Regionalization of hydrometeorological variables such as rainfall and temperature is necessary for various applications related to water resources planning and management. Sampling variability and randomness associated with the variables, as well as non-availability and paucity of data pose a challenge in modelling the variables. This challenge can be addressed by using stochastic models that utilize information from hydrometeorologically similar locations for modelling the variables. A set of locations that are hydrometeorologically similar are referred to as homogeneous region or pooling group and the process of identifying a homogeneous region is referred to as regionalization. The thesis concerns development of new approaches to regionalization of (i) extreme rainfall,(ii) maximum and minimum temperatures, and (iii) rainfall together with maximum and minimum temperatures. Regionalization of extreme rainfall and frequency analysis based on resulting regions yields quantile estimates that find use in design of water control (e.g., barrages, dams, levees) and conveyance structures (e.g., culverts, storm sewers, spillways) to mitigate damages that are likely due to floods triggered by extreme rainfall, and land-use planning and management. Regionalization based on both rainfall and temperature yield regions that could be used to address a wide spectrum of problems such as meteorological drought analysis, agricultural planning to cope with water shortages during droughts, downscaling of precipitation and temperature. Conventional approaches to regionalization of extreme rainfall are based extensively on statistics derived from extreme rainfall. Therefore delineated regions are susceptible to sampling variability and randomness associated with extreme rainfall records, which is undesirable. To address this, the idea of forming regions by considering attributes for regionalization as seasonality measure and site location indicators (which could be determined even for ungauged locations) is explored. For regionalization, Global Fuzzy c-means (GFCM) cluster analysis based methodology is developed in L-moment framework. The methodology is used to arrive at a set of 25 homogeneous extreme rainfall regions over India considering gridded rainfall records at daily scale, as there is dearth of regionalization studies on extreme rainfall in India Results are compared with those based on commonly used region of influence (ROI) approach that forms site-specific regions for quantile estimation, but lacks ability to delineate a geographical area into a reasonable number of homogeneous regions. Gridded data constitute spatially averaged rainfall that might originate from a different process (more synoptic) than point rainfall (more convective). Therefore to investigate utility of the developed GFCM methodology in arriving at meaningful regions when applied to point rainfall data, the methodology is applied to daily rainfall records available for 1032 gauges in Karnataka state of India. The application yielded 22 homogeneous extreme rainfall regions. Experiments carried out to examine utility of GFCM and ROI based regions in arriving at quantile estimates for ungauged sites in the study area reveal that performance of GFCM methodology is fairly close to that of ROI approach. Errors were marginally lower in the case of GFCM approach in analysis with observed point rainfall data over Karnataka, while its converse was noted in the case of analysis with gridded rainfall data over India. Neither of the approaches (CA, ROI) was found to be consistent in yielding least error in quantile estimates over all the sites. The existing approaches to regionalization of temperature are based on temperature time series or their related statistics, rather than attributes effecting temperature in the study area. Therefore independent validation of the delineated regions for homogeneity in temperature is not possible. Another drawback of the existing approaches is that they require adequate number of sites with contemporaneous temperature records for regionalization, because the delineated regions are susceptible to sampling variability and randomness associated with the temperature records that are often (i) short in length, (ii) limited over contemporaneous time period and (iii) spatially sparse. To address these issues, a two-stage clustering approach is developed to arrive at regions that are homogeneous in terms of both monthly maximum and minimum temperatures ( and ). First-stage of the approach involves (i) identifying a common set of possible predictors (LSAVs) influencing and over the entire study area, and (ii) using correlations of those predictors with and along with location indicators (latitude, longitude and altitude) as the basis to delineate sites in the study area into hard clusters through global k-means clustering algorithm. The second stage involves (i) identifying appropriate LSAVs corresponding to each of the first-stage clusters, which could be considered as potential predictors, and (ii) using the potential predictors along with location indicators (latitude, longitude and altitude) as the basis to partition each of the first-stage clusters into homogeneous temperature regions through global fuzzy c-means clustering algorithm. A set of 28 homogeneous temperature regions was delineated over India using the proposed approach. Those regions are shown to be effective when compared to an existing set of 6 temperature regions over India for which inter-site cross-correlations were found to be weak and negative for several months, which is undesirable. Effectiveness of the newly formed regions is demonstrated. Utility of the proposed maxTminT homogeneous temperature regions in arriving at PET estimates for ungauged locations within the study area was demonstrated. The estimates were found to be better when compared to those based on the existing regions. The existing approaches to regionalization of hydrometeorological variables are based on principal components (PCs)/ statistics/indices determined from time-series of those variables at monthly and seasonal scale. An issue with use of PCs for regionalization is that they have to be extracted from contemporaneous records of hydrometeorological variables. Therefore delineated regions may not be effective when the available records are limited over contemporaneous time period. A drawback associated with the use of statistics/indices is that they (i) may not be meaningful when data exhibit nonstationarity and (ii) do not encompass complete information in the original time series. Consequently the resulting regions may not be effective for the desired purpose. To address these issues, a new approach is proposed. It considers information extracted from wavelet transformations of the observed multivariate hydrometeorological time series as the basis for regionalization by global fuzzy c-means clustering procedure. The approach can account for dynamic variability in the time series and its nonstationarity (if any). Effectiveness of the proposed approach in forming homogeneous hydrometeorological regions is demonstrated by application to India, as there are no prior attempts to form such regions over the country. The investigations resulted in identification of 29 regions over India, which are found to be effective and meaningful. Drought Severity-Area-Frequency (SAF) curves are developed for each of the newly formed regions considering the drought index to be Standardized Precipitation Evapotranspiration Index (SPEI).

