Assessment of Point and Nonpoint Sources Pollution in Songhua River Basin,Northeast China by Using Revised Water Quality Model

Individual participation of pollutants in the pollution load should be estimated even if roughly for the appropriate environmental management of a river basin.It is difficult to identify the sources and to quantify the load, especially in modeling nonpoint source.In this study a revised model was established by integrating point and nonpoint sources into one-dimensional Streeter-Phelps(S-P) model on the basis of real-time hydrologic data and surface water quality monitoring data in the Jilin Reach of the Songhua River Basin.Chemical oxygen demand(COD) and ammonia nitrogen(NH 3-N) loads were estimated.Results showed that COD loads of point source and nonpoint source were 134 958 t/yr and 86 209 t/yr, accounting for 61.02% and 38.98% of total loads, respectively.NH 3-N loads of point source and nonpoint source were 16 739 t/yr and 14 272 t/yr, accounting for 53.98% and 46.02%, respectively.Point source pollution was stronger than nonpoint source pollution in the study area at present.The water quality of upstream was better than that of downstream of the rivers and cities.It is indispensable to treat industrial wastewater and municipal sewage out of point sources, to adopt the best management practices to control diffuse pollutants from agricultural land and urban surface runoff in improving water quality of the Songhua River Basin.The revised S-P model can be successfully used to identify pollution source and quantify point source and nonpoint source loads by calibrating and validating.

Artificial neural network modeling of water quality of the Yangtze River system:a case study in reaches crossing the city of Chongqing

An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) model and a radial basis function(RBF) model,to simulate the water quality of the Yangtze and Jialing Rivers in reaches crossing the city of Chongqing,P. R. China. Our models used the historical monitoring data of biological oxygen demand,dissolved oxygen,ammonia,oil and volatile phenolic compounds. Comparison with the one-dimensional traditional water quality model suggest that both BP and RBF models are superior; their higher accuracy and better goodness-of-fit indicate that the ANN calculation of water quality agrees better with measurement. It is demonstrated that ANN modeling can be a tool for estimating the water quality of the Yangtze River. Of the two ANN models,the RBF model calculates with a smaller mean error,but a larger root mean square error. More effort to identify out the causes of these differences would help optimize the structures of neural network water-quality models.

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 fiver reach of the Liaohe River Estuary. Dissolved oxygen （DO）, biochemical oxygen demand （BODs）, 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 wa- ter 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 fiver.

Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River,China

With the development of industry and agriculture,nitrogen,phosphorus and other nutrients in the Hanshui River greatly increase and eutrophication has become an important threat to the water quality of the Hanshui River,especially in the middle and lower reaches.The primary objective of this study was to establish the water quality model for the middle and lower reaches of the Hanshui River based on the model of MIKE 11.The main pollutants migration and transformation process could be simulated using the water quality model.The rainfall-runoff model,hy-drodynamic model and water quality model were established using MIKE 11.The pollutants,such as chemical oxygen demand(COD),biochemical oxygen demand(BOD),ammonia nitrogen,nitrate nitrogen,phosphorus,dissolved oxy-gen(DO),were simulated and predicted using the above three models.A set of methods computing non-point source pollution load of the Hanshui River Basin was proposed in this study.The simulated and observed values of COD,BOD5,ammonia,nitrate,DO,and total phosphorus were compared after the parameter calibration of the water quality model.The simulated and observed results match better,thus the model can be used to predict water quality in the fu-ture for the Hanshui River.The pollution trend could be predicted using the water quality model according pollution load generation.It is helpful for government to take effective measures to prevent the water bloom and protect water quality in the river.

