A model for the analysis of seasonal aspects of water quality control

A multiseasonal mathematical programming model for the analysis of water quality control within a river basin is presented. Phenomena of interseasonal variation in flow intensity and the river's pollutant assimilative capacity are introduced into the model by defining several seasons and their characterizations by seasonal parameters. An application of the model to a typical case situation is reported. The results suggest that seasonal adjustments in the treatment levels of wastewater treatment plants involve a considerable saving potential in comparison with a situation in which treatment levels are rigidly determined for the entire year.     

An integrated model for structure optimization and technology screening of urban wastewater systems

The conventional approach to wastewater system design and planning considers each component separately and does not provide the optimum performance of the entire system. However, the growing concern for environmental protection, economic efficiency, and sustainability of urban wastewater systems requires an integrated modeling of subsystems and a synthetic evaluation of multiple objectives. In this study, a multi-objective optimization model of an integrated urban wastewater system was developed. The model encompasses subsystems, such as a sewer system, stormwater management, municipal wastewater treatment, and a wastewater reclamation system. The non-dominated sorting genetic algorithm (NSGA-II) was used to generate a range of system design possibilities to optimize conflicting environmental and economic objectives. Information from a knowledge base, which included rules for generating treatment trains as well as the performance characteristics of commonly used water pollution control measures, was utilized. The trade-off relationships between the objectives, total water pollution loads to the environment, and life cycle costs (which consist of investment as well as operation and maintenance costs), can be illustrated using Pareto charts. The developed model can be used to assist decision makers in the preliminary planning of system structure. A benchmark city was constructed to illustrate the methods of multi-objective controls, highlight cost-effective water pollution control measures, and identify the main pressures on urban water environment.     

Design of a water quality monitoring network in a large river system using the genetic algorithm

Despite several decades of operations and the increasing importance of water quality monitoring networks, the authorities still rely on experiential insights and subjective judgments in siting water quality monitoring stations. This study proposes an integrated technique which uses a genetic algorithm (GA) and a geographic information system (GIS) for the design of an effective water quality monitoring network in a large river system. In order to develop a design scheme, planning objectives were identified for water quality monitoring networks and corresponding fitness functions were defined using linear combinations of five selection criteria that are critical for developing a monitoring system. The criteria include the representativeness of a river system, compliance with water quality standards, supervision of water use, surveillance of pollution sources and examination of water quality changes. The fitness levels were obtained through a series of calculations of the fitness functions using GIS data. A sensitivity analysis was performed for major parameters such as the numbers of generations, population sizes and probability of crossover and mutation, in order to determine a good fitness level and convergence for optimum solutions. The proposed methodology was applied to the design of water quality monitoring networks in the Nakdong River system, in Korea. The results showed that only 35 out of 110 stations currently in operation coincide with those in the new network design, therefore indicating that the effectiveness of the current monitoring network should be carefully re-examined. From this study, it was concluded that the proposed methodology could be a useful decision support tool for the optimized design of water quality monitoring networks.     

特定小流域水质模型的选择

根据特定小流域的水文特点和实际要求，建立一个流域综合水质模型，它由三个子模型支持，即：河流水质模型、水库富养营化模型和非点源污染模型。本工作对河流水质模型（ＱＵＡＬ２ＥＵ）加以改进，使之适应Ｗ河的具体情况，并在ＱＵＡＬ２ＥＵ增加了模拟ＣＯＤ、网箱养鱼和底泥泛起的功能。完成了作了水源地的水库地的水库富营养化模型，解决了流域内农业耕作、污水灌溉等造成的非点源污染随降雨径流进入水体过程的模拟和计算，使之     

A linear program model for point-nonpoint source control decisions: Theoretical development

A linear programming model for point-nonpoint pollutant source control decisions has been developed. Total phosphorus was highlighted as the water quality substance of concern, although the methodology presented is general enough to permit its use for other substances.The linear program was formulated to minimize the cost of meeting established constraints. Methods to achieve removal of pollutant sources included point and nonpoint (urban and rural) techniques. Constraints were established on the basis of available removal technologies and water quality considerations. The final model is presented in a form such that use of existing linear and separable program software is possible.     

