广西典型岩溶区土壤水分含量空间自相关分析

杨奇勇; 蒋忠诚; 袁道先; 蒋勇军; 沈丽娜

doi:10.11932/karst20150309

广西典型岩溶区土壤水分含量空间自相关分析

doi: 10.11932/karst20150309

1.
中国地质科学院岩溶地质研究所/国土资源部岩溶生态与石漠化治理重点实验室/西南大学地理科学学院
2.
中国地质科学院岩溶地质研究所/国土资源部岩溶生态与石漠化治理重点实验室
3.
西南大学地理科学学院

基金项目: 国家科技支撑计划项目(2012BAC16B02)；基于生态修复的石漠化土地利用适宜性评价（桂科攻1598016-11）；地质大调查项目“西南岩溶石漠化遥感调查与地面监测”(1212011220958)

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出版历程
- 发布日期: 2015-06-25

Spatial autocorrelation analysis of soil water content in a karst region of Guangxi Province

1.
Institute of Karst Geology, Chinese Academy of Geological Sciences/Key Laboratory of Karst Ecosystem and Treatment of Rocky Desertification, Ministry of Land and Resources/Southwest University, School of Geographical Sciences
2.
Institute of Karst Geology, Chinese Academy of Geological Sciences/Key Laboratory of Karst Ecosystem and Treatment of Rocky Desertification, Ministry of Land and Resources
3.
Southwest University, School of Geographical Sciences

摘要

摘要: 以广西壮族自治区马山县为研究区，在野外调查、室内实验测试获取182个土壤水分含量数据的基础上，采用半方差函数和Moran’s I统计量对研究区域土壤水分含量的空间自相关关系、空间相关尺度和空间分布规律进行了研究。结果表明：(1)研究区域土壤水含量平均值为16.97%，受结构性因素和随机因素共同作用，土壤水分含量具有中等强度的空间异质性；(2)研究区域土壤水分含量Moran’s I指数为0.423，表明研究区内土壤水分含量存在空间自相关性，在0~21 km和31~34 km范围内土壤水分含量自相关性为正，在21.7~31 km和34~45 km范围内自相关性为负；(3)Lisa聚类图表明，土壤水分含量空间聚集区和空间孤立区相伴存在，其中“高—高”空间聚集主要分布在马山县东北部，“低—低”聚集区主要分布在东南部。“低—低”聚集区和“高—低”孤立区土壤水分含量缺乏风险大。
- 土壤水分含量 /
- 半方差函数 /
- 空间自相关 /
- 空间异质性
Abstract: Mashan county, located in the middle Guangxi Zhuang Autonomous Region, southwestern China, was selected as the study area. Based on the plentiful information from field surveys, soil sampling and laboratory analysis, we were studied the spatial autocorrelation coefficients, correlation distances and spatial patterns of soil water content in topsoil (0–20 cm) using semi-variances and Moran’ s Istatistics. The results show that the mean value of soil water content is 16.97%. Soil water content shows a moderate spatial autocorrelation within the distance of 78.8 km, which is affected by the constitutive and random factors. (2) Moran index of soil water content in the study area is 0.43, suggesting that the soil water content possesses spatial autocorrelation. In the ranges of 0-21.7 km and 31-34 km, the values of Moran′s Iof soil water content are greater than 0, implying positive spatial autocorrelation; while in the ranges of 21.7-31 km and 34-45 km, the values are negative, indicating negative spatial autocorrelation. Lisa cluster maps show that there are spatial aggregation areas and spatial isolated areas of the soil water content. The “high-high” spatial aggregation areas cluster in the northeast of Mashan county and “low-low” spatial aggregation clustered in the southeast. There are bigger risk of short of soil water content in the “low-low” spatial aggregation and “high-low” spatial isolated areas.
- soil water content /
- semi-variances /
- spatial autocorrelation /
- spatial heterogeneity

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参考文献(21)

[1]	Bellamy P H, Loveland P J, Bradley R L, et al. Carbon losses from all soils across England and Wales 1978-2003［J］. Nature, 2005, 437: 245-248.
[2]	Cliff A D, Ord J K. Spatial process: Models and Applications［J］. London, UK: Pion, 1973:178.
[3]	Waser M N, Mitchell R J. Nectar standing crops in delphinium nelsonii flowers: Spatial autocorrelation among plants［J］. Ecology, 1990, 71 (1): 116-123.
[4]	Martin D. An aeeseement of surface and zonal models of population. Geographical Information Systerms, 1996, 10 (8): 973-989.
[5]	梁二，王小彬，蔡典雄，等. 河南省土壤有机碳分布空间自相关分析［J］. 应用生态学报，2007, 18(6)：1305-1310.
[6]	霍霄妮, 李红, 孙丹峰, 等. 北京耕作土壤水分含量的空间自相关分析［J］. 环境科学学报, 2009，29(6): 1339－1344.
[7]	杨奇勇，杨劲松，余世鹏，等. 不同尺度下耕地土壤Cr含量的空间自相关性分析［J］. 应用与环境生物学报，2011，17 (3): 393-397.
[8]	McGrath D，Zhang C S．Spatial distribution of soil organic carbon concentrations in grassland of Ireland ［J］．Applied Geochemistry，2003，18(10)：1629-1639.
[9]	杨泉，赵成章，史丽丽，等.祁连山地甘肃臭草斑块土壤水分的空间自相关分析［J］. 生态学杂志，2014，33(3)：716－722.
[10]	周亮广, 梁虹. 喀斯特地区水资源承载力评价研究:以贵州省为例［J］. 中国岩溶，2006,25（1）：23-28.
[11]	王家文，周跃，肖本秀，等. 中国西南喀斯特土壤水分特征研究进展［J］ . 中国水土保持，2013,2:37-42.
[12]	Boyer D G, Wright R J, Feldhake C M, et al.Soil spatial variability relationships in steeply sloping acid soil environment［J］. Soil Sci,1991,161:278-287.
[13]	Chopin P, Blazy J M. Assessment of regional variability in crop yields with spatial autocorrelation: Banana farms and policy implications in Martinique［J］. Agriculture, Ecosystems & Environment, 2013, 181(4):12-21.
[14]	Chen F, Du D S. Application of the integration of spatial statistical analysis with GIS to the analysis of regional economyic analysis［J］. Geo-Spatial Information Science, 2004, 7(4):262-267.
[15]	Griffith D A, Chun Y. Spatial Autocorrelation in Spatial Interactions Models: Geographic Scale and Resolution Implications for Network Resilience and Vulnerability［J］. Networks and Spatial Economics, 2014: 1-29.
[16]	Moran P. The Interpretation on Statistical Maps［J］. Journal of the Royal Statistical Society, Series,1948, 37 (10): 243-251.
[17]	陈翠英，江永真．土壤养分空间变异性的随机模拟及其应用［J］. 农业机械学报，2006，37(12)：67-70,95.
[18]	杨奇勇，蒋忠诚，罗为群，等. 岩溶峰丛洼地山体阴影区域植被指数的随机模拟［J］. 农业机械学报，2013，44(5)：232-237.
[19]	司涵，张展羽，吕梦醒，等. 小流域土壤氮磷空间变异特征分析［J］. 农业机械学报，2014, 45(3)：90-96.
[20]	Anselin L. GeoDa 0.9 User's Guide. Spatial Analysis Laboratory, University of Illinois, Urbana-Champaign, IL. 2003.
[21]	胡伟，邵明安，王全九. 黄土高原退耕坡地土壤水分含量空间变异的尺度性研究［J］. 农业工程学报，2005, 2l (8): 11-16.