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 Data mining in GRACE monthly solutions(2019) Javaid, Muhammad Athar; Keller, Wolfgang (Prof. Dr. sc. techn.)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 Evaluating impacts of irrigation and drought on river, groundwater and a terminal wetland in the Zayanderud Basin, Iran(2020) Abou Zaki, Nizar; Torabi Haghighi, Ali; Rossi, Pekka M.; Tourian, Mohammad J.; Bakhshaee, Alireza; Kløve, BjørnThe Zayanderud Basin is an important agricultural area in central Iran. In the Basin, irrigation consumes more than 90 percent of the water used, which threatens both the downstream historical city of Isfahan and the Gavkhuni Wetland reserve-the final recipient of the river water. To analyze impacts of land use changes and the occurrence of metrological and hydrological drought, we used groundwater data from 30 wells, the standardized precipitation index (SPI) and the streamflow drought index (SDI). Changes in the wetland were analyzed using normalized difference water index (NDWI) values and water mass depletion in the Basin was also assessed with gravity recovery and climate experiment (GRACE)-derived data. The results show that in 45 out of studied 50 years, the climate can be considered as normal in respect to mean precipitation amount, but hydrological droughts exist in more than half of the recorded years. The hydrological drought occurrence increased after the 1970s when large irrigation schemes were introduced. In recent decades, the flow rate reached zero in the downstream part of the Zayanderud River. NDWI values confirmed the severe drying of the Gavkhuni Wetland on several occasions, when compared to in situ data. The water mass depletion rate in the Basin is estimated to be 30 (±5) mm annually; groundwater exploitation has reached an average of 365 Mm3 annually, with a constant annual drop of 1 to 2.5 meters in the groundwater level annually. The results demonstrate the connection between groundwater and surface water resources management and highlight that groundwater depletion and the repeated occurrence of the Zayanderud River hydrological drought are directly related to human activities. The results can be used to assess sustainability of water management in the Basin.Item Open Access A novel spatial filter to reduce north-south striping noise in GRACE spherical harmonic coefficients(2022) Yi, Shuang; Sneeuw, NicoPrevalent north-south striping (NSS) noise in the spherical harmonic coefficient products of the satellite missions gravity recovery and climate experiment greatly impedes the interpretation of signals. The overwhelming NSS noise always leads to excessive smoothing of the data, allowing a large room for improvement in the spatial resolution if this particular NSS noise can be mitigated beforehand. Here, we put forward a new spatial filter that can effectively remove NSS noise while remaining orthogonal to physical signals. This new approach overcomes the limitations of the previous method proposed by Swenson and Wahr (2006), where signal distortion was large and high-order coefficients were uncorrectable. The filter is based on autocorrelation in the longitude direction and cross-correlation in the latitude direction. The NSS-type noise identified by our method is mainly located in coefficients of spherical harmonic order larger than about 20 and degree beyond 30, spatially between latitudes ± 60°. After removing the dominating NSS noise with our method, a weaker filter than before is added to handle the residual noise. Thereby, the spatial resolution can be increased and the amplitude damping can be reduced. Our method can coincidentally reduce outliers in time series without significant trend bias, which underpins its effectiveness and reliability.Item Open Access Application of spaceborne geodetic sensors for hydrology(2013) Tourian, Mohammad Javad; Sneeuw, Nico (Prof. Dr.-Ing.)How much freshwater do we have on land? How is the freshwater cycle changing with time? Actually, we can not properly answer these questions as our knowledge of the spatial and temporal dynamics of the hydrological cycle is limited. The lack of knowledge is mainly induced by shortage of observational evidence, which motivates the objective of this study: the monitoring of the hydrological cycle using spaceborne geodetic sensors. Among the current space geodetic sensors, GRACE and satellite altimetry are the two active mission concepts, that can capture part of the hydrological cycle. However, monitoring the hydrological cycle using these two sensors is challenging. Satellite altimetry is investigated as an independent spaceborne sensor that provides the water level and discharge time series. An algorithm is developed to improve the quality of water level time series over inland water surfaces. This algorithm particularly deals with the challenges of resolution and uncertainty of altimetry. The obtained altimetric water level time series is validated against in situ measurements showing about 10% improvement in accuracy of the time series. Moreover, this study proposes an algorithm to reduce the random noise from pre-retracked data. The algorithm combines the results of different retrackers and provides water level time series with reduced noise level. The validation shows a significant reduction of noise level and a clear improvement in correlation with in situ measurements. Moreover, this study proposes a statistical approach based on quantile functions to infer a functional relationship between altimetric water level and in situ river discharge without the need for synchronous data sets. This method is based on a scatter diagram of quantile functions, in which the probability-coordinate is eliminated. In contrast, the conventional methods for simultaneous measurements operate directly on time series and eliminate the