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土壤水分特性的分形特征与传递函数研究
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摘要
研究土壤特性的空间变异性对于推动农业、土壤和水科学等学科的发展和应用具有重要的科学意义。研究尺度不同时,土壤特性的空间变异特征有较大差异,主要影响因素和过程也不一定完全相同,多尺度分析能更深入地揭示土壤特性空间变异性的机理。此外,不同土层土壤水力特性参数的空间变异性及其与影响因素的尺度相关性不一定完全相同,不同土层土壤特性空间变异性之间可能存在某种程度的相互关系。为此,论文依托国家科技支撑计划项目(2006BAD11B04)和国家自然科学基金项目(50879072),以杨凌地区为例,利用多重分形方法研究分析不同土层土壤含水率、土壤电导率、土壤基本物理特性、土壤粒径分布分形维数、土壤水分特征曲线和土壤入渗特性的空间变异性;利用联合多重分形方法研究分析田间土壤粒径分布分形维数、土壤水分特征曲线、土壤入渗特性等土壤水分运动参数与影响因素在多尺度上的相关性,并基于上述分析得出的联合多重分形结论建立考虑尺度效应的田间尺度上上述参数的土壤传递函数;探索了田间尺度向区域尺度转换的方法,即将田间尺度上得出的联合多重分形结论应用到区域尺度上,建立区域尺度上土壤水分运动参数的土壤传递函数;同时探讨分析不同土层土壤含水率、土壤电导率、土壤基本物理特性、土壤粒径分布分形维数、土壤水分特征曲线空间变异性之间的相互关系。主要得出以下结论:
     (1)研究区域内土壤含水率、土壤电导率、砂粒含量、粘粒含量、有机质含量、稳定入渗率、前30min累积入渗量和van Genuchten模型参数α的多重分形特征比较明显;粗粉粒含量、土壤容重、土壤粒径分布分形维数、van Genuchten模型参数n和θs的多重分形特征不明显。
     (2)利用多重分形方法研究分析了土壤含水率、土壤电导率、土壤基本物理特性、土壤粒径分布分形维数、van Genuchten模型参数和土壤入渗特性的空间变异性,确定了引起上述研究对象空间变异性的局部信息,可为分析上述参数的空间变异性及尺度效应和深入揭示其空间变异机理等提供方法借鉴和参考。
     研究区域内土壤含水率和土壤电导率的空间变异性都分别随土壤含水率和土壤电导率平均值的增大而减弱。土壤含水率和土壤电导率的平均值不同时,土壤含水率和土壤电导率空间变异性的尺度效应都有所差异。土壤含水率和土壤电导率的平均值较大时,随着采样面积的增大,土壤含水率的空间变异性逐渐增强,土壤电导率的空间变异性很弱;土壤含水率和土壤电导率的平均值较小时,随着采样面积的增大,土壤含水率和土壤电导率的空间变异性较强,且空间分布中都存在斑块结构。
     土壤基本物理特性的多重分形分析表明,砂粒含量和粘粒含量的空间变异性较强,粗粉粒含量和有机质含量的空间变异性次之,土壤容重的空间变异性最弱;0~20cm土层和20~40cm土层砂粒含量的空间变异性都是由砂粒含量的高值分布造成的,不同土层粘粒含量、有机质含量和粗粉粒含量的空间变异性都是由对应变量的低值分布造成的。
     不同土层土壤粒径分布分形维数的空间变异性都很弱。0~20cm土层和20~40cm土层van Genuchten模型参数α的空间变异性较强,且分别是由其低值和高值分布引起的;参数n和θs的空间变异性较弱。稳定入渗率和前30min累积入渗量的空间变异性较强,其中前30min累积入渗量的空间变异性是由其高值分布造成的。
     (3)利用联合多重分形方法研究分析了田间土壤粒径分布分形维数、van Genuchten模型参数α和n、土壤入渗特性与影响因素在多尺度上的相关性,发现上述参数与影响因素的相关性具有尺度依赖性,在单一尺度和多尺度上的相关性特征并不完全相同。基于得出的联合多重分形结论建立了考虑尺度效应的田间尺度上上述参数的土壤传递函数,验证分析表明建立的土壤传递函数具有较强的理论基础,预测精度较高,可用于估算田间尺度上的上述参数。
     不同土层土壤粒径分布分形维数与土壤颗粒组成的相关特征相似,但土壤粒径分布分形维数与土壤颗粒组成在田间单一尺度和多尺度上的相关特征有所差异。田间单一尺度上,0~20cm和20~40cm土层土壤粒径分布分形维数与粘粒含量、砂粒含量、粗粉粒含量的相关程度依次降低;联合多重分形分析表明,田间多尺度上,不同土层土壤粒径分布分形维数与粘粒含量、粗粉粒含量、砂粒含量的相关程度依次降低。基于联合多重分形结论建立的考虑尺度效应的田间尺度上0~20cm和20~40cm土层土壤粒径分布分形维数的土壤传递函数具有较强的理论基础和适应性,预测精度很高,预测值的RMSE分别为0.0134和0.0117,可用于估算田间尺度上的土壤粒径分布分形维数。
     不同土层van Genuchten模型参数α、n与影响因素之间的相关特征不完全相同;van Genuchten模型参数α、n与影响因素相关的相关性特征,在田间单一尺度和多尺度上不完全相同。田间单一尺度上,0~20cm土层van Genuchten模型参数α与砂粒含量、粗粉粒含量之间的相关性最显著,参数n与砂粒含量、有机质含量之间的相关性最显著;20~40cm土层参数α与有机质含量之间的相关性最显著,参数n与砂粒含量、粗粉粒含量、有机质含量之间的相关性最显著。联合多重分形分析表明,田间多尺度上,0~20cm土层参数α与砂粒含量、粗粉粒含量之间的相关性最显著,参数n与砂粒含量、粘粒含量、有机质含量之间的相关性最显著;20~40cm土层参数α与土壤容重、有机质含量之间的相关性最显著,参数n与粗粉粒含量、砂粒含量、有机质含量之间的相关性最显著。基于联合多重分形结论建立的考虑尺度效应的田间尺度上不同土层van Genuchten模型参数α、n的土壤传递函数具有较强的理论基础,预测精度较高,其中利用0~20cm土层van Genuchten模型参数α、n的土壤传递函数预测的土壤含水量的RMSE为0.0386,利用20~40cm土层van Genuchten模型参数α、n的土壤传递函数预测的土壤含水量的RMSE为0.0473,可用于估算田间尺度上的van Genuchten模型参数α和n。
     土壤入渗特性与影响因素在田间单一尺度和多尺度上的相关特征并不完全相同。田间单一尺度上,稳定入渗率、前30min累积入渗量分别都与粗粉粒含量和粘粒含量的相关程度最高;联合多重分形分析表明,田间多尺度上,稳定入渗率与土壤容重、粗粉粒含量和粘粒含量之间的相关程度最高,前30min累积入渗量与粗粉粒含量和粘粒含量之间的相关程度最高。基于联合多重分形结论建立的考虑尺度效应的田间尺度上稳定入渗率和前30分钟累积入渗量的土壤传递函数具有较强的理论基础,预测精度较高,稳定入渗率和前30分钟累积入渗量土壤传递函数预测值的RMSE分别为0.1432和0.8019,可用于估算田间尺度上的土壤入渗特性。
     (4)探索了田间尺度向区域尺度转换的问题,即将田间尺度上土壤粒径分布分形维数、van Genuchten模型参数α和n、土壤入渗特性与影响因素之间的联合多重分形分析得出的结论进行尺度扩展,应用到区域尺度上,建立考虑尺度效应的区域尺度上上述参数的土壤传递函数。结果表明,可以将在田间尺度上得出的联合多重分形结论应用到区域尺度上,建立区域尺度上上述参数的土壤传递函数,基于此建立的土壤传递函数的预测精度较高,可用于估算较大尺度上的上述参数,这可为构建考虑尺度效应的区域尺度上上述参数的土壤传递函数提供方法借鉴和参考。
     区域尺度上,0~20cm土层和20~40cm土层土壤粒径分布分形维数的土壤传递函数的预测精度很高,预测值的RMSE分别为0.0129和0.0111。不同土层van Genuchten模型参数α、n土壤传递函数的预测精度较高,其中利用0~20cm土层和20~40cm土层van Genuchten模型参数α、n的土壤传递函数预测的土壤含水量的RMSE分别为0.0270和0.0304。稳定入渗率和前30分钟累积入渗量土壤传递函数的预测精度较高,预测值的RMSE分别为0.1855和0.9823。这说明建立的土壤传递函数可用于估算较大尺度上的上述参数,且具有较强的理论基础,可为构建考虑尺度效应的区域尺度上上述参数的土壤传递函数提供方法借鉴和。
