ISWC OpenIR  > 水保所知识产出(1956---)
黄土高原农田土壤有机碳空间变异性
张志霞
Subtype硕士
Thesis Advisor许明祥
2014-05
Degree Grantor中国科学院研究生院
Place of Conferral北京
Keyword黄土高原 农田有机碳 空间变异 尺度效应 不确定性
Abstract

伴随着生态环境问题的不断出现,各类碳问题逐渐成为科学家们探讨的热点。
作为陆地生态系统最大的碳库,土壤碳库储量的估算存在较大的不确定性,有机碳
空间变异是其不确定的重要原因之一。受人为活动的强烈影响,农田土壤有机碳具
有较大的空间变异。在黄土高原地区,由于地形起伏大、地貌类型多样,进一步增
加了农田土壤有机碳的变异性和碳储量估算的不确定性。目前对黄土高原区农田土
壤有机碳空间变异的研究大多集中在坡面和小流域尺度,在黄土高原区域尺度的研
究工作相对缺乏。本文以黄土高原丘陵区、高塬区、平原区为研究区域,从不同地
貌类型区域尺度、同种地貌类型对应的县域尺度、地貌单元尺度和乡镇尺度,采用
传统统计学与地统计学结合的方法,通过对不同尺度下土壤有机碳空间变异、影响
因素、合理样本数、布点方法的差异性研究,确定黄土高原典型地貌区及典型县有
机碳含量空间变异性、影响因素及尺度效应。研究结果对准确估算区域农田土壤有
机碳储量,建立合理的土壤采样布点方案具有重要的理论和现实意义。主要得出以
下结论:
(1) 黄土高原不同地貌类型区及对应的县域尺度下,土壤有机碳空间变异性
具有尺度效应 , 丘陵区的有机碳含量与变异系数尺度效应较为明显。区域尺度上平
原区有机碳含量最高,其次为高塬区与丘陵区,有机碳含量变异规律与之相反。县
域尺度上有机碳含量大小顺序为平原区>丘陵区>高塬区,变异规律为平原区>高塬
区>丘陵区。因此,丘陵区县域尺度上庄浪县有机碳含量代表性较差,其他两区县
域有机碳含量代表性较好。整体上看,研究区土壤有机碳空间相关性距离都表现出
与面积的正相关关系。丘陵区在区域尺度上和县域尺度上土壤有机碳都表现出强烈
的空间相关性,在平原地区随着面积的增大有机碳含量随机性增强,而在高塬区两种尺度下有机碳含量都呈现出随机效应。
(2) 黄土高原不同空间尺度下土壤有机碳变异的主要影响因子及其影响程度有
明显差异 , 但在相同地貌类型区 , 平原区除外 , 区域尺度 影响因子较为复杂 , 且 涵
盖了县域尺度上主要的影响因子 。在区域尺度上,土壤有机碳空间变异的主要影响
因子及其贡献率表现为丘陵区:土壤侵蚀程度 29.7%、海拔 29.6%、土壤类型 26.3%;
平原区为种植制度 57.4%、土壤类型 15.3%、土壤质地 12.3%;高塬区为土壤质地
66.6%、田面坡度 16.7%、坡向 16.7%。在县域尺度上,有机碳空间变异表现为丘陵
区海拔 86.5%、土壤类型 13.5%;平原区为种植制度 51.2%、海拔 29.9%;高塬区显
著性影响因子不明确。
(3) 丘陵区 庄浪县海拔与土壤类型是导致土壤有机碳发生空间变异的主要因素 ,
其 地貌单元尺度和乡镇尺度下土壤有机碳空间变异具有明显差异, , 不同空间尺度下
(县域- 地貌单元- 乡镇)土壤有机碳变异的影响因子存在差异,随着空间尺度的缩
小,海拔和土壤类型对有机碳空间变异的影响减弱 。海拔每升高 200m 有机碳含量
差异显著,黑垆土、黄绵土与红粘土三种土类对有机碳含量有显著影响。在完整地
貌单元尺度上,有机碳含量表现出高山区>低山丘陵区>丘陵沟壑区,变异系数表现
为丘陵沟壑区>低山丘陵区>高山区;乡镇尺度上,有机碳含量表现为低山丘陵区>
丘陵沟壑区>高山区,变异系数表现为高山区>丘陵沟壑区>低山丘陵区。丘陵沟壑
区地貌单元尺度和乡镇尺度土壤有机碳空间变异影响因子无尺度效应;在低山丘陵
区,地貌单元上农田土壤有机碳空间变异的主控因子是海拔与土壤类型,而在乡镇
尺度上则转化为田面坡度;在高山区,地貌单元上主控因子是土壤类型,而乡镇尺
度上主要影响因素为土壤侵蚀程度。
(4) 经典统计学与地统计学两种统计方法所确定的样本量相差较大, , 联合单元布
点较随机均匀布点需求的样本量要小。 。 黄土丘陵区庄浪县不同样本量下的各组样点
都具有充分的代表性 。 联合单元布点比随机均匀布点不确定 性 稍大 。庄浪县有机碳
含量采用传统统计学随机布点确定的合理样本数为 64 个,联合单元布点下的合理
样本为 61 个,差别较小。而采用地统计学在随机布点下所确定的样本量为 903 个
以上,联合单元布点下为 454 个以上,差别较大。因此,利用经典统计学对区域进
行大致趋势及特征的研究时,联合单元布点与随机均匀布点均可运用;但若采用克
里格法来获取县域水平土壤有机碳空间分布状况时,联合单元布点能大量地减少采
样量与投入及分析成本。关键词:黄土高原;农田有机碳;空间变异;尺度效应;不确定性