Mountains are hazardous places. Framed in political ecology and disaster theory in geography, this research set out to answer the overarching question of how the risk of climate-related disasters has changed in mountain areas of Guatemala at the start of the century. It involved four main related activities that examined key elements of disaster risk: 1) the trigger, assessing extreme rainfall trends based on daily records; 2) the hazards, through an evaluation of the relevance of land use and cover (LUC) to slope failure; 3) elements of social vulnerability, looking at its geography and trend at the turn of the century, and also exploring the role of globalisation in specific communities; and 4) an assessment and mapping of disaster risk in two sites, including an estimation of exposure levels to hazards. Methods range from statistical analysis of quantitative data (rainfall, landslide, and vulnerability chapters), GIS-based modelling (risk mapping), and qualitative analysis including interviews. The main findings state that: increasing annual and extreme rainfall has contributed to higher disaster risk only in a few areas; LUC change from forest to annual crops has increased risk in a few locations but it has not done so in most of the volcanic highlands either because there has been only minor LUC change or because LUC does not seem to have an effect on slope failure in certain types of geology. Disaster risk has decreased overall because vulnerability has become lower in the vast majority of mountain areas but risk may be higher as a result of increased exposure to hazards either in mountain communities or in marginal areas of the capital and surrounding municipios. The analysis of risk helped identify four mountain zones where risk is very likely to have increased. Further research questions are mostly related to studying the evolution of climate-related disaster risk in those areas.

Gävle kommun har planer på att exploatera Gävle stad söderut. Planerna finns enligt översiktsplanen Gävle Stad 2025 för bland annat områdena Järvsta och Ersbo. Dessa områden avvattnas mot Järvstabäcken. Detta examensarbete är en utredning av Järvstabäckens avrinningsområde med hänsyn till avrinningsområdets beskaffenhet, klimatförändringar och planerad exploatering. Utifrån dessa faktorer analyseras riskpunkter för översvämning inom avrinningsområdet. Utredningen av avrinningsområdet har genomförts via fältbesök, litteraturstudier och modellering i MIKE FLOOD.   Problematiken kring avrinningsområdet ligger i att Järvstabäcken redan är högt belastad. Med utökade exploateringsområden för bostäder och handelsområden i Hemlingby och Järvsta förväntas Järvstabäcken belastas ytterligare. Ersbo industriområde förväntas även påverka dagvattenflödena då mer andel hårdgjorda ytor tas i anspråk vid utökat handelsområde i kombination med planerad snötipp på industriområdet. Snötippen förväntas påverka flödet under smältperioden.   Riskpunkter för översvämningar återfinns i lågpunkter och passager under E4, Södra Kungsvägen, Upplandsleden och Bomhusvägen. I dessa punkter bör fördröjning av dagvattnet anläggas för att öka kontrollen över flödena och minska risken och kostnaderna för återställande av byggnader och infrastruktur vid översvämning. Riskpunkter i anslutning till befintlig bebyggelse och planerade bostadsområden bör prioriteras för utredning. / Gävle municipality's plans to exploit the city to the south are under the general plan for the areas Järvsta and Ersbo, these areas are dewatered to Järvsta stream. This thesis is an investigation of the Järvsta stream regarding flood risk areas within the basin with consideration to the planned development areas. Investigation of the catchment area has been carried out through field visits, literature studies and modeling with MIKE FLOOD. The problem with Järvsta stream is that it is already heavily loaded. With increased development areas for housing and commercial areas in Hemlingby and Järvsta expected Järvsta stream to be even more loaded in case of extreme rainfall. Ersbo industrial area is also expected to affect surface water flows, hence higher proportion paved surface in combination with the planned landfill for snow in the industrial area expect to impact the flow frequencies. The landfill for snow in Ersbo affects the flow frequencies during the melt period. Risk Points of flooding is found in low points and passages under E4, Södra Kungsvägen, Upplandsleden and Bomhusvägen. These points should delay stormwater to increase control over flows and reduce the risk of flooding and cost of restoration of the buildings and infrastructure. Risk points adjacent to the existing residential areas and planned residential areas should be prioritized for investigation.

