黑河中下游防风固沙功能时空变化及影响因子分析

彭婉月; 王兆云; 李海东; 柳本立

doi:10.13198/j.issn.1001-6929.2020.10.28

黑河中下游防风固沙功能时空变化及影响因子分析

doi: 10.13198/j.issn.1001-6929.2020.10.28

彭婉月^{1, 2, 3,},
王兆云^{1, 2, 3},
李海东⁴,
柳本立^{1, 2, ,}

1.
中国科学院西北生态环境资源研究院沙漠与沙漠化重点实验室, 甘肃兰州 730000
2.
甘肃省戈壁荒漠生态与环境野外科学观测研究站(敦煌), 甘肃兰州 730000
3.
中国科学院大学, 北京 100049
4.
生态环境部南京环境科学研究所, 江苏南京 210042

基金项目:

国家重点研发计划项目 2018YFD1100104

中国科学院青年创新促进会项目 2016373

详细信息

作者简介:
彭婉月(1998-), 女, 江西景德镇人, wanyue@lzb.ac.cn

通讯作者:
柳本立(1986-), 男, 河南漯河人, 副研究员, 博士, 主要从事风沙灾害防治研究, liubenli@lzb.ac.cn

中图分类号: X901
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- 被引次数: 0
出版历程
- 收稿日期: 2020-05-23
- 修回日期: 2020-10-13
- 刊出日期: 2020-12-25

Spatio-Temporal Changes of Sand-Fixing Function and Its Driving Forces in the Middle and Lower Reaches of Heihe River Basin

PENG Wanyue^{1, 2, 3
,},
WANG Zhaoyun^{1, 2, 3},
LI Haidong⁴,
LIU Benli^{1, 2
, ,}

1.
Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2.
Research Station of Gobi Desert Ecology and Environment in Dunhuang of Gansu Province, Lanzhou 730000, China
3.
University of Chinese Academy of Sciences, Beijing 100049, China
4.
Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing 210042, China

Funds:

National Key Research and Development Program of China 2018YFD1100104

Youth Innovation Promotion Association of CAS, China 2016373

摘要

摘要: 黑河中下游是我国重要的防风固沙生态功能区，分析该区域的防风固沙功能时空变化，明确其主要的影响因子贡献，对于指导荒漠化防治、维护流域生态安全十分重要.该研究基于修正风蚀方程(revised wind erosion equation，RWEQ)、一元线性回归斜率分析、灰色关联分析和GIS技术，分析了2000—2017年黑河中下游防风固沙功能动态变化及其影响因子.结果表明：①2000—2017年，黑河中下游年均防风固沙量为3.2×10⁹ t，年均防风固沙功能约为2.44×10⁴ t/km²；防风固沙量总体呈增强趋势，年均增加6.67×10⁷ t，年均变化率为1.85%.②区域防风固沙功能呈现中游较强，向下游递减的空间分布特征，防风固沙功能较高区约占研究区面积的31.54%，一般区占20.77%，较低区(北部荒漠区)占47.69%；甘肃省张掖市和嘉峪关市防风固沙功能呈增加趋势，回归方程系数(slope)为0~26.29%，占总面积的12.51%；额济纳旗东北部和甘肃省高台县中部防风固沙功能呈下降趋势，回归方程系数为-17.17%~0，占总面积的23.30%.③防风固沙功能主要影响因子中，风力因子最主要，贡献率为30.04%，其次为积雪覆盖、土壤湿度、植被覆盖，贡献率分别为24.57%、24.26%和21.13%.研究显示，防风固沙工程应综合考虑气候变化、植被覆盖、土壤特性及人类活动的复合影响，实行具有空间差异化的方案.
- 黑河 /
- 土壤风蚀 /
- 时空变化 /
- 防风固沙功能 /
- 修正风蚀方程
Abstract: The Heihe Basin is located in the middle of the Hexi Corridor is the second largest inland basin in northwest China. The middle and lower reaches of the Heihe Basin are important ecological function areas in terms of wind prevention and sand fixation. To control the desertification and maintain the ecological security of this region, it is necessary to analyze the temporal and spatial patterns of windbreak and sand-fixing ability, and to quantify the contributions of different driving forces. In the current study, we integrated the revised wind erosion equation (RWEQ), and carried out slope analysis of unary linear regression and grey relational analysis, and used GIS technology. Multi-years of wind, soil moisture, snow cover, vegetation cover, and soil surface characteristics were collected as input parameters. The results are as follows. (1) From 2000 to 2017, the average annual sand-fixing capacity of this region reached 3.2 billion tons in total, or 2.44×10⁴ t/km². The average annual sand-fixing capacity increased 6.67×10⁷ t per year with an average change rate of 1.85%. (2) The sand-fixing function showed a decreasing trend from the middle reach in the south to the lower reach in the north. Areas with high, medium and low sand-fixing functions accounted for 31.54%, 20.77% and 47.69% of the study area, respectively. It was found that the function increased mainly in Zhangye City and Jiayuguan City, with unary linear regression coefficient (slope) ranging from 0 to 26.29%, accounting for 12.51% of the total area, while decreasing trend areas mainly distributed in the northeast Ejin Banner and in the central Gaotai County, with slope between -17.17% and 0 and accounting for 23.30% of the total area. (3) Wind was the most important factor causing 30.04% of sand-fixing function variation, followed by snow cover, soil moisture and vegetation coverage with 24.57%, 24.26% and 21.13% contributions, respectively. It is suggested that the projects to prevent soil wind erosion and control desertification should consider the combined effects of climate change, vegetation coverage, soil characteristics, and human activities, and that differentiated approaches should be considered for areas with different conditions. Future changes of sand-fixing function in the study area will be estimated using the IPCC-projected climate data.
- Heihe Basin /
- wind erosion /
- temporal and spatial variation /
- sand-fixing function /
- revised wind erosion equation

