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浑河流域抚顺段水污染自动监测预报和应急处理研究

Study on Automated Monitoring, Forecasting and Emergency Disposal of Water Pollution in Fushun Section of Hun River Basin

【作者】 张丽

【导师】 杨国范; 刘玉机;

【作者基本信息】 沈阳农业大学 , 农业水土工程, 2013, 博士

【摘要】 水体污染给人们的生活和工农业生产带来严重的危害,已经成为制约我国社会经济可持续发展的重要因素。由于各种历史和现实原因,我国生态环境恶化与环境污染问题难以得到有效控制,突发环境污染事件进入高发期,突发水污染事件在各类突发环境污染事件中是发生频率最高的。浑河是贯穿辽宁省中东部地区的著名河流,全长368km,又被称为沈水、小辽河。浑河经过辽宁中部的城市地带,这里是传统的重工业区,人口密集,大量的城市废水被排放到其中。同一河流几十公里之内就流经两座或几座城市,上游城市排放的污染物还没有完全净化干净,就进入到了下游城市,又会排入大量的废水,从而加剧了环境污染,水污染及其测报应急处理问题亟待解决,尤其在信息获取与发布、应急机制、应急监测、应急系统组织等方面。针对存在的问题,选取我国浑河流域抚顺段来进行系统的研究,开发自动化测报系统和应急处理措施研究。本研究采用计算机技术、通信网络技术和“3S”(GIS、GPS、RS)技术,分析浑河流域抚顺段水污染情况,结合水质模型,针对目前我国浑河流域抚顺段水污染的突出问题及水污染事故进行模拟预测;分析在水源区域内工业开发对区域环境,尤其是对区域内的饮用水源地敏感目标的环境影响和潜在风险,识别出区域环境风险的主导因子。建立浑河流域抚顺段水污染自动化测报和应急处理的应用系统,为水环境安全管理提供服务。本文主要的研究成果如下:(1)对浑河流域抚顺段主要污染源及污染趋势进行分析,浑河污染源主要来自两岸工业和生活排污口、市政管网污水溢流口和浑河市区段主要支流河排入的污水。在浑河流域抚顺段主要27个污染源中,抚顺钢厂和腈纶化工厂排污量最大。(2)通过地面监测与卫星遥感监测相结合的方法,对浑河流域抚顺段污染水体进行遥感定量反演。利用遥感卫星Landsat ETM+波段对浑河抚顺段水污染进行监测研究,分析水体中的化学需氧量、高锰酸盐指数、挥发酚和氨氮等污染物与遥感波段之间的关系,建立遥感波段与水质参数之间的关系方程。研究表明,对水体中的化学需氧量、高锰酸盐指数、挥发酚和氨氮等污染物,遥感监测效果较好的Landsat ETM+波段是蓝绿波段、绿色波段、热红外和中红外波段,得到了该地区各波段灰度值与污染物之间的反演模型。(3)利用QUAL2K模型,以浑河流域抚顺段支流苏子河为例,选用NH3-N、COD和BOD水质参数进行模拟。结果表明,模拟误差均在10%以内,能够达到模型精度的要求;对苏子河水质参数摸拟精度最高的是NH3-N,平均相对误差为4.25%,其次是BOD和COD,平均相对误差分别为6.17%和6.18%;对苏子河中游模拟误差最大,而下游的入河口模拟误差最小。QUAL2K模型能够较好的模拟浑河流域苏子河河段水质状况。(4)利用组件式GIS及ArcGIS Engine技术,设计与开发了“浑河流域抚顺段水污染事故监控系统”和“浑河流域抚顺段水污染事故应急处理决策支持系统”,实现了集水污染事故监测、查询和决策为一体的监控系统。这两个系统具有一定的开放性、具有技术先进、结构简单、可靠性高、运行稳定和较高的多系统适应性等特点,能够及时掌握水体动态变化状况,发布事故动态变化信息,进行水源状况评测和物资调度,为及时采取应急处理措施提供帮助。

