Coastal Upwelling Influences Hypoxia Spatial Patterns and Nearshore Dynamics in Lake Erie

Abstract

Hypoxia, defined as dissolved oxygen (DO) < 2 mg/L, in the central basin of Lake Erie has been studied since the mid‐1900s. Even so, spatial patterns of hypoxia, and episodic hypoxia in nearshore areas where drinking water plant intakes are located, are not well characterized owing to limited observations and short‐term dynamics. We evaluated a physically based, DO model with respect to patterns of hypoxia observed in Lake Erie. The DO model used assigned rates of sediment and water column oxygen demand that were temperature dependent but otherwise spatially and temporally uniform. The DO model was linked to National Oceanic and Atmospheric Administration's (NOAA) Lake Erie Operational Forecasting System hydrodynamic model, an application of the Finite Volume Community Ocean Model (FVCOM). Model temperature and DO were compared with observations from ship‐based studies, real‐time sensor networks and an array of moored sensors that we deployed in 2017. In years with dominant southwesterly winds, persistent downwelling occurred along the south shore, which resulted in a thinner thermocline and earlier initiation of hypoxia along the south shore than the north. Occasional northeast winds temporarily reversed this pattern, causing upwelling along the south shore that brought hypoxic water to nearshore locations and water intakes. The DO model reproduced observed spatial and temporal patterns of hypoxia and revealed locations subject to episodes of hypoxia, including nearshore Ohio, north of Pelee Island, and near the Bass Islands. Model skill was limited in some respects, highlighting the importance of accurate simulation of the thermal structure and spatial patterns of oxygen demand rates.

Increases in Great Lake winds and extreme events facilitate interbasin coupling and reduce water quality in Lake Erie

“…The SRP flux from the sediment during hypoxic upwelling is, therefore, unlikely to contribute meaningfully to the internal loading of phosphorus in the western basin. Conversely, the SRP load in the upwelled hypoxic hypolimnetic water from the central basin can be considerable; i.e., (~ 21 ± 18) × 10 3 kg based on 0.035 ± 0.015 mg SRP L −149 × ~ 2.0 ± 0.5 m height 22 × ~ 305 ± 207 km 2 area (an average spatial extent of hypoxic water in the western basin due to upwelling events based on numerical simulations 64 ). This represents < 3.5% of the total volume of hypoxic water in the hypolimnion of the central basin (i.e., an average of ~ 5000 km 2 area based on observations during 1987-2007 56 × hypolimnion thickness of > 3.5 m 32,46 .…”

High Sensitivity of Lake Hypoxia to Air Temperatures, Winds, and Nutrient Loading: Insights From a 3‐D Lake Model

“…The present results show that higher temperatures and/or weaker winds would bring more hypoxic conditions to the southwestern part of the central basin, where water for over a million residents of Cleveland is taken (e.g., Figures 10e-10j). Results shown for 2016 and 2017 in Rowe et al (2019) depicted a broadly similar spatiotemporal pattern of hypoxia, although their results showed an even more pronounced and early invasion of hypoxic water to shallow nearshore locations, especially in the southwest central basin. Water intakes have already been affected by the advection of hypoxic waters in recent years (Ruberg et al, 2008).…”

“…The relatively thin (commonly 2–5 m thickness) and warm (from 5°C to more than 10°C) hypolimnion in the central basin has dissolved oxygen (DO) concentrations of mostly 2 mg L −1 or less by late summer, due to biological oxygen demand in sediments and in the water column (Bocaniov et al, 2016; Liu et al, 2014; Rowe et al, 2019; Rucinski et al, 2010). Low DO conditions put stress on public water supply systems (Bocaniov & Scavia, 2016; Rowe et al, 2019; Ruberg et al, 2008) and bottom‐dwelling aquatic organisms, especially sessile ones (Karatayev et al, 2018). The seasonal occurrence of waters with a DO concentration of 2 mg L −1 or less (commonly taken as the hypoxic threshold) creates differential losses of habitat quality among fish species, with potential to alter population dynamics (Scavia et al, 2014).…”

“…Rucinski et al (2014) used a 1‐D model to conclude that meteorology was a more powerful predictor of interannual variations of hypoxia than the external nutrient loads. Field observations and modeling show, however, that the hypoxic zone is dynamic and patchy (Bocaniov et al, 2016, 2017; Bocaniov & Scavia, 2016; Kraus et al, 2015; Rowe et al, 2019). Hypoxia is driven by a variety of physical processes such as vertical mixing and horizontal transport (Beletsky et al, 2012), downwelling/upwelling episodes (Rao et al, 2014), and near‐inertial internal waves (Rao et al, 2008) that can be at least partially captured in 3‐D, but not lower dimensional, modeling.…”

Intense variability of dissolved oxygen and temperature in the internal swash zone of Hamilton Harbour, Lake Ontario

“…To spatially extrapolate the field observations and estimate extent of internal swash zone, numerical modelling was conducted with the 3D finite-volume community ocean model FVCOM (Chen et al 2003(Chen et al , 2006. FVCOM has been used extensively to successfully resolve stratified flow dynamics in complex geometries (Anderson et al 2010, Rowe et al 2019. FVCOM uses an unstructured-grid and finite-volume approach to solve the primitive equations (momentum, continuity, temperature, salinity, density, and Coriolis).…”