风浪对浅水湖泊水质的影响机制

以太湖重要的浅水湖湾——东太湖为例,应用经典风浪经验公式,将风速转化为浪高,以直接体现风浪强度,在分析其与污染底泥卷起、水质指标相关关系的基础上,对风浪影响湖区水质的机制进行进一步探究。结果表明:随着风速、浪高的增加,水体浑浊度增加,偏北风作用下湖区浑浊度更高;DO的质量浓度呈降低趋势,全年浓度呈现冬季偏高而夏季偏低的规律;COD的质量浓度呈增加趋势,全年浓度呈现冬季偏高而夏季偏低的规律;TN的质量浓度与风速相关关系不明显,全年浓度呈现夏季偏高而冬季偏低的规律;浑浊度与COD存在较好的相关性。确定风浪对湖区水质的影响机制,旨在为针对性地制定湖泊水质改善措施提供技术支撑。     

浅水湖泊水质系统滤波模型

本文建立了浅水湖泊水质系统滤波模型和相应算法。根据滇池流场比较稳定等特点。对湖泊进行单元分区，考虑模型误差扰动和观测误差扰动的存在，建立系统的状态方程和观测方程，用吉尔（ＧＩＬＬ）算法求解微分方程，进行系统多点连续模拟和实时预报，用此法对滇池１９８８年的ＢＯＤ、ＣＯＤ时空变化进行连续预报，取得满意效果。     

泥沙污染水质模型研究综述

对现有的泥沙污染水质模型进行分类,总结了国内外泥沙污染基本问题及泥沙污染水质模型研究的成果,指出模型发展方面应加强泥沙与污染物相互作用机理研究,进一步揭示污染物在水体、悬浮泥沙、底泥之间迁移转化的机理,模型的建立应综合考虑污染物的沉降再悬浮、以及吸附解吸、底泥释放等动态过程。     

湖泊-河网耦合水动力水质模型研究

根据太湖地区水系复杂、湖泊众多、河道水流方向复杂多变且受到人为干扰的特征,基于一维河网水质模型,二维湖泊水质模型,采用有限控制体积法获得离散的水动力学和水质模型控制方程,通过河网与湖泊连接断面上河流的流量、水位、水质与湖泊的流速、水位和水质耦合求解,解决了河网湖泊水质模型的耦合,并将闸站控制对河流湖泊水动力水质影响过程进行了时间空间的线性化处理,以边界条件方式将闸站控制带入模型代数方程中进行统一求解,建立了适合于太湖流域的湖泊河网耦合水动力水质模型.采用太湖典型流域河网区2007年实测水文水质资料对耦合模型进行率定和验证.结果表明,模型计算值与实测资料吻合较好.该模型适用于复杂湖泊-河网区的水动力和水质变化的模拟和研究.     

浅水湖泊群连通与调水的二维水动力-水质藕合模型研究

将湖泊群连通并进行引清调水的水环境污染治理模式在浅水湖泊分布比较集中的地区逐渐受到人们的关注.为了探究独立湖泊群相互连通引水后各湖区的水动力水质变化情况,以武汉大东湖生态水网工程的建设为背景,建立了湖泊群二维水动力-水质耦合模型.采用适合复杂边界的非结构化网格,考虑湖底地形和气候条件,考虑污染物的输入、迁移和转化,以及蓝藻等浮游生物的生长条件,分别利用东湖2006年6月和2007年6月的野外数据对所建模型进行参数的率定和校核,并利用2012年6月实测数据对3种引水方案与3种连通模式组合情况下湖泊群的BOD5,TP,TN以及Chl-a等生化指标的变化情况进行模拟,对稳定运行30 d后的模拟结果进行比较分析.结果表明:引水工程中,对于水域面积较大的湖泊,风力作用依旧是影响流场的主要因素;同样的引水流量下,不同的调水方案对水质改善结果有较大差别;湖泊群中隔堤的存在会给湖泊污染治理带来困难,而在湖泊群中适当区域设置生态小岛对水质变化过程影响微弱.     

