黄土高原小流域土壤水分时间稳定性及空间尺度性研究
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摘要
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（0-300cm）、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（0-6cm）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2-3m）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2-3m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（0-100cm每10cm一层，100-300cm每20cm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（0-30cm）后增加（30-160cm）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，200cm为合理的采样深度。0-300cm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（0-60cm），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（60-160cm），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（160-300cm），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，200cm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（0-60cm）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10m），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（0-6cm）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。
The Loess Plateau of China has been susceptible to ongoing severe soil erosion.Among many controlling measures, vegetation restoration is the most economical andefficient. Soil moisture is the most critical factor affecting vegetation restoration on theLoess 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 astexture, saturated hydraulic conductivity and bulk density. Therefore, knowledge of thespatial-temporal characteristics of soil moisture and related variables is of great importanceto 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 statisticsand geostatistical methods, this dissertation mainly focuses on the following issues: thetemporal stability of soil water storage at the hillslope scale; the distribution ofspatio-temporal variability and temporal stability characteristics of water content withinsoil profiles (0-300cm); a feasibility analysis of the a priori prediction of temporalstability locations; the scaling of temporal stability for surface soil moisture (0-6cm); theinterpolation accuracy for seven soil properties at various sampling scales; and the spatialscaling of soil saturated hydraulic conductivity in a small watershed. The investigationswere all carried out at the hillslope scale except for the last one. The main results were asfollows:
(1) The temporal stability of soil water storage in different soil layers (0-1,1-2, and2-3m) was strong at the hillslope scale. The temporal stability was stronger with increasesin soil depth based on either the Spearman correlation coefficient or the standard deviationof relative difference (SDRD) index. Furthermore, the closer two soil layers were within agiven profile and the deeper any two adjacent soil layers were, the more similar was thetemporal pattern. Using the relative difference method, representative locations wereindentified 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 thelocations were able, individually, to represent the mean soil water storage for all threelayers. Temporal variability played a more important role than spatial variability indetermining the number of representative locations.
(2) The soil water storage during this study was more heterogeneously distributed onthe studied hillslope under wetter than under dryer conditions. A linear equation coulddescribe well the positive relationship between the mean soil water storage and its variance(p <0.01). Furthermore, this dependency increased with increasing soil depth. Thedetermination coefficients between mean soil water storage and their variance, based onthe full dataset, were0.33,0.91, and0.97for the soil layers of0–1,1–2, and2–3m,respectively. The soil water content data were then analyzed at smaller sampling intervals:10cm increments between soil depths of0and100cm; and at20cm increments betweenthe100and300cm soil depths. The relationships between the mean soil water contentsand their variances were fitted slightly better by a power function than by a linear equation.The coefficients of determination did not consistently increase down the0-300cm soilprofile, but followed the pattern of decreasing between0and30cm, increasing from30to160cm, and being relatively constant below160cm.
(3) Choosing200cm as the maximum soil sampling depth would be sufficient inareas similar to the study area when the spatio-temporal characteristics of soil moisture areto be studied. This was justified after identifying three soil sub-layers according to theprofile distribution of spatio-temporal variability and the temporal stability characteristics.Layer1, a complex layer (0-60cm), was considered to be the active root-zone in which thesoil water within the layer was also subject to the strongest effects resulting from climaticand topographical factors. The multiple influencing factors led to the diversity of thespatio-temporal characteristics of the soil moisture. Layer2was the steadily changinglayer (30-160cm), in which most of the spatio-temporal characteristics either increased ordecreased at an almost constant rate. This stable rate of change mainly occurred because ofthe effects of vegetation and rainfall on soil moisture, which steadily decreased withincreasing soil depth. Layer3(160to300cm) was the stable layer. In this soil layer,vegetation and rainfall had almost no effect on soil moisture. Thus, the variability of soilproperties 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 thestability of the soil moisture spatio-temporal characteristics within this soil layer. Therefore,when spatio-temporal variability and temporal stability characteristics in soil moisture areinvestigated, it would be reasonable to choose200cm as the maximum soil samplingdepth.
(4) Elevation and clay content of the soil were the dominant factors affecting thetemporal stability characteristics of soil water in the shallow soil layer (0-60cm). However,the a priori selection of representative locations based solely on soil properties andelevation was determined to be infeasible at the present time since predicted locationsdiffered greatly from those identified by measurement. Therefore, it is necessary tointroduce more variables or to use a more advanced method to obtain more reliablepredictions of the relationships between the indexes of temporal stability and the selectedvariables. Furthermore, the relationships between soil moisture and correlated variablesvaried in time and space, which limited the application of these empirical models.Therefore, we concluded that the a priori identification of representative locations ispresently infeasible, and that more work is needed.
(5) The temporal stability characteristics of surface soil moisture (0-6cm) at thehillslope scale were scale-dependent. Sampling extent had a stronger effect on the temporalstability of soil moisture than sampling spacing.For most of the parameters, a logarithmicequation could express well the relationships between these parameters and samplingscales. The parameters changed at a greater rate when sampling spacing or sampling extentwas smaller. However, the specific patterns of scaling differed among parameters. Forexample, the mean values of the Spearman rank correlation coefficient did not significantlychange with sampling spacing (p>0.05), but they increased significantly with increasingsampling extent (p <0.01). The ratio of the number of sites under diverse dates withsignificant temporal stability, at both the0.01and0.05probability levels, to the totalnumber of datasets decreased with increasing sampling spacing or decreasing samplingextent; the range of mean relative difference (MRD) decreased linearly with the increase insampling spacing (p <0.01), and increased logarithmically with the increase in samplingextent (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 moresensitive to changes in sampling extent.
（6）Sampling scaling had an important effect on the data distribution types andinterpolation accuracy, as defined by G values. The interpolation accuracy was predictedbetter by the scaling index than by the classic index or by the geo-statistic index. For theseven soil properties (clay, silt and sand contents, bulk density, saturated hydraulicconductivity (KS), surface soil moisture content and soil organic carbon content) thesmaller the sampling extent or the greater the sampling spacing, the greater the probabilitythat the sample distribution would be normal or log-normal. For all the studied soilproperties, the interpolation accuracy increased with either increasing sampling extent ordecreasing sampling spacing. However, the mean interpolation accuracy varied greatlyamong the seven investigated soil properties. To obtain the greatest contribution rate (theratio of the G value to the number of samples) under the same sampling extent, sandcontent required the fewest number of samples while soil organic carbon content requiredthe most, and about the same number of samples was required for the other five soilproperties.
（7）The statistical parameters (variance, correlation length and nugget-sill ratio) forsoil saturated hydraulic conductivity were scale-dependent in a small watershed, anddepended differently on the scale triplet, in terms of sampling spacing, sampling extent andsampling support. With increases in sampling spacing, apparent variance tended todecrease in a non-significant linear relationship (p=0.137); as sampling spacing increasedbelow1.1times the “true” correlation length (i.e. below80m), the apparent correlationlength decreased slightly but, as spacing increased above80m, it notably increased; thenugget-sill ratio decreased logarithmically with the increase in spacing (p <0.01). Thethree parameters all increased with increasing sampling extent but with different patterns.When the sampling support increased, apparent variance and nugget-sill ratio decreasedand correlation length increased. The mean coefficient of determination of the fittedmodels between the three parameters and sampling spacing, sampling extent and samplingsupport were0.53,0.96and0.83, respectively. Thus, for the soil property, KS, upscaling ordownscaling was more reliable when based on sampling extent than on spacing or supportin 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 amore 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 scalingof related variables were explored in a small watershed on the Loess Plateau. The findingspresented in this dissertation add to the knowledge about the spatio-temporalcharacteristics of soil moisture and related variables in semi-arid environments. They are ofbenefit to the application of the temporal stability concept to ecological construction andagricultural production in the Loess Plateau region. They can also add to the data related tospatio-temporal variability at multiple scales. Moreover, the findings can also be usefulwhen designing optimal sampling strategies for similar research work.
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（0-300cm）、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（0-6cm）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2-3m）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2-3m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（0-100cm每10cm一层，100-300cm每20cm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（0-30cm）后增加（30-160cm）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，200cm为合理的采样深度。0-300cm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（0-60cm），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（60-160cm），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（160-300cm），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，200cm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（0-60cm）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10m），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（0-6cm）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。
The Loess Plateau of China has been susceptible to ongoing severe soil erosion.Among many controlling measures, vegetation restoration is the most economical andefficient. Soil moisture is the most critical factor affecting vegetation restoration on theLoess 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 astexture, saturated hydraulic conductivity and bulk density. Therefore, knowledge of thespatial-temporal characteristics of soil moisture and related variables is of great importanceto 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 statisticsand geostatistical methods, this dissertation mainly focuses on the following issues: thetemporal stability of soil water storage at the hillslope scale; the distribution ofspatio-temporal variability and temporal stability characteristics of water content withinsoil profiles (0-300cm); a feasibility analysis of the a priori prediction of temporalstability locations; the scaling of temporal stability for surface soil moisture (0-6cm); theinterpolation accuracy for seven soil properties at various sampling scales; and the spatialscaling of soil saturated hydraulic conductivity in a small watershed. The investigationswere all carried out at the hillslope scale except for the last one. The main results were asfollows:
(1) The temporal stability of soil water storage in different soil layers (0-1,1-2, and2-3m) was strong at the hillslope scale. The temporal stability was stronger with increasesin soil depth based on either the Spearman correlation coefficient or the standard deviationof relative difference (SDRD) index. Furthermore, the closer two soil layers were within agiven profile and the deeper any two adjacent soil layers were, the more similar was thetemporal pattern. Using the relative difference method, representative locations wereindentified 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 thelocations were able, individually, to represent the mean soil water storage for all threelayers. Temporal variability played a more important role than spatial variability indetermining the number of representative locations.
