06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
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Item Open Access Der Einfluss der kontinentalen Wasserspeicherung auf das Rotationsverhalten der Erde(2008) Hengst, Rico; Wolf, Detlef (Prof. Dr. rer. nat. habil.)Die Schwankungen der Rotationsgeschwindigkeit der Erde und die Richtungsänderungen des Erdrotationsvektors werden mit modernen geodätischen Raumverfahren beobachtet und lassen sich auf Gravitationswechselwirkungen mit anderen Himmelskörpern und auf geophysikalische Prozesse zurückführen. Nach der Reduktion der beobachteten Erdrotationsschwankungen bezüglich der bekannten gravitativen Einflüsse werden die verbleibenden Schwankungen des Erdrotationsvektors maßgeblich durch Massenverlagerungen und Relativbewegungen von Massen in den einzelnen Teilsystemen der Erde, wie z.B. der Atmosphäre, hervorgerufen. Da die reduzierten geodätischen Beobachtungen stets die integrale Folgeerscheinung aller geophysikalischen Prozesse darstellen, sind einzelne ursächliche Anregungen nicht eindeutig identifizierbar. Eine Dekomposition und eine Interpretation des verbleibenden Restsignals erfordert es daher, den Zustand der Teilsysteme mit Messungen physikalischer Größen oder mit Hilfe von numerischen Modellen zu beschreiben. Neben der Analyse von Modellen der Atmosphäre und des Ozeans bezüglich der Erdrotationsschwankungen liegt der Schwerpunkt dieser Arbeit in der Untersuchung von vier hydrologischen Modellen, die die kontinentale Wasserspeicherung simulieren. Im Kontext der kontinentalen Massenverlagerungen werden die hydrologischen Modelle und die hinsichtlich atmosphärisch-ozeanischer Einflüsse reduzierten Schwerefeldbeobachtungen der GRACE-Mission verglichen, wobei sich die Untersuchung nicht auf den globalen Massenumsatz beschränkt, sondern zusätzlich um regionale Analysen erweitert ist. Die ermittelten Differenzen im jährlichen Massenumsatz zwischen den einzelnen Modellen und auch zwischen den Modellen und den GRACE-Daten ergeben mit Hinblick auf die Erdrotationsschwankungen ein unterschiedliches Anregungspotenzial (chi-Funktionen). So treten zwischen den modellierten und den aus Schwerefeldbeobachtungen resultierenden Anregungen Differenzen auf, die in den äquatorialen chi-Funktionen einer Phasenverschiebung der Jahresschwingung von bis zu drei Monaten entsprechen. Wavelet-Analysen der hydrologischen chi-Funktionen zeigen episodische und quasiperiodische Signalanteile auf, die zwischen den einzelnen Modellen signifikante Korrelationen aufweisen. Entsprechende Signalcharakteristika werden auch in den um gravitative, atmosphärische und ozeanische Einflüsse reduzierten Beobachtungen der Erdrotationsschwankungen detektiert. Als Ursachen stellen sich die Oszillationen ENSO (El Niño Southern Oscillation), QBO (Quasibiennial Oscillation), TBO (Tropospheric Biennial Oscillation) und der indische Monsun heraus, die adäquate Variationen in der Wasserspeicherung Südamerikas, Australiens and Asiens bewirken. Um die Übereinstimmungen zwischen den geodätischen Beobachtungen und den modellierten Anregungen aus atmosphärischen, ozeanischen und kontinentalhydrologischen Prozessen quantifizieren zu können, werden die Zeitreihen mit dem Verfahren der spektralen MRA (multiple Regressionsanalyse) untersucht. Im spektralen Band zwischen 10 und 13 Monaten ergeben sich Widersprüche, die auf der Modellierungsseite Probleme in einer der hier untersuchten atmosphärisch-ozeanischen Kombinationen signalisieren, unabhängig von der Wahl der hydrologischen Simulation. Je nachdem welche Modelle bei der spektralen MRA miteinander kombiniert werden, erklären diese im Spektralbereich zwischen 2 und 30 Monaten die Varianz der Tageslängenschwankung im Mittel zu 93% und die Varianz der beobachteten Polbewegung zu durchschnittlich 77%.Item Open Access Assessing the statistical relations of terrestrial water mass change with hydrological variables and climate variability(2019) Zhang, Jinwei; Sneeuw, Nico (Prof. Dr.-Ing.)Item Open Access Surface deformation analysis of dense GPS networks based on intrinsic geometry : deterministic and stochastic aspects(2007) Moghtasad-Azar, Khosro; Grafarend, Erik W. (Prof. Dr.-Ing. habil. Dr. tech. h. c. mult. Dr.-Ing. E. h. mult)The first step in this study is to review the properties of surface which are inherent to the surface and can be described without referring to the embedding space. In other words, it is a method of differential geometry. The methods of moving frames which allows deformation of surface could be described by its own rights as a more reliable estimate of surface deformation measures. The method takes advantage of the simplicity of the 2D surface versus the 3D Euclidean spaces without losing or neglecting information about the third dimension in the results. Based on this method, deformation can be described by using tangent vectors and the unit normal basis vector (attached to the bodies before and after deformation). However, basis vectors of the deformed configuration will need to complete