Modeling water quality and cyanobacteria blooms in Lake Okeechobee: I. Model descriptions, seasonal cycles, and spatial patterns

IF 3.2 3区 环境科学与生态学 Q2 ECOLOGY
Mingshun Jiang , Ashely Brereton , Jordon Beckler , Timothy Moore , Rachel A. Brewton , Chuanmin Hu , Brian E. Lapointe , Malcolm N. McFarland
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引用次数: 0

Abstract

Lake Okeechobee is a shallow subtropical lake that is critically important for south Florida agriculture and the Everglades. In summer, the lake typically experiences strong blooms of cyanobacteria including toxin producing Microcystis aeruginosa. To understand the dynamics of these blooms and water quality in the lake, a coupled hydrodynamic-biogeochemical model based on the Regional Ocean Modeling System (ROMS) has been developed. The biogeochemical model was constructed to simulate major biogeochemical processes including nitrogen (N) and phosphorus (P) cycles, phytoplankton growth, zooplankton grazing, and microbial loop, among others. A three-year (2018–2020) simulation was carried out and calibrated with available in situ and remote sensing data for key physical and biogeochemical parameters. Although model and data generally agree in spatial patterns and seasonal cycles, significant discrepancies exist including exact timings of the blooms and dissolved inorganic and organic P concentrations. Model results indicate that Lake Okeechobee typically exhibits a two-layer circulation in summer with surface and bottom currents generally moving in the opposite directions. This feature couples with diurnal cycles of atmospheric forcing (winds and heating/cooling) and diel vertical migration (DVM) of Microcystis to strongly affect not only the spatial patterns of cyanobacteria blooms but also the bloom intensity in summertime. Horizontally, both model results and remote sensing images indicate that cyanobacteria distributions are concentrated in the central and northern lake during summer and in western lake in spring and fall, in responses to the prevailing winds. Consistent with previous laboratory and observational studies, model results also suggest that, among the two main nutrients N and P, nitrogen is likely the primary limiting nutrient for phytoplankton growth along the northwestern coast where dissolved inorganic nitrogen is typically depleted in summer. In the central and southeastern lake, nutrient concentrations are relatively higher, and light and winds are likely the main factors limiting phytoplankton blooms. In addition, surface winds and water temperature are important in regulating the seasonality of phytoplankton blooms. The model, however, is limited by the uncertainties of key biogeochemical parameters including the specifics of Microcystis vertical migration, and sediment-water interactions including nutrient fluxes and sediment transport. Nevertheless, with further development, this model can be useful for forecasting water quality and phytoplankton blooms and to assist in water management decision-making in the future.
模拟奥基乔比湖的水质和蓝藻华:1 .模型描述、季节周期和空间模式
奥基乔比湖是一个亚热带浅湖,对南佛罗里达的农业和大沼泽地至关重要。在夏天,这个湖通常会经历蓝藻的强烈繁殖,包括产生毒素的铜绿微囊藻。为了了解这些水华的动态和水质,建立了基于区域海洋模拟系统(ROMS)的水动力-生物地球化学耦合模型。构建生物地球化学模型,模拟氮(N)和磷(P)循环、浮游植物生长、浮游动物放牧和微生物循环等主要生物地球化学过程。利用现有的原位和遥感数据,对关键物理和生物地球化学参数进行了为期三年(2018-2020年)的模拟和校准。虽然模型和数据在空间格局和季节周期上基本一致,但在华的确切时间和溶解的无机磷和有机磷浓度方面存在显著差异。模式结果表明,奥基乔比湖夏季典型地表现为两层环流,表层和底层的水流通常朝相反的方向运动。这一特征与大气强迫(风和加热/冷却)的日循环以及微囊藻的日垂直迁移(DVM)相结合,不仅强烈影响蓝藻华的空间格局,而且影响夏季蓝藻华的强度。在水平方向上,模式结果和遥感影像均表明,蓝藻在夏季集中分布在湖泊中部和北部,春秋季集中分布在湖泊西部,这是对盛行风的响应。与以往的实验室和观测研究一致,模式结果还表明,在氮和磷两种主要营养物质中,氮可能是西北海岸浮游植物生长的主要限制营养物质,而西北海岸的溶解无机氮通常在夏季耗尽。在湖泊中部和东南部,营养物浓度相对较高,光照和风可能是限制浮游植物繁殖的主要因素。此外,海面风和水温对浮游植物华生的季节性也有重要的调节作用。然而,该模型受到关键生物地球化学参数的不确定性的限制,包括微囊藻垂直迁移的细节,以及沉积物-水相互作用,包括养分通量和沉积物运输。然而,随着进一步发展,该模型可用于预测水质和浮游植物繁殖,并有助于未来的水管理决策。
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来源期刊
Ecological Modelling
Ecological Modelling 环境科学-生态学
CiteScore
5.60
自引率
6.50%
发文量
259
审稿时长
69 days
期刊介绍: The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).
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