2.3.2.1. Required data for modelling 2.3.2.2. Historical daily data required for the weather generators 2.3.2.3. Minimum requirements 2.3.2.4. Data Availability Chapter Four: Results Analysis and Evaluation of Climate Change 2.4.1. Weather Generators Comparison Test results 2.4.1.1.The p-value test Temperature Comparison results Precipitation Comparison Results 2.4.2. LARS Weather Generator Future Scenario 2.4.2.1.1. Climate Change Scenarios for the region of Babylon governorate Storm Water System and Urban Flooding in Al Hillah City Chapter one: Urban Water Modelling 3.1.1. General Overview and Background 3.1.1.1. Storm water systems 3.1.2. Urban Runoff Models 3.1.3. An Overview of Runoff Estimation Methods 3.1.3.1. Computer Modelling in Urban Drainage 3.1.3.2.Statistical Rational Method (SRM) 3.1.4. Models Based on Statistical Rational Method 3.1.5. Urban Rainfall-Runoff Methods 3.1.6. Accuracy Level in Urban Catchment Models Chapter Two: Urban Water System in Al Hillah City and Data Requirement for Modelling 3.2.1. History 3.2.2. Current Situation 3.2.2.1. Urban water system Iraq 3.2.2.2. Urban Water description in Babylon governorate 3.2.2.3. Drinking water network 3.2.2.4. Sewerage infrastructure 3.2.3. Required data for modelling Chapter Three: Methodology to Disaggregate Daily Rain Data and Model Storm Water Runoff 3.3.1. Temporal Disaggregation (hourly from daily) 3.3.1.1. Background of Disaggregation 3.3.1.2. Disaggregation techniques 3.3.1.3. DiMoN Disaggregation Tool 3.3.1.4. Input Data 3.3.1.5. Methods Formerly Used 3.3.2. EPA Storm Water Management Model (SWMM) 3.3.2.1. Verification and Calibration 3.3.2.2. Stormwater Management Model PCSWMM 3.3.2.3. Complete support for all USEPA SWMM5 engine capabilities Chapter Four: Urban Flooding Results 3.4.1. Disaggregation of the daily rain data to hourly data 3.4.1.1.The 1 hour events properties 3.4.1.2. Estimating the rain events in each climate change scenario 3.4.1.3. Past, Current and future return periods 3.4.2. Storm Water Management Model PCSWMM Calibration 3.4.3.Return periods and Urban Floods 3.4.3.1.Network simulation 3.4.3.2.Properties with previous flooding problems 3.4.3.3.Storm water system simulation under 1 hour-2, 5 and 10 years return period 3.4.3.4.Storm water system simulation under 1 hour-25 years return period 3.4.3.5.Storm water system simulation under 1 hour-50 years return period 3.4.3.6. Storm water system simulation under 1 hour – 100, 200, 500 and 1000 years return period 3.4.3.7.Total Flooding Adaptation Plan for Al Hillah City Chapter One: International Case Studies 4.1.1. Historical precipitation analysis 4.1.2. Current and projected future climate change, impacts and adaptation plan for each selected city 4.1.2.1. Seattle 4.1.2.2. Odense 4.1.2.3. Tehran 4.1.2.4. Khulna 4.1.2.5. Melbourne 4.1.3. Drainage System of the Studied Cities 4.1.3.1. Drainage System in Seattle 4.1.3.2. Drainage System in Odense 4.1.3.3. Drainage System in Tehran 4.1.3.4. Drainage System in Khulna 4.1.3.5. Drainage System in Melbourne Chapter Two: Adaptation Plan for Al Hillah City 4.2.1. Conclusions from Adaptation Options Analysed 4.2.2. Suggestions for Al Hillah City 4.2.3. Adaptation Actions Overall Conclusion Bibliography
Die Auswirkungen des Klimawandels auf die Gestaltung der städtischen Wasserinfrastruktur wie Regenwasser, Kanalisation und Trinkwassersysteme werden immer wichtiger. Eine wachsende Anzahl von Belegen zeigt, dass der Wassersektor nicht nur durch den Klimawandel beeinflusst werden wird, aber er wird zu reflektieren und liefern viele seiner Auswirkungen durch Überschwemmungen, Dürren oder extreme Niederschlagsereignisse. Die Wasserressourcen werden sich in Quantität und Qualität verändern, und die Infrastruktur von Regen-und Abwasseranlagen kann einer größeren Gefahr von Schäden durch