Articles | Volume 12, issue 6
https://doi.org/10.5194/gmd-12-2419-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-12-2419-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
19 Jun 2019
Model description paper |
| 19 Jun 2019
| 19 Jun 2019
Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage)
Potsdam Institute for Climate Impact Research (PIK), member of the
Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Wageningen University, Soil Geography and Landscape Group, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Tobias Herzfeld
Potsdam Institute for Climate Impact Research (PIK), member of the
Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Jens Heinke
Potsdam Institute for Climate Impact Research (PIK), member of the
Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Susanne Rolinski
Potsdam Institute for Climate Impact Research (PIK), member of the
Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Sibyll Schaphoff
Potsdam Institute for Climate Impact Research (PIK), member of the
Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Werner von Bloh
Potsdam Institute for Climate Impact Research (PIK), member of the
Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
Jetse J. Stoorvogel
Wageningen University, Soil Geography and Landscape Group, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Christoph Müller
Potsdam Institute for Climate Impact Research (PIK), member of the
Leibniz Association, P.O. Box 60 12 03, 14412 Potsdam, Germany
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Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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Elena Xoplaki, Florian Ellsäßer, Jens Grieger, Katrin M. Nissen, Joaquim G. Pinto, Markus Augenstein, Ting-Chen Chen, Hendrik Feldmann, Petra Friederichs, Daniel Gliksman, Laura Goulier, Karsten Haustein, Jens Heinke, Lisa Jach, Florian Knutzen, Stefan Kollet, Jürg Luterbacher, Niklas Luther, Susanna Mohr, Christoph Mudersbach, Christoph Müller, Efi Rousi, Felix Simon, Laura Suarez-Gutierrez, Svenja Szemkus, Sara M. Vallejo-Bernal, Odysseas Vlachopoulos, and Frederik Wolf
Nat. Hazards Earth Syst. Sci., 25, 541–564, https://doi.org/10.5194/nhess-25-541-2025, https://doi.org/10.5194/nhess-25-541-2025, 2025
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Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.
Stephen Björn Wirth, Johanna Braun, Jens Heinke, Sebastian Ostberg, Susanne Rolinski, Sibyll Schaphoff, Fabian Stenzel, Werner von Bloh, Friedhelm Taube, and Christoph Müller
Geosci. Model Dev., 17, 7889–7914, https://doi.org/10.5194/gmd-17-7889-2024, https://doi.org/10.5194/gmd-17-7889-2024, 2024
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We present a new approach to modelling biological nitrogen fixation (BNF) in the Lund–Potsdam–Jena managed Land dynamic global vegetation model. While in the original approach BNF depended on actual evapotranspiration, the new approach considers soil water content and temperature, vertical root distribution, the nitrogen (N) deficit and carbon (C) costs. The new approach improved simulated BNF compared to the scientific literature and the model ability to project future C and N cycle dynamics.
Felix Jäger, Jonas Schwaab, Yann Quilcaille, Michael Windisch, Jonathan Doelman, Stefan Frank, Mykola Gusti, Petr Havlik, Florian Humpenöder, Andrey Lessa Derci Augustynczik, Christoph Müller, Kanishka Balu Narayan, Ryan Sebastian Padrón, Alexander Popp, Detlef van Vuuren, Michael Wögerer, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 15, 1055–1071, https://doi.org/10.5194/esd-15-1055-2024, https://doi.org/10.5194/esd-15-1055-2024, 2024
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Climate change mitigation strategies developed with socioeconomic models rely on the widespread (re)planting of trees to limit global warming below 2°. However, most of these models neglect climate-driven shifts in forest damage like fires. By assessing existing mitigation scenarios, we show the exposure of projected forestation areas to fire-promoting weather conditions. Our study highlights the problem of ignoring climate-driven shifts in forest damage and ways to address it.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Markus Drüke, Wolfgang Lucht, Werner von Bloh, Stefan Petri, Boris Sakschewski, Arne Tobian, Sina Loriani, Sibyll Schaphoff, Georg Feulner, and Kirsten Thonicke
Earth Syst. Dynam., 15, 467–483, https://doi.org/10.5194/esd-15-467-2024, https://doi.org/10.5194/esd-15-467-2024, 2024
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The planetary boundary framework characterizes major risks of destabilization of the Earth system. We use the comprehensive Earth system model POEM to study the impact of the interacting boundaries for climate change and land system change. Our study shows the importance of long-term effects on carbon dynamics and climate, as well as the need to investigate both boundaries simultaneously and to generally keep both boundaries within acceptable ranges to avoid a catastrophic scenario for humanity.
Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, Sibyll Schaphoff, Werner von Bloh, and Susanne Rolinski
Biogeosciences, 21, 381–410, https://doi.org/10.5194/bg-21-381-2024, https://doi.org/10.5194/bg-21-381-2024, 2024
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In dynamic global vegetation models (DGVMs), the role of functional diversity in forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the Lund Potsdam Jena managed Land (LPJmL) DGVM using CSR theory. The new model reproduced well-known trade-offs between plant traits and can be used to quantify the role of functional diversity in climate change mitigation using different functional diversity scenarios.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
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We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Sebastian Ostberg, Christoph Müller, Jens Heinke, and Sibyll Schaphoff
Geosci. Model Dev., 16, 3375–3406, https://doi.org/10.5194/gmd-16-3375-2023, https://doi.org/10.5194/gmd-16-3375-2023, 2023
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We present a new toolbox for generating input datasets for terrestrial ecosystem models from diverse and partially conflicting data sources. The toolbox documents the sources and processing of data and is designed to make inconsistencies between source datasets transparent so that users can make their own decisions on how to resolve these should they not be content with our default assumptions. As an example, we use the toolbox to create input datasets at two different spatial resolutions.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
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We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Efi Rousi, Andreas H. Fink, Lauren S. Andersen, Florian N. Becker, Goratz Beobide-Arsuaga, Marcus Breil, Giacomo Cozzi, Jens Heinke, Lisa Jach, Deborah Niermann, Dragan Petrovic, Andy Richling, Johannes Riebold, Stella Steidl, Laura Suarez-Gutierrez, Jordis S. Tradowsky, Dim Coumou, André Düsterhus, Florian Ellsäßer, Georgios Fragkoulidis, Daniel Gliksman, Dörthe Handorf, Karsten Haustein, Kai Kornhuber, Harald Kunstmann, Joaquim G. Pinto, Kirsten Warrach-Sagi, and Elena Xoplaki
Nat. Hazards Earth Syst. Sci., 23, 1699–1718, https://doi.org/10.5194/nhess-23-1699-2023, https://doi.org/10.5194/nhess-23-1699-2023, 2023
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The objective of this study was to perform a comprehensive, multi-faceted analysis of the 2018 extreme summer in terms of heat and drought in central and northern Europe, with a particular focus on Germany. A combination of favorable large-scale conditions and locally dry soils were related with the intensity and persistence of the events. We also showed that such extremes have become more likely due to anthropogenic climate change and might occur almost every year under +2 °C of global warming.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
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The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
Kristine Karstens, Benjamin Leon Bodirsky, Jan Philipp Dietrich, Marta Dondini, Jens Heinke, Matthias Kuhnert, Christoph Müller, Susanne Rolinski, Pete Smith, Isabelle Weindl, Hermann Lotze-Campen, and Alexander Popp
Biogeosciences, 19, 5125–5149, https://doi.org/10.5194/bg-19-5125-2022, https://doi.org/10.5194/bg-19-5125-2022, 2022
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Soil organic carbon (SOC) has been depleted by anthropogenic land cover change and agricultural management. While SOC models often simulate detailed biochemical processes, the management decisions are still little investigated at the global scale. We estimate that soils have lost around 26 GtC relative to a counterfactual natural state in 1975. Yet, since 1975, SOC has been increasing again by 4 GtC due to a higher productivity, recycling of crop residues and manure, and no-tillage practices.
Vera Porwollik, Susanne Rolinski, Jens Heinke, Werner von Bloh, Sibyll Schaphoff, and Christoph Müller
Biogeosciences, 19, 957–977, https://doi.org/10.5194/bg-19-957-2022, https://doi.org/10.5194/bg-19-957-2022, 2022
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The study assesses impacts of grass cover crop cultivation on cropland during main-crop off-season periods applying the global vegetation model LPJmL (V.5.0-tillage-cc). Compared to simulated bare-soil fallowing practices, cover crops led to increased soil carbon content and reduced nitrogen leaching rates on the majority of global cropland. Yield responses of main crops following cover crops vary with location, duration of altered management, crop type, water regime, and tillage practice.
Tobias Herzfeld, Jens Heinke, Susanne Rolinski, and Christoph Müller
Earth Syst. Dynam., 12, 1037–1055, https://doi.org/10.5194/esd-12-1037-2021, https://doi.org/10.5194/esd-12-1037-2021, 2021
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Soil organic carbon sequestration on cropland has been proposed as a climate change mitigation strategy. We simulate different agricultural management practices under climate change scenarios using a global biophysical model. We find that at the global aggregated level, agricultural management practices are not capable of enhancing total carbon storage in the soil, yet for some climate regions, we find that there is potential to enhance the carbon content in cropland soils.
Cited articles
Abdalla, K., Chivenge, P., Ciais, P., and Chaplot, V.: No-tillage lessens soil CO2 emissions the most under arid and sandy soil conditions: results from a meta-analysis, Biogeosciences, 13, 3619–3633, https://doi.org/10.5194/bg-13-3619-2016, 2016.
