Soil Erosion Processes on Sloping Grassland in Heaven Lake Nature Reserve of Xinjiang Wei Autonomous Region

WANG Da-qing; ZHOU Hong-fei; MA Jian; JIN Fa-jun; YIN Xiang-jiang

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Soil Erosion Processes on Sloping Grassland in Heaven Lake Nature Reserve of Xinjiang Wei Autonomous Region

- Soil Erosion Processes on Sloping Grassland in Heaven Lake Nature Reserve of Xinjiang Wei Autonomous Region
- Bulletin of Soiland Water Conservation Vol. 28, Issue 3, Pages: 127-129(2009)
- 作者机构：
  
  1. 石河子大学,新疆,石河子,832000
  2. 中国科学院新疆生态与地理研究所新疆阜康,831505
  4. 中国科学院阜康荒漠生态系统观测试验站,新疆,乌鲁木齐,830011
  5. 天池管理委员会新疆阜康,831500
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2009
- 稿件说明：
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WANG Da-qing, ZHOU Hong-fei, MA Jian, et al. Soil Erosion Processes on Sloping Grassland in Heaven Lake Nature Reserve of Xinjiang Wei Autonomous Region[J]. Bulletin of Soiland Water Conservation, 2009, 28(3): 127-129.
DOI：

WANG Da-qing, ZHOU Hong-fei, MA Jian, et al. Soil Erosion Processes on Sloping Grassland in Heaven Lake Nature Reserve of Xinjiang Wei Autonomous Region[J]. Bulletin of Soiland Water Conservation, 2009, 28(3): 127-129. DOI：

摘要

通过对天山天池自然保护区径流小区的定位观测试验，采用数据统计分析的方法，对天山天池自然保护区草地坡地土壤侵蚀规律进行了研究。结果表明，(1)径流深随降雨量、降雨强度、坡度的增加而增大，而侵蚀量与降雨强度的关系比较明显；(2)植被显著地影响着坡地产沙量；(3)坡面径流深与降雨量、降雨强度、坡度之间的关系可以用多元线性回归函数很好地描述；(4)侵蚀量与土壤容重、径流深、降雨量、降雨强度之间的关系也可以用多元线性回归函数很好地描述。

Abstract

Through the located runoff plot observations in the Heaven Lake Nature Reserve of Xinjiang Wei Autonomous Region

soil erosion processes on sloping grassland were investigated.Results show that firstly

runoff depth increases with the increased rainfall amount

rainfall intensity

and gradient.The relationship between sediment and rainfall intensity is apparent.Secondly

grass has great influences on sediment yield on sloping grassland.Thirdly

the relatio nship among runoff depth

rainfall amount

rainfall intensity

and gradient can be well described by multiple linear regression function.Lastly

the relationship among sediment

soil bulk density

runoff depth

rainfall amount

and rainfall intensity can also be well described by multiple linear regression function.

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