(2) The soil water storage during this study was more heterogeneously distributed onthe studied hillslope under wetter than under dryer conditions. A linear equation coulddescribe well the positive relationship between the mean soil water storage and its variance(p <0.01). Furthermore, this dependency increased with increasing soil depth. Thedetermination coefficients between mean soil water storage and their variance, based onthe full dataset, were0.33,0.91, and0.97for the soil layers of0–1,1–2, and2–3m,respectively. The soil water content data were then analyzed at smaller sampling intervals:10cm increments between soil depths of0and100cm; and at20cm increments betweenthe100and300cm soil depths. The relationships between the mean soil water contentsand their variances were fitted slightly better by a power function than by a linear equation.The coefficients of determination did not consistently increase down the0-300cm soilprofile, but followed the pattern of decreasing between0and30cm, increasing from30to160cm, and being relatively constant below160cm.
(3) Choosing200cm as the maximum soil sampling depth would be sufficient inareas similar to the study area when the spatio-temporal characteristics of soil moisture areto be studied. This was justified after identifying three soil sub-layers according to theprofile distribution of spatio-temporal variability and the temporal stability characteristics.Layer1, a complex layer (0-60cm), was considered to be the active root-zone in which thesoil water within the layer was also subject to the strongest effects resulting from climaticand topographical factors. The multiple influencing factors led to the diversity of thespatio-temporal characteristics of the soil moisture. Layer2was the steadily changinglayer (30-160cm), in which most of the spatio-temporal characteristics either increased ordecreased at an almost constant rate. This stable rate of change mainly occurred because ofthe effects of vegetation and rainfall on soil moisture, which steadily decreased withincreasing soil depth. Layer3(160to300cm) was the stable layer. In this soil layer,vegetation and rainfall had almost no effect on soil moisture. Thus, the variability of soilproperties 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 thestability of the soil moisture spatio-temporal characteristics within this soil layer. Therefore,when spatio-temporal variability and temporal stability characteristics in soil moisture areinvestigated, it would be reasonable to choose200cm as the maximum soil samplingdepth.
(4) Elevation and clay content of the soil were the dominant factors affecting thetemporal stability characteristics of soil water in the shallow soil layer (0-60cm). However,the a priori selection of representative locations based solely on soil properties andelevation was determined to be infeasible at the present time since predicted locationsdiffered greatly from those identified by measurement. Therefore, it is necessary tointroduce more variables or to use a more advanced method to obtain more reliablepredictions of the relationships between the indexes of temporal stability and the selectedvariables. Furthermore, the relationships between soil moisture and correlated variablesvaried in time and space, which limited the application of these empirical models.Therefore, we concluded that the a priori identification of representative locations ispresently infeasible, and that more work is needed.
(5) The temporal stability characteristics of surface soil moisture (0-6cm) at thehillslope scale were scale-dependent. Sampling extent had a stronger effect on the temporalstability of soil moisture than sampling spacing.For most of the parameters, a logarithmicequation could express well the relationships between these parameters and samplingscales. The parameters changed at a greater rate when sampling spacing or sampling extentwas smaller. However, the specific patterns of scaling differed among parameters. Forexample, the mean values of the Spearman rank correlation coefficient did not significantlychange with sampling spacing (p>0.05), but they increased significantly with increasingsampling extent (p <0.01). The ratio of the number of sites under diverse dates withsignificant temporal stability, at both the0.01and0.05probability levels, to the totalnumber of datasets decreased with increasing sampling spacing or decreasing samplingextent; the range of mean relative difference (MRD) decreased linearly with the increase insampling spacing (p <0.01), and increased logarithmically with the increase in samplingextent (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 moresensitive to changes in sampling extent.
（6）Sampling scaling had an important effect on the data distribution types andinterpolation accuracy, as defined by G values. The interpolation accuracy was predictedbetter by the scaling index than by the classic index or by the geo-statistic index. For theseven soil properties (clay, silt and sand contents, bulk density, saturated hydraulicconductivity (KS), surface soil moisture content and soil organic carbon content) thesmaller the sampling extent or the greater the sampling spacing, the greater the probabilitythat the sample distribution would be normal or log-normal. For all the studied soilproperties, the interpolation accuracy increased with either increasing sampling extent ordecreasing sampling spacing. However, the mean interpolation accuracy varied greatlyamong the seven investigated soil properties. To obtain the greatest contribution rate (theratio of the G value to the number of samples) under the same sampling extent, sandcontent required the fewest number of samples while soil organic carbon content requiredthe most, and about the same number of samples was required for the other five soilproperties.
（7）The statistical parameters (variance, correlation length and nugget-sill ratio) forsoil saturated hydraulic conductivity were scale-dependent in a small watershed, anddepended differently on the scale triplet, in terms of sampling spacing, sampling extent andsampling support. With increases in sampling spacing, apparent variance tended todecrease in a non-significant linear relationship (p=0.137); as sampling spacing increasedbelow1.1times the “true” correlation length (i.e. below80m), the apparent correlationlength decreased slightly but, as spacing increased above80m, it notably increased; thenugget-sill ratio decreased logarithmically with the increase in spacing (p <0.01). Thethree parameters all increased with increasing sampling extent but with different patterns.When the sampling support increased, apparent variance and nugget-sill ratio decreasedand correlation length increased. The mean coefficient of determination of the fittedmodels between the three parameters and sampling spacing, sampling extent and samplingsupport were0.53,0.96and0.83, respectively. Thus, for the soil property, KS, upscaling ordownscaling was more reliable when based on sampling extent than on spacing or supportin 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 amore 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 scalingof related variables were explored in a small watershed on the Loess Plateau. The findingspresented in this dissertation add to the knowledge about the spatio-temporalcharacteristics of soil moisture and related variables in semi-arid environments. They are ofbenefit to the application of the temporal stability concept to ecological construction andagricultural production in the Loess Plateau region. They can also add to the data related tospatio-temporal variability at multiple scales. Moreover, the findings can also be usefulwhen designing optimal sampling strategies for similar research work.
引文
[1]孟庆枚.黄土高原水土保持[M].郑州:黄河水利出版社,1996.
[2]李玉山.黄土区土壤水分循环特征及其对陆地水分循环的影响[J].生态学报,1983,3:91-101.
[3]杨文治,邵明安.黄土高原土壤水分研究[M].北京:科学出版社,2000.
[4]中国科学院黄土高原综合科学考察队.黄土高原地区水资源问题及其对策[M].北京:中国科学技术出版社,1990.
[5] Chen LD, Wei W, Fu BJ, Lv YH. Soil and water conservation on the Loess Plateau inChina: review and perspective [J]. Progress in Physical Geography,2007,31:389-403.
[6] Vachaud G, Passerat De Silans A, Balabanis P, Vauclin M. Temporal stability ofspatially measured soil water probability density function [J]. Soil Science Society ofAmerica Journal,1985,49:822-828.
[7]李纪人.遥感和地理信息系统在分布式流域水文模型研制中的应用[J].水文,1997,3:8-12.
[8]金鑫,郝振纯,张金良,王加虎.考虑重力侵蚀影响的分布式土壤侵蚀模型[J].水科学进展,2008,19:257-263.
[9]王冬妮,马玉平,王石立,郭春明.东北玉米生长模型中土壤水分参数的敏感性分析[J].中国农业气象,2010,31:219-224.
[10]房全孝,于强,王建林.利用RZWQM-CERES模拟华北平原农田土壤水分动态及其对作物产量的影响[J].作物学报，2009,35:1122-1130.
[11] Xia Y Q, Shao M A. Soil water carrying capacity for vegetation: a hydrologic andbiogeochemical process model solution [J]. Ecological Modelling,2008,214:112-124.
[12] Henninger DL, Peterson GW, Engman ET. Surface soil moisture within a watershed:Variations, factors influencing, and relationships to surface runoff [J]. Soil ScienceSociety of America Journal,1976,40:773-776.
[13] Famiglietti JS, Rudnicki JW, Rodell M. Variability in surface moisture content along ahillslope transect: rattlesnake hill, Texas [J]. Journal of Hydrology,1998,210:259-281.
[14] Hu W, Shao MA, Han FM, Reichardt K. Spatio-temporal variability behavior of landsurface soil water content in shrub-and grass-land [J]. Geoderma,2011,162:260-272.
[15]潘颜霞,王新平,苏延桂,何明珠,贾荣亮.荒漠人工固沙植被区土壤水分的时空变异性[J].生态学报,2009,29:993-1000.
[16]蔡守华,徐英,王俊生,张礼华,荆国芳.土壤水分和养分时空变异性与作物产量的关系[J].农业工程学报,2009,25:26-31.
[17]马晓东,李卫红,朱成刚,陈亚宁.塔里木河下游土壤水分与植被时空变化特征[J].生态学报,2010,30:4035-4045.
[18] Kachanoski RG, de Jong, E. Scale dependence and the temporal persistence of spatialpatterns of soil water storage [J]. Water Resources Research,1988,24:85-91.
[19] Chen Y. Letter to the editor on Rank Stability or Temporal Stability [J]. Soil ScienceSociety of America Journal,2006,70:306.
[20] Guber AK, Gish TJ, Pachepsky YA, van Genuchten MT, Daughtry CST, Nicholson TJ,Cady RE.2008. Temporal stability in soil water content patterns across agriculturalfields [J]. Catena,73:125-133.
[21] Schneider K, Huisman JA, Breuer L, Zhao Y, Frede HG,2008. Temporal stability ofsoil moisture in various semi-arid steppe ecosystems and its application in remotesensing [J]. Journal of Hydrology,359:16-29.
[22] Brocca L, Melone F, Moramarco T, Morbidelli R. Soil moisture temporal stabilityover experimental areas in Central Italy [J]. Geoderma,2009,148:364-374.
