低温低浊水质特性的分析

＠霍明昕￥吉林建筑工程学院＠刘馨远￥哈尔滨建筑大学我国北方广大地区有长达５～６个月的冰封期，水质长时间处于低温低浊状态。江河水温在０～１℃，水库水下层水温２～４℃；江河水浊度为５～３０ｍｇ／Ｌ，水库水浊度为５～１０ｍｇ／Ｌ。在冬季，水质的物理化学特性与其它...     

台风导致的水库原水水质突变及其应对措施

以宁波市某净水厂为例,研究了因台风导致的水库原水水质突变的过程,发现由台风引发的暴雨主要对水库原水的浊度、色度、氨氮、CODMn、铁、锰、微生物指标等产生影响,其中浊度是水质控制的重点;在强降雨开始对原水水质产生影响之后的36 h是水质控制的重点时间段,强化混凝是控制出厂水各项指标稳定达标的关键。     

金海水库冰封期水质研究及与夏季水质对比分析

针对冰封期水库水体具有独特特征及冬季市区供水存在异味问题,在2012年11月至2013年2月期间,对处于冰封期的呼和浩特市水源地金海水库的理化指标和浮游藻类进行了监测,并将其结果与夏季监测值进行了对比分析,得出了其变化趋势。结果表明:水库水质良好,但存在轻度污染;水体中共检测到浮游藻类6门24属27种,其主要优势种为绿藻、硅藻和隐藻;相关性分析表明叶绿素a(Chla)、总磷(TP)与浮游藻类数量呈正相关关系,而总氮(TN)则无明显的相关性,溶解氧(DO)和透明度(SD)均呈负相关关系;冰封期水体的理化指标与夏季的相比,高锰酸钾指数(CODMn)、TN和TP值较大,而Chla、pH和SD值略小;夏季的浮游藻类数量明显高于冬季,但不同的季节优势种类存在区别,由此可得冰封期水质较差与浮游藻类的种类和数量存在一定的联系。     

天津北塘水库淡水壳菜生境分析

针对2018年在北塘水库和某个以其作为水源的水厂首次发现淡水壳菜的问题,分析、对比了北塘水库的生境和水质特点。结果表明:在水库生境和外部环境的共同作用下,来水进入北塘水库后水质发生了变化,叶绿素含量和藻类计数明显升高,更加适合淡水壳菜的生长和繁殖,是其他水库和水厂并未发现淡水壳菜这一差异性存在的主要原因。北塘水库水的浊度、氯化物、总碱度、总硬度、叶绿素a和藻类计数,也显著高于另一个以长江水为水源的泵站前池水。     

地表水中浊度与高锰酸盐指数的相关性研究

CODMn是衡量水质受污染程度的一项重要指标,通过对地表水浊度和CODMn的检测,分析了浊度和CODMn之间的相关性。结果表明,浊度和CODMn之间的相关关系较不稳定,其中在丰水期呈现出较好的相关性,相关系数为0.775 9,在平水期和枯水期无相关性。在丰水期,出厂水的浊度去除率与CODMn去除率之间也具有相关性,此时可以通过降低浊度的方法降低CODMn,以保证出水水质。在枯水期和平水期,出厂水的浊度去除率与CODMn去除率之间无相关性,降低浊度后,CODMn的去除效果并不明显。     

聚硅酸铝铁(PSAF)混凝处理微污染原水中试试验研究

针对珠海市某水库水水质污染特征,采用聚硅酸铝铁(PSAF)作为混凝剂,通过小试试验和中试试验对其混凝效果进行研究。结果表明,PSAF对此水库水具有良好混凝沉淀效果,形成的絮体密实、沉降速度快、产生污泥体积小。对浊度的去除效果优于聚合氯化铝铁(PAFC),且远远优于聚合硫酸铁(PFS)、聚合氯化铝(PAC)。中试试验装置中,PSAF的最佳投加量为7mg/L,在此投加量下,滤前浊度去除率达到70.8%,滤后出水对浊度去除率达到94.6%。     

基于Elman神经网络的供水管网浊度预测研究

浊度作为反映供水管网水质变化的重要指标,建立水质模型对浊度进行预测有利于指导水质控制措施的实施.为了适应浊度监测数据的动态性,选用Elman神经网络构建浊度预测模型.对数据进行缺失值处理、异常值识别与处理、标准化和重采样后,构建浊度单指标、浊度-余氯多指标和浊度-压力多指标Elman神经网络对供水管网浊度进行预测和评价...     

