Universität Stuttgart
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Item Open Access 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.)Item Open Access Electrical resistivity tomography (ERT) measurements on date palm stems to support irrigation scheduling(2025) Bukhary, Tarig; Huisman, Johan Alexander (Prof. Dr.)Commercial cultivation of date palms has high economic significance, particularly in arid and hyper-arid regions. In Israel, the commercial cultivation of date palms in the hyper-arid Arava and Jordan valleys (from the Sea of Galilee, along the Jordan valley to the Red Sea) has grown substantially in the past two decades. As such, achieving commercially viable yield of dates amid water scarcity and enforced restrictions on water use requires optimising the amount and timing of irrigation. To that end, better understanding of the temporal dynamics of the water use of date palm is of great importance. Traditionally, this can be achieved through sap flow estimates obtained using heat dissipation probes. However, such measurements lack the ability to provide information on the spatial distribution of sap flow, which is important considering that date palms transport water in the entire stem cross-section. Electrical resistivity tomography (ERT), a long established and widely used geophysical method for the imaging and characterisation of sub-surface structures may allow for obtaining improved estimates of transpiration from sap flow measurements and the assessment of stem water dynamics. The aim of this thesis is thus to explore the potential of combining sap flow and electrical measurements to obtain a better understanding of the transpiration and the spatiotemporal dynamics of water flow and storage in date palm trunks. In a first step, a suitable ERT set-up and data acquisition strategies were developed starting from ERT measurements on a sand column as a proof-of-concept, where ERT was used to monitor the progress of a tracer solution through a sand column. The results showed that the adopted strategy for ERT measurement acquisition was successful in capturing the development and breakthrough of the introduced tracer solution, not only in terms of the average real part of the electrical conductivity at each electrode plane, but also in terms of the spatial distribution of the real part of the electrical conductivity. The outcome of the flow experiment on a sand column was used as a starting point to further develop the ERT set-up and data acquisition strategies for measuring on date palm stems, which were then tested on a date palm stem segment. For this, flow was induced through a stem segment that was obtained from a felled date palm tree. ERT measurements were continuously obtained throughout a cycle of flow and no-flow periods. The results showed that the mean bulk electrical conductivity varied strongly due to changes in the flow conditions. In addition, it was found that the electrical conductivity of the outflow was much higher than that of the inflow, which indicates the release of stored salt from the stem segment. Analysis of the spatial distribution of the electrical conductivity suggested that flow mainly occurred in a limited part of the cross-sectional area of the stem. Extending from the flow experiment on a date palm stem segment, the electrical properties were further investigated using a multi-step outflow experiment on a smaller stem fragment. The results showed a slow water release from the date palm stem segment with increasing applied pressure, which suggests that the water is tightly bound in the stem as in a clay soil. The real part of the bulk electrical conductivity of the stem segment showed a declining pattern, which is generally in agreement with the decreasing water content in the stem segment. The real part of the electrical conductivity decreased with the saturation of the stem segment in a pattern that closely resembled that of a clay soil. From the laboratory experiments, it was concluded that ERT is a promising tool to investigate the spatial variability of water flow in date palm stems. In a second step, two field experiments involving irrigation deprivation were conducted on living date palms. In both experiments, ERT measurements were obtained at high temporal resolution following the established set-up and data acquisition strategies from the experiments in the laboratory. Sap flow estimates were obtained from heat dissipation probes in conjunction with continuous ERT measurements. The first experiment involved a juvenile date palm growing in a lysimeter, while the second experiment involved a mature date palm. The combined sap flow and ERT measurements were continuously obtained for a baseline period, followed by an induced water stress period. The monitoring was continued during the recovery period following the restoration of the irrigation treatment for a few days. It was found that the diurnal variations in the electrical properties of the date palm stem during the baseline period were consistent with the expected diurnal variation in transpiration and stem water storage. The findings also made clear that capturing those diurnal variations would not be possible without following a measurement acquisition strategy utilising a high temporal resolution. During the irrigation deprivation period, the juvenile date palm showed a strong response to water stress, as observed in the temporal dynamics of the average real part of the electrical resistivity over the plane as well as the average real part of the transfer impedances. The mature palm, on the other hand, showed no clear signs of water stress during the irrigation deprivation period. This finding was consistent with the results obtained on soil water content, which showed that the loss in water was superficial (above 60 cm depth). Furthermore, the observed spatial variation in the real part of the electrical resistivity showed that some regions of the stem cross-sectional area were more active than others, and that the distribution of areas with high and low electrical resistivity was dynamically changing throughout the day and night. This observation suggests an on-going redistribution of the stem water content and continuous changes in stem water storage. It was further observed that the areas with high electrical resistivity noticeably increased following the suspension of the irrigation treatment. A closer examination of this finding indicated that this was more evident for the juvenile date palm than for the mature date palm. The obtained sap flow estimates and ERT data showed no signs of quick recovery in case of the juvenile date palm after the irrigation was restored. However, subsequent