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过去36年中,陆地卫星对中国珠江口总悬浮固体浓度的观测。

Landsat observations of total suspended solids concentrations in the Pearl River Estuary, China, over the past 36 years.

作者信息

Sun Qiang, Luo Wei, Dong Xianzhang, Lei Shaohua, Mu Meng, Zeng Shuai

机构信息

South China Institute of Environmental Science, Ministry of Ecology and Environment, NO.18 Ruihe RD., Guangzhou, 510535, China; National Key Laboratory of Urban Ecological Environmental Simulation and Protection, Guangzhou, 510535, China.

School of Geography and Environmental Engineering, Jiangxi Provincial Key Laboratory of Low-Carbon Solid Waste Recycling, Gannan Normal University, Ganzhou, 341000, China.

出版信息

Environ Res. 2024 May 15;249:118461. doi: 10.1016/j.envres.2024.118461. Epub 2024 Feb 12.

Abstract

Information on long-term trends in total suspended solids (TSS) is critical for assessing aquatic ecosystems. However, the long-term patterns of TSS concentration (C) and its latent drivers have not been well investigated. In this study, we developed and validated three semi-analysis algorithms for deriving C using Landsat images. Subsequently, the long-term trends in C in the Pearl River Estuary (PRE) from 1987 to 2022 and the driving factors were clarified. The developed algorithms yielded excellent performance in estimating C, with mean absolute percentage errors <25% and root mean square errors of <13 mg/L. Long-term Landsat observations showed an overall decreasing trend and significant spatiotemporal dynamics of the C in the PRE from 1987 to 2022. The analysis of driving factors suggested that industrial sewage, cropland, forests and grasslands, and built-up land were the four potential driving forces that explained 87.81% of the long-term variation in C. This study not only provides 36-year recorded datasets of C in estuary water, but also offers new insights into the complex mechanisms that regulate C spatiotemporal dynamics for water resource management.

摘要

总悬浮固体(TSS)的长期趋势信息对于评估水生生态系统至关重要。然而,TSS浓度(C)的长期模式及其潜在驱动因素尚未得到充分研究。在本研究中,我们开发并验证了三种利用陆地卫星图像推导C的半分析算法。随后,明确了1987年至2022年珠江口(PRE)C的长期趋势及其驱动因素。所开发的算法在估算C方面表现出色,平均绝对百分比误差<25%,均方根误差<13mg/L。长期的陆地卫星观测显示,1987年至2022年PRE的C总体呈下降趋势,且具有显著的时空动态变化。驱动因素分析表明,工业污水、农田、森林和草地以及建设用地是解释C长期变化87.81%的四个潜在驱动力。本研究不仅提供了河口水中C的36年记录数据集,还为水资源管理中调节C时空动态的复杂机制提供了新的见解。

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