Understanding the Spatiotemporal Variation of Water Quality and Phytoplankton Biomass in Subtropical Reservoir Using the Blue–Sky Multispectral Data

IF 2.5 3区 环境科学与生态学 Q2 ECOLOGY
Ecohydrology Pub Date : 2025-07-11 DOI:10.1002/eco.70070
Tatenda Dalu, Faith F. Muthivhi, Farai Dondofema, Linton F. Munyai, Pule Mpopetsi, Timothy Dube, Naicheng Wu
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引用次数: 0

Abstract

Chlorophyll-a (chl-a) is an optically active compound used as a proxy for phytoplankton biomass to determine the trophic states of aquatic ecosystems. Blue–sky remote sensing technologies present low-cost and effective monitoring techniques for water quality on a large scale. This study was aimed at using readily available Landsat multispectral images to assess the spatial and temporal variation of phytoplankton biomass in Nandoni reservoir, Limpopo Province, and at examining the relationships that exist between the physicochemical variables and chl-a concentration. Landsat 7 ETM+ and Landsat 8 OLI images for June (dry) and December (wet), for the years 2008–2020, were used to derive the distribution of chl-a concentration. Using regression techniques, in situ measured chl-a showed a strong and perfectly linear relationship to the predicted Landsat chl-a in the Nandoni reservoir. There was a negative significant correlation between land use and land cover and water quality variables. Using permutational multivariate analysis of variance (PERMANOVA) analysis, we uncovered significant differences for chl-a concentration in sites, seasons and zones. A significant positive correlation was observed between water temperature and chl-a concentration. In contrast, a strong negative significant correlation was observed for chl-a with salinity and total dissolved solids. chl-a concentration in the Nandoni reservoir was derived using Landsat remote sensing images, suggesting that the Landsat data is suitable for monitoring small reservoirs in a short timescale. The results of this study suggest that remote sensing techniques can be used to control the development of an early warning system for this study and other reservoirs. Furthermore, the results highlight the role of using analysis ready Landsat series data in monitoring phytoplankton biomass and chl-a abundance in freshwater systems.

基于蓝天多光谱数据的亚热带水库水质和浮游植物生物量时空变化研究
叶绿素-a (chl-a)是一种光学活性化合物,被用作浮游植物生物量的代表,以确定水生生态系统的营养状态。蓝天遥感技术是一种低成本、有效的大规模水质监测技术。本研究旨在利用Landsat多光谱图像对林波波省Nandoni水库浮游植物生物量的时空变化进行评估,并探讨物理化学变量与chl-a浓度之间的关系。利用2008-2020年6月(干旱)和12月(潮湿)的Landsat 7 ETM+和Landsat 8 OLI图像,推导出chl-a浓度的分布。利用回归技术,原位测量的chl-a与Landsat预测的Nandoni储层chl-a表现出强烈而完美的线性关系。土地利用、土地覆被与水质变量呈显著负相关。利用多变量排列方差分析(peromova),我们发现chl-a浓度在不同地点、季节和地区存在显著差异。水温与chl-a浓度呈显著正相关。相反,chl-a与盐度和总溶解固形物呈显著负相关。利用Landsat遥感图像得到了Nandoni水库chl-a浓度,表明Landsat数据适合于短时间尺度的小型水库监测。本研究结果表明,遥感技术可用于控制本研究和其他水库预警系统的开发。此外,研究结果强调了利用可分析的Landsat系列数据在监测淡水系统中浮游植物生物量和chl-a丰度方面的作用。
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来源期刊
Ecohydrology
Ecohydrology 环境科学-生态学
CiteScore
5.10
自引率
7.70%
发文量
116
审稿时长
24 months
期刊介绍: Ecohydrology is an international journal publishing original scientific and review papers that aim to improve understanding of processes at the interface between ecology and hydrology and associated applications related to environmental management. Ecohydrology seeks to increase interdisciplinary insights by placing particular emphasis on interactions and associated feedbacks in both space and time between ecological systems and the hydrological cycle. Research contributions are solicited from disciplines focusing on the physical, ecological, biological, biogeochemical, geomorphological, drainage basin, mathematical and methodological aspects of ecohydrology. Research in both terrestrial and aquatic systems is of interest provided it explicitly links ecological systems and the hydrologic cycle; research such as aquatic ecological, channel engineering, or ecological or hydrological modelling is less appropriate for the journal unless it specifically addresses the criteria above. Manuscripts describing individual case studies are of interest in cases where broader insights are discussed beyond site- and species-specific results.
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