Optimal water and waste-load allocations in rivers using a fuzzy transformation technique: a case study

In this paper, a new methodology is developed for integrated allocation of water and waste-loads in river basins utilizing a fuzzy transformation method (FTM). The fuzzy transformation method is used to incorporate the existing uncertainties in model inputs. In the proposed methodology, the FTM, as a simulation model, is utilized in an optimization framework for constructing a fuzzy water and waste-loads allocation model. In addition, economic as well as environmental impacts of water allocation to different water users are considered. For equitable water and waste load allocation, all possible coalition of water users are considered and total benefit of each coalition, which is a fuzzy number, is reallocated to water users who are participating in the coalition. The fuzzy cost savings are reallocated using a fuzzy nucleolus cooperative game and the FTM. As a case study, the Dez River system in south-west of Iran is modeled and analyzed using the methodology developed here. The results show the effectiveness of the methodology in optimal water and waste-loads allocations under uncertainty.     

River water quality management under incomplete information: application of an N-person iterated signaling game

One of the important issues in river quality management is to provide pollution control strategies which are acceptable for all stakeholders. When there is only one water quality checkpoint in a reach of a river which receives pollution loads of several dischargers and dischargers are penalized for any water quality violation, the game theory can be used for modeling the natural process of bargaining among load dischargers considering the assimilative capacity of a river. There are also some types of uncertainties in river water quality management which should be incorporated throughout the bargaining process. Signaling games can be utilized for modeling the bargaining among dischargers and developing perfect Bayesian equilibrium (PBE) strategies for pollution control. In this paper, a new methodology called N-person iterated signaling game is developed for river quality management considering the existing uncertainties in pollution loads of dischargers. The methodology can provide the stable PBE waste load allocation strategies. The practical utility of the proposed methodology is illustrated by applying it to a reach of the Zarjub River in Iran. This reach includes seven pollution load dischargers.     

Critical Sampling Points Methodology: Case Studies of Geographically Diverse Watersheds

Only with a properly designed water quality monitoring network can data be collected that can lead to accurate information extraction. One of the main components of water quality monitoring network design is the allocation of sampling locations. For this purpose, a design methodology, called critical sampling points (CSP), has been developed for the determination of the critical sampling locations in small, rural watersheds with regard to total phosphorus (TP) load pollution. It considers hydrologic, topographic, soil, vegetative, and land use factors. The objective of the monitoring network design in this methodology is to identify the stream locations which receive the greatest TP loads from the upstream portions of a watershed. The CSP methodology has been translated into a model, called water quality monitoring station analysis (WQMSA), which integrates a geographic information system (GIS) for the handling of the spatial aspect of the data, a hydrologic/water quality simulation model for TP load estimation, and fuzzy logic for improved input data representation. In addition, the methodology was purposely designed to be useful in diverse rural watersheds, independent of geographic location. Three watershed case studies in Pennsylvania, Amazonian Ecuador, and central Chile were examined. Each case study offered a different degree of data availability. It was demonstrated that the developed methodology could be successfully used in all three case studies. The case studies suggest that the CSP methodology, in form of the WQMSA model, has potential in applications world-wide.     

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.     

机场使用除冰液的应急监测

介绍了机场除冰液污染的应急监测,包括监测方案制订、监测点位设置、分析对象确定、跟踪监测、数据分析等。监测结果表明,除冰液废液直排入河道在短期内对水环境造成了严重影响,但随着时间推移水体逐步恢复正常。机场除冰液污染的应急监测可通过监测水体中的化学需氧量进行。     

The impact of traditional coffee processing on river water quality in Ethiopia and the urgency of adopting sound environmental practices

Although waste from coffee processing is a valuable resource to make biogas, compost, and nutrient-rich animal food, it is usually dumped into nearby water courses. We carried out water quality assessment at 44 sampling sites along 18 rivers that receive untreated waste from 23 coffee pulping and processing plants in Jimma Zone, Ethiopia. Twenty upstream sampling sites free from coffee waste impact served as control, and 24 downstream sampling sites affected by coffee waste were selected for comparison. Physicochemical and biological results revealed a significant river water quality deterioration as a result of disposing untreated coffee waste into running water courses. During coffee-processing (wet) season, the highest organic load (1,900?mg/l), measured as biochemical oxygen demand, depleted dissolved oxygen (DO) to a level less than 0.01?mg/l, and thus curtailed nitrification. During off season, oxygen started to recuperate and augmented nitrification. The shift from significantly elevated organic load and reduced DO in the wet season to increased nitrate in the off season was found to be the determining factor for the difference in macroinvertebrate community structure as verified by ordination analysis. Macroinvertebrate diversity was significantly reduced in impacted sites during the wet season contrary to the off season. However, there was a significant difference in the ratio of sensitive to pollution-tolerant taxa in the off season, which remained depreciated in the longer term. This study highlights the urgency of research exploring on the feasibility of adopting appropriate pollution abatement technologies to implement ecologically sound coffee-processing systems in coffee-growing regions of Ethiopia.     

