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1.
平顶山市湛河水污染现状及防治对策   总被引:2,自引:0,他引:2  
以“九五”期间平顶山市湛河水质例行监测结果为依据,分析了湛河水污染现状、特征及原因,并提出综合性湛河污染防治对策。  相似文献   

2.
开展国家水环境质量预报预警工作是生态环境治理能力现代化的重要部分,是统筹山水林田湖草系统治理的重要抓手。文章介绍了国内外水质模型的研究进展,并概述了国内外水质预报预警系统研究进展,在此基础上分析目前我国水质预报预警方面存在的不足,并提出了国家水环境质量预报预警业务发展的初步思路。我国水质预报预警体系建设要以技术体系和业务体系为保障,以水质模型和面源污染模型为支撑,依托水环境质量预报预警决策支持平台,开展环境监管业务化应用、治理决策精细化支撑、污染事故科学化处置和数据产品社会化服务4种业务应用,逐步建成架构统一、业务协同、资源共享、上下游联动的全国-流域-省级-城市四级水环境质量预报预警网络。  相似文献   

3.
通过对五里湖,梅梁湖水质近5年(1989-1993)每年6次的监测资料分析,五里湖为(4-5)类水质的水体,属重营养化水体,梅梁湖为4类水质的水体,属富营养化-重营养化水体,近几年来富营养化程度在加剧,范围在扩大,通过五里湖,梅梁湖富营养伦原因分析以及水质在分析,提出了五里湖-梅梁湖水污染防治措施。  相似文献   

4.
介绍了由数据采集与传输子系统、数据库子系统、水质预警预报子系统、数据输出子系统和人机交互界面组成的南水北调中线工程输水干线的水质监测管理信息系统,根据该系统的实际需求,阐述了开发该系统应该具备的关键技术。  相似文献   

5.
介绍了大气污染气象潜势预报方法和兰州市大气污染气象潜势预报系统。通过2001年9-12月兰州市空气质量预报检验分析,表明该系统对首要污染物等级预报准确率在60%以上,对兰州空气质量预报具有较好的指示性。  相似文献   

6.
利用1990-1995年水源地水质监测资料,运用数理统计方法,研究了水源地水质现状及分布类型,定量分析了水质指标时间分布特征及变化趋势,最后提出了水源水质良好,未受到严重污染。  相似文献   

7.
塔里木河流域水质变化趋势分析   总被引:1,自引:0,他引:1  
应用季节性肯达尔非参数检验方法,对塔里木河干流及三大源流1992-1998年间的水质变化趋势进行了分析检验,客观、定量地描述了塔里木河的水质变化动态,对于进一步掌握塔里木河的水质变化有着重要意义。  相似文献   

8.
执行GB 3838- 2002《地表水环境质量标准》的思考   总被引:3,自引:0,他引:3       下载免费PDF全文
指出GB3838-2002《地表水环境质量标准》的内容与GHZB1-1999《地表水环境质量标准》相比有了较大的改动;适用范围增加了具有特定功能的水域,执行相应的专业用水水质标准,标准项目由75项增加至109项,突出了对集中式饮用水源地水质的保护;基本项目标准限值的变化体现Ⅰ、Ⅱ、Ⅲ类水从严,其余放宽,少数几项指标从严,总体放宽的原则。分析了GB3838-2002《地表水环境质量标准》水质评价和水质监测的内容,提出环境监测站应关注该标准中水质监测变化的内容。  相似文献   

9.
洪泽湖富营养化与环境理化因子间的关系   总被引:6,自引:1,他引:6       下载免费PDF全文
利用淮安市环境监测中心站1998年—2000年洪泽湖水质监测资料,以洪泽湖水体最能表征营养化状态进程的叶绿素a为基准因子,分析了洪泽湖水质富营养化的原因。通过QBASIC多元逐步回归分析,得出洪泽湖水质富营养化的主控因子是悬浮物、透明度,总磷是富营养化的潜在限制性营养盐。  相似文献   

