地表过程研究

近20 a黄河源园区土地退化时空演化分析

  • 秦彤 ,
  • 李功权 ,
  • 范佳晨
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  • 1.长江大学地球科学学院,湖北 武汉 430000
    2.西北师范大学地理与环境科学学院,甘肃 兰州 730070
秦彤(1995-),女,硕士研究生,主要从事GIS应用与土地生态研究. E-mail: 1344023414@qq.com

收稿日期: 2022-01-24

  修回日期: 2022-04-22

  网络出版日期: 2022-10-20

基金资助

国家自然科学基金项目(42004007)

Spatial-temporal evolution of land degradation in the Yellow River Source Park in recent 20 years

  • Tong QIN ,
  • Gongquan LI ,
  • Jiachen FAN
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  • 1. School of Geosciences, Yangtze University, Wuhan 430000, Hubei, China
    2. School of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, Gansu, China

Received date: 2022-01-24

  Revised date: 2022-04-22

  Online published: 2022-10-20

摘要

三江源黄河源园区作为黄河的发源地,它的生态系统对整个黄河流域至关重要。针对研究区2000—2020年存在的土地退化问题,选取土壤侵蚀模数、沙化特征指数与土壤湿度指数,采用空间托普利茨逆协方差聚类法开展了3个参数的聚类分析,从而进行黄河源园区土地退化时空演化分析,并采用极致梯度提升法进行时空演化影响因素分析。结果表明:(1) 土地退化现象最严重的地区是中部偏南地区与东北地区,其次为偏北地区。(2) 东北地区存在水土流失与土地沙化2种问题,中部偏南地区以严重的水土流失为主,偏北地区主要表现为土地沙化问题。(3) 近20 a来,土地退化指数呈现波动性下降,土地退化整体趋于好转,在偏南地区表现得更明显。(4) 水土流失问题整体好转,偏北地区有土地沙化的风险。该研究对掌握黄河源园区土地退化的时空分布及发展趋势、推进黄河源园区生态保护具有重要意义。

本文引用格式

秦彤 , 李功权 , 范佳晨 . 近20 a黄河源园区土地退化时空演化分析[J]. 干旱区地理, 2022 , 45(5) : 1490 -1499 . DOI: 10.12118/j.issn.1000-6060.2022.041

Abstract

Because Sanjiangyuan’s Yellow River Source Park flows into the Yellow River, its ecosystem is crucial to the entire Yellow River Basin of China. Of the land degradation problems observed in the study area from 2000 to 2020, this study focuses on the soil erosion modulus, sanding characteristic index and soil moisture index. To achieve a more in-depth analysis of spatial and temporal evolution of land degradation in the area, machine learning algorithms were used. The spatial Toeplitz inverse covariance-based clustering method was used to carry out the cluster analysis of three parameters as part of the spatio-temporal evolution analysis of land degradation in the Yellow River Source Park. The extreme gradient boosting method was used to analyze the factors influencing the spatio-temporal evolution. The results of the study showed that: (1) The most significant land degradation was observed in the central-southern and northeastern regions, followed by the northern region. (2) In the northeast, there are two categories of problems: soil erosion and land desertification. In the central-southern region, severe soil erosion is the main problem. In the northern region, land desertification is the main problem. (3) In the past two decades, the land degradation index has shown a fluctuating decline that land degradation overall tends to improve, and that the effects are more obvious in the remote southern region. (4) The problem of soil erosion is improving overall, and there is a risk of land sanding in the remote northern areas. This study is a critical tool for understanding the spatial and temporal trends in the distribution and development of land degradation in the Yellow River Source Park and, by extension, for the promotion of increased ecological protection in Yellow River Source Park.

