The implication of input data aggregation on up-scaling soil organic carbon changes

Balazs Grosz*, Rene Dechow, Soeren Gebbert, Holger Hoffmann, Gang Zhao, Julie Constantin, Helene Raynal, Daniel Wallach, Elsa Coucheney, Elisabet Lewan, Henrik Eckersten, Xenia Specka, Kurt-Christian Kersebaum, Claas Nendel, Matthias Kuhnert, Jagadeesh Yeluripati, Edwin Haas, Edmar Teixeira, Marco Bindi, Giacomo TrombiMarco Moriondo, Luca Doro, Pier Paolo Roggero, Zhigan Zhao, Enli Wang, Fulu Tao, Reimund Roetter, Belay Kassie, Davide Cammarano, Senthold Asseng, Lutz Weihermueller, Stefan Siebert, Thomas Gaiser, Frank Ewert

*Corresponding author for this work

Research output: Contribution to journalArticle

15 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)361-377
Number of pages17
JournalEnvironmental Modelling and Software
Volume96
Early online date1 Aug 2017
DOIs
Publication statusPublished - Oct 2017

Keywords

  • Biogeochemical model
  • Data aggregation
  • Up-scaling error
  • Soil organic carbon
  • DIFFERENT SPATIAL SCALES
  • NITROUS-OXIDE EMISSIONS
  • MODELING SYSTEM
  • DATA RESOLUTION
  • CROP MODELS
  • CLIMATE
  • LONG
  • PRODUCTIVITY
  • CROPLANDS
  • DAYCENT

Cite this

Grosz, B., Dechow, R., Gebbert, S., Hoffmann, H., Zhao, G., Constantin, J., Raynal, H., Wallach, D., Coucheney, E., Lewan, E., Eckersten, H., Specka, X., Kersebaum, K-C., Nendel, C., Kuhnert, M., Yeluripati, J., Haas, E., Teixeira, E., Bindi, M., ... Ewert, F. (2017). The implication of input data aggregation on up-scaling soil organic carbon changes. Environmental Modelling and Software, 96, 361-377. https://doi.org/10.1016/j.envsoft.2017.06.046