黄土高原作物C因子新方法

谢欣利; 李晴岚; 王林华; 张晖; 吴发启

doi:10.13870/j.cnki.stbcxb.2025.01.022

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黄土高原作物C因子新方法

更新时间：2025-03-14

- 黄土高原作物C因子新方法
- A New Method to Estimate the Cover Management Factor on the Loess Plateau in China
- 水土保持学报 2025年39卷第1期页码：294-302
- 作者机构：
  
  1. 西北农林科技大学黄土高原土壤侵蚀与旱地农业国家重点实验室, 陕西杨凌,712100
  2. 中国科学院深圳先进技术研究院,广东,深圳,518055
  3. 深圳市自然资源与不动产评估发展研究中心,广东,深圳,518055
  4. 中国科学院华南植物园,广州,510650
- 作者简介：
  
  [ "谢欣利(1994—), 女, 博士研究生, 主要从事土壤侵蚀研究。E-mail: xinli-xie@nwafu.edu.cn" ]
- 基金信息：
  
  国家自然科学基金项目(41977065, 41271288);国家基础研究计划项目(2007CB407201-5)
- DOI：10.13870/j.cnki.stbcxb.2025.01.022
  中图分类号： S154.3
- 纸质出版：2025
- 稿件说明：
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谢欣利, 李晴岚, 王林华, 等. 黄土高原作物C因子新方法[J]. 水土保持学报, 2025,39(1):294-302.

XIE Xinli, LI Qinglan, WANG Linhua, et al. A New Method to Estimate the Cover Management Factor on the Loess Plateau in China[J]. 2025, 39(1): 294-302.
谢欣利, 李晴岚, 王林华, 等. 黄土高原作物C因子新方法[J]. 水土保持学报, 2025,39(1):294-302. DOI： 10.13870/j.cnki.stbcxb.2025.01.022.

XIE Xinli, LI Qinglan, WANG Linhua, et al. A New Method to Estimate the Cover Management Factor on the Loess Plateau in China[J]. 2025, 39(1): 294-302. DOI： 10.13870/j.cnki.stbcxb.2025.01.022.

摘要

目的为探究不同作物覆盖与管理措施下坡面土壤流失率、作物覆盖与管理因子的响应机制，以便更精准地评价作物覆盖与管理措施对土壤侵蚀的抑制作用。方法以谷子为研究对象，采用人工模拟降雨，设置作物、有糙度作物、有结皮作物、裸露、有糙度、有结皮6个小区坡面条件，分别记作A1、A2、A3、B1、B2、B3。通过Matlab数值模拟得到SLR估算模型，结合降雨侵蚀力分布曲线计算不同C因子值。结果地表糙度、土壤结皮均能进一步减弱作物小区的水土流失，与作物小区相比，有糙度作物小区SLR平均减少21.00%，有结皮作物小区平均减少16.50%。得到的作物、有糙度作物、有结皮作物小区土壤侵蚀率模型3种土壤侵蚀率模型，结合降雨侵蚀力分布情况可计算全生育期C因子值。经淳化野外数据验证，作物、有糙度作物、有结皮作物小区土壤侵蚀率模型均可达到较精确的预测效果，其全生育期估算C因子分别为0.30、0.25、0.25，纳什系数分别为0.96、0.87、0.75。结论研究结果为开展全国性的C因子研究提供一定参考依据。

Abstract

ObjectiveTo investigate the combined effect of crop cover and crop management practices on preventing soil loss and improving the accuracy of C-factor estimation.MethodsSix millet plots with different treatments

i. e.

crop plot (C1)

crop-roughness plot (C2)

crop-crust plot (C3)

bare plot (B1)

roughness plot (B2)

and crust plot(B3)

were established and the soil loss at four growth stage was determined under simulated rainfall. The C factor was calculated using soil loss ratio (SLR). The major factors affecting SLR were also analyzed and their correlations with SLR were then regressed through numerical simulation using MATLAB. Subsequently

the SLR estimation models designed for soil erosion prediction on the Loess Plateau could be built. Finally

the C factor could be calculated using the proposed SLR estimation model combined with the distribution curve of rainfall erosivity.ResultsSurface roughness and soil crust could reduce soil loss in crop plot. Compared with SLRcrop

SLRcrop-roughness and SLRcrop-crust were on average 21.00% and 16.50% lower

respectively. The model formulas of crop plot

crop-roughness plot

crop-crust plot were obtained

through validating by field soil and water loss data conducted in Chunhua County

the model formulas could achieve accurate prediction. The estimated C values for the whole growth stage were 0.30

0.25 and 0.25

respectively

with the Nash coefficients being 0.96

0.87 and 0.75

respectively.ConclusionThe results can provide some insights for estimating C values at national scales.

关键词

Keywords

references

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