【Abstract】 Water pollution does harm to people’s lives and agricultural production, and it has become an important factor restricting sustainable social and economic development of China. Due to a variety of historical and practical reasons, the deterioration of ecological environment and environmental pollution problems can not be effectively controlled, and the risk of sudden environmental pollution incidents is increasing. Among all kinds of unexpected environmental pollution incidents, sudden water pollution incidents occurred most frequently. Hun River, also known as Shenshui and small Liao River, is368km in length, and it is a famous river which runs through the eastern part of Liaoning Province. Hun River goes through urban area in the middle of Liaoning Province which is the traditional heavy industrial area with dense population, and a large amount of urban waste water is discharged into it. Within tens of kilometers section of the river, it flows through two or several cities. Pollutant emissions in the river from upstream cities have not been yet fully purified, the river enters into the downstream cities. So, a large amount of waste water will be discharged into river again, and the phenomenon will aggravate environmental pollution. Water pollution and forecasting emergency problems need to be solved, especially problems about the acquisition and announcement of information, emergency mechanism, emergency monitoring and the organization of emergency response system. In order to address these problems, we select Fushun section of the Hun River Basin as research objective, and carry out study on its development of automated forecasting systems and emergency measures. In this study, computer technology, communication and network technology, namely "3S"(GIS, GPS, RS) technology was used to analyze the pollution in Fushun section of Hun River Basin, and simulated and predicted its outstanding issues and water pollution accident combined with the water quality model. Also, environmental impact and potential risks in regional environment especially in drinking water sources come from industrial development were analyzed, and dominant regional environmental risk factors were identified. Finally, automated forecasting and emergency response system of Fushun section of Hun River were established to provide service for safety management of water environment. The major study results are as follows.(1) The main sources of pollution and pollution trends of Fushun section of Hun River Basin were analyzed, and the results indicated that pollution mainly came from cross-strait industrial and domestic sewage outfall, municipal sewage overflow and sewage from main tributaries. Among27of the main sources of pollution, Fushun Steel Factory and Acrylic Chemical Company are the largest sewage emission producers.(2) Water pollution remote sensing quantitative inversion of Fushun section of Hun River Basin was carried out according to ground monitoring combined by satellite remote sensing. ETM band segment of remote sensing satellites Landsat was used to monitor water pollution of Fushun section of Hun River, and analyze the relationship between COD, permanganate index, ammonia, volatile phenols and remote sensing band in order to establish equations about the relationship between remote sensing band and water quality parameters. For the COD, permanganate index, volatile phenol and ammonia, blue-green, green, thermal infrared and mid-infrared band were the good bands to acquire better remote sensing monitoring results, and inversion model of gray value and pollutants in each bands was acquired.(3) Using QUAL2K model, water quality parameters such as NH3-N%COD and BOD was used to simulate the pollution in Suzi River, the tributary of Fushun section in Hun River. The results indicated that simulation error was less than10%, and it was enough to meet the accuracy requirement of the model. Water quality parameter NH3-N was the best one to acquire highest simulation accuracy of Suzi River, and its average error was4.25%, followed by BOD and COD, and the average relative error was6.17%and6.18%respectively. Maximum simulation and minimum error occurred in middle section of Suzi River and downstream estuaries respectively. In brief, QUAL2K model could well simulate the changes of water quality in Suzi River.(4)"The monitoring system for water pollution accidents of Hun River Basin in Fushun city" and "the emergency decision support system for water pollution accidents of Hun River Basin in Fushun city" were developed using the component-based GIS and ArcGIS Engine technology, and the two systems could provide accident monitoring, query and decision-making functions. Both systems are characterized by openness, advanced technology, simple structure and high reliability as well as multisystem adaptability. They are able to monitor the dynamic changes in water quality, announce information about dynamic changes of accident, carry out water conditions and material evaluation and provide helpful and timely emergency measures.

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