ISWC OpenIR  > 水保所知识产出(1956---)
黄土高原小流域土壤水分时间稳定性及空间尺度性研究
高磊
Subtype博士
Thesis Advisor邵明安
2012-05
Degree Grantor中国科学院研究生院
Place of Conferral北京
Keyword土壤水分 时间稳定性 代表性测点 插值精度 采样尺度
Abstract

黄土高原是我国水土流失最严重的地区,植被建设是治理黄土高原地区水土流失
最经济有效的措施。土壤水分作为该地区植被恢复与建设的关键因子,对植被生长、
农业发展、土壤侵蚀和溶质运移等有重要影响,土壤水分是气候、植被、地形和土壤
属性等因素共同作用的结果,与土壤质地、饱和导水率、容重等土壤指标密切相关,
研究土壤水分及其相关变量的时空变异性对黄土高原地区土壤水分管理和生态恢复
有重要意义。
本论文围绕土壤水分及相关土壤指标的时空问题,基于大量野外实测资料,结合
经典统计学和地统计学的基本理论方法,对土壤水分时间稳定性及相关土壤指标的空
间尺度性进行了研究,主要探讨了土壤储水量在坡面尺度的时间稳定性特征、坡面尺
度土壤含水量时空变异性和时间稳定性特征的剖面分布(0-300 cm)、利用常见的土
壤属性对代表性测点进行先验预测的可行性分析、坡面尺度表层土壤水分(0-6 cm)
时间稳定性特征的尺度性、坡面尺度七种土壤指标插值精度的尺度性以及饱和导水率
在小流域尺度上统计参数的空间尺度性等问题,取得的主要成果有:
(1)坡面尺度土壤储水量在不同深度上(0-1、1-2 和2-3 m)均存在良好的时间
稳定性。时间稳定性指标Spearman 秩相关系数与相对差分的标准差均表明,土壤储
水量的时间稳定性随深度的增加而增强,并且两个土壤层次越近或相邻的两个土壤层
次越深,其土壤储水量的空间模式在时间上越相似。相对差分法分析的结果表明,每
一层的土壤储水量均存在代表性测点,并且深层土壤储水量代表性测点数多于浅层土
壤,但是,一个测点不能同时预测三个土层的土壤储水量。相对于土壤储水量空间变
异性,其时间变异性对代表性测点的选择影响更大。
(2)土壤储水量在湿季的异质性强于干季。0-1、1-2 和2-3 m 平均的土壤储水
量与其方差的正相关关系(p < 0.01)随深度的增加而增强,决定系数分别为0.33、
0.91 和0.97。但是在更小的深度间隔(0-100 cm 每10 cm 一层,100-300 cm 每20 cm
一层),土层平均含水量与方差呈幂函数关系(略优于线性方程),其决定系数随深度
的增加呈先降低(0-30 cm)后增加(30-160 cm)最终趋于稳定(160-300cm)。(3)研究黄土高原北部坡面土壤水分时空动态时,200 cm 为合理的采样深度。
0-300 cm 土层土壤水分时空变异性和时间稳定性的剖面特征大致可以划分为三个层
次:Ⅰ)不规律变化层(0-60 cm),该土层为主要的根系活动层,同时又受到降水、
地形等因素的强烈影响,从而导致土壤水分时空特征分布的多变性;Ⅱ)规律变化层
(60-160 cm),植被、降水等影响因素对土壤水分的影响随土壤深度的增加而规律性
减弱,这导致该层土壤水分时空特征的稳定变化;Ⅲ)基本稳定层(160-300 cm),
这一层的土壤水分基本不受植被、降水等因素的影响,土壤属性在垂直方向的变异性
是土壤水分变化的主导因素,黄土地区土壤在垂直剖面上良好的均质性导致土壤水分
时空特征在这一层次展示了良好的稳定性。因此,在类似地区,200 cm 土壤层的土
壤水分时空动态可以反映较为完整的剖面信息。
(4)海拔和粘粒含量是坡面尺度浅层土壤水分(0-60 cm)时间稳定性特征主要
的控制因子,可以解释时间稳定性指标(平均相对差分)64%的变异。但是,具有相
似土壤属性、地形和植被分布的相邻土壤样带(间距为10 m),其时间稳定性特征
(Spearman 秩相关系数、代表性测点数量与分布特征及时间稳定性指标与相关变量
的关系)在样带间存在较大的差异。目前仅用土壤基本属性和海拔因子对代表性测点
进行先验鉴定是不可行的,需引进更多的变量或更先进的分析手段才能实现先验鉴定
代表性测点的目的。明确土壤水分的时空特征有助于先验鉴定代表性测点的模型在不
同时间和空间尺度上的应用。
(5)坡面表层土壤水分(0-6 cm)的时间稳定性特征具有尺度性,采样幅度对
表层土壤水分时间稳定性的影响强于采样间距。尺度性的具体模式因参数而异,对数
方程能够很好地描述大部分时间稳定性特征参数与采样尺度的关系。平均Spearman
秩相关系数随采样间距的增加无显著变化(p > 0.05),随采样幅度的增大呈对数增加
