IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v377y2018icp26-34.html
   My bibliography  Save this article

Evaluation of CLM-Crop for maize growth simulation over Northeast China

Author

Listed:
  • Sheng, Meiling
  • Liu, Junzhi
  • Zhu, A-Xing
  • Rossiter, David G.
  • Zhu, Liming
  • Peng, Guoqiang

Abstract

Climate change has significant impacts on crop yields and could greatly affect global food security. As an advanced process-based land surface model, the Community Land Model (CLM) includes a comprehensive crop model (CLM-Crop), which aims to simulate crop growth globally. Although this model has been evaluated in the United States, it is not clear whether it can be applied successfully in other parts of the world. In this study we evaluate the applicability of CLM-Crop for maize growth simulation in Northeast China, one of the major agricultural production areas in China. Simulated LAI, plant carbon, phenology and yields of maize were compared with observations at agricultural experiment and meteorological stations and with statistical reports. The CLM-Crop model overestimated LAI and underestimated leaf and stem carbon during the growing period. Planting and harvesting dates were overestimated in the eastern part of the study area, but underestimated in the southern part. Correlation (r = 0.26) between simulated and reported yield was poor. Yields were generally overestimated especially in the east and south parts, which may be due to imperfect farming practices on working farms. Some parameters, including temperature thresholds of planting and crop management parameters, have spatial heterogeneity rather than the default fixed parameters in CLM-Crop. Development of gridded crop parameters is expected to improve simulation of crop phenology and yield estimation at the regional and global scales.

