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    ItemOpen Access
    Climate sensitivity of a large lake
    (2013) Eder, Maria Magdalena; Bárdossy, András (Prof. Dr. rer. nat. Dr.-Ing.)
    Lakes are complex ecosystems that are on the one hand more or less enclosed by defined borders, but are on the other hand connected to their environment, especially to their catchment and the atmosphere. This study is examinig the climate sensitivity of large lakes using Lake Constance as an example. The lake is situated in Central Europe at the northern edge of the Alps, at the boundary of Austria, Germany and Switzerland. The maximum depth is 235 m, the total surface area is 535 km³ and the total volume 48.45 km². The numerical simulations in this study have been performed with the lake model system ELCOM-CAEDYM. The model system was validated using three different data sets: Observations of a turbid underflow after a flood flow in the main tributary, a lake-wide field campaign of temperature and phytoplankton, and long term monitoring data of temperature and oxygen in the hypolimion. The model system proved to be able to reproduce the effects of a flood flow in the largest tributary,. A huge turbid underflow was observed flowing into the main basin after an intense rain event in the Alps in August 2005. A numerical experiment showed the influence of the earth’s rotation on the flow path of the riverine water within the lake. The model also reproduced the temperature evolution and distribution and to some extent the phytoplankton patchiness measured in spring 2007 during an intensive field campaign. The model reproduced the measured time series of temperature and oxygen in the deep hypolimnion measured in the years 1980-2000. This indicates, that the vertical mixing and the lake’s cycle of mixing and stratification was reproduced correctly. Based on the model set-up validated with long term monitoring data, climate scenario simulations were run. The main focus was on temperature and oxygen concentrations in the hypolimnion, the cycle of stratification and mixing, and the heat budget of the lake. The meteorological boundary conditions for the climate scenario simulations were generated using a weather generator instead of downscaling climate projections from Global Climate Models. This approach gives the possibility to change different characteristics of the climate independently. The resulting lake model simulations are ”what-if”-scenarios rather than predictions, helping to obtain a deeper understanding of the processes in the lake. The main results can be summarized as follows: An increase in air temperature leads to an increase in water temperature, especially in the upper layers. The deep water temperature increases as well, but not to the same extent as the temperature of the epilimnion. This results in an increased vertical temperature difference. Due to the non-linear shape of the temperature-density curve, the difference in density grows even stronger than the temperature difference. This results in enhanced stratification stability, and consequently in less mixing. Complete mixing of the lake becomes more seldom in a warmer climate, but even in the scenario simulations with air temperature increased by 5 °C, full circulation took place every 3-4 years. Less complete mixing events lead to less oxygen in the hypolimnion. Additionally, as many biogeochemical processes are temperature dependant, the oxygen consumption rate is larger in warmer water. In the context of this study, climate variability is defined as episodes with daily average air temperatures deviating from the long-term average for this day of year. The episodes can be described by their duration in days and their amplitude in °C. Changes in climate variability can have very different effects, depending on the average air and water temperatures. The effects are stronger in lakes with higher water temperatures: For the hypolimnetic conditions, the seasonality in warming is important: Increasing winter air temperatures have a much stronger effect on the water temperatures in the lake than increasing summer temperatures. The combined effects of a warmer climate and higher nutrient concentrations enhances oxygen depletion in the hypolimnion. Finally, it is discussed, to what extent the results of this study are transferrable to other lakes. The reactions of Lake Constance to climate change are determined by the physical, geographical and ecological characteristics of the lake. Hydrodynamic reactions are defined by the mixing type, water temperatures and the residence time of the water in the lake. Furthermore it is important that the lake is almost never completely ice-covered, and that there are only minor salinity differences. The reactions of the ecosystem are determined also by the oligotrophic state of the lake. Results of this study thus can be transferred to other deep, monomictic, oligotrophic fresh water lakes, as for example the other large perialpine lakes of glacial origin.
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    Statistical downscaling of extremes of precipitation in mesoscale catchments from different RCMs and their effects on local hydrology
    (2011) Alam, Muhammad Mahboob; Bardossy, Andras (Prof. Dr. rer. nat. Dr. -Ing.)
