Controls on satellite altimetry over inland water surfaces for hydrological purposes

The global available and freely accessible in situ measurements of hydrological cycles is unsatisfactory, limited and has been on the decline, lately. This together with large modeling error for hydrological cycles, support the efforts to seek for alternative measuring techniques. In the recent past, satellite altimetry has been used to measure non-ocean water level variations for hydrological purposes. Due to the effect of topography and heterogeneity of reflecting surface and atmospheric propagation, the expected echo shape for altimeter returns over land differs from that over ocean surfaces. As a result, altimetry measurements over inland waters are erroneous and include missing data. In the present study, we have developed an algorithm to improve the quality of water level time series over non-ocean surfaces. This algorithm contains an outlier identification and elimination process, an algorithm for excluding the noisy waveforms, an unsupervised classification of the satellite waveforms and finally a retracking procedure. The two preliminary steps of outlier identification and noisy waveforms exclusion allow to achieve better results for further classification and retracking steps. We have employed data snooping algorithm to identify and eliminate outliers in the water level time series. Further, an algorithm based on comparing each waveform with fitted waveform from 5β algorithm is developed to identify the noisy waveforms. An unsupervised classification algorithm is implemented to classify the waveforms into consistent groups, for which the appropriate retracking algorithms are performed. The classification algorithm is based on computing the heterogeneity of data sets, which is computed through the difference between median and modal waveforms. We have employed the algorithm to improve the water level time series in Balaton (Hungary) and Urmia (Iran) lakes. After then, we validated the results of proposed algorithm against the available in situ measurements.In letzter Zeit ist die global verfügbare und frei zugängliche in situ-Messungen von hydrologischen Zyklen unbefriedigend, beschränkt und rückgängig geworden. Dies zusammen mit großen Modellierungsfehler der hydrologischen Zyklen unterstützen die Suche nach alternativen Messverfahren. In der jüngsten Vergangenheit hat die Satellitenaltimetrie verwendet worden, um die Variationen des kontinentalen Wasserstands für hydrologische Zwecke zu messen. Aufgrund der Wirkung der Topographie und der Heterogenität der reflektierenden Oberfläche und atmosphärische Ausbreitung unterscheidet sich die erwartete Echoform des Höhenmessers über das Land vom Echoform über die Ozeanoberflächen. In der vorliegenden Arbeit haben wir einen Algorithmus entwickelt, um die Qualität der Wasserstandszeitreihen über die kontinentale Oberflächen zu verbessern. Dieser Algorithmus enthält: • eine Ausreißer-Identifikation und einen Beseitigungsprozess • einen Algorithmus zum Ausschluss der gestörten Echoform • eine unüberwachten Klassifizierung der Echoform • ein „retracking“ Verfahren Die vorbereitende Schritte zur Ermittlung von Ausreißern und verrauschten Echoformen ermöglichen bessere Ergebnisse zur weiteren Klassifizierung und retracking Schritte. Wir haben Daten-Snooping-Algorithmus zur Identifizierung und Beseitigung von Ausreißern in der Wasserstand Zeitreihen verwendet. Um die verrauschten Echoformen zu identifizieren ist ein Algorithmus entwickelt, der sich auf den Vergleich jeder Echoform mit gepasster Echoform aus 5β-Algorithmus basiert. Ein überwachten Klassifizierungsalgorithmus ist implementiert, um die Echoformen in kohärente Gruppen zu klassifizieren. Für jede kohärente Gruppe ist ein entsprechender retracking-Algorithmus durchgeführt worden. Die Klassifizierung Algorithmus basiert sich auf der Berechnung der Heterogenität der Datensätze, die durch die Differenz zwischen Median und Modal-Echoformen berechnet wird. Wir haben diese Algorithmen verwendet, um die Wasserstandszeitreihen im Balaton (Ungarn) und Urmia (Iran) Seen zu verbessern. Danach haben wir die Ergebnisse der vorgeschlagenen Algorithmen gegen lokalen Daten geprüft

