Detailed overview of the multimodel multiproduct streamflow forecasting platform

References

• Aghakouchak A, Habib E. 2010. Application of a conceptual hydrologic model in teaching hydrologic processes. Int J Eng Educ. 26(4):1–11.
   Web of Science ®Google Scholar
• Boyle DP, Gupta HV, Sorooshian S. 2000. Toward improved calibration of hydrologic models: combining the strengths of manual and automatic methods. Water Resour Res. 36(12):3663–3674. doi:10.1029/2000WR900207.
   Web of Science ®Google Scholar
• Duan QY, Gupta VK, Sorooshian S. 1993. Shuffled complex evolution approach for effective and efficient global minimization. J Optim Theory Appl. 76(3):501–521. doi: 10.1007/BF00939380
   Web of Science ®Google Scholar
• Duan Q, Sorooshian S, Gupta V. 1992. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour Res. 28(4):1015–1031. doi:10.1029/91WR02985.
   Web of Science ®Google Scholar
• Funk C, Peterson P, Landsfeld M, Pedreros D, Verdin J, Shukla S, Husak G, Rowland J, Harrison L, Hoell A, Michaelsen J. 2015. The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Sci Data. 2:150066. doi:10.1038/sdata.2015.66.
   PubMed Web of Science ®Google Scholar
• Hong Y, Hsu K-L, Sorooshian S, Gao X. 2004. Precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system. J Appl Meteorol. 43(12):1834–1853. doi:10.1175/JAM2173.1.
   Google Scholar
• Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Hong Y, Bowman KP, Stocker EF. 2007. The TRMM Multisatellite Precipitation Analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol. 8(1):38–55. doi:10.1175/JHM560.1.
   Web of Science ®Google Scholar
• Joyce RJ, Janowiak JE, Arkin Pa, Xie P. 2004. CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeorol. 5(3):487–503. doi:10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2.
   Web of Science ®Google Scholar
• Liang X, Lettenmaier DP, Wood EF, Burges SJ. 1994. A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res. 99(D7):14415. doi:10.1029/94JD00483.
   Web of Science ®Google Scholar
• Lohmann D, Nolte-Holube R, Raschke E. 1996. A large-scale horizontal routing model to be coupled to land surface parametrization schemes. Tellus A. 48(5):708–721. doi:10.1034/j.1600-0870.1996.t01-3-00009.x. doi: 10.3402/tellusa.v48i5.12200
   Google Scholar
• Lohmann D, Raschke E, Nijssen B, Lettenmaier DP. 1998. Regional scale hydrology: I. Formulation of the VIC-2L model coupled to a routing model. Hydrol Sci J. 43(1):131–141. doi:10.1080/02626669809492107.
   Web of Science ®Google Scholar
• Mati BM, Mutie S, Home P, Mtalo F, Gadain H. 2005. Land use changes in the transboundary mara basin: a threat to pristine wildlife sanctuaries in East Africa. In A Paper presentation at the: 8th International River Symposium, Brisbane, Australia. In: 8th International River Symposium, Brisbane, Australia, p. 6–9. [online]. http://vicres.net/downloads/LandUseChanges.pdf.
   Google Scholar
• McClain ME, Subalusky AL, Anderson EP, Dessu SB, Melesse AM, Ndomba PM, Mtamba JOD, Tamatamah RA, Mligo C. 2014. Comparing flow regime, channel hydraulics, and biological communities to infer flow–ecology relationships in the Mara River of Kenya and Tanzania. Hydrol Sci J. 59(3–4):801–819. doi:10.1080/02626667.2013.853121.
   Web of Science ®Google Scholar
• Moore RJ. 1985. The probability-distributed principle and runoff production at point and basin scales. Hydrol Sci J. 30(2):273–297. doi:10.1080/02626668509490989.
   Web of Science ®Google Scholar
• Roy T, Serrat-Capdevila A, Gupta H, Valdes J. 2017a. A platform for probabilistic multimodel and multiproduct streamflow forecasting. Water Resour Res. 53(1):376–399. doi:10.1002/2016WR019752.
   Web of Science ®Google Scholar
• Roy T, Serrat-Capdevila A, Valdes J, Durcik M, Gupta H. 2017b. Design and implementation of an operational multimodel multiproduct real-time probabilistic streamflow forecasting platform. J Hydroinformatics. 19(6):911–919. doi:10.2166/hydro.2017.111.
   Web of Science ®Google Scholar
• Roy T, Valdés JB, Lyon B, Demaria EMC, Serrat-Capdevila A, Gupta HV, Valdés-Pineda R, Durcik M. 2018. Assessing hydrological impacts of short-term climate change in the Mara River basin of East Africa. J Hydrol. 566:818–829. doi:10.1016/j.jhydrol.2018.08.051.
   Web of Science ®Google Scholar
• Valdés-Pineda R, Valdés JB, Serrat A, Wi S, Roy T. 2020. Spatio-temporal constraints for operational hydrologic forecasting: the role of lead time and catchment size.
   Google Scholar