Spatial and temporal trends in water quality in a Mediterranean temporary river impacted by sewage effluents

This paper analyzes how changes in hydrological conditions can affect the water quality of a temporary river that receives direct inputs of sewage effluents. Data from 12 spatial surveys of the Vène river were examined. Physico-chemical parameters, major ion, and nutrient concentrations were measured. Analyses of variance (ANOVA) and multivariate analyses were performed. ANOVA revealed significant spatial differences for conductivity and major ion but no significant spatial differences for nutrient concentrations even if higher average concentrations were observed at stations located downstream from sewage effluent discharge points. Significant temporal differences were observed among all the parameters. Karstic springs had a marked dilution effect on the direct disposal of sewage effluents. During high-flow periods, nutrient concentrations were high to moderate whereas nutrient concentrations ranged from moderate to bad at stations located downstream from the direct inputs of sewage effluents during low-flow periods. Principal component analysis showed that water quality parameters that explained the water quality of the Vène river were highly dependent on hydrological conditions. Cluster analysis showed that when the karstic springs were flowing, water quality was homogeneous all along the river, whereas when karstic springs were dry, water quality at the monitoring stations was more fragmented. These results underline the importance of considering hydrological conditions when monitoring the water quality of temporary rivers. In view of the pollution observed in the Vène river, “good water chemical status” can probably only be achieved by improving the management of sewage effluents during low-flow periods.     

A multi-variate methodology for analyzing pre-existing lake water quality data

Environmental agencies are given the task of monitoring water quality in rivers, lakes, and other bodies of water, for the purpose of comparing the results with regulatory standards. Monitoring follows requirements set by regulations, and data are collected in a systematic way for the intended purpose. Monitoring enables agencies to determine whether water bodies are polluted. Much effort is spent per monitoring event, resulting in hundreds of data points typically used solely for comparison with regulatory standards and then stored for little further use. This paper devises a data analysis methodology that can make use of the pre-existing datasets to extract more useful information on water quality trends, without new sample collection and analysis. In this paper, measured lake water quality data are subjected to statistical analyses including Principal Component Analysis (PCA) to deduce changes in water quality spatially and temporally over several years. It was found that the lake as a whole changed temporally by season, rather than spatially. Storm events caused the greatest shifts in water quality, though the shifts were fairly consistent across sampling stations. This methodology can be applied to similar datasets, especially with the recent emphasis by the U.S. EPA on protection of lakes as water sources. Water quality managers using these techniques may be able to lower their monitoring costs by eliminating redundant water quality parameters found in this analysis.     

Water Quality Assessment of an Untreated Effluent Impacted Urban Stream: The Bharalu Tributary of the Brahmaputra River, India

Guwahati, the lone city on the bank of the entire midstream of the Brahmaputra River, is facing acute civic problem due to severe depletion of water quality of its natural water bodies. This work is an attempt towards water quality assessment of a relatively small tributary of the Brahmaputra called the Bharalu River flowing through the city that has been transformed today into a city drainage channel. By analyzing the key physical, chemical and biological parameters for samples drawn from different locations, an assessment of the dissolved load and pollution levels at different segments in the river was made. Locations where the contaminants exceeded the permissible limits during different seasons were identified by examining spatial and temporal variations. A GIS developed for the watershed with four layers of data was used for evaluating the influence of catchment land use characteristics. BOD, DO and total phosphorus were found to be the sensitive parameters that adversely affected the water quality of Bharalu. Relationship among different parameters revealed that the causes and sources of water quality degradation in the study area were due to catchments input, anthropogenic activities and poor waste management. Elevated levels of total phosphorus, BOD and depleted DO level in the downstream were used to develop an ANN model by taking total phosphorus and BOD as inputs and dissolved oxygen as output, which indicated that an ANN based predictive tool can be utilized for monitoring water quality in the future.     