Satellite Radar Altimetry for Inland Hydrologic Studies

This research is conducted under the supervision of Dr. C.K. Shum, Professor of Geodetic Science, School of Earth Sciences, The Ohio State University. The research results documented in this report resulted in a PhD Dissertation. NASA and CNES provided the TOPEX/POSEIDON (Geophysical Data Record and Sensor Data Record, GDR and SDR) data products; LEGOS, USDA/NASA/GSFC provided high-level radar altimetry data products; ANA Brazil, and Environment Canada provided the stage gauge data used for this research. This research is supported by grants from NSF’s Hydrology Program (EAR-0440007) and NGA’s NURI Program (HM1582-07-1-2024), and the study was conducted with the objective to contribute to the Climate, Water, and Carbon Program at The Ohio State University.Satellite radar altimetry, which is originally designed to measure global ocean surface height, has been applied to inland surface water hydrologic studies. We have developed a water-detection algorithm based on statistical analysis of decadal TOPEX/POSEIDON height measurement time series, used the backscatter coefficient to classify the inland surface properties, and the 10-Hz (corresponding to an along track spatial resolution of 700m) radar waveform-retracked TOPEX data, to be able to observe small (<300Km2) inland bodies of water for hydrologic studies. We applied the algorithm to the selected study regions in Manitoba and northwestern (SW) Ontario, Canada, Amazon River Basin, and southwestern Taiwan. Finally we studied the application of TOPEX altimetry to the 1997 Red River flood monitoring. For the study regions in western Manitoba, the correlation coefficient between stage and TOPEX altimetry data in the large Lakes reaches 0.98 using the 10-Hz retracked data, thus verifying the validity and accuracy of the satellite measurement. The importance of the waveform retracking for the inland water applications is validated by the improvement of the correlation coefficients from 0.34 to 0.87 before and after retracking. We detected the bodies of water, which are otherwise missed by using the original 1-Hz data from the Geophysical Data Records, and illustrated that a higher spatial resolution could be achieved using the individual 10-Hz retracked data. In the Amazon River Basin, the capability of the water-detection algorithm is compared with the use of a high water level mask generated by SAR and other data with a spatial resolution of 100m. It is shown that the algorithm could detect the bodies of water, which are missed by the mask primarily because that the frequency of water fluctuation is more than twice a year at some locations. The bodies of water detected only by the algorithm are confirmed using the detailed local hydrological maps in 3 tested regions. The retrieved water height over the small (<300Km2) body of water was compared with the nearby stage measurement and showed good seasonal agreement. In the southwest Taiwan, the monthly variation of 10-Hz AGC from 1992 to 2002 were examined, it is found that the high AGC values could be used to indicate inundated area. We detected the annual and semi-annual variations from the 10-Hz AGC and 10-Hz retracked water height time series, which are attributable to two rainy seasons per year in the study region. For the study of the 1997 Red River flood, we compared the geographic distribution of 0 σ0 before, during and after the 1997 flood and found the high 0 σ0 values (>35dB) indicate the inundated regions. In addition, the comparison of the geographically distributed 0 σ0 during Winter, Spring, Summer and Autumn of 1997 showed that the low 0 σ values (<10dB) indicate snow coverage. The retrieved water height measurements in the flooded regions are compared with the nearby USGS stage measurements and showed good agreements. The comparison of 10-Hz individual retracked measurements with the 1-Hz nonretracked height measurements confirmed the importance of the retracked data (with higher spatial variations) in the flood monitoring. Using 0 σ0 and the retrieved water height measurements, we detected the 1997 flooded regions include the Red River Basin of the North in North Dakota and in western Minnesota, the upper Mississippi River Basin in Minnesota, the Missouri River Basin in southern North Dakota and in South Dakota. The observed flood extents from TOPEX agree well with and complement the USGS stage gauge records

