水土资源

干旱区自然资源地表基质细化分类体系构建与调查深度

  • 李双媛 ,
  • 徐柱 ,
  • 王玉刚 ,
  • 孙金金
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  • 1.自然资源要素耦合过程与效应重点实验室,北京 100055
    2.中国科学院新疆生态与地理研究所,干旱区生态安全与可持续发展重点实验室,新疆 乌鲁木齐 830011
    3.中国科学院大学,北京 100049
    4.中国科学院阜康荒漠生态系统国家站,新疆 阜康 831505
    5.新疆天池管理委员会博格达生态环境监测站,新疆 阜康 831500
    6.自然资源部塔里木河流域下游水资源与生态效应野外科学观测研究站,新疆 乌鲁木齐 830057
李双媛(2000-),女,硕士研究生,研究方向为景观尺度土地资源. E-mail: lsy000615@126.com
王玉刚. E-mail: wangyg@ms.xjb.ac.cn

收稿日期: 2024-08-09

  修回日期: 2024-11-09

  网络出版日期: 2025-01-17

基金资助

自然资源要素耦合过程与效应重点实验室开放课题(2022KFKTC016);“天山英才”培养计划(2023TSYCLJ0048)

Construction of a refined classification system and survey depth of underground for natural resource ground substrates in arid zones

  • LI Shuangyuan ,
  • XU Zhu ,
  • WANG Yugang ,
  • SUN Jinjin
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  • 1. Key Laboratory of Coupling Process and Effect of Natural Resources Elements, Beijing 100055, China
    2. Key Laboratory of Ecological Safety and Sustainable Development in Arid Land; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
    4. Fukang Station of Desert Ecology, Chinese Academy of Sciences, Fukang 831505, Xinjiang, China
    5. Bogda Eco-environmental Station in Tianchi Management Committee, Fukang 831500, Xinjiang, China
    6. Field Observation and Research Station of Water Resources and Ecological Effect in Lower Reaches of Tarim River Basin, Urumqi 830057, Xinjiang, China

Received date: 2024-08-09

  Revised date: 2024-11-09

  Online published: 2025-01-17

摘要

地表基质分类是开展地表基质调查监测的基础,同时也是揭示地表基质与地表覆盖层的协同耦合关系的关键,有助于从地表覆被和地下空间要素两个层次认识地表基质与生态环境的作用机制。本研究以干旱区典型的内陆河流域——新疆三工河流域为靶区,依据干旱区山地-绿洲-荒漠景观异质性分布特征,在地表基质的分布区域、海拔范围及主要地表覆被的基础上,构建了一套地表基质三级分类分区体系。整体划分为4个地表基质一级类、17个二级类及28个三级类。根据土壤理化性质及植被根系分布特征,地表基质调查深度在南部山区以50 cm;中部平原区以3 m;北部沙漠区小于10 m为宜。此外,基于垂直带生态系统NPP的分异性特征,验证了分类体系的合理性,体现了地表基质层孕育支撑土地覆被的作用关系。研究成果为未来干旱区自然资源调查监测和科学管理决策提供理论与技术支撑。

本文引用格式

李双媛 , 徐柱 , 王玉刚 , 孙金金 . 干旱区自然资源地表基质细化分类体系构建与调查深度[J]. 干旱区研究, 2025 , 42(1) : 84 -96 . DOI: 10.13866/j.azr.2025.01.08

Abstract

The classification of the ground substrate is a fundamental basis for conducting ground substrate surveys and monitoring. It reveals the synergistic coupling relationship between the ground substrate and the surface cover layer, which aids in understanding the mechanisms of interaction between the ground substrate and the ecological environment from both the surface cover and subsurface spatial elements. This study targeted the Sangong River Basin in Xinjiang, a typical inland river basin in an arid region. Based on the heterogenous distribution of the mountain-oasis-desert landscape in arid regions, a three-tier classification and zoning system for ground substrates was developed, considering the distribution area, elevation range, and main surface cover of the surface substrates. The overall classification was divided into four primary categories, 17 secondary categories, and 28 tertiary categories. Considering the physical and chemical properties of the soil and the distribution characteristics of vegetation root systems, the suitable survey depth for ground substrates in the southern mountainous area was 50 cm; in the central plain area, it was 3 m; and in the northern desert area, it was less than 10 m. Additionally, based on the differentiation characteristics of Net Primary Productivity in vertical zonal ecosystems, the rationality of the classification system was validated, reflecting the role of ground substrate layers in nurturing and supporting land cover. These results provide theoretical and technical support for future natural resource surveys, monitoring, and scientific management decisions in arid regions.