     (5)利用联合多重分形方法研究分析了不同土层土壤特性空间变异性之间的相互关系,研究结果可为探讨不同土层土壤特性空间变异性之间的相互关系提供方法借鉴。研究区域内0~20cm土层土壤含水率、土壤容重、van Genuchten模型参数n和θs的空间变异性与20~40cm土层对应变量空间变异性之间的相互关系非常密切;0~20cm土层土壤电导率、砂粒含量、粘粒含量、有机质含量、土壤粒径分布分形维数和van Genuchten模型参数α与20~40cm土层对应变量空间变异性之间的相互关系比较密切;0~20cm土层粗粉粒含量的空间变异性与20~40cm土层粗粉粒含量空间变异性之间的相互关系不密切。
     论文研究结果可为研究揭示造成空间变异性的局部信息和深入分析研究对象的空间变异性机理等提供方法借鉴;可为识别在多尺度上对土壤水分运动参数都具有显著影响的因素,以及基于多尺度分析得出的结论建立考虑尺度效应的土壤水分运动参数的土壤传递函数等提供方法借鉴和参考;可为探索田间尺度向区域尺度的转换问题,即利用田间尺度上土壤水分运动参数与影响因素的联合多重分形结论,构建考虑尺度效应的区域尺度土壤水分运动参数的土壤传递函数提供方法借鉴和理论依据;可为深入分析不同土层土壤特性空间变异性之间的相互关系提供方法借鉴,同时也可为其它区域类似研究提供方法借鉴和参考。鉴于该研究的复杂性和时间限制,还需在以下几个方面展开深入研究:土壤特性的空间变异性是一个复杂问题,论文对造成土壤特性空间变异性的机理和物理解释还不够深入,在时间方面的变异性研究也尚且不足;研究区域和研究尺度不同时,论文中的一些规律和趋势有待于进一步研究和验证;基于田间尺度上土壤水分运动参数与影响因素的联合多重分形结论建立区域尺度上土壤水分运动参数土壤传递函数的可行性还有待于进一步研究;论文只是分析了上下两层土壤特性空间变异性之间的相互关系,多层土壤特性空间变异性之间的相互关系还有待于进一步深入分析;进一步研究离心机法测定土壤水分特征曲线过程中土壤容重的变化,对土壤水分特征曲线与影响因素尺度相关性的影响;如何将研究区域内土壤特性的时空变异性与作物生长有机结合起来,实施“精准农业”有待于进一步研究。
Study on spatial variability of soil properties had great significance in promoting the development and application of agriculture, soil and water science. When scale was different, spatial variability of soil properties was different, main factors and processes were also different, and mechanism of spatial variability of soil properties could be disclosed deeply with multi-scale analysis. Furthermore, spatial variability of soil properties in different soil layers and scale correlation between them and factors were not necessarily identical, and correlation of different degree between spatial variability of soil properties in different soil layers could exist. So the paper depended on National Key Technology R&D Program(2006BAD11B04) and National Natural Science Foundation of China(50879072), and firstly studied spatial variability of soil water, soil electrical conductivity, soil basic physical properties, fractal dimension of soil particle-size distribution, soil water retention curve in different soil layers and soil infiltration characteristics at the multiple scales with multifractal method; then studied scale dependency between fractal dimension of soil particle-size distribution, soil water retention curve and soil infiltration characteristics and their factors at the multiple scales with joint multifractal method, and established their pedo-transfer functions considering scale effect based on conclusions educed with joint multifractal analysis at the field scale; explored conversion from field scale to region scale, namely, conclusions educed with joint multifractal analysis at the field scale were applied at the region scale, and established pedo-transfer functions of soil water movement parameters at the region scale; at the same time, analyzed correlation between spatial variability of soil water, soil electrical conductivity, soil basic physical properties, fractal dimension of soil particle-size distribution, soil water retention curve in different soil layers. The main conclusions were as follows:
     (1)In the studied area, the multifractal characteristics of soil water, soil electrical conductivity, sand content, clay content, organic matter content, stable infiltration rate, cumulative infiltration within initial 30 min and parameterαin van Genuchten model were obvious, and the multifractal characteristics of silt content, bulk density, fractal dimension of soil particle-size distribution, parameter n andθs in van Genuchten model were not obvious.