    Global climate models are the only available comprehensive tools for studying the affects of climate change on our earth in terms of changes in different meteorological and hydrological variables in future. Precipitation and temperature are two of the most important meteorological variables with regards to their affects on other meteorological (e.g. humidity, evaporation etc.) and hydrological (e.g. river runoff) variables and on human life (e.g. food fibre production, economy etc.). Among other important local and large scale phenomenon that affects the occurrence and amount of precipitation (and severity of temperature), geographical and topographical conditions perhaps play most important role in the behaviour of these variables in certain area. This makes the two variables more or less local phenomenons that need to be specifically studied for each area of interest individually. Unfortunately the scale at which global climate models (GCMs) operate is too large for any meaningful study to be performed related to future patterns of these two variables on local scale. Different methodologies have thus been developed to downscale (i.e. to increase the resolution of) GCM data to the local scale. The two broad categories of downscaling methodologies are statistical and dynamical downscaling. In statistical downscaling methodology, an attempt is made to develop a relationship between large scale GCM modelled variable (called predictor) and local scale observed/measured variable (called predictant). Assuming that in future this relationship will hold, the relationship is used to predict local scale predictand for future simulated scenarios of predictor. In dynamical downscaling (the so called regional climate models (RCMs)) on the other hand, an attempt is made to embed a complete physical model of more or less the same complexity as GCM, in a GCM and upon receiving values from GCM at its boundaries, recalculate all possible physical formulations at a much finer scale. The local conditions are thus taken in to account and the results are believed to be more suitable for local scale studies. Both downscaling methodologies have been extensively applied in climate change and impact studies around the world with varying degree of success and new techniques are consistently being developed to improve upon them. Both methodologies have associated advantages and disadvantages. While statistical downscaling is computationally much cheaper than RCMs, statistical downscaling is based on basic assumption of stationarity which is sometimes hard to justify. RCMs on the other hand although attempt to solve physical equations at local scale, does also inherit bias from the parent GCM. This thesis presents statistical downscaling methodology which attempts to correct for the biases that are inherited by different RCMs. Three different RCMs are considered for German part of Rhine basin and using bias correction methodology based on correction of quantiles of precipitation (and temperature for some studies), new scenarios of precipitation are developed. Further, a distributed version of conceptual hydrological model HBV is calibrated and validated for German part of Rhine basin and raw and downscaled RCM scenarios of precipitation are fed into the model to ascertain the future hydrological regime in face of climate change for this important river. The downscaling procedure briefly discussed above was applied in two ways. In the first case the statistical downscaling methodology was performed on RCM data without considering any constraint during quantile-quantile exchange between RCM control and scenario runs. In the second case, the quantile-quantile exchange was conditioned on occurrence of certain circulation pattern. It was briefly discussed above how precipitation (occurrence and amount) is conditioned by certain phenomenon. In addition to geographical and topographical location, precipitation also depends upon large scale circulation patterns. Thus it was assumed that conditioning the downscaling methodology also on circulation patterns would bring about better results. To realize above concept, classification of circulation patterns is performed. Fuzzy rule based classification methodology is used to classify circulation patterns. Two new methodologies of classification of circulation patterns are presented in this thesis. One is based on low flow conditions in rivers in the study area and the other is based on clustering of precipitation stations. The new classification methodology is believed to provide better classification of circulation patterns in that the difference between the individual classes is enhanced and similarity among the same class intensified. A classification analysis measure called wetness index was developed and used to identify critical circulation patterns among the classified circulation patterns. Critical circulation patterns were identified for extreme wet and dry conditions and it was shown that all extreme cases of floods and droughts are caused by identified critical CPs. This thesis also presents and applies another statistical downscaling methodology based on multivariate autoregressive model of order 1 (one). The methodology makes use of the classification of circulation patterns described above. The parameters of the autoregressive model depend upon the circulation patterns. The methodology is used for number of head catchments in southern and eastern Germany. Head catchments by definition have very quick response time to any significant precipitation event. They contribute quickly to the surface runoff and if they are head catchments of larger rivers, may also result in bigger flood events. Downscaling of precipitation was performed for these catchments by using mean sea level pressure (MSLP) as predictor and local station precipitation as predictant. The model was developed such that ensemble of daily precipitation could be produced. Thereby enabling one to estimate associated uncertainty. Finally drought analysis are performed for German part of Rhine basin using Palmer drought severity index. A FORTRAN routine is developed which can calculate different kind of drought indices such as Palmer drought severity index, Palmer hydrological drought index, and monthly moisture anomaly index for certain catchment. The program developed is also capable of simultaneously mapping the results. The mapping of results makes it possible to ascertain the severity of drought over the larger area. The analysis of drought is performed for observational gridded data set and for control and A1B scenarios of three different RCMs.