I världen idag pågår en urbanisering, vilket innebär att fler människor flyttar in till städerna. Det innebär att fler bostäder måste byggas för att uppfylla de nya behoven, och detta görs ofta genom förtätning av redan exploaterade områden. Vid förtätning av bostadsområden ökar ofta andelen hårdgjorda ytor. En hårdgjord yta är en icke permeabel yta där dagvatten inte kan infiltrera ner i marken utan istället bildar ytavrinning. Vattnet som avrinner färdas mot lågpunkter i terrängen vilka riskerar att översvämmas. Klimatförändringar väntas leda till häftigare väder, bland annat i form av skyfall. Kraftigare regn i kombination med större andel hårdgjorda ytor väntas öka risken för pluviala översvämningar. För att undvika pluviala översvämningar krävs strategier för att hantera städers dagvatten. Det existerande ledningsnätet är högt belastat och kombineras med hållbara dagvattenlösningar för att minska avrinningen. Grönytor ses ofta som goda infiltrationsytor, men en osäkerhet råder kring hur effektiva olika typer av grönytor är. Det är därför av intresse att undersöka hur goda infiltrationsytor urbana grönområden är och hur stor betydelse de har vid skyfall för att minimera pluviala översvämningar. Syftet med examensarbetet är att undersöka infiltrationskapaciteten för grönytor på ett antal olika platser i Stockholm. Syftet är vidare att undersöka hur resultaten från fältförsöken kan användas i det hydrauliska modelleringsprogrammet MIKE 21 för att återspegla det verkliga infiltrationsförloppet och därmed få en god bild av hur stora översvämningsriskerna är för olika områden. Totalt utfördes 13 separata mätningar i två grönområden i Stockholm. Vid 11 av mätningarna användes en dubbelringsinfiltrometer och vid två av mätningarna användes en enkelringsinfiltrometer. Mätningarna utfördes under 0,5-2 timmar beroende på vattentillgång. Infiltrationsförsöken visade att det finns en stor variation i infiltrationskapacitet, även inom mycket små områden. De visade också att det finns en tendens till högre infiltrationskapacitet för mindre kompakterade grönytor. Kornstorleksfördelningen och vattenhalten skiljde sig inte nämnvärt mellan de två områdena och dessa två parametrar kunde inte kopplas till någon skillnad i infiltrationskapacitet för de två undersökta områdena. Resultaten från simuleringarna i MIKE 21 visade att vilka värden som anges för infiltrationskapaciteten är av större betydelse än på vilket sätt dessa anges. Resultaten visade också att parametrar såsom vattenhalt och porositet hade en inverkan på infiltrationsförloppet men infiltrationszonens mäktighet hade liten inverkan på resultaten. Sammanfattningsvis kan sägas att det finns en stor variation i infiltrationskapacitet för grönytor och den osäkerheten påverkar resultaten vid modellering av översvämningsrisker i MIKE 21. / The ongoing urbanization in the world today means that more people are moving into the cities and therefore more housing is required. When building in cities there is a tendency for an increase in impermeable surfaces. An impermeable surface is defined as a surface where no water can infiltrate into the subsurface soil and instead there is an increase in surface runoff. The water flows through the terrain towards low-lying areas, which are at risk for flooding. Climate changes are expected to result in more extreme weather such as extreme rain. An increase in extreme rain in combination with more impermeable surfaces will increase the risk for pluvial flooding. To avoid pluvial flooding different strategies is required to cope with the urban stormwater. The traditional stormwater systems are usually put under high stress and sustainable stormwater management needs to be implemented to decrease the surface runoff in urban areas. Green areas are often thought to be good infiltration surfaces but there is a big uncertainty in regards to exactly how effective different green areas is for infiltration purposes. There is an interest to investigate how good the infiltration capacity is for urban green areas to map and to mitigate pluvial flooding. The aim for this master thesis is to investigate the infiltration capacity through field measurements for two different green areas in the city of Stockholm, Sweden. Furthermore, the aim is to investigate how the results from the field measurements can be implemented in the hydraulic modelling software MIKE 21 to represent the real infiltration pattern in order to map the risk for pluvial flooding for different areas. A total of 13 measurements were conducted in two green areas around Stockholm, using a double ring infiltrometer. For two of the measurements a single ring infiltrometer was used. The measurements were conducted during 0.5-2 h depending on the water accessibility. The field measurements showed that there is a large variability in infiltration capacity, even within very small areas. The measurement showed that there was a tendency for higher infiltration rates for less compacted soil. The grain size distribution showed little impact on the infiltration rate, and so did the water content. The simulations in MIKE 21 showed that the magnitude of the infiltration rate is of greater importance than the way it is implemented in MIKE 21. The results also showed that parameters such as water content and porosity had an effect on the infiltrated volume, but the depth of the infiltration zone had little impact on the results. In conclusion, there is a large variability in infiltration capacity for green areas and this uncertainty does affect the results when modelling the risk for pluvial flooding in MIKE 21.

