Universität Stuttgart
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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 Using GRACE data to study the impact of snow and rainfall on terrestrial water storage in Northeast China(2020) Qian, An; Yi, Shuang; Chang, Le; Sun, Guangtong; Liu, XiaoyangWater resources are important for agricultural, industrial, and urban development. In this paper, we analyzed the influence of rainfall and snowfall on variations in terrestrial water storage (TWS) in Northeast China from Gravity Recovery and Climate Experiment (GRACE) gravity satellite data, GlobSnow snow water equivalent product, and ERA5-land monthly total precipitation, snowfall, and snow depth data. This study revealed the main composition and variation characteristics of TWS in Northeast China. We found that GRACE provided an effective method for monitoring large areas of stable seasonal snow cover and variations in TWS in Northeast China at both seasonal and interannual scales. On the seasonal scale, although summer rainfall was 10 times greater than winter snowfall, the terrestrial water storage in Northeast China peaked in winter, and summer rainfall brought about only a sub-peak, 1 month later than the maximum rainfall. On the interannual scale, TWS in Northeast China was controlled by rainfall. The correlation analysis results revealed that the annual fluctuations of TWS and rainfall in Northeast China appear to be influenced by ENSO (EI Niño-Southern Oscillation) events with a lag of 2-3 years. In addition, this study proposed a reconstruction model for the interannual variation in TWS in Northeast China from 2003 to 2016 on the basis of the contemporary terrestrial water storage and rainfall data.Item Open Access Exploring the performances of SAR altimetry and improvements offered by fully focused SAR(2021) Wu, YuweiWith the development of the altimetry techniques, the measurement principle has been changed from the conventional pulse-limited principle to the delay-Doppler principle since CryoSat-2. The delay-Doppler altimetry presents scientists with the chance to develop new processing schemes and improve products that maximize the benefits of the measurements. Nevertheless, one of the challenges for delay-Doppler Altimetry lies in the complexity of the post-processing, especially the Delay-Doppler processing. The focus of this thesis is to better understand delay-Doppler and fully focused SAR altimetry. This thesis compares the retrieved waveforms and resultant water level time series with different altimetry principles, processing options and retracking methods. By using platform SARvatore for delay-Doppler altimetry and SMAP for fully focused SAR altimetry, different processing options (data posting rate, Hamming window and zero padding) and different retrackers (SAMOSA family for SARvatore, PTR for SMAP) can be applied and compared. Our results reveal that the waveforms generated by different configurations have different peaks for SARvatore. For SMAP, with or without zero padding or Hamming window had very little impact, with more differences mainly coming from the different retracking methods. Our results also show that fully focused SAR does not bring a significant improvement when applied to Sentinel-3 data. In summary, different configurations and retracking methods can significantly affect the shape of waveforms and their derived ranges. According to this thesis's experiments, the configuration with 80 Hz data posting rate, Hamming window, zero padding, extended receiving window and retracker SAMOSA++ offers the best performance.Item Open Access Analyzing the spatio-temporal behavior of Poyang Lake using Google Earth Engine(2020) Schneider, Nicholas M.Poyang Lake, China’s largest freshwater lake, undergoes a yearly repeating cycle of drastic inundation and subsequent considerable shrinkage. Essentially, as a result of local precipitation and feedings from its tributaries, as well as a natural water exchange with the Yangtze River, Poyang Lake experiences such dimensional fluctuations on a annual and interannual scale. The ongoing change plays a significant role for the surrounding anthropogenic activity and wildlife. Despite being considered as a hydrological phenomenon, the dynamics of this Chinese water body set up a hurdle for any accurate documentation of its regime and therefore remains insufficiently studied upon to this day. Further impeding the comprehension of Poyang Lake’s behavior is the near inaccessibility and nonexistence of in situ data, such as water level measurements and bathymetric maps. Consequently, this study, driven by its aim to analyze the spatio-temporal behavior of Poyang Lake, focuses solely on satellite observations. Making use of the cloud computing platform, Google Earth Engine, image time series are used from Landsat-8 and Sentinel-1 datasets in order to map Poyang Lake’s spatio-temporal behavior on an annual and interannual scale. Produced from the Landsat-8 dataset, results show that only under circumstances, do techniques, such as the combination of visible and infrared bandsand the calculation of the Normalized Difference Water Index, provide a reasonable approach for the delineation of continental water bodies. For the study on Poyang Lake, a water body subject to humid climate and thus frequent cloud coverage, these techniques do not apply very well. With synthetic aperture radar observations from the Sentinel-1 dataset, dynamic water masks, involving the removal of certain