H118
Remote Sensing of Hydrology and Environmental Change in the Cryosphere
Session ID#: 85499
Session Description:
The cryosphere, including the northern high latitudes, polar regions, and High Mountain Asia, are highly sensitive to climate change and are undergoing dramatic changes in ecological, hydrologic, and climatic processes. Remote sensing is an invaluable resource for studying these remote and rugged regions, extending the value of sparse ground observations and providing synoptic monitoring. We welcome abstracts related to any aspect of remote sensing of hydrology or environmental change in the cryosphere, including 1) computational and algorithmic advances, 2) long-term monitoring, including in-situ calibration/validation, 3) novel observation techniques, and 4) cloud computation and machine learning techniques.
Index Terms:
0798 Modeling [CRYOSPHERE]
1655 Water cycles [GLOBAL CHANGE]
1855 Remote sensing [HYDROLOGY]
1863 Snow and ice [HYDROLOGY]
Primary Convener: Colin J Gleason, University of Massachusetts Amherst, Civil & Environmental Engineering, Amherst, MA, United States
Conveners: Hui Lu, Department of Earth System Science, Tsinghua University, Beijing, China, Sarah W Cooley, Brown University, Providence, RI, United States and Lingmei Jiang, Beijing Normal University, Beijing, China
Primary Liaison: Hui Lu, Department of Earth System Science, Tsinghua University, Beijing, China
The past and future of global river and lake ice (Invited) (488701)
Xiao Yang, University of North Carolina at Chapel Hill, Chapel Hill, United States, Tamlin Pavelsky, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States and George Henry Allen, Texas A&M University, Department of Geography, College Station, TX, United States
Comparing discharge estimates in high-order Arctic rivers derived solely from optical CubeSat, Landsat, and Sentinel-2 data (499638)
Dongmei Feng, University of Massachusetts Amherst, Amherst, MA, United States, Colin J Gleason, University of Massachusetts Amherst, Civil & Environmental Engineering, Amherst, MA, United States, Xiao Yang, University of North Carolina at Chapel Hill, Chapel Hill, United States and Tamlin Pavelsky, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
A Two-Step Fusion Framework for Quality Improvement of Remotely Sensed Soil Moisture Product: A Case Study for ECV product over the Tibetan Plateau (501235)
Yaokui Cui1, Yang Hong1, Xuebin Yang2, Xi Chen1, Wenjie Fan1, Chao Zeng3, Huan Li1 and Wentao Xiong1, (1)Peking University, Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Beijing, China, (2)University of Texas at Austin, Department of Geography and Environment, Austin, TX, United States, (3)Wuhan University, Beijing, China
Rapid River Discharge Estimation from Pressure Transducer Arrays in the Peace-Athabasca Delta, Canada (525554)
Merritt Harlan1, Colin J Gleason2, Laurence C Smith3, Tamlin Pavelsky4, Wayana Dolan4, Jessica V. Fayne5, Yuta Ishitsuka1, Ethan D. Kyzivat3, Theodore Langhorst4 and Lincoln H Pitcher6, (1)University of Massachusetts Amherst, Amherst, MA, United States, (2)University of Massachusetts Amherst, Civil & Environmental Engineering, Amherst, MA, United States, (3)Brown University, Providence, RI, United States, (4)University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, (5)University of California Los Angeles, Department of Geography, Los Angeles, CA, United States, (6)University of California Los Angeles, Los Angeles, CA, United States
Evaluation of Satellite Based Soil Freeze/Thaw Products in High Latitude Regions in Asia (525877)
Hui Lu1, Fengjie Ren1, Kun Yang2 and Bin Wang3, (1)Tsinghua University, Department of Earth System Science, Beijing, China, (2)Tsinghua University, Beijing, China, (3)Insititute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Remotely sensed discharge and sediment flux of the Sagavanirktok River (525944)
Theodore Langhorst1, Tamlin Pavelsky1, Simon Topp1, Matthew Ross2, Chunli Dai3, Michael T Durand4, Renato P. M. Frasson5 and Ian Howat6, (1)University of North Carolina at Chapel Hill, Chapel Hill, NC, United States, (2)Colorado State University, Ecosystem Science and Sustainability, Fort Collins, CO, United States, (3)Ohio State University Main Campus, Division of Geodetic Science, School of Earth Sciences, Columbus, OH, United States, (4)The Ohio State University, School of Earth Science and Byrd Polar and Climate Research Center, Columbus, OH, United States, (5)Ohio State University Main Campus, Byrd Polar and Climate Research Center, Columbus, OH, United States, (6)Ohio State University, Byrd Polar & Climate Research Center, Columbus, OH, United States
New Snow & Sea Ice Detection Algorithm Using the New Geostationary Meteorological Satellites Himawari-8 and 9/AHI (579902)
Yusuke Yogo1, Yusuke Ioka1, Haruma Ishida1, Tomonori Tanikawa2, Masahiro Hosaka2 and Teruo Aoki3, (1)JMA Japan Meteorological Agency, Tokyo, Japan, (2)Meteorological Research Institute, Tsukuba, Japan, (3)NIPR National Institute of Polar Research, Tokyo, Japan
Measurement of River Widths and Heights from ArcticDEM and High-Resolution Satellite Imagery (587655)
Bidhyananda Yadav1, Chunli Dai2, Michael T Durand3, Ian M Howat4 and Renato P. M. Frasson1, (1)Ohio State University Main Campus, Byrd Polar and Climate Research Center, Columbus, OH, United States, (2)Ohio State University Main Campus, Division of Geodetic Science, School of Earth Sciences, Columbus, OH, United States, (3)The Ohio State University, School of Earth Science and Byrd Polar and Climate Research Center, Columbus, OH, United States, (4)Ohio State University, Byrd Polar & Climate Research Center, Columbus, OH, United States
Climate Change Leads to A Doubling of Turbidity in A Rapidly Expanding Tibetan Lake (589347)
Huan MI1, Sergio Fagherazzi2, Gang Qiao1, Yang Hong3 and Cedric G Fichot2, (1)Tongji University, Shanghai, China, (2)Boston University, Boston, MA, United States, (3)University of Oklahoma, Norman, OK, United States
Downscaling Daily Remotely Sensed Snow Cover Fraction Based on a Two Stage Machine Learning Model (617450)
William Kleiber, University of Colorado, Boulder, CO, United States, Karl Rittger, University of Colorado at Boulder, Institute for Arctic and Alpine Research, Boulder, CO, United States, Balaji Rajagopalan, University of Colorado at Boulder, Department of Civil, Environmental and Architectural Engineering and CIRES, Boulder, CO, United States, Mary J. Brodzik, Univ Colorado, Boulder, CO, United States and Mitchell Krock, University of Colorado at Boulder, Boulder, United States
Extracting Supraglacial Streams on Greenland Ice Sheet Using High-Resolution Satellite Imagery (634201)
Samira Daneshgar Asl1, Vena W. Chu1, Morteza Noshad2 and Kang Yang3, (1)University of California Santa Barbara, Geography, Santa Barbara, CA, United States, (2)University of Michigan, Computer Science and Engineering, Ann Arbor, MI, United States, (3)Nanjing University, Geography, Nanjing, China
