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使用基于经验和过程的模型测试溪水溶解有机碳的季节性和长期控制因素。

Testing seasonal and long-term controls of streamwater DOC using empirical and process-based models.

作者信息

Futter Martyn N, de Wit Heleen A

机构信息

The Macaulay Institute, Craigiebuckler, Aberdeen, AB15 8QH, United Kingdom.

出版信息

Sci Total Environ. 2008 Dec 15;407(1):698-707. doi: 10.1016/j.scitotenv.2008.10.002. Epub 2008 Oct 30.

Abstract

Concentrations of dissolved organic carbon (DOC) in surface waters are increasing across Europe and parts of North America. Several mechanisms have been proposed to explain these increases including reductions in acid deposition, change in frequency of winter storms and changes in temperature and precipitation patterns. We used two modelling approaches to identify the mechanisms responsible for changing surface water DOC concentrations. Empirical regression analysis and INCA-C, a process-based model of stream-water DOC, were used to simulate long-term (1986--2003) patterns in stream water DOC concentrations in a small boreal stream. Both modelling approaches successfully simulated seasonal and inter-annual patterns in DOC concentration. In both models, seasonal patterns of DOC concentration were controlled by hydrology and inter-annual patterns were explained by climatic variation. There was a non-linear relationship between warmer summer temperatures and INCA-C predicted DOC. Only the empirical model was able to satisfactorily simulate the observed long-term increase in DOC. The observed long-term trends in DOC are likely to be driven by in-soil processes controlled by SO4(2-) and Cl(-) deposition, and to a lesser extent by temperature-controlled processes. Given the projected changes in climate and deposition, future modelling and experimental research should focus on the possible effects of soil temperature and moisture on organic carbon production, sorption and desorption rates, and chemical controls on organic matter solubility.

摘要

欧洲和北美部分地区地表水溶解有机碳(DOC)浓度正在上升。人们提出了多种机制来解释这些增加,包括酸沉降减少、冬季风暴频率变化以及温度和降水模式变化。我们使用了两种建模方法来确定导致地表水DOC浓度变化的机制。经验回归分析和INCA-C(一种基于过程的河流水DOC模型)被用于模拟一条小型北方溪流中河流水DOC浓度的长期(1986 - 2003年)模式。两种建模方法都成功模拟了DOC浓度的季节和年际模式。在两个模型中,DOC浓度的季节模式受水文控制,年际模式由气候变化解释。夏季气温升高与INCA-C预测的DOC之间存在非线性关系。只有经验模型能够令人满意地模拟观测到的DOC长期增加。观测到的DOC长期趋势可能由受SO4(2-)和Cl(-)沉积控制的土壤过程驱动,在较小程度上由温度控制的过程驱动。鉴于预计的气候和沉积变化,未来的建模和实验研究应关注土壤温度和湿度对有机碳生产、吸附和解吸速率以及对有机物溶解度的化学控制的可能影响。

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