[23] Gao XD, Wu PT, Zhao XN, Shi XG, Wang JW. Estimating spatial mean soil watercontents of sloping jujube orchards using temporal stability [J]. Agricultural WaterManagement,2011,102:66-73.
[24] Comegna V, Basile A. Temporal stability of spatial patterns of soil water storage in acultivated Vesuvian soil [J]. Geoderma,1994,62:299-310.
[25] Kamgar A, Hopmans JW, Wallender WW, Wendroth O. Plotsize and sample numberfor neutron probe measurements in small field trials [J]. Soil Science,1993,156:213-224.
[26] Hu W, Shao MA, Wang QJ, Reichardt K. Time stability of soil water storage measuredby neutron probe and the effects of calibration procedures in a small watershed [J].Catena,2009,79:72-82.
[27] Martínez-Fernández J, Ceballos A. Temporal stability of soil moisture in a large-fieldexperiment in Spain [J]. Soil Science Society of America Journal,2003,67:1647-1656.
[28] Cosh MH, Jackson TJ, Bindlish R, Prueger JH. Watershed scale temporal and spatialstability of soil moisture and its role in validating satellite estimates [J]. RemoteSensing of Environment,2004,92:427-435.
[29] de Rosnay P, Gruhier C, Timouk F, Baup F, Mougin E, Hiernaux P, Kergoat L,LeDantec V. Multi-scale soil moisture measurements at the Gourma meso-scale sitein Mali [J]. Journal of Hydrology,2009,375:241-252.
[30] Zhao Y, Peth S, Wang XY, Lin H, Horn R. Controls of surface soil moisture spatialpatterns and their temporal stability in a semi-arid steppe [J]. Hydrological Processes,2010,24:2507-2519.
[31] Biswas A, Si BC. Identifying scale specific controls of soil water storage in ahummocky landscape using wavelet coherency [J]. Geoderma,2011,165:50-59.
[32] Hu W, Shao MA, Reichardt K. Using a new criterion to identify sites for mean soilwater storage evaluation [J]. Soil Science Society of America Journal,2010,74:762-773.
[33] Williams CJ, McNamara JP, Chandler DG. Controls on the temporal and spatialvariability of soil water in a mountainous landscape: the signature of snow andcomplex terrain [J]. Hydrology and Earth System Sciences,2009,13:1325–1336.
[34] Lin H. Temporal stability of soil moisture spatial pattern and subsurface preferentialflow pathways in the Shale Hills Catchment [J]. Vadose Zone Journal,2006,5:317-340.
[35]朱首军,丁艳芳,薛泰谦.农林复合生态系统土壤水分空间交异性和时间稳定性研究[J].水土保持研究,2000,7:46-48.
[36] Heathman GC, Larose M, Cosh MH, Bindlish R. Surface and profile soil waterspatio-temporal analysis during an excessive rainfall period in the Southern GreatPlains, USA [J]. Catena,2009,78:159-169.
[37] Jacobs JM, Mohanty BP, Hsu E, Miller D. SMEX02: field scale variability, timestability and similarity of soil moisture [J]. Remote Sensing of Environment,2004,92:436-446.
[38] Starks PJ, Heathman GC, Jackson TJ, Cosh MH. Temporal stability of soil moistureprofile [J]. Journal of Hydrology,2006,324:400–411.
[39] de Souza ER, Montenegro AAdA, Montenegro SMG, de Matos JdA. Temporalstability of soil moisture in irrigated carrot crops in Northeast Brazil [J]. AgriculturalWater Management,2011,99:26-32.
[40] Coppola A, Comegna A, Dragonetti G, Lamaddalena N, Kader AM, Comegna V.Average moisture saturation effects on temporal stability of soil water spatialdistribution at field scale [J]. Soil and Tillage Research,2011,114:155-164.
[41] Van Pelt RS, Wierenga PJ. Temporal stability of spatially measured soil matricpotential probability density function [J]. Soil Science Society of America Journal,2001,65:668-677.
[42] Hu W, Shao MA, Han FP. Reichardt K, Tan J. Watershed scale temporal stability ofsoil water content [J]. Geoderma,2010,158:181-198.
[43]赵培培.黄土高原小流域典型坝地土壤水分和泥沙空间分布特征[D].陕西杨凌:中国科学院教育部水土保持与生态环境研究中心,2010.
[44] Dumedah G. Coulibaly P. Evaluation of statistical methods for infilling missing valuesin high-resolution soil moisture data [J]. Journal of Hydrology,2011,400:95-102.
[45] Mohanty BP, Skaggs TH. Spatio-temporal evolution and time-stable characteristics ofsoil moisture within remote sensing footprints with varying soils, slope, andvegetation [J]. Advances in Water Resources2001,24:1051-1067.
[46] Grayson RB, Western AW. Towards areal estimation of soil water content from pointmeasurements: time and space stability of mean response [J]. Journal of Hydrology,1998,207:68-82.
[47] Martínez-Fernández J, Ceballos A. Mean soil moisture estimation using temporalstability analysis [J]. Journal of Hydrology,2005,312,28-38.
[48] Cosh MH, Jackson TJ, Moran S, Bindlish R. Temporal persistence and stability ofsurface soil moisture in a semi-arid watershed [J]. Remote Sensing of Environment,2008,112:304-313.
[49] Gómez-Plaza A, Alvarez-Rogel J, Albaladejo J, Castillo V. Spatial patterns andtemporal stability of soil moisture across a range of scales in a semiarid environment[J]. Hydrological Processes,2000,14:1261-1277.
[50] da Silva AP, Nadler A, Kay BD. Factors contributing to temporal stability in spatialpatterns of water content in the tillage zone [J]. Soil and Tillage Research,2001,58:207-218.
[51] Tallon LK, Si, BC. Representative soil water benchmarking for environmentalmonitoring [J]. Journal of Environmental Informatics,2004,4:28-36.
[52] Vivoni ER, Gebremichael M, Watts CJ, Bindlish R, Jackson TJ. Comparison ofground-based and remotely-sensed surface soil moisture estimates over complexterrain during SMEX04[J]. Remote Sensing of Environment,2008,112:314-325.
[53] Sobieraj JA, Elsenbeer H, Cameron G. Scale dependency in spatial patterns ofsaturated hydraulic conductivity [J]. Catena,2004,55:49-77.
[54] Hawley Me, Jackson TJ, McCuen, RH. Surface soil moisture variation on smallagricultural watersheds [J]. Journal of Hydrology,1983,62:179-200.
[55] Hupet F, Vanclooster M. Intraseasonal dynamics of soil moisture variability within asmall agricultural maize cropped field [J]. Journal of Hydrology,2002,261:86-101.
[56]邵明安,王全九,黄明斌.土壤物理学[M].北京:高等教育出版社,2006.
[57] Hills TC, Reynolds SG. Illustrations of soil moisture variability in selected areas andplots of different sizes [J]. Journal of Hydrology,1969,8:27-47.
[58] Charpentier MA, Croffman PM. Soil moisture variability within remote sensing pixels[J]. Journal of Geophysical Research,1992,97:18987-18995.
[59] Zhu, YJ, Shao MA. Variability and pattern of surface moisture on a small-scalehillslope in Liudaogou catchment on the northern Loess Plateau of China [J].Geoderma,2008,147:185-191.
[60] Penna D, Borga, M, Norbiato D, Fontana GD.2009. Hillslope scale soil moisturevariability in a steep alpine terrain [J]. Journal of Hydrology,364:311-327.
[61] Mohanty BP, Famiglietti JS, Skaggs TH. Evolution of soil moisture spatial structure ina mixed vegetation pixel during the Southern Great Plains1997(SGP97) HydrologyExperiment [J]. Water Resources Research,2000,36:3675-3687.
[62] Bl schl G, Sivapalan M. Scale issue in hydrological modeling: a review in [A]. InKalma, J.D., Sivapalan, M.,(Eds.). Advance in hydrological processes. Scale issue inhydrological modeling [C]. Wiley, Chicester,9-48.
[63]Van Wesenbeeck IJ, Kachanoski RG. Spatial and temporal distribution of soil water inthe tilled layer under a corn crop [J]. Soil Science Society of America Journal,1988,52:363-368.
[64] Goovaerts P, Chiang CN. Temporal persistence of spatial patterns for mineralizablenitrogen and selected soil properties [J]. Soil Science Society of America Journal,1993,57:372-381.
[65] Cassel DK, Wendroth O, Nielsen DR. Assessing spatial variability in an agriculturalexperiment station field: opportunities arising from spatial dependence [J]. AgronomyJournal,2000,92:706-714.
[66]胡伟.黄土高原小流域土壤含水量与饱和导水率的时空变异[D].北京:中国科学院地理科学与资源研究所,2009.
[67]李芳松,雷晓云,陈大春,周世军,刘焕鲜,潘婷.膜下滴灌棉田土壤水分空间变异规律研究[J].灌溉排水学报,2010,29:68-71.
[68]何志斌,赵文智.荒漠绿洲区人工梭梭林土壤水分空间异质性的定量研究[J].冰川冻土,2004,26:207-211.
[69]胡伟,邵明安,王全九.黄土高原退耕坡地土壤水分空间变异的尺度性研究[J].农业工程学报,2005,21:11-16.
[70]陈利顶,张淑荣,傅伯杰,彭鸿嘉.流域尺度土地利用与土壤类型空间分布的相关性研究[J].生态学报,2003,23:2497-2505.
[71]连纲,郭旭东,傅伯杰,虎陈霞.黄土高原小流域土壤容重及水分空间变异特征[J].生态学报,2006,26:647-654.
[72]杨艳丽,史学正,于东升,王洪杰,徐茂,王果.区域尺度土壤养分空间变异及其影响因素研究[J].地理学报,2008,28:788-792.
