{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:22:00Z","timestamp":1760232120768,"version":"build-2065373602"},"reference-count":62,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,17]],"date-time":"2022-10-17T00:00:00Z","timestamp":1665964800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["41874095","41704013","42061134010","XDA20100300","XDA15017700","M.IF.A. QOP18098","2019CFA09","10.46540\/2035-00247B","SUBK00011366"],"award-info":[{"award-number":["41874095","41704013","42061134010","XDA20100300","XDA15017700","M.IF.A. 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QOP18098","2019CFA09","10.46540\/2035-00247B","SUBK00011366"],"award-info":[{"award-number":["41874095","41704013","42061134010","XDA20100300","XDA15017700","M.IF.A. QOP18098","2019CFA09","10.46540\/2035-00247B","SUBK00011366"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurately monitoring spatio-temporal changes in lake water levels is important for studying the impacts of climate change on freshwater resources, and for predicting natural hazards. In this study, we applied multi-mission radar satellite altimetry data from the Laurentian Great Lakes, North America to optimally reconstruct multi-decadal lake-wide spatio-temporal changes of water level. We used the results to study physical processes such as teleconnections of El Ni\u00f1o and southern oscillation (ENSO) episodes over approximately the past three-and-a-half decades (1985\u20132018). First, we assessed three reconstruction methods, namely the standard empirical orthogonal function (EOF), complex EOF (CEOF), and complex independent component analysis (CICA), to model the lake-wide changes of water level. The performance of these techniques was evaluated using in-situ gauge data, after correcting the Glacial Isostatic Adjustment (GIA) process using a contemporary GIA forward model. While altimeter-measured water level was much less affected by GIA, the averaged gauge-measured water level was found to have increased up to 14 cm over the three decades. Our results indicate that the CICA-reconstructed 35-year lake level was more accurate than the other two techniques. The correlation coefficients between the CICA reconstruction and the in situ water-level data were 0.96, 0.99, 0.97, 0.97, and 0.95, for Lake Superior, Lake Michigan, Lake Huron, Lake Erie, and Lake Ontario, respectively; ~7% higher than the original altimetry data. The root mean squares of errors (RMSE) were 6.07 cm, 4.89 cm, 9.27 cm, 7.71 cm, and 9.88 cm, respectively, for each of the lakes, and ~44% less than differencing with the original altimetry data. Furthermore, the CICA results indicated that the water-level changes in the Great Lakes were significantly correlated with ENSO, with correlation coefficients of 0.5\u20130.8. The lake levels were ~25 cm higher (~30 cm lower) than normal during EI Ni\u00f1o (La Ni\u00f1a) events.<\/jats:p>","DOI":"10.3390\/rs14205194","type":"journal-article","created":{"date-parts":[[2022,10,18]],"date-time":"2022-10-18T00:31:01Z","timestamp":1666053061000},"page":"5194","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Understanding Water Level Changes in the Great Lakes by an ICA-Based Merging of Multi-Mission Altimetry Measurements"],"prefix":"10.3390","volume":"14","author":[{"given":"Wei","family":"Chen","sequence":"first","affiliation":[{"name":"College of Resource Environment and Tourism, Hubei University of Arts and Science, Xiangyang 441053, China"}]},{"given":"C. K.","family":"Shum","sequence":"additional","affiliation":[{"name":"Division of Geodetic Science, School of Earth Sciences, Ohio State University, Columbus, OH 43210, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3055-041X","authenticated-orcid":false,"given":"Ehsan","family":"Forootan","sequence":"additional","affiliation":[{"name":"Department of Planning, Aalborg University, 9220 Aalborg, Denmark"}]},{"given":"Wei","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai 519082, China"}]},{"given":"Min","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-Sen University, Zhuhai 519082, China"}]},{"given":"Yuanyuan","family":"Jia","sequence":"additional","affiliation":[{"name":"Division of Geodetic Science, School of Earth Sciences, Ohio State University, Columbus, OH 43210, USA"}]},{"given":"Wenhao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211800, China"}]},{"given":"Junyi","family":"Guo","sequence":"additional","affiliation":[{"name":"Division of Geodetic Science, School of Earth Sciences, Ohio State University, Columbus, OH 43210, USA"}]},{"given":"Changqing","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Geodesy and Earth\u2019s Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, China"}]},{"given":"Quanguo","family":"Li","sequence":"additional","affiliation":[{"name":"College of Resource Environment and Tourism, Hubei University of Arts and Science, Xiangyang 441053, China"}]},{"given":"Lei","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Geographic Information and Tourism, Chuzhou University, Chuzhou 239099, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,17]]},"reference":[{"key":"ref_1","unstructured":"Waples, J.T., Eadie, B., Klump, J.V., Squires, M., Cotner, J., and McKinley, G. 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