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    Large-scale high head pico hydropower potential assessment
    (Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2018) Schröder, Hans Christoph; Wieprecht, Silke (Prof. Dr.-Ing.)
    Due to a lack of site-related information, Pico hydropower (PHP) has hardly been a projectable resource so far. This is particularly true for large area PHP potential information that could open a perspective to increase the size of development projects by aggregating individual PHP installations. The present work is extending the capabilities of GIS based hydropower potential assessment into the PHP domain through a GIS based PHP potential assessment procedure that facilitates the discrimination of areas without high head PHP potential against areas with PHP potential and against areas with so called “favorable PHP potential”. The basic unit of the spatial output is determined by the underlying PHP potential definition of this work: a standardized PHP installation and the required hydraulic source, together called standard unit, are located on an area of one square kilometer. The gradation of the output is a consequence of the verification techniques. Several large area PHP potential field assessment methods, based on contemplative analysis techniques, are developed in this work. Field assessments were conducted in Yunnan Province/China, Costa Rica, Ecuador and Sri Lanka. The aim for all field assessments is to get a comprehensive view on the PHP potential distribution of the entire country/province. Application of the GIS based PHP potential assessment procedure is aimed at the global tropical and subtropical regions.
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    Porosity and permeability alterations in processes of biomineralization in porous media - microfluidic investigations and their interpretation
    (Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2022) Weinhardt, Felix; Class, Holger (apl. Prof. Dr.-Ing)
    Motivation: Biomineralization refers to microbially induced processes resulting in mineral formations. In addition to complex biomineral structures frequently formed by marine organisms, like corals or mussels, microbial activities may also indirectly induce mineralization. A famous example is the formation of stromatolites, which result from biofilm activities that locally alter the chemical and physical properties of the environment in favor of carbonate precipitation. Recently, biomineralization gained attention as an engineering application. Especially with the background of global warming and the objective to reduce CO2 emissions, biomineralization offers an innovative and sustainable alternative to the usage of conventional Portland cement, whose production currently contributes significantly to global CO2 emissions. The most widely used method of biomineralization in engineering applications, is ureolytic calcium carbonate precipitation, which relies on the hydrolysis of urea and the subsequent precipitation of calcium carbonate. The hydrolysis of urea at moderate temperatures is relatively slow and therefore needs to be catalyzed by the enzyme urease to be practical for applications. Urease can be extracted from plants, for example from ground jack beans, and the process is consequently referred to as enzyme-induced calcium carbonate precipitation (ECIP). Another method is microbially induced calcium carbonate precipitation (MICP), which uses ureolytic bacteria that produce the enzyme in situ. EICP and MICP applications allow for producing various construction materials, stabilizing soils, or creating hydraulic barriers in the subsurface. The latter can be used, for example, to remediate leakages at the top layer of gas storage reservoirs, or to contain contaminant plumes in aquifers. Especially when remediating leakages in the subsurface, the most crucial parameter to be controlled is its intrinsic permeability. A valuable tool for predicting and planning field applications is the use of numerical simulation at the scale of representative elementary volumes (REV). For that, the considered domain is subdivided into several REV’s, which do not resolve the pore space in detail, but represent it by averaged parameters, such as the porosity and permeability. The porosity describes the ratio of the pore space to the considered bulk volume, and the permeability quantifies the ease of fluid flow through a porous medium. A change in porosity generally also affects permeability. Therefore, for REV-scale simulations, constitutive relationships are utilized to describe permeability as a function of porosity. There are several porosity-permeability relationships in the literature, such as the Kozeny-Carman relationship, Verma-Pruess, or simple power-law relationships. These constitutive relationships can describe individual states but usually do not include the underlying processes. Different boundary conditions during biomineralization may influence the course of porosity-permeability relationships. However, these relationships have not yet been adequately addressed. Pore-scale simulations are, in principle, very