Stürme, Überschwemmungen und Dürren ausgesetzt sein. Die Auswirkungen des Klimawandels werden zu mehr Schwierigkeiten im Betrieb gestörter Dienstleistungen und zu erhöhten Kosten für Wasser-und Abwasserdienstleistungen führen. Regierungen, Stadtplaner, und Wasser-Manager sollten daher die Entwicklungsprozesse für kommunale Wasser-und Abwasserdienstleistungen erneut überprüfen und Strategien anpassen, um den Klimawandel in Infrastruktur-Design, Investitionsprojekte, Planung von Leistungserbringung, sowie Betrieb und Wartung einzuarbeiten. Nach Angaben des Intergovernmental Panel on Climate Change hat die globale Mitteltemperatur in den letzten 100 Jahren um 0,7 °C zugenommen, und in der Folge hat sich der hydrologische Zyklus intensiviert mit, zum Beispiel, stärkeren Niederschlagsereignisse. Da die städtischen Entwässerungssysteme über einen langen Zeitraum entwickelt wurden und Design-Kriterien auf klimatischen Eigenschaften beruhen, werden diese Veränderungen die Systeme und die Stadt entsprechend beeinflussen. Das übergeordnete Ziel dieser Arbeit ist es, das Wissen über die Auswirkungen des Klimawandels auf das Regenwasser-System in der Stadt Hilla / Irak zu bereichern. Im Detail ist das Ziel, zu untersuchen, wie der Klimawandel die Siedlungsentwässerung und insbesondere die Regenwasser-Infrastruktur betreffen könnte. Desweiteren soll ein Anpassungsplan für diese Änderungen auf der Grundlage von beispielhaften Anpassungsplänen aus internationalen Fallstudienvorgeschlagen werden. Drei stochastische Wettergeneratoren wurden untersucht, um das Klima und den Klimawandel in Hilla zu verstehen. Stochastische Wettergeneratoren wurden in verschiedenen Untersuchungen und Studien zum Beispiel in der Hydrologie sowie im Hochwasser-Management, Siedlungswasser-Design- und Analyse, und Umweltschutz eingesetzt. Damit solche Studien effizient sind, ist es wichtig, lange Datensätze (in der Regel Tageswerte) haben, so dass der Wettergenerator synthetische tägliche Wetterdaten erzeugen kann, dieauf einem soliden statistischen Hintergrund basieren. Einige Wettergeneratoren können Klimaszenarien für verschiedene Arten von globalen Klimamodellen erzeugen. Sie können unter Verwendung von Interpolationsverfahren auch synthetische Daten für einen Standort generieren, für den nicht genügend Daten vorliegen. Um sicherzustellen, dass der Wettergenerator dem Klima der Region optimal entspricht, sollte gegen die beobachteten Daten geprüft werden, ob die synthetischen Daten ausreichend ähnlich sind. Gleichzeitig unterscheidet sich die Genauigkeit des Wettergenerator von Region zu Region und abhängig von den jeweiligen Klimaeigenschaften. Der Zweck des ersten Teils dieser Studie ist es daher, drei Wettergeneratoren, namentlich GEM6, ClimGen und LARS-WG, an acht Klimastationen in der Region des Gouvernements Babylon / Irak zu testen. LARS-WG verwendet eine semi-parametrische Verteilung (entwickelte Verteilung), wohingegen GEM6 und ClimGen eine parametrische Verteilung (weniger komplizierte Verteilung) verwenden. Verschiedene statistische Tests wurden ausgewählt, um die beobachteten und synthetischen Wetterdaten für identische Parameter zu vergleichen, zum Beispiel die Niederschlags- und Temperaturverteilung (Nass-und Trockenzeit). Das Ergebnis zeigt, dass LARS-WG die beobachteten Daten für die Region Babylon akkurater abzeichnet, als ClimGen, wobei GEM6 die beobachteten Daten zu verfehlen scheint. Die synthetischen Daten werden für eine erste Simulation des städtischen Run-offs in der Regenzeit sowie der Folgen des Klimawandels für das Design und Re-Design des städtischen Entwässerungssystems in Hilla verwendet. Der stochastische Wettergenerator LARS wird dann verwendet, um Gruppen zukünftiger Wetterdaten unter Verwendung von fünf globalen Klimamodellen (GCM), die das gesamte Spektrum der Unsicherheit am