[73] Kim G, Barros AP. Space–time characterization of soil moisture from passivemicrowave remotely sensed imagery and ancillary data [J]. Remote Sensing ofEnvironment,2002,81:393-403.
[74] Creutin JD, Obled C. Objective analyses and mapping techniques for rainfall fields:an objective comparison [J]. Water Resources Research,1982,18:413-431.
[75] Wilson JP, Gallant JC. Terrain analysis. Principles and applications [M]. Wiley, NewYork,2000.
[76] Zhao KL, Liu XM, Zhang WW, Xu JM, Wang F. Spatial dependence andbioavailability of metal fractions in paddy fields on metal concentrations in rice grainat a regional scale [J]. Journal of Soils and Sediments,2011,11:1165-1177
[77]杨奇勇,杨劲松,刘广明.土壤速效养分空间变异的尺度效应[J].应用生态学报,2011,22:431-436.
[78] Zimmerman D, Pavlik C, Ruggles A, Armstrong MP. An experimental comparison ofordinary and universal kriging and inverse distance weighting [J]. MathematicalGeolog,1999,31:375–390
[79] Chaplot V, Darboux F, Bourennane H, Leguédois S, Silvera N, Phachomphon K.Accuracy of interpolation techniques for the derivation of digital elevation models inrelation to landform types and data density [J]. Geomorphology,2006,77:126-141.
[80]Sun Y, Kang SZ, Li FS, Zhang L. Comparison of interpolation methods for depth togroundwater and its temporal and spatial variations in the Minqin oasis of northwestChina [J]. Environmental Modelling and Software,2009,24:1163-1170.
[81] Cressie N. Statistics for Spatial Data [M]. JohnWiley and Sons, Inc., New York,1993.
[82] Wu J, Norvell WA, Welch RM. Kriging on highly skewed data for DTPA-extractablesoil Zn with auxiliary information for pH and organic carbon [J]. Geoderma,2006,134:187-199.
[83] Li J, Heap AD. A review of comparative studies of spatial interpolation methods inenvironmental sciences: Performance and impact factors [J]. Ecological Informatics,2011,6:228-241.
[84] Schloeder CA, Zimmerman NE, Jacobs MJ. Comparison of methods for interpolatingsoil properties using limited data [J]. Soil Science Society of America Journal,2001,65:470-479.
[85] Wollenhaupt NC, Wolkowski RP, Clayton MK. Mapping soil test phosphorus andpotassium for variable-rate fertilizer application [J]. Journal of ProductionAgricultural,1994,7:441-448.
[86] Mueller TG, Pierce FJ, Schabenberger O, Warncke DD. Map quality for site-specificfertility management [J]. Soil Science Society of America Journal,2001,65:1547-1558.
[87]刘庆,孙景宽,陈印平,夏江宝.不同采样尺度下土壤重金属的空间变异特征[J].土壤通报,40:1406-1410.
[88] Garten Jr CT, Kang S, Brice DJ, Schadt CW, Zhou J. Variability in soil properties atdifferent spatial scales (1m–1km) in a deciduous forest ecosystem [J]. Soil Biologyand Biochemistry,2007,39:2621-2627.
[89] Western AW, Bl schl G, Grayson RB. Geostatistical characterisation of soil moisturepatterns in the Tarrawarra Catchment [J]. Journal of Hydrology,1998,205:20-37.
[90] Western AW, Bl schl G. On the spatial scaling of soil moisture [J]. Journal ofHydrology,1999,217:203-224.
[91] Klute A, Dirksen C. Hydraulic conductivity and diffusivity [A]. In: Klute A (ed),Methods of soil analysis [C], Part1. Soil Science Society of America Madison9,1986.687-734.
[92] Reynolds WD, Bowman BT, Brunke RR, Drury CF, Tan CS. Comparison of tensioninfiltrometer, pressure infiltrometer, and soil core estimates of saturated hydraulicconductivity [J]. Soil Science Society of American Journal,2000,64:478-484.
[93] Sidiras N, Roth CH. Infiltration rate, measured with double-ring infiltrometers and arainfall simulator, as affected by the amount of mulch and the tillage system [J]. Soiland Tillage Research,1987,9:161-168.
[94] Reynolds WD, Elrick DE. In-situ measurement of field-saturated hydraulicconductivity, sorptivity and the α-parameter using the Guelph permeameter [J]. SoilScience,1985,140:292-302.
[95] Abbaspour KC, van Genuchten MTh, Schulin R, Schl ppi E. A sequential uncertaintydomain inverse procedure for estimating subsurface flow and transport parameters [J].Water Resources Research,1997,33:1879-1892.
[96] Sobieraj JA, Elsenbeer H, Vertessy RA. Pedotransfer functions for estimatingsaturated hydraulic conductivity: implications for modeling storm flow generation [J].Journal of Hydrology,2001,251:202-220.
[97] Moustafa MM. A geostatistical approach to optimize the determination of saturatedhydraulic conductivity for large-scale subsurface drainage design in Egypt [J].Agricultural Water Management,2000,42:291-312.
[98]唐克丽,侯庆春,王斌科,张平仓.黄土高原水蚀风蚀交错带和神木试区的环境背景及整治方向[M].中科院西北水土保持研究所集刊,1993,第18集:2-15.
[99] Wang YQ, Shao MA. Spatial variability of soil physical properties in a region of theLoess Plateau of PR China subject to wind and water erosion [J]. Land Degradationand Development,2011, DOI:10.1002/ldr.1128.
[100] Wang YQ, Shao MA, Gao L. Spatial variability of soil particle size distribution andfractal features in Water-Wind Erosion Crisscross Region on the Loess Plateau ofChina [J]. Soil Science,2010,175:579-585.
[101]刘孝义.土壤物理及土壤改良研究法[M].上海:上海科学技术出版社,1982.
[102] Nielsen D, Bouma J. Soil spatial variability. Proceedings of a Workshop of the ISSSand the SSSA in Las Vegas, Pudoc, Wageningen, Netherlands,1985.
[103] Murphy AH. The coefficients correlation and determination as measures ofperformance in forecast verification [J]. Weather Forecast,1995,10:681-688.
[104] Obled C, Wendling J, Beven K. The sensitivity of hydrological models to spatialrainfall patterns: an evaluation using observed data [J]. Journal of Hydrology,1994,159:305-333.
[105] Cambardella C, Mooman TB, Novak JM, Parkin TB, Karlem DL, Turvo RF, KonopaAE. Field scale variability of soil properties in central Iowa soil [J]. Soil ScienceSociety of America Journal,1994,47:1501-1511.
[106] Choi M, Jacobs JM. Soil moisture variability of root zone profiles within SMEX02remote sensing footprints [J]. Advances in Water Resources,2007,30:883-896.
[107] Korsunskaya LP, Gummatov NG, Pachepsky YaA. Seasonal changes in root biomass,carbohydrate content, and structural characteristics of Gray Forest soil [J]. EurasianSoil Science,1995,27:45-52.
[108] Ceballos A, Martínez-Fernández J, Santos F, Alonso P. Soil-water behavior of sandysoils under semi-arid conditions in the Duero Basin (Spain)[J]. Journal of AridEnvironments,2002,51,501-519.
[109] Bi HX, Li XY, Liu X, Guo MX, Li J. A case study of spatial heterogeneity of soilmoisture in the Loess Plateau, western China: A geostatistical approach [J]. Journal ofSedimentary Research,2009,24:63-73.
[110] Western AW, Zhou SL, Grayson RB, McMahon TA, Bl schl G, Wilson DJ. Spatialcorrelation of soil moisture in small catchments and its relationship to dominantspatial hydrological processes [J]. Journal of Hydrology2004,286:113-134.
[111] Nyberg L. Spatial variability of soil water content in the covered catchment atGardsj n, Sweden [J]. Hydrological Processes,1996,10:89-103.
[112] Wang YQ, Shao MA, Shao HB. A preliminary investigation of the dynamiccharacteristics of dried soil layers on the Loess Plateau of China [J]. Journal ofHydrology,2010,381:9-17.
[113] Chen H.S, Shao MA, Li YY. The characteristics of soil water cycle and waterbalance on steep grassland under natural and simulated rainfall conditions in theLoess Plateau of China [J]. Journal of Hydrology,2008,360:242-251.
[114]杨文治,邵明安.黄土高原土壤水分研究[M].北京:科学出版社,2000.
[115] Grayson RB, Western AW, Chiew HS, Bl schl G. Preferred states in spatial soilmoisture patterns: local and nonlocal controls [J]. Water Resources Research,1997,33:2897-2908.
[116] Bouten W, Heimovaara TJ, Tiktak A. Spatial patterns of throughfall and soil waterdynamics in a Gouglas fir stand [J]. Water Resources Research,1992,28:3227-3233.
[117] Jost G, Heuvelink GBM, Papritz A. Analysing the space–time distribution of soilwater storage of a forest ecosystem using spatio-temporal kriging [J]. Geoderma,2005,128:258-273.
[118] Richards JH, Caldwell MM. Hydraulic lift: substantial nocturnal water transportbetween soil layers by Artemisia tridentata roots [J]. Oecologia,1987,73:486-489.
[119] Turner NC. Stomatal behavior and water status of maize, sorghum, and tobaccounder field conditions. Plant Physiology,1974,53:360-365.
[120] Warrick AW. Soil Water Dynamics [M]. New York, Oxford University Press,2003.
[121] Smart DR, Carlisle E, Goebel M, Nunez BA. Transverse hydraulic redistribution by agrapevine. Plant, Cell and Environment,2005,28:157-166.
[122] Smith DM, Jackson NA, Roberts JM, Ong CK. Reverse flow of sap in tree roots anddownward siphoning of water by Grevillea robusta [J]. Functional Ecology,1999,13:256-264.
