Satellite Radar and Laser Altimetry for Monitoring of Lake Water Level And

Satellite Radar and Laser Altimetry for Monitoring of Lake Water Level and Snow Accumulation in Arctic Regions A dissertation submitted to the Graduate School of the University of Cincinnati in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Geography & Geographic Information Science of the College of Arts and Sciences by Song Shu B.S., Physical Geography, East China Normal University, China, 2010 M.A., GIS, East China Normal University, China, 2013 Committee Chair: Hongxing Liu, Ph.D. March 2019 ABSTRACT Thermokarst lakes are the most conspicuous features in the Arctic coastal regions that cover roughly 15% - 40 % percent of the area. Those lakes play as a critical niche in the local environment system and provide habitats for a great number of species. In the context of global warming, lakes are experiencing dramatic changes in recent decades. The lake water level and the snow cover atop the ice in the winter are two sensitive indicators of the local and global climate change. Monitoring the variations in lake water level and snow accumulation in Arctic regions could provide more insights of the global climate change and facilitate our understanding of their influences on local hydrological and ecological systems. However, there are very rare in situ observations of lake water levels and lake snow accumulations for the Arctic regions due to the remote locations and also the harsh environmental conditions. Satellite radar and laser altimetry measures elevation profiles of Earth’s surface at the global scale and offers an alternative to achieve the purpose. Most previous studies have focused on the application of satellite radar and laser altimetry on lakes at low or middle latitudes, with few of them discussing the applicability of these data to high-latitude lakes. In this research, I explored the capability of satellite radar and laser altimetry missions to monitor lake water levels and snow accumulation on frozen lakes in the Arctic coastal regions. The performances of Sentinel-3, the most recent satellite radar altimetry, on the retrieval of lake water levels were assessed particularly for high-latitude ice-covered lakes. The results showed that lake ice can greatly reduce the accuracy of Sentinel-3 observations. I developed a new empirical retracking algorithm that significantly improves the measurements and provide more reliable and consistent water level estimates for the ice-covered lakes. I examined the performances of ICESat/GLAS, the first satellite laser altimetry mission, on the retrieval of lake surface elevations in Arctic regions. A novel probabilistic relaxation algorithm was then ii developed to correct and improve the laser altimetry measurements that were affected by the thin clouds, ice fogs and blowing snow in Arctic regions. The snow accumulations on frozen lake surfaces in the winter were then derived using the corrected ICESat repeat observations. As compared to the point-based in situ snow depth data, these relatively dense ICESat-derived snow accumulation estimates enable us to investigate its spatio-temporal variations across the Arctic coastal regions. Keywords: Satellite radar and laser altimetry, water levels, snow accumulation, Sentinel-3, ICESat/GLAS, altimetry waveform retracking. iii iv ACKNOWLEDGMENTS I would like to express my enormous gratitude to my advisor, Dr. Hongxing Liu, for his guidance over the past six years. Under his supervision, I learned how to define a research question, approach the question, find a solution, write a paper and finally publish the results. I could never push my way through the numerous obstacles and achieve this point without his encouragement and support. He not only teaches me how to do high-quality researches but also how to face the life difficulties with active and positive attitudes. I am so grateful to my dissertation committee members, Dr. Richard Beck, Dr. Kenneth Hinkel, Dr. Tomasz Stepinski and Dr. Emily Lei Kang for their valuable advices and insightful comments on my dissertation research. Special thanks should be given to Dr. Beck for his help and support during my last year at University of Cincinnati. I want to thank all the department faculties and staffs for making my study at University of Cincinnati a great unforgettable experience. I would also like to acknowledge some of my colleagues. I want to thank Lei Wang for his technical support on the processing of ICESat level-1 and level-2 data. Qiusheng Wu and Bo Yang provided valuable sources of experienced knowledge on the issues I met in my study and daily life in Cincinnati. Special thanks are extended to my friends in Remote Sensing Lab at UC: Shujie Wang, Min Xu, Yan Huang, Zuoqi Chen, Bin Wu, Yang Liu and Minxuan Lan for the wonderful time we spent together. Last, but not least, I want to thank my family for their patience, understanding and support. In particular, I would like to thank my beloved wife. Without her love, trust and encouragement the completion of this work could not have been possible. v CONTENTS ABSTRACT ........................................................................................................................ ii ACKNOWLEDGMENTS ................................................................................................... v CONTENTS ....................................................................................................................... vi LIST OF FIGURES .......................................................................................................... viii LIST OF TABLES .............................................................................................................. xi Chapter1: Introduction ....................................................................................................... 12 Chapter 2: Analysis of Sentinel-3 SAR Altimetry Waveform Retracking Algorithms for Deriving Temporally Consistent Water Levels over Inland Lakes .................................... 18 2.1 Introduction ......................................................................................................................... 18 2.2 Case study lakes and in situ water level measurements ...................................................... 22 2.2.1 Case study lakes and their winter ice conditions ....................................................................... 22 2.2.2 In situ water level and ice thickness measurements from gauge stations .................................. 25 2.3 Derivation of Sentinel-3 SRAL SAR lake water level estimates .......................................... 27 2.3.1 SRAL data products ................................................................................................................... 27 2.3.2 SRAL SAR waveform and SAR retrackers ............................................................................... 30 2.3.3 A new bimodal retracker for the retrieval of water-equivalent lake surface elevation over ice- covered lakes ....................................................................................................................................... 33 2.3.4 Estimation of lake water level using SRAL SAR elevation measurements ............................... 36 2.4 Results and Discussions ...................................................................................................... 38 2.4.1 Lake surface profiles retrieved by different SAR retrackers ...................................................... 38 2.4.2 SAR retracker performances over the lakes with different ice cover conditions ....................... 41 2.4.3 Detection of lake ice with simultaneous Sentinel-3 MWR measurements ................................ 49 2.4.4 Influence of lake ice on SAR altimetry waveform ..................................................................... 51 2.4.5 Application of bimodal retracker for the retrieval of water-equivalent lake levels ................... 57 2.5 Conclusions ......................................................................................................................... 59 Chapter 3: Improving Satellite Waveform Altimetry Measurements with a Probabilistic Relaxation Algorithm......................................................................................................... 61 3.1 Introduction ......................................................................................................................... 61 3.2 Datasets ............................................................................................................................... 65 3.3 ICESat/GLAS standard retracking methods ....................................................................... 66 vi 3.4 New probabilistic relaxation retracking method ................................................................ 69 3.4.1 Spatial contextual information along the satellite track ............................................................. 70 3.4.2 Decomposition of the returned waveform.................................................................................. 71 3.4.3 Identification of the true signal-peak using the probabilistic relaxation method ....................... 72 3.5 Application examples .......................................................................................................... 79 3.5.1 The snow surface of Lake Teshekpuk in Arctic Coastal Plain .................................................. 80 3.5.2 Tundra surface in the Arctic coastal plain.................................................................................

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