06 Fakultät Luft- und Raumfahrttechnik und Geodäsie
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/7
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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 Water level monitoring at SAPOS stations through GNSS-IR : a case study at the station Iffezheim(2023) Wagner, Sven B.The German SAPOS-Network comprises approximately 270 permanent GNSS receivers, capturing signals from Global Navigation Satellite Systems such as GPS, GLONASS, Galileo, and BeiDou. Primarily employed for generating kinematic, mathematical, and physical models within their respective regions, these receivers hold untapped potential for alternative applications. GNSS receivers capture multipath errors, typically considered unwanted interferences resulting from signal reflections off surfaces beneath the antenna. Despite their potential to adversely affect data precision, these interferences contain valuable information about the reflecting surface. As satellites pass through the receivers’ field of view at specific elevation angles, the interference between the direct and reflected signals leads to constructive and destructive patterns. This phenomenon occurs due to variations in signal phase between the direct and reflected signal, enhancing or dampening the signal strength. These variations in signal strength are captured in the satellites Signal-to-Noise Ratio (SNR) data. Spectral analysis of the SNR data can be used to determine the frequency of the interference pattern. Combining this frequency with the corresponding signal wavelength and satellite elevation angles allows the calculation of the vertical distance between the antenna phase centre and the reflecting surface on Earth. This method, known as GNSS Interferometric Reflectometry (GNSS-IR), provides a valuable means of monitoring surface information, including soil moisture, snow depth, and water levels. At SAPOS stations near rivers and water bodies, GNSS-IR offers a cost-effective, accessible, and innovative opportunity to gather water level information using the already existing infrastructure. This research explores the potential of GNSSIR for water level monitoring at SAPOS stations focusing on the Iffezheim station along the Rhine River near the City of Karlsruhe in southern Germany.Item Open Access Analysis of river surface slope using ICESat-2 satellite altimetry(2022) Bao, JingyiItem Open Access Spatio-temporal evaluation of GPM-IMERGV6.0 final run precipitation product in capturing extreme precipitation events across Iran(2022) Bakhtar, Aydin; Rahmati, Akbar; Shayeghi, Afshin; Teymoori, Javad; Ghajarnia, Navid; Saemian, PeymanExtreme precipitation events such as floods and droughts have occurred with higher frequency over the recent decades as a result of the climate change and anthropogenic activities. To understand and mitigate such events, it is crucial to investigate their spatio-temporal variations globally or regionally. Global precipitation products provide an alternative way to the in situ observations over such a region. In this study, we have evaluated the performance of the latest version of the Global Precipitation Measurement-Integrated Multi-satellitE Retrievals (GPM-IMERGV6.0 Final Run (GPM-IMERGF)). To this end, we have employed ten most common extreme precipitation indices, including maximum indices (Rx1day, Rx5day, CDD, and CWD), percentile indices (R95pTOT and R99pTOT), and absolute threshold indices (R10mm, R20mm, SDII, and PRCPTOT). Overall, the spatial distribution results for error metrics showed that the highest and lowest accuracy for GPM-IMERGF were reported for the absolute threshold indices and percentile indices, respectively. Considering the spatial distribution of the results, the highest accuracy of GPM-IMERGF in capturing extreme precipitations was observed over the western highlands, while the worst results were obtained along the Caspian Sea regions. Our analysis can significantly contribute to various hydro-metrological applications for the study region, including identifying drought and flood-prone areas and water resources planning.Item Open Access Item Open Access Crop water productivity mapping and benchmarking using remote sensing and Google Earth Engine cloud computing(2022) Ghorbanpour, Ali Karbalaye; Kisekka, Isaya; Afshar, Abbas; Hessels, Tim; Taraghi, Mahdi; Hessari, Behzad; Tourian, Mohammad J.; Duan, ZhengScarce water resources present a major hindrance to ensuring food security. Crop water productivity (WP), embraced as one of the Sustainable Development Goals (SDGs), is playing an integral role in the performance-based evaluation of agricultural systems and securing sustainable food production. This study aims at developing a cloud-based model within the Google Earth Engine (GEE) based on Landsat -7 and -8 satellite imagery to facilitate WP mapping at regional scales (30-m resolution) and analyzing the state of the water use efficiency and productivity of the agricultural sector as a means of benchmarking its WP and defining local gaps and targets at spatiotemporal scales. The model was tested in three major agricultural districts in the Lake Urmia Basin (LUB) with respect to five crop types, including irrigated wheat, rainfed wheat, apples, grapes, alfalfa, and sugar beets as the major grown crops. The actual evapotranspiration (ET) was estimated using geeSEBAL based on the Surface Energy Balance Algorithm for Land (SEBAL) methodology, while for crop yield estimations Monteith’s Light Use Efficiency model (LUE) was employed. The results indicate that the WP in the LUB is below its optimum targets, revealing that there is a significant degree of work necessary to ameliorate the WP in the LUB. The WP varies between 0.49-0.55 (kg/m3) for irrigated wheat, 0.27-0.34 for rainfed wheat, 1.7-2.2 for apples, 1.2-1.7 for grapes, 5.5-6.2 for sugar beets, and 0.67-1.08 for alfalfa, which could be potentially increased up to 80%, 150%, 76%, 83%, 55%, and 48%, respectively. The spatial variation of the WP and crop yield makes it feasible to detect the areas with the best and poorest on-farm practices, thereby facilitating the better targeting of resources to bridge the WP gap through water management practices. This study provides important insights into the status and potential of WP with possible worldwide applications at both farm and government levels for policymakers, practitioners, and growers to adopt effective policy guidelines and improve on-farm practices.Item Open Access Understanding the hydrological signature in gravity data(2023) Schollmeier, PhilippOver the past two decades, the subsequent advancements in Superconducting Gravimeters (SGs) have ushered in a level of precision that enables the measurement of the impact of ground water and soil water on gravity. Because of the challenging nature of monitoring the total