information of intrinsic properties of the deformed surface. Through this method, regularized Earth's surface is considered as a graded 2D surface, namely a curved surface, embedded in a Euclidean space . Thus, deformation of the surface can be completely specified by the change of the metric and curvature tensors, namely strain tensor and tensor of change of curvature (TCC). The curvature tensor, however, is responsible for the detection of vertical displacements on the surface. The next step of this study is to concentrate the local basis vectors of the deformed surface which can be formulated in terms of the local basis vectors of undeformed surface and curvilinear components of displacement vector. This will provide a representation of the intrinsic geometry of the deformed surface with deriving information about the displacement field. The new formulation of base vectors (for the deformed body) produces meaningful numerical results for the TCC and its associated invariants (mean and Gaussian curvatures). They can propose a shape-classification of the deformed surface based upon signs of mean and Gaussian curvatures which are new tools for studying the Earth's deformation. To enhance our understanding of the capabilities of the proposed method in defining new basis vectors (for deformed body), we present two examples, one with a simulated data set and the other with a real data set. However, through a real data set we demonstrated a comparison between the proposed method with the plane strain model (2D classical method). Dealing with eigenspace components e.g., principal components and principal directions of 2D symmetric random tensors of second order is of central importance in this study. In the third step of this research, we introduce an eigenspace analysis or a principal component analysis of strain tensor and TCC. However, due to the intricate relations between elements of tensors on one side and eigenspace components on other side, we will convert these relations to simple equations, by simultaneous diagonalization. This will provide simple synthesis equations of eigenspace components (e.g., applicable in stochastic aspects). The last part of this research is devoted to stochastic aspects of deformation analysis. In the presence of errors in measuring a random displacement field (under the normal distribution assumption of displacement field), stochastic behaviors of eigenspace components of strain tensor and TCC are discussed. It is performed by a propagation of errors from the displacement vector into elements of deformation tensors (strain and TCC). However, due to the intricacy of the relations between tensor components (strain or TCC) and their eigenspace components, we proceeded via simultaneous diagonalization. This part is followed by a linearization of the nonlinear multivariate Gauss - Markov model, which links the elements of transformed tensors (obtained by simultaneous diagonalization) with the eigenspace components. Then, we set up an observation model based on a linearized model under a sampling of eigenspace synthesis. Furthermore, we establish linearized observation equations for n samples of independent random vectors from transformed tensor elements (under the normal distribution assumption), each with an individual covariance matrix. This will provide us with the second-order statistics of the eigenspace components. Then we estimate the covariance components between transformed tensor elements by Helmert estimator, based on prior variance information. To enhance conceptual understanding of stochastic aspects of deformation analysis, the method is applied to a real data set of dense GPS network of Cascadia Subduction Zone(CSZ). Comparing the results showed that, in general, after estimating the covariance matrix of observations (transformed tensors via simultaneous diagonalization), variances of eigenspace components become smaller. However, in some areas this did not occur, which can be related to an incorrect description of initial accuracies, either too optimistic or too pessimistic.Item Open Access Understanding ocean tide aliasing in satellite gravimetry(2019) Liu, Wei; Sneeuw, Nico (Prof. Dr.-Ing.)Item Open Access Dynamic water masks from optical satellite imagery(München : Verlag der Bayerischen Akademie der Wissenschaften, 2019) Elmi, Omid; Sneeuw, Nico (Prof. Dr.