     (2)Spatial variability of soil water, soil electrical conductivity, soil basic physical properties, fractal dimension of soil particle-size distribution, van Genuchten model parameters and soil infiltration characteristics were studied with multifractal method, and local information that caused their spatial variability were also identified, which could provided methods reference for studying spatial variability, its scale effect and disclosing spatial variability mechanism of parameters mentioned above.
     Spatial variability of soil water and electrical conductivity decreased with the increase of average of water content and electrical conductivity. When average of water content and electrical conductivity was different, scale effect of soil water content and electrical conductivity was obviously different. As sampling area increased, when average of soil water content and electrical conductivity were high, spatial variability of soil water became large, spatial variability of soil electrical conductivity was very weak; when average of soil water content and electrical conductivity were low, spatial variability of soil water and electrical conductivity was high, and their spatial distribution had obvious patch structure.
     Multifractal analysis of soil basic physical properties showed that spatial variability of sand and clay was strong, spatial variability of silt and organic matter content took second place, and spatial variability of bulk density was weakest; spatial variability of sand content in 0~20cm and 20~40cm soil layer was caused by its high value, and spatial variability of clay, organic matter and silt content was caused respectively by their low value.
     Spatial variability of fractal dimension of soil particle-size distribution was very weak. Spatial variability parameterαin van Genuchten model in 0~20cm and 20~40cm soil layer was strong, its spatial variability were caused recpectively by its low and high value, and parameter n andθs in van Genuchten model were weak. Spatial variability of stable infiltration rate and cumulative infiltration within initial 30 min were strong, and spatial variability of cumulative infiltration within initial 30 min was caused by its high value.
     (3)Correlation characteristics between fractal dimensions of soil particle-size distribution, parameterαandnin van Genuchten model and soil infiltration and factors at the multiple scales were studied with joint multifractal method, which showed that correlation characteristics between parameters mentioned above and factors had scale dependency, and their correlation characteristics were not completely same at the single and multiple scales. Pedo-transfer functions of parameters mentioned above considering scale effect at the field scale that were established based on conclusions educed through joint multifractal analysis between them and factors. Validation anslysis showed that these pedo-transfer functions had strong theoretical foundation, high precision, and could be used to estimate parameters mentioned above at the field scale.
     Correlation characteristics between fractal dimensions of soil particle-size distribution and soil particle composition in different soil layers were same, however, correlation characteristics between fractal dimensions of soil particle-size distribution and soil particle composition were different at the single and multiple scales in the field. At the single scale, in 0~20cm and 20~40cm soil layers, correlation degree between fractal dimension of soil particle-size distribution and clay content was highest, correlation degree between fractal dimension of soil particle-size distribution and sand content took second place, and correlation degree between fractal dimension of soil particle-size distribution and silt content was lowest; at the multiple scales, in 0~20cm and 20~40cm soil layers, correlation degree between fractal dimension of soil particle-size distribution and clay content was highest, correlation degree between fractal dimension of soil particle-size distribution and silt content took second place, and correlation degree between fractal dimension of soil particle-size distribution and sand content was lowest. Pedo-transfer functions of fractal dimension of soil particle-size distribution in 0~20cm and 20~40cm soil layers parameters considering scale effect at the field scale that were established based on conclusions educed through joint multifractal analysis had strong theoretical foundation, application, high precision, RMSE of fractal dimension of soil particle-size distribution predicited with pedo-transfer functions was repectively 0.0134 and 0.0117, and these pedo-transfer functions could be used to estimate fractal dimension of soil particle-size distribution at the field scale.
     Correlation characteristics between parameterαand n in van Genuchten model and factors in different soil layers were different, and correlation characteristics parameterαand n in van Genuchten model and soil basic physical properties were also different at the single and multiple scales in the field. At the single scale, in 0~20cm soil layer, correlations between parameterαand sand and silt content were remarkable, and correlations between parametern and sand and organic matter were significant; in 20~40cm soil layers, correlation between parameterαand organic matter was significant, and correlations between parametern and sand, silt and organic matter were remarkable. At the multiple scales, in 0~20cm soil layer, correlations between parameterαand sand and silt content were remarkable, and correlations between parametern and sand, clay and organic matter content were remarkable; in 20~40cm soil layers, correlations between parameterαand bulk density and organic matter content were significant, and parametern and silt, sand and organic matter content were significant. Pedo-transfer functions of parameterαandnin van Genuchten model in 0~20cm and 20~40cm soil layers considering scale effect at the field scale that were established based on conclusions educed through joint multifractal analysis had strong theoretical foundation and high precision, RMSE of soil water predicited with pedo-transfer functions of parameterαandnin van Genuchten model in 0~20cm and 20~40cm soil layers was respectively 0.0386 and 0.0473, and thes pedo-transfer functions could be used to estimate fractal dimension of parameterαandnin van Genuchten model at the field scale.
     Correlation characteristics between soil infiltration characteristics and factors were different at the single and multiple scales in the field. At the single scale, correlations between stable infiltration rate and silt and clay content were most significant, and correlations between cumulative infiltration within initial 30 min and silt and clay content were also most remarkable; at the multiple scales, correlations between stable infiltration rate and bulk density, silt and clay content were most remarkable, and orrelations between cumulative infiltration within initial 30 min and silt and clay content were also most significant. Pedo-transfer functions of stable infiltration rate and cumulative infiltration within initial 30 min considering scale effect at the field scale that were established based on conclusions educed through joint multifractal analysis had strong theoretical foundation and high precision, RMSE of stable infiltration rate and cumulative infiltration within initial 30 min predicited with pedo-transfer functions was respectively 0.1432 and 0.8019, and these pedo-transfer functions could be used to estimate soil infiltration characteristics fractal dimension of parameterαandnin van Genuchten model at the field scale.