time-coordinate. The results show that the proposed methodology provides the same range of error as the common conventional empirical method. The good performance of the statistical approach supports the usage of altimetry to salvage pre-satellite altimetry discharge data and turn them into active use for the satellite altimetry time frame. In addition, a stochastic process model is implemented to (i) deal with the data outages in altimetric discharge, (ii) provide a scheme for data assimilation and (iii) smooth the discharge estimation. The model benefits from the cyclostationary behaviour of the discharge and is combined with the estimated discharge from altimetry and available in situ measurements to form a linear dynamic system. The dynamic system is solved using the Kalman filter, that provides an unbiased discharge with minimum variance. The error level of the results is comparable to the empirical approach. In this study, the utility of GRACE data as sensor of hydrological water storage changes is shown to be limited by the following challenges: consistency, resolution, separability and uncertainty. The challenge of inconsistency is addressed by developing two filters for hydrological and hydro-meteorological water storage changes, which lead to a better correlation with GRACE mass storage changes. The challenges of separability and resolution are not specifically investigated in this study, yet their consequences, which appear in different forms of uncertainties is investigated. To deal with the GRACE uncertainties, an algorithm is developed to detect outliers in monthly solutions. The outliers have been corrected by replacing them by an inter-annual monthly mean of the respective month. The results conclude that outlier identification and correction must be performed before further assimilation of GRACE products into hydrological or hydro-meteorological analysis. Further, a longrange correlation has been identified as another source of uncertainty in GRACE monthly solutions. EOF analysis is employed to identify the zonal behaviour of the GRACE C20 errors as the responsible source for the long-range correlation. It is considered as an error source because its residual contains tidal aliasing errors instead of white noise. Therefore, to reduce the uncertainties in GRACE monthly solutions, tidal aliasing errors are also investigated. Primary and secondary tidal aliasing errors of main tidal constituents, S1, S2, P1, K1, K2, M2, O2, O1 and Q1 are identified in GRACE monthly solutions. The effect of tidal aliasing error is estimated using a least squares Fourier analysis indicating errors up to 22mm over the globe. In general, after dealing with GRACE’s challenges and achieving a data set without outliers, long-range correlation and tidal aliasing errors, the noise level of GRACE is quantified. The quantification shows a variation between 2–20mm/month over different parts of the globe, with higher values over tropical and boreal regions. The results specifically confirm that small catchments in the tropics contain more noise contamination. It is also shown that a lower noise level of a catchment does not necessarily lead to a better correlation of GRACE with hydro-meteorological signal. Finally, the joint performance of spaceborne geodetic sensors for estimating the actual evapotranspiration ETa is assessed. There, two approaches are introduced to estimate ETa using the results of GRACE and satellite altimetry. The results of both approaches are compared with different models and their ensemble mean. All in all, given the obtained relative discrepancy, the methods seem to be a viable way for determining ETa for most non-desert catchments containing hot and warm summers.Item Open Access A probabilistic approach to characterizing drought using satellite gravimetry(2024) Saemian, Peyman; Tourian, Mohammad J.; Elmi, Omid; Sneeuw, Nico; AghaKouchak, AmirIn the recent past, the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its successor GRACE Follow‐On (GRACE‐FO), have become invaluable tools for characterizing drought through measurements of Total Water Storage Anomaly (TWSA). However, the existing approaches have often overlooked the uncertainties in TWSA that stem from GRACE orbit configuration, background models, and intrinsic data errors. Here we introduce a fresh view on this problem which incorporates the uncertainties in the data: the Probabilistic Storage‐based Drought Index (PSDI). Our method leverages Monte Carlo simulations to yield realistic realizations for the stochastic process of the TWSA time series. These realizations depict a range of plausible drought scenarios that later on are used to characterize drought. This approach provides probability for each drought category instead of selecting a single final category at each epoch. We have compared PSDI with the deterministic approach (Storage‐based Drought Index, SDI) over major global basins. Our results show that the deterministic approach often leans toward an overestimation of storage‐based drought severity. Furthermore, we scrutinize the performance of PSDI across diverse hydrologic events, spanning continents from the United States to Europe, the Middle East, Southern Africa, South America, and Australia. In each case, PSDI emerges as a reliable indicator for characterizing drought conditions, providing a more comprehensive perspective than conventional deterministic indices. In contrast to the common deterministic view, our probabilistic approach provides a more realistic characterization of the TWS drought, making it more suited for adaptive strategies and realistic risk management.Item Open Access Surface water extent monitoring using the Global WaterPack product: automated extraction, refinement, and analysis(2025) Jalali Jirandehi, MasoudMonitoring and analyzing surface water dynamics is critical