-Ing.)Investigation of the global freshwater system has a vital role in critical issues e.g. sustainable development of water resources, acceleration of the hydrological cycle, variability of global sea level. Measurement of river streamflow is vital for such investigations as it gives a reliable estimate of freshwater fluxes over the continents. Despite such importance, the number of river discharge gauging station has been decreasing. At the same time, information on the global freshwater system has been increasing because of various types of ground observations, water-use information and spaceborne geodetic observations. Nevertheless, we cannot answer properly crucial questions about the amount of freshwater available on a certain river basin, or the spatial and temporal dynamics of freshwater variations and discharge, or the distribution of world’s freshwater resources in the future. The lack of comprehensive measurements of surface water storage and river discharge is a major impediment for a realistic understanding of the hydrological water cycle, which is a must for answering the aforementioned questions. This thesis aims to improve the methods for monitoring the surface extent of inland water bodies using satellite images. Satellite imaging systems capture the Earth surface in a wide variety of spectral and spatial resolution repeatedly. Therefore satellite imagery provides the opportunity to monitor the spatial change in shorelines, which can serve as a way to determine the water extent. Each band of a multispectral image reveals a unique characteristic of the Earth surface features like surface water extent. However selecting the spectral bands which provide the relevant information is a challenging task. In this thesis, we analyse the potential of multispectral transformations like Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA) to tackle this issue by condensing the information available in all spectral bands in just a few uncorrelated variables. Moreover, we investigate how the change between multispectral images at different epochs can be highlighted by using the transformations. This study proposes an automatic algorithm for extracting the lake water extent from MODIS images and generating dynamics lake masks. For improving the accuracy of the lake masks and computational efficiency of the algorithm, two masks are defined for limiting the search area. The restricting masks are developed according to DEM of the surrounding area together with a map of the long-term variation of pixel values. Subsequently, an unsupervised pixel-based classification algorithm is applied for defining the lake coastline. The algorithm particularly deals with the challenges of generating long time series of lake masks. We apply the algorithm on five lakes in Africa and Asia, each of which demonstrates a challenge for lake area monitoring. However in the validation section, we demonstrate that the algorithm can generate accurate dynamic lake masks. Rivers show diverse behaviour along their path due to the contribution of different parameters like gradient of the elevation, river slope, tributaries and river bed morphology. Therefore for generating accurate river reach mask, we need to consider additional sources of information apart from pixel intensity. The region-based classification algorithm that we propose in this study takes advantages of all types of available information including pixel intensity and spatial and temporal interactions. Markov Random Fields provide a flexible frame for interaction between different sources of data and constraint. To find the most probable configuration of the field, the Maximum A Posteriori solution for the MRF must be found. To this end, the problem is reshaped as an energy minimization. The energy function is minimized applying graph cuts as a powerful optimization technique. The uncertainty in the graph cuts solution is also measured by calculating the minimum marginal energies. The proposed method is applied to four rivers reaches with different hydrological characteristics. We validate the obtained river area time series by comparing with in situ river discharge and satellite altimetric water level time series. Moreover, in this study, we present river discharge estimation models using the generated river reach masks. Our aim is to find an empirical relationship between the average river reach width and river discharge. The statistics in the validation periods support the idea of using river width-discharge prediction models as a complementary technique to the other spaceborne geodetic river discharge prediction approaches.Item Open Access Analyzing and modeling environmental loading induced displacements with GPS and GRACE(2015) Chen, Qiang; Sneeuw, Nico (Prof. Dr.-Ing.)The redistribution of atmospheric, oceanic and hydrological masses on the Earth's surface varies in time and this in turn loads and deforms the surface of the solid Earth. Analyzing such environmental loading signal and modeling its induced elastic displacements are of great importance for explaining geophysical phenomena. Based on the well-established loading theory, this thesis makes use of two different space-borne measurements, i.e. GPS and GRACE, along with other environmental loading data to investigate three different aspects of environmental loading and its induced elastic deformations: Firstly, an increasing concern is observed recently over time variable seasonal signals in geodesy. Several model based approaches were applied to extract amplitude and phase modulated annual and semiannual signals. In view of this phenomenon, this thesis introduces an alternative approach, namely, singular spectrum