Title: Spatiotemporal variability of global and regional climate models Author: RNDr. Lenka Crhová Department: Department of Atmospheric Physics Supervisor: RNDr. Eva Holtanová, Ph.D., Department of Atmospheric Physics Abstract: This thesis deals with variability of basic meteorological variables in global and regional climate models (GCMs and RCMs) outputs. Three different approaches were used in order to analyse climate models' ability to represent different aspects of variability of meteorological variables. The temporal variability with focus on its changes during a time and temporal scale components were studied. The relationship between air temperature and precipitation were employed in order to investigate the representation of spatiotemporal variability in climate models. Moreover, the influence of different characteristics of climate model simulations, such as the size of the RCM integration domain or differences between RCM and GCM simulations, were also considered. Two simulations of RCM ALADIN-Climate/CZ with different sizes of integration domain and their driving simulation of GCM ARPÉGE-Climat were used for analysis of the temporal changes in temperature mean and variability and selected simulations of RCMs and GCMs from the EURO-CORDEX and CMIP5 projects were employed for analyses of...

Les changements climatiques impactent de plus en plus la vie, le développement et la vulnérabilité de plusieurs communautés à travers le monde, lesquelles devant de plus en plus mitiger les risques naturels. Au Québec, la gestion des risques présente une philosophie de « retour à la normale » qui se penche davantage sur les dimensions d’intervention et de rétablissement. Cependant, à la lumière des incertitudes amenées par les changements climatiques, il est impératif que les communautés québécoises aient les capacités d’augmenter leur résilience face aux risques naturels qui s’accentuent rapidement. Ainsi, la capacité d’adaptation doit se retrouver au cœur de la gestion des risques. Cela dit, il existe peu d’outils d’évaluation de la capacité d’adaptation au Québec, entendue comme l’ensemble des ressources dynamiques disponibles et accessibles qui permettent une augmentation de la résilience et une diminution de la vulnérabilité en transformant positivement une communauté et son environnement. La présente recherche vise ainsi à développer une méthode d’analyse de la capacité d’adaptation des individus et des communautés québécoises touchées par les inondations à l’aide de systèmes d’information géographique (SIG), en utilisant la Ville de Saint-Raymond de Portneuf comme étude de cas. Ce projet se base principalement sur les concepts de vulnérabilité, de résilience et d’adaptation pour recenser des indicateurs pouvant servir à caractériser et évaluer la capacité des personnes et municipalités exposées aux inondations à mobiliser les ressources nécessaires pour non seulement atténuer les risques lors de tels événements, mais aussi mieux les prévenir et s’en préparer. Des données socioéconomiques et d’aménagement du territoire sont notamment mises à profit pour des fins d’analyse de même que des données issues d’un sondage effectué en 2014 à la suite d’une inondation majeure par la CAPSA, l’organisme de bassin versant de la région de Portneuf, en collaboration avec le comité Rivière de la Ville de Saint-Raymond. / Global climate change is increasingly impacting the well-being, development and vulnerability of communities across the world, whom must further mitigate disaster risk. In Québec, disaster risk management presents a “return to normal” philosophy that focuses primarily on intervention and short-term recovery. However, with the many uncertainties brought forth by global climate change, it is imperative that local communities in the province have the capacities to improve their resilience to natural hazards, which are becoming more devastating. Hence, the capacity to adapt must find itself at the heart of disaster risk management and sustainable development. That said, there are few tools that exist that enable decision-makers to assess adaptive capacity in Québec, which is understood as the dynamic resources that are available and accessible that increase resilience and reduce vulnerability by positively transforming a community and its environment. The present research seeks then to develop a method to evaluate the local citizens’ and their community’s adaptive capacity to flood risk with the help of GIS tools, using Saint-Raymond de Portneuf as a case study. This research founds itself on vulnerability, resilience et adaptation literature to elaborate indicators that could characterize and assess local capacities to mobilize the proper resources to not only cope with a flood event but also to better prevent and prepare for them in the long-term. Socio-economic et planning data are notably used as well as data taken from a survey conducted in 2014 following a major flood event by the CAPSA, the watershed organization in the Portneuf region, in collaboration with the Comité Rivière in the city of Saint-Raymond

