黄河小浪底库区土壤侵蚀驱动因子定量归因分析

余万洋; 赵龙山; 张劲松; 孟平; 巴音吉; 张金鑫

doi:10.13870/j.cnki.stbcxb.2023.03.021

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黄河小浪底库区土壤侵蚀驱动因子定量归因分析

更新时间：2025-03-12

- 黄河小浪底库区土壤侵蚀驱动因子定量归因分析
- Quantitative Attribution Analysis of Driving Factors of Soil Erosion in Xiaolangdi Reservoir Area of the Yellow River
- 水土保持学报 2023年37卷第3期页码：155-163
- 作者机构：
  
  1. 贵州大学林学院,贵阳,550025
  2. 中国林业科学研究院林业研究所,北京,100091
  3. 中国地质调查局烟台海岸带地质调查中心,山东,烟台,264004
- 作者简介：
  
  [ "余万洋(1996—),男,贵州六盘水人,博士研究生,主要从事土壤侵蚀与水土保持研究。E-mail:wanyangyu2022@163.com" ]
- 基金信息：
  
  财政部地质矿产与资源环境调查专项(ZD20220142);国家重点研发计划项目(2020YFA0608101);中国博士后科学基金项目(2020M670527)
- DOI：10.13870/j.cnki.stbcxb.2023.03.021
  中图分类号： S157.1
- 纸质出版：2023
- 稿件说明：
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余万洋, 赵龙山, 张劲松, 等. 黄河小浪底库区土壤侵蚀驱动因子定量归因分析[J]. 水土保持学报, 2023,37(3):155-163.

YU Wanyang, ZHAO Longshan, ZHANGJinsong, et al. Quantitative Attribution Analysis of Driving Factors of Soil Erosion in Xiaolangdi Reservoir Area of the Yellow River[J]. 2023, 37(3): 155-163.
余万洋, 赵龙山, 张劲松, 等. 黄河小浪底库区土壤侵蚀驱动因子定量归因分析[J]. 水土保持学报, 2023,37(3):155-163. DOI： 10.13870/j.cnki.stbcxb.2023.03.021.

YU Wanyang, ZHAO Longshan, ZHANGJinsong, et al. Quantitative Attribution Analysis of Driving Factors of Soil Erosion in Xiaolangdi Reservoir Area of the Yellow River[J]. 2023, 37(3): 155-163. DOI： 10.13870/j.cnki.stbcxb.2023.03.021.

摘要

为评价小浪底库区30年来土壤侵蚀特征及其影响因素

基于RUSLE模型

估算小浪底库区1990—2020年土壤侵蚀模数

分析土壤侵蚀时空变化特征

并结合地理探测器定量分析植被覆盖度、土地利用类型、海拔、坡度和降雨量等影响因子对土壤侵蚀格局的影响。结果表明:(1)小浪底库区土壤侵蚀模数从1990年的3 150 t/(km2·a)下降至2020年的1 554 t/(km2·a)

土壤流失总量减少50.00%。高等级土壤侵蚀持续向低等级侵蚀转变

从1990—2020年

剧烈、极强烈、强烈、中度和轻度侵蚀面积分别下降53.92%

64.51%

55.65%

39.68%和3.28%

而微度侵蚀面积则上升41.13%。现阶段土壤侵蚀强度以微度侵蚀为主

其次是轻度侵蚀

两者分别占总侵蚀面积的60.02%和24.08%。(2)小浪底库区严重的土壤侵蚀主要分布在库区西南部(平陆县、陕州区)、东南部(济源市、孟津县)和中部(垣曲县)等人类活动集中的部分地区

但在时空上呈收缩聚集的特征。(3)植被覆盖度与土地利用类型对小浪底库区土壤侵蚀强度的解释力高于其他因子

植被覆盖度最高可解释42.09%的土壤侵蚀

土地利用类型最高可解释28.64%的土壤侵蚀

双因子的协同作用增强对土壤侵蚀的解释力。低海拔(＜718 m)、缓坡(8°~16°)地区由于人类活动可及性高

植被覆盖度较低是土壤侵蚀的高风险区

可加强这些区域的生态恢复及水土保持措施建设。

Abstract

In order to evaluate the characteristics of soil erosion and its driving factors in the Xiaolangdi Reservoir area in the past 30 years

this study estimated the soil erosion modulus in the Xiaolangdi Reservoir area from 1990 to 2020 based on the Revised Universal Soil Loss Equation (RUSLE)

and analyzed the spatial-temporal variation characteristics of soil erosion. Then combined with geographic detector

the effects of vegetation coverage

land use type

altitude

slope and rainfall on soil loss patterns were quantitatively analyzed. Results showed that: (1) The soil erosion modulus in the Xiaolangdi reservoir area decreased from 3 150 t/(km2·a) in 1990 to 1 554 t/(km2·a) in 2020

and the total soil erosion decreased by 50.00%. The intensity of soil erosion also changed from high level to lower level. From 1990 to 2020

the area of extremely severe

very severe

severe

moderate and slight erosion decreased by 53.92%

64.51%

55.65%

39.68% and 3.28%

respectively. While the area of very slight erosion increased by 41.13%. At the present stage

the main erosionintensity was very slight erosion

followed by slight erosion

which accounted for 60.02% and 24.08% of the total erosion area

respectively. (2) Serious soil erosion in the Xiaolangdi Reservoir area was mainly distributed in the southwest (Pinglu County

Shanzhou District)

southeast (Jiyuan City

Mengjin County) and central (Yuanqu County) of the reservoir area where human activities are concentrated

but it tended to shrink and gather in time and space. (3) Vegetation coverage and land use type had higher explanatory power than other factors

vegetation coverage could explain up to 42.09% of soil erosion

while land use type could explain up to 28.64% of soil erosion

and the interaction of different factors enhanced the explanatory power of soil erosion risk. Low altitude (< 718 m) and gentle slope (8°~16°) areas were high risk areas for soil erosion due to the high accessibility of human activities and low vegetation coverage. Ecological restoration and soil and water conservation measures in these areas should be strengthened.

关键词

Keywords

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