     (4)Conclusions educed through joint multifractal analysis between fractal dimensions of soil particle-size distribution, parameterαand n in van Genuchten model and soil infiltration characteristics and factors at the field scale were applied at the region scale, based on conclusions mentioned above, pedo-transfer functions of fractal dimensions of soil particle-size distribution, parameterαand n in van Genuchten model and soil infiltration characteristics considering scale effect at the region scale were established. The results showed conclusions educed through joint multifractal analysis at the field scale could be applied at the region scale, and established pedo-transfer functions of fractal dimensions of soil particle-size distribution, parameterαandnin van Genuchten model and soil infiltration characteristics at the region scale based on these conclusions, which had also high precision and could be used to estimate fractal dimensions of soil particle-size distribution, parameterαandnin van Genuchten model and soil infiltration characteristics at the large scale. The result could provide methods reference for constructing pedo-transfer functions of parameters mention above.
     At the region scale, forecasting precision of pedo-transfer functions of fractal dimensions of soil particle-size distribution in 0~20cm and 20~40cm soil layers were very high, and RMSE were respectively 0.0129 and 0.0111. Forecasting precision of pedo-transfer functions of parameterαand n in van Genuchten model in different soil layer were high, RMSE of soil water content forecasted based on pedo-transfer functions of parameterαandnin van Genuchten model in 0~20cm and 20~40cm was respectively 0.0270 and 0.0304. Forecasting precision of pedo-transfer functions of stable infiltration rate and cumulative infiltration within initial 30 min were high, and RMSE were respectively 0.1855 and 0.9823. The results showed that established pedo-transfer functions could be used to estimate parameters mention above at the large scale,and had strong theoretical foundation, which could provide references for constructing pedo-transfer functions of parameters mention above considering scale effect at the large scale. In order to improve them applicability and precision, it was necessary to establish pedo-transfer functions based on conclusions educed at the multiple scales.
     (5)Relationship between spatial variability of soil properties in different soil layers were studied with joint multifractal method, and results could provide method reference for exploring correlation between spatial variability of different soil properties in different soil layers.
     In studied area, relationship between spatial variability of soil water, bulk density, parameterθs and n in van Genuchten model in 0~20cm soil layer and their spatial variability in 20~40cm soil layer were very close; relationship between spatial variability of soil electrical conductivity, sand content, clay content, organic matter content, fractal dimension of soil particle-size distribution and parameterαin van Genuchten model in 0~20cm soil layer and their spatial variability in 20~40cm soil layer were close; relationship between spatial variability of silt content in 0~20cm soil layer and its spatial variability in 20~40cm soil layer was not close.
     The results provided method reference for disclosing local information leading to spatial variability of soil properties and analyzing deeply mechanism of spatial variability of soil properties; supplied method reference for identifying factors that had significant effects on soil water movement parameters at the different scale and establishing pedo-transfer functions of soil water movement parameters considering scale effect based on conclusions educed with muti-scale analysis; provided method reference for exploreing conversion from field scale to region scale, namely, constructing pedo-transfer functions of soil water movement parameters considering scale effect at the region scale based on conclusions educed through joint multifractal analysis; supplied method reference for analyzing deep correlation between spatial variability of soil properties in different soil layers and carrying out similar study at the other region. Given the complexity of the study and time constraints, questions that need be studied