Considerable interest lies in understanding the hydrologic response to climate change in the upper Deschutes Basin, particularly as it relates to groundwater fed streams. Much of the precipitation occurring in the recharge zone falls as snow. Consequently, the timing of runoff and recharge depend on accumulation and melting of the snowpack. Numerical modeling can provide insights into evolving hydrologic system response for resource management consideration. A daily mass and energy balance model known as the Deep Percolation Model (DPM) was developed for the basin in the 1990s. This model uses spatially distributed data and is driven with daily climate data to calculate both daily and monthly mass and energy balance for the major components of the hydrologic budget across the basin. Previously historical daily climate data from weather stations in the basin was used to drive the model. Now we use the University of Washington Climate Impact Group's 1/16th degree daily downscaled climate data to drive the DPM for forecasting until the end of the 21st century. The downscaled climate data is comprised from the mean of eight GCM simulations well suited to the Pacific Northwest. Furthermore, there are low emission and high emission scenarios associated with each ensemble member leading to two distinct means. For the entire basin progressing into the 21st century, output from the DPM using both emission scenarios as a forcing show changes in the timing of runoff and recharge as well as significant reductions in snowpack. Although the DPM calculated amounts of recharge and runoff varies between the emission scenario of the ensemble under consideration, all model output shows loss of the spring snowmelt runoff / recharge peak as time progresses. The response of the groundwater system to changing in the time and amount of recharge varies spatially. Short flow paths in the upper part of the basin are potentially more sensitive to the change in seasonality. However, geologic controls on the system cause this signal to attenuate as it propagates into the lower portions of the basin. This scale-dependent variation to the response of the groundwater system to changes in seasonality and magnitude of recharge is explored by applying DPM calculated recharge to an existing regional groundwater flow model.

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).

Wind power presently plays a minor role in Western Canada as compared to hydroelectric power in British Columbia and coal and natural gas thermal power generation in Alberta. However, ongoing reductions in the cost of wind power generation facilities and the increasing costs of conventional power generation, particularly if the cost to the environment is included, suggest that assessment of the present and future wind field in Western Canada is of some importance. To assess present wind power, raw hourly wind speeds and homogenized monthly mean wind speeds from 30 stations in Western Canada were analyzed over the period 1971-2000 (past). The hourly data were adjusted using the homogenized monthly means to attempt to compensate for differences in anemometer height from the standard height of 10m and changes in observing equipment at stations. A regional reanalysis product, the North American Regional Reanalysis (NARR), and simulations conducted with the Canadian Regional Climate Model (CRCM) driven with global reanalysis boundary forcing, were compared to the adjusted station wind-speed time-series and probability distributions. The NARR had a better temporal correlation with the observations, than the CRCM. We posit this is due to the NARR assimilating regional observations, whereas the CRCM did not. The NARR was generally worse than the CRCM in reproducing the observed speed distribution, possibly due to the crude representation of the regional topography in NARR. While the CRCM was run at both standard (45 km) and fine (15 km) resolution, the fine grid spacing does not always provide better results: the character of the surrounding topography appears to be an important factor for determining the level of agreement. Multiple simulations of the CRCM at the 45 km resolution were also driven by two global climate models (GCMs) over the periods 1971-2000 (using only historic emissions) and 2031-2060 (using the A2 emissions scenario). In light of the CRCM biases relative to the observations, these simulations were calibrated using quantile-quantile matching to the adjusted station observations to obtain ensembles of 9 and 25 projected wind speed distributions for the 2031-2060 period (future) at the station locations. Both bias correction and change factor techniques were used for calibration. At most station locations modest increases in mean wind speed were found for most of the projected distributions, but with a large variance. Estimates of wind power density for the projected speed distributions were made using a relationship between wind speed and power from a CRCM simulation for both time periods using the 15km grid. As would be expected from the wind speed results and the proportionality of wind power to the cube of wind speed, wind power at the station locations is more likely than not to increase in the 2031-2060 period from the 1971-2000 period. Relative changes in mean wind speeds at station locations were found to be insensitive to the station observations and choice of calibration technique, suggesting that we estimate relative change at all 45km grid points using all pairs of past/future mean wind speeds from the CRCM simulations. Overall, our results suggest that wind energy resources in Western Canada are reasonably likely to increase at least modestly in the future. / Graduate / 0725 / 0608 / jtdaines@uvic.ca

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.

