Future changes in climate and land use are likely to affect catchment hydrological responses and consequently influence the amount of runoff reaching roads. Blockages and damage to under-dimensioned infrastructure can be extremely costly for the regions affected. This study aims to produce scientifically well-founded suggestions on adaptation of road drainage systems to climate changes resulting in more frequent floods. This thesis demonstrates the need to integrate aspects of climate change and land use impacts into the planning and practice of road construction and maintenance in Sweden. Tools such as hydrological models are needed to assess impacts on discharge dynamics. Identifying a ‘best’ practically performing hydrological model is often difficult due to the potential influence of modeller subjectivity on calibration procedure, parameter selection, etc. Hydrological models may need to be selected on a case-by-case basis and have their performance evaluated on an application-by-application basis. The work presented here began by examining current practice for road drainage systems in Sweden. Various hydrological models were then used to calculate the runoff from a catchment adjacent to a road and estimate changes in peak discharge and total runoff resulting from simulated land use measures. Overall, the results indicate that the specific effect of land use measures on catchment discharge depend on their spatial distribution and on the size and timing of storm events. Scenarios comprising a changing climate up to 2050 or to 2100 and forest clear-cutting were used to determine whether the current design of road drainage construction is sufficient for future conditions. Based on the findings, the approach developed can be used for similar studies, e.g. by the Swedish Transport Administration in dimensioning future road drainage structures to provide safe and robust infrastructure. Furthermore, a statistical method was developed for estimating and mapping flood hazard probability along roads using road and catchment characteristics. The method allows flood hazards to be estimated and provides insight into the relative roles of landscape characteristics in determining road-related flood hazards. Overall, this method provides an efficient way to estimate flooding hazards and to inform the planning of future roadways and the maintenance of existing roadways. / <p>QC 20140130</p>

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.

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.