deep in future included: spatial variability of soil properties was a comples problem, physical explanation on factors and processes leading to spatial variability of soil properties was not thorough enough, and studies on temporal variability of soil properties was also not enough; when study area and scale were different, law and trendency in the paper need be further studied and validated; feasibility of constructing pedo-transfer functions of soil water movement parameters considering scale effect at the region scale based on conclusions educed through joint multifractal analysis at the field scale needed to be further studied; the paper only analyzed correlation between spatial variability of soil properties in the upper and lower soil layer, and correlation between spatial variability of soil properties in different soil layer needed to be analyzed deep; bulk density of sample would change in the process of measuring soil water retention curve was measured with centrifuge method, which could had some effects on conclusions, so scale correlation between soil water retention curve and factors need to be further validated; it need further study how to combine spatial and temporal variability of soil properties and crop growth in the studied area and implement“precision agriculture”.
引文
白玉,张玉龙.2008.半干旱地区风沙土水分特征曲线V.G.模型参数的空间变异性.沈阳农业大学学报,39(3):318~323
    蔡阿兴,陈章英,蒋正琦,宋荣华. 1997.我国不同盐渍地区盐分含量与电导率的关系.土壤,1:54~57
    曹汉强,朱光喜,李旭涛,夏文芳.2004.多重分形及其在地形特征分析中的应用.北京航空航天大学学报,30(12):1182~1185
    陈伏生,曾德慧,陈广生,范志平. 2003.不同土地利用方式下沙地土壤水分空间变异规律.生态学杂志,22(6):43~48
    陈双平,韩凯,马猛,王煦法.2008.染色体碱基序列的联合多重分形分析.电子与信息学报,30(2):298~301
    陈亚新,史海滨,田圃德,刘贵义,张建国. 2000.水盐空间变异性监测的条件模拟.水利学报, 6:67~73
    陈彦光,周一星. 2001.豫北地区城镇体系空间结构的多分形研究.北京大学学报:自然科学版,37(6):810~818
    程冬兵,蔡崇法,彭艳平,莫琼. 2009.根据土壤粒径分形估计紫色土水分特征曲线.土壤学报,46(1):30~36
    慈恩,杨林章,程月琴,马力. 2009.不同耕作年限水稻土土壤颗粒的体积分形特征研究.土壤,2009,41(3):396~401
    杜华强,汤孟平,周国模,徐文兵,刘恩斌,施拥军. 2007.天目山物种多样性尺度依赖及其与空间格局关系的多重分形.生态学报,27(12):5038~5049
    冯娜娜,李廷轩,张锡洲,王永东,夏建国. 2006a.不同尺度下低山茶园土壤有机质含量的空间变异.生态学报,26(2):349~356
    冯娜娜,李廷轩,张锡洲,王永东,廖贵堂. 2006b.不同尺度下低山茶园土壤颗粒组成空间变异性特征.水土保持学报,20(3):123~128
    龚元石,廖超子,李保国. 1998.土壤含水量和容重的空间变异及其分形特征.土壤学报,35(1):10~15
    管孝艳,杨培岭,任树梅,李仙岳,吕烨. 2009.基于多重分形理论的壤土粒径分布非均匀性分析.应用基础与工程科学学报,17(2):196~205
    胡克林,李保国,陈研. 2006.表层土壤饱和导水率的空间变异对农田水分渗漏的影响.水利学报,37(10):1217~1223
    胡克林,李保国,陈德立,White R E. 2001.农田土壤水分和盐分的空间变异性及其协同克立格估值.水科学进展,12(4):460~466
    胡顺军,康绍忠,宋郁东,田长彦,王方. 2004.渭干河灌区土壤水盐空间变异性研究.水土保持学报,18(2):10~12
    胡伟,邵明安,王全九. 2005.黄土高原退耕坡地土壤水分空间变异的尺度性研究.农业工程学报,21(8):11~16
    胡云锋,刘纪远,庄大方,曹红霞,闫慧敏. 2005.不同土地利用/土地覆盖下土壤粒径分布的分维特征.土壤学报,42(2):336~339
    胡振琪,张学礼. 2008.基于ANN的复垦土壤水分特征曲线的预测研究.农业工程学报,24(10):15~18
    黄冠华,谢永华. 1999a.非饱和水分运动参数空间变异与最优估值研究.水科学进展,10(2):101~106
    黄冠华,詹卫华.2002.土壤颗粒的分形特征及其应用.土壤学报,39(4):490~497
    黄冠华. 1999b.土壤水力特性空间变异的试验研究进展.水科学进展,10(4):450~457
    黄元仿,李韵珠. 2002.土壤水力性质的估算——土壤转换函数.土壤学报,39(4):517~523
    黄元仿,周志宇,苑小勇,张红艳. 2004.干旱荒漠区土壤有机质空间变异特征.生态学报,24(12):2776~2781
    贾宏伟,康绍忠,张富仓. 2006a.土壤水力参数的单一参数模型.水利学报,37(3):272~277
    贾宏伟,康绍忠,张富仓,佟玲,姚立民. 2006b.石羊河流域平原区土壤入渗特性空间变异的研究.水科学进展,17(4):471~476
    贾宏伟. 2004.石羊河流域土壤水分运动参数空间分布的试验研究.[硕士学位论文].杨凌:西北农林科技大学
    贾晓红,李新荣,张景光,张志山,王新平,谭会娟. 2006.沙冬青灌丛地的土壤颗粒大小分形维数空间变异性分析.生态学报,26(9):2827~2833
    姜娜,邵明安,雷廷武,张兴昌. 2005a.黄土高原六道沟小流域坡面土壤入渗特性的空间变异研究. 水土保持学报,19(1):14~17
    姜娜,邵明安,雷廷武. 2005b.水蚀风蚀交错带坡面土壤入渗特性的空间变异及其分形特征.土壤学报,42(6):904~908
    姜秋香,付强,王子龙. 2007.黑龙江省西部半干旱区土壤水分空间变异性研究.水土保持学报,21(5):118~122
    蒋勇军,袁道先,谢世友,李林立. 2007.典型岩溶流域土壤有机质空间变异——以云南小江流域为例.生态学报,27(5):2040~2047
    景为. 2004.推求土壤水分运动参数的方法. [硕士学位论文].杨凌:西北农林科技大学
    雷能忠,蒋锦刚,黄大鹏. 2008.杭埠河流域土壤全氮和有机质的空间变异特征.厦门大学学报(自然科学版),47(2):300~304
    雷咏雯,危常州,李俊华,候振安,冶军,鲍柏杨. 2004.不同尺度下土壤养分空间变异特征的研究. 土壤,36(4):376~381
    雷志栋,杨诗秀,谢森传.1988.土壤水动力学.北京:清华大学出版社
    李朝生,杨晓晖,于春堂,慈龙骏,李红艳,王忠,白飞.2006.放牧对黄河低阶地盐化草场土壤水盐空间异质性的影响.生态学报,2006,26(7):2402~2408
    李海东. 2008.苏南丘陵区小流域土壤特性空间变异及其植被影响的研究.[硕士学位论文].南京:南京林业大学
    李洪义. 2008.滨海盐土三维土体电导率空间变异及可视化研究.[博士学位论文].杭州:浙江大学
    李进峰,宫渊波,陈林武,程永珍,张发会. 2007.广元市不同土地利用类型土壤的分形特征.水土保持学报,21(5):167~182
    李君,赵成义,朱宏,王锋,王丽娟,寇思勇. 2006.融雪后梭梭林地土壤水的多尺度空间异质性. 中国科学D辑地球科学,36 (增刊Ⅱ): 45~50
    李敏,李毅,曹伟,张江辉. 2009.不同尺度网格膜下滴灌土壤水盐的空间变异性分析.水利学报,40(10):1210~1218
    李艳,史舟,王人潮. 2005.基于GIS的土壤盐分时空变异及分区管理研究——以浙江省上虞市海涂围垦区为例.水土保持学报,19(3):121~124
    李艳. 2006.基于空间变异特性的滨海盐土采样及管理分区研究.[博士学位论文].杭州:浙江大学
    李晓鹏,张佳宝,吉丽青,朱安宁,刘金涛. 2009.土壤传递函数在计算土壤饱和导水率中的应用. 灌溉排水学报,28(2):70~73
    连纲,郭旭东,傅伯杰,虎陈霞. 2006.黄土高原小流域土壤容重及水分空间变异特征.生态学报,26(3):647~654