The intensity and frequency of precipitation events have increased because of global warming and its direct impact on the hydrological cycle. This poses a significant challenge for various locations around the globe where in recent years more unpredicted flooding has been observed. The utilization of hydrological models for accurate prediction of urban floods under heavy rainfall events is crucial to deal with such global problems. The purpose of this study is to develop a model based on the Spatial Distributed Travel Time (SDTT) approach that estimates the response of watersheds to a short and intense rainfall event in urban settings. The model is developed in Python and uses the ArcPy package, which allows access to all the geoprocessing tools available at ArcGIS, along with the Numpy package that supports matrices which makes mathematical calculation efficient.   One of the important factors affecting the response of watersheds is the contribution of upstream flow. The current study used Dynamic Upstream Contribution (DUC) to estimate the unit hydrograph and consider the effect of upstream runoff contributing to travel time equations using physical characteristics and the dynamic of rainfall events. The SDTT model was validated with a fully distributed model, MIKE 21, and showed that when the infiltration module estimates the total runoff volume accurately, the unit hydrograph of the DUC method can predict the peak almost as accurately as MIKE 21. Before validation, the excess rainfall estimated in the SDTT model is multiplied by a constant coefficient to align the total water volume of the model with that of the MIKE 21 model.  The peak flow is the most important component of a discharge hydrograph since its accurate prediction helps in assessing the severity of flooding and the capacity of drainage systems to handle the excess water. Another component of a discharge hydrograph is time to peak which the SDTT model predicts with a delay compared to MIKE 21. The sensitivity analysis showed the simplification regarding the dynamic of rainfall intensity used in travel time equations contributes to this delayed peak. The other simplification that might impact the watershed response is the approach the model used to handle depression volume which is too general. A conceptual method proposed in this report can be used in future studies to improve this part of the model by capturing the spatial distribution of depression locations as well as the temporal dynamics of charging the depressions.   After the model was validated in the first study area, it was implemented in another study area to evaluate the effect of urban development on the hydrological response of urban catchments to a short and intense rainfall event. This scenario-based analysis showed that by further development of the model, it can be used as a tool for the initial phase of hydrologic investigation of urban areas in response to heavy rainfall events. By conducting the screening phase of hydrological investigation and filtering the risky location, the SDTT model can be used as a complementary model for more advanced fully distributed models that are more computationally extensive.   The recorded simulation time demonstrated that the SDTT model is quick when it comes to small-sized watersheds, but it is less time-efficient for large catchments. An approach proposed in this report can be utilized to optimize the model's processing time for larger catchments. By making the model time efficient and addressing the issues mentioned in the report, the developed SDTT model can facilitate the hydrological investigation by reducing the initial data gathering burden and simulation time, and making the assessments of urban watersheds more efficient can facilitate informed decision-making in urban flood risk management. / Till följd av den globala uppvärmningen har intensiteten och frekvensen av nederbördshändelser ökat, en direkt inverkan på den hydrologiska cykeln som utgör en betydande utmaning för olika platser runt om i världen där oförutsedda översvämningar observerats under de senaste åren. Användningen av hydrologiska modeller för att med noggrannhet förutseurbana översvämningar under kraftiga nederbördshändelser är avgörande för att hantera detta globala problem. Syftet med denna studie är att utveckla en modell baserad på Spatial Distributed Travel Time (SDTT) metodiken. SDTT-metodiken beskriver responsen från ett avrinningsområde för en kort och intensiv nederbördshändelse i urban miljö. Modellen är utvecklad i Python och inkluderar ArcPy-paketet som ger tillgång till alla geoprocesseringsverktyg som finns i ArcGIS tillsammans med Numpy-paketet som stödjer matriser som effektiviserar matematiska beräkningar.  