Articles | Volume 7, issue 10
https://doi.org/10.5194/bg-7-3311-2010
https://doi.org/10.5194/bg-7-3311-2010
27 Oct 2010
 | 27 Oct 2010

The use of machine learning algorithms to design a generalized simplified denitrification model

F. Oehler, J. C. Rutherford, and G. Coco

Related subject area

Biogeochemistry: Air - Land Exchange
Monitoring cropland daily carbon dioxide exchange at field scales with Sentinel-2 satellite imagery
Pia Gottschalk, Aram Kalhori, Zhan Li, Christian Wille, and Torsten Sachs
Biogeosciences, 21, 3593–3616, https://doi.org/10.5194/bg-21-3593-2024,https://doi.org/10.5194/bg-21-3593-2024, 2024
Short summary
Compound soil and atmospheric drought (CSAD) events and CO2 fluxes of a mixed deciduous forest: the occurrence, impact, and temporal contribution of main drivers
Liliana Scapucci, Ankit Shekhar, Sergio Aranda-Barranco, Anastasiia Bolshakova, Lukas Hörtnagl, Mana Gharun, and Nina Buchmann
Biogeosciences, 21, 3571–3592, https://doi.org/10.5194/bg-21-3571-2024,https://doi.org/10.5194/bg-21-3571-2024, 2024
Short summary
The influence of plant water stress on vegetation–atmosphere exchanges: implications for ozone modelling
Tamara Emmerichs, Yen-Sen Lu, and Domenico Taraborrelli
Biogeosciences, 21, 3251–3269, https://doi.org/10.5194/bg-21-3251-2024,https://doi.org/10.5194/bg-21-3251-2024, 2024
Short summary
High interspecific variability in ice nucleation activity suggests pollen ice nucleators are incidental
Nina L. H. Kinney, Charles A. Hepburn, Matthew I. Gibson, Daniel Ballesteros, and Thomas F. Whale
Biogeosciences, 21, 3201–3214, https://doi.org/10.5194/bg-21-3201-2024,https://doi.org/10.5194/bg-21-3201-2024, 2024
Short summary
Using automated machine learning for the upscaling of gross primary productivity
Max Gaber, Yanghui Kang, Guy Schurgers, and Trevor Keenan
Biogeosciences, 21, 2447–2472, https://doi.org/10.5194/bg-21-2447-2024,https://doi.org/10.5194/bg-21-2447-2024, 2024
Short summary

Cited articles

Alpaydin, E.: Introduction to Machine Learning (Adaptive Computation and Machine Learning), The MIT Press, 2004.
Arnold, J. G. and Fohrer, N.: SWAT2000: current capabilities and research opportunities in applied watershed modelling, Hydrol. Process., 19, 563–572, 2005.
Basset-Mens, C., Anibar, L., Durand, P., and van der Werf, H. M. G.: Spatialised fate factors for nitrate in catchments: Modelling approach and implication for LCA results, Sci. Total Environ., 367, 367–382, 2006.
Beaujouan, V., Durand, P., and Ruiz, L.: Modelling the effect of the spatial distribution of agricultural practices on nitrogen fluxes in rural catchments, Ecol. Model., 137, 93–105, 2001.
Beven, K.: Prophecy, Reality and Uncertainty in Distributed Hydrological Modeling, Adv. Water Resour., 16, 41–51, 1993.
Download
Altmetrics
Final-revised paper
Preprint