Armand, R., Bockstaller, C., Auzet, A.-V., and Van Dijk, P.: Runoff
generation related to intra-field soil surface characteristics variability:
Application to conservation tillage context, Soil Till. Res., 102,
27–37, https://doi.org/10.1016/j.still.2008.07.009, 2009.
Aslam, T., Choudhary, M. A., and Saggar, S.: Influence of land-use management
on CO2 emissions from a silt loam soil in New Zealand, Agr. Ecosyst.
Environ., 77, 257–262, https://doi.org/10.1016/S0167-8809(99)00102-4, 2000.
Balland, V., Pollacco, J. A. P., and Arp, P. A.: Modeling soil hydraulic
properties for a wide range of soil conditions, Ecol. Model., 219,
300–316, https://doi.org/10.1016/j.ecolmodel.2008.07.009, 2008.
Batjes, N.: ISRIC-WISE global data set of derived soil properties on a 0.5
by 0.5 degree grid (version 3.0), ISRIC – World Soil Information,
Wageningen, 2005.
Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., Schamm, K., Schneider, U., and Ziese, M.: A description of the global land-surface precipitation data products of the Global Precipitation Climatology Centre with sample applications including centennial (trend) analysis from 1901–present, Earth Syst. Sci. Data, 5, 71–99, https://doi.org/10.5194/essd-5-71-2013, 2013.
Bertolino, A. V. F. A., Fernandes, N. F., Miranda, J. P. L., Souza, A. P.,
Lopes, M. R. S., and Palmieri, F.: Effects of plough pan development on
surface hydrology and on soil physical properties in Southeastern Brazilian
plateau, J. Hydrol., 393, 94–104, https://doi.org/10.1016/j.jhydrol.2010.07.038,
2010.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Bondeau, A., Smith, P. C., Zaehle, S., Schaphoff, S., Lucht, W., Cramer, W.,
Gerten, D., Lotze-Campen, H., MüLler, C., Reichstein, M., and Smith, B.:
Modelling the role of agriculture for the 20th century global terrestrial
carbon balance, Glob. Change Biol., 13, 679–706,
https://doi.org/10.1111/j.1365-2486.2006.01305.x, 2007.
Brady, N. C. and Weil, R. R.: The nature and properties of soils, Pearson
Prentice Hall Upper Saddle River, 2008.
Butterbach-Bahl, K., Baggs, E. M., Dannenmann, M., Kiese, R., and
Zechmeister-Boltenstern, S.: Nitrous oxide emissions from soils: how well do
we understand the processes and their controls?, Philos. T. Roy. Soc. B, 368, 20130122,
https://doi.org/10.1098/rstb.2013.0122, 2013.
Chatskikh, D., Olesen, J. E., Hansen, E. M., Elsgaard, L., and Petersen, B.
M.: Effects of reduced tillage on net greenhouse gas fluxes from loamy sand
soil under winter crops in Denmark, Agr. Ecosyst. Environ., 128,
117–126, https://doi.org/10.1016/j.agee.2008.05.010, 2008.
Chen, H., Hou, R., Gong, Y., Li, H., Fan, M., and Kuzyakov, Y.: Effects of 11
years of conservation tillage on soil organic matter fractions in wheat
monoculture in Loess Plateau of China, Soil Till. Res., 106, 85–94,
https://doi.org/10.1016/j.still.2009.09.009, 2009.
Ciais, P., Gervois, S., Vuichard, N., Piao, S. L., and Viovy, N.: Effects of
land use change and management on the European cropland carbon balance,
Glob. Change Biol., 17, 320–338, https://doi.org/10.1111/j.1365-2486.2010.02341.x,
2011.
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A Statistical
Exploration of the Relationships of Soil Moisture Characteristics to the
Physical Properties of Soils, Water Resour. Res., 20, 682–690,
https://doi.org/10.1029/WR020i006p00682, 1984.
Daigh, A. L. M. and DeJong-Hughes, J.: Fluffy soil syndrome: When tilled
soil does not settle, J. Soil Water Conserv., 72, 10A–14A,
https://doi.org/10.2489/jswc.72.1.10A, 2017.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P.,
Bechtold, P., Beljaars, A. C. M., Berg, L. van de, Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P.,
Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M.,
Morcrette, J.-J., Park, B.-K., Peubey, C., Rosnay, P. de, Tavolato, C.,
Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration
and performance of the data assimilation system, Q. J. Roy. Meteor. Soc.,
137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Elliott, J., Müller, C., Deryng, D., Chryssanthacopoulos, J., Boote, K. J., Büchner, M., Foster, I., Glotter, M., Heinke, J., Iizumi, T., Izaurralde, R. C., Mueller, N. D., Ray, D. K., Rosenzweig, C., Ruane, A. C., and Sheffield, J.: The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0), Geosci. Model Dev., 8, 261–277, https://doi.org/10.5194/gmd-8-261-2015, 2015.