monitoring showed that the juvenile date palm did eventually recover after a few weeks. The results further showed that the mature date palm did not experience significant water stress and by extension recovery. A long-term monitoring on a bi-monthly basis on the mature date palm showed a temporally stable spatial distribution of the real part of the electrical resistivity for measurements made at the same time for a period of several months. This finding provides further confidence in the established ERT set-up and data acquisition strategies as an approach to support irrigation scheduling for date palms and detecting early signs of water stress. In conclusion, the work presented in this thesis provides an important contribution to the establishment of a combined approach in which sap flow estimates obtained from heat dissipation probes and continuous ERT measurements are jointly used to obtain improved monitoring and interpretation of water flow and storage in date palm stems. It was shown that the proposed set-ups, ERT data acquisition protocols and inversion strategies allow for reliably obtaining representative ERT measurements on date palm stems that enabled monitoring of spatiotemporal variability in water flow and storage in date palm stems. The proposed approach also allows for improved estimation of daily variation in transpiration requirements, and detecting of early signs of water stress, which can make a valuable contribution to the planning and scheduling of irrigation treatments that account for transpiration requirements of date palms while adhering to imposed limitation in water use.Item Open Access 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.)Item Open Access Precipitation time-series generation using spectral methods(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2025) Mehrvand, Masoud; Bárdossy, András (Prof. Dr. rer. nat. Dr.-Ing.)Item Open Access Development and parameter estimation of conceptual snow-melt models using MODIS snow-cover distribution(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2023) Gyawali, Dhiraj Raj; Bárdossy, András (Prof. Dr. rer. nat. Dr.-Ing.)Due to a high spatio-temporal variability observed in the inherent snow-related processes in snow-dominated regimes, reliable representation of spatial distribution of seasonal snow has remained a critical challenge for effective monitoring of seasonal evolution of snow and subsequently hydrological estimations, in mountainous regions around the world. This issue, coupled with the crucial relevance to climate change, is further exacerbated by data scarcity in these regions. To address this issue, this thesis presents a novel standalone calibration technique employing the pixel-wise binary (’snow’, ’no snow’) information from MODIS snow-cover images to calibrate independent conceptual snow-melt models, thereby estimating model parameters from individual or sets of MODIS images. This methodology exploits the pertinent information of snow-cover distribution from the freely available remote sensing images, to reliably simulate snow-processes in data scarce regions. Switzerland and Baden-Württemberg were selected as study snow regimes, with the former representing partly longer duration snow and the latter associated with a shorter duration. Different extensions of parsimonious conceptual snow-melt models were developed and used to simulate the snow-cover distribution, with all models showcasing an adept and robust simulation. The selection of binary snow-cover information as calibration variable permits relatively complex snow-melt modules to be calibrated with more robustness because of reduced uncertainty associated with the calibration data. This work further identifies and recommends different simulation thresholds for defining the calibration data (NDSI thresholds), selecting the images for calibration (cloud cover thresholds), and reclassifying the snow water equivalent (SWE) outputs to snow-cover information (SWE thresholds). Furthermore, validation of the MODIS based snow-melt model calibration and the simulated melt outputs was carried out using a modified hydrological model (modified HBV variant) without the snow-routine. This hydrological performance was contrasted with the standard HBV model calibrated solely on discharge. The melt output provided as standalone inputs to the modified HBV was observed to impart an enhanced discharge prediction. As compared with the discharge calibrated standard HBV, a reduction in uncertainty in terms of model performance was observed along with reduced parameter compensation. The increase in model performance is deemed for ‘the right reason’ as the snow processes are adeptly represented by process-informed parameters. The estimation of the parameters solely from MODIS information not only eliminates the reliance on a single calibration variable ’discharge’ which is already an availability constraint in the higher altitudes but also preserves the spatial heterogeneity at a more regional level. This methodology holds a crucial relevance for discharge simulation in areas with episodic days of snow, where the snow processes can be calibrated quickly on images without having to calibrate the entire hydrological model. The study approach shows that the addition of freely available snow-cover information in estimating the parameters of snow-melt models utilizing the snow/no-snow information and a modest and globally available input data demand, facilitates a simple, spatially flexible approach to calibrate snow-cover distribution in mountainous areas with reasonably accurate precipitation and temperature data, especially in data scarce regions.Item Open Access Development of efficient multiscale multiphysics models accounting for reversible flow at various subsurface energy storage sites(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2021) Becker, Beatrix; Helmig, Rainer (Prof. Dr.