    缪驰远,汪亚峰,魏欣,徐霞,石文. 2007.黑土表层土壤颗粒的分形特征.应用生态学报,18(9):1987~1993
    廖凯华,徐绍辉,程桂福. 2009.大沽河流域土壤饱和导水率空间变异特征.土壤,41(1):147~151
    林正雨,高雪松,邓良基,李亨伟,郭燕梅. 2009.微地形土壤颗粒分形维数的空间变异特征研究. 土壤通报,40(3):471~475
    刘付程,史学正,潘贤章,王洪杰. 2003.苏南典型地区土壤颗粒的空间变异特征.土壤通报,34(4):246~249
    刘建国,王洪涛,聂永丰. 2004.多孔介质非饱和导水率预测的分形模型.水科学进展,15(3):269~275
    刘建立,徐绍辉,刘慧. 2004.估计土壤水分特征曲线的间接方法研究进展.水利学报,2:68~76
    刘晶,刘学录.2006.内陆河灌区土壤水分空间变异的尺度效应.甘肃农业大学学报,41(3):86~90
    刘世梁,郭旭东,连纲,傅伯杰,王静. 2005.黄土高原土壤养分空间变异的多尺度分析——以横山县为例.水土保持学报,19(5):105~108
    刘贤赵,李嘉竹,张振华. 2007.土壤持水曲线van Genuchten模型求参的一种新方法.土壤学报,44(6):1135~1138
    刘云鹏,王国栋,社奇,党亚爱. 2003.陕西4种土壤粒径分布的分形特征研究.西北农林科技大学学报(自然科学版),31(2):92~94
    刘云鹏,张社奇,党亚爱,贾根良. 2009.陕西合阳黄河湿地土壤颗粒体积分形特征研究.水资源与水工程学报,20(5):82~85
    吕贻忠,李保国,胡克林,徐艳. 2002.鄂尔多斯夏初不同地形土壤水分的空间变异.中国农业大学学报,7(5):38~43
    马晓刚,张兵,史东梅,吕刚. 2007.丘陵区不同土地利用类型紫色土入渗特征研究.水土保持学报,21(5):25~29
    孟宝. 2007.土壤特性的空间变异性与绿洲生态空间稳定性研究.[硕士学位论文].兰州:西北师范大学
    南京农学院主编. 1980.土壤农化分析.北京:农业出版社:39
    牛海山,李香真,陈佐忠. 1999.放牧率对土壤饱和导水率及其空间变异的影响.草地学报,7(3):211~216
    潘成忠,上官周平. 2003.土壤空间变异性研究评述.生态环境,12(3):371~375
    邵明安,王全九,黄明斌. 2006.土壤物理学.北京:高等教育出版社
    邵明安,黄明斌. 2000.土根系统水动力学.西安:陕西科学技术出版社
    宋孝玉,李亚娟,蒋俊,马玉霞. 2008.非饱和土壤水分运动参数空间变异性研究进展与展望.地球科学进展,23(6):613~618
    苏永中,赵哈林. 2004.科尔沁沙地农田沙漠化演变中土壤颗粒分形特征.生态学报,24(1):71~74
    王德,傅伯杰,陈利顶,赵文武,汪亚峰. 2007.不同土地利用类型下土壤粒径分形分析——以黄土丘陵沟壑区为例.生态学报,27(7):3081~3089
    王国梁,周生路,赵其国. 2005.土壤颗粒的体积分形维数及其在土地利用中的应用.土壤学报,42(4):545~550
    王红,宫鹏,刘高焕. 2006.黄河三角洲多尺度土壤盐分的空间分异.地理研究,25(4):649~658
    王慧芳,邵明安. 2006.含碎石土壤水分入渗试验研究.水科学进展,17(5):604~609
    王军,邱扬. 2005.土地质量的空间变异与尺度效应研究进展.地理科学进展,24(4):28~35
    王康,张仁铎,王富庆,安田裕. 2007.土壤水分运动空间变异性尺度效应的染色示踪入渗试验研究.水科学进展,18(2):158~163
    王淑英,路苹,王建立,杨柳,杨凯,于同泉. 2008.不同研究尺度下土壤有机质和全氮的空间变异特征——以北京市平谷区为例.生态学报,28(10):4957~4964
    魏建兵,肖笃宁,张兴义,隋跃宇. 2006.侵蚀黑土容重空间分异与地形和土地利用的关系.水土保持学报,20(3):118~122
    王永东,冯娜娜,李廷轩,张锡洲,廖桂堂. 2007.不同尺度下低山茶园土壤阳离子交换量空间变异性研究.中国农业科学,40(9):1980~1988
    肖波,王庆海,尧水红,却晓娥,曹志德. 2009.黄土高原东北缘退耕坡地土壤养分和容重空间变异特征研究.水土保持学报,23(3):92~96
    肖建英,李永涛,王丽. 2007.利用Van Genuchten模型拟合土壤水分特征曲线.地下水,29(5):46~47
    解文艳,樊贵盛. 2004.土壤质地对土壤入渗能力的影响.太原理工大学学报, 35(5):537~540
    徐冰,陈亚新,郭克贞. 2007.半干旱草地土壤粒径分形维数及空间变异特征.水利学报,增刊:691~695
    徐海芳,郭建青,郑丽萍,刘恩民. 2007.鲁西北黄泛区农田土壤稳定入渗率空间变异性分析.干旱地区农业研究,25(6):132~135
    徐绍辉,刘建立. 2003.估计不同质地土壤水分特征曲线的分形方法.水利学报,15(3):269~275
    徐英,陈亚新,史海滨,魏占民. 2004.土壤水盐空间变异尺度效应的研究.农业工程学报,20(2):1~5
    颜永强,段文标,王晶. 2008.莲花湖库区水源涵养林土壤入渗性能的空间分布特征.中国水土保持科学,2008, 6(3):88~93
    杨劲松,姚荣江. 2007.黄河三角洲地区土壤水盐空间变异特征研究.地理科学,27(3):348~353
    杨培岭,罗远培,石元春. 1993.用粒径的重量分布表征的土壤分形特征.科学通报,38(20):1896~1899
    姚荣江,杨劲松,刘广明,邹平. 2006a.黄河三角洲地区典型地块土壤盐分空间变异特征研究.农业工程学报,22(6):61~66
    姚荣江,杨劲松,刘广明. 2006b.黄河三角洲地区土壤容重空间变异性分析.灌溉排水学报,25(4):11~15
    姚荣江,杨劲松.2008.基于电磁感应仪的黄河三角洲地区土壤盐分时空变异特征.农业工程学报, 24(3):107~113
    杨玉玲,文启凯,田长彦,盛建东,刘军,郭文君,袁永胜. 2001.土壤空间变异研究现状及展望. 干旱区研究,18(2):50~55
    姚月锋,蔡体久. 2007.丘间低地不同年龄沙柳表层土壤水分与容重的空间变异.水土保持学报,21(5):114~117
    尤文忠,曾德慧,刘明国,宋西德,叶彦辉,张永. 2005.黄土丘陵区林草景观界面雨后土壤水分空间变异规律.应用生态学报,2005,16(9):1591~1596
    袁建平,张素丽,张春燕,蒋定生. 2001.黄土丘陵区小流域土壤稳定入渗速率空间变异.土壤学报,38(4):579~583
    苑小勇,黄元仿,高如泰,柴旭荣,贺勇. 2008.北京市平谷区农用地土壤有机质空间变异特征.农业工程学报,24(2):70~76
    曾宪勤,刘和平,路炳军,王秀颍,杨威. 2008.北京山区土壤粒径分布分形维数特征.山地学报,26(1):65~70
    张春敏,王根绪,龙训建,李元寿. 2007.高寒草甸典型植被退化小流域土壤容重空间变异特征.河南农业科学,6:90~95
    张继光,陈洪松,苏以荣,张伟,孔祥丽. 2008.喀斯特洼地表层土壤水分的空间异质性及其尺度效应.土壤学报,45(3):544~549
    张世熔,黄元仿,李保国. 2004.冲积平原区土壤颗粒组成的趋势效应与异向性特征.农业工程学报,20(1):56~60
    张新民,沈冰,谢志伟. 2000.非饱和土壤水分运动参数空间变异特性的统计分析.农业工程学报,16(1):18~21
    张展羽,詹红丽,郭相平.2002.滨海平原农田土壤含盐量空间变异分析.河海大学学报(自然科学版),30(4):61~65
    赵爱辉,黄明斌,史竹叶. 2008.两种土壤水分特征曲线间接推求方法对黄土的适应性评价.农业工程学报,24(9):11~15
    赵锐锋,陈亚宁,洪传勋,李卫红,白云岗. 2008.塔里木河源流区绿洲土壤含盐量空间变异和格局分析——以岳普湖绿洲为例.地理研究,27(1):135~144
    赵文智,刘志民,程国栋. 2002.土地沙质荒漠化过程的土壤分形特征.土壤学报,39(6):877~881
    赵勇钢,赵世伟,曹丽花,梁向锋. 2008.半干旱典型草原区退耕地土壤结构特征及其对入渗的影响.农业工程学报,24(6):14~20
    郑纪勇,邵明安,张兴昌. 2004.黄土区坡面表层土壤容重和饱和导水率空间变异特征.水土保持学报,18(3):53~56
    郑丽萍,郭建青,徐海芳,刘恩民. 2008.山东禹城地区土壤入渗特性的空间变异研究.节水灌溉,11:11~13
    中国土壤学会农业化学专业委员会. 1983.土壤农业化学常规分析方法.北京:科学出版社:75~77
    周先容,陈劲松. 2006.川西亚高山针叶林土壤颗粒的分形特征.生态学杂志,25(8):891~894
    Alletto L,Coquet Y.2009. Temporal and spatial variability of soil bulk density and near-saturated hydraulic conductivity under two contrasted tillage management systems. Geoderma, 152(1-2):85~94
    Benites V M, Machado P L O A, Fidalgo E C C, Coelho M R, Madari B E. 2007. Pedotransfer functions for estimating soil bulk density from existing soil survey reports in Brazil. Geoderma, 139(1-2):90~97