Enrique, G. S., Braud, I., Jean-Louis, T., Michel, V., Pierre, B., and
Jean-Christophe, C.: Modelling heat and water exchanges of fallow land
covered with plant-residue mulch, Agr. Forest Meteorol., 97, 151–169,
https://doi.org/10.1016/S0168-1923(99)00081-7, 1999.
Fader, M., Rost, S., Müller, C., Bondeau, A., and Gerten, D.: Virtual
water content of temperate cereals and maize: Present and potential future
patterns, J. Hydrol., 384, 218–231,
https://doi.org/10.1016/j.jhydrol.2009.12.011, 2010.
Friend, A. D., Lucht, W., Rademacher, T. T., Keribin, R., Betts, R., Cadule,
P., Ciais, P., Clark, D. B., Dankers, R., Falloon, P. D., Ito, A., Kahana,
R., Kleidon, A., Lomas, M. R., Nishina, K., Ostberg, S., Pavlick, R.,
Peylin, P., Schaphoff, S., Vuichard, N., Warszawski, L., Wiltshire, A., and
Woodward, F. I.: Carbon residence time dominates uncertainty in terrestrial
vegetation responses to future climate and atmospheric CO2, P. Natl.
Acad. Sci. USA, 111, 3280–3285, https://doi.org/10.1073/pnas.1222477110, 2014.
Glab, T. and Kulig, B.: Effect of mulch and tillage system on soil porosity
under wheat (Triticum aestivum), Soil Till. Res., 99, 169–178,
https://doi.org/10.1016/j.still.2008.02.004, 2008.
Govers, G., Vandaele, K., Desmet, P., Poesen, J., and Bunte, K.: The role of
tillage in soil redistribution on hillslopes, Eur. J. Soil Sci., 45, 469–478, 1994.
Green, T. R., Ahuja, L. R., and Benjamin, J. G.: Advances and challenges in
predicting agricultural management effects on soil hydraulic properties,
Geoderma, 116, 3–27, https://doi.org/10.1016/S0016-7061(03)00091-0, 2003.
Gregory, J. M.: Soil cover prediction with various amounts and types of crop
residue, T. ASAE, 25, 1333–1337, https://doi.org/10.13031/2013.33723, 1982.
Guérif, J., Richard, G., Dürr, C., Machet, J. M., Recous, S., and
Roger-Estrade, J.: A review of tillage effects on crop residue management,
seedbed conditions and seedling establishment, Soil Till. Res., 61,
13–32, 2001.
Harris, I., Jones, P. D., Osborn, T. J., and Lister, D. H.: Updated
high-resolution grids of monthly climatic observations – the CRU TS3.10
Dataset, Int. J. Climatol., 34, 623–642, https://doi.org/10.1002/joc.3711, 2014.
Herzfeld, T., Lutz, F., Heinke, J., Rolinski, S., Schaphoff, S., von Bloh, W., and Müller, C.: LPJmL (version 5.0-tillage) Model Code, Zenodo, https://doi.org/10.5281/zenodo.2652136, 2019.
Hillel, D.: Chapter 12 Soil temperature and heat flow, in: Introduction to
Envrionmental Soil Physics, Elsevier Academic Press Inc, 215–234,
Amsterdam, 2004.
Holland, J. M.: The environmental consequences of adopting conservation
tillage in Europe: reviewing the evidence, Agr. Ecosyst. Environ., 103,
1–25, 2004.
Horton, R., Horn, R., Bachmann, J., and Peth, S.: Essential Soil Physics – An
introduction to soil processes, functions, structure and mechanic, E.
Schweizerbart'sche Verlagsbuchhandlung, 2016.
Jägermeyr, J., Gerten, D., Heinke, J., Schaphoff, S., Kummu, M., and Lucht, W.: Water savings potentials of irrigation systems: global simulation of processes and linkages, Hydrol. Earth Syst. Sci., 19, 3073–3091, https://doi.org/10.5194/hess-19-3073-2015, 2015.
Jägermeyr, J., Gerten, D., Schaphoff, S., Heinke, J., Lucht, W., and
Rockström, J.: Integrated crop water management might sustainably halve
the global food gap, Environ. Res. Lett., 11, 025002,
https://doi.org/10.1088/1748-9326/11/2/025002, 2016.
Jarvis, P. G. and McNaughton, K. G.: Stomatal control of transpiration:
scaling up from leaf to region, Adv. Ecol. Res., 15, 1–49,
https://doi.org/10.1016/S0065-2504(08)60119-1, 1986.