En av de avgörande faktorerna som visade sig påverka reaktionen från ett avrinningsområde var flödet från uppströmsområdet. Den aktuella studien använde Dynamic Upstream Contribution (DUC) för att uppskatta enhetshydrografen med hänsyn till effekten avrinningen uppströms har på avrinningshastigheten med hjälp av fysiska egenskaper och nederbördsdynamik. SDTT-modellen validerades med en fullt distribuerad modell, MIKE 21, och visade att när infiltrationsmodulen uppskattar den totala avrinningsvolymen exakt, kan enhetshydrografen för DUC-metoden förutsäga toppflödet exakt. Innan validering multipliceras överskottsnederbörden uppskattad i SDTT-modellen med en konstant koefficient för att justera modellens totala vattenvolym med den i MIKE 21-modellen. Toppflödet är den viktigaste komponenten i en flödeshydrograf eftersom dess noggranna förutsägelse hjälper till att bedöma allvarsgraden av översvämningar samt dräneringssystemens kapacitet att hantera överskottsvatten. En annan komponent i en flödeshydrograf är den tid det tar tills toppflödet uppstår, något som SDTT-modellen förutsäger med en fördröjning jämfört med MIKE 21. Känslighetsanalysen visade att förenklingen gällande dynamiken för nederbördsintensitet som används i ekvationerna för avrinningshastighet bidrar till denna fördröjda topp. Den andra förenklingen som kan påverka responsen från avrinningsområdet är metoden som modellen använde för att hantera volymen vatten som lagras i sänkor, som är förgenerell. En konceptuell metod föreslås i denna rapport och kan användas i framtida studier för att förbättra denna del av modellen genom att fånga den rumsliga fördelningen av sänkor samt tidsaspekten i att fylla upp sänkvolymerna.   Efter att modellen validerats i det första studieområdet, implementerades den i ett annat studieområde för att utvärdera kopplingen mellan stadsutveckling och hydrologisk respons i urbana avrinningsområden i kontexten av en kort och intensiv nederbördshändelse. Denna scenariobaserade analys visade att modellen efter vidareutveckling kan användas som ett verktyg för den inledande fasen av hydrologisk undersökning av stadsområden, i syfte att utreda möjliga konsekvenser av kraftiga nederbördshändelser. Genom att genomföra screeningfasen av hydrologisk undersökning och filtrera den mest riskfyllda platsen kan SDTT-modellen användas som en kompletterande modell för mer avancerade fullt distribuerade modeller som är mer beräkningsmässigt omfattande.   Den registrerade simuleringstiden visade att SDTT-modellen är snabb när det kommer till ett litet avrinningsområde, men modellen är mindre tidseffektiv för stora avrinningsområden. Ett tillvägagångssätt som föreslås i denna rapport kan användas för att optimera modellens handläggningstid för större avrinningsområden. Genom att göra modellen tidseffektiv och åtgärda frågorna som nämns i rapporten, kan den utvecklade SDTT-modellen underlätta den hydrologiska undersökningen genom att minska den inledande datainsamlingsbördan, minskasimuleringstiden, och dessutom göra utvärderingarna av urbana avrinningsområden mer effektiva. Slutligen kan modellens resultat användas för att underlätta informerat beslutsfattande kopplat till hantering av översvämningsrisker i städer.

Doctor of Philosophy / Department of Biological & Agricultural Engineering / Stacy L. Hutchinson / Precipitation impacts hydrologic structures, agricultural production, water resources management, and recreational activities, all of which significantly affect a state’s economy. Water control structure design is based on the maximum runoff rate resulting from storms with a specific return period and duration. The Rainfall Frequency Atlas (National Weather Service Technical Paper 40, 1961) (TP-40) provided statistical rainfall analysis as the basis for hydrologic structure design until the information was updated for Kansas in February 2013 (National Oceanic and Atmospheric Administration Atlas 14, volume 8) (Atlas-14). With growing concern about the effects of global climate change and predictions of more precipitation and extreme weather events, it is necessary to explore rainfall distribution patterns using the most current and complete data available. In this work, the changes in rainfall patterns were studied using the daily rainfall data from 23 stations in Kansas and 15 stations from adjacent states with daily rainfall data of 1890 through 2012. Analysis showed an increase in extreme precipitation events in Kansas with increase in magnitude from the northwest to southeast part of the state. A comparison of results of the TP-40 analysis to period 1980–2009, showed that approximately 84% of the state had an increase in short-term rainfall event magnitudes. In addition, trend analyzes on the total annual rainfall indicated a gradual increase at 21 out of 23 stations, including eight statistically significant trends. A change-point analysis detected a significant sudden change at twelve stations as early as 1940 and as recently as 1980. The increasing trend, particularly after the significant change-points, is useful in updating water management plans and can assist with agricultural production decisions such as crop selection and new plant variety development. A comparison between 10-yr, 24-hr storms from TP-40 and Atlas-14 indicated a change of -12% to 5% in Kansas. However, the number of exceedances from the 10-yr, 1-, 2-, 3-, 4-, 7-, and 10-day storms demonstrated a tendency towards more exceedances, particularly in the last five decades. Results of this study are useful for hydrologic structure design and water resources management in order to prevent accepting additional risk of failure because of the current changing climate.

