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首页> 外文期刊>Agriculture, Ecosystems & Environment: An International Journal for Scientific Research on the Relationship of Agriculture and Food Production to the Biosphere >Modeling topsoil carbon sequestration in two contrasting crop production to set-aside conversions with RothC - Calibration issues and uncertainty analysis
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Modeling topsoil carbon sequestration in two contrasting crop production to set-aside conversions with RothC - Calibration issues and uncertainty analysis

机译:使用RothC对两种不同作物生产中的表土碳固存和预留转化进行建模-校准问题和不确定性分析

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Model simulations of soil organic carbon turnover in agricultural fields have inherent uncertainties due to input data, initial conditions, and model parameters. The RothC model was used in a Monte Carlo based framework to assess the uniqueness of solution in carbon sequestration simulations. The model was applied to crop production to set-aside conversions in Iowa (sandy clay-loam soil, humid-continental climate) and Greece (clay-loam soil, Mediterranean). The model was initialized and calibrated with particulate organic carbon data obtained by physical fractionation. The calibrated values for the Iowa grassland were 5.05 t C ha(-1), 0.34 y(-1), and 0.27 y(-1) for plant litter input and decomposition rate constants for resistant plant material (RPM) and humus, respectively, while for the Greek shrubland these were 3.79 t C ha(-1), 0.21 y(-1), and 0.0041 y(-1), correspondingly. The model sensitivity analysis revealed that for both sites, predicted soil organic carbon content was most sensitive to the total plant litter input and the RPM rate. The Iowa soil was projected to sequester 17.5 t C ha(-1) and the Greek soil 54 t C ha(-1) over 100 years and the projected uncertainty was 65.6% and 70.8%, respectively. We propose this methodology to assess the factors affecting carbon sequestration in agricultural soils and quantify the uncertainties
机译:由于输入数据,初始条件和模型参数,农田土壤有机碳周转的模型模拟具有固有的不确定性。 RothC模型用于基于Monte Carlo的框架中,以评估固碳模拟中溶液的唯一性。该模型已应用于爱荷华州(沙质壤土,湿润的大陆气候)和希腊(粘土质壤土,地中海)的农作物生产转换。使用通过物理分馏获得的颗粒有机碳数据初始化并校准模型。爱荷华州草地的凋落物输入和抗性植物材料(RPM)和腐殖质的分解速率常数分别为5.05 t C ha(-1),0.34 y(-1)和0.27 y(-1)。 ,而对于希腊灌木丛而言,分别为3.79 t C ha(-1),0.21 y(-1)和0.0041 y(-1)。模型敏感性分析表明,对于两个地点,预测的土壤有机碳含量对植物总凋落物输入量和RPM速率最敏感。预计爱荷华州土壤在100年内的固存量为17.5 t C ha(-1),希腊土壤为54 t C ha(-1),预测的不确定性分别为65.6%和70.8%。我们提出了这种方法来评估影响农业土壤中碳固存的因素并量化不确定性

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