Articles | Volume 6, issue 2
https://doi.org/10.5194/gmd-6-495-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-495-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Modeling agriculture in the Community Land Model
B. Drewniak
Environmental Science Division, Argonne National Laboratory, 9700 S. Cass Ave, Argonne, IL 60439, USA
J. Song
Northern Illinois University, Department of Geography, Davis Hall, Room 118, DeKalb, IL 60115, USA
J. Prell
Environmental Science Division, Argonne National Laboratory, 9700 S. Cass Ave, Argonne, IL 60439, USA
V. R. Kotamarthi
Environmental Science Division, Argonne National Laboratory, 9700 S. Cass Ave, Argonne, IL 60439, USA
Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Ave, Argonne, IL 60439, USA
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- Improving Representation of Crop Growth and Yield in the Dynamic Land Ecosystem Model and Its Application to China J. Zhang et al. 10.1029/2017MS001253
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- CLMcrop yields and water requirements: avoided impacts by choosing RCP 4.5 over 8.5 S. Levis et al. 10.1007/s10584-016-1654-9
- Evidence for a weakening strength of temperature-corn yield relation in the United States during 1980–2010 G. Leng 10.1016/j.scitotenv.2017.06.211
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- Global patterns of crop yield stability under additional nutrient and water inputs C. Müller et al. 10.1371/journal.pone.0198748
- Applications of land surface model to economic and environmental-friendly optimization of nitrogen fertilization and irrigation F. Wang et al. 10.1016/j.heliyon.2024.e27549
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- How Much Are Planting Dates for Maize Affected by the Climate Trend? Lessons for Scenario Analysis Using Land Surface Models M. Sheng et al. 10.3390/agronomy9060316
- Using the anomaly forcing Community Land Model (CLM 4.5) for crop yield projections Y. Lu & X. Yang 10.5194/gmd-14-1253-2021
- Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data‐model comparison Z. Hu et al. 10.1111/gcb.14274
- Integration of prognostic sowing and harvesting schemes to enhance crop dynamic growth simulation in Noah-MP-Crop model F. Wang et al. 10.1016/j.ecoinf.2024.102785
- Quantifying indirect groundwater-mediated effects of urbanization on agroecosystem productivity using MODFLOW-AgroIBIS (MAGI), a complete critical zone model S. Zipper et al. 10.1016/j.ecolmodel.2017.06.002
- Comparison of temporal trends from multiple soil moisture data sets and precipitation: The implication of irrigation on regional soil moisture trend J. Qiu et al. 10.1016/j.jag.2015.11.012
- Crop yield sensitivity of global major agricultural countries to droughts and the projected changes in the future G. Leng & J. Hall 10.1016/j.scitotenv.2018.10.434
- The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2) E. Sinha et al. 10.1029/2022JG007187
2 citations as recorded by crossref.
- Improve the Performance of the Noah‐MP‐Crop Model by Jointly Assimilating Soil Moisture and Vegetation Phenology Data T. Xu et al. 10.1029/2020MS002394
- Quantifying the effects of data integration algorithms on the outcomes of a subsurface–land surface processes model C. Shen et al. 10.1016/j.envsoft.2014.05.006
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