img

Wechat

  • CN 62-1070/P
  • ISSN 1000-694X
  • Bimonthly 1981
Adv search

Comprehensive evaluation of land desertification sensitivity in the Horqin Sandy Land based on the coupling of AHP and improved MEDALUS model

  • Hanchen Duan ,
  • Beiying Huang
Expand
  • Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China

Received date: 2024-04-18

  Revised date: 2024-05-20

  Online published: 2024-08-29

Abstract

The Horqin Sandy Land, as a vital component of the “Three-North” Shelter Forest Project, necessitates specific and urgent research on desertification within the region. This study innovatively introduces the Analytic Hierarchy Process (AHP) to select and optimize indicators and factor variables from the original MEDALUS model, thereby enhancing the model and developing a new evaluation system for land desertification sensitivity. This system integrates indicators from five aspects: climate, soil, vegetation, land management, and socio-economic factors to assess the sensitivity of land desertification. Furthermore, the study employs the Geographic Detector (GD) model to explore the factors influencing the spatial differentiation of land desertification sensitivity in the Horqin Sandy Land. The findings reveal that: (1) Vegetation quality index has the highest weight in the index system for assessing land desertification sensitivity, with a weight coefficient as high as 0.4624, followed by the climate and soil quality indices. (2) Areas sensitive to desertification in the Horqin Sandy Land account for 78.22% of the study area, indicating a broad distribution of affected regions. Although the proportion of highly sensitive and extremely sensitive areas is relatively small (8.77%), these areas are concentrated and severely desertified. (3) Single-factor analysis shows that soil texture has the most significant impact on the spatial differentiation of land desertification sensitivity, followed by soil moisture content. Interaction effects demonstrate that factors such as drought resistance, Net Primary Productivity (NPP), temperature, soil moisture content, and soil texture significantly enhance their impact on the spatial differentiation of land desertification sensitivity when combined. The findings of this study can provide a scientific basis for formulating targeted and reliable priority desertification prevention plans and sustainable development models for the region.

Cite this article

Hanchen Duan , Beiying Huang . Comprehensive evaluation of land desertification sensitivity in the Horqin Sandy Land based on the coupling of AHP and improved MEDALUS model[J]. Journal of Desert Research, 2024 , 44(4) : 137 -148 . DOI: 10.7522/j.issn.1000-694X.2024.00062

