Integration of ground and satellite data to model Mediterranean forest processes
Title | Integration of ground and satellite data to model Mediterranean forest processes |
Publication Type | Journal Article |
Year of Publication | 2011 |
Authors | Chiesi, M., Fibbi L., Genesio L., Gioli B., Magno R., Maselli F., Moriondo M., & Vaccari F. P. |
Journal | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION |
Volume | 13 |
Issue | 3 |
Pagination | 504 - 515 |
Date Published | 2011/// |
Keywords | BIOME-BGC, C-Fix, ET, GPP, mediterranean forest, NEE |
Abstract | The current work presents the testing of a modeling strategy that has been recently developed to simulate the gross and net carbon fluxes of Mediterranean forest ecosystems. The strategy is based on the use of a NDVI-driven parametric model, C-Fix, and of a biogeochemical model, BIOME-BGC, whose outputs are combined to simulate the behavior of forest ecosystems at different development stages. The performances of the modeling strategy are evaluated in three Italian study sites (San Rossore, Lecceto and Pianosa), where carbon fluxes are being measured through the eddy correlation technique. These sites are characterized by variable Mediterranean climates and are covered by different types of forest vegetation (pine wood, Holm oak forest and Macchia, respectively). The results of the tests indicate that the modeling strategy is generally capable of reproducing monthly GPP and NEE patterns in all three study sites. The highest accuracy is obtained in the most mature, homogenous pine wood of San Rossore, while the worst results are found in the Lecceto forest, where there are the most heterogeneous terrain, soil and vegetation conditions. The main error sources are identified in the inaccurate definition of the model inputs, particularly those regulating the site water budgets, which exert a strong control on forest productivity during the Mediterranean summer dry season. In general, the incorporation of NDVI-derived fAPAR estimates corrects for most of these errors and renders the forest flux simulations more stable and accurate. (C) 2010 Elsevier B.V. All rights reserved. |