-Ing.)Energy storage is an essential component of future energy systems with a large share of renewable energy. Apart from pumped hydro storage, large scale energy storage is mainly provided by underground energy storage systems. In this thesis we focus on chemical subsurface storage, i.e., the storage of synthetic hydrogen or synthetic natural gas in porous formations. To improve understanding of the complex and coupled processes in the underground and enable planning and risk assessment of subsurface energy storage, efficient, consistent and adequate numerical models for multiphase flow and transport are required. Simulating underground energy storage requires large domains, including local features such as fault zones and a representation of the transient saline front, and simulation times spanning the whole time of plant operation and beyond. In addition, often a large number of simulation runs need to be conducted to quantify parameter uncertainty, and efficient models are needed for data assimilation as well. Therefore, a reduction of model complexity and thus computing effort is required. Numerous simplified models that require less computational resources have been developed. In this thesis we focus on a group of multiscale models which use vertically integrated equations and implicitly include fine-scale information along the vertical direction that is reconstructed assuming vertical equilibrium (VE). Classical VE models are restricted to situations where vertical equilibrium is valid in the whole domain during most of the simulated time. This may not be the case for underground energy storage, where simulated times may be too short and locally a high degree of accuracy and complexity may be required, e.g., around the area where gas is extracted for the purpose of energy production. The three core chapters of this thesis present solutions to adapt VE models for the simulation of underground energy storage, with increasing complexity.Item Open Access A surrogate-assisted Bayesian framework for uncertainty-aware validation benchmarks(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2023) Mohammadi, Farid; Flemisch, Bernd (apl. Prof. Dr. rer. nat.)Over the last century, computational modeling in geoscience, especially in porous media research, has witnessed tremendous improvement. After decades of development, the state-of-the-art simulators can now solve coupled partial differential equations governing the complex subsurface multiphase flow system within a practically large spatial and temporal domain. Given the importance of computational modeling, quality assessment of these models in light of the purpose of a given simulation is of paramount importance to engineering designers and managers, public officials, and those affected by the decisions based on the predictions. Users and developers of computational simulations deal with a challenging question: How should confidence in modeling and simulation be critically assessed? Validation is one of the primary methods for building and quantifying confidence in modeling and simulation. It investigates the degree to which a model accurately represents reality from the perspective of the intended application of the model. Usually, this comparison between model outputs and experimental data constitutes plotting the model results against data on the same axes to provide a visual assessment of agreement or lack thereof. While comparisons between model and data are at the heart of any validation procedure, there are several concerns with such naive comparisons. First, these comparisons tend to provide qualitative rather than quantitative assessments and are clearly insufficient as a basis for making decisions regarding model validity. Second, naive comparisons often disregard or only partly account for existing uncertainties in the experimental observations or the model input parameters. Third, such comparisons can not reveal whether the model is appropriate for the intended purposes, as they mainly focus on the agreement in the observable quantities. These pitfalls give rise to the need for an uncertainty-aware framework that includes a validation metric. This metric shall provide a measure for comparison of the system response quantities of an experiment with the ones from a computational model while accounting for uncertainties in both in a rigorous way. To address this need, we developed a statistical framework incorporating a probabilistic modeling technique using a fully Bayesian approach. The dissertation aims to help modelers perform uncertainty aware model validation benchmarks. A two-stage Bayesian multi-model framework is discussed for modeling tasks where a set of models are at hand. To make this framework applicable for computationally demanding models, it is extended to a surrogate-assisted framework, keeping the computational costs at a reasonable level. Moreover, correction factors were introduced to compensate for the surrogate error in the Bayesian hypothesis testing and Bayesian model selection, as using surrogate representations instead of the full-fidelity computational models introduces additional errors to the validation metrics. In this dissertation, I show how the Bayesian formalism could be materialized by employing the concept of polynomial chaos expansion to achieve more accurate surrogates with a sparse representation and account for the uncertainty in the surrogate’s predictions. I also highlight how such surrogate models could be constructed with as few simulations as the computational budget allows. To this end, sequential adaptive sampling strategies are discussed, in which one attempts to augment the initial design iteratively. By doing so, informative regions in the parameter space are adequately explored. These regions are more likely to provide valuable information on the behavior of the original model responses. Using a sequential sampling strategy avoids the waste of computational resources, as opposed to the so-called one-shot designs. A series of benchmark studies are conducted to investigate the predictive capabilities of different sparsity and sequential adaptive sampling methods. Moreover, I introduce BayesValidRox, an open-source, object-oriented Python package that provides an automated workflow for surrogate-based sensitivity analysis, Bayesian calibration, and validation of computational models with a modular structure. The uncertainty-aware validation framework was applied to a range of cases in the field of subsurface hydro-system modeling, mainly to flow and transport in porous media, such as flow simulation models in fractured porous media, coupling free flow and porous medium flow, and microbially induced calcite precipitation. However, this validation framework can be transferred to other disciplines in which models are used for prediction.Item Open Access Modeling fixed-bed reactors for thermochemical heat storage with the reaction system CaO/Ca(OH)2(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2021) Seitz, Gabriele; Class, Holger (apl. Prof. Dr.-Ing.)Item Open Access Numerical modelling of bedload transport in rivers using implicit time discretisation to realise full and sequential coupling with shallow water flow(Stuttgart : Eigenverlag des Instituts für Wasser- und Umweltsystemmodellierung der Universität Stuttgart, 2025) Utz, Martin; Flemisch, Bernd (apl. Prof. Dr. rer. nat.)Item Open Access 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.