{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,16]],"date-time":"2025-01-16T05:22:39Z","timestamp":1737004959110,"version":"3.33.0"},"reference-count":54,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T00:00:00Z","timestamp":1673222400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["51909053","U2240201","52109002"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Visiting Researcher Fund Program of State Key Laboratory of Water Resources and Hydropower Engineering","award":["2019SWG02"]},{"DOI":"10.13039\/501100005416","name":"Research Council of Norway","doi-asserted-by":"crossref","award":["No. 274310","No. 302457"],"id":[{"id":"10.13039\/501100005416","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"The fundamental assumption of flood frequency analysis is that flood samples are generated by the same flood generation mechanism (FGM). However, flood events are usually triggered by the interaction of meteorological factors and watershed properties, which results in different FMGs. To solve this problem, researchers have put forward traditional two-component mixture distributions (TCMD-T) without clearly linking each component distribution to an explicit FGM. In order to improve the physical meaning of mixture distributions in seasonal snow-covered areas, the ratio of rainfall to flood volume (referred to as rainfall\u2013flood ratio, RF) method was used to classify distinct FGMs. Thus, the weighting coefficient of each component distribution was determined in advance in the rainfall\u2013flood ratio based TCMD (TCMD-RF). TCMD-RF model was applied to 34 basins in Norway. The results showed that flood types can be clearly divided into rain-on-snow-induced flood, snowmelt-induced flood and rainfall-induced flood. Moreover, the design flood and associated uncertainties were also estimated. It is found that TCMD-RF model can reduce the uncertainties of design flood by 20% compared with TCMD-T. The superiority of TCMD-RF is attributed to its clear classification of FGMs, thus determining the weighting coefficients without optimization and simplifying the parameter estimation procedure of mixture distributions.<\/jats:p>","DOI":"10.3390\/rs15020401","type":"journal-article","created":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T10:57:14Z","timestamp":1673261834000},"page":"401","source":"Crossref","is-referenced-by-count":3,"title":["Flood Frequency Analysis Using Mixture Distributions in Light of Prior Flood Type Classification in Norway"],"prefix":"10.3390","volume":"15","author":[{"given":"Lei","family":"Yan","sequence":"first","affiliation":[{"name":"State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China"},{"name":"College of Water Conservancy and Hydropower, Hebei University of Engineering, Handan 056021, China"},{"name":"Hebei Key Laboratory of Intelligent Water Conservancy, Hebei University of Engineering, Handan 056038, China"}]},{"given":"Liying","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Institute of Water Resources and Hydropower Research, Beijing 100038, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6990-2414","authenticated-orcid":false,"given":"Lihua","family":"Xiong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China"}]},{"given":"Pengtao","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Physics and Electronic Engineering, Xingtai University, Xingtai 054001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6733-959X","authenticated-orcid":false,"given":"Cong","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Environmental Studies, China University of Geosciences (Wuhan), Wuhan 430074, China"}]},{"given":"Wentao","family":"Xu","sequence":"additional","affiliation":[{"name":"Changjiang River Scientific Research Institute, Changjiang Water Resources Commission, Wuhan 430010, China"}]},{"given":"Bin","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Infrastructure Engineering, Nanchang University, Nanchang 330031, China"}]},{"given":"Kunxia","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Qiumei","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Water Resources and Hydropower Engineering, North China Electric Power University, Beijing 102206, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4826-5350","authenticated-orcid":false,"given":"Chong-Yu","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Geosciences, University of Oslo, N-0315 Oslo, Norway"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e1353","DOI":"10.1002\/wat2.1353","article-title":"Causative classification of river flood events","volume":"6","author":"Tarasova","year":"2019","journal-title":"Wiley Interdisc. 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