边界吸收条件下具有风效应的湿地流环境扩散

IF 1.3 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Journal of Earth System Science Pub Date : 2024-07-06 DOI:10.1007/s12040-024-02332-0
Buddhadeb Mondal, Krishnendu Barman, Bijoy S Mazumder
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引用次数: 0

摘要

湿地的特点是流动和环境分散,这在水管理系统中是必要的。在生物学和环境流体力学领域,湿地中的污染物迁移对保护鱼类和野生动物物种、防止水土流失以及休闲娱乐都有重要影响。当污染物瞬间释放到湿地中时,边界吸收和风都会对污染物的扩散过程产生重大影响。本研究强调了风效应和边界吸收对环境扩散的影响,以及在以宽度为主的水流中浅层湿地的平均浓度。研究考虑了多尺度时间段来确定扩散模型,说明污染物迁移过程受不同生态参数(如扩散时间、边界吸收、迂回度和植被阻力)的影响很大。结果表明,由于迂回和底部植被的影响,流向浓度分布与横向浓度分布几乎相同。值得注意的是,随着植被参数和迂回度的增加,污染物的全流浓度逐渐降低。不同风力下的流速分布由动量方程分析得出。讨论了边界吸收强度对全流和平均浓度的影响。此外,在风的作用下,边界吸收的浓度分布显然是复杂的。
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Environmental dispersion in wetland flow with wind effects under boundary absorptions

Wetlands are characterized by flow and environmental dispersion, which are necessary in the water management system. Contaminant transport in wetlands has a significant effect in the field of biology and environmental fluid dynamics for the conservation of fish and wildlife species, erosion prevention, and mainly recreation. When an instantaneous contaminant is released into a wetland, both boundary absorptions and wind have a significant impact on the contaminant dispersion process. The present study highlights the wind effects and boundary absorption on environmental dispersion and stream-wise mean concentration in a width-dominated flow for a shallow wetland. A multi-scale time period is considered to determine the dispersion model, which illustrates the contaminant transport process greatly affected by different ecological parameters like dispersion time, boundary absorption, tortuosity and vegetation drag. It is noted that the stream-wise concentration distribution is almost identical to the transversal concentration distribution due to tortuosity and bottom vegetation effect. It is noticed that the stream-wise concentration of contaminant gradually decreases due to the increase of vegetation parameters and tortuosity. The distribution of flow velocity is derived analytically from the momentum equation for different wind strengths. The effect of boundary absorption strength on stream-wise and mean concentration are discussed. Also, it is evident that the distribution of concentration is complex for boundary absorption under the effects of wind.

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来源期刊
Journal of Earth System Science
Journal of Earth System Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
3.20
自引率
5.30%
发文量
226
期刊介绍: The Journal of Earth System Science, an International Journal, was earlier a part of the Proceedings of the Indian Academy of Sciences – Section A begun in 1934, and later split in 1978 into theme journals. This journal was published as Proceedings – Earth and Planetary Sciences since 1978, and in 2005 was renamed ‘Journal of Earth System Science’. The journal is highly inter-disciplinary and publishes scholarly research – new data, ideas, and conceptual advances – in Earth System Science. The focus is on the evolution of the Earth as a system: manuscripts describing changes of anthropogenic origin in a limited region are not considered unless they go beyond describing the changes to include an analysis of earth-system processes. The journal''s scope includes the solid earth (geosphere), the atmosphere, the hydrosphere (including cryosphere), and the biosphere; it also addresses related aspects of planetary and space sciences. Contributions pertaining to the Indian sub- continent and the surrounding Indian-Ocean region are particularly welcome. Given that a large number of manuscripts report either observations or model results for a limited domain, manuscripts intended for publication in JESS are expected to fulfill at least one of the following three criteria. The data should be of relevance and should be of statistically significant size and from a region from where such data are sparse. If the data are from a well-sampled region, the data size should be considerable and advance our knowledge of the region. A model study is carried out to explain observations reported either in the same manuscript or in the literature. The analysis, whether of data or with models, is novel and the inferences advance the current knowledge.
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