well suited to investigate pore space changes and their effects on permeability systematically. However, these simulations also rely on simplifications and assumptions. Therefore, it is essential to conduct experimental studies to investigate the complex processes during calcium carbonate precipitation in detail at the pore scale. Recent studies have shown that microfluidic methods are particularly suitable for this purpose. However, previous microfluidic studies have not explicitly addressed the impact of biomineralization on hydraulic effects. Therefore, this work aims to identify relevant phenomena at the pore scale to conclude on the REV-scale parameters, porosity and permeability, and their relationship. Contributions: This work comprises three publications. First, a suitable microfluidic setup and workflow were developed in Weinhardt et al. [2021a] to study pore space changes and the associated hydraulic effects reliably. This paper illustrated the benefits and insights of combining optical microscopy and micro X-ray computed tomography (micro XRCT) with hydraulic measurements in microfluidic chips. The elaborated workflow allowed for quantitative analysis of the evolution of calcium carbonate precipitates in terms of their size, shape, and spatial distribution. At the same time, their influence on differential pressure could be observed as a measure of flow resistance. Consequently, porosity and permeability changes could be determined. Along with this paper, we published two data sets [Weinhardt et al., 2021b, Vahid Dastjerdi et al., 2021] and set the basis for two other publications. In the second publication [von Wolff et al., 2021], the simulation results of a pore-scale numerical model, developed by Lars von Wolff, were compared to the experimental data of the first paper [Weinhardt et al., 2021b]. We observed a good agreement between the experimental data and the model results. The numerical studies complemented the experimental observations in allowing for accurate analysis of crystal growth as a function of local velocity profiles. In particular, we observed that crystal aggregates tend to grow toward the upstream side, where the supply of reaction products is higher than on the downstream side. Crystal growth during biomineralization under continuous inflow is thus strongly dependent on the locally varying velocities in a porous medium. In the third publication [Weinhardt et al., 2022a], we conducted further microfluidic experiments based on the experimental setup and workflow of the first contribution and published another data set [Weinhardt et al., 2022b]. We used microfluidic cells with a different, more realistic pore structure and investigated the influence of different injection strategies. We found that the development of preferential flow paths during EICP application may depend on the given boundary conditions. Constant inflow rates can lead to the development of preferential flow paths and keep them open. Gradually reduced inflow rates can mitigate this effect. In addition, we concluded that the coexistence of multiple calcium carbonate polymorphs and their transformations could influence the temporal evolution of porosity-permeability relationships.
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    Modellierung von Bodenerosion und Sedimentaustrag bei Hochwasserereignissen am Beispiel des Einzugsgsgebiets der Rems
    (Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2022) Schönau, Steffen; Bárdossy, András (Prof. Dr. rer. nat. Dr.-Ing.)
    Die vorliegende Dissertation untersucht Bodenerosion und Sedimentaustrag bei Hochwasserereignissen und Starkniederschlägen im Einzugsgebiet der Rems (Flussgebiet Neckar, Stromgebiet Rhein). Es werden die Grundlagen des Zusammenspiels von (Stark-) Niederschlag, Hochwasser und Sturzfluten, Bodenerosion und Sedimentaustrag sowie deren messtechnische und modellbasierte Erfassung dargestellt. Die Anwendung empirischer Modellansätze im Untersuchungsgebiet beinhaltet Modellparametrisierung, -kalibrierung und -validierung sowie Regionalisierung für die Übertragbarkeit auf unbeobachtete Gebiete. Es erfolgt eine Untersuchung des räumlichen Zusammenhangs der flächenhaften Eingangsdaten und Modellergebnisse sowie die Beurteilung der Wirkung von konservierender Bodenbearbeitung auf die Bodenabtrags- und Sedimentaustragsschätzungen. Es werden sowohl langandauernde advektive, zu Flusshochwasser führende Niederschlagsereignisse betrachtet als auch kurzzeitige konvektive Sommerereignisse, die nur zu wenig Abfluss oder aber auch zu Sturzfluten führen. Mit der entwickelten Methodik können saisonale und gebietsspezifische Eigenheiten wie Niederschlagscharakteristika, Landnutzung und Landbedeckung sowie Anfangsbodenfeuchte berücksichtigt werden. Ein Ergebnis ist die Bereitstellung von Eingangsdaten für die Optimierung der Steuerung von Hochwasserrückhaltebecken und Speichern zur gezielten Retention stofflicher Belastungen. Teile der Untersuchungen für diese Dissertation haben ihren Ursprung im RIMAX-Verbundvorhaben "Entwicklung eines integrativen Bewirtschaftungskonzepts für Trockenbecken und Polder zur Hochwasserrückhaltung".
