Tesis por compendio / [ES] Los Pavimentos Permeables (PP) son una técnica de los denominados Sistemas Urbanos de Drenaje Sostenible (SUDS). A diferencia de otras técnicas de este tipo, proporciona una superficie dura transitable a la vez que gestiona las aguas pluviales superficiales, siendo sus propiedades hidráulicas fundamentales para su rendimiento como SUDS. Esta tesis explora el rendimiento hidráulico de los PP, basándose en el modelo hidrológico-hidráulico de PP proporcionado en el ampliamente utilizado Storm Water Management Model (SWMM). La tesis se presenta en un formato de tres artículos. Así, tras una aproximación a la pregunta general de investigación dada en el primer capítulo introductorio, el segundo capítulo del documento analiza qué parámetros son los más influyentes y cuáles son despreciables en el modelo, proporcionando un análisis de sensibilidad general. El siguiente capítulo explora la relación entre el modelo de PP de SWMM y el modelo de número de curva (CN), ampliamente utilizado, en lo que respecta a la escorrentía deducida por ambos modelos en función de la permeabilidad del pavimento. En el cuarto capítulo se analiza la respuesta del PP en condiciones experimentales controladas y se compara con el modelo de PP dado en SWMM. Tras una discusión general de los resultados en el quinto capítulo, se ofrecen unas conclusiones generales en el último. La tesis profundiza en el conocimiento del comportamiento hidráulico de los PP para ayudar a profesionales e investigadores en su caracterización. / [CA] Els Paviments Permeables (PP) són una tècnica dels denominats Sistemes Urbans de Drenatge Sostenible (SUDS). A diferència d'altres tècniques d'aquest tipus, proporciona una superfície dura transitable alhora que gestiona les aigües pluvials superficials, sent les seues propietats hidràuliques fonamentals per al seu rendiment com SUDS. Aquesta tesi explora el rendiment hidràulic dels PP, basant-se en el model hidrològic-hidràulic de PP proporcionat en l'àmpliament utilitzat Storm Water Management Model (SWMM). La tesi es presenta en un format de tres articles. Així, després d'una aproximació a la pregunta general d'investigació donada en el primer capítol introductori, el segon capítol del document analitza quins paràmetres són els més influents i quins són menyspreables en el model, proporcionant una anàlisi de sensibilitat general. El següent capítol explora la relació entre el model de PP de SWMM i el model de número de corba (CN), àmpliament utilitzat, pel que fa a l'escolament deduït per tots dos models en funció de la variable permeabilitat del paviment. En el quart capítol s'analitza la resposta del PP en condicions experimentals controlades i es compara amb el model de PP donat en SWMM. Després d'una discussió general dels resultats en el cinqué capítol, s'ofereixen unes conclusions generals en l'últim. La tesi aprofundix en el coneixement del comportament hidràulic dels PP per a ajudar a professionals i investigadors en la seua caracterització. / [EN] Permeable Pavements (PP) are a Sustainable Urban Drainage System (SUDS) technique. Unlike other such techniques, it provides a transitable hard surface while managing surface stormwater, being its hydraulic properties fundamental for its performance as a SUDS. This dissertation explores the hydraulic performance of PPs, based on the hydrologic-hydraulic model of PP provided in the widely used Storm Water Management Model (SWMM). The dissertation is presented in a \textit{three-paper} format. Accordingly, after an approach to the general research question given in the first introductory chapter, the second chapter of the document analyses which parameters are the most influential and which are negligible in the model by providing a general sensitivity analysis. The next chapter explores the relation between the PP model from SWMM and the widely used Curve Number (CN) model regarding runoff generated by both models and examines the relationship between both approaches based on the pavement permeability variable. The fourth chapter analyses the PP response under controlled experimental conditions and compares it with the PP model given in SWMM. After a general discussion of the results in the fifth chapter, general conclusions are given in the last chapter. The dissertation deepens the understanding of the hydraulic behaviour of PPs to help practitioners and researchers with its characterisation. / Madrazo Uribeetxebarria, E. (2023). Modelling the Hydraulic Response of Permeable Pavements: a Numerical and Experimental Approach for Model Comparison and Sensitivity Analysis to Design Parameters [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/196085 / Compendio

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.