| 摘要: |
| 目的 正确评估土壤盐渍化状况，掌握土壤盐分空间分布规律，是合理开发利用盐渍化土壤资源的基础和前提。方法 文章选取黄河三角洲典型地区垦利县作为采样区，利用4种确定性方法（全局多项式、局部多项式、反距离加权、径向基函数）和3种地统计不确定性方法（普通克里格、简单克里格、协同克里格），分别对研究区进行土壤含盐量的空间分布特性估计，从误差和空间分布特点上对比分析不同方法的预测效果，并明确了研究区土壤盐分的空间分布特征。结果 地统计不确定性插值方法的精度整体上优于确定性方法，简单克里格预测后的空间表达和误差精度均属最优。基于最优的空间预测方法，黄河三角洲土壤盐分目前在空间上整体呈现出东部高于西部的趋势，且部分区域存在斑块状现象。非盐渍化、轻度盐渍化、中度盐渍化、重度盐渍化和盐土面积分别占研究区总面积的2.54%、27.14%、43.70%、21.21%和5.41%。结论 在土壤属性变异强度大的时候，采用简单克里格效果会更好。 |
| 关键词: 黄河三角洲 空间分布 地统计学 土壤盐渍化 简单克里格 |
| DOI：10.7621/cjarrp.1005-9121.20210828 |
| 分类号:S158.9 |
| 基金项目:国家自然科学基金“山东省砂姜黑土土种的系统分类归属研究”（41601211）；山东省重点研发计划“盐渍土快速改良与地力培肥产品的研发与应用”（2017CXGC0303）；青岛农业大学人才基金“黄河三角洲典型地区土壤盐分空间分布预测方法研究”（1114344）；青岛农业大学研究生创新计划项目“基于多尺度影像纹理特征的土壤类型遥感解译研究”（QNYCX20080） |
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| PREDICTION METHOD OF SPATIAL DISTRIBUTION FOR SOIL SALINITY IN TYPICAL AREAS OF THE YELLOW RIVER DELTA |
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Duan Mengqi1, Zhang Xiaoguang1,2, Wang Bao1,3,4
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1.School of Resources and Environment, Qingdao Agricultural University, Qingdao 266109, Shandong, China;2.State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, Jiangsu, China;3.Department of Plant and Environmental Sciences, Faculty of Science, University of Copenhagen, Hojbakkegaard Alle 13, 2630 Taastrup, Denmark;4.College of Resources and Environment, Yunnan Agricultural University, Kunming 650201, Yunnan, China
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| Abstract: |
| Assessing the status of soil salinization correctly and mastering the spatial variation are the basis and prerequisites for the rational development and utilization of salinized soil resources. In this study, Kenli county, a typical area of ??the Yellow River Delta, was selected as the sampling area. Four deterministic methods (global polynomial interpolation, local polynomial interpolation, inverse distance weighting and radial basis function) and three kinds of geostatistical uncertainty methods (ordinary Kriging, simple Kriging and Co-Kriging) were used to estimate the spatial distribution characteristics of soil salinity in the study area, respectively. Then the prediction results of different methods were compared from the error and spatial distribution characteristics, and the spatial distribution characteristics of soil salinity were clarified in the study area. The results showed that the accuracy of the geostatistical uncertainty interpolation methods was better than that of the deterministic methods, and the spatial expression and error precision were optimal after the simple Kriging prediction. Based on the optimal spatial prediction method, the soil salinity of the Yellow River Delta was spatially higher in the east than that in the west, and there were plaques in some areas. After calculating the land area of salinization with different grades, non-salinization, mild salinization, moderate salinization, severe salinization and saline soil area accounted for 2.54%, 27.14%, 43.7%, 21.21%, and 5.41% of the total study area, respectively. This article concludes that it is better to use simple Kriging method to predict the spatial variation when the variability of soil property was high. |
| Key words: Yellow River Delta spatial distribution geostatistics soil salinization simple Kriging |