analysis (SSA). With respect to these model-dependent approaches, the advantage of SSA lies in data-driven and model-independence. Several aspects regarding the application of SSA, e.g. optimal choice of window size, are investigated before showing its abilities. Through applying SSA to the lake level time series of Lake Urmia (Iran) and the basin averaged equivalent water height time series of the Congo basin, the capabilities of SSA in separating time varying seasonal signals are demonstrated. In addition, we find that SSA is also able to extract the non-linear trend as well as long-term oscillations from geodetic time series. Secondly, we look into the comparison between GPS and GRACE with an emphasis on GRACE data filtering. Three types of deterministic filters and two types of stochastic filters are studied and compared over GPS sites from two regions, i.e. the Europe area and the Amazon area. The comparisons indicate that no single filtering scheme could provide consistently better performance over other considered filters. However, we find that the stochastic filters generally show better performance than the deterministic filters. The DDK 1 filter outperforms other filters in the Europe area and the regularization filter of parameter lambda=4, which follows the concept of the DDK filters, shows optimal performance in the Amazon area. The combination of the isotropic Gaussian filter of a low smoothing radius, e.g. around 300 km with the destriping filter is proved to be optimal filter choice if only the deterministic filters are considered. Thirdly, based on an overview of displacements modeling at various spatial scales, we evaluate three methods, i.e. two types of half-space approaches and the classic Green function approach, by using a high spatial resolution local load data along the lower Mississippi river when a severe flood happened in 2011. The equivalence between the two half-space approaches, i.e. point load approach and surface load approach, are demonstrated with the local load data. However, the point load approach is recommended for practical use in terms of computational efficiency. In addition, within such a limited spatial extent, we investigate the differences between the half-space approach and the Green function approach. It is shown that the half-space approach predicts larger displacements than the Green function approach and agrees better with the observed deformations at 11 considered GPS sites. Meanwhile, strong global environmental loading effects are found via two global hydrological models, i.e. GLDAS and MERRA. Thus, a reduction of these far-field loading effects beforehand is suggested before probing the local crustal structure using the half-space approach. Last but not least, based on the local load data, the effects of site-dependent Green functions are studied with two types of site-dependent Green functions, which were generated by modifying the local crustal structure of the REF Earth model using the CRUST 1.0 and CRUST 2.0 models. A relative RMS of differences of more than 5% in vertical component and 25% in horizontal components are found with respect to the PREM Earth model based Green functions. It indicates that the Green functions could contribute more uncertainties in loading induced displacements modeling than reported in the literature.Item Open Access Performance evaluation of different satellite radar altimetry missions for monitoring inland water bodies(2017) Roohi, Shirzad; Sneeuw, Nico (Prof. Dr.-Ing.)Inland water bodies, e.g. lakes and rivers, play vital roles in society and in nature. Moreover, these water bodies can be considered as integrators of environmental change to study climate effects and hydrological cycle at global and regional scales. Because changes in the water level of lakes and rivers indicate changes in climatic parameters, such as precipitation and evaporation, it is necessary to monitor water level variation of inland water bodies continuously to understand long term changes. Traditional methods, e.g. using in-situ gauges, provide precise water level determination. But they can not monitor these water bodies in a way that today’s human needs are to be satisfied, because in-situ gauge networks do not cover all inland water bodies and their data are not publicly available. Furthermore, they are expensive to install and to maintain, especially in remote areas. In-situ gauge networks follow national policy and there is not a unified data base of their measurements. Satellite altimetry as a space-borne technology helps us to partially solve the issue of water level monitoring. This technique was originally designed to observe ocean water surface. But due to advances in satellite radar systems and in data processing methodologies, the application of satellite altimetry has been extended to monitor small lakes and narrow rivers over the past 20 years. So far, studying water level variations of inland water bodies has been a challenge for satellite altimeters in terms of spatial and temporal