A fuzzy multi-stakeholder multi-criteria methodology for water allocation and reuse in metropolitan areas

In this paper, a fuzzy decision making methodology is proposed to find a socially optimal scenario for allocating effluent of wastewater treatment plants and urban and suburban runoffs to agricultural regions and recharging aquifers. The presented methodology named modified fuzzy social choice (MFSC) considers multi-stakeholder multi-criteria problems under uncertainties inherent in a decision making process utilizing a fuzzy ranking method and the fuzzy social choice (FSC) theory. A set of water and wastewater allocation scenarios are proposed for water quantity and quality management of the study area, while six main stakeholders with conflicting utilities and different negotiation powers are involved. The proposed methodology is applied to Tehran metropolitan area, the capital city of Iran with the population of about 8 million people, to examine its applicability and effectiveness. The results shows that using fuzzy multi-stakeholder multi-criteria decision making method considering equal and different negotiation powers can lead to different outcomes. Based on the results, the MFSC method, which considers a number of decision makers having different negotiation powers, degrees of importance of decision making criteria, and some important uncertainties, performs more promising in real water resources management problems.     

太湖主要入湖河流排污控制量研究

利用2006—2008年的监测数据对太湖主要入湖河流的水环境状况进行了分析,通过对研究区工业污染源、农业污染源和城镇生活污水排污的分布以及入河情况的调查,对各种污染源的入河量进行了计算,根据确定的水质目标,分别计算出主要入湖河流以及区域水系的水环境容量和排污控制量。结果表明:15条主要入湖河流超标现象显著,近3a来污染程度有所波动,N、P污染最为严重。研究区内污染物入河量较大,未接管的生活源污染物入河量所占比重最大,各类污染物均在50%～60%之间;张家港市的污染物入河量最大,各类污染物所占比重达总入河量的18%～20%。研究区内河网密布,水环境容量分布不均匀,望虞河、直湖港、武进港等7条河流水环境容量较大,张家港市区域水环境容量较大。为保证水质达标,研究区内近期共须削减CODCr66554.38t/a、NH4-N8105.71t/a、TP1324.42t/a;远期共须削减CODCr96719.08t/a、NH4-N11541.45t/a、TP1788.71t/a。     

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.     

Assessment of temporal variation in water quality of some important rivers in middle Gangetic plains, India

The study explains water quality of three important tributaries of the Ganga River in the middle Gangetic plains in India. Seasonal changes in the water quality of the studied rivers: Gandak, Ghaghra, and Sone were observed. During monsoon, several water quality parameters show considerable changes due to increased runoff from the catchments and other seasonal factors. Multivariate discriminant analysis delineated a few parameters responsible for temporal variation in water quality. Seasonal variation in water quality of the Gandak River was rendered by seven parameters??turbidity, sulfate, pH, phosphate, water temperature, total alkalinity, and sodium, while total alkalinity and water temperature were responsible for seasonal discrimination in water quality of Ghaghra River. Water temperature, turbidity, total dissolved solids, total suspended solids, calcium, and phosphate were important for seasonal discrimination in water quality of Sone River. The seasonal changes in water quality of the rivers were due to seasonal effects and catchment characteristics. The discriminant functions classified most of the cases correctly.     

A dynamic statistical experiment for atmospheric interactions

Interactions among atmospheric parameters exist at different scales. The pristine approach for observational or model data analysis involves changing the input parameters one at a time (OAT) and studying the effect on the system. Limitations of this approach for atmospheric applications are discussed. A fractional factorial (FF) based study is evolved and a methodology is outlined involving dynamic graphical analysis. Observational data from the FIFE and HAPEX‐MOBILHY experiments are utilized with a vegetation and soil moisture scheme dynamically coupled in a planetary boundary layer model to demonstrate the robustness of this approach. Both low‐resolution and high‐resolution designs are considered. Various aspects of the vegetation‐atmosphere interactions are delineated. Results obtained from the interaction‐based FF approach differ considerably from the earlier OAT‐type studies.     

基于GWLF模型的于桥水库入库河流水文模拟及氮磷负荷估算

流域模型技术应用是当前开展面源污染防治的重要工具,而水文过程的准确模拟是进行污染负荷估算的首要环节和关键步骤。为了弄清近年来于桥水库入库河流氮、磷输入负荷,选取GWLF模型对水平口子流域的水文过程进行模拟,首先利用2006—2018年气象、水文资料率定模型水文参数,然后将参数推广到整个流域,对2019—2020年3条主要入库河流流量进行模拟,最后乘以相应河流断面的总氮、总磷浓度估算氮磷输入负荷。结果显示：GWLF模型适用于研究区的水文过程模拟,校准期和验证期的纳氏系数分别为0.89和0.91,平均相对误差分别为12.2%和13.1%;2020年总氮入库负荷为3 977.0 t,其中引滦调水贡献占57.0%,3条入库河流共贡献43.0%;总磷入库负荷为48.8 t,其中引滦调水贡献占68.6%,3条入库河流共贡献31.4%。GWLF模型输入数据需求量较少,模型参数较少,模拟效果较好,适用于中小型流域的水资源和水环境管理,具有一定的推广应用前景。     

