Vote for your favorite mineral in #MinCup25! - Cuprosklodowskite vs. Ikaite
It's radioactive #cuprosklodowskite vs ephemeral #ikaite for today's match.
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Zhang, Xiaojing, Liu, Pan, Cheng, Lei, Liu, Zhangjun, Zhao, Yan (2018) A back-fitting algorithm to improve real-time flood forecasting. Journal of Hydrology, 562. 140-150 doi:10.1016/j.jhydrol.2018.04.051

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleA back-fitting algorithm to improve real-time flood forecasting
JournalJournal of Hydrology
AuthorsZhang, XiaojingAuthor
Liu, PanAuthor
Cheng, LeiAuthor
Liu, ZhangjunAuthor
Zhao, YanAuthor
Year2018 (July)Volume562
PublisherElsevier BV
DOIdoi:10.1016/j.jhydrol.2018.04.051Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID7245862Long-form Identifiermindat:1:5:7245862:4
GUID0
Full ReferenceZhang, Xiaojing, Liu, Pan, Cheng, Lei, Liu, Zhangjun, Zhao, Yan (2018) A back-fitting algorithm to improve real-time flood forecasting. Journal of Hydrology, 562. 140-150 doi:10.1016/j.jhydrol.2018.04.051
Plain TextZhang, Xiaojing, Liu, Pan, Cheng, Lei, Liu, Zhangjun, Zhao, Yan (2018) A back-fitting algorithm to improve real-time flood forecasting. Journal of Hydrology, 562. 140-150 doi:10.1016/j.jhydrol.2018.04.051
In(2018) Journal of Hydrology Vol. 562. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Zhang, Xiaojing, Liu, Pan, Cheng, Lei, Zhou, Liting, Liu, Weibo, Luo, Xinran (2024) Time-varying parameters from the same period in previous years to improve runoff forecasting. Journal of Hydrology, 631. 130685 doi:10.1016/j.jhydrol.2024.130685
Zhang, Xiaoqi, Liu, Pan, Xu, Chong-Yu, Gong, Yu, Cheng, Lei, He, Shaokun (2019) Real-time reservoir flood control operation for cascade reservoirs using a two-stage flood risk analysis method. Journal of Hydrology, 577. 123954pp. doi:10.1016/j.jhydrol.2019.123954
Xiong, Mengsi, Liu, Pan, Cheng, Lei, Deng, Chao, Gui, Ziling, Zhang, Xiaojing, Liu, Yanghe (2019) Identifying time-varying hydrological model parameters to improve simulation efficiency by the ensemble Kalman filter: A joint assimilation of streamflow and actual evapotranspiration. Journal of Hydrology, 568. 758-768 doi:10.1016/j.jhydrol.2018.11.038
Zhang, Jingwen, Cai, Ximing, Lei, Xiaohui, Liu, Pan, Wang, Hao (2021) Real-time reservoir flood control operation enhanced by data assimilation. Journal of Hydrology, 598. 126426pp. doi:10.1016/j.jhydrol.2021.126426
Zhou, Liting, Liu, Pan, Gui, Ziling, Zhang, Xiaojing, Liu, Weibo, Cheng, Lei, Xia, Jun (2022) Diagnosing structural deficiencies of a hydrological model by time-varying parameters. Journal of Hydrology, 605. 127305pp. doi:10.1016/j.jhydrol.2021.127305
Pan, Zhengke, Liu, Pan, Gao, Shida, Cheng, Lei, Chen, Jie, Zhang, Xiaojing (2019) Reducing the uncertainty of time-varying hydrological model parameters using spatial coherence within a hierarchical Bayesian framework. Journal of Hydrology, 577. 123927pp. doi:10.1016/j.jhydrol.2019.123927
Zhou, Liting, Liu, Pan, Zhang, Xiaojing, Cheng, Lei, Xia, Qian, Xie, Kang, Liu, Weibo, Xia, Jun (2023) Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework. Journal of Hydrology, 616. 128843 doi:10.1016/j.jhydrol.2022.128843
Liu, Pan, Zhang, Xiaojing, Zhao, Yan, Deng, Chao, Li, Zejun, Xiong, Mengsi (2019) Improving efficiencies of flood forecasting during lead times: an operational method and its application in the Baiyunshan Reservoir. Hydrology Research, 50 (2). 709-724 doi:10.2166/nh.2018.051
Barbetta, Silvia, Coccia, Gabriele, Moramarco, Tommaso, Todini, Ezio (2018) Real-time flood forecasting downstream river confluences using a Bayesian approach. Journal of Hydrology, 565. 516-523 doi:10.1016/j.jhydrol.2018.08.043
Biondi, D., De Luca, D.L. (2013) Performance assessment of a Bayesian Forecasting System (BFS) for real-time flood forecasting. Journal of Hydrology, 479. 51-63 doi:10.1016/j.jhydrol.2012.11.019
Yin, Jiabo, Guo, Shenglian, He, Shaokun, Guo, Jiali, Hong, Xingjun, Liu, Zhangjun (2018) A copula-based analysis of projected climate changes to bivariate flood quantiles. Journal of Hydrology, 566. 23-42 doi:10.1016/j.jhydrol.2018.08.053
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are Β© OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 14, 2025 11:13:11
Go to top of page