As a result of increase in global average surface temperature, abnormalities in different hydroclimatic components such as evapotranspiration, stream flow and precipitation have been experienced. So investigation has to be carried out to assess the hidden abnormality subsisting in the hydroclimatological time series in the form of trend. This thesis broadly consists of following four parts. The first part comprises of a detailed review of various trend detection approaches. Approaches incorporating the effect of serial correlation for trend detection and interesting developments concerning various non parametric approaches are focused explicitly. Recent trends in annual, monthly, and seasonl (winter, pre-monsoon, monsoon and post-monsoon) Tmax and Tmin have been analyzed considering three time slots viz. 1901-2003, 1948-2003 and 1970-2003. For this purpose, time series of Tmax and Tmin of India as a whole and for seven homogeneous regions, viz. Western Himalaya (WH), Northwest (NW), Northeast (NE), North Central (NC), East coast (EC), West coast (WC) and Interior Peninsula (IP) were originally considered. During the last three decades significant upward trend in Tmin is found to be present in all regions considered either at annual or seasonal level. Sequential Mann Kendall test revealed that most of the significant upward trends both in Tmax and Tmin began after 1970. The second part discusses about numerous climate models from both Coupled Model Inter comparison Project-5 and 3 (i.e. CMIP5, CMIP3) and their skills in simulating Indian climate and assessing their performance using various evaluation measures. Performances of climate models were evaluated for whole of India and over all the individual grid points covering India. The newly defined metric symbolized as Skill_All is an intersection of the three metrics i.e. Skill_r, Skill_s and Skill_rmse, is used for overall model evaluation analysis. A notable enhancement of Skill_All for CMIP5 over CMIP3 was found. After overall model evaluation study, Compromise Programming, a distance based decision making technique, was employed to rank the GCMs gridwise. Entropy method was employed to obtain weights of the chosen indicators. Group decision making methodology was used to arrive at a consensus based on the ranking pattern obtained by individual grid points. In the third part, a detailed detection and attribution (D&A) analysis is performed to determine the causes of changes in seasonal Tmax and Tmin during the period 1950-2005. This formal D&A exercise helps in providing better insight (than trend detection analysis) into the nature of the observed seasonal temperature changes. It was noticed that the emergence of observed trend was more pronounced in Tmin compared to Tmax. Although observed changes were not solely associated with one specific causative factor, most of the changes in Tmin are above the bounds of natural internal climate variability. Finally in the fourth part, to understand the climate change impact on the hydrological cycle, a spatiotemporal change detection study of potential evapotranspiration (PET) along with Tmax and Tmin over India has been performed. Climatology patterns for PET confirmed a greater PET rate during the month of March, April, May and June. A significant increasing trend in both Tmax and Tmin (Tmin being more) was observed in more number of grid points compared to PET. Significant positive trends in Tmax, Tmin and PET were observed over most of the grid points in the IP region. Heterogeneities existed in the spatiotemporal variability of PET over all India. This spatio-temporal change detection study would be helpful for present and future water resources management.