Application of Water Quality Model QUAL2K to Model the Dispersion of Pollutants in River Ndarugu, Kenya

Ndarugu River, Kenya, during its course through the different agricultural and industrial areas of Gatundu, Gachororo and Juja farms, receives untreated industrial, domestic and agricultural waste of point source discharges from coffee and tea factories. During wet season the water is also polluted by non-point (diffuse) sources created by runoff carrying soil, fertilizer and pesticide residues from the catchment area. This study involved the calibration of water quality model QUAL2K to predict the water quality of this segment of the river. The model was calibrated and validated for flow discharge (Q), temperature (T&deg), flow velocity (V), biochemical oxygen demand (BOD5), dissolved oxygen (DO) and nitrate (NO3-N), using data collected and analyzed during field and laboratory measurements done in July and November-December 2013. The model was then used in simulation and its performance was evaluated using statistical criteria based on correlation coefficient (R2) and standard errors (SE) between the observed and simulated data. The model reflected the field data quite well with minor exceptions. In spite of these minor differences between the measured and simulated data set at some points, the calibration and validation results are acceptable especially for developing countries where the financial resources for frequent monitoring works and higher accuracy data analysis are very limited. The water is being polluted by the human activities in the catchment. There is need for proper control of wastewater by various techniques, and preliminary treatment of waste discharges prior to effluent disposal. Management of the watershed is necessary so as to protect the river from the adverse impacts of agricultural activities and save it from further deterioration.

Three-Dimensional Water Quality Model Based on FVCOM for Total Load Control Management in Guan River Estuary,Northern Jiangsu Province

Guan River Estuary and adjacent coastal area(GREC) suffer from serious pollution and eutrophicational problems over the recent years.Thus,reducing the land-based load through the national pollutant total load control program and developing hydrodynamic and water quality models that can simulate the complex circulation and water quality kinetics within the system,including longitudinal and lateral variations in nutrient and COD concentrations,is a matter of urgency.In this study,a three-dimensional,hydrodynamic,water quality model was developed in GREC,Northern Jiangsu Province.The complex three-dimensional hydrodynamics of GREC were modeled using the unstructured-grid,finite-volume,free-surface,primitive equation coastal ocean circulation model(FVCOM).The water quality model was adapted from the mesocosm nutrients dynamic model in the south Yellow Sea and considers eight compartments:dissolved inorganic nitrogen,soluble reactive phosphorus(SRP),phytoplankton,zooplankton,detritus,dissolved organic nitrogen(DON),dissolved organic phosphorus(DOP),and chemical oxygen demand.The hydrodynamic and water quality models were calibrated and confirmed for 2012 and 2013.A comparison of the model simulations with extensive dataset shows that the models accurately simulate the longitudinal distribution of the hydrodynamics and water quality.The model can be used for total load control management to improve water quality in this area.

Application of QUAL2K for Water Quality Modeling of River Ghataprabha （India）

River Ghataprabha, during its course through Belgaum district in Karnataka state （India）, receives untreated domestic waste from Gokak town and other neighboring villages situated on the bank of the river. The present study involves the application of water quality model QUAL2K to predict the water quality of this polluted segment of the river. The model was calibrated and validated for biochemical oxygen demand （BOD）, dissolved oxygen （DO） and total nitrogen （TN） in pre-monsoon season. Data for calibration and validation were obtained after the field and laboratory measurements. The performance of the model was evaluated using statistics based on standard errors （SE） and mean multiplicative errors （MME）. The model represented the field data quite well with some exceptions. In spite of some differences between the measured and simulated data sets at some points, the calibration and validation results are acceptable especially for the developing countries where the financial resources are often limited for frequent monitoring campaigns and higher accuracy data analysis.

River Water Quality Model Based on Remote Sensing Information Methods——A Case Study of Lijing River in Guilin City

River water quality models based on remote sensing information models are superior to pure water quality models because they combine the inevitability and risk of geographical phenomena and can take complex geographical characteristics into account. A water quality model for forecasting COD has been established with remote sensing in- formation modeling methods by monitoring and analyzing water quantity and water quality of the Lijing River reach which flows through a complicated Karst mountain area. This model provides a good tool to predict water quality of complex rivers. It is validated by simulating contaminant concentrations of the study area. The results show that remote sensing information models are suitable for complex geography. It is not only a combined model of inevitability and risk of the geographical phenomena, but also a semi-theoretical and semi-empirical formula, providing a good tool to study organic contaminants in complicated rivers. The coefficients and indices obtained have limited value and the model is not suitable for all situations. Some improvements are required.