10.
水质综合评价的B—P网络模型   总被引:5,自引:0,他引:5  
为探索人工神经网络用于水质综合评价的可能性,提出了基于B-P算法的人工神经网络水质综合评价模型。实例研究表明,B-P网络模型用于水质综合评价简便实用,具有客观性和通用性。  相似文献   

11.
Belgaum city is a developmental hub of Karnataka State in India. In the recent time, the Government of Karnataka has planned to set up many processing industries in the vicinity of Belgaum to meet the growing needs of the region and to ease out the pressure on the already existing industrial hubs in Karnataka State. Ghataprabha, a tributary of river Krishna, is one of the major sources of water supply to Belgaum city and adjoining areas. During the last decade, a lot of anthropogenic activities such as unplanned agricultural activities are ongoing in many parts of the catchment. Therefore, people of Belgaum are more concerned about the quality of water in Ghataprabha river. Considering the significance of water quality of the river, surface water samples were collected during Pre- and Post-monsoon season from selected locations and analyzed for both physical and chemical constituents in the laboratory. The results indicate that the chemical parameters such as bicarbonates, sulphates, chlorides, sodium, potassium, calcium and magnesium are within the permissible limits. QUAL2E model was applied to assess the impact of point and non-point sources of pollution on the river water quality. Results show that the water quality conditions are highly acceptable all along the river stretch. Further, the variation of DO–BOD5 with river discharge was also estimated. Also, a significant variations in DO (decrease in DO) with the increase in river flow was observed. However, at the downstream end, considerable improvement in DO was noticed which is attributed to the damming effect of the reservoir.  相似文献   

12.
深圳市河流水质评价指标筛选方案探讨   总被引:4,自引:0,他引:4  
通过计算各条河流的综合污染指数和各项水质指标的污染分担率,对深圳市8条主要河流1999—2008年水质监测数据进行分析,最终从15项常规水质指标中筛选出氨氮、总磷、生化需氧量、化学需氧量、高锰酸盐指数、石油类、挥发酚、硫化物和六价铬9项指标,建议作为深圳市河流水质评价的统一指标。  相似文献   

13.
城市内河流水质监测点位的优化,是全面掌握河流水质状况的关键。文章采用贴近度法对萍乡市萍水河2005—2015年水质及监测点位变化进行分析评价,并提出优化建议。根据萍水河水质污染特征,选择化学需氧量、五日生化需氧量、氨氮、总磷、总氮和高锰酸钾盐指数作为评价指标,结果表明:2005—2015年,萍水河水环境质量整体情况较好,但在2010年后呈下降趋势;监测点布设方案的调整有一定合理性,也有欠妥之处;对目前监测点位进行删减,得到了水质优化监测布点方案。  相似文献   

14.
新疆地表水水质现状分析   总被引:2,自引:0,他引:2  
以2008年新疆环保系统的水质例行监测结果为基础,分析了新疆地表水水质现状。结果显示,全疆57条监测河流Ⅰ~Ⅲ类优良水质断面比例为81.9%,29座监测湖库Ⅰ~Ⅲ类优良水质比例为55.2%,总体上全疆地表水污染尚不严重,水质污染主要集中在少数流经城市河流的下游河段以及尾间湖和纳污水库,且不同区域间的水体污染程度和比例存在一定差别。  相似文献   

