Detailed overview of the multimodel multiproduct streamflow forecasting platform

Tirthankar Roy, Juan B. Valdés, Aleix Serrat-Capdevila, Matej Durcik, Eleonora M.C. Demaria, Rodrigo Valdés-Pineda, Hoshin V. Gupta

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)277-289
Number of pages13
JournalJournal of Applied Water Engineering and Research
Issue number4
StatePublished - Dec 2020


  • MMSF platform
  • operational forecasting
  • satellite precipitation
  • streamflow forecasting
  • streamflow monitoring

ASJC Scopus subject areas

  • Water Science and Technology


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