School of Marine Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China.
School of Marine Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China; Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China.
Water Res. 2024 May 1;254:121442. doi: 10.1016/j.watres.2024.121442. Epub 2024 Mar 9.
Suspended Particulate Matter (SPM) concentration stands as a pivotal determinant of water quality within lake ecosystems. However, comprehension of the enduring dynamics of SPM within lakes is severely hindered due to a shortage of long-term records. Our research has developed a robust remote sensing algorithm to retrieve the SPM concentration in Lake Gaoyou, situated in the lower reaches of the Huai River basin in China. The algorithm demonstrates commendable performance, with an uncertainty of 28.68 %. Leveraging Landsat series sensors imagery, our investigation yields high spatial resolution SPM concentration maps, which first provide a four-decades record of the SPM distribution within Lake Gaoyou. Our findings unveil a significant annual reduction of 1.35 mg L in SPM concentration over the past four decades. This notable decline is probably attributable to a series of ecological initiatives to enhancing the management of the eco-friendly within the basin. Furthermore, our research delineated the influence of environmental factors on the intra-annual SPM dynamics across distinct spatial domains, encompassing the natural inlet region, semi-obstructed inlet region and outlet areas within the lake The SPM concentration in the natural inlet region exhibits a conspicuous correlation with precipitation. Increased precipitation induces runoff within the basin, facilitating the transport of suspended solids and sediment into the lake, consequently augmenting SPM levels. Conversely, the semi-obstructed inlet and outlet areas are predominantly influenced by the wind field, with variations in SPM attributed to sediment resuspension caused by water mixing driven by wind forcing. Our research can be considered an important reference to the evaluation of the management of the lake over long periods.
悬浮颗粒物(SPM)浓度是湖泊生态系统水质的关键决定因素。然而,由于长期记录的缺乏,人们对湖泊中 SPM 的持久动态的理解受到严重阻碍。我们的研究开发了一种强大的遥感算法,用于检索位于中国淮河流域下游的高邮湖的 SPM 浓度。该算法表现出令人称赞的性能,不确定性为 28.68%。利用陆地卫星系列传感器图像,我们的调查产生了高空间分辨率的 SPM 浓度图,首次提供了高邮湖 SPM 分布的四十年记录。我们的研究结果表明,在过去的四十年里,SPM 浓度每年显著减少 1.35 毫克/升。这种显著的下降可能归因于一系列生态举措,旨在加强流域内的生态友好型管理。此外,我们的研究还描绘了环境因素对不同空间域内年度 SPM 动态的影响,包括自然入口区域、半阻塞入口区域和湖泊内的出口区域。自然入口区域的 SPM 浓度与降水表现出明显的相关性。增加的降水会导致流域内的径流水流,促进悬浮固体和沉积物进入湖泊,从而增加 SPM 水平。相反,半阻塞的入口和出口区域主要受风场的影响,SPM 的变化归因于风驱动的水混合引起的泥沙再悬浮。我们的研究可以被认为是对湖泊长期管理评估的重要参考。