HTML全文

图 1 黑河中下游遥感镶嵌图

注：数据来源于赵军, 王建华.国家青藏高原科学数据中心(http://data.tpdc.ac.cn/zh-hans)，2015.

Figure 1. Remote sensing mosaicking map of the middle and lower reaches of Heihe River Basin

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图 2 黑河中下游多年平均土壤风蚀模数及防风固沙功能空间分布

Figure 2. Distributions of average soil wind erosion modulus and average sand-fixing function in the middle and lower reaches of Heihe River Basin

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图 3 2000—2017年黑河中下游年防风固沙功能变化趋势

Figure 3. Variation in sand-fixing function between 2000 and 2017 in the middle and lower reaches of Heihe River Basin

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图 4 2000—2017年黑河中下游土壤风蚀模数变化

Figure 4. Changes of soil wind erosion modulus in the middle and lower reaches of Heihe River Basin from 2000 to 2017

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图 5 代表性年份的黑河中下游土壤风蚀模数变化

Figure 5. Distribution of soil wind erosion modulus in the middle and lower reaches of Heihe River Basin at four representative years

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图 6 2000—2017年黑河中下游防风固沙功能变化

Figure 6. Changes of sand-fixing function in the middle and lower reaches of Heihe River Basin from 2000 to 2017

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图 7 代表性年份的黑河中下游防风固沙功能变化

Figure 7. Distribution of sand-fixing function in the middle and lower reaches of Heihe River Basin at four representative years

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图 8 黑河中下游防风固沙功能主要影响因子空间分布

Figure 8. Distribution of the main driving factors of sand-fixing function in the middle and lower reaches of Heihe River Basin

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图 9 黑河中下游2000—2017年植被覆盖度变化趋势

Figure 9. Variation in vegetation coverage between 2000 and 2017 in the middle and lower reaches of Heihe River Basin

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图 10 各主要影响因子与防风固沙功能关联系数

Figure 10. Correlation coefficients between sand-fixing function and its driving forces

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表 1 数据来源介绍

Table 1. Introduction of data sources

数据名称	数据类型	时间分辨率	空间分辨率或比例尺	数据来源
气象数据	TXT	日	—	中国气象数据网(http://data.cma.cn/data/cdcdetail/dataCode/SURF_CLI_CHN_MUL_DAY.html)
土壤湿度数据	NETCDF	月	0.5°	NOAA(https://psl.noaa.gov/data/gridded/data.cpcsoil.html)
中国雪深长时间序列数据集	TXT	日	25 km	国家青藏高原科学数据中心(http://data.tpdc.ac.cn/zh-hans/data/df40346a-0202-4ed2-bb07-b65dfcda9368/?q=中国雪深长时间序列数据集)，参考文献[34-36]
黑河流域土壤粒径分布数据集	TIFF	—	0.008 33°	国家青藏高原科学数据中心(http://data.tpdc.ac.cn/zh-hans/data/cae9a5c0-8ab8-4952-9869-f736f824d2bd/?q=黑河流域土壤粒径分布数据集)，参考文献[37]
面向陆面模拟的中国土壤数据集	NETCDF	—	30″	国家青藏高原科学数据中心(http://data.tpdc.ac.cn/zh-hans/data/11573187-fd64-47b1-81a6-0c7c224112a0/?q=面向陆面模拟的中国土壤数据集)，参考文献[38]
中国土壤有机质数据集	NETCDF	—	30″	国家青藏高原科学数据中心(http://data.tpdc.ac.cn/zh-hans/data/8ba0a731-5b0b-4e2f-8b95-8b29cc3c0f3a/?q=中国土壤有机质数据集)
MOD13A3	HDR	月	1 km	NASA(https://ladsweb.modaps.eosdis.nasa.gov)
GDEM DEM	IMG	—	30 m	地理空间数据云(http://www.gscloud.cn)

下载: 导出CSV

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