References

1 Meng X Y, Gao X, Li S,et al.Monitoring desertification in Mongolia based on Landsat images and Google Earth Engine from 1990 to 2020[J].Ecological Indicators,2021,129:107908.
2 Zhou Y G, Hasi E, Wang Z R,et al.Dynamics of blowouts indicating the process of grassland desertification[J].Land Degradation & Development,2022,33(15):2885-2897.
3 Roy P, Pal S C, Chakrabortty R,et al.Climate change and geo-environmental factors influencing desertification:a critical review[J].Environmental Science and Pollution Research,2024,31(13):20343-20361.
4 Zhang J, Guan Q Y, Du Q Q,et al.Spatial and temporal dynamics of desertification and its driving mechanism in Hexi region[J].Land Degradation & Development,2022,33(17):3539-3556.
5 UNCCD.United nations convention to combat desertification in those countries experiencing serious drought and/or desertification particularly in africa:text with annexes[Z].Nairobi,Kenya:UNEP,1994.
6 Guo X N, Chen R S, Thomas D S G,et al.Divergent processes and trends of desertification in Inner Mongolia and Mongolia[J].Land Degradation & Development,2021,32(13):3684-3697.
7 Ferrara A, Kosmas C, Salvati L,et al.Updating the MEDALUS-ESA framework for worldwide land degradation and desertification assessment[J].Land Degradation & Development,2020,31(12):1593-1607.
8 吴建国,翟盘茂.关于气候变化与荒漠化关系的新认知[J].气候变化研究进展,2020,16(1):28-36.
9 刘俊壕,周海盛,郭群.中国北方干旱半干旱区沙漠化治理对植被格局的影响[J].中国沙漠,2023,43(5):204-213.
10 Shao W Y, Wang Q Z, Guan Q Y,et al.Environmental sensitivity assessment of land desertification in the Hexi Corridor,China[J].Catena,2023,220:106728.
11 王跃辉,张林波,郭杨,等.中国六省土地沙漠化敏感性时空格局与趋势分析[J].水土保持研究,2014,21(5):132-137.
12 孙滨峰,王效科.新疆沙漠化敏感性评价研究[J].西南师范大学学报(自然科学版),2015,40(7):108-112.
13 张慧,沈渭寿,王延松.临策铁路沿线土地沙漠化敏感性评价[J].生态与农村环境学报,2007,23(2):33-35.
14 姜旭海,韩玲,白宗璠,等.内蒙古自治区沙漠化敏感性时空演变格局和趋势分析[J].生态学报,2023,43(1):364-378.
15 D'Odorico P, Bhattachan A, Davis K F,et al.Global desertification:drivers and feedbacks[J].Advances in Water Resources,2013,51:326-344.
16 Song X, Wang T, Xue X,et al.Monitoring and analysis of aeolian desertification dynamics from 1975 to 2010 in the Heihe River Basin,northwestern China[J].Environmental Earth Sciences,2015,74(4):3123-3133.
17 Duan H C, Wang T, Xue X,et al.Dynamic monitoring of aeolian desertification based on multiple indicators in Horqin Sandy Land,China[J].Science of the Total Environment,2019,650:2374-2388.
18 赵哈林,苏永中,周瑞莲.我国北方沙区退化植被的恢复机理[J].中国沙漠,2006,26(3):323-328.
19 花婷,王训明.东亚干旱半干旱区沙漠化与气候变化相互影响研究进展[J].地理科学进展,2014,33(6):841-852.
20 常学礼,蔡明玉,张继平,等.科尔沁沙地典型地区人工造林对沙漠化过程的影响[J].中国沙漠,2009,29(4):611-616.
21 Karamesouti M, Panagos P, Kosmas C.Model-based spatio-temporal analysis of land desertification risk in Greece[J].Catena,2018,167:266-275.
22 Seddon A W R, Macias-Fauria M, Long P R,et al.Sensitivity of global terrestrial ecosystems to climate variability[J].Nature,2016,531(7593):229.
23 赵学勇,张春民,左小安,等.科尔沁沙地沙漠化土地恢复面临的挑战[J].应用生态学报,2009,20(7):1559-1564.
24 王涛.中国沙漠与沙漠化[M].石家庄:河北科学技术出版社,2003.
25 李新荣,周海燕,王新平,等.中国干旱沙区的生态重建与恢复:沙坡头站60年重要研究进展综述[J].中国沙漠,2016,36(2):247-264.
26 欧阳玲,马会瑶,王宗明,等.基于遥感与地理信息数据的科尔沁沙地生态环境状况动态评价[J].生态学报,2022,42(14):5906-5921.
27 Fan J Q, Xu Y, Ge H Y,et al.Vegetation growth variation in relation to topography in Horqin Sandy Land[J].Ecological Indicators,2020,113:106215.
28 岳喜元,左小安,赵学勇,等.科尔沁沙地沙漠化风险评价[J].中国沙漠,2018,38(1):8-16.
29 包苏日古嘎.生态恢复背景下科尔沁沙地植被净初级生产力时空变化研究[D].呼和浩特:内蒙古师范大学,2017.
30 赵欣,付蓉洁,辛存林,等.基于AHP的民勤县生态敏感性评价[J].西北师范大学学报(自然科学版),2022,58(6):38-46.
31 王奎峰,李娜.基于AHP和GIS耦合模型的山东半岛地质环境承载力评价[J].中国人口·资源与环境,2015,25():224-227.
32 Wang Y F, Zhang J Q, Guo E L,et al.Fuzzy Comprehensive evaluation-based disaster risk assessment of desertification in Horqin Sand Land,China[J].International Journal of Environmental Research and Public Health,2015,12(2):1703-1725.
33 Budak M, Günal H, ?elik I,et al.Environmental sensitivity to desertification in northern Mesopotamia; application of modified MEDALUS by using analytical hierarchy process[J].Arabian Journal of Geosciences,2018,11:481.
34 Xu D Y, You X G, Xia C L.Assessing the spatial-temporal pattern and evolution of areas sensitive to land desertification in North China[J].Ecological Indicators,2019,97:150-158.
35 Canora F, D'Angella A, Aiello A.Quantitative assessment of the sensitivity to desertification in the Bradano River Basin (Basilicata,southern Italy)[J].Journal of Maps,2015,11(5):745-759.
36 Yu Z Y, Deng X Z, Fu P,et al.Assessment of land degradation risks in the Loess Plateau[J].Land Degradation & Development,2024,35(7):2409-2424.
37 Jiang L L, Bao A M, Jiapaer G,et al.Monitoring land sensitivity to desertification in Central Asia:convergence or divergence [J].Science of the Total Environment,2019,658:669-683.
38 王劲峰,徐成东.地理探测器:原理与展望[J].地理学报,2017,72(1):116-134.
39 Zhang L, Jia X, Zhao Y H,et al.Spatio-temporal characteristics and driving mechanism of land degradation sensitivity in Northwest China[J].Science of the Total Environment,2024,918:170403.
40 任雨,张勃,陈曦东.科尔沁沙地土地荒漠化敏感性评估[J].中国沙漠,2023,43(2):159-169.
Outlines

/