Improving the simulation of soil temperature within the EPIC model
2021
Doro, Luca | Wang, Xiuying | Ammann, Christof | de Antoni Migliorati, Massimiliano | Grünwald, Thomas | Klumpp, Katja | Loubet, Benjamin | Pattey, Elizabeth | Wohlfahrt, Georg | Williams, Jimmy | Norfleet, M. Lee | Blackland Research & Extension Center ; Texas A&M University System | Agroscope FAL Reckenholz (AGROSCOPE) ; Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich) | Dept. of Environmental Sciences | Technische Universität Dresden = Dresden University of Technology (TU Dresden) | Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP) ; VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Université Clermont Auvergne (UCA) | Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS) | Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS) ; AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | Ottawa Research and Development Centre ; Agriculture and Agri-Food (AAFC) | Universität Innsbruck [Innsbruck] = University of Innsbruck | ANR-11-INBS-0001,ANAEE-FR,ANAEE-Services(2011)
International audience
Show more [+] Less [-]English. Soil temperature is a key driver of several physical, chemical, and biological processes. The Environmental Policy Integrated Climate (EPIC) is a comprehensive ecosystem model that simulates soil temperature dynamics using a cosine function approach driven by daily air temperature and average annual soil temperature at damping depth,which may erroneously predict lower soil temperatures in winter. A new cosine model and a pseudo-heat-transfer model were therefore developed and implemented for simulating soil temperature. The two methods were evaluated by comparing simulated daily soil temperatures with observed data at 24 study sites. Results showed that the two new methods had similar performance and the better statistical results obtained with these new methods demonstrated the ability to better predict the soil temperature for a wide range of pedoclimatic conditions, land management, and land uses. The main reason for the improved performance was due to a better prediction of soil temperature during the winter period.
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