参考文献

[1] 自然资源部. 自然资源部办公厅关于印发《地表基质分类方案(试行)》的通知[EB/OL]. 2020, http://gi.mnr.gov.cn/202012/t20201222_2596025.html.
  [ Ministry of Natural Resources. Notice of the General Office of the Ministry of Natural Resources Printing and Distributing the Ground Cover Layer Classification Scheme (Trial)[EB/OL]. 2020, http://gi.mnr.gov.cn/202012/t20201222_2596025.html. ]
[2] 侯红星, 张蜀冀, 鲁敏, 等. 自然资源地表基质层调查技术方法新经验——以保定地区地表基质层调查为例[J]. 西北地质, 2021, 54(3): 277-288.
  [Hou Hongxing, Zhang Shuji, Lu Min, et al. New experience of the natural resources ground substrate layer survey technology method: Taking Baoding area ground substrate layer survey as an example[J]. Northwestern Geology, 2021, 54(3): 277-288. ]
[3] 殷志强, 陈自然, 李霞, 等. 地表基质综合调查:内涵、分层、填图与支撑目标[J]. 水文地质工程地质, 2023, 50(1): 144-151.
  [Yin Zhiqiang, Chen Ziran, Li Xia, et al. Connotation, layering, mapping and supporting objectives of the integrated survey of ground substrates[J]. Hydrogeology & Engineering Geology, 2023, 50(1): 144-151. ]
[4] 孙禧勇, 许玮, 王明建. 地表基质层分层分类调查研究[J]. 中国土地, 2022(7): 34-36.
  [Sun Xiyong, Xu Wei, Wang Mingjian. Investigative study on stratification and classification of surface substrates layers[J]. China Land, 2022(7): 34-36. ]
[5] 朱永官, 李刚, 张甘霖, 等. 土壤安全: 从地球关键带到生态系统服务[J]. 地理学报, 2015, 70(12): 1859-1869.
  [Zhu Yongguan, Li Gang, Zhang Ganlin, et al. Soil security: From Earth’s critical zone to ecosystem services[J]. Acta Geographica Sinca, 2015, 70(12): 1859-1869. ]
[6] 殷志强, 秦小光, 张蜀冀, 等. 地表基质分类及调查初步研究[J]. 水文地质工程地质, 2020, 47(6): 8-14.
  [Yin Zhiqiang, Qin Xiaoguang, Zhang Shuji, et al. Preliminary study on classification and investigation of surface substrate[J]. Hydrogeology and Engineering Geology, 2020, 47(6): 8-14. ]
[7] 葛良胜, 侯红星, 夏锐. 自然资源地表基质调查技术体系构建[J]. 地理信息世界, 2022, 29(5): 20-27.
  [Ge Liangsheng, Hou Hongxing, Xia Rui. Construction of technical system for ground substrate survey of natural resources[J]. Geomatics World, 2022, 29(5): 20-27. ]
[8] 艾晓军, 陈占生, 耿国帅, 等. 辽阳—丹东地区黑土地地表基质有效土层分布规律及影响因素——以凤城市为例[J]. 河北农业科学, 2023, 27(3): 54-59, 65.
  [Ai Xiaojun, Chen Zhansheng, Geng Guoshuai, et al. Distribution patterns and influencing factors of effective soil layers in the surface matrix of black soil in Liaoyang-dandong area—Taking Fengcheng city as an example[J]. Journal of Hebei Agricultural Sciences, 2023, 27(3): 54-59, 65. ]
[9] 霍东, 陈占生, 艾晓军, 等. 遥感解译在辽阳-丹东地区黑土地地表基质调查中的应用——以宽甸满族自治县为例[J]. 农业与技术, 2023, 43(15): 115-119.
  [Huo Dong, Chen Zhansheng, Ai Xiaojun, et al. Application of remote sensing interpretation in surface substrate investigation of black soil in Liaoyang-dandong region: Taking Kuandian Manchu Autonomous County as an example[J]. Agriculture and Technology, 2023, 43(15): 115-119. ]
[10] 刘洪博, 孔繁鹏, 赵建, 等. 地表基质调查技术方法探索与实验——以黑龙江省宝清县黑土地调查为例[J]. 地理信息世界, 2022, 29(6): 1-5.
  [Liu Hongbo, Kong Fanpeng, Zhao Jian, et al. Exploration and experiment of surface substrate investigation technique: A case study of black soil investigation in Baoqing County, Heilongjiang Province[J]. Geomatics World, 2022, 29(6): 1-5. ]
[11] 孙勇刚, 张闯, 尚晓雨, 等. 不同地表基质类型理化性质探索与研究——以河北塞罕坝示范区为例[J]. 资源信息与工程, 2023, 38(2): 13-16.
