水库群联合调度对饮用水源区水污染事件的影响

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
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引用次数: 0

摘要

为减少饮用水源区水污染事件的危害,探索可行的方法,本研究基于二维水质水量方程、地理信息系统(GIS)和数字高程模型(DEM),建立了饮用水源区水动力水质模型。研究选择了三峡库区的和尚山饮用水源区(HDWSA)作为研究区域,水中的代表性污染物为总磷(TP)。研究探讨了污染事件下各水文阶段 TP 含量的变化,比较了水库群联合调度前后 TP 浓度超标的持续时间和趋势。结果表明,TP 污染物的迁移速度从慢到快依次为:枯水期、退水期、蓄水期和洪水期。在污染事件条件下,各水相 TP 含量达到标准值所需的时间分别为 36 分钟(枯水期)、33 分钟(退水期)、30 分钟(蓄水期)和 27 分钟(洪水期)。联合调度组 1-3 缩短了达标所需时间,分别为 6-13 分钟(枯水期)、5-11 分钟(退水期)、4-9 分钟(蓄水期)和 3-7 分钟(洪水期)。联合调度前后 TP 浓度变化趋势呈现四个阶段:显著上升、急剧下降、快速下降、缓慢下降。在污染事件下,水库群联合调度可有效降低 DWSA 的 TP 浓度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Impact of joint dispatch of reservoir group on water pollution incident in drinking water source area

Impact of joint dispatch of reservoir group on water pollution incident in drinking water source area

To reduce the harm of water contamination incidents in drinking water source areas (DWSAs) and explore feasible approaches, the research developed a hydrodynamic water quality model for DWSAs based on two dimensional water quality and quantity equations, Geographic Information System (GIS), and Digital Elevation Model (DEM). The Heshangshan Drinking Water Source Area (HDWSA) in the Three Gorges Reservoir Area (TGRA) was selected as the research area, with total phosphorus (TP) as the representative pollutant in the water. The research investigated the changes in TP content during various hydrological phase under pollution incident, compared the duration and trends of TP concentration exceeding standard value before and after joint reservoir group dispatch. The results showed that the migration speed of TP pollutants varied from slowest to fastest in the following order: dry phase, recession phase, storage phase, and flood phase. Under pollution incident condition, the time demanded for TP content to meet standard value in each water phase was 36 min (dry phase), 33 min (recession phase), 30 min (storage phase), and 27 min (flood phase). The joint dispatch group 1–3 shortened the time required to meet standard value by 6–13 min (dry phase), 5–11 min (recession phase), 4–9 min (storage phase), and 3–7 min (flood phase). The trend of TP concentration before and after joint dispatch showed four stages: significant increase, sharp decrease, rapid decrease, and slow decrease. Joint dispatch of reservoir group can effectively reduced the TP concentration in DWSA under pollution incident.

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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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