摘要
冲积平原区通常具有复杂的剖面质地层次排列，为了准确估算冲积平原区土壤碳密度的空间分布特征，该文在华北冲积平原区的河北曲周县选取了121个土壤剖面，测定了各土层有机碳含量，构建了基于负指数函数的土壤有机碳垂向分布模型，结合地统计学方法绘制了该县土壤碳密度的空间分布图。结果表明，土壤有机碳含量随深度增加呈逐渐递减的趋势，各土层有机碳含量均属于中等变异程度。0～20和＞20～40 cm土壤有机碳空间连续性较好，它们的空间相关距离分别为14和3 km，而下层（＞40 cm）土壤有机碳均表现为纯块金效应结构。土壤有机碳垂向分布模型可以很好地描述剖面土壤有机碳含量的变化特征，且预测与实测的土壤有机碳含量的均方根误差仅为0.70 kg/m3，决定系数达到了0.95。曲周县土壤有机碳密度的空间分布总体表现为西北高东南低的趋势。其空间分布主要受土壤类型和质地的影响，其中潮土和盐化潮土的碳密度明显高于褐土化潮土，质地较细的土壤（轻壤、中壤和粘土）碳密度明显高于质地较粗的土壤（砂土和砂壤）。该研究为冲积平原区土壤碳密度的估算提供了一种新的方法。
Soil organic carbon （SOC） is the key indicator in assessing soil quality, and it is also the important source and sink in global carbon cycle. Usually, the stratified summation method is used in estimation of SOC concentration at small scale, but it is costly and time-consuming process since it needs a large number of soil samples at regional scale. Recently, the vertical distribution models, such as the negative exponential, power and logarithmic functions are used to describe the changes of SOC content with the increasing of soil depth. The vertical distribution of soil texture in alluvial plain is very complicated. However, there are few reports on assessment of the suitability of the SOC vertical distribution model in an alluvial plain. The objectives of this study were to construct and assess a vertical distribution model to describe the changes of SOC content in an alluvial plain, and to determine the main variables that affected SOC concentration distribution. In this study, 605 soil samples were collected from 121 soil profiles in an alluvial plain area of Quzhou county, Hebei Province. SOC contents from topsoil to 1-m depth were determined. The vertical distribution model of SOC was constructed based on negative exponential function, and then regional spatial distribution of SOC concentration was obtained by geostatistical methods. The results indicated that SOC content showed a gradually decreasing trend with the increase of soil depth, and the mean SOC content in topsoil was the highest, reached to 8.25 g/kg soil. The coefficients of variation of SOC content for all layers ranged from 0.26 to 0.43, and all belonged to moderate degree of variation. The spatial continuity was better for SOC in 0-20 and＆gt;20-40 cm as compared to the rest soil depths, and their correlation distances were 14 and 3 km, respectively. However, SOC in subsoil （＆gt;40 cm） showed a pure nugget effect, which reflected the complex spatial distribution of soil textural layers in an alluvial plain. The negative exponential model can well describe the changes of SOC content with the increasing of depth in alluvial plain area, the root mean squared error was only 0.70 and the coefficient of determination of the predicted and measured SOC contents reached to 0.95. Spatial distribution of SOC density showed a decreasing trend from northwest to southeast across the county. Soil types and soil texture were the main influencing factors. The SOC concentration of fluvo-aquic soil and salinity fluvo-aquic soil were significantly higher than that of cinnamon fluvo-aquic soil. The SOC concentration of fine textural soil （light loam, medium loam and clay） was significantly higher than that of the coarse textural soil （sand and sandy loam）. The constructed vertical distribution model can well describe the changes of SOC content in soil profile, which not only provides a new method to estimate SOC contentin alluvial plain area, but also can serve as guidance on evaluation and improvement of regional soil fertility.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2014年第7期64-71,共8页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家科技支撑计划项目(2011BAD04B02)
公益性行业(农业)专项(201403014)
农业科研杰出人才及其创新团队项目(2012)
关键词
土壤
模型
碳
县域尺度
冲积平原区
垂向分布模型
空间分布
soils
models
carbon
county scale
alluvial plain area
vertical distribution model
spatial distribution
