PDF Download

[1]YANG Meiling,WANG Xuemei,LUO Mengyuan.Study on Spatial Variability of Topsoil Nutrients in Kuqa County Based on GIS[J].Research of Soil and Water Conservation,2015,22(01):61-65.

Copy

Study on Spatial Variability of Topsoil Nutrients in Kuqa County Based on GIS

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 22 Number of periods: 2015 01 Page number: 61-65 Column: Public date: 2015-02-28

Title:: Study on Spatial Variability of Topsoil Nutrients in Kuqa County Based on GIS

Author(s):: YANG Meiling¹, WANG Xuemei^1,2, LUO Mengyuan¹; 1. College of Geography Science and Tourism, Xinjiang Normal University, Urumqi 830054, China;
2. Xinjiang Uygur Autonomous Region Key Laboratory Xinjiang Laboratory of Lake Environment and Resources in Arid Zone, Urumqi 830054, China

Keywords:: spatial variability; soil nutrients; topsoil; Kuqa County

CLC:: S158.2;S158.5

DOI:: -

Abstract:: Based on the analysis methods of GIS and geostatistics, spatial variability characteristics of topsoil (0—20 cm) nutrient elements in Kuqa County were studied, the results showed that organic matter, total nitrogen, phosphorus and potassium are moderate degree of spatial variability and the coefficients of variation are 19.11%~65.34%. Theoretical models of organic matter and total nitrogen are fitful of spherical model, nitrogen, phosphorus and potassium fit the exponential model. Organic matter, total nitrogen, available nitrogen, phosphorus and potassium present a moderate degree of spatial autocorrelation due to combined effect of soil type, soil texture and fertilization. From the spatial distribution, the contents of organic matter, total nitrogen, available nitrogen and potassium showed significant flaky and patchy distribution in the southeast, decremented from southeast to the northwest, while phosphorus mainly presented plaques massive distribution, which was higher than the northeast to the southwest. In the study area, the contents of topsoil nutrients overall present the patterns that the southeast is higher than northwest direction.

References:: [1] 姜广辉,赵婷婷,段增强,等.北京山区耕地质量变化及未来趋势模拟[J].农业工程学报,2010,26(10):304-311.
[2] 左太安,苏维词,宋增伟,等.针对水土流失的三峡重庆库区土地质量评价[J].水土保持通报,2009,29(2):183-187.
[3] Pozdnyakova L, Zhang R. Geo-statistical analyses of soil salinity in a large field[J]. Precision Agriculture,1999,1(2):153-165.
[4] 刘志鹏,黄土高原地区土壤养分的空间分布及其影响因素[D].陕西杨凌:中国科学院教育部水土保持与生态环境研究中心,2013:20-26.
[5] 王激清,张宝悦.冀西北农牧交错带土壤养分时空变异与生产特性研究[J].干旱区资源与环境2014,28(3):86-90.
[6] 郭旭东,傅伯杰,陈利顶,等.河北省遵化平原土壤养分的时空变异特征:变异函数与Kriging插值分析[J].地理学报,2000,55(5):555-566.
[7] 范夫静,宋同清,黄国勤,等.西南峡谷型喀斯特坡地土壤养分的空间变异特征[J].应用生态学报,2014,25(1):92-98.
[8] 阿依古丽·买买提,吉力力·阿不都外力,葛拥晓.玛纳斯河流域绿洲土壤养分空间变异特征与格局[J].干旱区资源与环境,2013,27(9):153-159.
[9] 石淑芹,曹祺文,李正国,等.区域尺度土壤养分的协同克里格与普通克里格估值研究[J].干旱区资源与环境,2014,28(5):109-114.
[10] 王岩,陈永金,刘加珍.黄河三角洲湿地土壤养分空间分布特征[J].人民黄河,2013,35(2):72-74.
[11] 胡艳霞,周连第,魏长山,等.水源保护地土壤养分空间变异特征及其影响因素分析[J].土壤通报,2013,44(5):1184-1191.
[12] 刘伟.洞庭湖区耕地土壤养分评价与空间变异性研究[D].长沙:中南林业科技大学,2013:12-25.
[13] 农业部.中华人民共和国农业行业标准、测土配方施肥技术规范[S].北京:中国农业出版社,2006.
[14] 中国科学院南京土壤研究所.土壤理化分析[M].上海:上海科技出版社,1978:93-129.
[15] 刘成林,曹养同,杨海军,等.库车前陆盆地古近纪-新近纪盐湖环境变迁及其成钾效应探讨[J].地球学报,2013,34(5):547-558.
[16] 刘祖香,陈效民,靖彦,等.基于地统计学的农田尺度旱地红壤养分空间变异性研究[J].土壤通报,2013,44(2):392-397.
[17] 年佳乐,李跃进,景宇鹏,等.盐渍土有效态微量元素含量的空间变异特征研[J].中国农业科技导报,2013,15(4):163-167.
[18] 方斌,吴金凤.作物种植前后土壤有机质及养分因子的空间变异性分析[J].生态学报,2014,34(4):1-10.
[19] 李强,周冀衡,张永安,等.曲靖植烟土壤有效微量元素的空间变异和影响因子[J].烟草农学2013(10):63-69.
[20] 庞夙,李延轩,王永东,等.土壤速效氮、磷、钾含量空间变异特征及其影响因子[J].植物营养与肥料学报2009,15(1):114-120.

Similar References:

Memo

Last Update: 1900-01-01