Development and application of a two-dimensional water quality model for the Daqinghe River Mouth of the Dianchi Lake

Water quality models are important tools to support the optimization of aquatic ecosystem rehabilitation programs and assess their efficiency. Basing on the flow conditions of the Daqinghe River Mouth of the Dianchi Lake, China, a two-dimensional water quality model was developed in the research. The hydrodynamics module was numerically solved by the alternating direction iteration （ADI） method. The parameters of the water quality module were obtained through the in situ experiments and the laboratory analyses that were conducted from 2006 to 2007. The model was calibrated and verified by the observation data in 2007. Among the four modelled key variables, i.e., water level, COD （in CODcr）, NH4＋-N and PO43-P the minimum value of the coefficient of determination （COD） was 0.69, indicating the model performed reasonably well. The developed model was then applied to simulate the water quality changes at a downstream cross-section assuming that the designed restoration programs were implemented. According to the simulated results, the restoration programs could cut down the loads of COD and PO43-P about 15%. Such a load reduction, unfortunately, would have very little effect on the NH4^＋-N removal. Moreover, the water quality at the outlet cross-section would be still in class V （3838-02）, indicating more measures should be taken to further reduce the loads. The study demonstrated the capability of water quality models to support aquatic ecosystem restorations.

An attribute recognition model based on entropy weight for evaluating the quality of groundwater sources

In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by Chen Q S. In the model, firstly, the author establishes the attribute space matrix and determines the weight based on Shannon entropy theory; secondly, calculates attribute measure; thirdly, evaluates that with confidence criterion and score criterion; finally, an application example is given. The results show that the water quality of the groundwater sources for the city comes up to the grade II or III standard. There is no pollution that obviously exceeds the standard and the water can meet people’s needs .The results from an evaluation of this model are in basic agreement with the observed situation and with a set pair analysis (SPA) model.

Evaluation, prediction, and protection of water quality in Danjiangkou Reservoir, China

The water quality in the Danjiangkou Reservoir has attracted considerable attention from the Chinese public and government since the announcement of the Middle Route of the South to North Water Diversion Project （SNWDP）, which commenced transferring water in 2014. Integrated research on the evaluation, prediction, and protection of water quality in the Danjiangkou Reservoir was carried out in this study in order to improve environmental management. Based on 120 water samples, wherein 17 water quality indices were measured at 20 monitoring sites, a single factor evaluation method was used to evaluate the current status of water quality. The results show that the main indices influencing the water quality in the Danjiangkou Reservoir are total phosphorus （TP）, permanganate index （CODM,）, dissolved oxygen （DO）, and five-day biochemical oxygen demand （BODs）, and the concentrations of TP, BODs, ammonia nitrogen （NH3--N）, CODM,, DO, and anionic surfactant （Surfa） do not reach the specified standard levels in the tributaries. Seasonal Mann--Kendall tests indicated that the CODMn concentration shows a highly significant increasing trend, and the TP concentration shows a significant increasing trend in the Danjiangkou Reservoir. The distribution of the main water quality indices in the Danjiangkou Reservoir was predicted using a two-dimensional water quality numerical model, and showed that the sphere of influence from the tributaries can spread across half of the Han Reservoir if the pollutants are not controlled. Cluster analysis （CA） results suggest that the Shending River is heavily polluted, that the Jianghe, Sihe, and Jianhe rivers are moderately polluted, and that they should be the focus of environmental remediation.

Comprehensive Evaluation of Water Quality of Rivers in Binzhou Based on RAGA-PPCE Model

The water quality of main rivers in Binzhou City,Shandong Province was comprehensively evaluated based on RAGA-PPCE model. Six main factors such as ammonia nitrogen(NH-N),total phosphorus(TP),total nitrogen(TN),chemical oxygen demand(COD),dissolved oxygen(DO) and p H were used to establish the evaluation and classification standards of water quality. The results show that the evaluation results of water quality by RAGA-PPCE model and the fuzzy comprehensive evaluation method are basically the same. The evaluation results of RAGA-PPCE model are objective and reasonable and can be applied to the comprehensive evaluation of water quality.

Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model

Rivers in the Liaohe River Estuary area have been seriously polluted by discharges of wastewater containing petroleum pol- lutants and nutrients. In this paper, The Enhanced Stream Water Quality Model (QUAL2K) and its revised model as well as One-dimensional Tide Mean Model (1D model) were applied to predict and assess the water quality of the tidal river reach of the Liaohe River Estuary. Dissolved oxygen (DO), biochemical oxygen demand (BOD5), ammonia nitrogen (NH3-N) and total phosphorus (TP) were chosen as water quality indices in the two model simulations. The modelled results show that the major reasons for degraded rivers remain petroleum and non-point source pollution. Tidal water also has a critical effect on the variation of water quality. The sensitivity analysis identifies that flow rate, point load and diffuse load are the most sensitive parameters for the four water quality indices in the revised QUAL2K simulation. Uncertainty analysis based on a Monte Carlo simulation gives the probability distribution of the four water quality indices at two locations (6.50 km and 44.84 km from the river mouth). The statistical outcomes indicate that the observed data fall within the 90% confidence intervals at all sites measured, and show that the revised QUAL2K gives better results in simulating the water quality of a tidal river.

Complex Sequence Quality Evaluation Model for Concealed Water Supply Pipeline of Prefabricated Construction

The accurate assessment of the quality can materially affect the safety and life of the prefabricated construction.In this paper,we studied the overall module of concealed water supply pipeline,and a new complex sequence quality evaluation model was established.By analyzing the small evaluation index elements of the model,the weight of the larger evaluation index could be deduced.The total quality evaluation score of the overall module could be obtained by calculating the weight value of the evaluation index,and then the quality standard of the overall module could be obtained.

Applying PP Model Based on RAGA in Water Environment Quality Evaluation

Projection Pursuit (PP) model is a technique of falling high dimension. Real coding based on Accelerating Genetic Algorithm (RAGA) is a method of optimum. Through combining the PP model and RAGA, the paper applies the model in the water environment quality evaluation. The writer takes the water quality evaluated indexes of each sample as projection direction and turns high dimension data into low dimension projection value. Thus, the writer achieves on evaluating the grade of water samples and its optimum order. Based on this, the writer overcomes the jamming of weights calculated on fuzzy synthesize judge and gray system valuation. The paper can provide a new thought for water environment quality evaluation and other falling high dimension and optimum issue.

Water Resource Pricing Study Based on Water Quality Fuzzy Evaluation: A Case Study of Hefei City

Price plays an important role in water resources management. The price of water resources can also be considered as a “water resource tax” which reflects the value and opportunity cost of water, and people will pay for the right to use water. Currently, the water resource fees’ effect of regulating resource differential revenues is not manifest and it’s not enough to reflect the principle of paid use of resources as well as regulating resources differential revenues. Due to the ambiguity and complexity of water resources price, this paper uses methods relating to fuzzy mathematics for modeling and processing. The study had a comprehensive consideration of five factors including water quality, water resources per capita, household consumption level, per capita GNP, population or population density to evaluate the water resource price.

高质量发展视角下京津冀地区WEF系统综合评价研究

为综合评价京津冀地区的高质量发展水平,从创新、协调、绿色、开放、共享等5个维度构建高质量发展评价指标体系,采用熵值-变异系数综合赋权法计算指标权重,利用线性加权法构建综合评价指数模型测度京津冀地区WEF系统高质量发展的水平,并基于灰色关联度模型探究影响WEF系统高质量发展的关键因子与维度。结果表明:2011—2021年京津冀地区WEF系统综合评价指数呈现上升趋势,空间尺度上3个省市的均值排序为北京市>河北省>天津市;京津冀地区WEF系统各维度指数表现出不同的时空特征,其中共享维度表现出下降趋势,创新维度的空间差异性最显著;粮食产量、生活耗能占比、万元GDP耗能量、生活用水量占比、第三产业耗能占比等指标是影响WEF系统高质量发展的关键因子,协调与共享是影响WEF系统高质量发展的关键维度,本研究可为区域资源高水平管理提供科学的理论依据。

真空低温蒸煮鸭胸肉的水分迁移及风味物质变化规律

为探究鸭胸肉在真空低温蒸煮过程中水分迁移及挥发性风味物质的变化规律,分别将鸭胸肉的中心温度加热至60、65、70、75、80℃,并以100℃加热的鸭胸肉为空白对照,测定不同中心温度下鸭胸肉的水分自由度及挥发性风味物质。结果表明:真空低温蒸煮鸭胸肉烹饪失水率较低,不易流动水占比和感官评分较高。从鸭胸肉中共检出59种挥发性风味物质,低温组中的挥发性风味成分的种类及含量均远高于对照组。利用气味活性值筛选出20种特征挥发性风味物质,对20种特征风味物质进行主成分分析,得到真空低温蒸煮鸭胸肉风味强度评价模型为:F=0.49F_1+0.24F_2+0.13F_3,模型特征性风味强度评价结果与感官评分相关系数为0.89(P<0.05),该模型可应用于真空低温蒸煮鸭胸肉的风味评价。