  [Sun Yonggang, Zhang Chuang, Shang Xiaoyu, et al. Exploration and study on physiochemical properties of different ground substrate types: Taking the Saihanba demonstration area in Hebei Province as an example[J]. Resource Information and Engineering, 2023, 38(2): 13-16. ]
[12] 王根绪, 程国栋. 干旱荒漠绿洲景观空间格局及其受水资源条件的影响分析[J]. 生态学报, 2000, 20(3): 363-368.
  [Wang Genxu, Cheng Guodong. The spatial pattern and influence caused by water resources in arid desert oases[J]. Acta Ecologica Sinica, 2000, 20(3): 363-368. ]
[13] 鲁如坤. 土壤农业化学分析方法[M]. 北京: 中国农业科技出版社, 2000.
  [Lu Rukun. The Analysis Method of Soil Agricultural Chemistry[M]. Beijing: China Agricultural Science and Technology Press, 2000. ]
[14] 和清华, 谢云. 我国太阳总辐射气候学计算方法研究[J]. 自然资源学报, 2010, 25(2): 308-319.
  [He Qinghua, Xie Yun. Research on the climatological calculation method of solar radiation[J]. Journal of Natural Resources, 2010, 25(2): 308-319. ]
[15] 栾海军, 邢宸硕, 张荣凯, 等. 基于Chen NDVI模型的NDVI尺度转换分形特性分析[J]. 遥感信息, 2022, 37(3): 12-20.
  [Luan Haijun, Xing Chenshuo, Zhang Rongkai, et al. Analysis of fractal characteristics of NDVI scale conversion based on Chen NDVI model[J]. Remote Sensing Information, 2022, 37(3): 12-20. ]
[16] 朱文泉, 陈云浩, 徐丹, 等. 陆地植被净初级生产力计算模型研究进展[J]. 生态学杂志, 2005, 24(3): 296-300.
  [Zhu Wenquan, Chen Yunhao, Xu Dan, et al. Advances in terrestrial net primary productivity (NPP) estimation models[J]. Chinese Journal of Ecology, 2005, 24(3): 296-300. ]
[17] 朱文泉, 潘耀忠, 龙中华, 等. 基于GIS和RS的区域陆地植被NPP估算——以中国内蒙古为例[J]. 遥感学报, 2005, 9(3): 300-307.
  [Zhu Wenquan, Pan Yaozhong, Long Zhonghua, et al. Estimating net primary productivity of terrestrial vegetation based on GIS and RS: A case study in Inner Mongolia, China[J]. Journal of Remote Sensing, 2005, 9(3): 300-307. ]
[18] Yang H, Zhong X, Deng S, et al. Assessment of the impact of LUCC on NPP and its influencing factors in the Yangtze River basin, China[J]. Catena, 2021, 206: 105542.
[19] Hu C, Zhang L, Wu Q, et al. Response of LUCC on runoff generation process in Middle Yellow River Basin: The Gushanchuan Basin[J]. Water, 2020, 12(5): 1237.
[20] 尹小君, 祝宏辉, Gao Gerry, 等. 气候变化和人类活动对天山北坡净初级生产力变化的影响[J]. 农业工程学报, 2020, 36(20): 195-202.
  [Yin Xiaojun, Zhu Honghui, Gao Jerry, et al. Effects of climate change and human activities on net primary productivity in the Northern Slope of Tianshan, Xinjiang, China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2020, 36(20): 195-202. ]
[21] 陈炳铭, 赵善超, 孙丰华, 等. 气候变化和人类活动对干旱区垂直自然带NPP的影响[J]. 生态学杂志, 2023, 42(6): 1474-1483.
  [Chen Bingming, Zhao Shanchao, Sun Fenghua, et al. Impacts of climate change and human activities on the NPP of vertical natural belts in arid zones[J]. Chinese Journal of Ecology, 2023, 42(6): 1474-1483. ]
[22] 郝鑫怡, 张喆, 郑浩, 等. 天山北坡经济带植被覆盖度动态变化研究[J]. 中国环境科学, 2024, 44(2): 1020-1031.
  [Hao Xinyi, Zhang Zhe, Zheng Hao, et al. Dynamic change of vegetation cover in the economic zone of the northern slopes of Tianshan Mountains[J]. China Environmental Science, 2024, 44(2): 1020-1031. ]
[23] 李艳忠, 罗格平, 许文强, 等. 天山北坡三工河流域中山带森林发育与气候土壤的关系[J]. 山地学报, 2011, 29(1): 33-42.
  [Li Yanzhong, Luo Geping, Xu Wenqiang, et al. Forest development and their relationships with climatic and soil in the mid-mountain area of Sangong River watershed, northern slope of Tianshan Mountains[J]. Journal of Mountain Science, 2011, 29(1): 33-42. ]
[24] 田胜川, 赵善超, 郑新军, 等. 天山不同海拔雪岭云杉生长季水分来源[J]. 干旱区研究, 2023, 40(3): 436-444.
