浙江省水质站测点布设及采样频次的优化分析

本文运用数理统计方法，确定了浙江省水质站位测点及采样频次的优化方案并进行了验证，达到了使用最经济的手段获取最具代表性和可靠性的水质监测数据的目的。     

基于SWMM和MIKE11的城市河流水质动态模型构建及应用

为了对城市河流水污染治理提出精细化控制建议，科学合理地制定流域水环境综合治理措施，以茅洲河为研究对象，基于Visual Studio开发SWMM与MIKE11的耦合程序，采用映射配置文件将两个模型的空间拓扑关联，构建了城市河流水质动态模型，并在模型率定验证的基础上将其应用于流域水质情势预测。结果表明：城市河流水文-水动力-水质耦合模型具有较好的模拟能力和适应性，可用于类似流域水质动态模拟、预测及评估。     

基于变权物元的改进可拓评价法在输配水工程水质评价中的应用

合理的水质评价方法是城市输配水工程中水质综合评价的关键。文章采用改进变权物元可拓评价法和敏感分析法,利用2015年沈阳输配水工程中东配水厂、西配水厂、东净水厂及西净水厂四个测点的水质监测资料对四个测点的水质进行了综合评价,同时分析各指标变化对水质综合评价结果的影响。评价结果表明:2015年沈阳配水系统中四个测点的水质等级均为清洁,且偏向于较清洁等级的程度较大。通过敏感性分析得出,"pH"和"总氮"是影响输配水工程四个测点水质综合评价结果的敏感性指标。     

平潭及闽江口水资源配置工程莒口水源地水动力与水质模型构建

该文阐述福建省平潭及闽江口水资源配置工程莒口水源地水动力与水质模型建模：先采用Mike21 Flow Model搭建水动力模型，再采用Mike21 Ecolab完成水质耦合模型。模型分别率定河底糙率、水位(潮位)-流量和水质等，通过反复试算河底糙率模拟结果确定河道糙率场，不同水期条件下水位(潮位)-流量关系曲线计算值与实测值验证结果良好，6类22个水质反应参数模拟值与实测值的平均误差在0.285%～11.437%,均方根误差在0.511%～14.695%,表明模型精度较好，可为莒口水源地水质研究提供技术支撑。     

基于 BP 神经网络的大坝新多测点位移模型

大坝位移监测资料分析大多以单一测点得到的数据建立模型,这种单测点模型无法反映大坝作为一个整体各点位移之间的相互联系,也就不能真实地反映坝体的整体安全性态。为此,将多个同源测点联合考虑,通过测点之间的相关性对目标测点建模,再通过该模型推求未布置测点位置的大坝位移值,为推求大坝整体单向位移创造条件。经实例验证,这种新模型在对目标测点的位移预测和补全缺失数据两方面相对常规的单测点模型效果更佳,而且在对未知点的位移值进行预测方面也具有良好效果。     

QUAL2K模型在大凌河流域水资源保护管理中的应用

水质模型的应用,是水质评价及预测的重要手段.本文依据调查与监测的数据,建立了朝阳大凌河流域枯水期阎王鼻子水库至白石水库段的QUAL 2K水质模型,结合GIS系统完成模拟值与监测值的参数估计,并通过水质模型得到验证,为水资源综合管理提供依据.     

水质监测优化布点的物元分析法

水质监测中采样点的优化问题是个很重要的问题，要用少理的测点和少的监测次数，尽可能完整地准确地反映监测水体的水质状况，常规的历史数据估算法优选点带有一定的主观性，而应用蔡文教授创立的物元分析法进行水质优化布点，可为监测部门合理地设置监测点位提供科学依据。     

高坝基岩多点变形监测的GRNN模型研究

为有效地进行大坝基岩多测点变形分析预测，在既有的大坝变形安全监测数学模型结构基础上，利用广义回归神经网络（GRNN）良好的非线性拟合能力建立变形预测模型，并针对高坝基岩多点位移计监测的实际情况，以多个测点的变形量为分析对象，在利用历史变形资料进行训练后实现多点变形预测。实例计算与比较结果表明，GRNN模型计算快、精度高，是进行多测点非线性变形监测预报的有效工具。     

