长江大保护战略下水文-水质-水生态协同监测研究进展与展望OA
Research Progress and Prospects for Synergistic Monitoring of Hydrology-Water Quality-Aquatic Ecology Under the Yangtze River Protection Strategy
阐述水文-水质-水生态协同监测在长江大保护中的支撑作用与应用创新,为长江流域生态保护与修复提供理论和技术支撑.在技术体系构建方面,整合卫星遥感、无人机航测、物联网及原位观测等多元技术,搭建覆盖全流域、区域、河段多梯度的"天空地水"立体观测网络;垂直维度形成天基遥感宏观监测、空基无人机精细感知、地基物联网实时采集、水中移动单元动态巡查的多维架构,水平维度构建固定监测站、移动监测单元、应急监测设备的网格化布局,有效提升不同尺度下水文动态变化、水质核心参数、水生态系统特征的协同刻画能力.在技术体系应用方面,重点推进多源数据融合与模型耦合机制创新:提出针对性的数据融合路径,整合水文、水质、生物、气象等多维度信息,形成数据-模型-应用一体化数据处理平台;通过耦合物理模型与数据驱动模型,强化对复杂流域过程的模拟能力,显著增强生态系统健康诊断与突发风险预警的科学支撑效能,为长江流域生态保护实践提供精准技术支持.同时,梳理当前协同监测面临的核心挑战:数据异构性导致多源数据协同效率不高,跨尺度模拟精度不足制约流域关键生态过程解析,协同管理机制缺位影响技术成果落地转化等,因此未来需突破智能感知技术瓶颈,建立数据采集处理共享标准化体系、优化跨尺度动态耦合模型、解析全球变化下流域生态韧性响应机制,推动协同监测从技术集成向智慧决策进阶.
In this study,we systematically reviewed technological innovations and applications of hy-drology-water quality-aquatic ecology synergistic monitoring in the Yangtze River basin and discussed fu-ture directions of development.Our aim was to provide theoretical and technical support for ecological protection and restoration of the Yangtze River basin.In terms of technological system development,we integrated a suite of advanced technologies that includes satellite remote sensing,the Internet of Things(IoT),in-situ observation,and unmanned aerial vehicle(UAV)surveys to construct a comprehensive"space-air-ground-water"stereoscopic observation network.This network spans the entire basin and en-compasses regional and river section gradients to ensure full coverage.Vertically,a collaborative frame-work has been established that features macro-level monitoring via space-based remote sensing,precise measurements by airborne UAVs,real-time data acquisition by ground-based IoT devices,and subsurface inspection utilizing underwater mobile units.Horizontally,a grid of fixed monitoring stations,mobile monitoring units,and emergency monitoring equipment have been implemented,effectively enhancing the ability to synergistically characterize hydrological dynamics,core water quality parameters,and aquat-ic ecosystem characteristics across different scales.In terms of implementing the comprehensive monitor-ing system,extensive efforts have been made to advance innovations in multi-source data fusion and mod-el coupling.We have proposed targeted data fusion approaches to integrate multi-dimensional information encompassing data on hydrology,water quality,biology and meteorology,forming an integrated"data-model-application"processing platform.By coupling theoretical models with empirical models,we have enhanced our capability to simulate complex river basin processes that improve scientific support for eco-system health assessment and early warning systems.Synergistic environmental monitoring provides cru-cial support for ecological protection in the Yangtze River basin.We have also identified core challenges to synergistic monitoring:data heterogeneity that lowers the efficiency of multi-source data collection,in-sufficient accuracy in cross-scale simulations that limit the analysis of key ecological processes,and lack of collaborative management mechanisms that reward rapid transformation of technological achievements into practical applications.In the future,we must overcome the limitations of intelligent sensing technolo-gy,establish a standardized framework for data collection,processing,and sharing,optimize cross-scale dynamic coupling models,and analyze response mechanisms of basin ecological resilience to global cli-mate change.These efforts will promote synergistic monitoring,integration of technologies and intelligent decision-making,thereby laying a solid scientific foundation for sustainable development in the Yangtze River basin.
钱宝;李晓慧;熊明
长江水利委员会水文局,湖北 武汉 430010长江水利委员会水文局"天空地水"立体化生态感知创新团队,湖北 武汉 430010长江水利委员会水文局,湖北 武汉 430010
资源环境
长江大保护流域管理水文-水质-水生态协同监测多源数据融合
Yangtze River protectionriver basin managementhydrology-water quality-aquatic ecolo-gysynergistic monitoringmulti-source data fusion
《水生态学杂志》 2026 (1)
1-12,12
国家自然科学基金(U2340209)湖北省智慧水电技术创新中心开放研究基金(1524020004)长江水利委员会水文局科技创新基金(SWJ-24CJX06)国家留学基金资助项目(202303340012).
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