A two-phase grey fuzzy optimization approach for water quality management of a river system

An extension of the Grey Fuzzy Waste Load Allocation Model (GFWLAM) developed in an earlier work is presented here to address the problem of multiple solutions. Formulation of GFWLAM is based on the approach for solving fuzzy multiple objective optimization problems with max–min as the operator, which usually may not result in a unique solution. The multiple solutions of fuzzy multiobjective optimization model should be obtained as parametric equations or equations that represent a subspace. A two-phase optimization technique, two-phase GFWLAM, is developed to capture all alternative or multiple solutions of GFWLAM. The optimization model in Phase 1 is exactly same as the optimization model described in GFWLAM. The optimization model in Phase 2 maximizes the upper bounds of fractional removal levels of pollutants and minimizes the lower bounds of fractional removal levels of pollutants keeping the value of goal fulfillment level same as obtained from Phase 1. The widths of the interval-valued fractional removal levels play an important role in decision-making as these can be adjusted within their intervals by the decision-maker considering technical and economic feasibility in the final decision scheme. Two-phase GFWLAM widens the widths of interval-valued removal levels of pollutants, thus enhancing the flexibility in decision-making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.     

Uncertainty assessment for watershed water quality modeling: A Probabilistic Collocation Method based approach

Watershed water quality models are increasingly used in management. However, simulations by such complex models often involve significant uncertainty, especially those for non-conventional pollutants which are often poorly monitored. This study first proposed an integrated framework for watershed water quality modeling. Within this framework, Probabilistic Collocation Method (PCM) was then applied to a WARMF model of diazinon pollution to assess the modeling uncertainty. Based on PCM, a global sensitivity analysis method named PCM-VD (VD stands for variance decomposition) was also developed, which quantifies variance contribution of all uncertain parameters. The study results validated the applicability of PCM and PCM-VD to the WARMF model. The PCM-based approach is much more efficient, regarding computational time, than conventional Monte Carlo methods. It has also been demonstrated that analysis using the PCM-based approach could provide insights into data collection, model structure improvement and management practices. It was concluded that the PCM-based approach could play an important role in watershed water quality modeling, as an alternative to conventional Monte Carlo methods to account for parametric uncertainty and uncertainty propagation.     

A stochastic conflict resolution model for water quality management in reservoir–river systems

In this paper, optimal operating rules for water quality management in reservoir–river systems are developed using a methodology combining a water quality simulation model and a stochastic GA-based conflict resolution technique. As different decision-makers and stakeholders are involved in the water quality management in reservoir–river systems, a new stochastic form of the Nash bargaining theory is used to resolve the existing conflict of interests related to water supply to different demands, allocated water quality and waste load allocation in downstream river. The expected value of the Nash product is considered as the objective function of the model which can incorporate the inherent uncertainty of reservoir inflow. A water quality simulation model is also developed to simulate the thermal stratification cycle in the reservoir, the quality of releases from different outlets as well as the temporal and spatial variation of the pollutants in the downstream river. In this study, a Varying Chromosome Length Genetic Algorithm (VLGA), which has computational advantages comparing to other alternative models, is used. VLGA provides a good initial solution for Simple Genetic Algorithms and comparing to Stochastic Dynamic Programming (SDP) reduces the number of state transitions checked in each stage. The proposed model, which is called Stochastic Varying Chromosome Length Genetic Algorithm with water Quality constraints (SVLGAQ), is applied to the Ghomrud Reservoir–River system in the central part of Iran. The results show, the proposed model for reservoir operation and waste load allocation can reduce the salinity of the allocated water demands as well as the salinity build-up in the reservoir.     

A derived probability distribution approach to stormwater quality modeling

The closed-form analytical stormwater quality models are developed for simulating urban catchment pollutant buildup and washoff processes. By integrating the rainfall–runoff transformation with pollutant buildup and washoff functions, stormwater quality measures, such as the cumulative distribution functions (CDFs) of pollutant loads, the expected value of pollutant event mean concentrations (EMCs) and the average annual pollutant load can be derived. This paper presents methodologies and major procedures for the development of urban stormwater quality models based on derived probability distribution theory. In order to investigate the spatial variation in model parameters and its impact on stormwater pollutant buildup and washoff processes as well as pollutant loads to receiving waters, an extended form of the original rainfall–runoff transformation which is based on lumped runoff coefficient approach is proposed to differentiate runoff generation mechanisms between the impervious and pervious areas of the catchment. In addition, as a contrast to the aggregated pollutant buildup models formulated with a single lumped buildup parameter, the disaggregated form of the pollutant buildup model is proposed by introducing a number of physically-based parameters associated with pollutant buildup and washoff processes into the pollutant load models. The results from the case study indicate that analytical urban stormwater management model are capable of providing results in good agreement with the field measurements, and can be employed as alternatives to continuous simulation models in the evaluation of long-term stormwater quality measures.     

