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现代地质 ›› 2025, Vol. 39 ›› Issue (02): 384-395.DOI: 10.19657/j.geoscience.1000-8527.2024.145

• 表生资源观测模拟与综合评价 • 上一篇    下一篇

关于构建自然资源要素综合观测网络的思考:以长江中下游流域为例

任继军1,2,3(), 肖粤新1,2,3,4(), 孙泽龙1,2,3, 赵元1,2,3, 成明1,3, 陈盼盼1,2,3, 兰建梅2   

  1. 1.黄山水土资源野外科学观测研究站,安徽 黄山 245000
    2.自然资源部洞庭湖流域生态保护修复工程技术创新中心,湖南 长沙 410007
    3.中国地质调查局长沙自然资源综合调查中心,湖南 长沙 410600
    4.自然资源部自然资源要素耦合过程与效应重点实验室,北京 100055
  • 出版日期:2025-04-10 发布日期:2025-05-08
  • 通信作者: 肖粤新,男,工程师,1994年出生,主要从事地表基质调查监测、自然资源综合观测研究工作。Email: 1154694361@qq.com
  • 作者简介:任继军,男,技术员,1990年出生,主要从事地表基质调查监测、自然资源综合观测研究工作。Email: 475578934@qq.com
  • 基金资助:
    中国地质调查局项目“江南丘陵区自然资源与地表基质观测监测评价”(DD20230515);自然资源部洞庭湖流域生态保护修复工程技术创新中心开放课题基金项目(2023016)

Reflections on Building a Comprehensive Observation Network for Natural Resource Components: A Case Study of the Middle and Lower Yangtze River Basin

REN Jijun1,2,3(), XIAO Yuexin1,2,3,4(), SUN Zelong1,2,3, ZHAO Yuan1,2,3, CHENG Ming1,3, CHEN Panpan1,2,3, LAN Jianmei2   

  1. 1. Huangshan Observation and Research Station for Land-water Resources, Huangshan, Anhui 245000, China
    2. Technology Innovation Center for Ecological Conservation and Restoration in Dongting Lake Basin Ministry of Natural Resources, Changsha, Hunan 410007, China
    3. Changsha General Survey of Natural Resources Center, China Geological Survey, Changsha, Hunan 410600, China
    4. Key Laboratory of Natural Resource Coupling Process and Effects, Ministry of Natural Resources, Beijing 100055, China
  • Published:2025-04-10 Online:2025-05-08

摘要:

基于《自然资源科技创新发展规划纲要》的战略指引,本研究针对长江中下游流域这一国家资源核心区与生态屏障,创新构建多技术融合的自然资源要素综合观测体系进行探讨。通过总结梳理制约区域观测网络效能的三大关键瓶颈:单要素监测导致的系统耦合缺失、数据异构性阻碍跨域整合分析、智能技术应用滞后制约动态评估能力。研究突破传统监测范式,首创“三级梯度观测体系”,构建“1+12+52”的立体站网架构(综合中心站-区域站-专业站),有效填补流域尺度自然资源系统耦合研究的空白。以黄山水土资源观测站为例,多要素协同监测使数据采集效率大大提升,实现水文、土壤、植被等要素的同步动态感知。技术体系创新形成“要素耦合-过程模拟-效应评估”三位一体的观测范式,显著提升生态过程解析与系统响应预测能力。实践应用表明,长江中下游流域自然资源要素综合观测网络建设可以效破解了传统监测的碎片化问题,为长江经济带自然资源动态监管提供了全要素、多尺度的数据支撑。其创新性架构设计为构建“山、水、林、田、湖、草、沙”生命共同体监测网络提供了可推广的范式参考。研究成果对提升区域生态安全预警能力和科学决策水平具有重要实践价值,为我国自然资源治理现代化提供了技术支撑。

关键词: 自然资源综合观测, 系统耦合分析, 梯度观测网络, 多源数据融合

Abstract:

Building on the strategic guidance provided by the “Development of Scientific and Technological Innovation in Natural Resources”, this study explores the innovative development of a multi-technology integrated observation system for natural resource elements, focusing on the core area and ecological barrier of the middle and lower Yangtze River Basin.The research systematically addresses three critical constraints affecting regional observation network effectiveness: Ⅰ) Lack of systemic coupling due to single-element monitoring; Ⅱ) Data heterogeneity hindering cross-domain integrated analysis; Ⅲ) Lagging intelligent technology application limiting dynamic assessment capabilities.Breaking through traditional monitoring paradigms byintroducing the innovative “three-level gradient observation system”, the study pioneers a dimensional station network framework of “1+12+52”(comprehensive central station-regional stations-specialized stations), effectively bridging the research gap in basin-scale natural resource system coupling.Taking Huangshan Observation and Research Station for Land-water Resources as an example, multi-element collaborative monitoring has significantly enhanced data collection efficiency, enabling synchronous dynamic monitoring of hydrological, soil, and vegetation parameters.The innovation in the technical system leads to the development of a “coupling of elements-process simulation-effect assessment” observation paradigm, which markedly improves the analysis of ecological processes and the prediction of system responses.Practical applications demonstrate that the comprehensive observation network effectively resolves fragmentation issues in traditional monitoring, providing full-element, multi-scale data support for dynamic resource management in the Yangtze Economic Belt.The innovative design offers a scalable reference for building a “mountain-water-forest-farmland-lake-grassland-desert” life communities.The research outcomes substantially enhance regional ecological security early-warning capabilities and scientific decision-making levels, providing crucial technical support for modernizing China’s natural resource governance system.Implementation results show significant improvements in cross-departmental data interoperability and ecological risk prediction accuracy compared to conventional methods.

Key words: integrated natural resource monitoring, system coupling analysis, gradient observation networ, multi-source data fusion

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