En Afrique de l'Ouest, la diminution brutale de la pluviométrie depuis les années 1970 s'est produite en concomitance avec une augmentation des dommages liés aux inondations. Si une accentuation de la vulnérabilité des populations est indéniable, la question d'une évolution de l'aléa pluviométrique en particulier des pluies les plus intenses reste posée - notamment dans un contexte où le réchauffement climatique devrait s'accompagner d'une intensification du cycle hydrologique globale. Cette thèse s'attache améliorer nos connaissances sur le régime de pluies extrêmes en Afrique de l'Ouest sous-documenté à l'heure actuelle dans les sciences du climat et de l'hydrologie opérationnelle. Le travail s'articule autour des trois objectifs: (i) fournir une vision régionale intégrée de l'organisation spatiale des extrêmes, (ii) étudier l'évolution du régime de précipitations extrêmes en lien avec la variabilité décennale des cumuls pluviométriques annuels, (iii) caractériser les extrêmes pluviométriques en produisant des cartes d'aléa pluviométrique et en étudiant les liens d'échelles entre les extrêmes de pluie à différents résolutions spatio-temporelles. On se base ici sur les données journalières des réseaux nationaux disponibles depuis les années 1950 sur l'Afrique de l'Ouest et actualisées sur le Sahel Central jusqu'en 2010; les données de précipitation à haute résolution disponibles depuis 1990 sur l'observatoire AMMA-CATCH Niger. Les modèles statistiques classiques issus de la théorie des valeurs extrêmes, ont été adaptés pour incorporer des covariables représentant des non-stationnarités spatiales et temporelles dans les pluies extrêmes. On montre la grande robustesse de ces modèles pour estimer les quantiles rares et détecter les tendances régionales dans les séries d'extrêmes. Le cadre théorique des fractales a été utilisé pour modéliser les relations d'échelles spatio-temporelles. On montre ainsi qu'une représentation de type "simple scaling" permet de décrire de manière très satisfaisante ces relations sur la gamme des pas de temps allant de 1 à 24 heures. Les résultats climatologiques confirment que la sécheresse de la fin du XXeme siècle a été avant tout associée à une baisse de l'occurrence des précipitations, leur intensité demeurant relativement inchangée. On note en revanche un comportement singulier sur la dernière décennie durant laquelle un déficit persistant d'occurrence est compensé par une intensification des précipitations qui explique un retour vers une meilleure pluviométrie annuelle, associée cependant à des extrêmes plus marqués et donc porteurs de risque hydrologique. / In West Africa, the sharp decrease of rainfall since the 70s has occurred concurrently with an increase of flood damage. If it is certain that the vulnerability of the population has increased, the question of the evolution of extreme rainfall remains unanswered - especially in a context where global warming should be accompanied by an intensification of the global water cycle. This thesis aims to improve our understanding of the extreme rainfall regime in West Africa. The work is based on three objectives: (i) provide an integrated regional vision of the spatial organization of extremes, (ii) study the evolution of extreme precipitation regime in connection with the decadal variability of annual rainfall (iii) characterize the extreme rainfall by producing rainfall hazard maps and IDAF (Intensity-Duration-Area-Frequency) curves. In this work, two datasets are used: (i) daily data from national networks, available since 1950 on West Africa, have been updated on the Central Sahel until 2010; (ii) precipitation data with high resolution available since 1990 from the AMMA-CATCH Niger observatory. Conventional statistical models from the extreme value theory has been adapted to incorporate covariates in order to represent spatial and temporal non-stationarity in extreme rainfall. These models show a high robustness to estimate the high quantiles and detect regional trends in the extreme series. The theoretical framework of fractals has been used to model the relationships of spatial and temporal scales. Climatological results confirm that the drought of the late 20th century was primarily associated with a decrease in the occurrence of rainfall, intensity remained relatively unchanged. We note, however, a singular behavior in the last decade: a persistent deficit of occurrence of rainfall is compensated by higher intensities which explains a return to better annual rainfall associated with more extreme rainfall.

