【作者】 郭丽俊；

【导师】 李毅；

【作者基本信息】 西北农林科技大学 ， 农业水土工程， 2011， 硕士

【摘要】 土壤水盐特性是用于描述土壤水分、盐分运动过程与分布情况的参数。研究土壤水盐特性的空间变异性对于科学研究土壤环境、土壤农作、土壤水分运动等学科都具有重要的指导意义。通过对杨凌塿土直线取样（方案一）、新疆盐碱土空间网格取样（方案二）和直线取样（方案三）的样品分析测定,采用经典统计学原理、地统计学原理、空间自相关原理、小波分析、多重分形和联合多重分形等方法对其进行空间分析,从不同角度对比揭示土壤水盐特性的空间变异性。得到以下主要结论:（1）经典统计学原理分析可知,方案一中的Brooks-Corey模型拟合参数（α）和饱和导水率（Ks）的变异系数大于1,表现为强变异;Brooks-Corey模型拟合参数（n）的变异系数介于0.1到1之间,表现为中等变异水平;Brooks-Corey模型饱和含水量（θs）、质量含水率（θ）及容重（ρ）的分布较为均匀,且变异系数小于0.1,表现为弱变异。方案二中绝大多数土壤水盐特性表现为中等变异水平,只有Na⁺在大、小尺度上表现为强变异。方案三中各土壤水盐特性绝大多数表现为中等变异强度,只有pH表现为弱变异。（2）地统计学分析表明,三方案中各土壤水盐特性的半方差函数基本上可以用球状模型来模拟,属于中等变异程度。（3）空间自相关理论分析表明,方案一中四个方向上的各土壤水盐特性的空间自相关程度不一,但同一方向上呈现类似的变化趋势,Moran’s I系数的变化范围在[-0.3,0.3],表明随机分布格局相对占较大比重。方案二中三尺度下土壤各水盐特性的Moran’s I系数变化具有相似性,在-0.8～0.6范围内波动。方案三中各土壤水盐特性的Moran’s I系数变化各异,但均在-0.5⁰.4之间变化。（4）由小波方差图谱分析可知,方案一和三中的各土壤水盐特性在整个空间上至少表现出两个尺度结构,而绝大多数的土壤水盐特性最大尺度结构分别出现在200m和64m处,这就说明在此处引起土壤水盐特性的空间变化的信息较为丰富,空间分布结构比较复杂。（5）从多重分形理论来分析,在无标度尺度-4⁴内,各土壤水盐特性存在多重分形特征,方案一中θs、θ及ρ的多重结构较弱,而Ks、α及n的多重分形结构特征明显。通过对广义分形维数的计算,表明θs、θ及ρ的空间变异性较弱,Ks的空间变异性很强,α的空间变异性较强,n的空间变异性强,且Ks比α和n具有更为复杂的空间分布结构。方案三中土壤含盐量、滴水穿透时间、pH、Na⁺、Mg²⁺和Ca²⁺均具有多重分形结构,但pH的多重分形特征不明显,表明pH的空间变异性较弱。（6）利用联合多重分形对土壤水盐特性的空间关联性进行分析表明,方案一中Ks和α、n,ρ和n之间的空间关联性较弱,Ks和θs、ρ、θ,ρ和α之间的空间关联性较强,方案三中土壤含盐量与pH、Na⁺、Mg²⁺、Ca²⁺,Na⁺与Mg²⁺、Ca²⁺,Mg²⁺和Ca²⁺、滴水穿透时间之间存在一定的空间关联性。更多还原

【Abstract】 Soil hydraulic and saline properties are parameters used to describe soil water and salt movement and distribution. Study on spatial variability of soil hydraulic and saline properties had great significance on guiding the development and application of soil environment, soil tillage, and soil water movement. Based on the measurement of Lou soil samples taken in yangling region along straight lines （scheme one）, saline-alkalin sail samples taken in Xinjiang region at different scales of grids （scheme two） and along straight lines （scheme three）. Spatial variability of soil hydraulic and saline properties were analyzed by means of principles of classical statistics, geostatistics, spatial autocorrelation theory, wavelet analysis, the BP artificial neural network, multifractal theory, and joint multifractal theory. In order to reveal spatial variability of soil hydraulic and saline properties from different angles. The main conclusions were as following:（1） From the analysis of classical statistics for scheme one, variation coefficients of Brooks-Corey model fitting parameter （α） and saturated hydraulic conductivity （Ks） were larger than 1, belonged to strong variations; variation coefficients of Brooks-Corey model fitting parameter （n） varied from 0.1 to 1, belonged to moderate variation; Brooks-Corey model saturated water content （θs）, mass water content（θ） and bulk density（ρ） distributed uniformly, and variation coefficients were smaller than 0.1, belonged to weak variation. For scheme two, most soil hydraulic and saline properties varied to a moderate degree. For scheme three, most of the soil hydraulic and saline properties varied to a moderate degree while pH belonged to weak variation.（2） From the analysis of Geostatistics, most semi-variance theoretical models of soil hydraulic and saline properties of three schemes could be fit with spherical models, and showed moderate variation level.（3） From the analysis of spatial autocorrelation theory for scheme one, spatial autocorrelation degree of soil hydraulic and saline properties were different in four directions, Moran’s I coefficients ranged from -0.3 to 0.3, showed that random distribution took up a large proportion. For scheme two, Moran’s I coefficients of all the soil hydraulic and saline properties were quite similar in variation, which ranged from -0.8 to 0.6 at all the three scales. For scheme three, Moran’s I coefficients of all the soil hydraulic and saline properties were different, but which ranged from -0.5 to 0.4.（4） From the analysis of the wavelet variance map, for scheme one and three, every soil hydraulic and saline properties in space showed at least two scale structures, most of their biggest scale structure appeared near 200 and 64 meter respectively. It suggested that in these positions, the spatial variability information of soil hydraulic and saline properties were more abundant, and spatial distribution structure were more complex.（5） From the analysis of multifractal theory, in scale-free scale from -4 to 4, soil hydraulic and saline properties had multifractal feature. For scheme one, the multifractal features ofθs,θandρwere weak, and the multifractal features of Ks,αand n were obvious. According to the calculations of generalized dimensions of soil hydraulic and saline properties, spatial variability ofθs,θandρwere weak, the spatial variability of Ks was stronger thanαand n, suggested that spatial structure of Ks was more complex. For scheme three, soil salt content, WDPT, pH, Na⁺, Mg²⁺, and Ca²⁺ had multifractal structure, but multifractal features of pH was not obvious, suggested that spatial variability of pH was weak.（6） From joint multifractal analyse for spatial correlation of soil hydraulic and saline properties, for scheme one, the result showed that in the first program spatial correlation between Ks andα, n, and betweenρand n were weak, spatial correlation between Ks andθs,ρ,θ, and betweenρandαwere strong. For scheme three, spatial correlation between salt content and pH, Na⁺, Mg²⁺, Ca²⁺, between Na⁺ and Mg²⁺, Ca²⁺, between Mg²⁺ and Ca²⁺ , WDPT were strong.更多还原