for understanding hydrological variations, climate change impacts, and water resource management. Traditional methods of surface water storage monitoring rely on in-situ measurements, which are often spatially and temporally limited. Remote sensing has revolutionized this field by enabling large-scale, consistent, and continuous observations of area and height water storages. This study presents a methodology for generating accurate water area time series using the Global WaterPack (GWP), a monthly satellite-derived dataset. Developed by the German Aerospace Center (DLR), the GWP dataset is specifically designed for monitoring surface water dynamics on a global scale. A Python-based processing tool is developed to systematically extract and analyze lake and river water extents, mitigating key challenges such as cloud contamination, defining proper threshold, and classification inaccuracies. By integrating high-frequency surface water observations from GWP with the Prior Lake Database PLD (a static dataset for extracting the initial search area), and the SWOT (The Surface Water and Ocean Topography) prior River Database (SWORD), which provides a standardized framework of high-resolution river nodes and reaches, this tool enhances the reliability of time-series analysis. This framework improves surface water change detection, reduces computational complexity, and refines water occurrence assessments under diverse hydroclimatic conditions. The workflow automates the entire process, allowing users to select lakes interactively via a geospatial interface or upload coordinate lists for batch processing. Key steps include (1) downloading images, (2) defining the search area, (3) normalization, (4) generating a water occurrence map, (5) defining constant water and land masks, (6) residual analysis, (7) deriving and applying thresholds, (8) generating time series plots, and (9) correlation analysis. Advanced filtering methods, such as threshold-based classification and residual analysis, refine water occurrence measurements, while an adaptive thresholding approach using the Cumulative Distribution Function (CDF) enhances water body delineation accuracy. To evaluate the reliability of the extracted data, the resulting surface area time series are compared against altimetry-derived water height records using correlation analysis. The analysis revealed clear seasonal and interannual variations in lake water areas, aligning well with natural hydrological patterns. Many lakes showed strong positive correlations between satellite-derived surface area and altimetry-based water levels, validating the method’s effectiveness. However, weaker correlations in some cases were attributed to issues like cloud cover, sensor limitations, and complex hydrodynamics. The study emphasized that a fixed threshold is insufficient for all systems, whereas the corrected method provided more reliable results across diverse conditions. Although river analysis showed varied hydraulic responses, the tool proved useful for monitoring floods, seasonal changes, and long-term water trends, especially with proper calibration. By providing an automated, scalable, and accurate tool for water body monitoring, this thesis contributes to advancing hydrological analysis using remote sensing and geospatial processing techniques. The developed tool can aid in climate studies, water resource management, and flood risk assessment, offering a valuable framework for long-term surface water monitoring.Item Open Access Evaluation of gravitational curvatures for a tesseroid and spherical shell with arbitrary-order polynomial density(2023) Deng, Xiao-LeIn recent years, there are research trends from constant to variable density and low-order to high-order gravitational potential gradients in gravity field modeling. Under the research circumstances, this paper focuses on the variable density model for gravitational curvatures (or gravity curvatures, third-order derivatives of gravitational potential) of a tesseroid and spherical shell in the spatial domain of gravity field modeling. In this contribution, the general formula of the gravitational curvatures of a tesseroid with arbitrary-order polynomial density is derived. The general expressions for gravitational effects up to the gravitational curvatures of a spherical shell with arbitrary-order polynomial density are derived when the computation point is located above, inside, and below the spherical shell. When the computation point is located above the spherical shell, the general expressions for the mass of a spherical shell and the relation between the radial gravitational effects up to arbitrary-order and the mass of a spherical shell with arbitrary-order polynomial density are derived. The influence of the computation point’s height and latitude on gravitational curvatures with the polynomial density up to fourth-order is numerically investigated using tesseroids to discretize a spherical shell. Numerical results reveal that the near-zone problem exists for the fourth-order polynomial density of the gravitational curvatures, i.e., relative errors in log10scale of gravitational curvatures are large than 0 below the height of about 50 km by a grid size of 15′×15′. The polar-singularity problem does not occur for the gravitational curvatures with polynomial density up to fourth-order because of the Cartesian integral kernels of the tesseroid. The density variation can be revealed in the absolute errors as the superposition effects of Laplace parameters of gravitational curvatures other than the relative errors. The derived expressions are examples of the high-order gravitational potential gradients of the mass body with variable density in the spatial domain, which will provide the theoretical basis for future applications of gravity field modeling in geodesy and geophysics.