Source apportionment of river water pollution in a typical agricultural city of Anhui Province, eastern China using multivariate statistical techniques with APCS– MLR

The deterioration of the surface water environment has become a serious challenge for water resources management due to increasing anthropogenic disturbance. Water resources protection requires control of potential pollution sources. In this study, 99 water samples were collected from a river in a typical agricultural city of Anhui Province in eastern China, and these samples were analyzed in terms of pH, electrical conductivity, and the concentrations of F-, Cl-, SO42-, Na+, K+, Mg2+, Ca2+, As, Cr, Cu, Zn, and Pb. Cluster analysis, co-occurrence network analysis, and principal component analysis/factor analysis were conducted to qualitatively identify the potential sources of river water pollution in the study area. An absolute principal component score-multiple linear regression receptor model was used to quantitatively evaluate the contribution of each source to water quality parameters. The results showed that all observed water quality indices met the quality criteria specified in the Chinese drinking water standards, except for pH, ρ(F-), ρ(SO42-), and ρ(As). The heat map showed that the frequent recharge of pollutants from the tributaries during the wet season was the main reason for the deterioration of water quality. Five sources of river water pollution were identified, and their contribution ratios in a descending order were as follows: the geogenic process (24%) > agricultural activities (21%) > poultry farming sources (17%) > domestic pollution (9%) > transportation pollution (5%). Therefore, controlling pollution from agricultural activities, strengthening the regulation of livestock farming, and improving the sewage network are the recommended strategies for improving the quality of surface water resources in this area.

Three-Dimensional Water-Quality Simulation for River Based on VOF Method

In the present study, considering the transport and transformation processes of variables, a threedimensional water quality model for the river system was established, which coupled the volume of fluid(VOF) method with the k-ε turbulence mathematical model. Then, the water hydrodynamic characteristics and transport processes for BOD_5, NH_(3^-)N and TP were analyzed. The results showed that the water surface of convex bank was a little lower than that of concave bank due to the centrifugal force near the bend, and most concentrations were inferior to the type Ⅴ standard indexes of surface water environmental quality. The model validation indicated that the errors between the simulated and monitored values were comparatively small, satisfying the application demands and providing scientific basis and decision support for the restoration and protection of water quality.

Modelling of water quality of Minjiang estuary

In order to establish economic development region at Mawei districtwhich is nearby downstream of Minjiang river and to answer the question of impact of economic development on water quality of Minjiang estuary, the analyses of hydrologic and hydraulic characteristics of Mawei reach of Minjiang tidal river, a two-dimensional mathematical model has been established and simulation of water quality was studied. The results show that the flushing time of a conservative pollutant during dry and raining period are 12 and 7 days respectively from Mawei to Minjiang mouth, the decay rate constants of BOD and NH3-N are 0.1 to 0.4 and 0.18 to 0.45 d-1 respectively. The capacity of dilution and assimilation for pollutants is larger.

The Changes of Water Quality in Space and Time in the Mekong River, Bassac River and Adjacent Waterways

Catfish （Pangasianodon hypophthalmus） farming along Mekong river and Bassac river depends heavily on water quality of the two rivers, whereas water quality of these rivers are affected by the waste of aquaculture activities, agricultural production, industrial and municipal waste. This report analyzes the monitoring data on Mekong river, Bassac river and adjacent waterways in the period of 2011-2012, focusing on parameters of organic pollution to assess the current quality of these two rivers. Based on the results, the water quality in the river-head was generally better than in the middle and at the end of the river, and the quality of water of the Mekong river was better than Bassac river. In terms of time, water quality in July was considered the best in all the basins. At adjacent natural rivers and canals, ammonia levels increased and exceeded the Vietnamese standard in April, and BOD values were also much higher compared to two major rivers. The results of the model also showed that the levels of pollution index of the Mekong and Bassac river were very low （1.33 and 1.47）, and the values （Y） in the canals were higher （1.63-1.67） but still in permitted level. Therefore, the water quality of the Mekong and Bassac river in the period 2011-2012 was generally still quite good.