besten abdecken, zu generieren. Diese globalen Klimamodelle werden verwendet, um zukünftige Klimaszenarien der Temperatur und des Niederschlags für die Region Babylon zu konstruieren. Die Ergebnisse zeigen, eine Steigerung der monatlichen Temperaturen und eine Abnahme der Gesamtmenge der Regen, wobei es jedoch extremere Regenereignissen mit höherer Intensivität in kürzerer Zeit geben wird. Veränderungen der Höhe, des Zeitpunkt und der Intensität der Regenereignisse können die Menge des Abflusses von Regenwasser, die kontrolliert werden muss, beeinflussen. Die Klimawandel-Prognosen können bestehende regenwasserbedingte Überschwemmungen verschlimmern. Verschiedene Bezirke in Hilla können stärker von Regenfluten betroffen werden als bisher aufgrund der Prognosen. Alle Ergebnisse, die von den globalen Klimamodellen übernommen wurden, sind in täglicher Auflösung und um das Regenwasser-Management-Modell anzuwenden, ist es wichtig, dass alle Daten in einer Mindestauflösung von einer Stunde vorliegen. Zur Erfüllung dieser Bedingung wurde ein eine Aufschlüsselungs-Modell verwendet. Einige Stunden-Niederschlagsdaten waren erforderlich, um das zeitliche Aufschlüsselungs-Modell zu kalibrieren. Da weder die Klimastationen noch die Regen-Messgeräte im Interessenbereich über stundenauflösende Daten verfügt, wurden die Stundendaten von Flughäfen in Bagdad verwendet. Die Veränderungen in den Hochwasserrückkehrperioden sind in den projizierten Ergebnissen des Klimawandels ersichtlich, und eine Rückkehrperiode wird nur dann über Zeit gültig bleiben, wenn sich die Umweltbedingungen nicht ändern. Dies bedeutet, dass Wiederkehrperioden, die für Planungszwecke verwendet werden, öfter als bisher aktualisiert werden müssen, da die auf Grundlage von Daten der letzten 30 Jahre berechneten Werte innerhalb einer relativ kurzen Zeitspanneunrepräsentativ werden können. Während Wiederkehrperioden bieten nützliche Hinweise für die Planung die Effekte von Überschwemmungen und die damit verbundenen Auswirkungen, müssen aber mit Vorsicht verwendet werden, und Extreme, die öfter eintreten könnten als erwartet, sollten berücksichtigt werden. Im Studienbereich mit getrennten Regenwassersystemen zeigt die Simulation des Regenwasser-Management-Modells, dass sich die Anzahl der Oberflächenhochwasser sowie der Überschwemmungen im Zeitraum 2050e-2080 erhöhen wird. Zukünftige Niederschläge werdensowohl die Hochwasser-Frequenz als auch die Dauer von Überschwemmungen erhöhen. Daher ist die Notwendigkeit offensichtlich, zukünftige Situationen in städtischen Entwässerungssystemen zu berücksichtigen und eine gut geplante Strategie zu haben, um zukünftige Bedingungen zu bewältigen. Die gesamten Auswirkungen auf die Siedlungsentwässerungssyteme aufgrund der Zunahme von intensiven Niederschlagsereignissen müssen angepasst werden. Aus diesem Grund wurden Empfehlungen für die Anpassung an den Klimawandel in der Stadt Hilla vorgeschlagen. Diese wurden durch die Zusammenführung von Informationen aus der Prüfung von fünf Fallstudien, ausgewählt aufgrund der Menge und Qualität der verfügbaren Informationen, erarbeitet,. Die bewerteten Städte sind Seattle (USA), Odense (Dänemark), Teheran (Iran), und Khulna (Bangladesch).:Preface Acknowledgment Abstract Kurzfassung Contents List of Figures List of Tables List of Listing List of Abbreviation Introduction 1.1. Background of The Research 1.2. The Climate Change Challenge 1.3. Urban Water Systems and Climate Change 1.4. Climate Change and Urban Drainage Adaptation Plan 1.5. Objectives of the Research 1.6. Research Problems and Hypothesis 1.7. Dissertation Structure 1.8. Delimitations Climate History and Climate Change Projections in Al Hillah City Chapter One: State of the Art on Climate Change 2.1.1. The Earth’s Climate System 2.1.2. Climate Change 2.1.3. Emission Scenarios 2.1.4. Global