resolution as well as accuracy of water level determination. Due to a relatively large radar footprint, the illuminated area inside the footprint can be inhomogeneous, i.e. consisting of water, land and vegetation. Therefore, responses to the radar pulses from such a surface are complex and lead to multi-peak waveforms (corrupted waveforms). Seriously corrupted waveforms need to be analyzed to extract optimal ranges. Retracking is an effective method to improve the accuracy of the range measurement from contaminated waveforms and, consequently, to determine a more accurate water level. The design of an optimal retracking algorithm appropriate for a specific inland water body is very important in this respect. The quality of retracked water level depends on the type of altimeters and on the algorithm that is used in the retracking process. Moreover, the shape and size of the inland water bodies can affect the quality of the water level determination. In this thesis, we analyzed the waveforms in two different ways: full-waveform and sub-waveform retracking. For this purpose, different physical and empirical retracking algorithms have been employed to retrack the waveforms. In full-waveform retracking, for a given waveform one retracked range correction is estimated. But in sub-waveform retracking more than one retracked range correction can be calculated. We analyze all sub-waveforms in a given waveform and select the optimal one to retrack and consequently to determine water level variations. Three different analyses have been performed to select the optimal sub-waveform. In the first analysis we retracked only the first sub-waveform for all of the waveforms. In the second analysis all detected sub-waveforms in a given waveform are retracked to calculate the mean retracked range correction. In the last analysis we retrack the sub-waveform that provides the water level with minimum RMS with respect to model fits. For a given satellite, first we determine the water level according to on-board retrackers. The results of the on-board retrackers have been validated against available in-situ gauge data to find the best on-board retracker. Then, the full and sub-waveforms have been processed by different retracking algorithms to define the retracked water level. The retracked water level derived from different retracking scenarios have been compared with in-situ gauge data to evaluate the accuracy of each scenario. Finally, the results of the best on-board retracker were compared with the results from post-processing the waveforms to find the most accurate water level estimator. Radar characteristics and geometry of the satellite orbit, that affect on the altimeter’s performance, are designed based on main objectives of a given mission. Monitoring inland water bodies have not been the main objectives for the altimetry missions till now. We therefore do our analysis over data from different altimeters and evaluate their performance in water level monitoring of different inland water bodies. To complete our analysis, a comparison between different satellite altimeters has been performed to assess the performance of each altimeter in continental water level determination. We selected challenging objects with different shapes and sizes in different continents. For a given object, two or three satellite altimetry data sets have been analyzed to study water level variations. We used different satellite altimetry missions in our study, divided into pulse-limited and beam-limited altimeters. For the pulse-limited altimeters we selected Envisat, Jason-2, SARAL and CryoSat-2 LRM and for the beam-limited ones we used CryoSat-2 SAR and SARI n modes and I CES at satellite altimeters. GDR and SGDR data of these altimeters have been analyzed over four lakes: Neagh (Northern Ireland), Nasser (Egypt), Urmia (Iran) and Qinghai (China). We also analyzed the same data type of Envisat, Jason-2 and SARAL missions over different sections of the Danube river. We have found that over inland water bodies it is necessary to retrack the waveforms to achieve a qualified water level determination. Comparing the results from the on-board retrackers with those of the post-processed waveforms indicates that there tracked water level is more accurate. Our numerical results of the waveform retracking show that the sub-waveform outperforms the full-waveform especially over small lakes and complex shape (even large) lakes as well as over narrow rivers, e.g. Danube river. Over lakes Neagh and Nasser the beam-limited altimeters show better performance than the pulse-limited altimeters. In the case of Urmia lake, we analyzed only pulse-limited altimeters. Envisat provides the water level more accurately than CryoSat-2 LRM . Over Qinghai lake, covered by beam- and pulse-limited altimeters, both Envisat and CryoSat-2 LRM have the same performance. They show better performance than I CES at. Over Danube river, Envisat and SARAL show the same performance which is better than that of Jason-2. If we compare the results of all retracking scenarios for all missions, we can conclude that the mean sub-waveform retracked with the threshold retracker is the best retracking scenario to monitor small and complex shape inland water bodies. The first sub-waveform retracked with this retracker is an alternative scenario for the inland water bodies.Item Open Access Data mining in GRACE monthly solutions(2019) Javaid, Muhammad Athar; Keller, Wolfgang (Prof. Dr. sc. techn.)Item Open Access Analyzing and characterizing spaceborne observation of water storage variation : past, present, future(2024) Saemian, Peyman; Sneeuw, Nico (Prof. Dr.