The influence of land use patterns on water quality at multiple spatial scales in a river system

The influence of land use patterns on water quality in a river system is scale‐dependent. In this study, a four‐order hierarchical arrangement method was used to select water sampling sites and to delineate sub‐basins in the Daliao River Basin, China. The 20 sub‐basins were classified into four spatial scales that represented four different stream orders. Pearson correlation analysis was used to quantify relationships between land use composition and the river's physical‐chemical variables for all samples collected. This analysis showed that the presence of forest cover was associated with higher water quality at the scale of the whole basin. The scale effects of land use patterns on water quality were then examined using stepwise multiple regression analysis that compared different land use types with water quality variables. The results from this analysis showed that urban areas, as opposed to forest areas, became the most significant contributors of water pollutants when scale effects were considered. The influence of urban land cover on water pollution was significantly higher at larger scales. The lack of a significant regression correlation for the forest land use type at smaller scales revealed that forest located upstream of the Daliao River Basin did not provide a buffer for improved water quality. Further analysis showed that this result could be because of disproportionate spatial distributions for forest and urban land use types. The topographic characteristics of sub‐basins, such as average slope (S) and size (A), were determined to be secondary explanatory variables that affected land use impacts on stream water quality. Areas with steep slopes were associated with increased water oxygenation, whereas areas with flatter slopes were associated with higher concentrations of pollutants. These results are significant because they can provide a better understanding of the appropriate spatial scale required for effective river basin management in the future. Copyright © 2013 John Wiley & Sons, Ltd.     

太湖流域典型滨湖河网水动力与水质时空异质性

基于中国太湖梅梁湾东部的无锡市滨湖区河网29个监测点在丰水期、平水期和枯水期的流速和水质监测数据,将河网分为梁溪河、曹王泾、骂蠡港、城市河网南区以及城市河网北区5个区域,对流速和典型水质指标的时空异质性进行分析,结合主成分分析和相关性分析,得到各区域水动力与水质现状及其成因.结果显示:梁溪河和曹王泾的水质条件和水动力条件较好,多数水质因子与流速表现出了强相关性;骂蠡港的水质和流速区域变化明显,表现弱相关性;城市河网北区和南区的流速较缓,河道污染负荷较大,流速与水质因子之间的相关性较低.通过在滨湖河网开展流速和水质的野外监测,分析流速对于河网水环境的实际效果,验证不同水质指标与流速之间的响应关系,为滨湖河网区水质保护和科学的水污染治理技术提供基础支撑.     

Processes governing river water quality identified by principal component analysis

The present study demonstrates the usefulness of principal component analysis in condensing and interpreting multivariate time‐series of water quality data. In a case study the water quality system of the lock‐regulated part of the River Neckar (Germany) was analysed, with special emphasis on the oxygen budget. Pooled data of ten water quality parameters and discharge, which had been determined at six stations along a 200 km reach of the river between the years 1993 and 1998, were subjected to principal component analysis. The analysis yielded four stable principal components, explaining 72% of the total variance of the 11 parameters. The four components could be interpreted confidently in terms of underlying processes: biological activity, dilution by high discharge, seasonal effects and the influence of wastewater. From analysing the data of single stations separately, these processes were found to be active throughout the complete reach. Considering the oxygen budget of the river, the variance of biological activity, representing the counteracting processes of primary production and microbial degradation, was found to be most important. This principal component explained 79% of the observed variance of oxygen saturation. In contrast, the analysis of a reduced data set from the 1970s showed that oxygen saturation was then dominated by discharge and temperature variations. The findings indicate that the oxygen budget used to be governed directly by the emission of degradable matter, whereas nowadays eutrophication is most important for extreme oxygen concentrations. Therefore, controlling eutrophication has to be the primary goal, in order to mitigate the rare episodes of pronounced oxygen over‐ and undersaturation in the future. Copyright © 2002 John Wiley & Sons, Ltd.     

