{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:12:39Z","timestamp":1777889559084,"version":"3.51.4"},"reference-count":54,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T00:00:00Z","timestamp":1623283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["NNX15AT74A"],"award-info":[{"award-number":["NNX15AT74A"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["80NSSC18K0980"],"award-info":[{"award-number":["80NSSC18K0980"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Yukon River basin encompasses over 832,000 km2 of boreal Arctic Alaska and northwest Canada, providing a major transportation corridor and multiple natural resources to regional communities. The river seasonal hydrology is defined by a long winter frozen season and a snowmelt-driven spring flood pulse. Capabilities for accurate monitoring and forecasting of the annual spring freshet and river ice breakup (RIB) in the Yukon and other northern rivers is limited, but critical for understanding hydrologic processes related to snow, and for assessing flood-related risks to regional communities. We developed a regional snow phenology record using satellite passive microwave remote sensing to elucidate interactions between the timing of upland snowmelt and the downstream spring flood pulse and RIB in the Yukon. The seasonal snow metrics included annual Main Melt Onset Date (MMOD), Snowoff (SO) and Snowmelt Duration (SMD) derived from multifrequency (18.7 and 36.5 GHz) daily brightness temperatures and a physically-based Gradient Ratio Polarization (GRP) retrieval algorithm. The resulting snow phenology record extends over a 29-year period (1988\u20132016) with 6.25 km grid resolution. The MMOD retrievals showed good agreement with similar snow metrics derived from in situ weather station measurements of snowpack water equivalence (r = 0.48, bias = \u22123.63 days) and surface air temperatures (r = 0.69, bias = 1 day). The MMOD and SO impact on the spring freshet was investigated by comparing areal quantiles of the remotely sensed snow metrics with measured streamflow quantiles over selected sub-basins. The SO 50% quantile showed the strongest (p &lt; 0.1) correspondence with the measured spring flood pulse at Stevens Village (r = 0.71) and Pilot (r = 0.63) river gaging stations, representing two major Yukon sub-basins. MMOD quantiles indicating 20% and 50% of a catchment under active snowmelt corresponded favorably with downstream RIB (r = 0.61) from 19 river observation stations spanning a range of Yukon sub-basins; these results also revealed a 14\u201327 day lag between MMOD and subsequent RIB. Together, the satellite based MMOD and SO metrics show potential value for regional monitoring and forecasting of the spring flood pulse and RIB timing in the Yukon and other boreal Arctic basins.<\/jats:p>","DOI":"10.3390\/rs13122284","type":"journal-article","created":{"date-parts":[[2021,6,10]],"date-time":"2021-06-10T21:34:38Z","timestamp":1623360878000},"page":"2284","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Snow Phenology and Hydrologic Timing in the Yukon River Basin, AK, USA"],"prefix":"10.3390","volume":"13","author":[{"given":"Caleb G.","family":"Pan","sequence":"first","affiliation":[{"name":"Innov8.ag Solutions, Walla Walla, WA 99362, USA"},{"name":"Numerical Terradynamic Simulations Group, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT 59801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9770-5530","authenticated-orcid":false,"given":"Peter B.","family":"Kirchner","sequence":"additional","affiliation":[{"name":"Southwest Alaska Network Inventory and Monitoring Program, National Park Service, Anchorage, AK 99501, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5493-5878","authenticated-orcid":false,"given":"John S.","family":"Kimball","sequence":"additional","affiliation":[{"name":"Numerical Terradynamic Simulations Group, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT 59801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinyang","family":"Du","sequence":"additional","affiliation":[{"name":"Numerical Terradynamic Simulations Group, W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT 59801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3323-8256","authenticated-orcid":false,"given":"Michael A.","family":"Rawlins","sequence":"additional","affiliation":[{"name":"Department of Geosciences, University of Massachusetts, Amherst, MA 01003, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8006","DOI":"10.1002\/2016GL069690","article-title":"Snowmelt rate dictates streamflow","volume":"43","author":"Barnhart","year":"2016","journal-title":"Geophys. Res. 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