Managing Oxygen in Lakes and Reservoirs with Improved One-dimensional and Three-dimensional Hydrodynamic and Water-quality Models

Abstract

Water-quality problems including hypoxia, eutrophication, algal blooms and the release of reduced species from the sediments in lakes and reservoirs remain a global challenge due to their negative impacts on fisheries, greenhouse gas emissions and water-related tourism. Water-quality management systems such as bubble plume diffusers and side-stream supersaturation systems (SSS) are deployed to deal with these water-quality problems. To successfully manage water-quality using these systems, it is important for water-quality managers to accurately evaluate the performance of the water-quality management systems and design oxygenation schedules accordingly. For performance evaluation purpose it is necessary to couple models of oxygenation and mixing system with hydrodynamic and water-quality models. In addition, sediment oxygen demand (J_(O_2 )) is a critical driver of water quality and a focus for water quality modelling and management. It has been demonstrated that management interventions to increase hypolimnetic dissolved oxygen (DO) concentration may unintentionally enhance the overall J_(O_2 ). Existing J_(O_2 ) models include one-layer bulk model, two-layer models and sediment diagenesis models. These models lack spatial resolution, especially in freshwater bodies. Another drawback of these models is that they were derived from laboratory experiments where field oxygenation conditions cannot be replicated. This drawback prevents existing J_(O_2 ) model from accurately predicting J_(O_2 ) in dynamic field conditions, for example, accounting for the changes between oxic/anoxic hypolimnion and thinning/thickening diffusive boundary layer (DBL). Further, existing DBL characterization procedures in J_(O_2 ) models are subjective, which adversely impacts J_(O_2 ) model performance. The present study aims to resolve hypolimnetic DO dynamics with oxygenation and mixing systems in operation, leading to improved one-dimensional (1-D) and three-dimensional (3-D) hydrodynamic and water-quality models. First, the research sought to develop a mechanistic model for J_(O_2 ) based on high-resolution in situ and laboratory DO microprofiler data. For laboratory studies, a mini-diffuser was adopted to simulate field oxygenation conditions with various oxygenation rates. Kinetic models were fit to DO microprofiles with both zero and negative-flux lower boundary conditions. The negative-flux lower boundary condition accounted for the oxidation of an upward flux of reduced species. Based on visual inspection, goodness-of-fit criteria of the sediment DO profiles and DO fluxes at the sediment-water interface (SWI), the negative-flux lower boundary condition was found to describe DO consumption kinetics more accurately. Subsequently, a computational procedure characterizing DBL and SWI was introduced, which worked well for microprofiles collected at different oxygenation rates and from different water bodies. The correlation between computationally characterized DBL thickness (δ_DBL) and oxygenation rates was investigated, and a decreasing trend of the δ_DBL with increasing oxygenation rate was observed. J_(O_2 ) modeled by assuming the J_(O_2 ) balance at the SWI agreed well with the field J_(O_2 ), with the differences between the average field and modeled J_(O_2 ) less than 15% for all three water bodies. To allow hydrodynamic and water-quality models to better represent oxygenation and mixing processes, the present research coupled the 1-D model with bubble plume diffuser and SSS models. The 3-D water-quality model was calibrated using the 1-D water-quality model to reduce computational time. The 1-D bubble plume model adequately simulated the bubble plume mixing effect, and the 3-D coupled hydrodynamic and water-quality model produced satisfactory water-quality results. To evaluate and compare the performance of these models, predicted temperature and DO for two sets of one-year simulations were analyzed based on two goodness-of-fit criteria. It was recommended that the 1-D model be adopted when stratification and artificial mixing do not substantially vary during the simulation period, and that the 3-D model be adopted to resolve stratification, artificial mixing and spatially sensitive water-quality variables during dynamic periods. The improved models provide useful tools for the design and operation of water quality management systems.