(p < 0.01),土壤水分的时间模式在0.01 和0.05 概率水平上显著的比例随采样间距
的增加或采样幅度的降低而降低;平均相对差分的极差随采样间距的增加呈线性减小
(p < 0.01),随采样幅度的增大呈对数增加(p < 0.01);相对差分标准差的平均值随
采样间距和采样幅度的增大均呈对数增加(p < 0.01)。并且采样间距和采样幅度较小
时,土壤水分时间稳定性参数的变化速率较大。
(6) 采样尺度影响土壤指标样本数据的分布类型及插值精度(用G 值表示),
尺度指标(E & S)对插值精度的预测效果优于经典统计指标(CV)和地统计指标
(S/R),并且线性模型可以很好地描述E & S 与G 值的关系。七种土壤指标(粘粒
含量、粉粒含量、砂粒含量、土壤容重、饱和导水率、表层土壤水分和土壤有机碳)随采样幅度的降低或采样间距的增加,呈正态或对数正态分布的概率升高。随着采样
幅度的增大或采样间距的降低,七种土壤指标的插值精度均有不同程度的提高,但各
土壤指标的平均插值精度存在很大差异。从单个样本对插值精度贡献率最大的角度出
发,在相同的采样幅度下,砂粒含量需要的样本数最少,土壤有机碳含量需要的样本
最多,而其它五种指标需要的样本数大致相同。
(7)小流域饱和导水率的统计参数(方差、相关距离和块金基台比)存在尺度
性依赖性,并且对各尺度要素的依赖程度不同。饱和导水率的方差与采样间距的线性
负相关关系并不显著(p = 0.137);采样间距在1.1 倍“真实的”相关距离范围内变化
时,“表现的”相关距离没有显著的变化,但是当采样间距在1.1 倍“真实的”相关
距离以上变化时,“表现的”相关距离与采样间距呈显著正相关关系;块金基台比与
采样间距呈负对数关系(p < 0.01)。三个参数随采样幅度的增大而以不同的模式增大。
采样体积增大导致测量方差和块金基台比下降、相关距离增加。三个参数与采样间距、
采样幅度和采样体积的拟合方程的平均决定系数分别为0.53、0.96 和0.83。因此,相
对于采样间距和采样体积,采样幅度更适合作为尺度转换的载体,将有限的样本以高
密度分布在小的次级区域比将相同的样本以大的采样间距分布在整个研究区能更精
确推绎所需参数,但是,需要注意的是,所选次级区域必须能比较好地代表研究区的
平均状况。
在野外实测数据的基础上,本论文较深入探讨了土壤水分时间稳定性以及相关变
量的空间尺度性。本研究有助于深化对半干旱地区小流域土壤水分和相关变量时空特
征的认识,为多尺度时空变异研究积累必要的数据,进一步推动土壤水分时间稳定性
概念在黄土高原生态建设和农业生产中的推广应用。同时,本论文的研究成果可为将
来在类似问题的研究中采样方案的设计提供有益参考。
关键词:土壤水分;时间稳定性;代表性测点;插值精度;采样尺度

Other Abstract

The Loess Plateau of China has been susceptible to ongoing severe soil erosion.
Among many controlling measures, vegetation restoration is the most economical and
efficient. Soil moisture is the most critical factor affecting vegetation restoration on the
Loess Plateau, and exerts major influences on vegetation growth, agricultural development,
soil erosion, and solute transport. Soil moisture is an integrated response to climate,
vegetation, topography, and soil properties, and is closely related to soil indexes such as
texture, saturated hydraulic conductivity and bulk density. Therefore, knowledge of the
spatial-temporal characteristics of soil moisture and related variables is of great importance
to soil water management and vegetation restoration.
