Application of QUAL2Kw for water quality modeling and dissolved oxygen control in the river Bagmati

A stream water quality model, QUAL2Kw, was calibrated and validated for the river Bagmati of Nepal. The model represented the field data quite well with some exceptions. The influences of various water quality management strategies have on DO concentrations were examined considering: (i) pollution loads modification; (ii) flow augmentation; (iii) local oxygenation. The study showed the local oxygenation is effective in raising DO levels. The combination of wastewater modification, flow augmentation and local oxygenation is necessary to ensure minimum DO concentrations. This reasonable modeling guarantees the use of QUAL2Kw for future river water quality policy options.     

Comprehensive River Water Quality Management by Simulation and Optimization Models

In this paper, the performance of water quality modeling is investigated in the analysis of the natural assimilative capacity (NAC) of a river system. The new data available, along with the appropriate integrated model, allow for the analysis of the NAC of the entire river. The integrated model developed here emphasized the implementation of the QUAL2E simulation model and the appropriate allocation of waste loads (optimization model) in a subtropical area. Simulations are calibrated and validated according to the data from the Water Quality and Flow Rate Monitoring Project using the QUAL2E model. On the basis of the optimal allocation model, the results of the NAC and allowable pollution loading in the Putzu River basin are discussed. The study provides a framework of the integrated model that can be used as a guideline to determine the NAC of subtropical rivers.     

基于QUAL2K模型的鹤壁卫河水质模拟预警研究

水质预报预警对于防范水污染、降低水污染风险及其带来的损失、保障用水安全及水环境质量等具有重大意义。提出了一种基于QUAL2K模型的水质模拟预警方法,包括水质模拟预测、预警指数计算和警情确定,以海河流域鹤壁市卫河为例进行实证研究。研究结果表明:基于QUAL2K模型模拟精度分别为COD 97.7%、NH_3-N 98.5%,水质模拟效果较好;所选河段预警时段内COD基本处于无警和轻警2个级别,氨氮大多是巨警,浓度严重超标,是导致监测断面预警指数高的主要原因。     

Water quality in Minho/Miño River (Portugal/Spain)

Minho River, also called Miño (in Spain), extends to about 300 km from Spain to Portugal. The source of the river lies in Spain and in the last 75 km, the river defines the border between Portugal and Spain. Under the scope of a cooperation project between North Portugal and Galicia region of Spain, titled: “Valorization of the natural resources of the Minho/Miño drainage basin”, seven water-sampling campaigns were carried out during the last 2 years in Minho River basin. Seven sampling sites were selected along the international stretch, and five were chosen in the main Portuguese and Spanish tributaries of Minho River. Water quality based on the physicochemical and microbial parameters was assessed. According to the Portuguese legislation for surface waters, the international section of Minho River presents a reasonably good water quality (BOD₅ <5 mg/L, TNK <2 mg/L, and total phosphorous <1 mg P/L). Valença and Louro were found to be the most polluted sampling sites and Louro the most polluted tributary (maximum values observed: TSS?=?26 mg/L, BOD₅?=?6.6 mg O₂/L, COD?=?20.8 mg O₂/L, total nitrogen?=?9.9 mg N/L; minimum value observed: OD?=?1.3 mg O₂/L). A one-dimensional stream water quality model QUAL2Kw was calibrated using data measured in field surveys along the international stretch of Minho River. QUAL2Kw was also used to predict the impact of flow conditions, discharges, and tributaries on the water quality of international stretch of Minho River, essential to establish proposals for management and planning of Minho River Basin.     

