Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China; Department of Lake Research, Helmholtz Centre for Environmental Research-UFZ, 39114, Magdeburg, Germany.
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China; College of Resources and Environment, University of Chinese Academy of Sciences, 100190, Beijing, China.
Environ Pollut. 2022 Jun 15;303:119125. doi: 10.1016/j.envpol.2022.119125. Epub 2022 Mar 10.
Despite streams and rivers play a critical role as conduits of terrestrially produced organic carbon to the atmosphere, fluvial CO and CH are seldom integrated into regional carbon budgets. High spatial variability hinders our ability to understand how local and longitudinal controls affect underlying processes of riverine CO and CH and challenge the prediction and upscaling across large areas. Here, we conducted a survey of fluvial CO and CH concentrations spanning multiple stream orders within an agriculturally impacted region, the North China Plain. We explored the spatial patterns of fluvial CO and CH concentrations, and then examined whether catchment and network properties and water chemical parameters can explain the variations in both carbon gases. Streams and rivers were systematically supersaturated with CO and CH with the mean concentrations being 111 and 0.63 μmol L, respectively. Spatial variability of both gases was regulated by network properties and catchment features. Fluvial CO and CH declined longitudinally and could be modeled as functions of stream order, dissolved oxygen, and water temperature. Both models explained about half of the variability and reflected longitudinal and local drivers simultaneously, albeit CO was more local-influenced and CH more longitudinal-influenced. Our empirical models in this work contribute to the upscaling and prediction of CO and CH emissions from streams and rivers and the understanding of proximal and remote controls on spatial patterns of both gases in agriculturally impacted regions.
尽管溪流和河流作为陆源有机碳向大气输送的重要通道发挥着关键作用,但河流 CO 和 CH 很少被纳入区域碳预算。高空间变异性阻碍了我们理解局部和纵向控制如何影响河流 CO 和 CH 的潜在过程,并挑战了在大面积范围内进行预测和推广的能力。在这里,我们对华北平原受农业影响地区的多个流域等级内的河流 CO 和 CH 浓度进行了调查。我们探讨了河流 CO 和 CH 浓度的空间格局,然后检验了流域和网络特性以及水化学参数是否可以解释两种碳气体的变化。河流和溪流对 CO 和 CH 均呈超饱和状态,平均浓度分别为 111 和 0.63 μmol L。两种气体的空间变异性受网络特性和流域特征的调节。河流 CO 和 CH 沿程呈下降趋势,可用河序、溶解氧和水温的函数来模拟。这两个模型解释了约一半的变化,同时反映了纵向和局部驱动因素,尽管 CO 受局部影响更大,CH 受纵向影响更大。我们在这项工作中的经验模型有助于从溪流和河流中扩大和预测 CO 和 CH 排放,并有助于理解受农业影响地区两种气体空间格局的近端和远程控制。