Klein Goldewijk, K., Beusen, A., Van Drecht, G., and De Vos, M.: The HYDE 3.1
spatially explicit database of human-induced global land-use change over the
past 12,000 years: HYDE 3.1 Holocene land use, Global Ecol. Biogeogr., 20,
73–86, https://doi.org/10.1111/j.1466-8238.2010.00587.x, 2010.
Kurothe, R. S., Kumar, G., Singh, R., Singh, H. B., Tiwari, S. P.,
Vishwakarma, A. K., Sena, D. R., and Pande, V. C.: Effect of tillage and
cropping systems on runoff, soil loss and crop yields under semiarid rainfed
agriculture in India, Soil Till. Res., 140, 126–134,
https://doi.org/10.1016/j.still.2014.03.005, 2014.
Lal, R.: Managing soil water to improve rainfed agriculture in India, J.
Sustain. Agr., 32, 51–75, 2008.
Lamarque, J.-F., Dentener, F., McConnell, J., Ro, C.-U., Shaw, M., Vet, R., Bergmann, D., Cameron-Smith, P., Dalsoren, S., Doherty, R., Faluvegi, G., Ghan, S. J., Josse, B., Lee, Y. H., MacKenzie, I. A., Plummer, D., Shindell, D. T., Skeie, R. B., Stevenson, D. S., Strode, S., Zeng, G., Curran, M., Dahl-Jensen, D., Das, S., Fritzsche, D., and Nolan, M.: Multi-model mean nitrogen and sulfur deposition from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): evaluation of historical and projected future changes, Atmos. Chem. Phys., 13, 7997–8018, https://doi.org/10.5194/acp-13-7997-2013, 2013.
Levis, S., Hartman, M. D., and Bonan, G. B.: The Community Land Model underestimates land-use CO2 emissions by neglecting soil disturbance from cultivation, Geosci. Model Dev., 7, 613–620, https://doi.org/10.5194/gmd-7-613-2014, 2014.
Linn, D. M. and Doran, J. W.: Effect of water-filled pore space on carbon
dioxide and nitrous oxide production in tilled and nontilled soils, Soil
Sci. Soc. Am. J., 48, 1267–1272, 1984.
Lugato, E., Leip, A., and Jones, A.: Mitigation Potential of Soil Carbon
Management Overestimated by Neglecting N2O Emissions, Nat. Clim. Change,
8, 219–223, https://doi.org/10.1038/s41558-018-0087-z, 2018.
Lutz, F., Stoorvogel, J. J., and Müller, C.: Options to model the effects
of tillage on N2O emissions at the global scale, Ecol. Model., 392,
212–225, 2019.
Maharjan, G. R., Prescher, A.-K., Nendel, C., Ewert, F., Mboh, C. M.,
Gaiser, T., and Seidel, S. J.: Approaches to model the impact of tillage
implements on soil physical and nutrient properties in different
agro-ecosystem models, Soil Till. Res., 180, 210–221, 2018.
Mangalassery, S., Sjoegersten, S., Sparkes, D. L., and Mooney, S. J.:
Examining the potential for climate change mitigation from zero tillage, J.
Agr. Sci., 153, 1151–1173, https://doi.org/10.1017/S0021859614001002, 2015.
Martins, I. C. F., Cividanes, F. J., Barbosa, J. C., Araújo, E. de S.,
and Haddad, G. Q.: Faunal analysis and population fluctuation of Carabidae
and Staphylinidae (Coleoptera) in no-tillage and conventional tillage
systems, Rev. Bras. Entomol., 53, 432–443, 2009.
Mauser, W. and Bach, H.: PROMET–Large scale distributed hydrological
modelling to study the impact of climate change on the water flows of
mountain watersheds, J. Hydrol., 376, 362–377, 2009.
Mei, K., Wang, Z., Huang, H., Zhang, C., Shang, X., Dahlgren, R. A., Zhang,
M., and Xia, F.: Stimulation of N2O emission by conservation tillage
management in agricultural lands: A meta-analysis, Soil Till Res., 182,
86–93, https://doi.org/10.1016/j.still.2018.05.006, 2018.
Minasny, B. and McBratney, A. B.: Limited effect of organic matter on soil
available water capacity, Eur. J. Soil Sci., 69, 39–47, 2018.
Nachtergaele, F., Van Velthuizen, H., Verelst, L., Batjes, N., Dijkshoorn,
K., van Engelen, V., Fischer, G., Jones, A., Montanarella, L., and Petri, M.:
Harmonized World Soil Database (version 1.1). Food and Agriculture
Organization of the United Nations. Rome, Italy and IIASA, Laxenburg,
Austria, available at:
http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/harmonized-world-soil-database-v12/en/
(last access: 12 July 2018), 2009.
Ogle, S. M., Breidt, F. J., and Paustian, K.: Agricultural management impacts
on soil organic carbon storage under moist and dry climatic conditions of
temperate and tropical regions, Biogeochemistry, 72, 87–121,
https://doi.org/10.1007/s10533-004-0360-2, 2005.
Ogle, S. M., Swan, A., and Paustian, K.: No-till management impacts on crop
productivity, carbon input and soil carbon sequestration, Agr. Ecosyst.
Environ., 149, 37–49, https://doi.org/10.1016/j.agee.2011.12.010, 2012.
Oleson, K. W., Lawrence, D. M., Gordon, B., Flanner, M. G., Kluzek, E.,
Peter, J., Levis, S., Swenson, S. C., Thornton, E., and Feddema, J.:
Technical description of version 4.0 of the Community Land Model (CLM),
2010.
Olin, S., Lindeskog, M., Pugh, T. A. M., Schurgers, G., Wårlind, D., Mishurov, M., Zaehle, S., Stocker, B. D., Smith, B., and Arneth, A.: Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching, Earth Syst. Dynam., 6, 745–768, https://doi.org/10.5194/esd-6-745-2015, 2015.
Oorts, K., Merckx, R., Gréhan, E., Labreuche, J., and Nicolardot, B.:
Determinants of annual fluxes of CO2 and N2O in long-term no-tillage and
conventional tillage systems in northern France, Soil Till Res., 95,
133–148, https://doi.org/10.1016/j.still.2006.12.002, 2007.
Pittelkow, C. M., Liang, X., Linquist, B. A., van Groenigen, K. J., Lee, J.,
Lundy, M. E., van Gestel, N., Six, J., Venterea, R. T., and van Kessel, C.:
Productivity limits and potentials of the principles of conservation
agriculture, Nature, 517, 365–368, https://doi.org/10.1038/nature13809, 2015a.
Pittelkow, C. M., Linquist, B. A., Lundy, M. E., Liang, X., van Groenigen,
K. J., Lee, J., van Gestel, N., Six, J., Venterea, R. T., and van Kessel, C.:
When does no-till yield more? A global meta-analysis, Field Crops Res., 183,
156–168, https://doi.org/10.1016/j.fcr.2015.07.020, 2015b.
Podder, M., Akter, M., Saifullah, A., and Roy, S.: Impacts of Plough Pan on
Physical and Chemical Properties of Soil, J. Environ. Sci. Nat. Resour.,
5, 289–294, https://doi.org/10.3329/jesnr.v5i1.11594, 2012.
Portmann, F. T., Siebert, S., and Döll, P.: MIRCA2000 – Global monthly
irrigated and rainfed crop areas around the year 2000: A new high-resolution
data set for agricultural and hydrological modeling, Global Biogeochem.
Cy., 24, GB1011, https://doi.org/10.1029/2008GB003435, 2010.
Pribyl, D. W.: A critical review of the conventional SOC to SOM conversion
factor, Geoderma, 156, 75–83, https://doi.org/10.1016/j.geoderma.2010.02.003,
2010.
Priestley, C. H. B. and Taylor, R. J.: On the assessment of surface heat
flux and evaporation using large-scale parameters, Mon. Weather Rev.,
100, 81–92, 1972.
Pugh, T. A. M., Arneth, A., Olin, S., Ahlström, A., Bayer, A. D., Klein
Goldewijk, K., Lindeskog, M., and Schurgers, G.: Simulated carbon emissions
from land-use change are substantially enhanced by accounting for
agricultural management, Environ. Res. Lett., 10, 124008,
https://doi.org/10.1088/1748-9326/10/12/124008, 2015.
Ranaivoson, L., Naudin, K., Ripoche, A., Affholder, F., Rabeharisoa, L., and
Corbeels, M.: Agro-ecological functions of crop residues under conservation
agriculture. A review, Agron. Sustain. Dev., 37, 1–17,
https://doi.org/10.1007/s13593-017-0432-z, 2017.
Saxton, K. E. and Rawls, W. J.: Soil Water Characteristic Estimates by
Texture and Organic Matter for Hydrologic Solutions, Soil Sci. Soc. Am. J.,
70, 1569–1577, https://doi.org/10.2136/sssaj2005.0117, 2006.
Schaphoff, S., Heyder, U., Ostberg, S., Gerten, D., Heinke, J., and Lucht,
W.: Contribution of permafrost soils to the global carbon budget, Environ.
Res. Lett., 8, 014026, https://doi.org/10.1088/1748-9326/8/1/014026, 2013.
Schaphoff, S., Forkel, M., Müller, C., Knauer, J., von Bloh, W., Gerten, D., Jägermeyr, J., Lucht, W., Rammig, A., Thonicke, K., and Waha, K.: LPJmL4 – a dynamic global vegetation model with managed land – Part 2: Model evaluation, Geosci. Model Dev., 11, 1377–1403, https://doi.org/10.5194/gmd-11-1377-2018, 2018a.