Wasteload Allocation Using Wastewater Treatment and Flow Augmentation

A Wasteload allocation model, named Cost-Flow-Augmentation Model involving wastewater treatment and flow augmentation as a method of pollution abatement has been developed. The cost functions for wastewater treatment were developed as power functions of biochemical oxygen demand (BOD) removal using the regression module of the SPSS10 software. The cost function for flow augmentation was also developed using a regression between cost of dam/barrage and corresponding flow released from upstream reservoir for downstream water quality improvement. The response of wasteloads and flow augmentation on the water quality was quantified in terms of transfer coefficient calculated using the QUAL2E water quality simulation model. The performance of these models is demonstrated on the 22-km-long Delhi stretch of river Yamuna, India. Optimal solutions of the formulated models were obtained using the Web-based interactive non-differentiable interactive multiobjective bundle-based optimization system software. The optimal solutions obtained reveal that flow augmentation is not an economically feasible pollution abatement option for the Delhi stretch of river Yamuna.     

Parameter Sensitivity of a Surface Water Quality Model of the Lower South Saskatchewan River—Comparison Between Ice-On and Ice-Off Periods

Little is known about seasonal differences (ice-on vs. ice-off periods) and the sensitivity of in-stream processes to surface water quality constituents in rivers that have a persistent ice cover in winter. The goal of this study is to investigate the sensitivity of nutrient transformation processes on surface water quality, especially rivers in cold regions where ice-covered conditions persist for a substantial part of the year. We established a sensitivity analysis framework for water quality modelling and monitoring of rivers in cold regions using the Water Quality Analysis Program WASP7. The lower South Saskatchewan River in the interior of western Canada, from the Gardiner Dam at Lake Diefenbaker to the confluence of the North and South Saskatchewan rivers, is used as a test case for this purpose. The study reveals that parameter sensitivities differ between ice-covered and ice-free periods and biological model parameters related to nutrient-phytoplankton dynamics can still be sensitive during the ice-covered season. For example, sediment oxygen demand is an important parameter during the ice-on period, whereas parameters related to nitrification are more sensitive in the ice-off period. These results provide insight into important water quality monitoring aspects in cold regions during different seasons.     

Pollution risk assessment based on QUAL2E-UNCAS simulations of a tropical river in Northern India

This paper exemplifies the application of U.S. Environmental Protection Agency's water quality model, QUAL2E-UNCAS in assessing the pollution risk of a tropical river. The rivers selected for study were Hindon (main river) and Kali (its tributary) flowing through Uttar Pradesh district of Northern India. The model application to the two rivers revealed poor water quality in terms of dissolved oxygen (DO), biochemical oxygen demand (BOD), and ammonia concentrations. Monte Carlo simulations were performed on two different data sets that were confirming to marked seasonal variations. The Monte Carlo simulation (MCS) derived 95 % confidence level for these parameters strengthened the fact that all point sources were exploiting the assimilative capacity of the two rivers. In order to ascertain probabilistically the risk at which two rivers were falling short of desired water quality, probability curves based on effluent standards and available water quality were prepared. On mapping the two curves, it was found that at 95 % probability, Hindon River was flowing with 53 to 100 % less of desired DO, up to 100 % more of minimum BOD, and probability with which ammonia concentration would not be more than the desired concentration was found to fall downstream. The Kali headwaters showed better quality during low river temperature but worsened downstream with up to 100 % violation in all the above observed parameters. It is expected that similar studies wherein the dependable levels with which a polluted river can be understood to fall short of desired water quality can prove to be useful in ascertaining the efficacy of effluent standards and/or follow-up of pollution control measures.     

Application of Qual2Kw model as a tool for water quality management: Cértima River as a case study

Modelling can be a useful management tool because models allow the understanding of water body response to different pollution pressure scenarios which may help on the decision-making process and in prosecuting the Water Framework Directive objectives. This study aims to evaluate the usage of simple water quality models (Qual2Kw) applied to small river basins in order to better understand the response of a river to different loads of nitrogen and phosphorus. Qual2Kw model was applied to Cértima River (Portugal), a small river that ends in a shallow lake called Pateira Fermentelos and represents a very important ecosystem to the local community. Along its pathway, Cértima River has a significant enrichment in nutrients due to agriculture, livestock, domestic sewage and industrial effluents discharged into the river. In case of nitrogen, the highest loads are from domestic (44%) and diffuse (35%) sources. The main sources of phosphorous are domestic (46%), livestock (24%) and diffuse sources (20%). Cértima River is strongly enriched with nutrients, and neither nitrogen nor phosphorous is limiting the algal growth. According to the criterion of Dodds et al. (Water Res, 32(5):1455-1462, 1998), the river is classified as eutrophic. By comparing in stream measurements with Qual2Kw simulations, it can be concluded that it would be necessary to decrease the actual pollutants loads of nitrogen and phosphorous 5 and 10 times, respectively, in order to change Cértima River classification from eutrophic to mesotrophic.     

