粗颗粒土壤坡面侵蚀泥沙颗粒特征

杨青松; 倪世民; 王军光; 蔡崇法

doi:10.13870/j.cnki.stbcxb.2022.04.005

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粗颗粒土壤坡面侵蚀泥沙颗粒特征

更新时间：2025-03-12

- 粗颗粒土壤坡面侵蚀泥沙颗粒特征
- Characteristics of Erosion and Sediment Particles on Coarse Texture Soil Slope
- 水土保持学报 2022年36卷第4期页码：30-36
- 作者机构：
  
  华中农业大学水土保持研究中心, 农业农村部长江中下游耕地保育重点实验室,武汉,430070
- 作者简介：
  
  [ "杨青松(1997—),男,在读硕士研究生,主要从事土壤侵蚀机理研究。E-mail:yqsynl_4545@163.com" ]
- 基金信息：
  
  国家自然科学基金项目（42177317）
- DOI：10.13870/j.cnki.stbcxb.2022.04.005
  中图分类号： S157.1
- 纸质出版：2022
- 稿件说明：
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杨青松, 倪世民, 王军光, 等. 粗颗粒土壤坡面侵蚀泥沙颗粒特征[J]. 水土保持学报, 2022,36(4):30-36.

YANG Qingsong, NI Shimin, WANG Junguang, et al. Characteristics of Erosion and Sediment Particles on Coarse Texture Soil Slope[J]. 2022, 36(4): 30-36.
杨青松, 倪世民, 王军光, 等. 粗颗粒土壤坡面侵蚀泥沙颗粒特征[J]. 水土保持学报, 2022,36(4):30-36. DOI： 10.13870/j.cnki.stbcxb.2022.04.005.

YANG Qingsong, NI Shimin, WANG Junguang, et al. Characteristics of Erosion and Sediment Particles on Coarse Texture Soil Slope[J]. 2022, 36(4): 30-36. DOI： 10.13870/j.cnki.stbcxb.2022.04.005.

摘要

为揭示粗颗粒土壤坡面侵蚀机理，采用湖北通城县、江西赣县、福建长汀县、广东五华县4个样地的4种粗颗粒土壤（分别定义为TCA、GXA、CTA、WHA）进行室内模拟降雨试验，研究粗颗粒土壤坡面侵蚀过程及侵蚀泥沙颗粒组成的变化规律。结果表明：（1）4种土壤的地表径流随着降雨时间的增长呈现出先增加后递减并趋于稳定的规律；（2）4种土壤的侵蚀特征存在差异，土壤侵蚀速率表现为WHA>TCA>GXA>CTA；（3）4种土壤的侵蚀泥沙中颗粒分布百分比大小均为砂粒>黏粒>粉粒>砾石。不同土壤侵蚀泥沙富集率表现出明显差异；（4）水流功率与土壤侵蚀速率的相关性显著，用幂函数可以准确描述其关系。在表达式中引入土壤黏粒含量、砾石含量后模型更加可靠（Dr=0.001ω1.163Cl-4.069，R2=0.82；Dr=0.003ω1.149Gr-1.934，R2=0.84），提高了模型预测土壤侵蚀速率的精度，在实际应用中具有更广的适应范围与现实价值。

Abstract

To reveal the slope erosion mechanism of coarse texture soil in China

we conducted the indoor rainfall simulation experiments with the four coarse texture soils (sieved soils of TCA

GXA

CTA

WHA from the counties of Tongcheng

Ganxian

Changting and Wuhua

China) to discussed the slope erosion process and sediment particle composition of coarse texture soil. The results showed:(1) The changes of surface runoff characteristics of the soils were significant. The surface runoff increased with the extension of rainfall time

and then decreased and tended to be stable. (2) The erosion characteristics of the soils were different

and the soil erosion rate decreased in the order of WHA>TCA>GXA>CTA. (3) The percentage of grain distribution in erosion sediment of the soils decreased in the order of Clay>Silt>Sand>Gravel. The enrichment ratio of different soils showed obvious difference. (4) There was a significant correlation between water flow power and soil erosion rate

and the relationship between them could be accurately described by power function. The model was more reliable after introducing the soil clay and gravel contents in the expression(Dr=0.001ω1.163Cl-4.069

R2=0.82; Dr=0.003ω1.149Gr-1.934

R2=0.84). The accuracy of predicting soil erosion rate was improved with a wider range of application and more realistic value in practice.

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