water volume and the relatively subtle amplitude of the hydrological signal, a comprehensive understanding of the precise hydrological signature in continuous gravity data remains elusive. In this study, I use SG data in conjunction with hydrological measurements from a geoscientific observatory in Germany to find the signature of hydrological signals in gravity data. I scrutinize the various steps involved in extracting this signal, presenting new methodologies, including a technique to eliminate oscillations in gravity residuals that are likely attributed to remaining tidal signals due to an imperfect tidal model. A major contribution of this work involves constructing a data-driven model that incorporates precipitation and soil moisture measurements to elucidate gravity variations. I address critical questions such as the impact of utilizing soil moisture data on the model’s performance, determining the optimal model for achieving the closest fit with gravity measurements, and assessing the applicability of computed model parameters to new epochs. Furthermore, I provide recommendations for refining the model-building process in future investigations. Results show that a convolution of the different hydrological timeseries with one half of a Gaussian bell curve leads to a strong agreement with the gravity measurements. The use of soil moisture data significantly improves the fit, especially when the measurement stations are spatially well distributed. This fit becomes less strong when the computed parameters are applied to new events, but the approach showed promise for some of the events. Enhancing our comprehension of the hydrological influence on gravity measurements holds promising implications, potentially positioning SGs as instruments for monitoring soil and ground water in the future. Moreover, this improved understanding could elevate the pre cision of analyzing other subtle signals, such as the effects of Polar Motion.Item Open Access Understanding the limitations of Sentinel-3 inland altimetry through validation over the Rhine River(2022) Schneider, Nicholas M.Satellite altimetry is developing into one of the most powerful measurement techniques for long-term water body monitoring thanks to its high spatial resolution and its increasing level of precision. Although the principle of satellite altimetry is very straightforward, the retrieval of correct water levels remains rather difficult due to various factors. Waveform retracking is an approach to optimize the initially determined range between the satellite and the water body on Earth by exploiting the information within the power-signal of the returned radar pulse to the altimeter. Several so-called retrackers have been designed to this end, yet remain one of the most open study areas in satellite altimetry due to their crucial role they play in water level retrieval. Moreover, geophysical properties of the stratified atmosphere and the target on Earth have an effect on the travel time of the transmitted radar pulse and can amount to severalmeters in range. In this study we provide an overall analysis of the performances of the retrackers dedicated to the Sentinel-3 mission and the applied geophysical corrections. For this matter, we focus on nine different locations within the Rhine River basin where locally gauged data is available to validate the Sentinel-3 level-2 products. Furthermore, we present a reverse retracking approach in the sense that we use the given in-situ data to determine the offset to each altimetry-derived measurement of every epoch. Under the assumption that these offsets are legitimate, they can be seen as an a-posteriori correction which we project onto the range and thus on a waveform level. Further analyses consist in the investigation of the relationship these a-posteriori corrections have to the waveform properties of the same epoch. Later, the question whether the a-posteriori corrections to the initial retracking gates are appropriate for the retrieval of correct water levels, drives us to assign a probability to each and every bin of the waveform. Following this idea, we design stochastic-based retrackers which determine the retracking gate for water level retrieval from the bin with the highest probability assigned to it. To distribute the probabilities across all bins of the waveform, we consider three empirical approaches that take both the waveform itself and its first derivative into account: Addition, multiplication and maximum of both signals. For all three of the new retrackers, we generate the water level timeseries over the aforementioned sites and validate them against in-situ data and the retrackers dedicated to the Sentinel-3 mission.Item Open Access Dealing with challenges of altimetry-based surface water height derivation over boreal catchments : case study of Mackenzie river(2022) Liu, JiaxinThe Earth is a watery place, which fills the oceans, rivers, and lakes. Approximately 71% of the Earth’s surface is water-covered. Measurements of surface water level in oceans, lakes, rivers and coastal waters are important for a variety of reasons. In the short term, this can, for example, help to alert to dangerous water level so that actions can be taken in advance, while in the long term, monitoring water levels can provide even greater insight into patterns of water dispersal in the area, and measure, for example, the effects of global warming. Satellite altimetry, which was originally designed for oceanography in the 1970s, has revolutionized our knowledge of the marine gravity field, of the dynamics of the oceans and even ofland hydrology. It is a space measurement technique that uses artificial satellites to measure the altitude from the satellite to the Earth’s surface. Due to its high resolution, global coverage and short revisit time, it is playing an increasingly important role in measurements of water level. For some years, this technology has also been used to retrieve water levels from rivers, lakes, and any inland water body as well. However, compared with the wide seas, measurements of inland water bodies involve many challenges. In this paper, we will take the Mackenzie River in northern Canada as a research object and process the data through the Matlab-based program Atlbundle+ to study the potential of inland altimetry, the problems it faces and the possible ways to find the solution. In general, there are two perspectives that will be considered: Firstly, how we can accurately remove outliers in the measurements, and secondly, how to improve the altimetry-driven water level time series by improving the retracking methods. Finally, based on the results and the procedure, a systematic analysis of the inland altimetry can be carried out.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.
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