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基于Matlab的大连地区突发水污染事件预报模型研究及应用
引用本文:孙大明. 基于Matlab的大连地区突发水污染事件预报模型研究及应用[J]. 水资源开发与管理, 2022, 0(3): 55-60
作者姓名:孙大明
作者单位:辽宁省大连水文局
摘    要:本文基于Matlab软件对大连地区独流入海的季节性河流污染物扩散进行模拟,并以挥发酚为例进行水污染动态时空可视化展示,结果发现:污染团在降解过程中随着水流向下游漂移,污染范围有所增加,但浓度也在不断降低,并且汛期污染物浓度降低与扩散范围远大于非汛期。对污染源下游1000m处应急入连取水口处污染物变化情况进行模拟。研究发现:该处污染物浓度变化为先增加后减少,并存在最大峰值,由此可得到此处污染物预警的开始与解除时间。该研究能够为山地丘陵地区季节性河流发生的水污染事故水质安全预警预报提供关键技术支撑,促进水生态友好和行业科技的进步,具有广阔的应用前景。

关 键 词:Matlab  大连地区  突发水污染事件  预报模型

Research and application of forecasting model of sudden water pollution events in Dalian based on Matlab
SUN Daming. Research and application of forecasting model of sudden water pollution events in Dalian based on Matlab[J]. WATER RESOURCES DEVELOPMENT AND MANAGEMENT, 2022, 0(3): 55-60
Authors:SUN Daming
Affiliation:(Liaoning Province Dalian Water Affairs Bureau,Dalian 116023,China)
Abstract:Based on Matlab, this paper simulates the pollutant diffusion of seasonal rivers flowing into the sea alone in Dalian, and takes volatile phenol as an example to display the dynamic spatio-temporal visualization of water pollution. The results show that: In the process of degradation, with the water flowing downstream, the pollution range increases, but the concentration is also decreasing, and the concentration reduction and diffusion range of pollutants in flood season is much larger than that in non-flood season. The change of pollutants at the water intake of emergency connection at 1000 m downstream of the pollution source was simulated. It was found that the concentration of pollutants in this area increased at first and then decreased, and there was a maximum peak, which could be used to judge the start and release time of pollutant early warning.The research can provide key technical support for the early warning and forecast of water pollution accidents in seasonal rivers in mountainous and hilly areas, promote the friendly operation of water ecology and the progress of industry science and technology, and have broad application prospects.
Keywords:Matlab  Dalian area  sudden water pollution incidents  forecasting model
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