滇池流域土地利用对入湖河流水质的影响

利用滇池流域2008年TM影像数据和入湖河流67个监测点的水质数据,以子流域为基本研究单元,从子流域综合分析和子流域分类分析两个角度,研究土地利用类型(国家分类标准)对入湖河流水质的影响.结果表明,21个子流域单元的水质污染指标(CODMn、TP、TN、NH3-N)与居民点及工矿用地呈显著正相关,与耕地、林地、草地呈负相关.对整个流域而言,城镇及工矿用地是入湖河流水质污染的主要来源,其污染贡献掩盖了耕地的贡献;根据土地利用结构和空间分布格局的差异,将滇池流域的21个子流域分为3类(城镇及工矿用地为主、耕地为主、林地为主).分类分析表明,水质污染指标与居民点及工矿用地始终呈现正相关,与林地始终呈现负相关.同时,讨论了土地利用空间格局差异对水质的影响,说明土地利用比例结构和分布格局对水质亦具有重要影响,     

太湖内源营养盐负荷状况及其对上覆水水质的影响

以太湖沉积物-上覆水界面为研究对象,于2013年夏季采集46个样点的沉积物柱状样,分析表层沉积物孔隙水中营养盐(正磷酸盐、氨氮、硝氮)的浓度空间分布,估算表层沉积物中磷、氮的扩散通量,明确营养盐在沉积物-水界面的分布规律,以探明内源营养盐负荷对太湖上覆水的污染贡献,并为沉积物-水界面氮磷的转移过程理论补充证据.结果表明:太湖西北部区域的表层沉积物孔隙水中正磷酸盐和硝氮浓度较高,分别达到1.11 mg·L~(-1)和1.25 mg·L~(-1)以上;大部分湖区的氨氮浓度超过2 mg·L~(-1).全湖区范围内,从表层沉积物的上覆水到孔隙水,氨氮含量呈现升高趋势而硝氮含量呈现降低趋势.北部3个湖湾区的沉积物营养盐扩散通量最高,正磷酸盐为2.69~4.60 mg·m~(-2)·d~~(-1),氨氮为17.8~45.7 mg·m-2·d~(-1),而湖岸河口区是沉积物硝氮内源释放显著的区域.沉积物向上覆水释放正磷酸盐和氨氮的年内源污染负荷分别为64.6 t·a~(-1)和1756 t·a~(-1);而上覆水向沉积物汇入硝氮的年负荷为1102 t·a~(-1).氨氮的内源污染负荷与外源污染负荷之比高达18.7%,氨氮、总磷和总氮内源污染为上覆水贡献的浓度分别为0.361、0.013和0.134 mg·L~(-1),表明自由扩散带来的内源负荷会使太湖水中营养盐污染恶化,需引起重视.     

温瑞塘河流域水体污染时空分异特征及污染源识别

不同季节主要污染物的空间分布特征及其潜在的污染源分析对水资源管理与污染控制具有重要意义.本研究应用GIS、主成分分析方法对2008-09~2009-10温瑞塘河水的温度、DO、电导率、p H、浊度、NH+4-N、NO-2、NO-3、PO3-4、Si O2-3、H2S、TOC、TN等水质参数进行时空分异特征分析和潜在污染源的识别.结果表明流域内丰水期、平水期、枯水期的典型污染物是TN、NH+4-N、PO3-4,主要来自于工业和生活点源;空间上水质污染程度是三级河道二级河道一级河道,无论几级河道市区的水质都劣于郊区和湿地;时间上水质污染程度是枯水期平水期丰水期;另外河道周边人口密度、土地利用类型及其调水对温瑞塘河的水质产生了不同程度的影响.     

