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Assessing Potential Algal Blooms in a Shallow Fluvial Lake by Combining Hydrodynamic Modelling and Remote-Sensed Images

机译:结合水动力模型和遥感图像评估浅水河湖中潜在的藻华

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Shallow fluvial lakes are dynamic ecosystems shaped by physical and biological factors and characterized by the coexistence of phytoplankton and macrophytes. Due to multiple interplaying factors, understanding the distribution of phytoplankton in fluvial lakes is a complex but fundamental issue, in the context of increasing eutrophication, climate change, and multiple water uses. We analyze the distribution of phytoplankton by combining remotely sensed maps of chlorophyll-a with a hydrodynamic model in a dammed fluvial lake (Mantua Superior Lake, Northern Italy). The numerical simulation of different conditions shows that the main hydrodynamic effects which influence algal distribution are related to the combined effect of advection due to wind forces and local currents, as well as to the presence of large gyres which induce recirculation and stagnation regions, favoring phytoplankton accumulation. Therefore, the general characters of the phytoplankton horizontal patchiness can be inferred from the results of the hydrodynamic model. Conversely, hyperspectral remote-sensing products can be used to validate this model, as they provide chlorophyll-a distribution maps. The integration of ecological, hydraulic, and remote-sensing techniques may therefore help the monitoring and protection of inland water quality, with important improvements in management actions by policy makers.
机译:浅河湖泊是由物理和生物因素塑造的动态生态系统,其特征是浮游植物和大型植物共存。由于多种相互作用的因素,在富营养化,气候变化和多种用水增加的背景下,了解河流湖泊中浮游植物的分布是一个复杂但基本的问题。我们通过结合遥感的叶绿素-a映射和水坝模型(在意大利北部的曼图亚优越湖)中的水动力模型来分析浮游植物的分布。不同条件下的数值模拟表明,影响藻类分布的主要水动力效应与风力和局部水流对流的综合作用有关,还与大旋涡的存在有关,大旋涡引起回流和滞流区域,有利于浮游植物积累。因此,从水动力模型的结果可以推断出浮游植物水平斑驳的一般特征。相反,由于高光谱遥感产品提供了叶绿素a分布图,因此可以用来验证该模型。因此,生态,水力和遥感技术的整合可能有助于内陆水质的监测和保护,决策者在管理行动上的重要改进。

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