elevated areas and the classification of water from thresholding, could be generated. The resulting binary water masks are then merged with a digital terrain model to create monthly maps of the study area. The results show an evident correlation between this study’s visual and numeric findings. Although the results are nearly impossible to compare with any in situ data, they show a trend that annually occurs in Poyang Lake’s hydrological regime. In particular, they reveal the cycle of drastic inundation in rainy summer months and considerable shrinkage in dry winter months, especially when examining the years prior to 2019. Using SAR imagery for continental water body delineation, particularly in humid climates, proved to be a suitable technique and should be considered for future documentations of the lake.Item Open Access Characterizing storage-based drought using satellite gravimetry(2021) Saemian, PeymanDrought is a complex phenomenon leading to a wide range of socio-economic, environmental, and political problems. The storage-based drought which represents the persistent lack of water in different levels of the Total Water Storage (TWS) from deep groundwater to surface water plays a vital role in proactive drought management. Despite its necessity, TWS could not be monitored due to the lack of consistent measurements from regional to continental scale. Since its launch in 2002, the Gravity Recovery and Climate Experiment (grace) mission and its successor GRACE Follow-On have provided unique observations of the TWS change at the global scale. In this study, we have investigated characterizing the storage-based drought at the global scale using GRACE measurements. To this end, the Equivalent Water Height (EWH) has been retrieved from GRACE level 02 solutions. We have addressed the short record of GRACE observations in capturing the full hydroclimate variations. Based on our analysis, regions with a considerable direct human intervention like overexploitation of groundwater in the Middle East, regions that were affected by climate change like ice-melting over the Mackenzie river basin in Canada, or extreme precipitation events over the Ob river basin in the boreal regions are more sensitive to the length of ewh time series. Due to the crucial need for a long (at least 30 years) record of EWH, we have extended GRACE observations back to 1980 using an ensemble of models. The extended dataset has been developed using a pixel-wise selection of best-performed models among global hydrological models, land surface models, and atmospheric reanalysis models. The extended dataset has been used in the study for drought characterization over the grac period. The proposed Storage-based Drought Index (SDI) successfully captured the documented drought events globally in terms of intensity and spatio-temporal distribution. Moreover, the analysis of SDI over the five classes of drought from D0 as abnormally dry to D4 as exceptional drought showed that most regions have suffered at least once from the storage-based drought over the GRACE period (2002–2016). Besides, the map of exceptional drought frequency highlights regions with significant groundwater extraction like California, the Middle East, and north of India and regions with exceptional shifts in the precipitation and temperature pattern and intensity like Amazon in South America and China. Finally, our comparison of SDI with three most widely used drought indices namely the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), and the Palmer Drought Severity Index (PDSI) reveals that despite their high correlation over climate-driven regions, these indices failed to characterize anthropogenic drought events, especially over regions with considerable groundwater withdraws. The study allows for a more informative storage-based drought with a more robust climatology as the reference, thus enabling a more realistic risk assessment.Item Open Access Analysis of water volume change of the lakes and reservoirs in the Mississippi River basin using Landsat imagery and satellite altimetry(2021) Wang, LingkeIn recent years, the demand for freshwater has been steadily increasing owing to population growth and economic expansion. Surface waters such as lakes and reservoirs function as a dominant factor in mankind's freshwater provision. Analysis of changes in their water storage is consequently vital for understanding of the global water cycle and water resources. However, the water volume changes in lakes or reservoirs cannot be measured directly from space, but can be inferred from lake areas and lake water levels. Lake area can be measured globally from space but lake water level is not easy to be obtained globally. Because the number of in situ stations is few, and in situ data are only accessible for some lakes with few measurement epochs, despite in situ stations can measure lake water level and provide high accuracy observations. Although the altimetry technique can generate the time series of the water level for the majority of lakes, they are not global coverage due to the distance between satellite tracks and the gap between different missions. Therefore, in situ data and satellite altimetry measurements of water levels of lakes and reservoirs are not always available. For example, there are only 22 lakes or reservoirs in this study covered by satellite altimetry or in situ stations out of 90 research cases in Mississippi River Basin. Then, in case of unavailable in situ data or altimetry measurements, this