Study of River Water Environment Simulation on WebGIS

Along with economic development, river pollution has become a serious phenomenon. It＇s rational to simulate variation of pollutants by using water quality model. Thus, relevant departments could take appropriate measures to improve the water environment. However, the traditional image of mathematical modeling is not intuitive. The advantage of WebGIS is the ability of visualization on web browser by the combination ofgeospatial data and pollution attribute data.

长江中上游重要渔业水域环境质量评估

为准确评估长江中上游重要渔业水域水环境质量现状及变化趋势,提高水质评价效率,本研究基于11个水质参数,采用水质指数法(water quality index,WQI)对2006-2021年长江中上游三个重要渔业水域水质进行了综合评价,建立WQI min综合评价模型。结果显示:(1)长江中上游重要渔业水域的水温和高锰酸盐指数呈上升趋势;基于地表水环境质量标准(GB38338-2002),单因素水质评价结果表明监测水域内整体水质处于地表水Ⅴ类水标准,部分年份达劣Ⅴ类,主要污染指标为总氮。(2)通过综合评价方法分析,长江中上游重要渔业水域整体为“良”;2006~2021年长江中上游重要渔业水域水质质量呈逐年改善的趋势,且上游保护区的改善较大。(3)基于WQI方法,确定了长江中上游重要渔业水域的关键水质参数为:总氮、高锰酸盐指数、汞、溶解氧、氨氮、悬浮物以及水温,分别构建了上游保护区、中华鲟保护区以及四大家鱼保护区的WQI_(min)模型;考虑权重和不考虑权重的WQI min模型对比分析表明,考虑权重的WQI min模型的水质评价结果更加准确,该方法可有效评估长江中上游重要渔业水域的水质变化特征并可扩展用于其他水域。

基于VMD-TCN-GRU模型的水质预测研究

为充分挖掘水质数据在短时震荡中的变化特征,提升预测模型的精度,提出一种基于VMD(变分模态分解)、TCN(卷积时间神经网络)及GRU(门控循环单元)组成的混合水质预测模型,采用VMD-TCN-GRU模型对汾河水库出水口高锰酸盐指数进行预测,并与此类研究中常见的SVR(支持向量回归)、LSTM(长短期记忆神经网络)、TCN和CNN-LSTM(卷积神经网络-长短期记忆神经网络)这4种模型预测结果对比表明:VMD-TCN-GRU模型能更好挖掘水质数据在短时震荡过程中的特征信息,提升水质预测精度;VMD-TCN-GRU模型的MAE(平均绝对误差)、RMSE(均方根误差)下降,R^(2)(确定系数)提高,其MAE、RMSE、R^(2)分别为0.0553、0.0717、0.9351;其预测性能优越,预测精度更高且拥有更强的泛化能力,可以应用于汾河水质预测。

平原河网水动力优化调度与水环境改善的响应关系研究

平原河网河道流动性较差是引起水环境污染严重的主要原因,引调水是改善平原河网地区水环境的重要措施之一。本文以佛山市三山围为例,基于实测资料构建了河网水动力水质耦合模型,采用15天的连续水动力水质监测数据对模型进行了验证,并将NSE和RMSE模型评价指标用于模型评价。同时结合地势、潮汐规律和景观水位等设计了4种闸控模式和7种景观控制水位,共28种模拟工况,模拟分析了不同条件下的水动力水质改善与内外江潮位变化、引排水流量及其空间分布、闸控方式和景观水位等综合响应机理。结果表明:构建的模型合理可靠。研究区域受引排水路径的影响,河道流动性差异较为显著。综合考虑河道流量分布、水流路径、分汊河道分流作用和外江污染物浓度等对河道水质的作用效果并有效结合潮汐河网的动态水环境容量和污染源排放的时空分布对水环境的改善作用将非常显著。与低景观控制水位相比,高景观控制水位的内江动态水环境容量相对较大,污染物浓度较低。景观控制水位从0.2 m上升至0.8 m时,不同引调水路径的引水流量上升28.00%~64.70%,断面氨氮浓度削减了0.85~5.50 mg/L,削减比例达到28.89%~67.23%。本研究为平原潮汐河网水环境优化调度研究提供了新的思路,为相关部门对平原河网的水环境改善提供了重要的参考。