基于数字钻探与多尺度模型融合的隧道岩体完整性自动解译技术研究及应用

在多岩性与多指标钻探数据收集的基础上,综合考虑解译精度与预报效果,借助机器学习工具,提出一种基于数字钻探与多尺度模型融合的隧道岩体完整性自动解译技术。首先,对原始钻探数据有针对性的进行降噪与等距分割(0.5,1,2 m)等预处理,形成多尺度、高质量机器学习数据集;然后,进行模型参数自动寻优、训练、评估与可解释性等操作,验证模型的准确性与可靠性;最后,采用加权平均的方法进行多尺度模型解译结果的融合,以增强该技术的工程实用效果。为方便实际工程应用,以上述技术为核心开发轻量化数字钻探智能解译平台,经多条灰岩与砂岩隧道应用结果表明:对比地质雷达与常规钻探解译,多尺度模型融合解译在解译效率、预测效果等方面总体表现优异,可为隧道施工的开挖与支护提供可靠的岩体完整性信息。

基于水动力水质模型的浅水型湖泊水环境治理目标可达性评估

当前湖泊水环境治理仍然面临着湖泊水质的实际改善效果与工程方案预期不相符的难题,特别是城市浅水型湖泊,其受外源污染、底泥释放、降雨冲击等因素,对治理成效扰动响应更为剧烈,因此,进行多因素成效评估对城市浅水型湖泊水环境治理尤为重要。采用InfoWorks ICM模型,以武汉市墨水湖为例,搭建浅水型湖泊水质水动力模型,依据气象水文、城市开发建设、湖泊污染情况等现状数据,基于模型计算原理,研究COD、NH_(3)-N、TP等污染物的变化趋势,定量分析不同工况情景下湖泊水质的可达性,评估规划拟建工程的实施效果,可为同类湖泊水环境治理工程方案优化提供参考。

基于加速分层遗传算法-投影寻踪模型的三峡水质评价

针对基于遗传算法的投影寻踪模型的不足,提出了基于加速分层遗传算法的投影寻踪模型,提高了全局搜索能力和收敛速度。并将其应用于长江流域水体水质的评价中。利用长江三峡库区8个断面的水质指标监测数据,建立基于加速分层遗传算法的投影寻踪模型,对各断面水质展开评价。结果显示:该段流域内水体质量整体良好,水质等级主要分布在《地表水环境质量标准》(GB3838-2002)Ⅱ类、Ⅲ类、Ⅳ类等级中。该模型能够合理的评价水质等级,值得广泛推广应用。

Analysis of Ammonia Nitrogen Content in Water Based on Weighted Least Squares Support Vector Machine (WLSSVM) Algorithm

Determination of ammonia nitrogen content in water is the basic item of the environmental water pollution, and is the key index to evaluate the water quality. This article designs a water quality monitoring system based on the on-line automatic ammonia nitrogen monitoring system, and establishes a forecasting model based on the weighted least squares support vector machine algorithm. The weighted least squares support vector machine algorithm increases the weight parameter setting, improves the speed and accuracy of prediction learning, and improves the robustness. In this article, a comparison between neural network model and weighted least square support vector machine model is made, which shows that the weighted least squares support vector machine model has better prediction accuracy.

毕业生就业质量预测模型研究

高等教育的深化改革和高质量发展对高校的学科、专业建设以及招生工作带来巨大挑战,高校应结合实际情况调整专业设置和招生计划以应对新形势.本文针对毕业生就业质量各评价指标构建灰色预测模型,结合层次分析法,对毕业生未来几年的就业质量进行预测,并对各专业进行内部评价,以期为招生管理部门科学调整招生计划提供理论依据.

