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不同阈值下土壤盐分的空间变异特征研究

ISSN号：0564-3929
期刊名称：土壤学报
时间：2011.11.15
页码：1109-1115
分类：S156.4[农业科学—土壤学;农业科学—农业基础科学]
作者机构：[1]土壤与农业可持续发展重点实验室（中国科学院南京土壤研究所）,南京210008
相关基金：公益性行业（农业）科研专项经费项目（200903001）、中国科学院知识创新工程重要方向项目（KZCXZ-YW-359）、国家自然科学基金项目（41171181）、江苏省科技支撑计划（BE2010313）资助
相关项目：滨海盐渍土固碳影响要素与土壤增碳的管理调控机制研究

关键词：土壤盐分, 阈值, 指示克里格法, 空间变异, Soils salinity, Threshold, Indicator Kriging, Spatial variability

中文摘要：

指示克里格法（Indicator Kriging，IK）应用的关键是阈值的合理选择。本文以黄淮海平原盐渍土改良区典型县域禹城市为研究区域，在1．0gkg-1、2．0gkg-1、3．0gkg-1等3个盐分阈值下，对0—20cm耕地土壤盐分的变异函数、预测概率、预测概率空间分布的变化规律进行了研究。结果表明，（1）不同阈值下土壤盐分含量均具有中等强度的自相关性，随着阈值的减小，土壤盐分的空间结构性增强，变异函数的模型精度增大，因此从指示变异函数模型精度考虑，1．0gkg-1盐分含量为研究区域盐渍化风险评价的最佳阈值；（2）土壤盐分的预测概率最大值和预测概率均值随盐分阈值的减小而增大，可为不同土壤盐渍化风险评价目标下的阈值选择提供参考；（3）不同阎值下土壤盐分的概率预测分布存在空间上的规律性与相似性，高概率区域主要集中在研究区域的西部，低概率区域主要集中在研究区域的东部。研究区域土壤盐分含量的概率分布与地形地貌特征和河流的分布状况有着密切的关系。

英文摘要：

The key to application of the Indicator Kriging method is the choice of an appropriate threshold. Three soil salinity thresholds, i.e. 1.0 g kg-1 , 2.0 g kg-1 and 3.0 g kg-1 were set for the study on variograms, prediction probability and spatial distribution of the prediction probability of soil salinity in the top layer （0 - 20 cm） of a farmland in relation to soil salinity threshold in Yucheng, typical of the salt-affected soil amelioration zone in the Huang-Huai-Hai Plain. Results show （ 1 ） regardless of threshold values, salt contents in all soils are all moderate in spatial autocorrela- tion; however, with threshold declining, soil salinity intensifies in spatial structure and its model of variation function increases in accuracy ; therefore, taking into account the accuracy of the indicator variogram model, the soil salt content of 1.0 g kg-1 is the optimal threshold for assessment of the risk of salinization of the studied region ; （2） both the maximum value and the mean value of prediction probability increase with rising salinity threshold, which may serve as reference for selecting thresholds for different objects of soil salinization risk assessment; and （3） predictive distribution of probability prediction of soil salinity using different thresholds demonstrates certain spatial regularity and similarity ; high probability is concentrated mainly in the west part of the studied region, while low probability in the east. Distribution of the prediction probability of soil salt content is closely related to landform and topography and distribution of rivers in the study area.

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