Journal article

Rejecting hydro-biogeochemical model structures by multi-criteria evaluation


Authors listHouska, T; Kraft, R; Liebermann, R; Klatt, S; Kraus, D; Haas, E; Santabarbara, I; Kiese, R; Butterbach-Bahl, K; Müller, C; Breuer, L

Publication year2017

Pages1-12

JournalEnvironmental Modelling and Software

Volume number93

ISSN1364-8152

DOI Linkhttps://doi.org/10.1016/j.envsoft.2017.03.005

PublisherElsevier


Abstract
This work presents a novel way for assessing and comparing different hydro-biogeochemical model structures and their performances. We used the LandscapeDNDC modelling framework to set up four models of different complexity, considering two soil-biogeochemical and two hydrological modules. The performance of each model combination was assessed using long-term (8 years) data and applying different thresholds, considering multiple criteria and objective functions. Our results show that each model combination had its strength for particular criteria. However, only 0.01% of all model runs passed the complete rejectionist framework. In contrast, our comparatively applied assessments of single thresholds, as frequently used in other studies, lead to a much higher acceptance rate of 40-70%. Therefore, our study indicates that models can be right for the wrong reasons, i.e., matching GHG emissions while at the same time failing to simulate other criteria such as soil moisture or plant biomass dynamics. (C) 2017 Elsevier Ltd. All rights reserved.



Citation Styles

Harvard Citation styleHouska, T., Kraft, R., Liebermann, R., Klatt, S., Kraus, D., Haas, E., et al. (2017) Rejecting hydro-biogeochemical model structures by multi-criteria evaluation, Environmental Modelling and Software, 93, pp. 1-12. https://doi.org/10.1016/j.envsoft.2017.03.005

APA Citation styleHouska, T., Kraft, R., Liebermann, R., Klatt, S., Kraus, D., Haas, E., Santabarbara, I., Kiese, R., Butterbach-Bahl, K., Müller, C., & Breuer, L. (2017). Rejecting hydro-biogeochemical model structures by multi-criteria evaluation. Environmental Modelling and Software. 93, 1-12. https://doi.org/10.1016/j.envsoft.2017.03.005


Last updated on 2025-21-05 at 15:30