Two-dimensional modeling of channel evolution under the influence of large-scale river regulation works

In the middle and lower reaches of alluvial rivers, various kinds of river regulation projects affecting natural channel evolution often are distributed due to the requirements of flood control, navigation,and channel stability. However, the influence of large-scale river regulation works on fluvial processes is not fully known. Therefore, a two-dimensional(2D) morphodynamic model has been improved to address this problem. The new detailed procedure is presented in this paper:(i) First, each nod...     

Implementing of the JPWSPC method in RIV1H for unsteady flow modeling in general river networks

RIV1H is the stand-alone hydraulic program of CE-QUAL-RIV1, a longitudinal hydraulic and water quality model developed by U.S. Army Corps of Engineers Waterways Experiment Station. RIV1H solves the Saint-Venant equations using the widely accepted four-point implicit Preissmann scheme, and the resulting nonlinear equations are solved using the Newton-Raphson method. RIV1H is capable of simulating multiple branches, and in-stream hydraulic control structures. It treats tributary networks using a double sweep algorithm based on upstream ordering of the branches. It treats the control structures following a downstream solution order, which also is based on the upstream ordering of the branches. Since an upstream ordering cannot be achieved for looped networks, RIV1H is only applicable to non-looped tributary networks. In the current study, the junction-point water stage prediction and correction (JPWSPC) method is extended to take into account the control structures and the method is used to improve the RIV1H model, enabling it to be applied to both non-looped and looped networks with in-stream hydraulic control structures. The JPWSPC method makes the linear equation system for each segment complete while maintaining the banded property, thus the system can be independently and efficiently solved. It has the advantages to be efficient, robust, and very suitable for parallel computing. The improved RIV1H model was tested using two idealized networks and the results demonstrated the success of the improvement.     

Risk minimization in water quality control problems of a river system

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte–Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga–Bhadra river system in southern India, with a steady state BOD–DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality.     

Modeling river/reservoir system management, water allocation, and supply reliability

The state of Texas has implemented a modeling system for assessing the availability and reliability of water resources that consists of a generalized simulation model called the Water Rights Analysis Package (WRAP) and input datasets for the state's 23 river basins. Reservoir/river system management and water allocation practices are simulated using historical naturalized monthly streamflow sequences to represent basin hydrology. Institutional systems for allocating streamflow and reservoir storage resources among numerous water users are considered in detail in evaluating basinwide impacts of water management decisions. The generalized WRAP model is a flexible tool that may be applied to river basins anywhere. The Texas experience in implementing a statewide modeling system illustrates issues that are relevant to water management in many other regions of the world.     

Strontium isotope identification of water mixing and recharge sources in a river system (Oder River,central Europe): A quantitative approach

This study uses Sr isotope composition (⁸⁷Sr/⁸⁶Sr) and Sr content of waters of the Oder, one of the largest rivers in central Europe, to fingerprint natural and anthropogenic contributions to its Sr budget and to evaluate water mixing processes in its hydrological system. It also demonstrates a simple method of quantifying natural and anthropogenic Sr inputs in the watershed. The method has potential for environmental and archaeological research because past Sr geochemistry of river water can easily be reconstructed. For the first time, a catchment‐scale impact of anthropogenic sources on the Sr budget of a middle‐size river is shown in a quantitative way. The water of the Oder is characterized by a relatively uniform Sr isotope composition, from 0.7100 to 0.7108, contrasting with strong variations in Sr concentration, from 0.25 to 1.27 mg/L. There is a general seasonal trend in variability, with waters becoming more radiogenic and dilute with respect to the Sr in the spring time. This Sr systematics differs significantly from the Sr budgets of the majority of the Oder tributaries that exhibit more radiogenic composition and systematically lower Sr concentrations. A mixing scenario in the Oder involves Sr contribution from four principal water sources: (a) shallow ground waters with Sr derived from near‐surface weathering of silicates, (b) moderately radiogenic mine waters from the Upper Silesian Coal Basin, (c) unradiogenic mine waters from the Permian sequence of the copper district, and (d) unradiogenic ground waters from shallow‐seated Palaeogene, