Modeling temporal and spatial variations of biogeochemical processes in a large subtropical lake: Assessing alternative solutions to algal blooms in Lake Okeechobee, Florida

Abstract

Study region:: Algal blooms (ABs), often exacerbated by excess nutrients from anthropogenic activities, can pose serious risks to public health, fisheries, and ecosystem structure and functions. Lake Okeechobee is located in southcentral Florida (USA), and with a surface area of 1730 km2, it is the largest subtropical lake in the United States. This lake is shallow, nutrient-rich, and subject to frequent and intense blooms of cyanobacteria, some of which are toxic. Study focus:: In this study, a three-dimensional (3D) model was developed, coupling long-term monitoring data with complex physical, chemical, and ecological processes at fine spatial (15–1000 m horizontal mesh size) and temporal (1 h) resolution. We used this model to understand the influence of environmental factors and nutrient management on ABs dynamics in Lake Okeechobee. New Hydrological Insights for the Region:: The model showed that ABs mostly developed in shallow nearshore regions near canal outlets, and then spread over the lake as a result of prevailing winds and currents. Hypothetical scenario modeling showed that reducing both nitrogen and phosphorus inputs by 50%–75% would be more effective at reducing ABs in the lake than targeting a single nutrient. The model could be used as a tool to assess the effectiveness of different nutrient management strategies in Lake Okeechobee and its watershed, while the framework could be adopted to other large water bodies facing similar issues.

Keywords

• Numerical modeling
• Algal blooms
• Lake Okeechobee
• Management options
• Legacy nutrients
• Delft3D