Schaphoff, S., von Bloh, W., Rammig, A., Thonicke, K., Biemans, H., Forkel, M., Gerten, D., Heinke, J., Jägermeyr, J., Knauer, J., Langerwisch, F., Lucht, W., Müller, C., Rolinski, S., and Waha, K.: LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description, Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018, 2018b.
Scopel, E., Da Silva, F. A. M., Corbeels, M., Affholder, F., and Maraux, F.:
Modelling crop residue mulching effects on water use and production of maize
under semi-arid and humid tropical conditions, Agronomie, 24,
383–395, https://doi.org/10.1051/agro:2004029, 2004.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B.,
Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil
moisture–climate interactions in a changing climate: A review, Earth-Sci.
Rev., 99, 125–161, 2010.
Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky, S.: Evaluation of
ecosystem dynamics, plant geography and terrestrial carbon cycling in the
LPJ dynamic global vegetation model, Glob. Change Biol., 9, 161–185,
https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003.
Six, J., Ogle, S. M., Jay breidt, F., Conant, R. T., Mosier, A. R., and
Paustian, K.: The potential to mitigate global warming with no-tillage
management is only realized when practised in the long term, Glob. Change
Biol., 10, 155–160, https://doi.org/10.1111/j.1529-8817.2003.00730.x, 2004.
Smith, P., Martino, D., Cai, Z., Gwary, D., Janzen, H., Kumar, P., McCarl,
B., Ogle, S., O'Mara, F., Rice, C., Scholes, B., Sirotenko, O., Howden, M.,
McAllister, T., Pan, G., Romanenkov, V., Schneider, U., Towprayoon, S.,
Wattenbach, M. and Smith, J.: Greenhouse gas mitigation in agriculture,
Philos. T. R. Soc. B, 363, 789–813,
https://doi.org/10.1098/rstb.2007.2184, 2008.
Snyder, C. S., Bruulsema, T. W., Jensen, T. L., and Fixen, P. E.: Review of
greenhouse gas emissions from crop production systems and fertilizer
management effects, Agr. Ecosyst. Environ., 133, 247–266,
https://doi.org/10.1016/j.agee.2009.04.021, 2009.
Steinbach, H. S. and Alvarez, R.: Changes in soil organic carbon contents
and nitrous oxide emissions after introduction of no-till in Pampean
agroecosystems, J. Environ. Qual., 35, 3–13, 2006.
Strudley, M. W., Green, T. R., and Ascough, J. C.: Tillage effects on soil
hydraulic properties in space and time: State of the science, Soil Till.
Res., 99, 4–48, https://doi.org/10.1016/j.still.2008.01.007, 2008.
Tans, P. and Keeling, R.: Trends in Atmospheric Carbon Dioxide, National
Oceanic & Atmospheric Administration, Earth System Research Laboratory
(NOAA/ESRL), available at: https://www.esrl.noaa.gov/gmd/ccgg/trends/
(last access: 12 July 2018), 2015.
Tapia-Vargas, M., Tiscareño-López, M., Stone, J. J., Oropeza-Mota,
J. L., and Velázquez-Valle, M.: Tillage system effects on runoff and
sediment yield in hillslope agriculture, Field Crops Res., 69, 173–182,
https://doi.org/10.1016/S0378-4290(00)00139-8, 2001.
Tian, H., Chen, G., Liu, M., Zhang, C., Sun, G., Lu, C., Xu, X., Ren, W.,
Pan, S., and Chappelka, A.: Model estimates of net primary productivity,
evapotranspiration, and water use efficiency in the terrestrial ecosystems
of the southern United States during 1895–2007, Forest Ecol. Manag., 259, 1311–1327, 2010.
University of East Anglia Climatic Research Unit, Harris, I. C., and Jones, P.: CRU TS3.23: Climatic Research Unit
(CRU) Time-Series (TS) Version 3.23 of High Resolution Gridded Data of Month-by-month Variation in Climate
(Jan 1901–-Dec 2014), Centre for Environmental Data Analysis, https://doi.org/10.5285/4c7fdfa6-f176-4c58-acee-683d5e9d2ed5, 2015.
Van Genuchten, M.: A Closed-form Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils1, Soil Sci. Soc. Am. J., 44, 892–898,
https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
van Kessel, C., Venterea, R., Six, J., Adviento-Borbe, M. A., Linquist, B.,
and Van Groenigen, K. J.: Climate, duration, and N placement determine N2O
emissions in reduced tillage systems: a meta-analysis, Glob. Change Biol.,
19, 33–44, 2013.