[123] Gómez-Plaza A, Martinez-Mena M, Albaladejo J, Castillo VM. Factors regulatingspatial distribution of soil water content in small semi-arid catchments [J]. Journal ofHydrology,2001,253:1261-1277.
[124] de Souza ER, Montenegro AAdA, Montenegro SMG, de Matos JdA. Temporalstability of soil moisture in irrigated carrot crops in Northeast Brazil [J]. AgriculturalWater Management,2011,99:26-32.
[125] Hébrard O, Voltz M, Andrieux P, Moussa R. Spatio-temporal distribution of soilsurface moisture in a heterogeneously farmed Mediterranean catchment [J]. Journal ofHydrology,2006,329:110-121.
[126] Zhao Y, Peth S, Hallett P, Wang XY, Giese M, Gao YZ. Factors controlling thespatial patterns of soil moisture in a grazed semi-arid steppe investigated bymultivariate geostatistics [J]. Ecohydrology,2011,4:36-48.
[127] Nakano K, Miyazaki T. Predicting the saturated hydraulic conductivity of compactedsub-soils using the non-similar media concept [J]. Soil and Tillage Research,2005,84:145-153.
[128] She DL, Shao MA. Spatial variability of soil organic C and total N in a smallcatchment of the Loess Plateau, China [J]. Acta Agriculturae Scandinavica, SectionB-Soil and Plant Science,2009,59:514-524.
[129] Peters-Lidard CD, Pan F, Wood EF. A re-examination of modeled and measured soilmoisture spatial variability and its implications for land surface modeling [J].Advances in Water Resources,2001,24:1069-1083.
[130] Ma KM, Fu BJ, Liu SL, Guan WB, Liu GH, LV YH, Anand M. Multiple-scale soilmoisture distribution and its implications for ecosystem restoration in an arid rivervalley, China [J]. Land Degradation and Development,200415:75-78.
[131] Wang CM, Zuo Q, Zhang RD. Estimating the necessary sampling size of surface soilmoisture at different scales using a random combination method [J]. Journal ofHydrology,2008,352:309-321.
[132] Hu W, Shao MA, Wang QJ, Reichardt K. Soil water content temporal-spatialvariability of the surface layer of a Loess Plateau hillside in China [J]. ScientiaAgricola,2008,65:277-289.
[133] Wang YQ, Shao MA, Zhu YJ, Liu ZP. Impacts of land use and plant characteristicson dried soil layers in different climatic regions on the Loess Plateau of China [J].Agricultural and Forest Meteorology,2011,151:437-448.
[134] Jenkins GM, Watts DG. Spectral analysis and its applications [M]. Holden–Day, SanFrancisco,1968.
[135] Vanmarcke E. Random Fields: Analysis and Synthesis [M]. The MIT Press,Cambridge, Massachusetts,1983.
[136] Sigua GC, Hudnall WH. Kriging analysis of soil properties [J]. Journal of Soils andSediments,2008,8:193-202.
[137]文波龙,刘兴土,张乃明.滇池大清河流域农田土壤磷素空间变异特征及对地表径流的影响[J].土壤学报,2012,49:173-178.
[138] Wang YQ, Zhang XC, Huang CQ. Spatial variability of soil total nitrogen and soiltotal phosphorus under different land uses in a small watershed on the Loess Plateau,China [J]. Geoderma,2009,150:141-149.
[139] Liu ZP, Shao MA, Wang YQ. Effect of environmental factors on regional soilorganic carbon stocks across the Loess Plateau region, China [J]. Agriculture,Ecosystems and Environment,2011,142:184-194.
[140]肖波,王庆海,李翠,曹志德.黄土高原退耕地复垦对土壤理化性状及空间变异特征的影响[J].西北农林科技大学学报(自然科学版),2011,39:185-192.
[141] Treasurer JW, Pope JA. Selection of host sample number and design of a monitoringprogramme for ectoparasitic sea lice (Copepoda: Caligidae) on farmed Atlanticsalmon, Salmo salar [J]. Aquaculture,2000,187:247-260.
[142] Mcbratney AB, Webster R. How many observations are needed for regionalestimation of soil properties [J]? Soil Science,1983,135:177-183.
[143] Park SJ, van de Giesen N. Soil-landscape delineation to define spatial samplingdomains for hillslope hydrology [J]. Journal of Hydrology,2004,295:28-46.
[144] Bishop TFA, McBratney AB. A comparison of prediction methods for the creation offield-extent soil property maps [J]. Geoderma,2001,103:149-160.
[145] Hirzel A, Guisan A. Which is the optimal sampling strategy for habitat suitabilitymodeling [J]? Ecological Modelling,2002,157:331-341.
[146] Voltz M, Webster R. A comparison of kriging, cubic splines and classification forpredicting soil properties from sample information [J]. Journal of Soil Science,1990,41:473-490.
[147] Shi Z, Wang K, Bailey JS, Jordan C, Higgins AJ. Sampling strategies for mappingsoil phosphorus and soil potassium distribution in cool temperate grassland [J].Precision Agriculture,2000,2:347-357.
[148] Kravchenko AN. Influence of spatial structure on accuracy of interpolation methods[J]. Soil Science Society of America Journal,2003,67:1564-1571.
[149] Mollitor AV, Leaf AL, Morris LA. Forest soil variability on northeastern flood plains[J]. Soil Science Society of America Journal,1980,44:617-620.
[150] Romano N. Use of an inverse method and geostatistics to estimate soil hydraulicconductivity for spatial variability analysis [J]. Geoderma,1993,60:169-186.
[151] Logsdon SD. Determination of preferential flow model parametres [J]. Soil ScienceSociety of America Journal,2002,66:1095-1103.
[152] Mohanty BP, Mousli Z. Saturated hydraulic conductivity and soil water retentionproperties across a soil-slope transition [J]. Water Resources Research,2000,36:3311-3324.
[153] Zimmermann B, Elsenbeer H. Spatial and temporal variability of soil saturatedhydraulic conductivity in gradients of disturbance [J]. Journal of Hydrology,2008,361:78-95.
[154] Journel AG. The lognormal approach to predicting local distributions of selectivemining unit grades [J]. Mathematical Geology,1980,12:285-303.
[155] Saito H, Goovaerts P. Geostatistical interpolation of positively skewed and censoreddata in a dioxin-contaminated site [J]. Environmental Science and Technology,2000,34:4228-4235.
[156] Rawls WJ, Gimenez D, Grossman R. Use of soil texture, bulk density, and slope ofthe water retention curve to predict saturated hydraulic conductivity [J]. Transactionsof the ASABE,1998,41:983-988.
[157] D rner J, Dec D, Peng X, Horn R. Effect of land use change on the dynamicbehaviour of structural properties of an Andisol in southern Chile under saturated andunsaturated hydraulic conditions [J]. Geoderma,2010,159:189-197.
[158] Wang YQ, Shao MA, Liu ZP, Warrington DN. Investigation of factors controlling theregional-Scale distribution of dried soil layers under forestland on the Loess Plateau,China [J]. Surveys in Geophysics,2012,33:311-330.
[159] Kerry R, Oliver MA. Comparing sampling needs for variograms of soil propertiescomputed by the method of moments and residual maximum likelihood [J]. Geoderma,2007,140:383-396.
[160] Gelhar LW. Stochastic Subsurface Hydrology. Prentice Hall, Englewood Cliffs [M],NJ,1993.
[161] Bl schl G. Scale and Scaling in Hydrology–a framework for thinking and analysis[M]. John Wiley, Chichester,1998.
[162] Lauren JG, Wagnet RJ, Bouma J, Wosten JHM. Variability of saturated hydraulicconductivity in a glossaquic hapludalf with macropores [J]. Soil Science,1988,145:20-28.
[163] Rodríguez-Iturbe I, Vogel GK, Rigon R, Entekhabi D, Castelli F, Rinaldo A. On thespatial organization of soil moisture fields [J]. Geophysical Research Letters,1995,22:2757-2760.
[2]李玉山.黄土区土壤水分循环特征及其对陆地水分循环的影响[J].生态学报,1983,3:91-101.
[3]杨文治,邵明安.黄土高原土壤水分研究[M].北京:科学出版社,2000.
[4]中国科学院黄土高原综合科学考察队.黄土高原地区水资源问题及其对策[M].北京:中国科学技术出版社,1990.
[5] Chen LD, Wei W, Fu BJ, Lv YH. Soil and water conservation on the Loess Plateau inChina: review and perspective [J]. Progress in Physical Geography,2007,31:389-403.
[6] Vachaud G, Passerat De Silans A, Balabanis P, Vauclin M. Temporal stability ofspatially measured soil water probability density function [J]. Soil Science Society ofAmerica Journal,1985,49:822-828.
[7]李纪人.遥感和地理信息系统在分布式流域水文模型研制中的应用[J].水文,1997,3:8-12.
[8]金鑫,郝振纯,张金良,王加虎.考虑重力侵蚀影响的分布式土壤侵蚀模型[J].水科学进展,2008,19:257-263.
[9]王冬妮,马玉平,王石立,郭春明.东北玉米生长模型中土壤水分参数的敏感性分析[J].中国农业气象,2010,31:219-224.
[10]房全孝,于强,王建林.利用RZWQM-CERES模拟华北平原农田土壤水分动态及其对作物产量的影响[J].作物学报，2009,35:1122-1130.
[11] Xia Y Q, Shao M A. Soil water carrying capacity for vegetation: a hydrologic andbiogeochemical process model solution [J]. Ecological Modelling,2008,214:112-124.
[12] Henninger DL, Peterson GW, Engman ET. Surface soil moisture within a watershed:Variations, factors influencing, and relationships to surface runoff [J]. Soil ScienceSociety of America Journal,1976,40:773-776.