A simulation framework for water allocation to meet the environmental requirements of urban rivers: model development and a case study for the Liming River in Daqing City,China

In this paper, we describe the development of a simulation framework for allocating water from different sources to meet the environmental flows of an urban river. The model permits the development of a rational balance in the utilization of storm water, reclaimed water from wastewater treatment plants, and freshwater from reservoirs with consideration of the limited capacities of different water resources. It is designed to permit the full utilization of unconventional water sources for the restoration of river water quality by increasing river flow and improving water quality. To demonstrate practical use of the model, a case study is presented in which the model was used to simulate the environmental water allocation for the Liming River in Daqing City, China, based on the three water sources mentioned above. The results demonstrate that the model provides an effective approach for helping managers allocate water to satisfy the river’s environmental water requirements.     

Water quality prediction of copper-molybdenum mining-beneficiation wastewater based on the PSO-SVR model

● Data acquisition and pre-processing for wastewater treatment were summarized. ● A PSO-SVR model for predicting COD_eff in wastewater was proposed. ● The COD_eff prediction performances of the three models in the paper were compared. ● The COD_eff prediction effects of different models in other studies were discussed. The mining-beneficiation wastewater treatment is highly complex and nonlinear. Various factors like influent quality, flow rate, pH and chemical dose, tend to restrict the effluent effectiveness of mining-beneficiation wastewater treatment. Chemical oxygen demand (COD) is a crucial indicator to measure the quality of mining-beneficiation wastewater. Predicting COD concentration accurately of mining-beneficiation wastewater after treatment is essential for achieving stable and compliant discharge. This reduces environmental risk and significantly improves the discharge quality of wastewater. This paper presents a novel AI algorithm PSO-SVR, to predict water quality. Hyperparameter optimization of our proposed model PSO-SVR, uses particle swarm optimization to improve support vector regression for COD prediction. The generalization capacity tested on out-of-distribution (OOD) data for our PSO-SVR model is strong, with the following performance metrics of root means square error (RMSE) is 1.51, mean absolute error (MAE) is 1.26, and the coefficient of determination (R²) is 0.85. We compare the performance of PSO-SVR model with back propagation neural network (BPNN) and radial basis function neural network (RBFNN) and shows it edges over in terms of the performance metrics of RMSE, MAE and R², and is the best model for COD prediction of mining-beneficiation wastewater. This is because of the less overfitting tendency of PSO-SVR compared with neural network architectures. Our proposed PSO-SVR model is optimum for the prediction of COD in copper-molybdenum mining-beneficiation wastewater treatment. In addition, PSO-SVR can be used to predict COD on a wide variety of wastewater through the process of transfer learning.     

Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved Bayesian-Markov chain Monte Carlo algorithm

● A hydrodynamic-Bayesian inference model was developed for water pollution tracking. ● Model is not stuck in local optimal solutions for high-dimensional problem. ● Model can estimate source parameters accurately with known river water levels. ● Both sudden spill incident and normal sewage inputs into the river can be tracked. ● Model is superior to the traditional approaches based on the test cases. Water quality restoration in rivers requires identification of the locations and discharges of pollution sources, and a reliable mathematical model to accomplish this identification is essential. In this paper, an innovative framework is presented to inversely estimate pollution sources for both accident preparedness and normal management of the allowable pollutant discharge. The proposed model integrates the concepts of the hydrodynamic diffusion wave equation and an improved Bayesian-Markov chain Monte Carlo method (MCMC). The methodological framework is tested using a designed case of a sudden wastewater spill incident (i.e., source location, flow rate, and starting and ending times of the discharge) and a real case of multiple sewage inputs into a river (i.e., locations and daily flows of sewage sources). The proposed modeling based on the improved Bayesian-MCMC method can effectively solve high-dimensional search and optimization problems according to known river water levels at pre-set monitoring sites. It can adequately provide accurate source estimation parameters using only one simulation through exploration of the full parameter space. In comparison, the inverse models based on the popular random walk Metropolis (RWM) algorithm and microbial genetic algorithm (MGA) do not produce reliable estimates for the two scenarios even after multiple simulation runs, and they fall into locally optimal solutions. Since much more water level data are available than water quality data, the proposed approach also provides a cost-effective solution for identifying pollution sources in rivers with the support of high-frequency water level data, especially for rivers receiving significant sewage discharges.     

