{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T19:30:58Z","timestamp":1774553458354,"version":"3.50.1"},"reference-count":95,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T00:00:00Z","timestamp":1708992000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42371394"],"award-info":[{"award-number":["42371394"]}]},{"name":"National Natural Science Foundation of China","award":["B230201031"],"award-info":[{"award-number":["B230201031"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["42371394"],"award-info":[{"award-number":["42371394"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["B230201031"],"award-info":[{"award-number":["B230201031"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Rivers in arid regions serve as crucial freshwater resources for local communities and play an essential role in global hydrological and biogeochemical cycles. The Aral Sea Basin (ASB) in Central Asia is characterized by an arid climate and river dynamics that are sensitive to climate change and human activities. Monitoring the spatiotemporal variations in river water extent in the ASB is essential to maintain an ecological balance and ensure water security. In this study, we extracted data regarding monthly river water bodies in the ASB from 2017 to 2022 by synthesizing monthly Sentinel-2 images. The water extents on the Sentinel images were automatically mapped using the Otsu method, and the river widths for all river channels were calculated using the RivWidth algorithm. We investigated the relationships between the river dynamics and the geomorphology, climatic change, human activities, and the annual and interannual variations in the river width in different reaches of the basin. The results show a seasonal variability in the river width, with most rivers reaching the largest width in the warm season and a few rivers in the middle and lower areas reaching the valley value in the warm season. Compared to their tributaries, the mainstem in the middle\/lower regions showed less seasonal variability. According to interannual analysis, most of the rivers in the ASB significantly narrowed between 2017 and 2022, a phenomenon which is generally impacted by temperature and evapotranspiration variations. Comparisons show that our results provide improved information about the narrow river reaches and denser river networks compared to the previous global dataset, demonstrating the advantageous properties of high spatial resolution in Sentinel-2 imagery.<\/jats:p>","DOI":"10.3390\/rs16050822","type":"journal-article","created":{"date-parts":[[2024,2,28]],"date-time":"2024-02-28T07:56:02Z","timestamp":1709106962000},"page":"822","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Monitoring Spatial\u2013Temporal Variations in River Width in the Aral Sea Basin with Sentinel-2 Imagery"],"prefix":"10.3390","volume":"16","author":[{"given":"Jingjing","family":"Zhou","sequence":"first","affiliation":[{"name":"College of Geography and Remote Sensing, Hohai University, Nanjing 210098, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9374-943X","authenticated-orcid":false,"given":"Linghong","family":"Ke","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing, Hohai University, Nanjing 210098, China"}]},{"given":"Xin","family":"Ding","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing, Hohai University, Nanjing 210098, China"}]},{"given":"Ruizhe","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing, Hohai University, Nanjing 210098, China"}]},{"given":"Fanxuan","family":"Zeng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1068","DOI":"10.1126\/science.1128845","article-title":"Global Hydrological Cycles and World Water Resources","volume":"313","author":"Oki","year":"2006","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"7753","DOI":"10.1029\/2019WR025599","article-title":"Comparing Discharge Estimates Made via the BAM Algorithm in High-Order Arctic Rivers Derived Solely from Optical CubeSat, Landsat, and Sentinel-2 Data","volume":"55","author":"Feng","year":"2019","journal-title":"Water Resour. 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