84166 20210507081948.0 doi 10.1007/s11269-018-2114-2 sideral 108321 ART-2018-108321 eng Cebrián, A.C. Universidad de Zaragoza (orcid)0000-0002-9052-9674 Dynamic regression model for hourly river level forecasting under risk situations: An application to the Ebro River 2018 Access copy available to the general public Unrestricted This work proposes a new statistical modelling approach to forecast the hourly river level at a gauging station, under potential flood risk situations and over a medium-term prediction horizon (around three days). For that aim we introduce a new model, the switching regression model with ARMA errors, which takes into account the serial correlation structure of the hourly level series, and the changing time delay between them. A whole modelling approach is developed, including a two-step estimation, which improves the medium-term prediction performance of the model, and uncertainty measures of the predictions. The proposed model not only provides predictions for longer periods than other statistical models, but also helps to understand the physics of the river, by characterizing the relationship between the river level in a gauging station and its influential factors. This approach is applied to forecast the Ebro River level at Zaragoza (Spain), using as input the series at Tudela. The approach has shown to be useful and the resulting model provides satisfactory hourly predictions, which can be fast and easily updated, together with their confidence intervals. The fitted model outperforms the predictions from other statistical and numerical models, specially in long prediction horizons. info:eu-repo/grantAgreement/ES/DGA/E22 info:eu-repo/grantAgreement/ES/MICINN/MTM2017-83812-P info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 2.987 2018 WATER RESOURCES 18 / 91 = 0.198 2018 Q1 T1 ENGINEERING, CIVIL 24 / 132 = 0.182 2018 Q1 T1 1.097 2018 Water Science and Technology 2018 Q1 Civil and Structural Engineering 2018 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Abaurrea, J. Universidad de Zaragoza (orcid)0000-0002-7974-7435 Asín, J. Universidad de Zaragoza (orcid)0000-0002-0174-789X Segarra, E. 2007 265 Universidad de Zaragoza Dpto. Métodos Estadísticos Área Estadís. Investig. Opera. 33, 2 (2018), 523–537 Water resour. manag. WATER RESOURCES MANAGEMENT 0920-4741 2084558 http://zaguan.unizar.es/record/84166/files/texto_completo.pdf Postprint 54301 http://zaguan.unizar.es/record/84166/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:84166 articulos driver 2021-05-07-08:11:15 ARTICLE