Ammonium in Fließgewässern des Saale-Einzugsgebietes

Exposure assessment of rarely measured substances or newly identified chemicals requires the usage of mathematical methods. The georeferenced exposure model GREAT-ER was designed to accurately predict the concentration of ‘down-the-drain’ chemicals under consideration of their spatial and temporal variability in surface waters. In the past, successful validations of the model have been performed predominantly for small and middle-sized catchments and were accompanied by extensive monitoring of the detergent-ingredients boron and linear alkylbenzene sulphonate (LAS). A proof of the adaptability of GREAT-ER to large catchments is given here by example of the Saale river basin. Furthermore, it could be shown that ammonium is a suitable parameter for validations of the model. This corroborated the hypothesis that the non-point-emissions of ammonium are of less importance in comparison to the ammonium loads in the effluents of wastewater treatment plants.     

Source and material balance of total organic halogen pollution in the Ayase River system,Japan

The total organic halogen (TOX) pollution in the highly polluted Ayase River system was investigated. Using the concentration of coexisting linear undecylbenzenesulfonate and the difference in the flowing water volume between summer and winter, the fractions of domestic and agricultural wastewaters in the whole water column were calculated and the variety of the TOX sources in the river was estimated. The river carried about 100 kgCl of TOX materials in one day; about 50 kgCl of the materials was from residential area in the basin. The contribution of agricultural drainage from paddy field was not negligible in summer. Highly contribution of industrial wastewater was observed in a tributary Furuayase River basin while the amount of TOX loaded in the area was widely varied; 0–105 kgCl of the materials was discharged as industrial wastewater.     

Assesment of the response of a shallow macrotidal estuary to changes in hydrological and wastewater inputs through numerical modelling

The aim of this study was to investigate the response to short-term changes in river freshwater discharges and in nutrients loadings (mainly from the treatment of urban wastewater), of the shallow macrotidal Urdaibai estuary (north of Spain), by using numerical tools. A two-dimensional hydrodynamic model and a water quality model were applied to the estuary, in order to better use it as a prediction tool in the study of the effects of variations in hydrodynamic conditions and in waste water inputs. The model was calibrated and verified using data measured under different hydrological conditions (spring and summer). A model calibration was carried out with field data measured during the summer, while the model validation was conducted for spring conditions. The calibration process allowed the model parameter definition, while the model validation permitted the verification of the calibrated parameters under different environmental conditions. The model results were in reasonable agreement with field measurements, in both the calibration and the validation phases. The model showed a significant decrease in phytoplankton concentration with river input increase. A study on the effects of nutrient input reduction from the Gernika Waste Water Treatment Plant (WWTP) was conducted. It showed a decrease in phytoplankton concentration with decreasing levels of nutrient discharge. This reduction was more pronounced in conjunction with the highest river discharge. In that case, a 50% decrease for the elimination of the WWTP discharge was observed.     

沿河城市多点污染排放量优化控制

本文针对沿河城市污染排放的情况,分析了污染物排放对河流造成的污染,并根据Streeter—Phelps模型和城市河流对水质的要求,建立了沿河城市多点污染排放优化控制的线性规划模模,并编制了计算程序用来求解该数学模型.文中提供的算例及计算结果表明,本文提出的沿河城市多点污染排放量优化控制方法对城市排水系统的建设有较大的指导意义.     

