{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T21:58:13Z","timestamp":1766267893505,"version":"build-2065373602"},"reference-count":114,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T00:00:00Z","timestamp":1700006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Science and Innovation","award":["PID2021-12323SNB-I00"],"award-info":[{"award-number":["PID2021-12323SNB-I00"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring snowmelt dynamics in mountains is crucial to understand water releases downstream. Sentinel-1 (S-1) synthetic-aperture radar (SAR) has become one of the most widely used techniques to achieve this aim due to its high frequency of acquisitions and all-weather capability. This work aims to understand the possibilities of S-1 SAR imagery to capture snowmelt dynamics and related changes in streamflow response in semi-arid mountains. The results proved that S-1 SAR imagery was able not only to capture the final spring melting but also all melting cycles that commonly appear throughout the year in these types of environments. The general change detection approach to identify wet snow was adapted for these regions using as reference the average S-1 SAR image from the previous summer, and a threshold of \u22123.00 dB, which has been assessed using Landsat images as reference dataset obtaining a general accuracy of 0.79. In addition, four different types of melting-runoff onsets depending on physical snow condition were identified. When translating that at the catchment scale, distributed melting-runoff onset maps were defined to better understand the spatiotemporal evolution of melting dynamics. Finally, a linear connection between melting dynamics and streamflow was found for long-lasting melting cycles, with a determination coefficient (R2) ranging from 0.62 to 0.83 and an average delay between the melting onset and streamflow peak of about 21 days.<\/jats:p>","DOI":"10.3390\/rs15225365","type":"journal-article","created":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T10:57:46Z","timestamp":1700045866000},"page":"5365","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Characterizing Snow Dynamics in Semi-Arid Mountain Regions with Multitemporal Sentinel-1 Imagery: A Case Study in the Sierra Nevada, Spain"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8771-1635","authenticated-orcid":false,"given":"Pedro","family":"Torralbo","sequence":"first","affiliation":[{"name":"Fluvial Dynamics and Hydrology Research Group, Andalusian Institute for Earth System Research, University of C\u00f3rdoba, Campus Rabanales, Edificio Leonardo da Vinci, \u00c1rea de Ingenier\u00eda Hidr\u00e1ulica, 14071 C\u00f3rdoba, Spain"},{"name":"Department of Agronomy, Unit of Excellence Mar\u00eda de Maeztu (DAUCO), University of C\u00f3rdoba, 14071 C\u00f3rdoba, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6990-4874","authenticated-orcid":false,"given":"Rafael","family":"Pimentel","sequence":"additional","affiliation":[{"name":"Fluvial Dynamics and Hydrology Research Group, Andalusian Institute for Earth System Research, University of C\u00f3rdoba, Campus Rabanales, Edificio Leonardo da Vinci, \u00c1rea de Ingenier\u00eda Hidr\u00e1ulica, 14071 C\u00f3rdoba, Spain"},{"name":"Department of Agronomy, Unit of Excellence Mar\u00eda de Maeztu (DAUCO), University of C\u00f3rdoba, 14071 C\u00f3rdoba, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6296-2198","authenticated-orcid":false,"given":"Maria Jos\u00e9","family":"Polo","sequence":"additional","affiliation":[{"name":"Fluvial Dynamics and Hydrology Research Group, Andalusian Institute for Earth System Research, University of C\u00f3rdoba, Campus Rabanales, Edificio Leonardo da Vinci, \u00c1rea de Ingenier\u00eda Hidr\u00e1ulica, 14071 C\u00f3rdoba, Spain"},{"name":"Department of Agronomy, Unit of Excellence Mar\u00eda de Maeztu (DAUCO), University of C\u00f3rdoba, 14071 C\u00f3rdoba, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1968-0125","authenticated-orcid":false,"given":"Claudia","family":"Notarnicola","sequence":"additional","affiliation":[{"name":"Institute for Earth Observation, EURAC Research, 39100 Bolzano, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1111\/nyas.14337","article-title":"Advances in Understanding Large-Scale Responses of the Water Cycle to Climate Change","volume":"1472","author":"Allan","year":"2020","journal-title":"Ann. 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