浅谈黄河泥沙与水质的关系

分析了黄河内蒙古段泥沙与水质之间的关系，对黄河内蒙古段水质监测和分析提出定性化描述和定量化指标，对全区水质监测和分析工作具有指导性作用。     

城市浅水湖泊水质模拟研究——以昆承湖为例

采用环境流体动力学模型(EFDC)对苏州市浅水湖泊昆承湖丰水期和枯水期水质进行模拟。结果表明,昆承湖COD高浓度带位于湖西部,东南部较低,主要受张家港河和莫城河2条入湖河道水体影响。湖西南部TP浓度较高;莫城河河道是导致昆承湖TP浓度较高的主要污染源。丰水期,NH4+-N高浓度区分布在湖西南部,莫城河河道水体对昆承湖NH4+-N浓度影响较大;枯水期,全湖西北部NH4+-N浓度较高,主要受张家港河河道水体影响。研究结果对昆承湖的水环境管理和环境综合整治有一定的参考价值。     

河流底泥冲刷沉降对水质影响的研究

河流底泥中含有大量的污染物质，是对水质影响的不可忽视的重要污染源，本文将环境水力学、泥沙运动学及水化学相结合进行研究，从水流中污染物的对流扩散方程出发，通过理论推导得到包括有底泥刷及沉降，底泥释放等因素的水质基本方程，通过实验确定方程中的有关因素，用实测资料验证，取得较好的结果，并付诸应用。     

内嵌神经网络的不确定水质模型研究

不确定水质模型研究是提高和认识水环境中各种不确定性因素常用的手段，目前水质不确定模型主要是增加一个外部观测量，通过对观测结果的回归分析或滤波来分析不确定性因素的影响。本文将神经网络内嵌到水质模型中，构成一个具有学习功能的不确定性水质模型，此模型能从内部感知各种不确定性因素的变化，实践证明此模型在对具有不确定性污染物排放的预测上具有较高精度。     

Three-dimensional modeling of sediment resuspension in a large shallow lake

We simulated bottom resuspension events in Lake Erie, using a coupled three-dimensional hydrodynamic and water quality model. Key parameters in the model, including critical bottom shear stress (${\tau }_{\mathit{cr}}$) and resuspension rate (α) were calibrated and validated by comparing the model output to observations. These included total suspended solid (TSS) concentrations in the bottom boundary layer (RMSE = 0.74 $\text{mg}{\text{L}}^{\text{-1}}$) and water column (RMSE = 0.81 $\text{mg}{\text{L}}^{\text{-1}}$), and to time series of acoustic backscatter signal (R² > 0.8) and turbidity (R² ≈ 0.4) from long-term moorings near the lakebed in 2008–09 and 2013. Signals from phytoplankton, in spring and summer, caused discrepancies between modeled TSS and the observed turbidity data. Although common practice, we show that literature-based or field-observed critical shear stress should not be directly applied in large-scale Reynolds-averaged sediment model as this will likely underestimate resuspension. In agreement with the literature, the model reproduced more frequent and intensive surface-wave driven resuspension in the shallow regions (< ~20 m), particularly in the western basin, compared to the deeper central and eastern basins, where bottom stresses induced by mean currents (${\tau }_c$) were comparable with those due to surface waves (${\tau }_w$). However, on the north-shore of the eastern basin, ${\tau }_c$ often predominated over ${\tau }_w$. We simulated thermocline motion, including up- and down-welling events and swashing of the internal Poincaré wave, to contribute to ${\tau }_c$ in the central basin and form nepheloid layers.     

Assessment of sediment quality of a tropical lake using sediment quality standards

Sediments are often reservoirs of contaminants in aquatic waterbodies, and their quality can be an indicator of the health of their ecosystems. Heavy metal pollution in sediments is highly significant because of their persistent and bioaccumulative nature. In this regard, sediment quality guidelines (SQG) are useful for categorizing sediment quality with respect to the contaminant level in them. An attempt was made in this study to assess the sediment quality of the Akkulam‐Veli (AV) Lake system on the basis of guidelines that incorporate assessment scales that differ in their approaches. Some link threshold levels of heavy metal concentrations on the basis of their likelihood to cause adverse effects, while others classify the sediment concentration ranges that correspond to the degrees of toxicity caused by them. The sediment quality of the study area was assessed by combining the available guidelines to formulate two new approaches in this study. Based on this approach, AV Lake is highly polluted with respect to chromium (Cr), nickel (Ni) and lead (Pb), while arsenic (As) and cadmium (Cd) are non‐polluting with a negligible potential for adverse effects.     

