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中国农学通报

中国农学通报 ›› 2014, Vol. 30 ›› Issue (17): 204-207.doi: 10.11924/j.issn.1000-6850.2013-3222

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

海口自然坡地土壤湿度变化特征分析

王刚 陈统强 高峰   

  • 收稿日期:2013-12-10 修回日期:2014-01-19 出版日期:2014-06-14 发布日期:2014-06-14
  • 基金资助:
    海南省自然科学基金项目 “海南省橡胶气象灾害时空分布特征” (411103)。

Analysis on the Soil Moisture Change Characters of Natural Slope in Haikou City

  • Received:2013-12-10 Revised:2014-01-19 Online:2014-06-14 Published:2014-06-14

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摘要： 为了更好地了解在气候变化大背景下，海口自然坡地土壤水分状况及影响因子。根据海口市琼山气象站2005—2011年的气象观测资料和自然坡地土壤湿度资料，利用统计学方法，分析海口市自然坡地土壤湿度的变化特征及其与气象因子的响应关系。结果表明：（1）自然土坡地10~50 cm土壤湿度年变化呈正趋势变化，各季节土壤湿度的变化与年变化一致，冬、春季土壤湿度变化大，不稳定；（2）10~ 50 cm土壤湿度月变化呈波形变化，2—10月土壤湿度呈上湿下干型，11—1月土壤湿度呈上干下湿型。（3）随土层深度的增加，土壤湿度的变化变小，各层间的土壤湿度差异越显著，40~50 cm上下层的土壤湿度差异达到极显著水平。（4）20 cm土壤湿度与其他层土壤湿度相关最为密切，利用20 cm土壤湿度作为10~50 cm土壤湿度的代表值与气象因子进行分析，土壤湿度与地温呈负相关，与降水量呈正相关，各季节20 cm土壤湿度回归方程通过1%的显著检验。

关键词: 幼龄胶园, 幼龄胶园, 间种, 甘蔗, 菠萝, 香蕉, 土壤肥力

Abstract: In order to better understand soil moisture of natural slope and related factors of Haikou in the context of climate change. Based on soil moisture data of natural slope and meteorological observation data from 2005 to 2011 in Qiongshan meteorological observation station at Haikou, the relationship between soil moisture of natural slope and meteorological factors were analyzed by statistical methods. Results were shown as follows: (1) the annual variation of soil moisture from 10 to 50 cm of natural slope had a positive trend, the seasonal variation be same to annual variation, but instability in winter and spring; (2) monthly variation of soil moisture from 10 to 50 cm had a wavy change, up wet and down dry during February to October and on the contrary during November to January; (3) as the depth of soil, the deeper moisture was more smaller, and the difference was more significant, especially in layer 40-50 cm. (4) soil moisture at 20 cm was closely related to the soil moisture, so used soil moisture at 20 cm to instead of soil moisture at 10-50 cm, and found that soil moisture had a negatively correlated with soil temperature, a positively correlated with precipitation, and the regression equations on soil moisture and meteorological factors on different seasons passed the T-test at a confidence level of 0.99.