中国底栖动物水质生物监测指数和水质等级构建

水质生物监测是水生态环境质量管理的重要内容,构建实用性强的生物指数有助于推动中国的水质生物监测工作。根据江苏、浙江、辽宁、江西和湖南等省份的溪流与河流湖泊共计839个底栖动物数据,将中国已有的底栖动物科级分类单元水质敏感性分值打分表扩充和修订至159个科。采用统计法分别构建了符合中国可涉水水体(溪流等)和不可涉水水体(河流、湖泊等)底栖动物分值指数(Chinese Macroinvertebrate Score Index,CMSI)和底栖动物平均分值指数(Average Chinese Macroinvertebrate Score Index,ACMSI)及水质评价等级体系。CMSI和ACMSI与总氮、总磷、高锰酸盐指数和溶解氧之间Pearson相关性显著,表明研究构建的CMSI和ACMSI是可以反映水质变化的。建议通过实践进一步验证CMSI和ACMSI的可靠性和实用性。     

湖泊富营养化机理模型研究进展

湖泊富营养化机理模型是模拟和预测水质参数变化趋势和水体富营养化状态的有效工具,可为水环境污染预防和治理提供数据支撑与科学依据。在回顾湖泊富营养化机理模型分类及发展的基础上,重点分析和总结了CAEDYM模型、PCLake模型、AQUATOX模型和WASP模型等生态动力学模型研究热点,探讨了各个模型的适用性与局限性;并进一步从湖泊富营养化影响机制探究和水质水环境管理保护决策服务两方面梳理了富营养化模型的应用现状,指出了富营养化机理模型当前存在的问题与发展方向,旨在为模型研究和应用提供参考。     

Sensitivity of Simulated Conservation Practice Effectiveness to Representation of Field and In-Stream Processes in the Little River Watershed

Evaluating the effectiveness of conservation practices (CPs) is an important step to achieving efficient and successful water quality management. Watershed-scale simulation models can provide useful and convenient tools for this evaluation, but simulated conservation practice effectiveness should be responsive to parameter values used to represent the practices in the modeling. The objectives of this study were to (1) assess the impacts of a set of conservation practices on hydrology and water quality of a watershed and (2) evaluate the sensitivity of Soil and Water Assessment Tool (SWAT) modeling outputs and simulated conservation practice effectiveness to parameters. The modeling study was conducted in an agricultural watershed, the subwatershed K (16.9 km²) of the Little River Experimental watershed located in the South Atlantic Coastal Plain of the USA. Sensitivity analysis showed that hydrologic response unit (HRU) and watershed-scale simulations for water quality were most sensitive to CN and FILTERW parameters. Load reduction rates as a function of increased aerial coverage of the conservation practices were greatest for total phosphorus (TP), followed by sediment and total nitrogen (TN). The results indicated that conservation practices would have a limited impact on stream flow volume but could have a significant impact on sediment and TP loads within this region. Watershed-scale TN and TP loads were also sensitive to an in-stream nutrient transformation process represented using the QUAL2E algorithm in SWAT. The study clearly demonstrated the most sensitive model parameters and the optimal conservation practices for this watershed.     

