Summer drought enhances diurnal amplitude of CO2 in two German rivers of different size

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2024-11-28 DOI:10.1016/j.watres.2024.122870
Peifang Leng, Michael Rode, Matthias Koschorreck
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Abstract

Drought is becoming increasingly prevalent globally, stimulating research into its effects on river ecosystems. However, our understanding of how droughts affect riverine CO2 dynamic on a daily scale remains limited, particularly considering the likelihood of future drought occurrence. Here, we seize the opportunity to compare daily CO2 cycles between a non-drought summer and an unprecedented drought summer. We developed a new diel CO2 process model to examine how droughts affect diel change in riverine CO2. Our findings reveal that summer drought amplifies diurnal CO2 fluctuations and the pattern holds true across rivers of varying sizes, with increases of 62% for the stream and 24% for the river during drought conditions. We demonstrate that, in comparison to higher radiation and temperature induced by droughts, diel amplitude is more sensitive to low water depths. A decrease in water depth by 43% and 44% corresponded to 13% and 25% less gas exchange in the studied stream and river, respectively, while decreasing ecosystem respiration by 26% and 57%. Our model effectively captures diel CO2 variations driven by drought considering river size, contributing valuable insights into aquatic ecosystem behavior and refining CO2 emission estimates. We emphasize the vulnerability of shallow rivers to drought, and carbon emissions from shallower waters should be explicitly assessed at sub-daily scales to improve the estimates of daily CO2 emissions.

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夏季干旱加剧了德国两条不同大小河流的二氧化碳日振幅
干旱在全球范围内日益普遍,激发了有关干旱对河流生态系统影响的研究。然而,我们对干旱如何影响河流二氧化碳日动态的了解仍然有限,特别是考虑到未来干旱发生的可能性。在此,我们抓住机会,比较了非干旱夏季和前所未有的干旱夏季的二氧化碳日周期。我们建立了一个新的昼夜二氧化碳过程模型,以研究干旱如何影响河流二氧化碳的昼夜变化。我们的研究结果表明,夏季干旱放大了昼夜二氧化碳波动,而且这种模式在不同大小的河流中都适用,在干旱条件下,溪流和河流的二氧化碳分别增加了 62% 和 24%。我们证明,与干旱引起的辐射和温度升高相比,昼夜波动幅度对低水深更为敏感。水深减少 43% 和 44% 相当于溪流和河流的气体交换量分别减少 13% 和 25%,同时生态系统呼吸作用分别减少 26% 和 57%。我们的模型有效地捕捉到了干旱导致的二氧化碳昼夜变化,同时考虑到了河流的大小,对水生生态系统的行为提供了有价值的见解,并完善了二氧化碳排放量的估算。我们强调浅水河流易受干旱影响,因此应明确评估较浅水域在亚日尺度上的碳排放量,以改进对日二氧化碳排放量的估算。
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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