The purpose of this study is to determine if Low Impact Development (LID) can effectively mitigate flooding under projected climate scenarios. LID relies on runoff management measures that seek to control rainwater volume at the source by reducing imperviousness and retaining, infiltrating and reusing rainwater. An event-driven hydrologic/hydraulic model was developed to simulate how climate change, land use and LID scenarios may affect runoff response in the Bowker Creek watershed, a 10km2 urbanized catchment located in the area of greater Victoria, British Columbia, Canada. The first part of the study examined flood impacts for the 2050s (2040-2069) following the A2 emissions scenario. For the 24-hour, 25-year local design storm, results show that projected changes in rainfall intensity may increase flood extents by 21% to 50%. When combined with continued urbanization flood extents may increase by 50% to 72%. The second part of the study identified potential locations for three LID treatments (green roofs, rain gardens and top soil amendments) and simulated their effect on peak in-stream flow rates and flood volumes. Results indicate that full implementation of modeled LID treatments can alleviate the additional flooding that is associated with the median climate change projection for the 5-year, 10-year and 25-year rainfall events. For the projected 100-year event, the volume of overland flood flows is expected to increase by 1%. This compares favourably to the estimated 29% increase without LID. In term of individual performance, rain gardens had the greatest hydrologic effect during more frequent rainfall events; green roofs had minimal effect on runoff for all modelled events; and top soil amendments had the greatest effect during the heaviest rainfall events. The cumulative performance of LID practices depends on several variables including design specifications, level of implementation, location and site conditions. Antecedent soil moisture has a considerable influence on LID performance. The dynamic nature of soil moisture means that at times LID could meet the mitigation target and at other times it may only partially satisfy it. Future research should run continuous simulations using an appropriately long rainfall record to establish the probabilities of meeting performance requirements. In general, simulations suggest that if future heavy rainfall events follow the median climate change projection, then LID can be used to maintain or reduce flood hazard for rainfall events up to the 25-year return period. This study demonstrates that in a smaller urban watershed, LID can play an important role in reducing the flood impacts associated with climate change. / Graduate

The goal of this work is to define the atmospheric patterns associated with the extreme precipitation events in the Rio Grande do Sul (RS) state in spring. The data used were the rainfall series provided by the Agência Nacional das Águas (ANA, in portugues) and reanalysis data of high resolution of the Climate Forecast System Reanalysis (CFSR) of 00 and 12 UTC. From the data of the ANA, on the RS, six homogeneous regions of precipitation were obtained through of Hierarchical Cluster Analysis technique, which are: the East and North Coast (R1), Southern and South Coast (R2), the West and the border with Uruguay (R3), Northern (R4), Midwest (R5) and Northwest (R6). With the averages series for each homogeneous regions, utilizing the technique of quantis, has located the days that precipitation over each region was equal or superior to the quantile 99%. With data of the CFSR was generated a matrix (NxM) being N the dates of extreme events and M are meteorological fields normalized in grid points, selected in a grid 21x19 on the RS. The fields chosen are: mean sea level pressure, thickness between 500 and 1000hPa, geopotential height at 500, zonal component of wind at 850hPa, meridional component of wind at 850hPa, zonal component of wind at 200hPa, meridional component of wind at 200hPa and specific humidity at 850hPa. Using the Non-Hierarchical Cluster Analysis, over the array, were obtained 5 atmospheric clusters, defined as the patterns. For the Cluster 1 the principal events of extreme precipitation had locating in the regions R2, R3, R5 and R6. In Cluster 2, the events of extreme of precipitation was, principally, over the region R1. In Cluster 3, the events of extreme precipitation ocurred in the coastal regions (R1 and R2), border with Uruguay (R3) and regions wit high topography (R4 and R5). In Cluster 4, the rainfall extremes is widespread over all regions. And in Cluster 5, extreme precipitation ocurred principally in the R2, R3 and R4 regions. The Cluster 3 showed strong features of a front incursion, while the characteristics of a Mesoscale Convective System (MCS) are present in Cluters 1, 4 and 5. Thus, the three major weather systems that cause extreme precipitation in RS, the MCS are the most important and only the Upper-level cut-off low not has been clearly identified, but the Cluster 2 presents some features that may indicate their presence, which are for example, the trough axis on the RS and the formation of a surface cyclone on the coast. / O objetivo desta dissertação é a definição de padrões atmosféricos associados a eventos extremos de precipitação no estado do Rio Grande do Sul (RS), na primavera. Os dados utilizados foram as séries pluviométricas disponibilizada pela Agência Nacional das Águas (ANA) e os dados de reanálise de alta resolução do Climate Forecast System Reanalysis (CFSR) das 00 e 12 UTC. A partir dos dados da ANA, sobre o RS, foram obtidas seis regiões homogêneas de precipitação, por meio da técnica de Análise de Agrupamento hierárquica, que são: o Leste e Litoral Norte (R1), Extremo Sul e Litoral Sul (R2), Oeste e Fronteira com o Uruguai (R3), Extremo Norte (R4), Centro-Oeste (R5) e Noroeste (R6). Com as séries médias para cada uma das regiões homogêneas foram localizados, por meio da técnica dos quantis, os dias em que a precipitação sobre cada região foi igual ou superior ao quantil 99%. Com os dados do CFSR foi gerada uma matriz N x M sendo o N as datas de eventos extremos e o M são dados normalizados, em pontos de grade, dos campos meteorológicos selecionados em uma grade 21x19 sobre o RS. Os campos meteorológicos escolhidos foram: Pressão ao Nível Médio do Mar, Espessura entre 500hPa e 1000hPa, Altura Geopotencial em 500hPa, Componente Zonal do vento em 850hPa, Componente Meridional do vento em 850hPa, Componente Zonal do vento em 200hPa, Componente Meridional do vento em 200hPa e Umidade Específica em 850hPa. Aplicando a Análise de Agrupamento Não-Hierárquica sobre a matriz dos campos meteorológicos foram obtidos 5 agrupamentos atmosféricos, definidos como os padrões atmosféricos. Para o Agrupamento 1 os extremos de precipitação ficaram localizados principalmente sobre as regiões R2, R3, R5 e R6. No Agrupamento 2 o extremo de precipitação ficou principalmente sobre a região R1. No Agrupamento 3 os extremos de precipitação ficaram sobre as regiões litorâneas (R1 e R2), de fronteira com o Uruguai (R3) e de regiões com elevação no relevo (R4 e R5). No Agrupamento 4 os extremos de precipitação ficaram generalizados sobre o todas as regiões e no Agrupamento 5 ocasionaram extremos de precipitação nas regiões R2, R3 e R4. O Agrupamento 3 apresenta fortes características de uma incursão frontal, enquanto que as características de um Sistema Convectivo de Mesoescala (SCM) estão presentes nos Agrupamentos 1, 4 e 5. Assim, dos três principais sistemas meteorológicos que causam precipitação extrema no RS, os SCM são os mais importantes e somente o Vórtice Ciclônico em Altos Níveis não foi claramente identificado, mas o Agrupamento 2 apresenta algumas características que podem indicar a sua presença, que são por exemplo, o eixo do cavado sobre o RS e a formação de um ciclone em superfície sobre o litoral.

