Articles | Volume 45
https://doi.org/10.5194/adgeo-45-147-2018
https://doi.org/10.5194/adgeo-45-147-2018
17 Aug 2018
 | 17 Aug 2018

Large-scale assessment of Prophet for multi-step ahead forecasting of monthly streamflow

Hristos Tyralis and Georgia A. Papacharalampous

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Cited articles

Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: Catchment attributes for large-sample studies, UCAR/NCAR, Boulder, CO, https://doi.org/10.5065/D6G73C3Q, 2017a. 
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017b. 
Allaire, J. J., Xie, Y., McPherson, J., Luraschi, J., Ushey, K., Atkins, A., Wickham, H., Cheng, J., and Chang, W.: rmarkdown: Dynamic Documents for R, R package version 1.9, available at: https://CRAN.R-project.org/package=rmarkdown (last access: 15 August 2018), 2018. 
Ballini, R., Soares, S., and Andrade, M. G.: Multi-step-ahead monthly streamflow forecasting by a neurofuzzy network model, IFSA World Congress and 20th NAFIPS International Conference, 992–997, https://doi.org/10.1109/NAFIPS.2001.944740, 2001. 
Brownrigg, R., Minka, T. P., and Deckmyn, A.: maps: Draw Geographical Maps, R package version 3.3.0, available at: https://CRAN.R-project.org/package=maps (last access: 15 August 2018), 2018. 
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Short summary
We use the CAMELS dataset to compare two different approaches in multi-step ahead forecasting of monthly streamflow. The first approach uses past monthly streamflow information only, while the second approach additionally uses past information about monthly precipitation and/or temperature (exogenous information). The incorporation of exogenous information is made by utilizing Prophet, a model largely implemented in Facebook. The findings suggest that the compared approaches are equally useful.