参考文献

[1] Stocking M A. Land Degradation[DB/OL]. Science Direct. [2002-11-02]. https://www.sciencedirect.com/science/article/pii/B008043076704184X.html.
[2] 黄炎和. 土地生态学[M]. 北京: 中国农业出版社, 2013: 131-134.
[2] [Huang Yanhe. Land ecology[M]. Beijing: China Agricultural Press, 2013: 131-134. ]
[3] Yue Y J, Li M, Zhu A X, et al. Land degradation monitoring in the Ordos Plateau of China using an expert knowledge and BP-ANN-based approach[J]. Sustainability, 2016, 8(11): 1174, doi: 10.3390/su8111174.
[4] Han W Y, Liu G H, Su X K, et al. Assessment of potential land degradation and recommendations for management in the south subtropical region, southwest China[J]. Land Degradation & Development, 2019, 30(8): 979-990.
[5] Yang C, Li Q Q, Chen J Y, et al. Spatiotemporal characteristics of land degradation in the Fuxian Lake Basin, China: Past and future[J]. Land Degradation & Development, 2020, 32(16): 2446-2460.
[6] 杜子涛, 杨小明, 颜树强, 等. 奈曼旗土地退化遥感监测研究[J]. 农业工程学报, 2012, 28(3): 154-161.
[6] [Du Zitao, Yang Xiaoming, Yan Shuqiang, et al. Study on land degradation monitoring in Naiman County using remote sensing[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(3): 154-161. ]
[7] Ye W, Wang Q B, Guo B, et al. A novel large-scale land degradation remote sensing index and its application in Three River Source Region[J/OL]. Earth Science Informatics. [2022-01-27]. http://link.springer.com/article/10.1007/s12145-021-00724-0.html.
[8] 许明杰, 牛瑞卿, 杨柯, 等. 一种土地生态敏感性评估的加权聚类方法[J]. 测绘科学, 2021, 46(10): 118-129, 144.
[8] [Xu Mingjie, Niu Ruiqing, Yang Ke, et al. A weighted clustering model for land eco-environmental sensitivity evaluation[J]. Science of Surveying and Mapping, 2021, 46(10): 118-129, 144. ]
[9] Grinand C, Vieilledent G, Razafimbelo T. Landscape-scale spatial modelling of deforestation, land degradation, and regeneration using machine learning tools[J]. Land Degradation & Development, 2020, 31(13): 1699-1712.
[10] 赵新全, 周华坤. 三江源区生态环境退化、恢复治理及其可持续发展[J]. 中国科学院院刊, 2005, 20(6): 37-42.
[10] [Zhao Xinquan, Zhou Huakun. Eco-environmental degradation, vegetation regeneration and sustainable development in the headwaters of Three Rivers on Tibetan Plateau[J]. Bulletin of Chinese Academy of Sciences, 2005, 20(6): 37-42. ]
[11] 董锁成, 周长进, 王海英. “三江源”地区主要生态环境问题与对策[J]. 自然资源学报, 2002, 17(6): 713-720.
[11] [Dong Suocheng, Zhou Changjin, Wang Haiying. Ecological crisis and countermeasures of the Three Rivers’ headstream regions[J]. Journal of Natural Resources, 2002, 17(6): 713-720. ]
[12] Kang Y H, Wu K, Gao S, et al. STICC: A multivariate spatial clustering method for repeated geographic pattern discovery with consideration of spatial contiguity[J/OL]. International Journal of Geographical Information Science.[2002-03-30]. https://doi.org/10.1080/13658816.2022.2053980.html.
[13] Chen T Q, Guestrin C. XGBoost: A scalable tree boosting system[DB/OL]. ACM Digital Library. [2016-08-13]. https://dl.acm.org/doi/10.1145/2939672.2939785.html.
[14] 王旭峰. 三江源国家公园界线矢量数据集[DB/OL]. 国家青藏高原科学数据中心. [2021-04-22]. http://data.tpdc.ac.cn/zh-hans/data/a2cc2fb2-ba29-4059-af5f-6d58acf654c8.html.
[14] [Wang Xufeng. Boundary vector data set of Sanjiangyuan National Park[DB/OL]. National Tibetan Plateau Data Center. [2021-04-22]. http://data.tpdc.ac.cn/zh-hans/data/a2cc2fb2-ba29-4059-af5f-6d58acf654c8.html. ]
[15] 刘婷婷, 朱秀芳, 郭锐, 等. ERA5再分析降水数据在中国的适用性分析[J]. 干旱区地理, 2022, 45(1): 66-79.
[15] [Liu Tingting, Zhu Xiufang, Guo Rui, et al. Applicability of ERA5 reanalysis of precipitation data in China[J]. Arid Land Geography, 2022, 45(1): 66-79. ]
[16] 戴永久, 上官微. 中国土壤有机质数据集[DB/OL]. 国家青藏高原科学数据中心. [2021-04-19]. http://data.tpdc.ac.cn/zh-hans/data/8ba0a731-5b0b-4e2f-8b95-8b29cc3c0f3a.html.
[16] [Dai Yongjiu, Shangguan Wei. Dataset of soil properties for land surface modeling over China[DB/OL]. National Tibetan Plateau Data Center. [2021-04-19]. http://data.tpdc.ac.cn/zh-hans/data/8ba0a731-5b0b-4e2f-8b95-8b29cc3c0f3a.html. ]