Satellite Radar Altimetry for Inland Hydrologic Studies

This research is conducted under the supervision of Dr. C.K. Shum, Professor of Geodetic Science, School of Earth Sciences, The Ohio State University. The research results documented in this report resulted in a PhD Dissertation. NASA and CNES provided the TOPEX/POSEIDON (Geophysical Data Record and Sensor Data Record, GDR and SDR) data products; LEGOS, USDA/NASA/GSFC provided high-level radar altimetry data products; ANA Brazil, and Environment Canada provided the stage gauge data used for this research. This research is supported by grants from NSF’s Hydrology Program (EAR-0440007) and NGA’s NURI Program (HM1582-07-1-2024), and the study was conducted with the objective to contribute to the Climate, Water, and Carbon Program at The Ohio State University.Satellite radar altimetry, which is originally designed to measure global ocean surface height, has been applied to inland surface water hydrologic studies. We have developed a water-detection algorithm based on statistical analysis of decadal TOPEX/POSEIDON height measurement time series, used the backscatter coefficient to classify the inland surface properties, and the 10-Hz (corresponding to an along track spatial resolution of 700m) radar waveform-retracked TOPEX data, to be able to observe small (<300Km2) inland bodies of water for hydrologic studies. We applied the algorithm to the selected study regions in Manitoba and northwestern (SW) Ontario, Canada, Amazon River Basin, and southwestern Taiwan. Finally we studied the application of TOPEX altimetry to the 1997 Red River flood monitoring. For the study regions in western Manitoba, the correlation coefficient between stage and TOPEX altimetry data in the large Lakes reaches 0.98 using the 10-Hz retracked data, thus verifying the validity and accuracy of the satellite measurement. The importance of the waveform retracking for the inland water applications is validated by the improvement of the correlation coefficients from 0.34 to 0.87 before and after retracking. We detected the bodies of water, which are otherwise missed by using the original 1-Hz data from the Geophysical Data Records, and illustrated that a higher spatial resolution could be achieved using the individual 10-Hz retracked data. In the Amazon River Basin, the capability of the water-detection algorithm is compared with the use of a high water level mask generated by SAR and other data with a spatial resolution of 100m. It is shown that the algorithm could detect the bodies of water, which are missed by the mask primarily because that the frequency of water fluctuation is more than twice a year at some locations. The bodies of water detected only by the algorithm are confirmed using the detailed local hydrological maps in 3 tested regions. The retrieved water height over the small (<300Km2) body of water was compared with the nearby stage measurement and showed good seasonal agreement. In the southwest Taiwan, the monthly variation of 10-Hz AGC from 1992 to 2002 were examined, it is found that the high AGC values could be used to indicate inundated area. We detected the annual and semi-annual variations from the 10-Hz AGC and 10-Hz retracked water height time series, which are attributable to two rainy seasons per year in the study region. For the study of the 1997 Red River flood, we compared the geographic distribution of 0 σ0 before, during and after the 1997 flood and found the high 0 σ0 values (>35dB) indicate the inundated regions. In addition, the comparison of the geographically distributed 0 σ0 during Winter, Spring, Summer and Autumn of 1997 showed that the low 0 σ values (<10dB) indicate snow coverage. The retrieved water height measurements in the flooded regions are compared with the nearby USGS stage measurements and showed good agreements. The comparison of 10-Hz individual retracked measurements with the 1-Hz nonretracked height measurements confirmed the importance of the retracked data (with higher spatial variations) in the flood monitoring. Using 0 σ0 and the retrieved water height measurements, we detected the 1997 flooded regions include the Red River Basin of the North in North Dakota and in western Minnesota, the upper Mississippi River Basin in Minnesota, the Missouri River Basin in southern North Dakota and in South Dakota. The observed flood extents from TOPEX agree well with and complement the USGS stage gauge records

The gulf of cadiz as a natural laboratory for the validation and exploitation of coastal altimetry and model data

