典型农业流域河流和地下水CO2浓度时空变异

穆涛敏; 马凯月; 阮鹏; 谈欣睿; 邬建红; 张方方; 何圣嘉; 姜培坤

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中国环境科学 ›› 2025, Vol. 45 ›› Issue (7) : 3935-3943.

环境生态

典型农业流域河流和地下水CO₂浓度时空变异

穆涛敏¹, 马凯月¹, 阮鹏¹, 谈欣睿¹, 邬建红^1,2, 张方方¹, 何圣嘉^1,2, 姜培坤^1,2

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The temporal and spatiotemporal variation of CO₂ concentration in river and groundwater in typical agricultural watersheds.

MU Tao-min¹, MA Kai-yue¹, RUAN Peng¹, TAN Xin-rui¹, WU Jian-hong^1,2, ZHANG Fang-fang¹, HE Sheng-jia^1,2, JIANG Pei-kun^1,2

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摘要

于2023年10月~2024年9月在临安南苕溪上游流域定期开展常规水质及河流和地下水CO₂浓度监测,定量研究该地区河流水体、地下水CO₂浓度时空变异特征.结果表明:河流水体和地下水CO₂浓度均呈现显著的时间变化.在月尺度上,两者的峰值均出现于7月,但其最小值并不同步,分别出现在12月和1月;就季节尺度而言,河流水体和地下水CO₂浓度由高到低依次为:夏季＞春季＞秋季＞冬季.整体来看,地下水CO₂浓度均值高达(152.04±35.15)µmol/L,是河流浓度均值(33.24±6.19)µmol/L)的4.57倍,表明地下水是该地区水体CO₂排放一个重要的潜在“源”.农业活动密集区水体CO₂浓度(河流68.47µmol/L,地下水306.09µmol/L)与林地区域(河流20.64µmol/L,地下水73.93µmol/L)相比普遍较高,且河流和地下水CO₂浓度与农业相关水质指标(如TN、TP、DOC)均呈显著正相关(P＜0.01),而与DO、pH值和WT呈显著负相关(P＜0.01).基于多元线性回归方法,得到南苕溪上游流域不同土地利类型组合(面积占比)对该地区河流水体、地下水CO₂浓度的最佳影响半径分别为750m (R²=0.88)和1250m (R²=0.58).相关性分析结果表明,尽管在最佳影响半径内河流水体CO₂浓度与人居地相关性最强(r=0.90,P＜0.01),但地下水CO₂浓度变化更易受耕地占比的影响(r=0.83,P＜0.05).由此推断集约化农业生产可能是导致农业流域地下水CO₂的“富集”的一个重要原因,而CO₂浓度较高的地下水将成为临安南苕溪上游流域水体CO₂排放的一个重要来源.

Abstract

From October 2023 to September 2024, regular monitoring of water quality parameters and CO₂ concentrations in river water and groundwater was conducted in the upstream watershed of the Nantiao River in Lin’an, to quantitatively investigate their spatiotemporal variability. Results showed that both riverine and groundwater CO₂ concentrations exhibited pronounced temporal fluctuations. On a monthly scale, peak CO₂ concentrations in both river water and groundwater occurred in July, whereas the minima were temporally asynchronous, observed in December for rivers and January for groundwater, respectively. And seasonally, CO₂ concentrations in both river water and groundwater followed the order:summer ＞ spring ＞ autumn ＞ winter. Overall, groundwater CO₂ concentrations averaged (152.04 ± 35.15) µmol/L, approximately 4.57 times higher than those in river water (33.24 ± 6.19 µmol/L), indicating that groundwater may represent a significant potential source of aquatic CO₂ emissions in this region. CO₂ levels were markedly elevated in agricultural zones (river:68.47µmol/L; groundwater: 306.09µmol/L) compared to forested areas (river: 20.64µmol/L; groundwater: 73.93µmol/L). Significant positive correlations (P ＜ 0.01) were observed between CO₂ concentrations and agricultural-related water quality indicators (e.g., TN, TP, DOC), whereas negative correlations were found with DO, pH, and water temperature. Multiple linear regression revealed that the optimal spatial scales of land-use type combination influence on CO₂ concentrations were 750m for river water (R² = 0.88) and 1250m for groundwater (R² = 0.58). Within these spatial buffers, riverine CO₂ concentrations were most strongly associated with residential land cover (r = 0.90, P ＜ 0.01), while groundwater CO₂ was more influenced by cropland proportion (r = 0.83, P ＜ 0.05). These findings suggest that intensive agricultural activities may significantly contribute to CO₂ enrichment in groundwater, which in turn serves as an important source of aquatic CO₂ emissions in the upstream watershed of the Nantiao River in Lin’an.

导出引用

穆涛敏, 马凯月, 阮鹏, 谈欣睿, 邬建红, 张方方, 何圣嘉, 姜培坤. 典型农业流域河流和地下水CO₂浓度时空变异[J]. 中国环境科学. 2025, 45(7): 3935-3943

MU Tao-min, MA Kai-yue, RUAN Peng, TAN Xin-rui, WU Jian-hong, ZHANG Fang-fang, HE Sheng-jia, JIANG Pei-kun. The temporal and spatiotemporal variation of CO₂ concentration in river and groundwater in typical agricultural watersheds.[J]. China Environmental Science. 2025, 45(7): 3935-3943

中图分类号： X52

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