High-frequency dissolved organic carbon, nitrate, and total dissolved nitrogen from the Kuparuk River outlet near Toolik Field Station, Alaska, summer 2020-2021

Climate change is predicted to accelerate hydrologic cycle and amplify the release of carbon and nutrients from the permafrost landscapes of the Arctic. However, we have limited understanding of how seasonality and landscape characteristics influence hydrologic mobilization and transport of carbon and nutrients into Arctic river networks. To fill this knowledge gap, we assessed river carbon and nutrient dynamics across a lake-dominated. We deployed submersible, uv-visible optical sensors (V2 s::can uv-vis spectrophotometers) that quantify water chemistry at high frequencies at the outlet of the Oksrukuyik Creek watershed (72 square kilometers) near Toolik Field Station, on the North Slope of Alaska. We deployed the sensors continuously from June through August or September and optically determined absorbance spectra (220-700 nanometers), which were paired with grab samples to build calibration models to predict solute concentration using partial-least squares regression (PLSR). This data file includes these predicted high frequency concentrations of river chemistry data taken every ~15 minutes during the flow season post-freshet conditions. The data file includes date and time, and PLSR-calibrated dissolved organic carbon (DOC), nitrate (NO3), and total dissolved nitrogen (TDN) concentrations.

据预测，气候变化将加速水文循环（hydrologic cycle），并加剧北极多年冻土（permafrost）景观中碳与营养物质的释放。然而，目前学界对季节节律（seasonality）与景观特征如何影响碳、营养物质的水文活化过程及其向北极河网的输运机制仍缺乏充分认知。为填补这一认知空白，我们针对湖泊主导的流域开展了河流碳与营养物质动态特征评估。我们于阿拉斯加北坡图利克野外站（Toolik Field Station）附近的奥克斯鲁伊克溪流域（Oksrukuyik Creek watershed，面积72平方千米）出口处，部署了水下原位紫外-可见光学传感器（submersible uv-visible optical sensors），具体为V2 s::can紫外-可见分光光度计（V2 s::can uv-vis spectrophotometers），可高频量化水体化学组分。我们于6月至8月（或9月）连续部署该传感器，采集了220~700纳米波段的吸光度光谱（absorbance spectra），并与瞬时水样（grab samples）进行匹配，通过偏最小二乘回归（partial-least squares regression, PLSR）构建校准模型以预测溶质浓度。本数据集包含融雪春汛（freshet）后径流季节内，每约15分钟采集一次的高频预测水体化学组分浓度数据。数据集包含日期、时间，以及经偏最小二乘回归校准的溶解性有机碳（dissolved organic carbon, DOC）、硝酸盐（nitrate, NO3）和总溶解氮（total dissolved nitrogen, TDN）浓度数据。