基于模糊数学理论的河道生态效益综合评价

河道既是水生态环境的重要载体,也是水文化中不可或缺的景观资源,其生态效益在社会可持续发展中起着重要作用。文中构建了涵盖河道特性、水流特性、生物特性、社会服务特性4个维度的河道生态效益评价指标体系,其中,河道特性、生物特性以及社会服务特性指标基于基础数据统计量化;水流特性指标基于河道水动力水质模型模拟结果来衡量。引入模糊数学理论构建了河道生态效益综合评价模型,其中各指标的权重采用层次分析法确定。最终形成了一套涵盖指标体系构建与量化、指标权重确定及综合评价模型构建与应用的河道生态效益评价体系。以唐山清水润城项目西沙河治理河段为研究对象,比较了5 a、10 a、20 a重现期设计降雨情景下河道治理前后的生态效益。结果显示:3种重现期设计降雨情景下,河道生态效益综合评价等级均由“差”转为“优”,表明河道清淤疏浚、堤防建设及岸坡防护工程等治理措施显著改善了河道的生态效益。

隐马尔科夫模型的鱼塘水质评价研究

为了避免在鱼塘养殖中因为水质改善不及时而带来的经济损失,建立一种准确快速的水质评价模型是必要的。本文构建了基于隐马尔科夫的鱼塘水质评价模型,分析了鱼塘水质和鱼的活跃程度之间的关系,通过实验验证了该模型的可行性与正确性。隐马尔可夫模型能够为养殖者从根源上解决鱼塘水质问题提供理论依据,对改善传统依靠传感器直接测量水质指标的繁琐的过程起到了促进作用。

山地城市主要河流水质评价及预测研究——以四川省绵阳市为例

综合客观评价河流水质的健康及污染状况,科学分析预测水环境质量的变化趋势,对于河流水污染精准防治具有重要意义。选取绵阳市境内主要河流为研究对象,基于2014-2022年绵阳市12个水质监测断面的4项污染物指标监测数据,结合模糊综合评价法及主成分分析法对其断面水质进行评价并判断污染程度,建立带外源输入的非线性自回归(NARX)神经网络模型,预测研究区域内2025年和2030年的水质变化趋势。结果表明:1)综合不同水期来看,在枯水期,芙蓉溪仙鱼桥与梓潼垢家渡断面的水质级别分别在2015年和2016年都未能达到水质目标,满足水质功能标准的断面占12个监测断面的92%,而在平水期与丰水期各断面水质均能达到各自的标准;2)凯江老南桥、梓潼垢家渡及天仙镇大佛寺断面水质受水期影响较大,平武水文站在所选断面中总体水质较好,而芙蓉溪仙鱼桥较差;3)溶解氧(DO)、高锰酸盐指数(CODMn)、五日生化需氧量(BOD5)及氨氮(NH3-N)的实测值与预测值之间高度相关,均方误差均较小,满足水质预测的精度要求;4)从水质变化趋势来看,除天仙镇大佛寺断面2028-2030年的水质级别由2023-2027年的Ⅰ级降为Ⅱ级以及芙蓉溪仙鱼桥断面2025年和2030年水质级别分别为Ⅱ级与Ⅲ级外,其余断面水质级别均为Ⅰ级,总体水质有所提升。该研究提出的基于模糊综合评价法-主成分分析法-NARX神经网络模型研究框架能够准确地对河流多断面各水期的水质进行客观评价,并在一定程度上弥补水文观测的“数据盲区”,适用于其他类似河流的水质预测,可为河流水质综合评价及预测预警提供科学依据与技术支持。

山西省7条河的流域水生态承载力评估

为科学研判山西省7条河的流域水生态承载现状和存在问题,有效提升河流水生态承载力,构建7条河的流域水生态承载力评估指标体系,应用模糊综合评价法定级评估7条河的流域水生态承载力,使用差分自回归移动平均(autoregressive integrated moving average,ARIMA)模型和长短期记忆(long short-term memory,LSTM)模型对比预测水生态承载力变化趋势。结果表明,2011—2021年,7条河的流域水生态承载力总体为一般超载等级。其中,汾河流域水生态承载力呈基本承载,其他流域为一般超载,水环境指数和水资源指数对7条河的流域水生态承载力影响较大。ARIMA-LSTM模型预测表明:2022—2031年汾河水生态承载力变化呈上升趋势,涑水河、沁(丹)河流域水生态承载力未来趋势存在较大不确定性,其他流域水生态承载力呈不同幅度波动趋势;2031年左右,各流域水生态承载力将得到提升。建议通过提升流域水资源利用率以及加强7条河的流域绿色生态走廊建设来推进流域水生态保护工作。