白城市地下水质量现状评价

根据吉林省白城市境内选取的9个测点地下水指标的实测数据,对白城市地下水质量现状进行评价。选取的评价指标分别为氨氮、铁、氟化物、铅、砷、高锰酸钾、矿化度、硬度。评价方法分别采用加附注评分法与人工神经网络法,其中人工神经网络法选用BP神经网络、T-S模糊神经网络2种方法。评价结果显示:2种人工神经网络法评价的水质类别均在Ⅰ～Ⅲ类之间,水质较好;加附注评分法评价出的水质类别中只有穆家店屯水质属于Ⅱ类,其他测点均为Ⅳ类。对比3种方法评价的结果可知,BP神经网络与模糊神经网络评价的水质类型之间的差异较小,加附注评分法比其他2种方法评价得出的水质类别大。     

淮河干流淮南段二维水质模拟

利用二维水质模型，基于交替方向法（ADI法）对模型进行离散求解，结合面向对象的MATLAB高级编程语言，编制了水质模型计算程序，对淮河干流淮南段（鲁台子至田家庵河段）的污染物浓度场进行了数值模拟；并利用MATLAB的图形可视化技术，对水质模型数值模拟结果进行了图形化处理。经模型验证，模拟结果与该段河流的实际水质监测结果基本吻合。     

平原感潮河网水质模型研究

针对平原感潮河网水质状况的待点，利用一维对流扩散方程、水质过程方程建立了河网水质模型；利用GIS对1999年全市点源和面源污染负荷进行合理的分配和计算；进行主要水质参数的灵敏度分析；利用1999年6月～9月的实测水质资料进行了率定，结果表明计算值同实测值吻合较好。     

Simulation of environmental change in response to operation of dams in Huaihe Basin

This paper describes the model simulation of a portion of the Huaihe Basin upstream of the river mouth at Hongze Lake,with an area of 130 520 km2.The MIKE 11 modeling system was used to assess the flows and water quality in the Huaihe,Shayinghe,Honghe,Guohe,and Pihe rivers.The hydraulic part of the model was used to study the propagation of flows in the Huaihe River,which was calibrated with data from 2002-2003 and verified with data from 2004-2005.In general,there was agreement between measured and simulated discharges at all the hydrological stations.Except for some places close to large gates,there was reasonable agreement between measured and simulated water levels in the simulated rivers.The MIKE 11 WQ (water quality)model was used to study general sanitary parameters describing the river water quality in areas influenced by human activities.The water quality model simulated dissolved oxygen (DO),chemical oxygen demand (COD) and ammonia nitrogen (NH3-N).The difference between the simulated and observed concentrations was within the range that could be expected from water quality modeling,taking into account uncertainties such as pollution loads,and monitoring and sampling frequency.This model setup was also suitable for the subsequent scenario modeling of periods of water project operation.In the simulation of the Pihe River,increasing the discharge at Hengpaitou Dam was shown to cause a significant improvement in water quality downstream of Lu'an City.In the Shayinghe and Huaihe rivers,the effect was less visible.This suggests that the poor water quality in the Huaihe Basin is mainly caused by extensive discharge of domestic and industrial wastewater.     

一维河流水团示踪试验数据的模糊线性回归

将模糊线性回归的概念引入分析河流水团示踪试验数据、确定河流水质参数的计算过程中,建立计算河流水质参数的模糊线性回归模型,利用该模型能计算出不同置信水平下水质参数的取值范围。算例验证结果表明,应用模糊线性回归模型可以有效地确定河流的水质参数,且计算过程具有一定的稳定性、可靠性和灵活性,模糊线性回归模型是分析河流水团示踪试验数据、确定河流水质参数的一种有效的途径。     

临淮岗工程不同蓄水条件下的水质可达性分析

建立临淮岗工程淹没区在不同蓄水条件下的二维非稳态FVS格式水流水质模型,基于水量、水质同步实测数据对模型进行率定验证。运用所建模型对研究区域水流水质过程进行数值模拟,定量分析了研究区域在最不利条件下对临淮岗坝前水质的影响程度。对不同库容条件下在库区北部农业用水时的库区水质浓度场进行计算分析,结果表明:当上游边界来水为功能区Ⅲ类,临淮岗坝前COD、NH3-N和TP浓度都能达到GB 3838—2002Ⅲ类水质标准;当边界条件为枯水期水质时,临淮岗坝前的NH3-N浓度超标,超标率为28%,COD及TP均能达标。     