考虑水动力条件及水系连通的平原河网圩区畅流活水方案

针对平原河网地区水动力条件不足等问题,以嘉兴市新塍镇为例,探究不同畅流活水方案对河道水质的改善效果。构建MIKE11水动力学水质耦合模型,分析“引水/水系连通—水质”驱动响应规律,以NH3-N浓度为主要指标,分析不同活水方案的水质改善效果,并提出优化调控方案。结果表明,集中引水对区域水质改善影响较小,分散设置多个引水点可明显提高水质;直接对水质较差河道进行补水,污染物消减率在8%~30%之间,水质改善效果较明显;合理的水系连通工程可进一步增加畅流活水方案水质改善效果。

结合光谱降维的IPSO-SVR水体总磷浓度预测模型

[目的]选择最优模型对水体中总磷浓度进行预测,为准确、实时、高效检测水资源状况提供支持。[方法]以2021年在长江中下游武汉—安徽地区采集的水质样本作为研究对象,首先,对采集到的长江光谱数据进行最大最小归一化和均值中心化两种预处理操作以便统一数据的范围和均值点,并使用核主成分分析(KPCA)技术对预处理后的光谱数据进行降维操作。选取方差解释率为99.6%下的6个特征向量进行后续预测模型的训练,接着在原有粒子群算法的基础上引入自适应惯性权重更新公式和遗传—模拟退火变异思想,提高算法的寻优能力。使用改进的粒子群优化算法对支持向量回归模型中的超参数组合进行寻优,对支持向量回归模型使用输出的结果进行预测模型的训练,最后使用测试集数据进行总磷浓度的预测。[结果]提出了一种结合光谱降维的改进粒子群优化算法(IPSO)结合支持向量回归(SVR)的水体总磷含量预测模型。通过和当前预测性能较好的几种机器学习模型进行精度的比较发现,该试验模型对长江水体总磷浓度进行预测时决定系数(R^(2))为0.973920,均方根差(RMSE)为0.003012,平均绝对误差(MAE)为0.002105。[结论]使用光谱数据结合降维技术、粒子群优化算法和机器学习模型的算法融合模型检测水体总磷浓度可行性强,精确度高,且拟合效果良好。

黄河流域水环境问题研究现状、挑战与展望

黄河流域生态保护和高质量发展是国家重大发展战略,保护黄河是事关中华民族伟大复兴和永续发展的千秋大计.近年来,黄河流域水环境质量明显改善,但有限的水资源和脆弱的生态系统使得黄河流域水环境保护仍面临巨大的挑战.科学诊断黄河流域重大水环境问题是新时期治理黄河的前提和关键.本文围绕黄河流域水环境问题诊断这一主题,聚焦黄河流域断面水质改善的核心需求,首先分析黄河流域水环境现状,发现黄河流域整体水质持续向好,但干支流水质改善不同步,流域主要污染指标时空差异显著,中下游和部分支流污染严重;其次梳理国内外相关研究进展和主要挑战,总结断面水质提升所需的核心理论与技术,如水环境承载力评价、污染排放清单构建与水环境模型模拟等方面的应用与发展趋势,发现黄河流域存在气候变化影响下水沙变化大、现有排放清单分辨率不足、水环境模拟缺乏多尺度污染排放-断面水质响应关系研究等问题,难以支撑未来精细化水环境管理.对黄河流域水环境研究的未来发展进行了展望,建议未来在以下几个方面开展进一步研究,包括气候变化下黄河流域水环境承载力研究、黄河流域高分辨率排放清单构建、多尺度污染排放与断面水质响应关系.