-Ing.)Water storage is an indispensable constituent of the intricate water cycle, as it governs the availability and distribution of this precious resource. Any alteration in the water storage can trigger a cascade of consequences, affecting not only our agricultural practices but also the well-being of various ecosystems and the occurrence of natural hazards. Therefore, it is essential to monitor and manage the water storage levels prudently to ensure a sustainable future for our planet. Despite significant advancements in ground-based measurements and modeling techniques, accurately measuring water storage variation remained a major challenge for a long time. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and its successor GRACE Follow-On (GRACE-FO) satellites have revolutionized our understanding of the Earth's water cycle. By detecting variations in the Earth's gravity field caused by changes in water distribution, these satellites can precisely measure changes in total water storage (TWS) across the entire globe, providing a truly comprehensive view of the world's water resources. This information has proved invaluable for understanding how water resources are changing over time, and for developing strategies to manage these resources sustainably. However, GRACE and GRACE-FO are subject to various challenges that must be addressed in order to enhance the efficacy of our exploitation of GRACE observations for scientific and practical purposes. This thesis aims to address some of the challenges faced by GRACE and GRACE-FO. Since the inception of the GRACE mission, scholars have commonly extracted mass changes from observations by approximating the Earth's gravity field utilizing mathematical functions termed spherical harmonics. Various institutions have already processed GRACE(-FO) data, known as level-2 data in the GRACE community, considering the constraints, approaches, and models that have been utilized. However, this processed data necessitates post-processing to be used for several applications, such as hydrology and climate research. In this thesis, we evaluate various methods of processing GRACE(-FO) level-2 data and assess the spatio-temporal effect of the post-processing steps. Furthermore, we aim to compare the consistency between GRACE and its successor mission, GRACE-FO, in terms of data quality and measurement accuracy. By analyzing and comparing the data from these two missions, we can identify any potential discrepancies or differences and establish the level of confidence in the accuracy and reliability of the GRACE-FO measurements. Finally, we will compare the processed level-3 products with the level-3 products that are presently accessible online. The relatively short record of the GRACE measurements, compared to other satellite missions and observational records, can limit some studies that require long-term data. This short record makes it challenging to separate long-term signals from short-term variability and validate the data with ground-based measurements or other satellite missions. To address this limitation, this thesis expands the temporal coverage of GRACE(-FO) observations using global hydrological, atmospheric, and reanalysis models. First, we assess these models in estimating the TWS variation at a global scale. We compare the performance of various methods including data-driven and machine learning approaches in incorporating models and reconstruct GRACE TWS change. The results are also validated against Satellite Laser Ranging (SLR) observations over the pre-GRACE period. This thesis develops a hindcasted GRACE, which provides a better understanding of the changes in the Earth's water storage on a longer time scale. The GRACE satellite mission detects changes in the overall water storage in a specific region but cannot distinguish between the different compartments of TWS, such as surface water, groundwater, and soil moisture. Understanding these individual components is crucial for managing water resources and addressing the effects of droughts and floods. This study aims to integrate various data sources to improve our understanding of water storage variations at the continental to basin scale, including water fluxes, lake water level, and lake storage change data. Additionally, the study demonstrates the importance of combining GRACE(-FO) observations with other measurements, such as piezometric wells