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

[ES] La gestión de los recursos hídricos es de vital importancia para la comprensión de las sequias a largo plazo. En la actualidad, se presentan problemas debido a la disponibilidad y manejo del recurso hídrico. Además, el cambio climático afecta de manera negativa las variables climáticas y la disponibilidad del recurso hídrico. El tomar decisiones en base a información confiable y precisa conlleva un arduo trabajo y es necesario contar con diferentes herramientas que permitan llegar a la gestión de los recursos hídricos. La modelización de las variables climáticas es parte fundamental para determinar la disponibilidad del recurso hídrico. Las más importantes son la precipitación y temperatura o precipitación y evapotranspiración. Los modelos estocásticos se encuentran en un proceso de evolución que permiten reducir la escala de análisis. En esta investigación se ha abordado la modelación de variables climáticas con detalle diario. Se ha planteado una metodología para la generación de series sintéticas de precipitación y temperatura mediante modelización estocástica continua multivariada a escala diaria. Esta metodología también incorpora la corrección del sesgo para precipitación y temperatura de los escenarios de cambio climático con detalle diario. Los resultados de la presente tesis indican que los modelos estocásticos multivariados pueden representar las condiciones espaciales y temporales de las diferentes variables climáticas (precipitación y temperatura). Además, se plantea una metodología para la determinación de la evapotranspiración en función de los datos climáticos disponibles. Por otro lado, los modelos estocásticos multivariados permiten la corrección del sesgo con resultados diarios, mensuales y anuales más realistas que otros métodos de corrección de sesgo. Estos modelos climáticos son una herramienta para pronosticar eventos o escenarios futuros que permiten tomar mejores decisiones de manera anticipada. Estos modelos se programaron en el entorno de MatLab con el objetivo de aplicarlos a diferentes zonas de estudio de manera eficiente y automatizada. Los análisis realizados en la presente tesis se realizaron para la cuenca del Júcar con un buen desempeño para las condiciones de la cuenca. / [CA] La gestió dels recursos hídrics és de vital importància per a la comprensió de les sequeres a llarg termini. En l'actualitat, es presenten problemes a causa de la disponibilitat i maneig del recurs hídric. A més, el canvi climàtic afecta de manera negativa les variables climàtiques i la disponibilitat del recurs hídric. El prendre decisions sobre la base informació de confiança i precisa comporta un ardu treball i és necessari comptar amb diferents eines que permeten arribar a la gestió dels recursos hídrics. La modelització de les variables climàtiques és part fonamental per a determinar la disponibilitat del recurs hídric. Les més importants són la precipitació i temperatura o precipitació i evapotranspiració. Els models estocàstics es troben en un procés d'evolució que permet la incorporació de més detalls reduint l'escala d'anàlisi. En aquesta investigació s'ha abordat el modelatge de variables climàtiques amb detall diari. S'ha plantejat una metodologia per a la generació de sèries sintètiques de precipitació i temperatura mitjançant modelització estocàstica contínua multivariada a escala diària. Aquesta metodologia també incorpora la correcció del biaix per a precipitació i temperatura dels escenaris de canvi climàtic amb detall diari. Els resultats de la present tesi indiquen que els models estocàstics multivariats poden representar les condicions espacials i temporals de les diferents variables climàtiques (precipitació i temperatura). A més es planteja una metodologia per a la determinació de l'evapotranspiració en funció de les dades climàtiques disponibles. D'altra banda, els models estocàstics multivariats permeten la correcció del biaix amb resultats diaris, mensuals i anuals més realistes que altres mètodes de correcció de biaix. Aquests models climàtics són una eina per a pronosticar esdeveniments o escenaris futurs que permeten prendre millors decisions de manera anticipada. Aquests models es van programar a l'entorn de Matlab amb l'objectiu d'aplicar-los a diferents zones d'estudi de manera eficient i automatitzada. Les anàlisis realitzades en la present tesi es van realitzar per a la conca del Xúquer amb un bon acompliment per a les condicions de la conca. / [EN] Management of the water resources is important for understanding long-term droughts. Currently, there are problems due to the availability and management of water resources. Furthermore, climate change negatively affecting climate variables and the availability of water resources. Making decisions based on reliable and accurate information involves hard work and it is necessary to have different tools to achieve the management of water resources. The modeling of the climatic variables is a fundamental part to determine the availability of the water resource. The most important are precipitation and temperature or precipitation and evapotranspiration. Stochastic models are in a process of evolution that allows the incorporation of more details by reducing the scale of analysis. In this research, the modeling of climatic variables has been approached in daily detail. A methodology has been proposed for the generation of synthetic series of precipitation and temperature by means of multivariate continuous stochastic modeling on a daily scale. This methodology also incorporates the bias correction for precipitation and temperature of the climate change scenarios with daily detail. The results of this thesis indicate that multivariate stochastic models can represent the spatial and temporal conditions of the different climatic variables (precipitation and temperature). In addition, a methodology is proposed for the determination of evapotranspiration based on the available climatic data. On the other hand, multivariate stochastic models allow bias correction with more realistic daily, monthly and annual results than other bias correction methods. These climate models are a tool to forecast future events or scenarios that allow better decisions to be made in advance. These models were programmed in the MatLab software with the aim of applying them to different study areas in an efficient and automatically. The work in this thesis was carried out for the Júcar basin with a good performance for the conditions of the basin / Hernández Bedolla, J. (2022). Análisis estocástico de datos climáticos como predictor para la gestión anticipada de sequías en recursos hídricos [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/182095 / TESIS

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