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 $d\mathrm{D}\mathrm{O}/dt$ (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 $d\mathrm{D}\mathrm{O}/dt$. 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.

摘要

沉积物需氧量 (SOD) 和水下需氧量 (HOD) 导致湖泊中深水溶解氧 (DO) 耗竭，但这些参数可能难以常规测量。为了解决这个问题，我们根据下层 DO 和水柱温度剖面的时间序列测量提出了一个经验 DO 消耗模型，以估计下层厚度 ( H )。该模型基于一个数据集，该数据集包括加拿大安大略省的 3 个温带湖泊（伊利湖、西姆科湖和鹰湖），它们的大小和营养状态各不相同。我们报告基于回归拟合的SOD（平均值 [标准偏差]；0.30 [0.07] gm ^-2  d ^-1）和 HOD（0.08 [0.03] gm ^-3  d ^-1）值$d\mathrm{D}\mathrm{哦}/d吨$（其中t是时间）和来自这些湖泊的H。该模型表明，当夏季的 DO 预算中可以忽略垂直（通过温跃层）和水平通量时，SOD 和 HOD 是驱动$d\mathrm{D}\mathrm{哦}/d吨$. 经验模型预测了 3 个湖泊中的潜水溶解氧（DO < 3.58 gm ^{-3 的}均方根误差 [RMSE] ），随后根据来自第四个湖泊（安大略省小银湖；DO 的 RMSE = 1.07）的观测结果进行了验证gm ^-3 )。该模型提供了对物理特性重要性的洞察（即 1/ H) 的 DO 预算中，以及物理运输与生物地球化学源和汇在 DO 预算中的相对影响。当春季周转 DO 浓度已知时，该模型可用于使用常规收集的温度分布数据来模拟低水层中 DO 的消耗，包括缺氧的开始。我们建议，当没有可用信息时，SOD 和 HOD 的建议值可以作为水质模型校准的估计值。