密云水库上游流域不同尺度景观特征对水质的影响

选取北京市饮用水源地——密云水库上游流域为研究区,采用空间分析、冗余分析与多元线性回归等多种方法,识别不同空间尺度及季节变化下景观格局与水质的相关关系.研究结果表明,研究区河流水质与流域景观特征显著相关,景观变量能够解释水质变异的58%.子流域面积对水质的影响最大,其他影响变量依次为居民用地比例、林地比例及聚集度指数.季节性流量变化与人为活动的强度对景观与水质关系有很大的影响;雨季前景观对水质的影响最弱,雨季中景观对水质的解释能力最强,雨季后景观对水质的影响减弱,略大于雨季前.岸边带尺度景观对于水质的解释能力要大于流域尺度.通过比较50m,100m,150m,300m4个尺度岸边带景观对水质的影响,发现100m宽岸边带内景观与水质关系最为显著.研究结果对岸边缓冲带的设计及水污染的控制具有指导意义.     

应用蚕豆根尖细胞微核技术监测太湖水质的研究

应用蚕豆根尖细胞微核技术对太湖水质进行监测,测定太湖各样点水样的蚕豆根尖细胞微核千分率（MCN‰）及污染指数（PI）,并进行F检验。结果表明,各样点MCN‰有显著性差异,39个样点中有6个采样点的PI在2以上,和对照组相比有显著差异（p＜0.05）,表明太湖部分区域水质受到不同程度的污染。     

Composition analysis of colored dissolved organic matter in Taihu Lake based on three dimension excitation-emission fluorescence matrix and PARAFAC model, and the potential application in water quality monitoring

Taihu Lake is one of the five biggest lakes in China. Surface water samples from 26 sampling sites of Taihu Lake were collected. Furthermore wet chemical analysis （CODCr and BOD5） and measurement of three dimensional excitation-emission matrix （3DEEM） spectra in the laboratory have been conducted. Using parallel factor analysis （PARAFAC） model, three components of colored dissolved organic matter （CDOM） have been identified successfully, based on the analysis of 3DEEM data. The characteristics of the three components also have been described by comparing them to some components of CDOM, identified in earlier researches. Meanwhile, spatial variations of concentration for the three components in Taihu Lake have been analyzed, and the result indicates that the concentration of component 1 depends more on the situation of wastewater pollution and can be used as the indicator of wastewater pollution. The relationship between the concentrations of the three components and results of the wet chemical analysis show that none of the three components can be used as indicators of gross organic matter in water. However, the concentrations of all the three components have obvious linear relationships with the BOD5 value, especially for component 1 （r = 0.72878）. Finally, the potential applications of the composition analysis based on 3DEEM and PARAFAC model in water quality monitoring have been illuminated.     

Composition analysis of colored dissolved organic matter in Taihu Lake based on three dimension excitation-emission fuorescence matrix and PARAFAC model, and the potential application in water quality monitoring

Taihu Lake is one of the five biggest lakes in China. Surface water samples from 26 sampling sites of Taihu Lake were collected. Furthermore wet chemical analysis (CODCr and BOD5) and measurement of three dimensional excitation-emission matrix (3DEEM) spectra in the laboratory have been conducted. Using parallel factor analysis (PARAFAC) model, three components of colored dissolved organic matter (CDOM) have been identified successfully, based on the analysis of 3DEEM data. The characteristics of the three components also have been described by comparing them to some components of CDOM, identified in earlier researches. Meanwhile, spatial variations of concentration for the three components in Taihu Lake have been analyzed, and the result indicates that the concentration of component 1 depends more on the situation of wastewater pollution and can be used as the indicator of wastewater pollution. The relationship between the concentrations of the three components and results of the wet chemical analysis show that none of the three components can be used as indicators of gross organic matter in water. However, the concentrations of all the three components have obvious linear relationships with the BOD5 value, especially for component 1 (r=0.72878). Finally, the potential applications of the composition analysis based on 3DEEM and PARAFAC model in water quality monitoring have been illuminated.     

松花江哈尔滨段城市水环境质量评价

为了科学地对松花江哈尔滨段水环境质量进行评价,基于水环境功能区划,采用灰色关联度法将其分为4个区域,运用主、客观相结合的方法分区域建立相应的评价指标体系,使用模糊综合评价法进行水质评价,同时,验证指标体系构建的合理性.结果表明:构建的指标体系能够反映研究对象水环境质量;除阿什河口内水质评价结果为V类,达不到水环境功能区划要求外,其他区域水质均能达标.研究结果将有利于促进水资源的科学管理和有效利用,研究方法可为水环境质量评价提供新的思路.