疏浚土排水固结过程中水质分析与污染性评价

为了分析疏浚淤泥排水固结过程中水质的污染特点,首先分析了土样的粒径组成及变化规律,了解其颗粒在渣场内的分选落淤特点,然后测试了水中各种有机、无机污染物的浓度及其变化过程。研究表明,疏浚土以粉粒、黏粒为主,比表面积大,吸附能力强;堆泥场内设置溢流堤、纵向隔堤,形成一定水头差的环形流道,从而有利于颗粒的落淤分选和污染物的吸附悬浮。水体、悬浮物和污染物等在负压抽吸作用下汇集进入排水管网而迁移排出。水质pH值变化很小,符合地表水质量标准;真空预压法可阻隔、过滤、吸附悬浮物、污染物,降低SS值,有利于氮的溶解、富集,总氮(TN)浓度变化不大;管道阻隔吸附、尾水沉淀、水生植物过滤等处治工艺对磷的溶解、吸附效果好,总磷(TP)减少,总溶解磷(TDP)增大,排放的余水中总磷(TP)未超湖、库Ⅲ类水质标准值;水质污染综合指数由基本合格提升为合格。     

阳澄湖入湖河道水质变化及污染物通量分析

分析阳澄湖主要入湖河道的近几年的水质状况,找出水质较差的几条河流以及主要的污染物指标,计算其入湖污染物通量,并进行趋势分析;比较分析外围进入准保护区的污染物通量和准保护区直接入湖的污染物通量的大小,找出污染物来源的主要区域及各河道各项污染物通量比重。结果表明:阳澄湖主要入湖河道水质无恶化趋势,基本维持在原有水平;阳澄湖西湖的主要入湖河道中,污染物通量主要来自里塘河;近5年准保护区直接入湖的总污染物通量大于外围入准保护区的总污染物通量;准保护区内NH3-N通量的年均增长率最大,是主要污染指标。     

Multivariate analysis of the sediment quality of a tropical coastal lake system

Accurate knowledge of sediment quality is essential because it affects the magnitude and trends of water quality constituents. There are only a few analyses of sediment quality characteristics using multivariate analysis tools. This study utilizes hierarchical cluster analysis (HCA), factor analysis (FA) and multiple regression analysis (MRA) to demonstrate the usefulness of these techniques to analyse sediment quality for Akkulam–Veli Lake, a tropical coastal lake system in Kerala, India. The variation of sediment quality patterns during the premonsoon (PRM), monsoon (MON) and postmonsoon (POM) periods were assessed with cluster analysis. Factor analysis was used to identify prominent factors influencing sediment quality, while the factors influencing heavy metal partitioning in the sediment and overlying water were identified using multiple regression analysis. The study results indicated the sediment in the upstream portion of the lake was polluted during PRM, with the prominent factors being the ‘heavy metal factor’ and the ‘organic pollution factor’, followed by the ‘phosphorus pollution factor’ and the ‘cadmium pollution factor’. The ‘heavy metal factor’ and the ‘organic pollution factor’ are the prominent factors during MON, whereas the ‘heavy metal factor’, ‘organic pollution factor’ and ‘salinity factor’ were prominent POM factors. The salinity of the overlying water above the sediments plays an important role during PRM and POM, whereas the dissolved oxygen content was important during MON.     

城市湖泊生态修复的水质响应研究

生态修复对遏制城市湖泊生态系统的退化意义重大,寻找一种有效且简单的生态修复效果预测方法有利于进一步推动湖泊修复研究的发展。利用综合污染指数法、基于专家调查法的湖泊污染物浓度确定方法及水质提升贡献度分析了生态修复的水质响应,并采用基于污染负荷平衡的水质模型预测了生态修复措施作用下的潜龙渠水质。结果表明:4种污染物浓度均有下降,潜龙渠水质提升显著,但各污染物对不同修复措施的响应程度不同,COD的浓度控制需要污染源控制与修复净化的共同支撑,TN对各项措施的敏感性接近,TP、NH_3—N分别对污染源控制、生态补水敏感性最高。情景预测表明,依据水质响应关系制定的生态修复方案,能够稳定保持潜龙渠的生态修复效果。     

基于模糊物元的湖泊水质评价模型研究

在模糊物元分析原理的基础上,结合水质评价的特点和海明贴近度的概念,提出了基于模糊物元分析方法的水质评价模型。在对水质进行综合评价时。分别把水质的分类等级和水样作为物元的事物,以它们的各项评价指标及其相应的模糊量值构造复合模糊物元,通过计算与理想模糊物元之间的海明贴近度,实现对水样水质的等级评价和水样排序。研究结果说明：该模糊物元模型简便、通用,计算结果较为客观和稳定,为水质综合评价提供了新的有效方法。