中山市2009年度生活饮用水水源水质卫生质量分析

目的通过对中山市城区和各镇区的生活饮用水水源水质卫生质量进行分析,了解并掌握中山市生活饮用水水源水质的卫生状况,为改善生活饮用水水质提供科学依据。方法采用定期抽样的方法,每季度对中山市城区和各镇区的生活饮用水水源水进行采样分析,分析的项目主要包括毒理指标(砷、镉、六价格、铅、汞、硒、氰化物、氟化物、硝酸盐、三氯甲烷、四氯化碳、三氯乙烯、四氯乙烯、马拉硫磷、对硫磷、甲基对硫磷、乐果、敌敌畏、苯、甲苯、二甲苯、乙苯、苯乙烯等)和一般化学指标(pH值、铁、锰、锌、铜、氯化物、硫酸盐、耗氧量、挥发酚类、阴离子合成洗涤剂等)。检测结果按《地表水环境质量标准》(GB3838-2002)中的Ⅱ类地表水(主要适用于生活饮用水地表水源地二级保护区)标准限值进行评价。结果分析生活饮用水水源水质共120份,所检项目全部达到国家《地表水环境质量标准》(GB3838-2002)中的Ⅱ类地表水标准的共73份,达标率为60.8%。未达标项目为氨氮、铁、锰、汞等,其余参与评价的检测项目均符合质量标准。结论中山市城区和各镇区的生活饮用水水源水超标指标集中在几个项目上,应引起相关部门的足够重视。

我国不同区域水源水拉森指数比较分析

目前远距离调水已经成为解决区域水资源不足的一项重要措施。但在水源切换时,切换前后水源水的腐蚀性如果存在显著差异,可能会因腐蚀加剧而出现"黄水"或"红水"现象。因此,了解不同区域、不同类型水源的腐蚀性差异,对于科学合理地进行水资源调配具有重要意义。拉森指数(LR)是目前评价水质对铁质管网腐蚀程度的常用方法。本研究以14个城市的26个水源水为研究对象,对模拟常规工艺处理后的滤后水进行了水质分析,并计算出其拉森指数。结果表明,相对于湖库水和地下水,河流水的拉森指数偏高,有44%的河流水拉森指数大于1,具有较强的腐蚀倾向。按区域分华东和中南地区、按流域分黄河和珠江流域的水源水拉森指数平均值大于1,水源切换条件下应关注其腐蚀性情况。

Water Quality Evaluation and Analysis on the Causes of Pollution for Groundwater Sources in Yantai, China

Based on the investigation for the 14 groundwater sources, the water quality of the groundwater sources had been analyzed, using the evaluation method of the combination of inorganic and organic index instead of the traditional method which was only based on inorganic index. The results showed that the quality of 12 groundwater sources satisfied class III standard of groundwater quality and other two exceeded class III standard. There were one groundwater source, whose water quality reached class 1 standard, and five groundwater sources, whose water quality reached class II standard. There were seven groundwater sources, in which the fluorine, an organic pollutant, was detected. The results showed that the groundwater resources in Yantai City were less polluted and the main pollutant in groundwater was nitrate. According to the analytical data and the environmental conditions of groundwater sources, the conclusion was drawn that the agriculture and rural non-point pollution were the main reasons of groundwater pollution.

Groundwater Quality Index Mapping for Gulbarga City, Karnataka State, India

The present work is aimed at assessing the water quality index （WQI） for the groundwater for Gulbarga city. The water quality index （WQI） is a mathematical instrument used to transform large quantities of water quality data into a single number which represents the water quality level. In fact, developing WQI in an area is a fundamental process in the planning of land use and water resources management. One can then compare different samples for quality on the basis of the index value of each sample. The present work relates to the development of water quality index for the study area based on the experimental results of physicochemical analysis of water samples. For calculating the WQI, the following 11 parameters have been considered, pH, TH, Ca, Mg, NO3, SO4, TDS, F, CI, K and Na. The WQI for these samples ranges from 10.40 to 155. Using developed indices, groundwater isopleth map has been prepared for study area. In the case study, the WQI map reveals that groundwater quality in two areas is extremely near to mineral water quality. Created index map provides a comprehensive picture that is easily interpretable for regional decision makers for better planning and management. The results of analysis have been used to suggest models for predicting water quality. The analysis reveals that the groundwater of the area needs some degree of treatment before consumption, and it also needs to be protected from the perils of contamination.

Analysis of Surface and Ground Water Exchange in Two Different Watersheds

Water regime of Albanian rivers is a Mediterranean typical one. During the wet period, it flows 85%-90% of the annual flow and the dry period represents only 10%-15% of the annual amount. In this paper the water regime of the Semani and Vjosa River is analyzed. These are two rivers with total different hydro-geological characteristics. Vjosa river watershed is mainly composed of massif calcareous rocks that are streaky and karstifled. A totally different view is in the other river, in Seman where the impermeable rocks dominate. Even the distribution of the precipitation is quite different. In the Vjosa River the amount of the precipitation varies from 1,500 mm to 2,500 mm per year and in Semani River only 1,100 mm per year. The flow in the wet period is mainly a result of the precipitation and the minimum discharge occurs during the dry period representing the base flow that is the contribution from the groundwater. In this point of view the flow in the dry period is also an indicator of the underground water resource. During the dry period the watershed gives what it received and what has cumulated during the wet period. This is more evident in the case of a karstic watershed. The recession curves were analysed for all the hydrometric stations in both river basins and the parameters of these curves are evaluated. These results are analyzed and compared between the two different watersheds reflecting the differences on water exchange of surface and ground water. Finally, an assessment of groundwater resources in both hydro geological basins is worked out.

Contribution of baseflow nitrate export to non-point source pollution

As a common pollutant of nitrogen in groundwater, nitrate contamination has become a major concern worldwide. Baseflow, one of the dominant hydrological pathways for nitrate migration to streamflow, has been confirmed as a leading nitrate source for stream water where groundwater or subsurface flow contaminated heavily by nitrate. That is, sufficient improvements of water quality may not be attained without proper management for baseflow, even if non-point sources(NPS) pollutants discharged through surface runoff are being well managed. This article reviews the primary nitrate sources, the main factors affecting its transport, and the methodologies for baseflow nitrate estimation, to give some recommendations for future works, including:(1) giving sufficient consideration for the effects of climatological, morphological, and geological factors on baseflow recessions to obtain more reliable and accurate baseflow separation;(2) trying to solve calibration and validation problems for baseflow loads determining in storm flow period;(3) developing a simple and convenient algorithm with certain physics that can be used to separate baseflow NPS pollution from the total directly in different regions, for a reliable estimation of baseflow NPS pollution at larger scale(e.g., national scale);(4) improving groundwater quality simulation module of existing NPS pollution models to have a better simulation for biogeochemical processes in shallow aquifers;(5) taking integrated measures of "source control", "process interception" and "end remediation" to prevent and control NPS nitrate pollution effectively, not just only the strict control of nutrients loss from surface runoff.