    Brocca L,Morbidelli R,Melone F,Moramarco T.2007. Soil moisture spatial variability in experimental areas of central Italy. Journal of Hydrology,333(2-4):356~373
    Buttafuoco G,CastrignanóA.2005. Study of the spatio-temporal variation of soil moisture under forest using intrinsic random functions of order k. Geoderma, 128(3-4):208~220
    Caniego F J,Espejo R,Martín M A,JoséF S. 2005. Multifractal scaling of soil spatial variability. Ecological Modelling, 182(3-4):291~303
    Cerri C E P,Bernoux M,Chaplot V,Volkoff B,Victoria R L,Melillo J M,Paustian K,Cerri C C.2004. Assessment of soil property spatial variation in an Amazon pasture: basis for selecting an agronomic experimental area. Geoderma,123(1-2):51~68
    Cetin M,Kirda C.2003. Spatial and temporal changes of soil salinity in a cotton field irrigated with low-quality water. Journal of Hydrology,272(1-4):238~249
    Chirico G B,Medina H,Romano N.2007. Uncertainty in predicting soil hydraulic properties at the hillslope scale with indirect methods. Journal of Hydrology,334(3-4):405~422
    Comegna V,Damiani P,Sommella A. 1998. Use of a fractal model for determining soil water retention curves. Geoderma,85(4):307~323
    Douaik A,Meirvenne M V,Tóth T. 2007. Statistical methods for evaluating soil salinity spatial and temporal variability. Soil Sci. Soc. Am. J. 71:1629~1635
    Eghball B,Schepers J S,Negahban M,Schlemmer M R. 2003. Spatial and temporal variability of soil nitrate and corn yield: multifractal analysis. Agron. J. 95(2):339~346
    Ersahin S. 2003. Comparing ordinary Kriging and Cokriging to Estimate Infiltration Rate. Soil Sci. Soc. Am. J. 67:1848~1855
    Ersahin S,Brohi A R. 2006. Spatial variation of soil water content in topsoil and subsoil of a Typic Ustifluvent. Agricultural Water Management,83(1-2):79~86
    Feng Q,Liu Y S,Mikami M. 2004. Geostatistical analysis of soil moisture variability in grassland. Journal of Arid Environments, 58(3):357~372
    Franzluebbers A J. 2002. Water infiltration and soil structure related to organic matter and its stratification with depth. Soil & Tillage Research,66(2):197~205
    Gaston L A, Locke M A,Zablotowicz R M, Reddy K N.2001. Spatial variability of soil properties and weed populations in the Mississippi Delta. Soil Sci. Soc. Am. J., 65:449~459
    Gupta S D,Mohanty B P,K?hne J M. 2006. Soil hydraulic conductivities and their spatial and temporal variations in a Vertisol. Soil Sci. Soc. Am. J. 70:1872~1881
    Haws N W, Liu B W, Boast C W,Rao P S C, Kladivko E J,Franzmeier D P.2004. Spatial Variability and Measurement Scale of Infiltration Rate on an Agricultural Landscape. Soil Sci. Soc. Am. J. 68:1818~1826
    Herbst M,Diekkrüger B. 2003. Modelling the spatial variability of soil moisture in a micro-scale catchment and comparison with field data using geostatistics. Physics and Chemistry of the Earth, 28(6-7):239~245
    Huang G H,Zhang R D,Huang Q Z.2006. Modeling soil water retention curve with a fractal method. Pedosphere,16(2):137~146
    Jung W K,Kitchen N R,Sudduth K A,Anderson S H. 2006. Spatial characteristics of Claypan soil properties in an agricultural field. Soil Sci. Soc. Am. J., 70:1387~1397
    Júnior V V,Carvalho M P,Dafonte J,Freddi O S,Vázquez E V,Ingaramo O E. 2006. Spatial variability of soil water content and mechanical resistance of Brazilian ferralsol. Soil & Tillage Research,85(1-2):166~177
    Iqbal J,Thomasson J A,Jenkins J N,Owens P R,Whisler F D. 2005. Spatial Variability Analysis of Soil Physical Properties of Alluvial Soils. Soil Sci. Soc. Am. J. 69:1338~1350
    K?l?? K,?zg?z E,Akba? F.2004. Assessment of spatial variability in penetration resistance as related to some soil physical properties of two fluvents in Turkey. Soil & Tillage Research, 76(1):1~11
    Kravchenko A N, Boast C W, Bullock D G. 1999. Multifractal analysis of soil spatial variability. Agron. J.,91(6):1033~1041
    Kravchenko A N,Bullock D G,Boast C W. 2000. Joint multifractal analysis of crop yield and terrain slope. Agron. J., 92(6):1279-1290
    Leonard J,Andrieux P. 1998. Infiltration characteristics of soils in Mediterranean vineyards in Southern France. Catena 32(3-4):209~223
    Li Y,Chen D,White R E,Zhu A,Zhang J. 2007. Estimating soil hydraulic properties of Fengqiu County soils in the North China Plain using pedo-transfer functions. Geoderma,138(3-4):261~271
