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Modeling the mechanisms that control in-stream dissolved organic carbon dynamics in upland and forested catchments

机译:对控制高地和森林集水区流中溶解有机碳动态的机制进行建模

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摘要

We present a new, process-based model of soil and stream water dissolved organic carbon (DOC): the Integrated Catchments Model for Carbon (INCA-C). INCA-C is the first model of DOC cycling to explicitly include effects of different land cover types, hydrological flow paths, in-soil carbon biogeochemistry, and surface water processes on in-stream DOC concentrations. It can be calibrated using only routinely available monitoring data. INCA-C simulates daily DOC concentrations over a period of years to decades. Sources, sinks, and transformation of solid and dissolved organic carbon in peat and forest soils, wetlands, and streams as well as organic carbon mineralization in stream waters are modeled. INCA-C is designed to be applied to natural and seminatural forested and peat-dominated catchments in boreal and temperate regions. Simulations at two forested catchments showed that seasonal and interannual patterns of DOC concentration could be modeled using climate-related parameters alone. A sensitivity analysis showed that model predictions were dependent on the mass of organic carbon in the soil and that in-soil process rates were dependent on soil moisture status. Sensitive rate coefficients in the model included those for organic carbon sorption and desorption and DOC mineralization in the soil. The model was also sensitive to the amount of litter fall. Our results show the importance of climate variability in controlling surface water DOC concentrations and suggest the need for further research on the mechanisms controlling production and consumption of DOC in soils.
机译:我们提出了一种新的基于过程的土壤和溪流水中溶解有机碳(DOC)模型:碳综合集水模型(INCA-C)。 INCA-C是DOC循环的第一个模型,该模型明确包括不同土地覆盖类型,水文流动路径,土壤中碳生物地球化学和地表水过程对河流中DOC浓度的影响。只能使用常规可用的监视数据对其进行校准。 INCA-C模拟了几年到几十年间的每日DOC浓度。对泥炭和森林土壤,湿地和溪流的源,汇,固体和溶解有机碳的转化以及溪流水中的有机碳矿化进行了建模。 INCA-C设计用于北方和温带地区的天然和半天然森林和以泥炭为主的流域。在两个森林集水区的模拟显示,DOC浓度的季节和年际模式可以仅使用与气候相关的参数进行建模。敏感性分析表明,模型预测取决于土壤中有机碳的质量,土壤处理速率取决于土壤水分状况。模型中的敏感速率系数包括土壤中有机碳吸附和解吸以及DOC矿化的敏感速率系数。该模型还对垫料掉落量敏感。我们的研究结果表明了气候变化对控制地表水DOC浓度的重要性,并表明需要进一步研究控制土壤中DOC的产生和消耗的机制。

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