and rain-gauges, to understand the water scarcity predicament in Iran and other regions facing similar challenges. The GRACE satellite mission provides valuable insights into the Earth's system. However, the GRACE product has a level of uncertainty due to several error sources. While the mission has taken measures to minimize these uncertainties, researchers need to account for them when analyzing the data and communicate them when reporting findings. This thesis proposes a probabilistic approach to incorporate the Total Water Storage Anomaly (TWSA) data from GRACE(-FO). By accounting for the uncertainty in the TWSA data, this approach can provide a more comprehensive understanding of drought conditions, which is essential for decision makers managing water resources and responding to drought events.Item Open Access Assessment of ICESat-2 laser altimetry in hydrological applications(2024) Wang, Bo; Sneeuw, Nico (Prof. Dr.-Ing.)Water bodies act as critical components of the hydrological cycle, serving as reservoirs, lakes, wetlands, and aquifers that store and release water over time. Monitoring changes in the extent and volume of these water bodies is crucial for understanding their role in regulating water flow, maintaining baseflow during dry periods, and supporting ecological habitats. Furthermore, the identification of trends and alterations in water body dynamics aids in detecting potential impacts of climate change and human activities on the hydrological cycle. Historically, gauge stations have been employed to monitor the water level of these bodies since the 19th century. However, their numbers have been dwindling since the 1970s due to maintenance challenges. With the development of satellite altimetry missions, more accurate and continuous monitoring of lakes and rivers has become possible. These satellites in recent years offer the capability to provide water level data with different along-track sampling distances. For instance, ICESat-2 offers a sampling distance of 70 cm with a footprint size of ~17 m, while Sentinel-3 provides a sampling distance of 300 m. The temporal resolution ranges from 10 days (Jason-3) to 369 days (Cryosat-2). These advances allow researchers to effectively observe and understand changes in water bodies. The invention of satellite-based laser altimetry has brought a revolutionary advancement in our ability to monitor and study Earth’s water bodies with unprecedented precision and extensive spatial coverage. This doctoral thesis aims to explore the diverse applications of ICESat-2 laser altimetry data over inland water bodies. Through these investigations, the aim is to advance our understanding of global hydrological processes and acquire valuable insights to improve water resource management strategies. It is important to understand the error budget of the altimetric observations, one component of which is radial orbit error. Apart from the altimetric ranging errors, radial orbit errors directly influence the accuracy of the measurement of Earth’s surface heights. These errors can be assessed by analyzing the difference of surface heights at ground track intersections, so-called crossover differences (XO differences). An effective approach is to model the orbit error by minimizing the residual XO difference by the least-squares (LS) method, which is commonly known as XO adjustment. This method was implemented in the Arctic region to examine the performance of the LS adjustment over spherical cap geometry and assess the level of radial orbit error across a large-scale area. This analysis will aid in understanding the accuracy and reliability of ICESat-2 satellite orbit over the Arctic region. The ICESat-2 satellite captures high-resolution observations of Earth’s surface, including land and water, thus enabling dense measurements of heights. The green laser used in ICESat-2 has the capability to penetrate water surfaces, allowing measurements of not only the lake water level but also the nearshore water bottom. This study proposes a novel algorithm that combines ICESat-2 measurements with Landsat imagery to extract lake water level, extent and volume. This algorithm was applied to Lake Mead, resulting in a long-term time series of water level, extent and volume dating back to 1984, only derived from remote sensing data. The ICESat-2 satellite is equipped with three pairs of laser transmitters, which concurrently generate three pairs of ground tracks. This unique characteristic enables us to derive river surface heights for each ground track, thereby calculating the river slope between two tracks, referred to as the across-track river slope. Moreover, when one ground track passes through the river surface, producing dense measurements, it allows us to obtain the small-scale slope for that specific track, termed the along-track based river slope. By using these methods, both types of slopes were estimated for the entire length of the Rhine River and subsequently generated the average slope for each reach along the river.