Water transparency and color in large rivers observed by Sentinel-2 MSI and its implications for SDG 6.3.2 monitoring

IF 8.6 Q1 REMOTE SENSING
Xuezhu Jiang , Shenglei Wang , Junsheng Li , Evangelos Spyrakos , Huaxin Yao , Fangfang Zhang , Andrew N. Tyler , Bing Zhang
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引用次数: 0

Abstract

Rivers are vital to Earth’s water cycle and human societies, yet their water quality is increasingly threatened by climate change and human activities. While satellite remote sensing has emerged as a powerful tool for large-scale water quality monitoring across diverse aquatic ecosystems, a systematic analysis of water optical properties in rivers remains limited, restricting its use in supporting Sustainable Development Goal (SDG) monitoring. This study presents the first comprehensive analysis of water transparency (Secchi disk depth, ZSD) and color (Forel-Ule Index) in the five large rivers (Yangtze, Danube, Mississippi, Nile, and Amazon) using Sentinel-2 MSI data (2019–2021). Results reveal significant spatial-seasonal variations: Danube had the highest transparency (ZSD) and bluest color (FUI), followed by Nile, Yangtze, Mississippi, and Amazon. These differences were primarily driven by basin-specific soil erodibility and precipitation. Spatially, the Yangtze, Mississippi, and Amazon exhibited decreasing ZSD and increasing FUI from their upper to lower reaches, contrasting with different trends in Danube and Nile, highlighting the influence of large dams. Seasonally, two different patterns were observed in the five rivers, underscoring the hydrological influences on water optical properties. Furthermore, as two key optical water quality parameters, ZSD and FUI were analyzed for their complementary roles in characterizing river turbidity across varying water conditions. By quantifying spatiotemporal patterns, this study establishes a global baseline for river optical properties and supports SDG 6.3.2 monitoring. Our findings offer new insights into large-scale river ecosystem dynamics under environmental change.
Sentinel-2 MSI观测到的大河的水透明度和颜色及其对可持续发展目标6.3.2监测的影响
河流对地球水循环和人类社会至关重要,但其水质正日益受到气候变化和人类活动的威胁。虽然卫星遥感已成为跨多种水生生态系统进行大规模水质监测的有力工具,但对河流水光学特性的系统分析仍然有限,限制了卫星遥感在支持可持续发展目标监测方面的应用。本研究首次利用Sentinel-2 MSI数据(2019-2021)对五大河流(长江、多瑙河、密西西比河、尼罗河和亚马逊河)的水透明度(塞奇盘深度,ZSD)和颜色(Forel-Ule指数)进行了综合分析。结果表明:多瑙河的透明度(ZSD)和颜色(FUI)最高,其次是尼罗河、长江、密西西比河和亚马逊河;这些差异主要是由流域特有的土壤可蚀性和降水驱动的。从空间上看,长江、密西西比河和亚马孙河流域从上游到下游ZSD降低,FUI增加,与多瑙河和尼罗河的变化趋势不同,大坝的影响突出。在季节分布上,5条河流有两种不同的模式,强调了水文对水光学性质的影响。此外,作为两个关键的光学水质参数,ZSD和FUI分析了它们在不同水质条件下表征河流浊度的互补作用。通过量化时空格局,建立全球河流光学特性基线,支持可持续发展目标6.3.2监测。研究结果为研究环境变化下大尺度河流生态系统动态提供了新的思路。
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来源期刊
International journal of applied earth observation and geoinformation : ITC journal
International journal of applied earth observation and geoinformation : ITC journal Global and Planetary Change, Management, Monitoring, Policy and Law, Earth-Surface Processes, Computers in Earth Sciences
CiteScore
12.00
自引率
0.00%
发文量
0
审稿时长
77 days
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
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