Modeled Organic Carbon, Dissolved Oxygen, and Secchi for six Wisconsin Lakes, 1995-2014

This data package contains model output data, driving data, and supplemental information for a two-layer modeling study that investigated organic carbon and oxygen dynamics within six Wisconsin lakes over a twenty-year period (1995-2014). The six lakes are Lake Mendota, Lake Monona, Trout Lake, Allequash Lake, Big Muskellunge Lake, and Sparkling Lake. The model output includes daily predictions of six state variables: labile particulate organic carbon, recalcitrant particulate organic carbon, labile dissolved organic carbon, recalcitrant dissolved organic carbon, dissolved oxygen, and Secchi depth. The output also includes daily predictions of physical and metabolism fluxes that were used in the prediction of the state variables. This data package also contains model driving data for each lake and other supplemental information that was calculated during the modeling runs.

本数据集包含一项双层建模研究的模型输出数据、驱动数据与补充信息。该研究针对威斯康星州6座湖泊在1995-2014年的20年周期内的有机碳与氧动态开展了系统探究。这6座湖泊分别为门多塔湖（Lake Mendota）、莫诺纳湖（Lake Monona）、特劳特湖（Trout Lake）、阿莱夸什湖（Allequash Lake）、大马斯凯尔伦奇湖（Big Muskellunge Lake）与斯帕克林湖（Sparkling Lake）。模型输出涵盖6个状态变量的逐日预测结果：活性颗粒有机碳（labile particulate organic carbon）、难降解颗粒有机碳（recalcitrant particulate organic carbon）、活性溶解有机碳（labile dissolved organic carbon）、难降解溶解有机碳（recalcitrant dissolved organic carbon）、溶解氧（dissolved oxygen）以及塞氏深度（Secchi depth）。模型输出同时包含用于支撑上述状态变量预测的物理通量与代谢通量的逐日预测结果。本数据集还收录了各湖泊的模型驱动数据，以及建模运行过程中计算得到的其他补充信息。