Other Abstract

With the increasing concern of the ecological environmental problems, carbon
related scientific questions have been becoming the research focus of scientists all over
the world. As the biggest carbon pool on the terrestrial ecosystem, soil carbon pool is a
main research field for soil scientists. For an accurate estimation of soil carbon storage, it
is critical to understand soil carbon spatial variation at a specific scale. The Loess Plateau
of China is characterized for its diverse landforms induced by serious soil erosion. It is a
challenging work to estimate soil carbon storage on the Loess Plateau, especially the soil
carbon storage in farmland with a mosaic distribution on the region. So far, most
researches on soil carbon spatial variability were focused on field and small watershed
scale on the Loess Plateau. Fresh work has been done on regional scale as well as
different scales. In this thesis soil carbon spatial variability at regional scale and county
scale on the Loess Plateau were studied using a geo-statistics method combined with
Geographic Information System (GIS).The main content of the thesis include the spatial
variability of soil organic carbon and its influencing factors, a reasonable number of
samples and differences of sampling methods about organic carbon, which may provide a
scientific basis for the calculation model of organic carbon storage and accurately
understanding the current situation of farmland soil organic matter and nutrient for
agricultural departments. The main conclusions are as following:
(1) Variability of soil organic carbon had scale effect in different scales and different landscape types on the Loess Plateau, and the scale effect was obvious
about the SOC and coefficient variation in Loess Hilly Region. The SOC in the Plains
was the highest, followed by Plateau Area and the Loess Hilly Region on regional scale,
but the variation of SOC was in contrast. On the country scale, the highest of SOC was in
the Plains, followed by the Loess Hilly Region and Plateau Area, and the order of
variation was the Plains, the Plateau Area and the Loess Hilly Region. The
representativeness of SOC in Zhuanglang county was relatively poor in the Loess Hilly
Region, and the other two areas were representative. On the whole, the study area
correlation distance shown that the greater area, greater distance. The SOC have showed
a strongly spatial self-relativity either country scale or regional scale in the Loess Hilly
Region; Randomness were strengthened with increased the area in the plains, while
showed nugget effect in Plateau Area.
(2) The rule about contribution of different factors to SOC variation on the
Loess Plateau was as follows: Main influencing factors for SOC on regional scale
was complex and covered the country scale in the same landforms except the plains.
On regional scale, soil erosion degree could explain 29.7% of variability, soil type 26.3%
and altitude 29.6% in the Loess Hilly Region; Cropping system could explain 57.4% of
variability, soil type 15.3% and soil texture 12.3% in the Plains; Soil texture could
explain 66.6% of variability, field surface slope 16.7% and Aspect 16.7% in Plateau Area.
On the country scale, altitude could explain 86.5% of variability, soil type 13.5% in the
Loess Hilly Region; Cropping system could explain 51.2% of variability, altitude 29.9%
in the plains; No influencing factors was noted in Plateau Area.
(3) The results indicated that main influencing factors for the SOC variation
were altitude and soil type in Zhuanglang county, and difference about SOC
variability was significant in different scales and different landscape types in Loess
Hilly Region. There are statistically significant differences in every increase of 200m
elevation group. Dark loessial soils, red clay soils and Cultivated loessial soils had a
statistically significant effect on SOC. The impact of natural factor on the variance of
SOC did not significantly change in high mountain region, and the others had obvious
scale effect. With the narrowing of spatial scale, SOC variation effect of altitude and soil
type began to lessen. In gully region, all the factors were not significant between the   complete geomorphic units and the town scale. In the hilly region, the main factors were
the altitude and the soil type in the complete geomorphic unit scale, but in town scale
was the slope gradient of field surface. In the high mountain region, the main controlling
factor was soil type in the geomorphic unit scale, but the town scale was the soil erosion
degree.
(4) Classical statistics and Geostatistics were different in sampling. The
reasonable sampling number in combine unit stationing was less than the random
smooth stationing. It showed fully representativeness among different sample sizes
and the uncertainty of combine unit stationing was slightly larger than the random
smooth stationing. Classical statistics showed reasonable sampling number was 64 in
random smooth stationing and 61 in combine unit stationing, which expressed the
smaller difference. Based on the Geostatistics, we concluded that reasonable sampling
number of SOC was respectively about 903 and 454 in random smooth stationing and
combine unit stationing , which had great difference. Consequently, both combine unit
stationing and random smooth stationing can be applied when studied the overall trend
and characteristics by classical statistics, and the combine unit stationing was best when
studied precision distribution of nutrient by Geostatistics.
Keywords: the Loess Plateau, farmland soil organic carbon, spatial variation,
scale effect, uncertainty

Language中文
Document Type学位论文
Identifierhttp://ir.iswc.ac.cn/handle/361005/9003
Collection水保所知识产出(1956---)
Recommended Citation
GB/T 7714
张志霞. 黄土高原农田土壤有机碳空间变异性[D]. 北京. 中国科学院研究生院,2014.
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