Rainfall possibly disturbs the diurnal pattern of CO2 degassing in the Lijiang River, SW China

被引:11
|
作者
Zhang, Tao [1 ]
Li, Jianhong [1 ]
Pu, Junbing [1 ]
Martin, Jonathan B. [2 ]
Wang, Sainan [1 ]
Yuan, Daoxian [1 ]
机构
[1] Chinese Acad Geol Sci, Inst Karst Geol, Key Lab Karst Dynam, MNR & Guangxi, Guilin 541004, Peoples R China
[2] Univ Florida, Dept Geol Sci, Gainesville, FL 32611 USA
基金
中国国家自然科学基金;
关键词
CO2; flux; Diel pattern; Precipitation; Water level; Karst river; DISSOLVED INORGANIC CARBON; HYDROCHEMICAL VARIATIONS; ISOTOPE FRACTIONATION; ATMOSPHERIC CARBON; PARTIAL-PRESSURE; FLUXES; KARST; DYNAMICS; DIOXIDE; STREAM;
D O I
10.1016/j.jhydrol.2020.125540
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Estimates of CO2 flux from rivers are uncertain due to limited measurements at high-resolution. In addition, precipitation may impact diurnal variation of riverine CO2 flux but the processes controlling those impacts are unknown. Here, we examine the diurnal characteristics of some physicochemical parameters, meteorological parameters, water level, delta C-13(DIC) values, and the CO2 emission flux at two transects (DM and PY) of a typical karst river (Lijiang River, LJR), southwest China, during May 13-16, 2017. Our results show significant correlations between CO2 flux, DO, pCO(2), and delta C-13(DIC) and reflect control of CO2 flux diel pattern (decreasing during daytime and increasing at night) by metabolic processes of aquatic plants. The amplitude of CO2 flux diel pattern is weakened at DM. In contrast, diurnal pattern are interrupted at PY by the precipitation, and afterwards controlled by water level due to the significant positive correlation between water level and CO2 flux. Certainly, this amplitude will return to prestorm values as the water level recovered. We suggest that effects of precipitation on regional CO2 efflux estimate require scaling water level and CO2 flux with a linear relationship, and converting hourly flux to daily flux (alpha values) to improve the estimate of CO2 flux diel cycle. These methods will optimize sampling monitoring strategies and provide more reliable estimates of regional riverine CO2 emissions.
引用
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页数:11
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