[17] 郑子豪, 吴志峰, 陈颖彪, 等. 基于Google Earth Engine的长三角城市群生态环境变化与城市化特征分析[J]. 生态学报, 2021, 41(2): 717-729.
[17] [Zheng Zihao, Wu Zhifeng, Chen Yingbiao, et al. Analyzing the ecological environment and urbanization characteristics of the Yangtze River Delta urban agglomeration based on Google Earth Engine[J]. Acta Ecologica Sinica, 2021, 41(2): 717-729. ]
[18] Panagosa P, Borrellia P, Poesen J, et al. The new assessment of soil loss by water erosion in Europe[J]. Environmental Science & Policy, 2015, 54: 438-447.
[19] 周来, 李艳洁, 孙玉军. 修正的通用土壤流失方程中各因子单位的确定[J]. 水土保持通报, 2018, 38(1): 169-174.
[19] [Zhou Lai, Li Yanjie, Sun Yujun. Determination of each factor unit in the modified general soil loss equation[J]. Bulletin of Soil and Water Conservation, 2018, 38(1): 169-174. ]
[20] 章文波, 谢云, 刘宝元. 中国降雨侵蚀力空间变化特征[J]. 山地学报, 2003, 2003(1): 33-40.
[20] [Zhang Wenbo, Xie Yun, Liu Baoyuan. Spatial variation characteristics of rainfall erosivity in China[J]. Mountain Research, 2003, 2003(1): 33-40. ]
[21] 张科利, 彭文英, 杨红丽. 中国土壤可蚀性值及其估算[J]. 土壤学报, 2007, 44(1): 7-13.
[21] [Zhang Keli, Peng Wenying, Yang Hongli. Soil erodibility and its estimation for agricultural soil in China[J]. Acta Pedologica Sinica, 2007, 44(1): 7-13. ]
[22] Liu B Y, Nearing M A, Risse L M. Slope gradient effects on soil loss for steep slopes[J]. Transaction of the ASAE, 1994, 37(6): 1835-1840.
[23] Foster G R, Wischmeier W H. Evaluating irregular slopes for soil loss prediction[J]. Environment Earth Sciences, 2014, 73(1): 2141-2151.
[24] Wischmier W H, Smith D D. Predicting grainfall erosion losses: A guide to conservation planning[M]. Washington: United States Department of Agriculture, 1978: 537.
[25] 蔡崇法, 丁树文, 史志华, 等. 应用USLE模型与地理信息系统IDRISI预测小流域土壤侵蚀量的研究[J]. 水土保持学报, 2000, 14(2): 19-24.
[25] [Cai Chongfa, Ding Shuwen, Shi Zhihua, et al. Study of applying USLE and geographical information system IDRISI to predict soil erosion in small watershed[J]. Journal of Soil and Water Conservation, 2000, 14(2): 19-24. ]
[26] 章影, 廖畅, 姜庆虎, 等. 丹江口库区土壤侵蚀对土地利用变化的响应[J]. 水土保持通报, 2017, 37(1): 104-111, 2.
[26] [Zhang Ying, Liao Chang, Jiang Qinghu, et al. Response of soil erosion to land use change in Danjiangkou Reservoir area[J]. Bulletin of Soil and Water Conservation, 2017, 37(1): 104-111, 2. ]
[27] 赖晗, 芮小平, 梁汉东, 等. 基于均值变点分析的三峡库区河网提取研究[J]. 测绘科学, 2012, 37(5): 173-175.
[27] [Lai Han, Rui Xiaoping, Liang Handong, et al. Extraction of drainage network in Three Gorge Reservoir area based on mean change point method[J]. Science of Surveying and Mapping, 2012, 37(5): 173-175. ]
[28] 山成菊, 董增川, 樊孔明, 等. 组合赋权法在河流健康评价权重计算中的应用[J]. 河海大学学报(自然科学版), 2012, 40(6): 622-628.
[28] [Shan Chengju, Dong Zengchuan, Fan Kongming, et al. Application of combination weighting method to weight calculation in river health evaluation[J]. Journal of Hehai University (Natural Science Edition), 2012, 40(6): 622-628. ]
[29] 谷昊鑫, 秦伟山, 赵明明, 等. 黄河流域旅游经济与生态环境协调发展时空演变及影响因素探究[J]. 干旱区地理, 2022, 45(2): 628-638.
[29] [Gu Haoxin, Qin Weishan, Zhao Mingming, et al. Spatial and temporal evolution and influencing factors of coordinated development of tourism economy and ecological environment in the Yellow River Basin[J]. Arid Land Geography, 2022, 45(2): 628-638. ]
[30] 胡光印, 董治宝, 逯军峰, 等. 黄河流域沙漠化空间格局与成因[J]. 中国沙漠, 2021, 41(4): 213-224.
[30] [Hu Guangyin, Dong Zhibao, Lu Junfeng, et al. Spatial pattern of aeolian desertification and its causes in the Yellow River catchment[J]. Journal of Desert Research, 2021, 41(4): 213-224. ]
[31] 姚旭阳, 张明军, 张宇, 等. 中国西北地区气候转型的新认识[J]. 干旱区地理, 2022, 45(3): 671-683.
[31] [Yao Xuyang, Zhang Mingjun, Zhang Yu, et al. New insights into climate transition in northwest China[J]. Arid Land Geography, 2022, 45(3): 671-683. ]
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