Tirthankar Roy, J. Valdes, A. Serrat-Capdevila, M. Durcik, E. Demaria, R. Valdés-Pineda, H. Gupta
{"title":"详细介绍了多模型多产品流量预报平台","authors":"Tirthankar Roy, J. Valdes, A. Serrat-Capdevila, M. Durcik, E. Demaria, R. Valdés-Pineda, H. Gupta","doi":"10.1080/23249676.2020.1799442","DOIUrl":null,"url":null,"abstract":"We present a detailed overview of the Multi-model Multi-product Streamflow Forecasting (MMSF) Platform, which has been developed recently at the University of Arizona under the NASA SERVIR Program, to ease its operational implementation. The platform is based on the use of multiple hydrologic models, satellite-based precipitation products, advanced bias correction schemes, model calibration, and probabilistic model averaging, with the goal of improving forecast accuracy and better-characterizing forecast uncertainties, especially in poorly gauged basins. This paper includes a brief description of the platform, followed by all the relevant information a user would need to implement the platform on any new river basin.","PeriodicalId":51911,"journal":{"name":"Journal of Applied Water Engineering and Research","volume":"8 1","pages":"277 - 289"},"PeriodicalIF":1.4000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23249676.2020.1799442","citationCount":"6","resultStr":"{\"title\":\"Detailed overview of the multimodel multiproduct streamflow forecasting platform\",\"authors\":\"Tirthankar Roy, J. Valdes, A. Serrat-Capdevila, M. Durcik, E. Demaria, R. Valdés-Pineda, H. Gupta\",\"doi\":\"10.1080/23249676.2020.1799442\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a detailed overview of the Multi-model Multi-product Streamflow Forecasting (MMSF) Platform, which has been developed recently at the University of Arizona under the NASA SERVIR Program, to ease its operational implementation. The platform is based on the use of multiple hydrologic models, satellite-based precipitation products, advanced bias correction schemes, model calibration, and probabilistic model averaging, with the goal of improving forecast accuracy and better-characterizing forecast uncertainties, especially in poorly gauged basins. This paper includes a brief description of the platform, followed by all the relevant information a user would need to implement the platform on any new river basin.\",\"PeriodicalId\":51911,\"journal\":{\"name\":\"Journal of Applied Water Engineering and Research\",\"volume\":\"8 1\",\"pages\":\"277 - 289\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/23249676.2020.1799442\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Water Engineering and Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23249676.2020.1799442\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Water Engineering and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23249676.2020.1799442","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"WATER RESOURCES","Score":null,"Total":0}
Detailed overview of the multimodel multiproduct streamflow forecasting platform
We present a detailed overview of the Multi-model Multi-product Streamflow Forecasting (MMSF) Platform, which has been developed recently at the University of Arizona under the NASA SERVIR Program, to ease its operational implementation. The platform is based on the use of multiple hydrologic models, satellite-based precipitation products, advanced bias correction schemes, model calibration, and probabilistic model averaging, with the goal of improving forecast accuracy and better-characterizing forecast uncertainties, especially in poorly gauged basins. This paper includes a brief description of the platform, followed by all the relevant information a user would need to implement the platform on any new river basin.
期刊介绍:
JAWER’s paradigm-changing (online only) articles provide directly applicable solutions to water engineering problems within the whole hydrosphere (rivers, lakes groundwater, estuaries, coastal and marine waters) covering areas such as: integrated water resources management and catchment hydraulics hydraulic machinery and structures hydraulics applied to water supply, treatment and drainage systems (including outfalls) water quality, security and governance in an engineering context environmental monitoring maritime hydraulics ecohydraulics flood risk modelling and management water related hazards desalination and re-use.