    Machiwal D,Jha M K,Mal B C. 2006. Modelling infiltration and quantifying spatial soil variability in a wasteland of Kharagpur, India. Biosystems Engineering, 95(4):569~582
    Manyame C,Morgan C L,Heilman J L,Fatondji D,Gerard B,Payne W A. 2007. Modeling hydraulic properties of sandy soils of Niger using pedotransfer functions. Geoderma,141(3-4):407~415
    Meirvenne M V,Maes K,Hofman G. 2003. Three-dimensional variability of soil nitrate-nitrogen in an agriculture field. Biology Fertility Soils, 37(3):147~153
    Meneveau C,Sreenivasan K R,Kailasnath P,Fan M S. 1990. Joint multifractal measures:Theory and application to turbulence. Phys. Rev. A,41(2):894~913
    Pan Y X,Wang X P,Jia R L,Chen Y W,He M Z.2008. Spatial variability of surface soil moisture content in a re-vegetated desert area in Shapotou, Northern China. Journal of Arid Environments, 72(9):1675~1683
    Parasuraman K,Elshorbagy A,Si B C. 2006. Estimating Saturated Hydraulic Conductivity In Spatially Variable Fields Using Neural Network Ensembles. Soil Sci. Soc. Am. J. 70:1851~1859
    Parasuraman K,Elshorbagy A,Si B C. 2007. Estimating saturated hydraulic conductivity using genetic programming. Soil Sci. Soc. Am. J., 71(6):1676~1684
    Peitgen H O,Jürgens H,Saupe D. 1992. Chaos and fractals: New frontier of science. Springer-Verlag,New York,737
    Penna D,Borga M,Norbiato D,Fontana G D. 2009. Hillslope scale soil moisture variability in a steep alpine terrain. Journal of Hydrology, 364(3-4):311~327
    Petersen C T,Trautner A,Hansen S.2008. Spatio-temporal variation of anisotropy of saturated hydraulic conductivity in a tilled sandy loam soil. Soil & Tillage Research,100(1-2):108~113
    Qiu Y,Fu B J,Wang J,Chen L D. 2001. Spatial variability of soil moisture content and its relation to environmental indices in a semi-arid gully catchment of the Loess Plateau, China. Journal of Arid Environments, 49(4):723~750
    Rüth B,Lennartz B. 2008. Spatial variability of soil properties and rice yield along two catenas in southeast China. Pedosphere,18(4):409~420
    Santra P,Das B S. 2008. Pedotransfer functions for soil hydraulic properties developed from a hilly watershed of Eastern India. Geoderma,146(3-4):439~448
    Sobieraj J A,Elsenbeer H,Cameron G. 2004. Scale dependency in spatial patterns of saturated hydraulic conductivity. Catena,55(1):49~77
    Starr G C. 2005. Assessing temporal stability and spatial variability of soil water patterns with implications for precision water management. Agricultural Water Management,72(3): 223~243
    Tang C L, Piechota T C. 2009. Spatial and temporal soil moisture and drought variability in the Upper Colorado River Basin. Journal of Hydrology, 379(1-2):122~135
    Tennekoon L,Boufadel M C,Lavallee D,Weaver J. 2003. Multifractal anisotropic scaling of the hydraulic conductivity. Water Resour. Res.,39(7):1193~1205
    van Genuchten M Th. 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J., 44:892~898
    Walczak R T,Moreno F,S?awński C,Fernandez E,Arrue J L. 2006. Modeling of soil water retention curve using soil solid phase parameters. Journal of Hydrology,329(3-4):527~533
    Wang Y G,Li Y,Xiao D N. 2008. Catchment scale spatial variability of soil salt content in agricultural oasis, Northwest China. Environ Geol,56(2):439~446
    Western A W,Bl?schl G,Grayson R B. 1998. Geostatistical characterisation of soil moisture patterns in the Tarrawarra catchment. Journal of Hydrology, 205(1-2):20~37
    Xu Y F,Dong P. 2004. Fractal approach to hydraulic properties in unsaturated porous media. Chaos, Solitons and Fractals,19(2):327~337
    Zeleke T B, Si B C. 2005. Scaling relationships between saturated hydraulic conductivity and soil physical properties. Soil Sci. Soc. Am. J., 69:1691~1702
    Zeleke T B,Si B C. 2006. Characterizing scale-dependent spatial relationships between soil properties using multifractal techniques. Geoderma,134(3-4):440~452
    Zhao Y, Peth S, Krümmelbeina J, Horn R, Wang Z, Steffens M, Hoffmann C, Peng X. 2007. Spatial variability of soil properties affected by grazing intensity in Inner Mongolia grassland.Ecological Modeling, 205(1-2):241~254
    Zheng Z,Zhang F R,Ma F Y,Chai X R,Zhu Z Q,Shi J L,Zhang S X. 2009. Spatiotemporal changes in soil salinity in a drip-irrigated field. Geoderma,149(3-4):243~248

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