In connection to the spatio-temporal issues of soil moisture and related soil indexes,
and based on a large number of in-situ measurement data and the use of classical statistics
and geostatistical methods, this dissertation mainly focuses on the following issues: the
temporal stability of soil water storage at the hillslope scale; the distribution of
spatio-temporal variability and temporal stability characteristics of water content within
soil profiles (0-300 cm); a feasibility analysis of the a priori prediction of temporal
stability locations; the scaling of temporal stability for surface soil moisture (0-6 cm); the
interpolation accuracy for seven soil properties at various sampling scales; and the spatial
scaling of soil saturated hydraulic conductivity in a small watershed. The investigations
were all carried out at the hillslope scale except for the last one. The main results were as
follows:
(1) The temporal stability of soil water storage in different soil layers (0-1, 1-2, and
2-3 m) was strong at the hillslope scale. The temporal stability was stronger with increases
in soil depth based on either the Spearman correlation coefficient or the standard deviation
of relative difference (SDRD) index. Furthermore, the closer two soil layers were within a
given profile and the deeper any two adjacent soil layers were, the more similar was the
temporal pattern. Using the relative difference method, representative locations were
indentified for each soil layer. More locations estimated the mean soil water storage of the  study area accurately in deeper soil layers than in shallower layers. However, none of the
locations were able, individually, to represent the mean soil water storage for all three
layers. Temporal variability played a more important role than spatial variability in
determining the number of representative locations.
(2) The soil water storage during this study was more heterogeneously distributed on
the studied hillslope under wetter than under dryer conditions. A linear equation could
describe well the positive relationship between the mean soil water storage and its variance
(p < 0.01). Furthermore, this dependency increased with increasing soil depth. The
determination coefficients between mean soil water storage and their variance, based on
the full dataset, were 0.33, 0.91, and 0.97 for the soil layers of 0–1, 1–2, and 2–3 m,
respectively. The soil water content data were then analyzed at smaller sampling intervals:
10 cm increments between soil depths of 0 and 100 cm; and at 20 cm increments between
the 100 and 300 cm soil depths. The relationships between the mean soil water contents
and their variances were fitted slightly better by a power function than by a linear equation.
The coefficients of determination did not consistently increase down the 0-300 cm soil
profile, but followed the pattern of decreasing between 0 and 30 cm, increasing from 30 to
160 cm, and being relatively constant below 160 cm.
(3) Choosing 200 cm as the maximum soil sampling depth would be sufficient in
areas similar to the study area when the spatio-temporal characteristics of soil moisture are
to be studied. This was justified after identifying three soil sub-layers according to the
profile distribution of spatio-temporal variability and the temporal stability characteristics.
Layer 1, a complex layer (0-60 cm), was considered to be the active root-zone in which the
soil water within the layer was also subject to the strongest effects resulting from climatic
and topographical factors. The multiple influencing factors led to the diversity of the
spatio-temporal characteristics of the soil moisture. Layer 2 was the steadily changing
layer (30-160 cm), in which most of the spatio-temporal characteristics either increased or
decreased at an almost constant rate. This stable rate of change mainly occurred because of
the effects of vegetation and rainfall on soil moisture, which steadily decreased with
increasing soil depth. Layer 3 (160 to 300 cm) was the stable layer. In this soil layer,
vegetation and rainfall had almost no effect on soil moisture. Thus, the variability of soil
properties became the most important factor to the spatio-temporal characteristics of soil  moisture in this layer. The loessial soils have homogeneous soil profiles, which leads to the
stability of the soil moisture spatio-temporal characteristics within this soil layer. Therefore,
when spatio-temporal variability and temporal stability characteristics in soil moisture are
investigated, it would be reasonable to choose 200 cm as the maximum soil sampling
depth.
(4) Elevation and clay content of the soil were the dominant factors affecting the
temporal stability characteristics of soil water in the shallow soil layer (0-60 cm). However,
the a priori selection of representative locations based solely on soil properties and
elevation was determined to be infeasible at the present time since predicted locations
differed greatly from those identified by measurement. Therefore, it is necessary to
introduce more variables or to use a more advanced method to obtain more reliable
predictions of the relationships between the indexes of temporal stability and the selected
variables. Furthermore, the relationships between soil moisture and correlated variables
varied in time and space, which limited the application of these empirical models.
