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模拟美国大西洋中部异质流域的碳动态:分布式校准和独立验证 (DCIV) 方法

Sadiya B Tijjani¹, Subhasis Giri², Richard Lathrop²

¹Department of Geography, Rutgers, The State University of New Jersey, Lucy Stone Hall, 54 Joyce Kilmer Avenue, Piscataway, NJ 08854, USA.

The Science of the total environment

|November 3, 2024

概括

这项研究使用一种结合遥感和现场数据的新方法来增强生态系统碳流量预测. 将草原转化为叶森林显著增加了碳吸收和土壤有机碳储存.

科学领域:

陆地生态系统的碳循环.
环境建模环境建模
遥感应用遥感应用

背景情况:

陆地生态系统对全球碳预算至关重要,生态系统模型被广泛用于流量估计.
目前的模型在参数化和输入数据方面面临不确定性,需要改进预测能力.
准确的碳流量预测对于了解气候变化影响和为土地管理提供信息至关重要.

研究的目的:

提高水域规模的陆地生态系统中碳流的可预测性.
评估分布式校准和独立验证 (DCIV) 方法在改善生态系统模型性能方面的有效性.
评估碳库存和碳流在不同土地管理情景下在异质流域的碳库存和碳流.

主要方法:

采用分布式校准和独立验证 (DCIV) 方法,整合MODIS衍生的净初级生产 (NPP) 和蒸发 (ET) 数据.
利用了多个站点的状共变净生态系统交换 (NEE) 数据和土壤有机碳 (SOC) 和地面生物质 (ABG) 的现场测量.
将DCIV方法应用于先进的土壤和水评估工具 (SWAT) -碳模型,使用基于世纪的SOC算法.

主要成果:

在混合森林,叶,灌木和洪水平原 (草地) 生态系统中确定了显著的SOC库存 (≥100ha-1).
将洪水平原 (草地) 转化为叶森林,使二氧化碳吸收 (NEE) 增加了三倍,ABG增加了77%,在20年内,SOC增加了23%.
将未被放草的草地转换为被放草的牧场显示了SOC的非统计学上显著下降,特别是在顶部0-30厘米的土壤层.

结论:

通过整合多种数据源,DCIV方法有效地改善了异质流域的碳流量预测.
土地管理决策,如草原的植树造林,可以大大提高碳捕获和储存.
该方法为改善复杂的陆地生态系统的区域碳动态预测提供了一个可扩展的解决方案.

关键词:

在地表生物质 (ABG)碳储存是碳的储存方式.生态系统模型生态系统模型厄迪协变量 (EC) 是一个土地使用变化 (LULC)净生态系统交换 (NEE)特别突击队的特种部队.土壤有机碳 (SOC) 是土壤中的有机碳.

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