In this thesis, we investigated modes of intraseasonal variability (ISV) observed in the Indian monsoon rainfall and how these modes modulate rainfall over India. We identified a decreasing trend in the intensity of low-frequency intraseasonal mode with increasing strength in synoptic variability over India. We also made an attempt to understand the reason for these observed trends using numerical simulations. In the first part of the thesis, satellite rainfall estimates are used to understand the spatiotem-poral structures of convection in the intraseasonal timescale and their intensity during boreal sum-mer over south Asia. Two dominant modes of variability with periodicities of 10–20-days (high-frequency) and 20–60-days (low-frequency) are found, with the latter strongly modulated by sea surface temperature. The 20–60-day mode shows northward propagation from the equatorial In-dian Ocean linked with eastward propagating modes of convective systems over the tropics. The 10–20-day mode shows a complex space-time structure with a northwestward propagating anoma-lous pattern emanating from the Indonesian coast. This pattern is found to be interacting with a structure emerging from higher latitudes propagating southeastwards. This could be related to ver-tical shear of zonal wind over northern India. The two modes exhibit variability in their intensity on the interannual time scale and contribute a significant amount to the daily rainfall variability in a season. The intensities of the 20–60-day and 10–20-day modes show significantly strong inverse and direct relationship, respectively, with the all-India June–September rainfall. This study also establishes that the probability of occurrence of substantial rainfall over central India increases significantly if the two intraseasonal modes simultaneously exhibit positive anomalies over the region. There also exists a phase-locking between the two modes. In the second part of the thesis, we investigated the changing nature of these intraseasonal modes over Indian region, and their association with extreme rainfall events using ground based observed rainfall. We found that the relative strength of the northward propagating 20–60-day mode has a significant decreasing trend during the past six decades, possibly attributed to the weakening of large-scale circulation in the region during monsoon. This reduction is compensated by a gain in synoptic-scale (3–9 days) variability. The decrease in the low-frequency ISV is associated with a significant decreasing trend in the percentage of extreme events during the active phase of the monsoon. However, this decrease is balanced by a significant increasing trend in the percentage of extreme events in break phase. We also find a significant rise in occurrence of extremes during early- and late-monsoon months, mainly over the eastern coastal regions of India. We do not observe any significant trend in the high-frequency ISV. In the last part of the thesis, we used numerical simulations to understand the observed changes in the ISV features. Using the atmospheric component of a global climate model (GCM), we have performed two experiments: control experiment (CE) and heating experiment (HE). The CE is the default simulation for 10 years. In HE, we prescribed heating in the atmosphere in such a way that it mimics the conditions for extreme rainfall events as observed over central India during June– September. Heating is prescribed primarily during the break phase of the 20–60-day mode. This basically increases the number of extremes, majority of which are in break phase. The design of the experiment reflects the observed current scenario of increased extreme events during breaks. We found that the increased extreme events in the HE decreased the intensity of the 20–60-day mode over the Indian region. This reduction is associated with a reduction of rainfall in active phase and increase in the length of break phase. A reduction in the seasonal mean over India is also observed. The reduction of active phase rainfall is linked with an increased stability of the atmosphere over central India. Lastly, we propose a possible mechanism for the reduction of rainfall in active phase. We found that there is a significant reduction in the strength of the vertical easterly shear over the northern Indian region during break–active transition phase. This basically weakens the conditions for the growth of Rossby wave instability, thereby elongating break phase and reducing the rainfall intensity in the following active phase. This study highlights the redistribution of rainfall intensity among periodic (low-frequency) and non-periodic (extreme) modes in a changing climate scenario, which is further tested in a modeling study. The results presented in this thesis will provide a pathway to understand, using observations and numerical model simulations, the ISV and its relative contribution to the Indian summer monsoon. It can also be used for model evaluation.