15.
Both climatic and non-climatic factors affect surface water quality. Similar to its effect across various sectors and areas, climate change has potential to affect surface water quality directly and indirectly. On the one hand, the rise in temperature enhances the microbial activity and decomposition of organic matter in the river system and changes in rainfall alter discharge and water flow in the river ultimately affecting pollution dilution level. On the other hand, the disposal of organic waste and channelizing municipal sewage into the rivers seriously worsen water quality. This study attempts to relate hydro-climatology, water quality, and impact of climatic and non-climatic stresses in affecting river water quality in the upper Bagmati basin in Central Nepal. The results showed that the key water quality indicators such as dissolved oxygen and chemical oxygen demand are getting worse in recent years. No significant relationships were found between the key water quality indicators and changes in key climatic variables. However, the water quality indicators correlated with the increase in urban population and per capita waste production in the city. The findings of this study indicate that dealing with non-climatic stressors such as reducing direct disposal of sewerage and other wastes in the river rather than emphasizing on working with the effects from climate change would largely help to improve water quality in the river flowing from highly populated urban areas.  相似文献   

16.
Narmada is considered to be the lifeline of the state of Madhya Pradesh in Central India. The Narmada water is used for bathing, drinking, irrigation and industrial purposes. The city sewage and industrial effluent from Security paper mill at Hoshangabad drains in the Narmada River and pollutes the water quality. Urban sewage enters into Narmada through main nallas. River water quality at Hoshangabad has become a matter of concern due to continuous changing environment and increasing social and industrial activity that influence the water quality directly or indirectly. The present investigation is undertaken to study the effect of domestic sewage and effluent from Security paper Mill on the water quality and ecology of river Narmada at Hoshangabad. The study is carried on at four sites along with the bank of river Narmada. Water samples from four stations were collected, out of which three main sewage mixing points of the city and one fresh water site are taken into account. The samples collected were analyzed, as per standard methods parameters such as Temperature, pH, were measured in-situ. The statistical evaluations were also made. The result showed increase in BOD, Nitrates, Phosphates and Total Coliforms, No. of phytoplanktons. The results revealed that most of the water samples were below or out of limited; according to the WHO, BIS standards.  相似文献   

17.
根据丹江口库区及其上游河流5个区域42个断面2012-2013年的水质监测数据,采用主成分分析法确定主要污染因子及权重,对不同流域的水质进行综合评价。第一主成分包括总氮、溶解氧、五日生化需氧量、总磷、氨氮、高锰酸盐指数,第二主成分为氟化物、粪大肠菌群,第三主成分为化学需氧量;其权重分别为5.022,2.256,1.508。评价结果表明,湖北十堰市和丹江口市流域水环境污染相对较重,其次为河南南阳市、陕西商洛市、陕西安康市以及陕西汉中市流域。  相似文献   

18.
The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.  相似文献   

19.
The usefulness of water quality indices, as the indicators of water pollution, for assessment of spatial-temporal changes and classification of river water qualities was verified. Four water quality indices were investigated: WQI (considering 18 water quality parameters), WQI(min) and WQI(m) (considering five water quality parameters: temperature, pH, DO, EC and TSS) and WQI(DO) (considering a single parameter, DO). The water quality indices WQI(min), WQI(m) and WQI(DO) could be of particular interest for the developing countries because of the minimum analytical cost involved. As a case study, water quality indices were used to evaluate spatial and temporal changes of the water quality in the Bagmati river basin (Nepal) for the study period 1999-2003. The results allowed us to determine the serious negative effects of the city urban activity on the river water quality. In the studied section of the river, the water quality index (WQI) was 71 units (classified as good) at the entry station and 47.6 units (classified as bad) at the outlet station. For the studied period, a significant decrease in water quality (mean WQI decrease = 11.6%, p = 0.042) was observed in the rural areas. A comparative analysis revealed that the urban water quality was significantly bad as compared with rural. The analysis enabled to classify the water quality stations into three groups: good water quality, medium water quality and bad water quality. WQI(min) resulted in overestimation of the water quality but with similar trend as with WQI and is useful for the periodic routine monitoring program. The correlation of WQI with WQI(min) and DO resulted two new indices WQI(m) and WQI(DO), respectively. The classification of waters based on WQI(m) and WQI(DO) coincided in 90 and 93% of the samples, respectively.  相似文献   

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