Therefore, we concluded that the a priori identification of representative locations is
presently infeasible, and that more work is needed.
(5) The temporal stability characteristics of surface soil moisture (0-6 cm) at the
hillslope scale were scale-dependent. Sampling extent had a stronger effect on the temporal
stability of soil moisture than sampling spacing.For most of the parameters, a logarithmic
equation could express well the relationships between these parameters and sampling
scales. The parameters changed at a greater rate when sampling spacing or sampling extent
was smaller. However, the specific patterns of scaling differed among parameters. For
example, the mean values of the Spearman rank correlation coefficient did not significantly
change with sampling spacing (p > 0.05), but they increased significantly with increasing
sampling extent (p < 0.01). The ratio of the number of sites under diverse dates with
significant temporal stability, at both the 0.01 and 0.05 probability levels, to the total
number of datasets decreased with increasing sampling spacing or decreasing sampling
extent; the range of mean relative difference (MRD) decreased linearly with the increase in
sampling spacing (p < 0.01), and increased logarithmically with the increase in sampling
extent (p < 0.01); the mean values of the SDRD increased logarithmically with the increase  in both sampling spacing and sampling extent (p < 0.01), but the increase was more
sensitive to changes in sampling extent.
(6)Sampling scaling had an important effect on the data distribution types and
interpolation accuracy, as defined by G values. The interpolation accuracy was predicted
better by the scaling index than by the classic index or by the geo-statistic index. For the
seven soil properties (clay, silt and sand contents, bulk density, saturated hydraulic
conductivity (KS), surface soil moisture content and soil organic carbon content) the
smaller the sampling extent or the greater the sampling spacing, the greater the probability
that the sample distribution would be normal or log-normal. For all the studied soil
properties, the interpolation accuracy increased with either increasing sampling extent or
decreasing sampling spacing. However, the mean interpolation accuracy varied greatly
among the seven investigated soil properties. To obtain the greatest contribution rate (the
ratio of the G value to the number of samples) under the same sampling extent, sand
content required the fewest number of samples while soil organic carbon content required
the most, and about the same number of samples was required for the other five soil
properties.
(7)The statistical parameters (variance, correlation length and nugget-sill ratio) for
soil saturated hydraulic conductivity were scale-dependent in a small watershed, and
depended differently on the scale triplet, in terms of sampling spacing, sampling extent and
sampling support. With increases in sampling spacing, apparent variance tended to
decrease in a non-significant linear relationship (p = 0.137); as sampling spacing increased
below 1.1 times the “true” correlation length (i.e. below 80 m), the apparent correlation
length decreased slightly but, as spacing increased above 80 m, it notably increased; the
nugget-sill ratio decreased logarithmically with the increase in spacing (p < 0.01). The
three parameters all increased with increasing sampling extent but with different patterns.
When the sampling support increased, apparent variance and nugget-sill ratio decreased
and correlation length increased. The mean coefficient of determination of the fitted
models between the three parameters and sampling spacing, sampling extent and sampling
support were 0.53, 0.96 and 0.83, respectively. Thus, for the soil property, KS, upscaling or
downscaling was more reliable when based on sampling extent than on spacing or support
in this study. Consequently, distributing limited sample locations in a sub-area of the main  study area at a higher sampling density is an alternative sampling method, especially in a
more homogeneous study area.
Based on a large number of field measurements of soil moisture and related variables,
a series of issues concerning the temporal stability of soil moisture and the spatial scaling
of related variables were explored in a small watershed on the Loess Plateau. The findings
presented in this dissertation add to the knowledge about the spatio-temporal
characteristics of soil moisture and related variables in semi-arid environments. They are of
benefit to the application of the temporal stability concept to ecological construction and
agricultural production in the Loess Plateau region. They can also add to the data related to
spatio-temporal variability at multiple scales. Moreover, the findings can also be useful
when designing optimal sampling strategies for similar research work.
Keywords: Soil moisture; Temporal stability; Representative location; Interpolation
accuracy; Sampling scale

Language中文
Document Type学位论文
Identifierhttp://ir.iswc.ac.cn/handle/361005/8934
Collection水保所知识产出(1956---)
Recommended Citation
GB/T 7714
高磊. 黄土高原小流域土壤水分时间稳定性及空间尺度性研究[D]. 北京. 中国科学院研究生院,2012.
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