Van Looy, K., Bouma, J., Herbst, M., Koestel, J., Minasny, B., Mishra, U.,
Montzka, C., Nemes, A., Pachepsky, Y. A., Padarian, J., Schaap, M. G.,
Tóth, B., Verhoef, A., Vanderborght, J., van der Ploeg, M. J.,
Weihermüller, L., Zacharias, S., Zhang, Y., and Vereecken, H.:
Pedotransfer Functions in Earth System Science: Challenges and Perspectives:
PTFs in Earth system science perspective, Rev. Geophys., 55, 1199–1256,
https://doi.org/10.1002/2017RG000581, 2017.
Vereecken, H., Weynants, M., Javaux, M., Pachepsky, Y., Schaap, M. G., and
van Genuchten, M. Th.: Using Pedotransfer Functions to Estimate the van
Genuchten–Mualem Soil Hydraulic Properties: A Review, Vadose Zone J., 9, 795–820,
https://doi.org/10.2136/vzj2010.0045, 2010.
Vereecken, H., Schnepf, A., Hopmans, J. W., Javaux, M., Or, D., Roose, T.,
Vanderborght, J., Young, M. H., Amelung, W., Aitkenhead, M., Allison, S. D.,
Assouline, S., Baveye, P., Berli, M., Brüggemann, N., Finke, P., Flury,
M., Gaiser, T., Govers, G., Ghezzehei, T., Hallett, P., Hendricks Franssen,
H. J., Heppell, J., Horn, R., Huisman, J. A., Jacques, D., Jonard, F.,
Kollet, S., Lafolie, F., Lamorski, K., Leitner, D., McBratney, A., Minasny,
B., Montzka, C., Nowak, W., Pachepsky, Y., Padarian, J., Romano, N., Roth,
K., Rothfuss, Y., Rowe, E. C., Schwen, A., Šimůnek, J., Tiktak, A.,
Van Dam, J., van der Zee, S. E. a. T. M., Vogel, H. J., Vrugt, J. A.,
Wöhling, T., and Young, I. M.: Modeling Soil Processes: Review, Key
Challenges, and New Perspectives, Vadose Zone J., 15, 5,
https://doi.org/10.2136/vzj2015.09.0131, 2016.
von Bloh, W., Schaphoff, S., Müller, C., Rolinski, S., Waha, K., and Zaehle, S.: Implementing the nitrogen cycle into the dynamic global vegetation, hydrology, and crop growth model LPJmL (version 5.0), Geosci. Model Dev., 11, 2789–2812, https://doi.org/10.5194/gmd-11-2789-2018, 2018.
White, J. W., Jones, J. W., Porter, C., McMaster, G. S., and Sommer, R.:
Issues of spatial and temporal scale in modeling the effects of field
operations on soil properties, Oper. Res., 10, 279–299,
https://doi.org/10.1007/s12351-009-0067-1, 2010.
Willekens, K., Vandecasteele, B., Buchan, D., and De Neve, S.: Soil quality
is positively affected by reduced tillage and compost in an intensive
vegetable cropping system, Appl. Soil Ecol., 82, 61–71,
https://doi.org/10.1016/j.apsoil.2014.05.009, 2014.
Williams, J. R., Renard, K. G., and Dyke, P. T.: EPIC: A new method for
assessing erosion's effect on soil productivity, J. Soil Water Conserv.,
38, 381–383, 1983.
Williams, J. R., Izaurralde, R. C., Williams, C., and Steglich, E. M.:
Agricultural Policy/Environmental eXtender Model, Theoretical
Documentation. Version 0806, AgriLIFE Research, Texas A&M System, 2015.
Wilson, G. V., McGregor, K. C., and Boykin, D.: Residue impacts on runoff and
soil erosion for different corn plant populations, Soil Till. Res., 99,
300–307, https://doi.org/10.1016/j.still.2008.04.001, 2008.
Wösten, J. H. M., Lilly, A., Nemes, A., and Le Bas, C.: Development and
use of a database of hydraulic properties of European soils, Geoderma,
90, 169–185, https://doi.org/10.1016/S0016-7061(98)00132-3, 1999.
Zhao, X., Liu, S.-L., Pu, C., Zhang, X.-Q., Xue, J.-F., Zhang, R., Wang,
Y.-Q., Lal, R., Zhang, H.-L., and Chen, F.: Methane and nitrous oxide
emissions under no-till farming in China: a meta-analysis, Glob. Change
Biol., 22, 1372–1384, 2016.
Short summary
Tillage practices are under-represented in global biogeochemical models so that assessments of agricultural greenhouse gas emissions and climate mitigation options are hampered. We describe the implementation of tillage modules into the model LPJmL5.0, including multiple feedbacks between soil water, nitrogen, and productivity. By comparing simulation results with observational data, we show that the model can reproduce reported tillage effects on carbon and water dynamics and crop yields.
Tillage practices are under-represented in global biogeochemical models so that assessments of...
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