Climate Change 2.1.5. Climate Models 2.1.6. Downscaling Chapter Two: Topography and Climate of the Study Area 2.2.1. Location 2.2.2. Topography 2.2.3. Climate Chapter Three: Climate Change - Methodology and Data 2.3.1. Methodology 2.3.1.1. Stochastic Weather Generators 2.3.1.2. Description of Generators Used in the Comparison 2.3.1.3. Statistical Analysis Comparison Test 2.3.2. Data 2.3.2.1. Required data for modelling 2.3.2.2. Historical daily data required for the weather generators 2.3.2.3. Minimum requirements 2.3.2.4. Data Availability Chapter Four: Results Analysis and Evaluation of Climate Change 2.4.1. Weather Generators Comparison Test results 2.4.1.1.The p-value test Temperature Comparison results Precipitation Comparison Results 2.4.2. LARS Weather Generator Future Scenario 2.4.2.1.1. Climate Change Scenarios for the region of Babylon governorate Storm Water System and Urban Flooding in Al Hillah City Chapter one: Urban Water Modelling 3.1.1. General Overview and Background 3.1.1.1. Storm water systems 3.1.2. Urban Runoff Models 3.1.3. An Overview of Runoff Estimation Methods 3.1.3.1. Computer Modelling in Urban Drainage 3.1.3.2.Statistical Rational Method (SRM) 3.1.4. Models Based on Statistical Rational Method 3.1.5. Urban Rainfall-Runoff Methods 3.1.6. Accuracy Level in Urban Catchment Models Chapter Two: Urban Water System in Al Hillah City and Data Requirement for Modelling 3.2.1. History 3.2.2. Current Situation 3.2.2.1. Urban water system Iraq 3.2.2.2. Urban Water description in Babylon governorate 3.2.2.3. Drinking water network 3.2.2.4. Sewerage infrastructure 3.2.3. Required data for modelling Chapter Three: Methodology to Disaggregate Daily Rain Data and Model Storm Water Runoff 3.3.1. Temporal Disaggregation (hourly from daily) 3.3.1.1. Background of Disaggregation 3.3.1.2. Disaggregation techniques 3.3.1.3. DiMoN Disaggregation Tool 3.3.1.4. Input Data 3.3.1.5. Methods Formerly Used 3.3.2. EPA Storm Water Management Model (SWMM) 3.3.2.1. Verification and Calibration 3.3.2.2. Stormwater Management Model PCSWMM 3.3.2.3. Complete support for all USEPA SWMM5 engine capabilities Chapter Four: Urban Flooding Results 3.4.1. Disaggregation of the daily rain data to hourly data 3.4.1.1.The 1 hour events properties 3.4.1.2. Estimating the rain events in each climate change scenario 3.4.1.3. Past, Current and future return periods 3.4.2. Storm Water Management Model PCSWMM Calibration 3.4.3.Return periods and Urban Floods 3.4.3.1.Network simulation 3.4.3.2.Properties with previous flooding problems 3.4.3.3.Storm water system simulation under 1 hour-2, 5 and 10 years return period 3.4.3.4.Storm water system simulation under 1 hour-25 years return period 3.4.3.5.Storm water system simulation under 1 hour-50 years return period 3.4.3.6. Storm water system simulation under 1 hour – 100, 200, 500 and 1000 years return period 3.4.3.7.Total Flooding Adaptation Plan for Al Hillah City Chapter One: International Case Studies 4.1.1. Historical precipitation analysis 4.1.2. Current and projected future climate change, impacts and adaptation plan for each selected city 4.1.2.1. Seattle 4.1.2.2. Odense 4.1.2.3. Tehran 4.1.2.4. Khulna 4.1.2.5. Melbourne 4.1.3. Drainage System of the Studied Cities 4.1.3.1. Drainage System in Seattle 4.1.3.2. Drainage System in Odense 4.1.3.3. Drainage System in Tehran 4.1.3.4. Drainage System in Khulna 4.1.3.5. Drainage System in Melbourne Chapter Two: Adaptation Plan for Al Hillah City 4.2.1. Conclusions from Adaptation Options Analysed 4.2.2. Suggestions for Al Hillah City 4.2.3. Adaptation Actions Overall Conclusion Bibliography

