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Parameter estimation for a global model of terrestrial biogeochemical cycling by an iterative method [Review]

机译:通过迭代方法估算地球生物地球化学循环全球模型的参数

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We have implemented a geographically distributed ecosystem model TERRA for the carbon, nitrogen, and water dynamics of the global terrestrial biosphere. The ecosystem model in each grid cell has state variables of soil water; vegetation carbon, soil carbon, vegetation nitrogen, soil organic nitrogen, soil inorganic nitrogen, and a variable for allocation. Eight parameters associated with eight carbon or nitrogen fluxes are determined during model calibration at specific sites for each of 17 vegetation types that cover the globe. Calibration is performed by an iterative method that brings calculated fluxes into agreement with observed fluxes over successive iterations. For the 17 vegetation types, calibration required a geometric mean number of 123 iterations for convergence with a geometric S.D. of 2.25. The minimum and maximum iterations required was 52 and 1060 for xeromorphic woodland and tropical evergreen forest, respectively. The parameter controlling gross primary productivity C-max was found to be correlated with maximum projected leaf area index (plus cover of nonvascular plants) with a correlation coefficient of 0.90 (r(2) = 0.81). Correlation of parameters with the input fluxes and average standing crops corresponding to the iteration equation was high in those cases in which temperature and precipitation were not explicit factors in the iteration equation. The parameters K-fall, L-nc, and N-loss had correlation coefficients of 1.0 each with the appropriate ratio of the matching observed transfer flux and standing crop. In iteration equations with explicit dependence on temperature, soil moisture, and other factors, the correlation coefficients were less than 1.0 with these ratios; the parameters C-max, K-r, K-d, N-max, and N-up had correlation coefficients of 0.83, 0.66, 0.60, 0.61, and 0.87, respectively. These correlation coefficients indicate the importance of environmental factors such as temperature and soil moisture in the calibration process and the robustness of the iteration method in determining parameters in systems with time-varying coefficients. (C) 2001 Elsevier Science B.V. All rights reserved. [References: 148]
机译:我们已针对全球陆地生物圈的碳,氮和水动力学实施了地理分布的生态系统模型TERRA。每个网格单元中的生态系统模型都具有土壤水的状态变量。植被碳,土壤碳,植被氮,土壤有机氮,土壤无机氮和分配变量。在模型校准期间,针对覆盖地球的17种植被类型中的每一种,在特定位置确定了与八个碳或氮通量相关的八个参数。通过迭代方法执行校准,该方法使计算的通量与连续迭代中观察到的通量一致。对于17种植被类型,校准需要123次迭代的几何平均值才能与几何S.D收敛。 2.25。对于干性林地和热带常绿森林,所需的最小和最大迭代次数分别为52和1060。发现控制总初级生产力C-max的参数与最大预计叶面积指数(无维管植物的覆盖)相关,相关系数为0.90(r(2)= 0.81)。在温度和降水不是迭代方程中显式因素的情况下,参数与输入通量和与该迭代方程相对应的平均站立作物的相关性很高。参数K-fall,L-nc和N-loss的相关系数均为1.0,且与观察到的通量和站立作物的匹配比例合适。在明显依赖温度,土壤湿度和其他因素的迭代方程中,在这些比率下,相关系数小于1.0。参数C-max,K-r,K-d,N-max和N-up的相关系数分别为0.83、0.66、0.60、0.61和0.87。这些相关系数表明环境因素(例如温度和土壤湿度)在校准过程中的重要性,以及迭代方法在确定具有时变系数的系统中的参数时的鲁棒性。 (C)2001 Elsevier Science B.V.保留所有权利。 [参考:148]

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