Hydrodynamic models and satellite altimetry can be complementary tools for the study of sea level variations. Nowadays, users of these tools demand high quality products in coastal zones. In this sense, this doctoral dissertation focusses on the validation of innovative products that entail an advance in the understanding of sea level variation in coastal areas. The study was carried out in the Gulf of Cadiz (GoC), an important region that connects the Atlantic Ocean and the Mediterranean Sea, although other study areas were also used to strengthen the analysis. The research was performed using: in-situ data, sea level altimetry measurements from Sentinel-3 SRAL, and observations from a hydrodynamic model implemented in the main study area. The in-situ data were used to validate the altimetry measurements, as well as to calibrate and validate the numerical model. Different specific objectives were proposed. The first was to determine the quality of altimetric data in coastal areas from the new Sentinel-3 space mission. Altimetry data of Sentinel-3A SRAL (S3A) were validated at the sampling frequency of 80 Hz. The data were obtained from the European Space Agency (ESA) Grid Processing On Demand (GPOD) service over three coastal sites in Spain: Huelva (GoC), Barcelona (Western Mediterranean Sea), and Bilbao (Bay of Biscay). Two tracks were selected at each site: one ascending and one descending. Data were validated using in-situ tide gauge (TG) data provided by the Spanish Puertos del Estado. The altimetry Sea Level Anomaly (SLA) time series were obtained using the corrections available in GPOD. The validation was performed using two statistical parameters, the Pearson correlation coefficient (r) and the root mean square error (rmse). In the 5–20 km segment with respect to the coastline, the results obtained were 6–8 cm (rmse) and 0.7–0.8 (r) for all of the tracks. The 0–5 km segment was also analysed in detail to study the effect of land on the quality of altimetry data. Results showed that the track orientation, the angle of intersection with the coast, and the land topography concur to determine the nearest distance to the coast at which the data retain a similar level of accuracy than in the 5–20 km segment. This ‗distance of good quality‘ to shore reaches a minimum of 3 km for the tracks at Huelva and the descending track at Barcelona. In addition, altimetry sea level data of Sentinel-3A and Sentinel-3B SRAL (S3A and S3B) were also validated at the sampling frequency of 80 Hz. Two tracks of S3A and two of S3B were selected at seven different coasts around the Iberian Peninsula. The altimetry SLA time series obtained were compared with TG in-situ data using the standard deviation of the difference (sdd) and the normalized sdd (sdd_n). Two tidal models were used: TPXO8 and TPXO9. They were previously validated with in-situ data and then used in the S3 assessment. Contrary to expectations, a more current version of the tide model did not always lead to improvements for all of the coasts studied. The same data availability and accuracy results (mean sdd <9cm) were obtained for both satellites, as the radar altimeter on-board S3A and S3B are identical instruments. The sdd_n results were generally ranged between 0.1 and 0.25 cm, higher values were obtained in coastal areas with a complex hydrodynamic. The second specific objective was to implement the Delft3D model in the estuary of the Guadalquivir River and part of the GoC continental shelf with the aim of studying the influence of its discharges on the sea level variability. Details of the Delft3D FLOW module implementation are given in the manuscript. The model was calibrated and validated along the river estuary comparing the output with in-situ observations of water level and current velocities during normal and high-discharge events. In order to obtain the best possible adjustment, the friction coefficient and bathymetry were used as adjustment parameters. The determination coefficients attained mean values of R2= 0.9 and R2=0.8, for calibration and validation, respectively. Moreover, the model was calibrated for the continental shelf during normal discharge conditions using data from three current meters, obtaining good correlation results (rmse= 3.0 cm·s -1 and R2=0.7, on average). The model simulations were able to reproduce the low salinity plume-induced over-elevations at the mouth of the estuary and its adjacent inner shelf during periods of high river discharge from the head dam (> 400 m3 ·s -1 ). These over-elevations were also identified in a qualitative comparison with altimetry data. Despite the good results obtained, there are some improvements that could be made for future work: including wind, coupling the wave module, updating the bathymetry, etc. The aim of this thesis last section was to apply the new Fully Focused SAR (FF SAR) processing technique for the Sentinel-3 altimetry signal. The accuracy and precision of this novel product were analysed in order to provide the best quality product close to the coast (0-5 km track segment). FF SAR processing is similar to SAR altimetry, but with an unprecedented high along-track resolution which goes up to the theoretical limit equal to half the antenna length (~0.5 m). Two FF SAR algorithms still in development were used in this work: FF SAR Back Projection (BP) (S3 prototype version of Kleinherenbrink et al., 2020), and FF SAR Omega-Kappa (WK) (Guccione et al., 2018), as well as different retracking algorithms. Two tracks from Sentinel-3A and two from Sentinel-3B were processed, at 80 Hz. The products were validated by comparing time series of SLA with those obtained from a tide gauge in the Gulf of Cadiz. The accuracy was analysed using the Percentage of Cycles for High Correlation (PCHC) and the standard deviation of the difference (sdd); and the precision was determined by calculating the along-track noise. FF SAR and unfocused SAR products were compared. The results showed improvements using Adaptative Leading Edge Subwaveform (ALES+) retracker for unfocused SAR, although FF SAR BP with ALES+ was the most precise product for all the tracks. In addition, highly accurate SLA measurements were also obtained with FF SAR products. The greatest advantage of FF SAR is that it produces good quality data closer to the coast (1-2 km) than unfocused SAR (3-4 km). Finally, these results highlight the potential of the implementation of validated altimetry data and hydrodynamic models in sea level studies. Furthermore, the methodology described here can be useful to validate altimetry data, as well as to implement the Delft3D model in other coastal areas

