{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T12:37:34Z","timestamp":1764333454126,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T00:00:00Z","timestamp":1721174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Flow\u2013duration curves (FDCs) provide a compact view of the historical variability of river flows, reflecting climate conditions and the main hydrologic features of river basins. The Surface Water and Ocean Topography (SWOT) satellite mission will enable the estimation of river flows globally, by sensing rivers wider than 100 m with a sampling recurrence from 3 to 21 days. This study investigated the lifetime mission potential for FDC estimation through the comparison between remotely-sensed and empirical FDCs. We employed the Global Runoff Data Center dataset and derived SWOT-like river flows by selecting gauging stations of rivers wider than 100 m with more than 10-year long daily river flow time series. Overall, 1200 gauged river cross-sections were examined. For each site, we created a set of 24 SWOT-simulated FDCs (i.e., based on different sampling recurrences, mean biases, and random errors) to be compared against their empirical counterparts through the Nash\u2013Sutcliffe efficiency and the mean relative error. Our results show that climate and the sampling recurrence play a key role on the performance of SWOT-based FDCs. Tropical and temperate climates performed the best, whereas arid climates mostly revealed higher uncertainties, especially for high- and low-flows.<\/jats:p>","DOI":"10.3390\/rs16142607","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T08:48:29Z","timestamp":1721206109000},"page":"2607","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Potential Legacy of SWOT Mission for the Estimation of Flow\u2013Duration Curves"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4726-5316","authenticated-orcid":false,"given":"Alessio","family":"Domeneghetti","sequence":"first","affiliation":[{"name":"Department of Civil, Chemical, Environmental and Materials Engineering, Alma Mater Studiorum Universit\u00e0 di Bologna, 40136 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1757-509X","authenticated-orcid":false,"given":"Serena","family":"Ceola","sequence":"additional","affiliation":[{"name":"Department of Civil, Chemical, Environmental and Materials Engineering, Alma Mater Studiorum Universit\u00e0 di Bologna, 40136 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0403-0533","authenticated-orcid":false,"given":"Alessio","family":"Pugliese","sequence":"additional","affiliation":[{"name":"Arpae-SIMC, Hydro-Meteo-Climate Service of the Regional Agency for Prevention, Environment and Energy (ARPAE), 43125 Parma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9857-738X","authenticated-orcid":false,"given":"Simone","family":"Persiano","sequence":"additional","affiliation":[{"name":"Catastrophe Risk Modeling & Mitigation, UnipolSai Assicurazioni S.p.A., Piazza Della Costituzione 2\/2, 40128 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8273-2472","authenticated-orcid":false,"given":"Irene","family":"Palazzoli","sequence":"additional","affiliation":[{"name":"Department of Civil, Chemical, Environmental and Materials Engineering, Alma Mater Studiorum Universit\u00e0 di Bologna, 40136 Bologna, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6111-0612","authenticated-orcid":false,"given":"Attilio","family":"Castellarin","sequence":"additional","affiliation":[{"name":"Department of Civil, Chemical, Environmental and Materials Engineering, Alma Mater Studiorum Universit\u00e0 di Bologna, 40136 Bologna, Italy"}]},{"given":"Alberto","family":"Marinelli","sequence":"additional","affiliation":[{"name":"Department of Civil, Chemical, Environmental and Materials Engineering, Alma Mater Studiorum Universit\u00e0 di Bologna, 40136 Bologna, Italy"}]},{"given":"Armando","family":"Brath","sequence":"additional","affiliation":[{"name":"Department of Civil, Chemical, Environmental and Materials Engineering, Alma Mater Studiorum Universit\u00e0 di Bologna, 40136 Bologna, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"586","DOI":"10.1038\/s41893-022-00873-0","article-title":"Assessing Placement Bias of the Global River Gauge Network","volume":"5","author":"Krabbenhoft","year":"2022","journal-title":"Nat. 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