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Improving leaf area index simulation of IBIS model and its effect on water carbon and energy—A case study in Changbai Mountain broadleaved forest of China

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  • Cao, XiaoLei
  • Zhou, ZuHao
  • Chen, XiangDong
  • Shao, WeiWei
  • Wang, ZiRu

Abstract

Leaf area index (LAI) is a key parameter for the simulation of water and carbon cycle in many ecological and hydrological models. However, it is difficult to estimate the LAI dynamics accurately. In this work, a modified model based on the Logistic Statistical Model and the Mechanistic Model was developed to solve the problem of IBIS (Integrated Biosphere Simulator) in LAI simulation, which noted as IBIS–LAI. Comparison between the primary IBIS, IBIS–LAI, as well as Logistic Statistical Model and the Mechanistic Model are performed in Changbai Mountain broadleaved forest of China. Results show that model performance could be enhanced by modification of LAI simulation, especially in spring and autumn. The relative error of upper canopy LAI simulation by IBIS, IBIS–LAI, Logistic statistical model and mechanistic model is 86.80%, 5.39%, 8.25% and 9.53%, respectively; while the relative error of lower canopy LAI simulation is 80.01%, 18.57%, 33.63% and 20.94%. With the improvement of LAI simulation accuracy, simulation of evapotranspiration (ET), gross primary productivity (GPP) and soil temperature by IBIS–LAI has been improved. It is concluded that the modification of LAI simulation can improve the performance of IBIS on the simulation of land surface processes.

Suggested Citation

  • Cao, XiaoLei & Zhou, ZuHao & Chen, XiangDong & Shao, WeiWei & Wang, ZiRu, 2015. "Improving leaf area index simulation of IBIS model and its effect on water carbon and energy—A case study in Changbai Mountain broadleaved forest of China," Ecological Modelling, Elsevier, vol. 303(C), pages 97-104.
    • Handle: RePEc:eee:ecomod:v:303:y:2015:i:c:p:97-104
    DOI: 10.1016/j.ecolmodel.2015.02.012
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    References listed on IDEAS

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    1. Braune, Henning & Müller, Johannes & Diepenbrock, Wulf, 2009. "Integrating effects of leaf nitrogen, age, rank, and growth temperature into the photosynthesis-stomatal conductance model LEAFC3-N parameterised for barley (Hordeum vulgare L.)," Ecological Modelling, Elsevier, vol. 220(13), pages 1599-1612.
    2. Chiang, Jyh-Min & Brown, Kim J., 2007. "Improving the budburst phenology subroutine in the forest carbon model PnET," Ecological Modelling, Elsevier, vol. 205(3), pages 515-526.
    3. Akter, Sonia & Grafton, R. Quentin & Merritt, Wendy S., 2014. "Integrated hydro-ecological and economic modeling of environmental flows: Macquarie Marshes, Australia," Agricultural Water Management, Elsevier, vol. 145(C), pages 98-109.
    4. Yuan, Fengming & Arain, M. Altaf & Black, T. Andrew & Morgenstern, Kai, 2007. "Energy and water exchanges modulated by soil–plant nitrogen cycling in a temperate Pacific Northwest conifer forest," Ecological Modelling, Elsevier, vol. 201(3), pages 331-347.
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    1. Zahra Parisay & Vahedberdi Sheikh & Abdolreza Bahremand & Chooghi Bairam Komaki & Khodayar Abdollahi, 2019. "An Approach for Estimating Monthly Curve Number Based on Remotely-Sensed MODIS Leaf Area Index Products," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(8), pages 2955-2972, June.

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