Cape Town, South Africa, falls within a winter rainfall region, making it difficult to assess the feasibility of rain- and stormwater harvesting. The reason for this is because the region’s high water demand period coincides with the low rainfall summer season, thereby limiting the availability of this alternative water resource when most needed. During this study, rainwater harvesting for toilet flushing purposes, collected from roof surfaces, was practically assessed by means of inserted flow meters at a pilot study site in Kommetjie, Cape Town. The combined and single system roof- and land surface runoff yields and savings of commercial buildings within the Kommetjie business area, were also theoretically assessed by making use of a mathematical roof- and land surface runoff model specifically developed during this study. The statistical testing of the hypotheses statements relating to the pre- and post-harvesting savings at the pilot study building, compared against the average actual municipal water usage, were performed. Hypotheses testing were also performed in order to compare the theoretical rain- and stormwater runoff yields for the commercial business area against the average actual municipal water consumption. The conclusions drawn from this study indicated that valuable potable water, as well as related financial savings, can be achieved within a winter rainfall region, thereby making rain- and stormwater harvesting a feasible option for commercial businesses in Cape Town.
Environmental Sciences
M.Sc. (Environmental Management)

abstract: City administrators and real-estate developers have been setting up rather aggressive energy efficiency targets. This, in turn, has led the building science research groups across the globe to focus on urban scale building performance studies and level of abstraction associated with the simulations of the same. The increasing maturity of the stakeholders towards energy efficiency and creating comfortable working environment has led researchers to develop methodologies and tools for addressing the policy driven interventions whether it’s urban level energy systems, buildings’ operational optimization or retrofit guidelines. Typically, these large-scale simulations are carried out by grouping buildings based on their design similarities i.e. standardization of the buildings. Such an approach does not necessarily lead to potential working inputs which can make decision-making effective. To address this, a novel approach is proposed in the present study. The principle objective of this study is to propose, to define and evaluate the methodology to utilize machine learning algorithms in defining representative building archetypes for the Stock-level Building Energy Modeling (SBEM) which are based on operational parameter database. The study uses “Phoenix- climate” based CBECS-2012 survey microdata for analysis and validation. Using the database, parameter correlations are studied to understand the relation between input parameters and the energy performance. Contrary to precedence, the study establishes that the energy performance is better explained by the non-linear models. The non-linear behavior is explained by advanced learning algorithms. Based on these algorithms, the buildings at study are grouped into meaningful clusters. The cluster “mediod” (statistically the centroid, meaning building that can be represented as the centroid of the cluster) are established statistically to identify the level of abstraction that is acceptable for the whole building energy simulations and post that the retrofit decision-making. Further, the methodology is validated by conducting Monte-Carlo simulations on 13 key input simulation parameters. The sensitivity analysis of these 13 parameters is utilized to identify the optimum retrofits. From the sample analysis, the envelope parameters are found to be more sensitive towards the EUI of the building and thus retrofit packages should also be directed to maximize the energy usage reduction.
