Scaling Relationships between Saturated Hydraulic Conductivity and Soil Physical Properties
Scaling Relationships between Saturated Hydraulic Conductivity and Soil Physical Properties
复制标题
DOI：
10.2136/sssaj2005.0072
复制
发表时间：
2005-11
影响因子：
2.9
通讯作者：
T. Zeleke;B. Si
中科院分区：
文献类型：
--
作者：
T. Zeleke;B. Si
饱和导水率（K）是重要的土壤水力特性，影响水流和溶解溶质的输送。由于极高的空间变异性，获得足够且可靠的 K 数据用于大规模过程建模始终是一个挑战。本研究的目的是 (i) 确定是否需要单分形或多重分形方法来描述 K s 及其土壤替代物的变异性，以及 (ii) 确定哪种土壤特性最能反映 K s 在更广泛尺度上的空间分布。饱和导水率和土壤物理性质数据是从位于加拿大 SK 斯米顿的 384 米横断面收集的。使用统计和地统计学方法检查观测尺度的变异性和关系。统计尺度不变性通过 Hurst 尺度参数 (H) 进行评估。使用多重分形和联合多重分形技术研究了多尺度变异性和关系。结果表明，对于所有研究变量 0.80 < H < 0.90，表明存在一定程度的统计尺度不变性和长期依赖性。在观测尺度上，X 的变异性与沙子 (SA) 和淤泥 (SI) 的分布显着相关（SA 的 R = 0.40，SI 的 -0.39，P < 0.01；n = 128），而在更广泛的尺度上，K s 的变异性仅与粘土 (CL) 和有机碳 (OC) 相关。结果表明 K 和土壤物理性质之间存在尺度依赖性关系，这意味着土壤传递函数 (PTF) 和 K 聚合技术等预测模型的成功很大程度上取决于观测和实施尺度之间的对应关系。
Saturated hydraulic conductivity (K,) is an important soil hydraulic property that affects water flow and the transport of dissolved solutes. Obtaining sufficient and reliable K, data for large-scale process modeling is always a challenge due to the extremely high spatial variability. The objectives of this study were (i) to determine if a monofractal or multifractal approach is needed to describe the variability in K s and its soil surrogates, and (ii) to identify which soil property best reflects the spatial distribution of K s across a wider range of scales. Saturated hydraulic conductivity and soil physical property data were collected from a 384-m transect, located at Smeaton, SK, Canada. Observation scale variability and relationships were examined using statistical and geostatistical methods. Statistical scale-invariance was evaluated through the Hurst scaling parameter (H). Multiple scale variability and relationships were studied using multifractal and joint multifractal techniques. Results indicate that for all the studied variables 0.80 < H < 0.90, suggesting a certain degree of statistical scale-invariance and long-range dependency. At the observation scale, the variability in X, was significantly related to sand (SA) and silt (SI) distribution (R = 0.40 for SA and -0.39 for SI, P < 0.01; n = 128), whereas, across a wider range of scales, the variability in K s was related only to clay (CL) and organic C (OC). The result indicates scale dependent relationships between K, and soil physical properties, which implies that the success of predictive models such as pedotransfer functions (PTFs) and K, aggregation techniques depends largely on the correspondence between observation and implementation scales.