Satellite Altimetry and Hydrologic Modeling of Poorly-Gauged Tropical Watershed

This report was prepared for and submitted to the Graduate School of the Ohio State University as a dissertation for partial fulfillment of the requirements for the Doctor of Philosophy (PhD) degree.This research was carried out under supervision of Professor C.K. Shum, Division of Geodetic Science, School of Earth Sciences, The Ohio State University. Hidayat at Hydrology and Quantitative Water Management Department of Wageningen University and Limnology Research Agency of Indonesian Institute of Sciences (LIPI) are especially acknowledged for providing in-situ discharge, rating curve and precipitation data for the Upper Mahakam Sub-watershed study region.This research is primarily supported by the Fulbright PhD Presidential Scholarship administered by American Indonesian Exchange Foundation (AMINEF) and the Institute for International Education (IIE). In addition, this study is partially funded by grants from NASA's Ocean Surface Topography Science Team project (Univ. of Colorado, 154-5322), NASA's Geodetic Imaging project (NNX12AQ07G), NASA's Application Science Program under the SERVIR project (NNX12AM85G), and The Ohio State University's Climate, Water, and Carbon (http://cwc.osu.edu/) program.Fresh water resources are critical for daily human consumption. Therefore, a continuous monitoring effort over their quantity and quality is instrumental. One important model for water quantity monitoring is the rainfall-runoff model, which represents the response of a watershed to the variability of precipitation, thus estimating the discharge of a channel (Bedient and Huber, 2002, Beven, 2012). Remote sensing and satellite geodetic observations are capable to provide critical hydrological parameters, which can be used to support hydrologic modeling. For the case of satellite radar altimetry, limited temporal resolutions (e.g., satellite revisit period) prohibit the use of this method for a short (<weekly) interval monitoring of water level or discharge. On the other hand, the current satellite radar altimeter footprints limit the water level measurement for rivers wider than 1 km (Birkett, 1998, Birkett et al., 2002). Some studies indeed reported successful retrieval of water level for small-size rivers as narrow as 80 m (Kuo and Kao, 2011, Michailovsky et al., 2012); however, the processing of current satellite altimetry signals for small water bodies to retrieve accurate water levels, remains challenging. To address this scientific challenge, this study poses two main objectives: (1) to monitor small (40–200 m width) and medium-sized (200–800 m width) rivers and lakes using satellite altimetry through identification and choice of the over-water radar waveforms corresponding to the appropriately waveform-retracked water level; and (2) to develop a rainfall-runoff hydrological model to represent the response of mesoscale watershed to the variability of precipitation. Both studies address the humid tropics of Southeast Asia, specifically in Indonesia, where similar studies do not yet exist. This study uses the Level 2 radar altimeter measurements generated by European Space Agency’s (ESA’s) Envisat (Environmental Satellite) mission. The first study proves that satellite altimetry provides a good alternative or the only means in some regions to measure the water level of medium-sized river (200–800 m width) and small lake (extent <1000 km2) in Southeast Asia humid tropic with reasonable accuracy. In addition, the procedure to choose retracked Envisat altimetry water level heights via identification or selection of over water waveform shapes is reliable; therefore this study concluded that the use of waveform shape selection procedure should be a standard measure in determining qualified range measurements especially over small rivers and lakes. This study also found that Ice-1 is not necessarily the best retracker as reported by previous studies, among the four standard waveform retracking algorithms for Envisat altimetry observing hydrologic bodies. The second study modeled the response of the poorly-gauged watershed in the Southeast Asia’s humid tropic through the application of Hydrologic Engineering Center – Hydrologic Modeling System (HEC-HMS). The performance evaluation of HEC-HMS discharge estimation confirms a good match between the simulated discharges with the observed ones. As the result of precipitation data analysis, this study found that Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is the preferred input forcing for the model, given the thorough evaluation of its relationship with field-measured precipitation data prior to its use as primary climatic forcing. This iii research also proposes a novel approach to process the TRMM precipitation estimation spatially through Thiessen polygon and area average hybrid method, which model the spatial distribution of TRMM data to match the spatial location of field meteorological stations. Through a simultaneous validation that compares the water level anomaly transformed from HEC-HMS simulated discharge and satellite altimetry measurement, this study found that satellite altimetry measures water level anomaly closer to the true water level anomaly than the water level anomaly converted from HEC-HMS simulated discharge. Some critical recommendations for future studies include the use of waveform shape selection procedure in the satellite altimetry based water level measurement of small and medium-sized rivers and small lakes, as well as the exploration to implement data assimilation between satellite altimetry and the hydrologic model for better discharge and water level estimations