Using diatoms as quality indicators for a newly-formed urban lake and its catchment

Periphytic diatoms were studied to evaluate the water quality of a newly created lake, formed by the enclosure of the formerly tidal Cardiff Bay (Wales, UK), and the effects of two inflowing rivers which drain densely populated and industrialised catchments. Seven sites in Cardiff Bay and two locations on the inflowing rivers were monitored for diatoms and water chemistry over 2 years. Water quality was assessed using a revised UK trophic diatom index (TDI) and new methods to determine ecological quality ratios and ecological status classes as required by the EU Water Framework Directive. Diatom assemblages reflected spatiotemporal variations in environmental conditions between the rivers and Cardiff Bay and within the bay. In the bay, diatoms reflected differences in river quality and possibly local pollution in certain areas of the lake. High values of the TDI indicated eutrophic to hypertrophic conditions in both rivers and in the bay and diatoms indicated poor ecological status.     

基于WASP 7模型的水质模拟应用——以淮沭新河东海段为例

应用WASP 7模型的EUTRO子模块对淮沭新河东海段的溶解氧(DO)和化学需氧量(COD)指标进行模拟研究,采用2014年与2015年的水文、水质数据进行模型参数率定,并以2016年1月—2017年9月的水质数据进行验证,验证结果为DO和COD的模拟值与实际值的相对误差分别能控制在15%和10%以内,线性回归分析结论显示相关系数R2均在0.9以上,表明两者的吻合度较高。     

Sensitivity analysis of water quality for Delhi stretch of the River Yamuna,India

Simulation models are used to aid the decision makers about water pollution control and management in river systems. However, uncertainty of model parameters affects the model predictions and hence the pollution control decision. Therefore, it often is necessary to identify the model parameters that significantly affect the model output uncertainty prior to or as a supplement to model application to water pollution control and planning problems. In this study, sensitivity analysis, as a tool for uncertainty analysis was carried out to assess the sensitivity of water quality to (a) model parameters (b) pollution abatement measures such as wastewater treatment, waste discharge and flow augmentation from upstream reservoir. In addition, sensitivity analysis for the “best practical solution” was carried out to help the decision makers in choosing an appropriate option. The Delhi stretch of the river Yamuna was considered as a case study. The QUAL2E model is used for water quality simulation. The results obtained indicate that parameters K ₁ (deoxygenation constant) and K ₃ (settling oxygen demand), which is the rate of biochemical decomposition of organic matter and rate of BOD removal by settling, respectively, are the most sensitive parameters for the considered river stretch. Different combinations of variations in K ₁ and K ₂ also revealed similar results for better understanding of inter-dependability of K ₁ and K ₂. Also, among the pollution abatement methods, the change (perturbation) in wastewater treatment level at primary, secondary, tertiary, and advanced has the greatest effect on the uncertainty of the simulated dissolved oxygen and biochemical oxygen demand concentrations.     

On the use of multivariate statistical methods for combining in-stream monitoring data and spatial analysis to characterize water quality conditions in the White River Basin,Indiana, USA

Mechanistic hydrologic and water quality models provide useful alternatives for estimating water quality in unmonitored streams. However, developing these elaborate models for large watersheds can be time-consuming and expensive, in addition to challenges that arise during calibration when there is limited spatial and/or temporal monitored in-stream water quality data. The main objective of this research was to investigate different approaches for developing multivariate analysis models as alternative methods for rapidly assessing relationships between spatio-temporal physical attributes of the watershed and water quality conditions in monitored streams, and then using the developed relationships for estimating water quality conditions in unmonitored streams. The study compares the use of various statistical estimates (mean, geometric mean, trimmed mean, and median) of monitored water quality variables to represent annual and seasonal water quality conditions. The relationship between these estimates and the spatial data is then modeled via linear and non-linear multivariate methods. Overall, the non-linear techniques for classification outperformed the linear techniques with an average cross-validation accuracy of 79.7%. Additionally, the geometric mean based models outperformed models based on other statistical indicators with an average cross-validation accuracy of 80.2%. Dividing the data into annual and quarterly datasets also offered important insights into the behavior of certain water quality variables impacted by seasonal variations. The research provides useful guidance on the use and interpretation of the various statistical estimates and statistical models for multivariate water quality analyses.     