Suggested Citation

  • Sheng, Meiling & Liu, Junzhi & Zhu, A-Xing & Rossiter, David G. & Zhu, Liming & Peng, Guoqiang, 2018. "Evaluation of CLM-Crop for maize growth simulation over Northeast China," Ecological Modelling, Elsevier, vol. 377(C), pages 26-34.
    • Handle: RePEc:eee:ecomod:v:377:y:2018:i:c:p:26-34
    DOI: 10.1016/j.ecolmodel.2018.03.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380018300899
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2018.03.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Junguo & Williams, Jimmy R. & Zehnder, Alexander J.B. & Yang, Hong, 2007. "GEPIC - modelling wheat yield and crop water productivity with high resolution on a global scale," Agricultural Systems, Elsevier, vol. 94(2), pages 478-493, May.
    2. Samuel Levis, 2010. "Modeling vegetation and land use in models of the Earth System," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 1(6), pages 840-856, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ren, Dongyang & Xu, Xu & Engel, Bernard & Huang, Quanzhong & Xiong, Yunwu & Huo, Zailin & Huang, Guanhua, 2021. "A comprehensive analysis of water productivity in natural vegetation and various crops coexistent agro-ecosystems," Agricultural Water Management, Elsevier, vol. 243(C).
    2. Dono, Gabriele & Cortignani, Raffaele & Doro, Luca & Giraldo, Luca & Ledda, Luigi & Pasqui, Massimiliano & Roggero, Pier Paolo, 2013. "Adapting to uncertainty associated with short-term climate variability changes in irrigated Mediterranean farming systems," Agricultural Systems, Elsevier, vol. 117(C), pages 1-12.
    3. Zamani, Omid & Azadi, Hossein & Mortazavi, Seyed Abolghasem & Balali, Hamid & Moghaddam, Saghi Movahhed & Jurik, Lubos, 2021. "The impact of water-pricing policies on water productivity: Evidence of agriculture sector in Iran," Agricultural Water Management, Elsevier, vol. 245(C).
    4. Scheierling, Susanne M. & Treguer, David O. & Booker, James F. & Decker, Elisabeth, 2014. "How to assess agricultural water productivity ? looking for water in the agricultural productivity and efficiency literature," Policy Research Working Paper Series 6982, The World Bank.
    5. Arjen Y. Hoekstra, 2017. "Water Footprint Assessment: Evolvement of a New Research Field," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3061-3081, August.
    6. Pinki Mondal & Sonali Shukla McDermid, 2021. "Editorial for Special Issue: “Global Vegetation and Land Surface Dynamics in a Changing Climate”," Land, MDPI, vol. 10(1), pages 1-4, January.
    7. Thomas, Timothy S., 2015. "US maize data reveals adaptation to heat and water stress:," IFPRI discussion papers 1485, International Food Policy Research Institute (IFPRI).
    8. Xiong, Wei & Balkovič, Juraj & van der Velde, Marijn & Zhang, Xuesong & Izaurralde, R. César & Skalský, Rastislav & Lin, Erda & Mueller, Nathan & Obersteiner, Michael, 2014. "A calibration procedure to improve global rice yield simulations with EPIC," Ecological Modelling, Elsevier, vol. 273(C), pages 128-139.
    9. María Jesús Beltrán & Esther Velázquez, 2011. "Del metabolismo social al metabolismo hídrico," Documentos de Trabajo de la Asociación de Economía Ecológica en España 01_2011, Asociación de Economía Ecológica en España.
    10. Gaiser, Thomas & Judex, Michael & Hiepe, Claudia & Kuhn, Arnim, 2010. "Regional simulation of maize production in tropical savanna fallow systems as affected by fallow availability," Agricultural Systems, Elsevier, vol. 103(9), pages 656-665, November.
    11. Zwart, Sander J. & Bastiaanssen, Wim G.M. & de Fraiture, Charlotte & Molden, David J., 2010. "WATPRO: A remote sensing based model for mapping water productivity of wheat," Agricultural Water Management, Elsevier, vol. 97(10), pages 1628-1636, October.
    12. Folberth, Christian & Yang, Hong & Gaiser, Thomas & Abbaspour, Karim C. & Schulin, Rainer, 2013. "Modeling maize yield responses to improvement in nutrient, water and cultivar inputs in sub-Saharan Africa," Agricultural Systems, Elsevier, vol. 119(C), pages 22-34.
    13. Tomaz, Alexandra & Palma, José Ferro & Ramos, Tiago & Costa, Maria Natividade & Rosa, Elizabete & Santos, Marta & Boteta, Luís & Dôres, José & Patanita, Manuel, 2021. "Yield, technological quality and water footprints of wheat under Mediterranean climate conditions: A field experiment to evaluate the effects of irrigation and nitrogen fertilization strategies," Agricultural Water Management, Elsevier, vol. 258(C).
    14. Folberth, Christian & Yang, Hong & Wang, Xiuying & Abbaspour, Karim C., 2012. "Impact of input data resolution and extent of harvested areas on crop yield estimates in large-scale agricultural modeling for maize in the USA," Ecological Modelling, Elsevier, vol. 235, pages 8-18.
    15. Luxon Nhamo & James Magidi & Adolph Nyamugama & Alistair D. Clulow & Mbulisi Sibanda & Vimbayi G. P. Chimonyo & Tafadzwanashe Mabhaudhi, 2020. "Prospects of Improving Agricultural and Water Productivity through Unmanned Aerial Vehicles," Agriculture, MDPI, vol. 10(7), pages 1-18, July.
    16. Sierra, Jorge & Causeret, François & Chopin, Pierre, 2017. "A framework coupling farm typology and biophysical modelling to assess the impact of vegetable crop-based systems on soil carbon stocks. Application in the Caribbean," Agricultural Systems, Elsevier, vol. 153(C), pages 172-180.
    17. Wang, Zhiqiang & Ye, Li & Jiang, Jingyi & Fan, Yida & Zhang, Xiaoran, 2022. "Review of application of EPIC crop growth model," Ecological Modelling, Elsevier, vol. 467(C).
    18. Dourte, Daniel R. & Fraisse, Clyde W. & Uryasev, Oxana, 2014. "WaterFootprint on AgroClimate: A dynamic, web-based tool for comparing agricultural systems," Agricultural Systems, Elsevier, vol. 125(C), pages 33-41.
    19. Wang, Xiangping & Huang, Guanhua & Yang, Jingsong & Huang, Quanzhong & Liu, Haijun & Yu, Lipeng, 2015. "An assessment of irrigation practices: Sprinkler irrigation of winter wheat in the North China Plain," Agricultural Water Management, Elsevier, vol. 159(C), pages 197-208.
    20. Cai, Liping & Wang, Hui & Liu, Yanxu & Fan, Donglin & Li, Xiaoxiao, 2022. "Is potential cultivated land expanding or shrinking in the dryland of China? Spatiotemporal evaluation based on remote sensing and SVM," Land Use Policy, Elsevier, vol. 112(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:377:y:2018:i:c:p:26-34. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.