[13] Famiglietti JS, Rudnicki JW, Rodell M. Variability in surface moisture content along ahillslope transect: rattlesnake hill, Texas [J]. Journal of Hydrology,1998,210:259-281.
[14] Hu W, Shao MA, Han FM, Reichardt K. Spatio-temporal variability behavior of landsurface soil water content in shrub-and grass-land [J]. Geoderma,2011,162:260-272.
[15]潘颜霞,王新平,苏延桂,何明珠,贾荣亮.荒漠人工固沙植被区土壤水分的时空变异性[J].生态学报,2009,29:993-1000.
[16]蔡守华,徐英,王俊生,张礼华,荆国芳.土壤水分和养分时空变异性与作物产量的关系[J].农业工程学报,2009,25:26-31.
[17]马晓东,李卫红,朱成刚,陈亚宁.塔里木河下游土壤水分与植被时空变化特征[J].生态学报,2010,30:4035-4045.
[18] Kachanoski RG, de Jong, E. Scale dependence and the temporal persistence of spatialpatterns of soil water storage [J]. Water Resources Research,1988,24:85-91.
[19] Chen Y. Letter to the editor on Rank Stability or Temporal Stability [J]. Soil ScienceSociety of America Journal,2006,70:306.
[20] Guber AK, Gish TJ, Pachepsky YA, van Genuchten MT, Daughtry CST, Nicholson TJ,Cady RE.2008. Temporal stability in soil water content patterns across agriculturalfields [J]. Catena,73:125-133.
[21] Schneider K, Huisman JA, Breuer L, Zhao Y, Frede HG,2008. Temporal stability ofsoil moisture in various semi-arid steppe ecosystems and its application in remotesensing [J]. Journal of Hydrology,359:16-29.
[22] Brocca L, Melone F, Moramarco T, Morbidelli R. Soil moisture temporal stabilityover experimental areas in Central Italy [J]. Geoderma,2009,148:364-374.
[23] Gao XD, Wu PT, Zhao XN, Shi XG, Wang JW. Estimating spatial mean soil watercontents of sloping jujube orchards using temporal stability [J]. Agricultural WaterManagement,2011,102:66-73.
[24] Comegna V, Basile A. Temporal stability of spatial patterns of soil water storage in acultivated Vesuvian soil [J]. Geoderma,1994,62:299-310.
[25] Kamgar A, Hopmans JW, Wallender WW, Wendroth O. Plotsize and sample numberfor neutron probe measurements in small field trials [J]. Soil Science,1993,156:213-224.
[26] Hu W, Shao MA, Wang QJ, Reichardt K. Time stability of soil water storage measuredby neutron probe and the effects of calibration procedures in a small watershed [J].Catena,2009,79:72-82.
[27] Martínez-Fernández J, Ceballos A. Temporal stability of soil moisture in a large-fieldexperiment in Spain [J]. Soil Science Society of America Journal,2003,67:1647-1656.
[28] Cosh MH, Jackson TJ, Bindlish R, Prueger JH. Watershed scale temporal and spatialstability of soil moisture and its role in validating satellite estimates [J]. RemoteSensing of Environment,2004,92:427-435.
[29] de Rosnay P, Gruhier C, Timouk F, Baup F, Mougin E, Hiernaux P, Kergoat L,LeDantec V. Multi-scale soil moisture measurements at the Gourma meso-scale sitein Mali [J]. Journal of Hydrology,2009,375:241-252.
[30] Zhao Y, Peth S, Wang XY, Lin H, Horn R. Controls of surface soil moisture spatialpatterns and their temporal stability in a semi-arid steppe [J]. Hydrological Processes,2010,24:2507-2519.
[31] Biswas A, Si BC. Identifying scale specific controls of soil water storage in ahummocky landscape using wavelet coherency [J]. Geoderma,2011,165:50-59.
[32] Hu W, Shao MA, Reichardt K. Using a new criterion to identify sites for mean soilwater storage evaluation [J]. Soil Science Society of America Journal,2010,74:762-773.
[33] Williams CJ, McNamara JP, Chandler DG. Controls on the temporal and spatialvariability of soil water in a mountainous landscape: the signature of snow andcomplex terrain [J]. Hydrology and Earth System Sciences,2009,13:1325–1336.
[34] Lin H. Temporal stability of soil moisture spatial pattern and subsurface preferentialflow pathways in the Shale Hills Catchment [J]. Vadose Zone Journal,2006,5:317-340.
[35]朱首军,丁艳芳,薛泰谦.农林复合生态系统土壤水分空间交异性和时间稳定性研究[J].水土保持研究,2000,7:46-48.
[36] Heathman GC, Larose M, Cosh MH, Bindlish R. Surface and profile soil waterspatio-temporal analysis during an excessive rainfall period in the Southern GreatPlains, USA [J]. Catena,2009,78:159-169.
[37] Jacobs JM, Mohanty BP, Hsu E, Miller D. SMEX02: field scale variability, timestability and similarity of soil moisture [J]. Remote Sensing of Environment,2004,92:436-446.
[38] Starks PJ, Heathman GC, Jackson TJ, Cosh MH. Temporal stability of soil moistureprofile [J]. Journal of Hydrology,2006,324:400–411.
[39] de Souza ER, Montenegro AAdA, Montenegro SMG, de Matos JdA. Temporalstability of soil moisture in irrigated carrot crops in Northeast Brazil [J]. AgriculturalWater Management,2011,99:26-32.
[40] Coppola A, Comegna A, Dragonetti G, Lamaddalena N, Kader AM, Comegna V.Average moisture saturation effects on temporal stability of soil water spatialdistribution at field scale [J]. Soil and Tillage Research,2011,114:155-164.
[41] Van Pelt RS, Wierenga PJ. Temporal stability of spatially measured soil matricpotential probability density function [J]. Soil Science Society of America Journal,2001,65:668-677.
[42] Hu W, Shao MA, Han FP. Reichardt K, Tan J. Watershed scale temporal stability ofsoil water content [J]. Geoderma,2010,158:181-198.
[43]赵培培.黄土高原小流域典型坝地土壤水分和泥沙空间分布特征[D].陕西杨凌:中国科学院教育部水土保持与生态环境研究中心,2010.
[44] Dumedah G. Coulibaly P. Evaluation of statistical methods for infilling missing valuesin high-resolution soil moisture data [J]. Journal of Hydrology,2011,400:95-102.
[45] Mohanty BP, Skaggs TH. Spatio-temporal evolution and time-stable characteristics ofsoil moisture within remote sensing footprints with varying soils, slope, andvegetation [J]. Advances in Water Resources2001,24:1051-1067.
[46] Grayson RB, Western AW. Towards areal estimation of soil water content from pointmeasurements: time and space stability of mean response [J]. Journal of Hydrology,1998,207:68-82.
[47] Martínez-Fernández J, Ceballos A. Mean soil moisture estimation using temporalstability analysis [J]. Journal of Hydrology,2005,312,28-38.
[48] Cosh MH, Jackson TJ, Moran S, Bindlish R. Temporal persistence and stability ofsurface soil moisture in a semi-arid watershed [J]. Remote Sensing of Environment,2008,112:304-313.
[49] Gómez-Plaza A, Alvarez-Rogel J, Albaladejo J, Castillo V. Spatial patterns andtemporal stability of soil moisture across a range of scales in a semiarid environment[J]. Hydrological Processes,2000,14:1261-1277.
[50] da Silva AP, Nadler A, Kay BD. Factors contributing to temporal stability in spatialpatterns of water content in the tillage zone [J]. Soil and Tillage Research,2001,58:207-218.
[51] Tallon LK, Si, BC. Representative soil water benchmarking for environmentalmonitoring [J]. Journal of Environmental Informatics,2004,4:28-36.
[52] Vivoni ER, Gebremichael M, Watts CJ, Bindlish R, Jackson TJ. Comparison ofground-based and remotely-sensed surface soil moisture estimates over complexterrain during SMEX04[J]. Remote Sensing of Environment,2008,112:314-325.
[53] Sobieraj JA, Elsenbeer H, Cameron G. Scale dependency in spatial patterns ofsaturated hydraulic conductivity [J]. Catena,2004,55:49-77.
[54] Hawley Me, Jackson TJ, McCuen, RH. Surface soil moisture variation on smallagricultural watersheds [J]. Journal of Hydrology,1983,62:179-200.
[55] Hupet F, Vanclooster M. Intraseasonal dynamics of soil moisture variability within asmall agricultural maize cropped field [J]. Journal of Hydrology,2002,261:86-101.
[56]邵明安,王全九,黄明斌.土壤物理学[M].北京:高等教育出版社,2006.
[57] Hills TC, Reynolds SG. Illustrations of soil moisture variability in selected areas andplots of different sizes [J]. Journal of Hydrology,1969,8:27-47.
[58] Charpentier MA, Croffman PM. Soil moisture variability within remote sensing pixels[J]. Journal of Geophysical Research,1992,97:18987-18995.
[59] Zhu, YJ, Shao MA. Variability and pattern of surface moisture on a small-scalehillslope in Liudaogou catchment on the northern Loess Plateau of China [J].Geoderma,2008,147:185-191.
[60] Penna D, Borga, M, Norbiato D, Fontana GD.2009. Hillslope scale soil moisturevariability in a steep alpine terrain [J]. Journal of Hydrology,364:311-327.
[61] Mohanty BP, Famiglietti JS, Skaggs TH. Evolution of soil moisture spatial structure ina mixed vegetation pixel during the Southern Great Plains1997(SGP97) HydrologyExperiment [J]. Water Resources Research,2000,36:3675-3687.
[62] Bl schl G, Sivapalan M. Scale issue in hydrological modeling: a review in [A]. InKalma, J.D., Sivapalan, M.,(Eds.). Advance in hydrological processes. Scale issue inhydrological modeling [C]. Wiley, Chicester,9-48.