基于污染物通量的潘家口—大黑汀水源地水污染生态补偿量化研究

回顾我国水污染补偿的研究及实践,分析潘家口—大黑汀水源地及入库河流的水质状况,在明确考核断面及考核指标的基础上,建立基于污染物通量的水污染补偿量化估算模型,并根据2013年潘家口—大黑汀水源地入库河流的水质和水量监测数据,估算入库河流水污染生态补偿量。     

基于BP神经网络的潇河流域水质预测

针对传统水质预测方法存在预测精度不理想以及对实测数据要求较高的问题,建立基于BP神经网络的水质预测模型,以掌握研究流域未来一定时段的水环境质量情况。模型以潇河流域6个水质监测断面2017年1月-2020年5月的重铬酸盐指数和高锰酸盐指数的浓度作为训练集,以2020年6月-2020年8月的水质数据作为验证集进行模拟与预测。结果表明：BP神经网络模型经训练后,模拟的各断面水质指标平均相对误差均小于7%,相关性系数均超过了0.98,验证集的水质指标平均相对误差均小于18%。构建的BP神经网络模型预测精度较高,可以用于潇河流域的水质预测。     

RESEARCH ON HYDRODYNAMIC AND WATER QUALITY MODEL FOR TIDAL RIVER NETWORKS

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A Water Quality Model with Three Dimensional Variational Data Assimilation for Contaminant Transport

The safety of water delivery and water quality in the South to North Water Transfer Project is important to China. When sudden pollution accidents happen in this project, a high-accuracy water quality model is needed to simulate contaminant transport. Data assimilation algorithm can be used to improve the accuracy of model, and a water quality model with three dimensional variational data assimilation (3DVAR-WQM), are developed in this paper. A contaminant transport experiment has been conducted for verifying the feasibility and accuracy of this model. After analyzing the simulated results in 3DVAR-WQM and the standard water quality model without assimilation, it has been found that the model with simulation estimates the arrival time and value of the peak concentration more accurately, and that the error between the simulated and observed data in this model is little. At the same time, the root mean square error of this model are smaller. This paper increases forecasting skills through data assimilation techniques, and it provides a tool for improving water quality management in the South to North Water Transfer Project of China.     

混合智能算法在引水冲污方案优选中的应用

考虑水质、经济和生态环境影响等因素,建立佛山水道的引水规划优化模型。利用河网水环境数学模型模拟多组引水冲污方案的水质,将输入输出数据作为样本用于人工训练神经网络;将训练好的网络嵌入遗传算法,形成混合智能算法,求解引水规划优化模型。结果表明,混合智能算法能够自动求出不同引水流量下的最优方案,精度较高,无需人工试算,运算速度快,不必对遗传算法与河网模型进行接口处理,具有普遍适用性,为求解耦合复杂模拟模型的优化问题提供了一种理想的工具。     

Identification of River Sections for Domestic Water Supply along the Yangtze River in Jiangsu Province, China

This paper presents major findings from a recent study aiming to systematically determine suitable river sections for local domestic water supply along the Yangtze River in Jiangsu Province, China. On the basis of analysis on the current riverbank utilization and bank stability, accessible and stable river sections in the region were selected. The water quality in these river sections was then studied using a two-dimensional unsteady flow and pollutant transport/transformation model, RBFVM-2D. The model was calibrated and verified against the hydrodynamic data, water quality data and remote sensing data collected from the river. The investigation on the pollution sources along the river identified 56 main pollution point sources. The pollution zones downstream of these point sources are the main threat for the water quality in the river. The model was used to compute the pollution zones. In particular, simulations were conducted to establish the relationship between the extent of the pollution zone and the wastewater discharge rate of the associated point source. These water quality simulation results were combined with the riverbank stability analysis to determine suitable river sections for local domestic water supply.