Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches

• DOI: 10.1002/hyp.10913
• Publication Date: 2016-05-07T15:06:20Z
• Authors: Sebastiano Piccol...; Elisa Calamita; Bruno Majone; Aurélien Gallice; Annunziato Siviglia; Marco Toffolon
• Keywords: hydrological regime; thermal regime; thermal response; 0207 environmental engineering; 02 engineering and technology; stream temperature; statistical models; hybrid models; air temperature; 13. Climate action; thermal regime; heat budget; hybrid models; thermal response; hydrological regime; air temperature; stream temperature; statistical models; heat budget

Abstract River water temperature is a key physical variable controlling several chemical, biological and ecological processes. Its reliable prediction main issue in many environmental applications, which however hampered by data scarcity, when using data‐demanding deterministic models, modelling limitations, simpler statistical models. In this work we test suite of models belonging to air2stream family, are characterized hybrid formulation that combines derivation the equation with stochastic calibration parameters. The rely solely on air streamflow, similar complexity as standard performances different versions predicting river compared those most common typically used literature. To aim, dataset 38 Swiss rivers used, includes classified into four categories according their hydrological characteristics: low‐land natural rivers, lake outlets, snow‐fed regulated rivers. results analysis provide practical indications regarding type model suitable simulate across time scales (from daily seasonal) for regimes. A intercomparison exercise suggests family generally outperforms while cross‐validation conducted over 30‐year period indicates they can be suitably adopted long‐term analyses. Copyright © 2016 John Wiley & Sons, Ltd.