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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

机译:改进的IBIS模型叶面积指数模拟及其对水碳和能量的影响-以中国长白山阔叶林为例

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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. (C) 2015 Elsevier B.V. All rights reserved.
机译:叶面积指数(LAI)是许多生态和水文模型中水和碳循环模拟的关键参数。但是,很难准确估计LAI动态。在这项工作中,开发了一种基于逻辑统计模型和机械模型的改进模型来解决IBIS(集成生物圈模拟器)在LAI仿真中的问题,该模型称为IBIS-LAI。在中国长白山阔叶林中进行了主要的IBIS,IBIS-LAI,逻辑统计模型和机理模型的比较。结果表明,通过修改LAI仿真可以提高模型性能,尤其是在春季和秋季。 IBIS,IBIS-LAI,Logistic统计模型和力学模型对上层LAI模拟的相对误差分别为86.80%,5.39%,8.25%和9.53%;下冠层LAI模拟的相对误差为80.01%,18.57%,33.63%和20.94%。随着LAI模拟精度的提高,IBIS-LAI对蒸散量(ET),总初级生产力(GPP)和土壤温度的模拟得到了改善。结论是,对LAI模拟的修改可以提高IBIS在地表过程模拟中的性能。 (C)2015 Elsevier B.V.保留所有权利。

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