Eco-hydrological modelling in a highly regulated lowland catchment to find measures for improving water quality

Water quality modelling in the meso-scale Rhin catchment in the German federal state Brandenburg was done (1) to answer some specific questions concerning identification of point and diffuse sources of nutrient pollution in the catchment, (2) to assess the influences of possible climate and land use changes on water quantity and quality and (3) to evaluate potential measures to be done in order to achieve a “good ecological status” of the river and its lakes as required by the Water Framework Directive (WFD).The Rhin catchment is a typical highly regulated lowland river basin in Northern Germany. The regulations complicate water quantity and quality modelling in the catchment. The research was done by using the eco-hydrological model SWIM (Soil and Water Integrated Model), which simulates water and nutrient fluxes in soil and vegetation, as well as transport of water and nutrients to and within the river network. The modelling period was from 1981 until 2005. After calibrating the hydrological processes at different gauges within the basin with satisfactory results, water quality (nitrogen and phosphorus) modelling was done taking into account the emissions of different point sources (sewage treatment plants, etc.) and identifying the amount of diffuse pollution caused mainly by agriculture.For suggesting some feasible measures to improve water quality and to reduce diffuse pollution considering possible climate and land use changes, different reasonable scenarios were applied in consultation with the Environmental Agency of Brandenburg (LUA). The study revealed that the amount of water discharge has significant influence on the concentration of nutrients in the river network, and that nitrogen pollution, caused mainly by diffuse sources, could be notably reduced by application of agricultural measures, whereas the pollution by phosphorus could be diminished most effectively by the reduction of point source emissions.     

邯郸市沁河水污染治理方案

本文对邯郸市沁河水污染现状进行了调查分析，总结了城市内河治理经验，通过方案比较，推荐“清淤，护坡，建坝，分质截污，邯钢废水混凝沉淀处理”为沁河治理方案。     

Development of a coupled reservoir operation and water diversion model: Balancing human and environmental flow requirements

Maintaining a natural flow regime helps preserve the health of riverine ecosystems. Conventional studies on reservoir operations have focused mainly on identifying optimal operational schemes for satisfying human water demands. To systematically reflect the ecological effects of both natural and human-induced hydrologic alterations, water diversions downstream of the reservoirs should be considered as well. This research focused on a coupled reservoir operation and water diversion (CROWD) model, created through the integration of a reservoir operation model and a water diversion model. The proposed model considers both human and environmental flow requirements, and represents a compromise that balances ecological protection (preservation of the natural flow regime of a river) and human needs (reduced water shortages). In the reservoir operation model, the reservoir space is divided into three zones and different operating rules are developed for directing reservoir operation when water levels are in different zones; in the water diversion model, different water users are assigned different supply priorities with the instream flows no more than the minimum environmental flows having the highest priority; and the two models are coupled by the water mass balance between the two hydraulic facilities. The non-dominated-sorting genetic algorithm II (NSGA-II) was used to determine the parameters of the developed CROWD model and the model was applied to support the joint operational management of the Tanghe Reservoir and the Liaoyang Diversion in the Tang river basin, China. The resulting reservoir operation and water diversion schemes indicate that the CROWD model is useful for optimizing the operation of reservoirs and water diversion schemes. Moreover, it helps to analyze tradeoffs between human and environmental water needs, resulting in solutions that reduce the risk of water shortages and minimize ecological integrity disturbances.     