台风引发的底泥扰动对水源水质的影响及保护建议

以水库水作为饮用水水源的宁波,在台风影响下水库水质污染类型复杂。通过对水库底泥和溪流底泥的对比研究发现,上游溪流底泥比水库底泥污染严重,溪流底泥中氨氮含量呈"表层低、底层高"分布;台风引发的上游溪流底泥扰动会引起水库水的浊度、氨氮、CODMn含量升高,水源水出现的污染与溪流底泥的扰动密切相关;水库底泥由于受到水源地良好的保护,受到扰动后,对上覆水水质的影响微弱;在台风影响下水源水出现的突发性铁污染与底泥扰动无关;为减弱上游流域底泥受到的潜在污染,可以在上游流域保护区内进行生态移民、退耕还林、建立生态缓冲带、关闭工业源等措施,防止各类污染物进入溪流底泥,从而减弱上游底泥在台风扰动下对水源水质造成的污染。     

城市饮用水水源水质的变化特性分析

从季节性差异分析了我国东北某城市两座水源地水库的浊度、CODMn氨氮、UV254三卤甲烷生成潜能(THMFP)、叶绿素a的变化规律.结果表明,B水库原水水质要好于A水库,两座水库原水浊度、有机物和三卤甲烷前驱物含量均呈季节性变化;A水库CODMn最高值为6.5 mg/L,最低值为2.8 mg/L;B水库CODMn最高值为5.0 mg/L,全年的最低值0.5 mg/L出现在3月;B水库叶绿素a在春夏之交变化较明显,A水库和B水库六个月内叶绿素a的平均值分别为36.53和22.25 mg/m3,UV254平均值分别为0.11和0.112 cm-1.     

基于智能分析的供水管网浊度模拟研究

在分析国内外供水管网水质研究现状的基础上,对管网水的浊度特性及演变规律进行了深入研究,总结了饮用水浊度指标在管网中的变化规律,并据此筛选出对管网水浊度变化影响较大的三方面因素,即流速、水龄、总铁含量.在对主要因素进行连续监测的基础上,运用MATLAB分别构建BP和RBF神经网络模型对管网水浊度进行模拟分析,结果表明模拟值与实测值吻合良好,RBF神经网络的非线性逼近能力更强,预测精度更高.     

基于贝叶斯方法的饮用水水质预测及可视化研究

在研究基于时间序列的贝叶斯水质指标预测方法的基础上,建立了基于贝叶斯方法的水质等级预测模型,同时利用济南市第二中学的样本数据对该方法与模型进行了有效性验证;在此基础上,对山东省黄河流域周围的8个主要大型水库进行了水质等级实例预测及可视化展示,为城市水质监管部门避免或减少饮用水污染提供了清晰直观、科学有效的技术途径。     

城市地表水体径流污染模拟分析:以苍海湖为例

在我国城市持续推进绿色发展理念的背景下,为科学支撑海绵城市规划编制工作,以梧州市苍海湖为研究实例,结合国内外相关研究经验和属地化的测量参数,应用InfoWorks ICM构建研究区水量水质数学模型。设计旱季和雨季两种模拟情景,分别对苍海湖汇水区内的污染物径流冲刷效应和湖体内污染物迁移扩散规律进行模拟分析,计算不同设计情景下地表污染物随雨水径流进入苍海湖及在湖内扩散的演进过程,并基于计算结果为苍海湖水动力条件改善、湖泊水质保护等提出工程指引建议,以期为水量水质数学模型在海绵城市规划中的应用提供参考。     

BP神经网络在水厂预测混凝投药量中的应用研究

建立了一种基于三层结构BP神经网络的混凝投药量前馈控制模型,采用烧杯试验数据进行了仿真验证,同时建立了传统的线性回归混凝投药量前馈控制模型,并采用两种模型基于同一样本数据进行仿真。从投药预测值一实际值的对比图和均方根误差等可以看出,BP模型优于回归模型,它通过学习可以根据原水水质进行投药量的有效预测,有一定的自适应性,实用性较强,但也存在一定的局限性,对某些水质的投药预测值还存在一定误差。     

Quantification and relative comparison of different types of uncertainties in sewer water quality modeling

Quantifiable sources of uncertainty have been identified for a case study of integrated modeling of a sewer system with a more downstream wastewater treatment plant and storage sedimentation tank. The different sources were classified in model input and model-structure-related uncertainties. They were quantified and propagated towards the uncertainty in the event-based prediction of sewer emissions (flow, and physico-chemical water quality concentrations and loads). Based on the concept of variance decomposition, the total prediction uncertainty was split into the contributions of the various uncertainty sources and the different submodels. Although the results strongly depend on the water quality variable considered, it is in most general terms concluded that the uncertainty contribution by the water quality submodels is an order of magnitude higher than that for the flow submodels. Future model improvement should therefore mainly focus on water quality data collection, which would reduce current problems of spurious model calibration and verification, but also of knowledge gaps in in-sewer processes.     