[63]Van Wesenbeeck IJ, Kachanoski RG. Spatial and temporal distribution of soil water inthe tilled layer under a corn crop [J]. Soil Science Society of America Journal,1988,52:363-368.
[64] Goovaerts P, Chiang CN. Temporal persistence of spatial patterns for mineralizablenitrogen and selected soil properties [J]. Soil Science Society of America Journal,1993,57:372-381.
[65] Cassel DK, Wendroth O, Nielsen DR. Assessing spatial variability in an agriculturalexperiment station field: opportunities arising from spatial dependence [J]. AgronomyJournal,2000,92:706-714.
[66]胡伟.黄土高原小流域土壤含水量与饱和导水率的时空变异[D].北京:中国科学院地理科学与资源研究所,2009.
[67]李芳松,雷晓云,陈大春,周世军,刘焕鲜,潘婷.膜下滴灌棉田土壤水分空间变异规律研究[J].灌溉排水学报,2010,29:68-71.
[68]何志斌,赵文智.荒漠绿洲区人工梭梭林土壤水分空间异质性的定量研究[J].冰川冻土,2004,26:207-211.
[69]胡伟,邵明安,王全九.黄土高原退耕坡地土壤水分空间变异的尺度性研究[J].农业工程学报,2005,21:11-16.
[70]陈利顶,张淑荣,傅伯杰,彭鸿嘉.流域尺度土地利用与土壤类型空间分布的相关性研究[J].生态学报,2003,23:2497-2505.
[71]连纲,郭旭东,傅伯杰,虎陈霞.黄土高原小流域土壤容重及水分空间变异特征[J].生态学报,2006,26:647-654.
[72]杨艳丽,史学正,于东升,王洪杰,徐茂,王果.区域尺度土壤养分空间变异及其影响因素研究[J].地理学报,2008,28:788-792.
[73] Kim G, Barros AP. Space–time characterization of soil moisture from passivemicrowave remotely sensed imagery and ancillary data [J]. Remote Sensing ofEnvironment,2002,81:393-403.
[74] Creutin JD, Obled C. Objective analyses and mapping techniques for rainfall fields:an objective comparison [J]. Water Resources Research,1982,18:413-431.
[75] Wilson JP, Gallant JC. Terrain analysis. Principles and applications [M]. Wiley, NewYork,2000.
[76] Zhao KL, Liu XM, Zhang WW, Xu JM, Wang F. Spatial dependence andbioavailability of metal fractions in paddy fields on metal concentrations in rice grainat a regional scale [J]. Journal of Soils and Sediments,2011,11:1165-1177
[77]杨奇勇,杨劲松,刘广明.土壤速效养分空间变异的尺度效应[J].应用生态学报,2011,22:431-436.
[78] Zimmerman D, Pavlik C, Ruggles A, Armstrong MP. An experimental comparison ofordinary and universal kriging and inverse distance weighting [J]. MathematicalGeolog,1999,31:375–390
[79] Chaplot V, Darboux F, Bourennane H, Leguédois S, Silvera N, Phachomphon K.Accuracy of interpolation techniques for the derivation of digital elevation models inrelation to landform types and data density [J]. Geomorphology,2006,77:126-141.
[80]Sun Y, Kang SZ, Li FS, Zhang L. Comparison of interpolation methods for depth togroundwater and its temporal and spatial variations in the Minqin oasis of northwestChina [J]. Environmental Modelling and Software,2009,24:1163-1170.
[81] Cressie N. Statistics for Spatial Data [M]. JohnWiley and Sons, Inc., New York,1993.
[82] Wu J, Norvell WA, Welch RM. Kriging on highly skewed data for DTPA-extractablesoil Zn with auxiliary information for pH and organic carbon [J]. Geoderma,2006,134:187-199.
[83] Li J, Heap AD. A review of comparative studies of spatial interpolation methods inenvironmental sciences: Performance and impact factors [J]. Ecological Informatics,2011,6:228-241.
[84] Schloeder CA, Zimmerman NE, Jacobs MJ. Comparison of methods for interpolatingsoil properties using limited data [J]. Soil Science Society of America Journal,2001,65:470-479.
[85] Wollenhaupt NC, Wolkowski RP, Clayton MK. Mapping soil test phosphorus andpotassium for variable-rate fertilizer application [J]. Journal of ProductionAgricultural,1994,7:441-448.
[86] Mueller TG, Pierce FJ, Schabenberger O, Warncke DD. Map quality for site-specificfertility management [J]. Soil Science Society of America Journal,2001,65:1547-1558.
[87]刘庆,孙景宽,陈印平,夏江宝.不同采样尺度下土壤重金属的空间变异特征[J].土壤通报,40:1406-1410.
[88] Garten Jr CT, Kang S, Brice DJ, Schadt CW, Zhou J. Variability in soil properties atdifferent spatial scales (1m–1km) in a deciduous forest ecosystem [J]. Soil Biologyand Biochemistry,2007,39:2621-2627.
[89] Western AW, Bl schl G, Grayson RB. Geostatistical characterisation of soil moisturepatterns in the Tarrawarra Catchment [J]. Journal of Hydrology,1998,205:20-37.
[90] Western AW, Bl schl G. On the spatial scaling of soil moisture [J]. Journal ofHydrology,1999,217:203-224.
[91] Klute A, Dirksen C. Hydraulic conductivity and diffusivity [A]. In: Klute A (ed),Methods of soil analysis [C], Part1. Soil Science Society of America Madison9,1986.687-734.
[92] Reynolds WD, Bowman BT, Brunke RR, Drury CF, Tan CS. Comparison of tensioninfiltrometer, pressure infiltrometer, and soil core estimates of saturated hydraulicconductivity [J]. Soil Science Society of American Journal,2000,64:478-484.
[93] Sidiras N, Roth CH. Infiltration rate, measured with double-ring infiltrometers and arainfall simulator, as affected by the amount of mulch and the tillage system [J]. Soiland Tillage Research,1987,9:161-168.
[94] Reynolds WD, Elrick DE. In-situ measurement of field-saturated hydraulicconductivity, sorptivity and the α-parameter using the Guelph permeameter [J]. SoilScience,1985,140:292-302.
[95] Abbaspour KC, van Genuchten MTh, Schulin R, Schl ppi E. A sequential uncertaintydomain inverse procedure for estimating subsurface flow and transport parameters [J].Water Resources Research,1997,33:1879-1892.
[96] Sobieraj JA, Elsenbeer H, Vertessy RA. Pedotransfer functions for estimatingsaturated hydraulic conductivity: implications for modeling storm flow generation [J].Journal of Hydrology,2001,251:202-220.
[97] Moustafa MM. A geostatistical approach to optimize the determination of saturatedhydraulic conductivity for large-scale subsurface drainage design in Egypt [J].Agricultural Water Management,2000,42:291-312.
[98]唐克丽,侯庆春,王斌科,张平仓.黄土高原水蚀风蚀交错带和神木试区的环境背景及整治方向[M].中科院西北水土保持研究所集刊,1993,第18集:2-15.
[99] Wang YQ, Shao MA. Spatial variability of soil physical properties in a region of theLoess Plateau of PR China subject to wind and water erosion [J]. Land Degradationand Development,2011, DOI:10.1002/ldr.1128.
[100] Wang YQ, Shao MA, Gao L. Spatial variability of soil particle size distribution andfractal features in Water-Wind Erosion Crisscross Region on the Loess Plateau ofChina [J]. Soil Science,2010,175:579-585.
[101]刘孝义.土壤物理及土壤改良研究法[M].上海:上海科学技术出版社,1982.
[102] Nielsen D, Bouma J. Soil spatial variability. Proceedings of a Workshop of the ISSSand the SSSA in Las Vegas, Pudoc, Wageningen, Netherlands,1985.
[103] Murphy AH. The coefficients correlation and determination as measures ofperformance in forecast verification [J]. Weather Forecast,1995,10:681-688.
[104] Obled C, Wendling J, Beven K. The sensitivity of hydrological models to spatialrainfall patterns: an evaluation using observed data [J]. Journal of Hydrology,1994,159:305-333.
[105] Cambardella C, Mooman TB, Novak JM, Parkin TB, Karlem DL, Turvo RF, KonopaAE. Field scale variability of soil properties in central Iowa soil [J]. Soil ScienceSociety of America Journal,1994,47:1501-1511.
[106] Choi M, Jacobs JM. Soil moisture variability of root zone profiles within SMEX02remote sensing footprints [J]. Advances in Water Resources,2007,30:883-896.
[107] Korsunskaya LP, Gummatov NG, Pachepsky YaA. Seasonal changes in root biomass,carbohydrate content, and structural characteristics of Gray Forest soil [J]. EurasianSoil Science,1995,27:45-52.
[108] Ceballos A, Martínez-Fernández J, Santos F, Alonso P. Soil-water behavior of sandysoils under semi-arid conditions in the Duero Basin (Spain)[J]. Journal of AridEnvironments,2002,51,501-519.
[109] Bi HX, Li XY, Liu X, Guo MX, Li J. A case study of spatial heterogeneity of soilmoisture in the Loess Plateau, western China: A geostatistical approach [J]. Journal ofSedimentary Research,2009,24:63-73.
[110] Western AW, Zhou SL, Grayson RB, McMahon TA, Bl schl G, Wilson DJ. Spatialcorrelation of soil moisture in small catchments and its relationship to dominantspatial hydrological processes [J]. Journal of Hydrology2004,286:113-134.
[111] Nyberg L. Spatial variability of soil water content in the covered catchment atGardsj n, Sweden [J]. Hydrological Processes,1996,10:89-103.
[112] Wang YQ, Shao MA, Shao HB. A preliminary investigation of the dynamiccharacteristics of dried soil layers on the Loess Plateau of China [J]. Journal ofHydrology,2010,381:9-17.