Defining and modelling the coastal zone affected by the Po river (Italy)

One of the most important sources of pollution in coastal zones (CZ) is certainly that one produced by human activities in the associated river basin. Understanding the linkage between water quality in CZ and river catchments is important in order to better assess CZ processes and to evaluate different management options aimed at improving the coastal ecosystem state. CZ water quality targets as identified by the Water Framework Directive (EC 2000/60) require an accurate study of the effects of pollutant loads coming from river discharge.In order to evaluate the impacts of human activities in river catchments on the associated coastal zone, a sound definition for this geographic area is needed. Many definitions for this area have been proposed in different contexts. The definition is generally built upon a particular goal, and is henceforth highly variable according to the different purposes. In this paper a general methodology allowing to discern those areas of the sea that are directly influenced by fluvial discharge is presented. The methodology is based on the variation pattern of sea water characteristics, and provides a numerical evaluation of this influence. In particular an analysis based on salinity as tracer, results in a sound definition of this area. The methodology has been applied on the case study of the Po river. Due to the significant nutrient loads discharged by the river, the CZ associated with Po is affected by severe eutrophication phenomena that have important consequences on the ecosystem and on the socio-economy of the area.In order to study the impacts of nutrients loads carried by the river, a water quality model (WASP6) has been implemented. The model simulates the seasonal variability of nutrient concentrations, phytoplankton biomass and dissolved oxygen. Using the CZ model is possible to compare the effects of variations of nutrient loads on the biochemical (short term) and ecological (long term) quality of the coastal environment. This is accomplished by feeding nutrients loads forecasted for different scenarios by the catchment model (MONERIS) as forcing functions to the CZ model. This way the effect of the different catchment management scenarios are propagated to the CZ model, and the trophic conditions of the coastal ecosystem evaluated using TRIX.This study has been developed in the context of the European project EUROCAT.     

Economic efficiency and equity in water quality control: Effluent taxes and information requirements

Water quality standards for any river system can be achieved under numerous management programs or assignment patterns for waste treatment responsibility. This study examines three effluent charge (tax) programs along with a management program based on equal percentage treatment. Each program is developed within the general framework of a water quality management model and is designed to minimize the total real resource cost of waste treatment subject to program constraints (information availability) and water quality standards. An assessment of the relative efficiency and equity of these programs is made within a water quality management simulation of the Patuxent River in Maryland.     

跨界融合子处理高浓度有机废水投资最小化模型研究

以跨界融合子基因工程菌处理高浓度有机废水为研究对象,建立了处理系统投资最小化数学模型及相应的约束方程,探讨该处理系统的优化设计问题。研究中以进水ＢＯＤ浓度Ｓ０、微生物浓度Ｘ和回流比Ｒ为初始控制变量,通过对跨界融合子降解豆制品废水实例验证,表明在给定的初始变量范围内有惟一的最优解,为处理工艺的合理设计提供了依据。     

Assessment of non-point source pollution using a spatial multicriteria analysis approach

Eutrophication caused by the enrichment of nutrients from diffusing sources is degrading surface water quality throughout the world. Assessing the potential contributions of different land areas in diffuse nutrient export has become an important task in non-point source (NPS) pollution control. Existing methods were often limited by the availability of local data and the complexity of model formulation. This study developed a spatial multicriteria method to evaluate the nitrogen loss potential at the basin level. Four criteria were formulated to characterize the source capacity of nitrogen export, the flow path to water body, the efficiency of runoff generation and the climatic driving force. The proposed method is a low-effort approach since the required data is either already available in a global context or easily produced with limited inputs. Being implemented in GIS environment, this method generates maps that can be easily interpreted to provide decision support. The method was applied to the Huai River Basin, China. The results were validated based on the correlation between the nitrogen loss potential of sub-basin and the water quality class of river. The maps of nitrogen loss potential were helpful for examining the regional pattern of diffuse nitrogen loss, and could facilitate the decisions of NPS pollution management at the provincial or basin level.     

Estimation of Wastewater Treatment Objectives through Maximum Entropy

The paper examines how a public wastewater treatment plant balances objectives of cost minimization and pollution prevention. The parameters of the objective function and state equation in an optimal control model are estimated using maximum entropy and time series observations of water quality and expenditures for wastewater treatment. The estimation method does not require restrictions needed by other techniques used to estimate nonlinear, ill-posed problems. The parameter estimates indicate that the treatment plant emphasizes water quality enhancement over cost minimization. Results from the sensitivity analysis show that the plant favors conventional treatment over pollution prevention.