Dissertation/Thesis
Masters Thesis Architecture 2017

Understanding climate change and variability at urban scale is essential for water resource management, land use planning, and development of adaption plans. However, there are serious challenges to meet these goals due to unavailability of observed and / or simulated high resolution spatial and temporal climate data. Recent efforts made possible the availability of high resolution climate data from non-hydrostatic regional climate model (RCM) and statistically downscaled General Circulation Models (GCMs). This study investigates trends in climate and urbanization and their impact on surface water supply for the city of Addis Ababa, Ethiopia. The methodology presented in this study focused on the observed and projected NIMRHadGEM2- AO model and Special Report on Emissions Scenarios (SRES) of B2 and A2 of HadCM3 model are also employed for rainfall, maximum temperature and minimum temperature data using for climate analysis. Water Evaluation and Planning (WEAP) modeling system was used for determination of climate and urbanization impacts on water. Land-Sat images were analyzed using Normalized Differencing Vegetation Index (NDVI). Statistical downscaling model (SDSM) was employed to investigate the major changes and intensity of the urban heat island (UHI). The result indicates monthly rainfall anomalies with respect to the baseline mean showing wet anomaly in summer (kiremt) during 2030s and 2050s, and a dry anomaly in the 2080s under A2 and B2 scenarios with exception of a wet anomaly in September over the city. The maximum temperature anomalies under Representative Concentration Pathways (RCPs) also show warming during near, mid and end terms. The mean monthly minimum temperature anomalies under A2 and B2 scenarios are warm but the anomalies are much lower than RCPs. The climate under the RCP 8.5 and high population growth (3.3 %) scenario will lead to the unmet demand of 462.77 million m3 by 2039. Future projection of urban heat island under emission pathway of A2 and B2 scenario shows that, the nocturnal UHI will be intense in winter or dry season episodes in the city. Under A2 scenario the highest urban warming will occur during October to December (2.5 ºC to 3.2 ºC). Under RCP 8.5 scenario the highest urban warming will occur during October to December (0.5 ºC to 1.0 °C) in the 2050s and 2080s. Future management and adaptation strategies are to expand water supply to meet future demand and to implement demand side water management systems of the city and UHI
Environmental Sciences
Ph. D. (Environmental Management)

Indiana University-Purdue University Indianapolis (IUPUI)
Over the past two decades, northern parts of the United States have experienced extreme heat conditions. Some of the notable heat wave impacts have occurred in Chicago in 1995 with over 600 reported deaths and in Philadelphia in 1993 with over 180 reported deaths. The distribution of extreme heat events in Indianapolis has varied since the year 2000. The Urban Heat Island effect has caused the temperatures to rise unusually high during the summer months. Although the number of reported deaths in Indianapolis is smaller when compared to Chicago and Philadelphia, the heat wave in the year 2010 affected primarily the vulnerable population comprised of the elderly and the lower socio-economic groups. Studying the spatial distribution of high temperatures in the vulnerable areas helps determine not only the extent of the heat affected areas, but also to devise strategies and methods to plan, mitigate, and tackle extreme heat. In addition, examining spatial patterns of vulnerability can aid in development of a heat warning system to alert the populations at risk during extreme heat events. This study focuses on the qualitative and quantitative methods used to measure extreme heat events. Land surface temperatures obtained from the Landsat TM images provide useful means by which the spatial distribution of temperatures can be studied in relation to the temporal changes and socioeconomic vulnerability. The percentile method used, helps to determine the vulnerable areas and their extents. The maximum temperatures measured using LST conversion of the original digital number values of the Landsat TM images is reliable in terms of identifying the heat-affected regions.