配水管网中细菌再生长的预测研究

管网中细菌的再生长及其所带来的问题日益得到了人们的关注和重视，为此以某高校的校园管网为研究对象，建立了细菌总数的预测模型。算例结果表明，线性回归模型对细菌再生长的预测结果不理想，但创新性地选用Logistic回归模型并结合主成分分析法则可对细菌总数（二分变量）的超标概率进行准确预测，当将模型判别概率设为0．85时其精度〉90％，满足水质预警的要求。     

The effect of a wildfire on stream water quality and catchment water yield in a tropical savanna excluded from fire for 10 years (Kakadu National Park, North Australia)

The wet/dry tropics of the Australian savannas are particularly prone to fire due to the highly seasonal rainfall and accumulation of grassy fuels. The effect of an early dry season wildfire (May, 1998) on the water quality of a seasonally flowing stream (December-June) was examined for a lowland savanna forest in Kakadu National Park (northern Australia) which had remained unburnt for 10 years. The water quality variables assessed were: total and volatile suspended sediment, phosphorus, nitrogen, iron and manganese. Compared to three years of pre-fire water quality data and 5 years of stream flow data, there was no detectable impact of the wildfire on the volume of stream flow, mean concentrations and the total mass transported by the stream for each water quality variable, except possibly nitrogen. The limited effect on water quality is attributed primarily to the timing of the wildfire and the low intensity relative to fires later in the dry season (September). The retention of canopy cover and the accumulation of leaf litter following the wildfire, and the catchment's gently undulating terrain all contributed to the negligible impact on water quality. Early dry season fires appear to be a viable management option for reducing accumulated fuel loads and hence reducing the risk of destructive wildfires later in the dry season.     

Water quality and uses of the Bangpakong River (eastern Thailand)

The Bangpakong River is the most important watershed in the Eastern part of Thailand. Water quality parameters were sampled from June 1998 through May 1999 at 11 sites along a 227 km gradient, covering the wet season (June-November) and the dry season (December-May). Surface water was collected at three different stations per site (close to the banks and in the middle of the river), and analyzed for temperature, dissolved oxygen, turbidity, suspended solids, pH. ammonia, fecal coliforms, biochemical oxygen demand and chemical oxygen demand as well as conductivity, phosphate, and heavy metals. The Scottish water quality index (WQI) was adaptated to the tropical environment. The averaged WQI was low (41%) and quality declined significantly during the dry season (ANOVA, p<0.001). Although the quality rose somewhat at middle sites, only 27% of the WQI values during wet season and 2.5% during dry season were higher than 50%, denoting poor environmental quality. Within each season, the main sources of variability were the differences between sites along the gradient (48% during the wet season, 63% during the dry season), whereas monthly variability represented less than 20% of the variability. The seasonal results show that the river is suitable only for tolerant fish and wildlife species and is of doubtful use for potable water supply during the dry season. As quality improves during the wet period, water can be used for the production of potable water, but only with advanced treatment, and for indirect and noncontact recreational activities. In the middle stretches of the river, higher water quality permits multiple uses at moderate cost.     

给水管网中细菌总数快速预测模型的建立与应用

对选定实际给水管网的水质进行了长期监测,研究了水质与细菌总数的相关关系,分析确定了与细菌总数相关性较高且易于测定的水温、自由余氯、总余氯、浊度及UV254等5项指标.应用多元线性回归分析建立了实际给水管网中细菌总数的快速预测模型.经验证,该模型预测的准确度为64.55%,能够用于实际给水管网中细菌总数的快速预测,可为保障供水管网水质微生物学指标的安全提供快速、可靠的技术支持.     

基于遗传优化神经网络的市政管网水质模型研究

将遗传算法的全局搜索能力和BP神经网络的局部学习能力有机结合,得到一种快速高效的建立供水管网余氯的水质模型的新方法。验证结果表明,遗传算法优化后的神经网络模型所需要考虑的参数较少,应用方便,预测精度和效率较高,在城市给水系统水质模拟预测研究中有一定的参考应用价值。     

不确定水质模型在城市河流水质模拟中的应用

鉴于城市景观河流受沿河排水污染,水质波动较大,建立了内嵌神经网络的一维不确定性水质模型,利用改进适应度函数的遗传算法,优化水质模型的参数解.经实例验证,不确定性水质模型拟合的精度更高,对排入污染物的波动更敏感,其对景观河流水质预测的平均准确度基本在80%以上,普遍高于确定性水质模型,尤其是在靠近污染源的监测断面,其不确...