生态与农村环境学报 ›› 2018, Vol. 34 ›› Issue (1): 74-80.doi: 10.11934/j.issn.1673-4831.2018.01.009

• 自然保护与生态 • 上一篇    下一篇

大柳塔矿区农田砂壤土含水率对土壤紧实度的影响及模型研究

陈秀琴1,2, 杜国强1,2, 杨德军1,2   

  1. 1. 中国矿业大学环境与测绘学院, 江苏徐州 221116;
    2. 徐州徐工环境技术有限公司, 江苏徐州 221116
  • 收稿日期:2016-09-12 出版日期:2018-01-25 发布日期:2018-01-26
  • 通讯作者: 杨德军 E-mail:yangdj81@163.com
  • 作者简介:陈秀琴(1990-),女,甘肃张掖人,硕士生,主要从事环境工程方面的研究。E-mail:cxq2393818839@163.com
  • 基金资助:

    江苏省普通高校专业学位研究生创新计划(SJZZ16-0281);西部重点矿区土地退化因素调查项目(2014FY110800);国家自然科学基金重点项目(U1361214);国家重点基础研究发展计划(2013CB227904)

Effect of Moisture Content on Compactness of Sandy Loam Soil of Farmland in Daliuta Mine and Modelling

CHEN Xiu-qin1,2, DU Guo-qiang1,2, YANG De-jun1,2   

  1. 1. School of Environment Science and Spatial Informatics, China University of Mining & Technology, Xuzhou 221116, China;
    2. Xuzhou XCMG Environmental Technology Co. Ltd., Xuzhou 221116, China
  • Received:2016-09-12 Online:2018-01-25 Published:2018-01-26

摘要:

选取陕西省大柳塔矿区农田砂壤土作为研究对象,实地测定了土壤紧实度和土壤含水率,对所测数据进行统计分析和线性拟合,并结合4种半经验模型进行对比分析和模拟预测。结果表明:在收割初期大柳塔矿区农田土壤紧实度最低,土壤含水率最高,种植绿豆降低土壤紧实度的效果较好;土壤紧实度与含水率w(8.30%~16.14%)呈线性负相关;线性模型和4种半经验模型均在玉米种植区的拟合效果最好,相关系数均大于0.7;Ayers模型预测效果最佳,能较好地反映半干旱矿区土壤状况。

关键词: 土壤紧实度, 土壤含水率, 相关关系, 模型预测

Abstract:

Farmlands of sandy loam soil in the Daliuta mining in Shaanxi Province was chosen as object of the study. Soil compactness and moisture content was measured in situ for statistical analysis and linear fitting, and furthermore, for comparative analysis in combination with four semi-empirical models in simulation and prediction. Results show that soil at the early harvesting stage was the lowest in compactness, and the highest in soil moisture content; Planting of mung bean reduced soil compactness fairly; soil moisture content in the range of 8.30%-16.14% was linearly and negatively related to soil compactness; The linear model and the four semi-empirical models all fitted well in Area B (corn), with correlation coefficients being all higher than 0.7; Among the models, the Ayers model performed the best in prediction, which means that the model can be used to predict soil conditions of the semi-arid mining areas.

Key words: soil compaction, moisture content, correlation, model prediction

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