Coucheney, Elsa
- Department of Soil and Environment, Swedish University of Agricultural Sciences
Research article2017Peer reviewedOpen access
The implication of input data aggregation on up-scaling soil organic carbon changes
Grosz, Balazs; Dechow, Rene; Gebbert, Soeren; Hoffmann, Holger; Zhao, Gang; Constantin, Julie; Raynal, Helene; Wallach, Daniel; Coucheney, Elsa; Lewan, Elisabet; Eckersten, Henrik; Specka, Xenia; Kersebaum, Kurt-Christian; Nendel, Claas; Kuhnert, Matthias; Yeluripati, Jagadeesh; Haas, Edwin; Teixeira, Edmar; Bindi, Marco; Trombi, Giacomo;
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Abstract
In up-scaling studies, model input data aggregation is a common method to cope with deficient data availability and limit the computational effort. We analyzed model errors due to soil data aggregation for modeled SOC trends. For a region in North West Germany, gridded soil data of spatial resolutions between 1 km and 100 km has been derived by majority selection. This data was used to simulate changes in SOC for a period of 30 years by 7 biogeochemical models. Soil data aggregation strongly affected modeled SOC trends. Prediction errors of simulated SOC changes decreased with increasing spatial resolution of model output. Output data aggregation only marginally reduced differences of model outputs between models indicating that errors caused by deficient model structure are likely to persist even if requirements on the spatial resolution of model outputs are low. (C)2017 Elsevier Ltd. All rights reserved.
Keywords
Biogeochemical model; Data aggregation; Up-scaling error; Soil organic carbon
Published in
Environmental Modelling and Software
2017, volume: 96, pages: 361-377
SLU Authors
Lewan, Elisabet
- Department of Soil and Environment, Swedish University of Agricultural Sciences
- Department of Soil and Environment, Swedish University of Agricultural Sciences
Eckersten, Henrik
- Department of Crop Production Ecology, Swedish University of Agricultural Sciences
- Department of Crop Production Ecology, Swedish University of Agricultural Sciences
UKÄ Subject classification
Environmental Sciences
Publication identifier
- DOI: https://doi.org/10.1016/j.envsoft.2017.06.046
Permanent link to this page (URI)
https://res.slu.se/id/publ/85146