城市河流水质参数空间变异性研究——以苏南某市为例

基于现场的采样数据,结合河流自身特点,应用地质统计学的理论和方法分析了苏南某城市河流水质参数的空间变异规律及其原因。研究结果表明,根据变差函数模型分析,发现研究区河流3个水质参数在一定范围内存在空间相关性;研究区河流的CODMn呈现中南部较高,其他部位相对均匀的趋势,CODMn的空间变异性主要是由居民的日常活动及河道的自身特点引起;研究区河流的TP和NH3-N含量严重超标,水体富营养化程度严重。TP和NH3-N的空间变异性相似,含量较高区域集中在研究区的西南部、东南部和东北部,其空间变异性主要由工业活动和居民日常生活共同作用引起,其中工业活动占主导作用。     

A probabilistic water quality index for river water quality assessment: a case study

Available water quality indices have some limitations such as incorporating a limited number of water quality variables and providing deterministic outputs. This paper presents a hybrid probabilistic water quality index by utilizing fuzzy inference systems (FIS), Bayesian networks (BNs), and probabilistic neural networks (PNNs). The outputs of two traditional water quality indices, namely the indices proposed by the National Sanitation Foundation and the Canadian Council of Ministers of the Environment, are selected as inputs of the FIS. The FIS is trained based on the opinions of several water quality experts. Then the trained FIS is used in a Monte Carlo analysis to provide the required input-output data for training both the BN and PNN. The trained BN and PNN can be used for probabilistic water quality assessment using water quality monitoring data. The efficiency and applicability of the proposed methodology is evaluated using water quality data obtained from water quality monitoring system of the Jajrood River in Iran.     

太湖流域河流入河污染负荷通量与入湖水质响应关系分析——以殷村港为例

以2020年1—12月太湖主要入湖河流殷村港水质自动监测站的监测数据及2020年太湖水位资料为依据,构建了一维水量水质耦合数学模型,建立了入河污染负荷通量与入湖控制断面水质响应关系,以入太湖控制断面殷村港站达Ⅲ类水质水为目标,模拟计算了殷村港站主要污染物入湖水质变化过程。结果表明,殷村港站高锰酸盐指数、氨氮、总磷等水质指标浓度最大值均明显的降低,其中氨氮浓度降低幅度相对较大,主要集中于3—6月;高锰酸盐指数和总磷日均入河污染负荷通量变化相对较小,氨氮日均入河污染负荷通量降低幅度相对较大;殷村港站高锰酸盐指数、氨氮、总磷等水质指标年入河污染负荷削减量分别为24.17,41.43,3.87 t。提出,基于核算出的削减量需进一步结合污染负荷通量过程和污染源溯源分析,确定不同水质指标下入河污染负荷控制方向,为科学合理规划殷村港主要污染物的入河污染负荷总量控制提供科学依据。     

A Review of Public Domain Water Quality Models for Simulating Dissolved Oxygen in Rivers and Streams

The review discusses six major public domain water quality models currently available for rivers and streams. These major models, which differ greatly in terms of processes they represent, data inputs requirements, assumptions, modeling capability, their strengths and weaknesses, could yield useful results if appropriately selected for the desired purposes. The public domain models, which are most suitable for simulating dissolved oxygen along rivers and streams, chosen in this review are simulation catchment (SIMCAT), temporal overall model for catchments (TOMCAT), QUAL2Kw, QUAL2EU, water quality analysis simulation program (WASP7), and quality simulation along rivers (QUASAR). Each of these models is described based on a consistent set of criteria-conceptualization, processes, input data, model capability, limitations, model strengths, and its application. The results revealed that SIMCAT and TOMCAT are over-simplistic but useful to quickly assess impact of point sources. The QUAL2Kw has provision for conversion of algal death to carbonaceous biochemical oxygen demand (CBOD) and thus more appropriate than QUAL2EU, where macrophytes play an important interaction. The extensive requirement of data in WASP7 and QUASAR is difficult to justify the time and costs required to set up these complex models. Thus, a single model could not serve all wide range of functionalities required. The choice of a model depends upon availability of time, financial cost and a specific application. This review may help to choose appropriate model for a particular water quality problem.     

Spatiotemporal trend analysis of recent river water quality conditions in Japan

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.