Water Quality Evaluation and Trend Analysis in Selected Watersheds of the Atlantic Region of Canada

Water quality indices (WQIs) have been developed to assess the suitability of water for a variety of uses. These indices reflect the status of water quality in lakes, streams, rivers, and reservoirs. The concept of WQIs is based on a comparison of the concentration of contaminants with the respective environmental standards. The number, frequency, and magnitude by which the environmental standards for specific variables are not met in a given time period are reflected in WQIs. Further, the water quality trend analysis predicts the behavior of the water quality parameters and overall water quality in the time domain. In this paper, the concept of WQI was applied to three selected watersheds of Atlantic region: the Mersey River, the Point Wolfe River, and the Dunk River sites. To have robust study, two different water quality indices are used: Canadian Water Quality Index (CWQI), and British Columbia Water Quality Index (BWQI). The complete study was conducted in two steps. The first step was to organize and process the data into a format compatible with WQI analysis. After processing the input data, the WQI was calculated. The second step outlined in the paper discusses detailed trend analysis using linear and quadratic models for all the three sites. As per the 25 years trend analysis, overall water quality for agriculture use observed an improving trend at all the three sites studied. Water quality for raw water used for drinking (prior to treatment) and aquatic uses has shown improving trend at Point Wolfe River. It is further observed that pH, SO₄, and NO₃ concentrations are improving at Dunk River, Mersey River, and Point Wolfe River sites. To ascertain the reliability and significance of the trend analysis, a detailed error analysis and parametric significance tests were also conducted It was observed that for most of the sites and water uses quadratic trend models were a better fit than the linear models.     

Instream-Flow Needs for Anadromous Salmonids and Lamprey on the Pacific Coast, with Special Reference to the Pacific Southwest

This paper addresses differences in instream-flow needs (IFNs) of Pacific salmonids and lamprey across species, life stages, and stream sizes on the Pacific coast, with additional consideration of salmonid-IFN data from northern Europe. The Pacific Southwest data set was for various life stages of coho salmon and steelhead trout in small coastal streams of central and southern California. These data showed that younger life stages required less flow than adults. The Pacific Northwest data set was for spawning adults of all five salmon species and steelhead trout in Washington or northern California. These data showed that spawning salmonids required more flow, relative to mean annual flow, in smaller streams. Although these IFNs varied by species, all were much higher than IFNs to protect wetted perimeters (rearing habitat) and water quality in these streams. The high-flow guild included chinook, pink, and chum salmon, whereas the low-flow guild included coho and sockeye salmon. Steelhead were unique in showing relatively high spawning IFNs for creeks and small rivers, unlike large rivers, such that IFNs were more affected by stream size for this species than salmon.     

Water and waste load allocation in rivers with emphasis on agricultural return flows: application of fractional factorial analysis

In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.     

Chemical monitoring of river water bodies in an EU outermost region: examples from the Azores archipelago (Portugal)

Chemical monitoring of water quality on a total of 16 rivers in the Azores archipelago (Portugal), since 2003, made it possible to identify the major pressures and spatial geochemical variations along main course of the rivers. River water pollution is to a large extent associated to point sources, namely domestic wastewater discharges, especially in urban areas, and diffuse sources, associated with pasture land, and explain the high values on BOD(5) and nutrients (P and N). Heavy metals and metalloids, as well as hydrocarbons and pesticides, are generally under the detection limits of the analytical methods. Generally, river water reflects pollution loads according to a simple model, derived from land use in the watershed: in the upper part conditions are pristine, in the intermediate portion of the basin pasture land dominates and near the coast urban discharges are increasingly important. Results stress the role that an approach based on the watershed scale, coupled with land use management measures, are crucial to water management procedures and a successful WFD implementation in small river basin districts like the Azores. The paper also shows the need for full compliance regarding EU directives on urban wastewater and nitrate pollution due to agriculture.