Application of Geostatistical Methods in the Study of Algae in Water Reservoirs: A Review

被引:0
|
作者
Zawadzki, Jaroslaw [1 ]
Fabijanczyk, Piotr [1 ]
机构
[1] Warsaw Univ Technol, Fac Bldg Serv Hydro & Environm Engn, Ul Nowowiejska 20, PL-00661 Warsaw, Poland
关键词
phytoplankton; algae; algae blooms; geostatistics; spatial statistics; water reservoirs; time-space phenomena; kriging; co-kriging; environment; water pollution; climate change; EUTROPHICATION ASSESSMENT; CHLOROPHYLL-A; LAKE BALATON; PHYTOPLANKTON; PATTERNS; NUTRIENT; IMAGERY; BLOOM;
D O I
10.2478/eces-2024-0031
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The growing pollution of aquatic environments, primarily of anthropogenic origin, combined with global climate change, has led to significant increases in eutrophication. This process often results in harmful algal blooms (HABs) of phytoplankton and algae in various water bodies, including inland lakes, marshes, rivers, seas, and oceans. These blooms pose a serious threat not only to aquatic ecosystems but also to human health. Understanding phytoplankton and algal blooms is inherently complex, as these phenomena manifest on multiple spatial and temporal scales. Comprehensive studies of phytoplankton and algae require the collaboration of scientists from diverse scientific disciplines, including biology, ecology, and environmental science. One of the critical tools in this multidisciplinary approach is geostatistics, an advanced and continuously evolving branch of statistics that specialises in analysing spatial and temporal phenomena. Geostatistics is particularly well-suited for the study of phytoplankton and algal blooms due to its ability to handle data that varies across different scales and locations. This review presents and discusses selected studies that employ geostatistical methods to investigate plankton and algae in various water bodies. It highlights the most significant scientific works that, in the authors' opinion, represent milestones in the application of these studies. Furthermore, various geostatistical methods are explored, ranging from variography to spatiotemporal modelling, providing insights into spatial and temporal patterns and their variability of phytoplankton and algal blooms in aquatic ecosystems.
引用
收藏
页码:473 / 491
页数:19
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