  [Tian Shengchuan, Zhao Shanchao, Zheng Xinjun, et al. Water source of spruce (Picea schrenkiana) at different altitudes in the Tianshan Mountains during the growing season[J]. Arid Zone Research, 2023, 40(3): 436-444. ]
[25] 宋昕妮, 李路, 常亚鹏, 等. 天山北坡雪岭云杉林叶片-土壤氮磷化学计量特征[J]. 西北农林科技大学学报(自然科学版), 2020, 48(9): 97-104.
  [Song Xinni, Li Lu, Chang Yapeng, et al. Stoichiometric characteristics of nitrogen and phosphorus in leaves and soils of Picea schrenk’s spruce forest on the northern slope of the Tianshan Mountains[J]. Journal of Northwest A & F University (Natural Science Edition), 2020, 48(9): 97-104. ]
[26] 龙威夷, 施建飞, 李双媛, 等. 流域绿洲土壤盐分多模型反演效果评估[J]. 干旱区研究, 2024, 41(7): 1120-1130.
  [Long Weiyi, Shi Jianfei, Li Shuangyuan, et al. Evaluation of multimodel inversion effects on soil salinity in oasis basin[J]. Arid Zone Research, 2024, 41(7): 1120-1130. ]
[27] 孙芳强, 尹立河, 马洪云, 等. 准噶尔盆地南缘土壤水运移特征及其补给来源识别[J]. 干旱区研究, 2017, 34(6): 1271-1277.
  [Sun Fangqiang, Yin Lihe, Ma Hongyun, et al. Identification of soil water migration and recharge sources in the southern marginal zone of the Junggar Basin China[J]. Arid Zone Research, 2017, 34(6): 1271-1277. ]
[28] 董雪, 李永华, 辛智鸣, 等. 唐古特白刺叶性状及叶片δ13C、δ15N沿降水梯度的变化特征[J]. 生态学报, 2019, 39(10): 3700-3709.
  [Dong Xue, Li Yonghua, Xin Zhiming, et al. Variation in leaf traits and leaf δ13C and δ15N content in Nitraria tangutorum along precipitation gradient[J]. Acta Ecologica Sinica, 2019, 39(10): 3700-3709. ]
[29] 孙芳强, 尹立河, 王晓勇, 等. 新疆三工河流域厚层包气带区地下水垂向补给量的厘定[J]. 中国地质, 2017, 44(5): 913-923.
  [Sun Fangqiang, Yin Lihe, Wang Xiaoyong, et al. Determination of vertical infiltration recharge of groundwater in the thick unsaturated zone of Sangong River Basin, Xinjiang[J]. Geology in China, 2017, 44(5): 913-923. ]
[30] 戴岳, 郑新军, 唐立松, 等. 古尔班通古特沙漠南缘梭梭水分利用动态[J]. 植物生态学报, 2014, 38(11): 1214-1225.
  [Dai Yue, Zheng Xinjun, Tang Lisong, et al. Dynamics of water usage in Haloxylon ammodendron in the southern edge of the Gurbantünggüt Desert[J]. Chinese Journal of Plant Ecology, 2014, 38(11): 1214-1225. ]
[31] 徐贵青, 李彦. 共生条件下三种荒漠灌木的根系分布特征及其对降水的响应[J]. 生态学报, 2009, 29(1): 130-137.
  [Xu Guiqing, Li Yan. Roots distribution of three desert shrubs and their response to precipitation under co-occurring conditions[J]. Acta Ecologica Sinica, 2009, 29(1): 130-137. ]
[32] Zeng J, Li Z, Chen Q, et al. Evaluation of remotely sensed and reanalysis soil moisture products over the Tibetan Plateau using in-situ observations[J]. Remote Sensing of Environment, 2015, 163: 91-110.
[33] Luo M, Meng F, Sa C, et al. Response of vegetation phenology to soil moisture dynamics in the Mongolian Plateau[J]. Catena, 2021, 206: 105505.
[34] 赵文智, 刘鹄. 荒漠区植被对地下水埋深响应研究进展[J]. 生态学报, 2006, 26(8): 2702-2708.
  [Zhao Wenzhi, Liu Hu. Recent advances in desert vegetation response to groundwater table changes[J]. Acta Ecologica Sinica, 2006, 26(8): 2702-2708. ]
[35] 徐海量, 宋郁东, 王强, 等. 塔里木河中下游地区不同地下水位对植被的影响[J]. 植物生态学报, 2004, 28(3): 400-405.
  [Xu Hailiang, Song Yudong, Wang Qiang, et al. The effect of groundwater level on vegetation in the middle and lower reaches of the Tarim River, Xinjiang, China[J]. Chinese Journal of Plant Ecology, 2004, 28(3): 400-405. ]
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