research proposes an alternative method to estimate the water level through Digital Elevation Model (DEM). Because satellite imagery offers global coverage and DEM is the global digital representation of the land surface elevation with respect to any reference datum, this study allows for the evaluation of global water volume changes by acquiring lake area data from space and lake height data from DEM. Therefore, the objective of this study is that changes in water volume in lakes or reservoirs can be successfully monitored even when in situ data and satellite altimetry measurements are not available for lakes or reservoirs. Hereby, we investigate 90 lakes and reservoirs in the Mississippi River Basin and develop an alternative remote sensing technique to monitor the water volume changes by combining the improved water mask with DEM. Meanwhile, we propose practical methods to detect the shoreline pixels of the water body from improved water mask. Given the assumption that all pixels in the shoreline should have the same height, four water level estimation models are developed, including water level estimation model based on statistical analysis, frequency maps, change pixels and pixel pair analysis. To this end, the study estimates the time series of lake height from water level estimation model and obtains the time series of lake surface area from HydroSat. Subsequently, this study builds the unique function between the lake water level and the lake surface area and then develops the function between the lake water volume change and the lake surface area. Finally, this study analyses the water volume changes of lakes and reservoirs in the Mississippi River Basin using this alternative remote sensing method. Four water level estimation models are proposed and evaluated. They are respectively based on statistical analysis, frequency maps, change pixels and pixel pair analysis. As a result of their actions, the first model based on statistical analysis, with an average correlation of 0.62 and an average RMSE of 0.91 meters, functions in the majority of situations and demonstrates excessive outlier removal in some cases. The second model based on frequency maps is more general than the first, with an average correlation of 0.66 and an average RMSE of 1.11 meters. The average correlation for the third model based on change pixels is 0.71, and the average RMSE is 0.99 meters. The resulting model based on pixel pair analysis obtains a mean correlation of 0.67 and a mean RMSE of 1.00 meters. Finally, these models behave differently in different seasons, so they exhibit distinct monthly behaviour. To conclude, the above validation results show that this alternative method can be used in different lakes and reservoirs in case of absence of water level observation data, and achieve to monitor the water volume changes during a long period.Item Open Access Estimation of significant wave height using Sentinel-3 data(2020) Gou, JunyangCoastal area is one of the most important area for us. More than 600 million people (around 10% of the word’s population) live in coastal areas that are less than 10m above sea level. Nearly 2.4 billion people (about 40% of the world’s population) live within 100km of the coast. Therefore, monitoring of coastal waters is extremely important. Due to the limitation of the number and location, the tide gauge stations around the world cannot provide a sufficient amount of in-situ data. Therefore, satellite altimetry plays an increasingly important role, especially when the SAR altimeter is put into use. However, due to the complexity of the coastal water surfaces, the performance of the satellite altimeter over the coastal area is far worse than over ocean. This thesis is dedicated to developing a method to determine one of the essential characters of the water surfaces - the significant wave height (SWH), using the Sentinel-3 data in the coastal area. The three primary steps of the method are extracting the thermal noise and the leading edge, fitting this part of waveform and determining the relationship between the new retracker and the physical model. In the first step, an algorithm is developed to avoid the interferences of the noise on the trailing edge. Therefore, the peak of the leading edge could be determined more accurately. The condition for the start point of the leading edge of the PLRM waveforms is Dwf > 0.01, inherited from ALES, whereas a more appropriate threshold for the SAR waveforms has been found as Dwf > 0.03. In the second step, the limitation of the Gauss-Markov model for the waveform adjustment has been discussed. Thus, the Levenberg-Marquardt method has been chosen to adjust the waveform. In the third step, the relationship between the raising time and the beta4 has been found. Then, we could estimate the SWH directly from the raising time which makes it possible to estimate the SWH from some complicated waveforms in coastal areas. We have employed the developed methodology to determine the significant wave height in the coastal area near the Cuxhaven. The quality of the results has been proved by comparing with the in-situ data from the Elbe measuring station provided by the Federal Maritime and Hydrographic Agency of Germany. The validation showed that the proposed method can determine reliable SWH from approximately 1km offshore, which is an improvement of earlier results.Item Open Access Analysis of river surface slope using ICESat-2 satellite altimetry(2022) Bao, JingyiItem Open Access