[113] Chen H.S, Shao MA, Li YY. The characteristics of soil water cycle and waterbalance on steep grassland under natural and simulated rainfall conditions in theLoess Plateau of China [J]. Journal of Hydrology,2008,360:242-251.
[114]杨文治,邵明安.黄土高原土壤水分研究[M].北京:科学出版社,2000.
[115] Grayson RB, Western AW, Chiew HS, Bl schl G. Preferred states in spatial soilmoisture patterns: local and nonlocal controls [J]. Water Resources Research,1997,33:2897-2908.
[116] Bouten W, Heimovaara TJ, Tiktak A. Spatial patterns of throughfall and soil waterdynamics in a Gouglas fir stand [J]. Water Resources Research,1992,28:3227-3233.
[117] Jost G, Heuvelink GBM, Papritz A. Analysing the space–time distribution of soilwater storage of a forest ecosystem using spatio-temporal kriging [J]. Geoderma,2005,128:258-273.
[118] Richards JH, Caldwell MM. Hydraulic lift: substantial nocturnal water transportbetween soil layers by Artemisia tridentata roots [J]. Oecologia,1987,73:486-489.
[119] Turner NC. Stomatal behavior and water status of maize, sorghum, and tobaccounder field conditions. Plant Physiology,1974,53:360-365.
[120] Warrick AW. Soil Water Dynamics [M]. New York, Oxford University Press,2003.
[121] Smart DR, Carlisle E, Goebel M, Nunez BA. Transverse hydraulic redistribution by agrapevine. Plant, Cell and Environment,2005,28:157-166.
[122] Smith DM, Jackson NA, Roberts JM, Ong CK. Reverse flow of sap in tree roots anddownward siphoning of water by Grevillea robusta [J]. Functional Ecology,1999,13:256-264.
[123] Gómez-Plaza A, Martinez-Mena M, Albaladejo J, Castillo VM. Factors regulatingspatial distribution of soil water content in small semi-arid catchments [J]. Journal ofHydrology,2001,253:1261-1277.
[124] de Souza ER, Montenegro AAdA, Montenegro SMG, de Matos JdA. Temporalstability of soil moisture in irrigated carrot crops in Northeast Brazil [J]. AgriculturalWater Management,2011,99:26-32.
[125] Hébrard O, Voltz M, Andrieux P, Moussa R. Spatio-temporal distribution of soilsurface moisture in a heterogeneously farmed Mediterranean catchment [J]. Journal ofHydrology,2006,329:110-121.
[126] Zhao Y, Peth S, Hallett P, Wang XY, Giese M, Gao YZ. Factors controlling thespatial patterns of soil moisture in a grazed semi-arid steppe investigated bymultivariate geostatistics [J]. Ecohydrology,2011,4:36-48.
[127] Nakano K, Miyazaki T. Predicting the saturated hydraulic conductivity of compactedsub-soils using the non-similar media concept [J]. Soil and Tillage Research,2005,84:145-153.
[128] She DL, Shao MA. Spatial variability of soil organic C and total N in a smallcatchment of the Loess Plateau, China [J]. Acta Agriculturae Scandinavica, SectionB-Soil and Plant Science,2009,59:514-524.
[129] Peters-Lidard CD, Pan F, Wood EF. A re-examination of modeled and measured soilmoisture spatial variability and its implications for land surface modeling [J].Advances in Water Resources,2001,24:1069-1083.
[130] Ma KM, Fu BJ, Liu SL, Guan WB, Liu GH, LV YH, Anand M. Multiple-scale soilmoisture distribution and its implications for ecosystem restoration in an arid rivervalley, China [J]. Land Degradation and Development,200415:75-78.
[131] Wang CM, Zuo Q, Zhang RD. Estimating the necessary sampling size of surface soilmoisture at different scales using a random combination method [J]. Journal ofHydrology,2008,352:309-321.
[132] Hu W, Shao MA, Wang QJ, Reichardt K. Soil water content temporal-spatialvariability of the surface layer of a Loess Plateau hillside in China [J]. ScientiaAgricola,2008,65:277-289.
[133] Wang YQ, Shao MA, Zhu YJ, Liu ZP. Impacts of land use and plant characteristicson dried soil layers in different climatic regions on the Loess Plateau of China [J].Agricultural and Forest Meteorology,2011,151:437-448.
[134] Jenkins GM, Watts DG. Spectral analysis and its applications [M]. Holden–Day, SanFrancisco,1968.
[135] Vanmarcke E. Random Fields: Analysis and Synthesis [M]. The MIT Press,Cambridge, Massachusetts,1983.
[136] Sigua GC, Hudnall WH. Kriging analysis of soil properties [J]. Journal of Soils andSediments,2008,8:193-202.
[137]文波龙,刘兴土,张乃明.滇池大清河流域农田土壤磷素空间变异特征及对地表径流的影响[J].土壤学报,2012,49:173-178.
[138] Wang YQ, Zhang XC, Huang CQ. Spatial variability of soil total nitrogen and soiltotal phosphorus under different land uses in a small watershed on the Loess Plateau,China [J]. Geoderma,2009,150:141-149.
[139] Liu ZP, Shao MA, Wang YQ. Effect of environmental factors on regional soilorganic carbon stocks across the Loess Plateau region, China [J]. Agriculture,Ecosystems and Environment,2011,142:184-194.
[140]肖波,王庆海,李翠,曹志德.黄土高原退耕地复垦对土壤理化性状及空间变异特征的影响[J].西北农林科技大学学报(自然科学版),2011,39:185-192.
[141] Treasurer JW, Pope JA. Selection of host sample number and design of a monitoringprogramme for ectoparasitic sea lice (Copepoda: Caligidae) on farmed Atlanticsalmon, Salmo salar [J]. Aquaculture,2000,187:247-260.
[142] Mcbratney AB, Webster R. How many observations are needed for regionalestimation of soil properties [J]? Soil Science,1983,135:177-183.
[143] Park SJ, van de Giesen N. Soil-landscape delineation to define spatial samplingdomains for hillslope hydrology [J]. Journal of Hydrology,2004,295:28-46.
[144] Bishop TFA, McBratney AB. A comparison of prediction methods for the creation offield-extent soil property maps [J]. Geoderma,2001,103:149-160.
[145] Hirzel A, Guisan A. Which is the optimal sampling strategy for habitat suitabilitymodeling [J]? Ecological Modelling,2002,157:331-341.
[146] Voltz M, Webster R. A comparison of kriging, cubic splines and classification forpredicting soil properties from sample information [J]. Journal of Soil Science,1990,41:473-490.
[147] Shi Z, Wang K, Bailey JS, Jordan C, Higgins AJ. Sampling strategies for mappingsoil phosphorus and soil potassium distribution in cool temperate grassland [J].Precision Agriculture,2000,2:347-357.
[148] Kravchenko AN. Influence of spatial structure on accuracy of interpolation methods[J]. Soil Science Society of America Journal,2003,67:1564-1571.
[149] Mollitor AV, Leaf AL, Morris LA. Forest soil variability on northeastern flood plains[J]. Soil Science Society of America Journal,1980,44:617-620.
[150] Romano N. Use of an inverse method and geostatistics to estimate soil hydraulicconductivity for spatial variability analysis [J]. Geoderma,1993,60:169-186.
[151] Logsdon SD. Determination of preferential flow model parametres [J]. Soil ScienceSociety of America Journal,2002,66:1095-1103.
[152] Mohanty BP, Mousli Z. Saturated hydraulic conductivity and soil water retentionproperties across a soil-slope transition [J]. Water Resources Research,2000,36:3311-3324.
[153] Zimmermann B, Elsenbeer H. Spatial and temporal variability of soil saturatedhydraulic conductivity in gradients of disturbance [J]. Journal of Hydrology,2008,361:78-95.
[154] Journel AG. The lognormal approach to predicting local distributions of selectivemining unit grades [J]. Mathematical Geology,1980,12:285-303.
[155] Saito H, Goovaerts P. Geostatistical interpolation of positively skewed and censoreddata in a dioxin-contaminated site [J]. Environmental Science and Technology,2000,34:4228-4235.
[156] Rawls WJ, Gimenez D, Grossman R. Use of soil texture, bulk density, and slope ofthe water retention curve to predict saturated hydraulic conductivity [J]. Transactionsof the ASABE,1998,41:983-988.
[157] D rner J, Dec D, Peng X, Horn R. Effect of land use change on the dynamicbehaviour of structural properties of an Andisol in southern Chile under saturated andunsaturated hydraulic conditions [J]. Geoderma,2010,159:189-197.
[158] Wang YQ, Shao MA, Liu ZP, Warrington DN. Investigation of factors controlling theregional-Scale distribution of dried soil layers under forestland on the Loess Plateau,China [J]. Surveys in Geophysics,2012,33:311-330.
[159] Kerry R, Oliver MA. Comparing sampling needs for variograms of soil propertiescomputed by the method of moments and residual maximum likelihood [J]. Geoderma,2007,140:383-396.
[160] Gelhar LW. Stochastic Subsurface Hydrology. Prentice Hall, Englewood Cliffs [M],NJ,1993.
[161] Bl schl G. Scale and Scaling in Hydrology–a framework for thinking and analysis[M]. John Wiley, Chichester,1998.
[162] Lauren JG, Wagnet RJ, Bouma J, Wosten JHM. Variability of saturated hydraulicconductivity in a glossaquic hapludalf with macropores [J]. Soil Science,1988,145:20-28.
[163] Rodríguez-Iturbe I, Vogel GK, Rigon R, Entekhabi D, Castelli F, Rinaldo A. On thespatial organization of soil moisture fields [J]. Geophysical Research Letters,1995,22:2757-2760.