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    Investigations on functional relationships between cohesive sediment erosion and sediment characteristics
    (Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2021) Beckers, Felix; Wieprecht, Silke (Prof. Dr.-Ing.)
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    Long-term lumped projections of groundwater balances in the face of limited data
    (Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2024) Ejaz, Fahad; Nowak, Wolfgang (Prof. Dr.-Ing.)
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    Bayesian inversion and model selection of heterogeneities in geostatistical subsurface modeling
    (Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2021) Reuschen, Sebastian; Nowak, Wolfgang (Prof. Dr.-Ing.)
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    Investigation of changes in hydro-meteorological time series using a depth-based approach
    (2015) Yulizar; Bárdossy, András (Prof. Dr. rer. nat. Dr.-Ing.)
    The climate is a complex interactive system between the atmosphere, the land surface, the oceans and others. A change in climate is not an issue of one or two days, but it takes place over a long period of time. Hydrology is one of the fields that is affected due to climate change. It describes the process of the movement of water on Earth, also known as the water cycle system. In this field, temperature and precipitation are the two main parameters that need to be analyzed in order to know about the water cycle system's behavior. Temperature increases throughout the globe and changes in precipitation distribution are two examples where change has already occurred on Earth. These phenomena that occur on Earth give us information about changes in the meteorological variables which have no boundaries and which affect the process of the water cycle system. This means that changes in the hydro-meteorological series might not only affect the means, variances, and extremes at individual locations, but they might also have an affect on the spatial and temporal dynamics. These changes in the multivariate scale would lead to the occurrence of unusual events. An example of an unusual event could be, one area being very warm but at the same time another area being very cold. Situations that have never occurred before might appear and others might disappear. Within the framework of this research, the frequencies and magnitudes of unusual events on temporal and spatial scales are investigated. Here a statistical tool that is called a depth function is used. It is based on the outlyingness function. Many types of depth function have been developed nowadays, and in this study the half-space depth function is used due to its robustness for defining the occurrence of unusual events. The general idea of a depth function is to measure the centrality of a point with respect to a dataset. Here, points that have a low depth that are located on, near, and outside a boundary are classified as unusual events. In another word, unusual events are defined based on their geometrical position in a multivariate set of observations using outlyingness function. Under this definition, all extremes are unusual events, but other combinations might also be considered as unusual. In this study, a low depth value with a threshold of 5 is used for the analysis. The main methodology is based on a cross depth calculation. It enables the identification of newly appearing and disappearing situations. Three possibilities might be obtained from the analysis; growing, shrinking, and translation. The daily data from temperature and precipitation series across Europe and the United States are used in this study to illustrate the methodology. In addition, the daily discharge series from the River Rhine and the River Neckar in Germany are also used to define the occurrence of unusual events. The investigation was carried out based on spatial and temporal scales that consist of discrete and over-time analysis, respectively. In the discrete approach, two equally long periods were analyzed with a cross depth calculation, so that we will define on how many days there are appearances and disappearances. In another way, the over-time approach or moving windows analysis with different aggregation levels was used so that we can observe the oscillation of unusual events. From the analysis, it shows any individual events may not be considered as an extreme at one time or one location, but due to their joint or simultaneous occurrence, it might lead to extreme events on a multivariate scale. These events, furthermore are called as unusual events. The results show that all the hydro-meteorological events show an oscillation in the occurrence unusual events. This means that unusual events not only occur at one time, but they change dynamically at different time periods on the spatial and temporal scales. In the temperature series, we can clearly observe that unusual events change dynamically from time to time. A similar situation also can be found in the precipitation series, where the unusual events show an oscillation in their occurrence. In the precipitation analysis, zero values are taken into consideration during the investigation. The discharge series also shows a similar condition with temperature and precipitation, where they have an oscillation in the occurrence of unusual events. With regard to magnitude, the number of unusual days for temperature is higher than for precipitation. This result leads to a situation, for instance, where droughts occur for a longer time than floods, that take place on a short time scale. Another result also shows that the occurrence of unusual precipitation does not showing a coherent situation with regard to the occurrence of unusual discharge events. This situation might be influenced by a time lag in the rainfall going between the surface into the river, catchment characteristics, river training, and others.
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    Advanced experimental methods for investigating flow-biofilm-sediment interactions
    (Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2022) Koca, Kaan; Wieprecht, Silke (Prof. Dr.-Ing.)