基于 Sentinel-2 卫星影像的采煤沉陷水域水质反演与时空特征研究：以淮南谢李矿区为例

Spatio-temporal characteristics of the surface water quality in coal mining subsidence area revealed from sentinel-2 satellite imagery: a case study of the Xieli mining area in Huainan

摘要

【目的】揭示淮南煤田采煤沉陷区地表水环境的时空演变规律，阐明土地利用对水质的影响，为矿区生态与农业环境可持续发展提供依据。【方法】结合野外水质采样与2018—2024年Sentinel-2遥感影像，采用Pearson相关性分析构建叶绿素a、COD和浊度的遥感反演模型，并运用多尺度缓冲区与冗余分析（RDA）定量评估土地利用对水质的空间尺度效应。【结果】构建的叶绿素a（R²=0.645）、COD（R²=0.692）和浊度（R²=0.822）遥感模型均具有较高适用性。时空分析表明，叶绿素a浓度总体下降，西部和南部较高；COD浓度先升后降，2022年达峰值；浊度波动变化，空间异质性显著。土地利用分析显示，建设用地与叶绿素a呈稳定负相关（r_min=－0.86），与浊度正相关（r_max=0.40）；耕地与浊度呈极强负相关（r≈－0.90）。RDA模型表明土地利用共同解释水质变量74.80%的变异（P=0.002）。【结论】本研究构建了有效的水质遥感反演模型，揭示了采煤沉陷区水质参数的时空演变规律，明确了农业活动等土地利用方式对水环境的多尺度影响，对推动矿区“水-农系统”协同治理具有重要实践意义。

Abstract

[Objective] This study aimed to reveal the spatiotemporal evolution of the surface water environment in the Huainan coal mining subsidence area, clarify the impact of land use on water quality, and provide a basis for the sustainable development of the ecological and agricultural environment in the mining area. [Method] By combining field water quality sampling with multi-temporal Sentinel-2 remote sensing images from 2018 to 2024, Pearson correlation analysis was used to develop remote sensing inversion models for chlorophyll-a, chemical oxygen demand (COD), and turbidity. Multi-scale buffer analysis and redundancy analysis (RDA) were applied to quantitatively assess the spatial scale effects of land use on water quality. [Result] The constructed remote sensing inversion models demonstrated high applicability, with R² values of 0.645 for chlorophyll-a, 0.692 for COD, and 0.822 for turbidity. Spatiotemporal analysis showed that chlorophyll-a concentrations generally decreased, with higher levels in the western and southern regions. COD concentrations initially increased, peaked in 2022, and then declined, while turbidity exhibited fluctuating changes with significant spatial heterogeneity. Land use analysis revealed a stable negative correlation between construction land and chlorophyll-a (r_min = -0.86), a positive correlation with turbidity (r_max = 0.40), and a strong negative correlation between cultivated land and turbidity (r ≈ -0.90). The RDA model indicated that land use collectively explained 74.80% of the variation in water quality variables (P = 0.002). [Conclusion] This study establishes effective remote sensing inversion models for water quality, reveals the spatiotemporal evolution patterns of water quality parameters in the coal mining subsidence area, and clarifies the multi-scale impacts of land use, such as agricultural activities, on the water environment. The findings hold significant practical value for promoting the coordinated management of the "water-agriculture system" in mining areas.

关键词

采煤沉陷区 / 水质反演 / Sentinel-2 / 时空特征 / 相关性分析

Key words

mining subsidence area / water quality retrieval / sentinel-2 / spatio-temporal characteristics / cor- relation analysis

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基金资助

安徽省绿色矿山工程研究中心开放基金项目(AGMERC-23KF-06)

国家自然科学基金项目(32171573)