ABSTRACT Sediment oxygen demand (SOD) and hypolimnetic oxygen demand (HOD) drive deep-water dissolved oxygen (DO) depletion in lakes, yet these parameters can be difficult to be measure routinely. To address this issue, we present an empirical DO depletion model from time-series measurements of hypolimnetic DO and water-column temperature profiles to estimate hypolimnion thickness (H). The model is based on a dataset that includes 3 temperate lakes (Lake Erie, Lake Simcoe, and Eagle Lake) in Ontario, Canada, of varying size and trophic state. We report SOD (mean [standard deviation]; 0.30 [0.07] g m−2 d−1) and HOD (0.08 [0.03] g m−3 d−1) values based on regression fits of (where t is time) and H from these lakes. The model shows that when vertical (through thermocline) and horizontal fluxes can be neglected in the DO budget during summer, SOD and HOD are the first-order parameters driving . The empirical model predicted hypolimnetic DO in the 3 lakes (root-mean-square error [RMSE] of DO < 3.58 g m−3) and was subsequently validated against observations from a fourth lake (Little Silver Lake, Ontario; RMSE of DO = 1.07 g m−3). The model provides insight into the importance of physical characteristics (i.e., 1/H) in the hypolimnetic DO budget and the relative impact of physical transport versus biogeochemical sources and sinks in the DO budget. When the spring turnover DO concentration is known, the model can be used to simulate depletion of DO in the hypolimnion, including the onset of hypoxia, using routinely collected temperature profile data. We suggest that the proposed values for SOD and HOD can serve as estimates for water quality model calibration when no information is available.
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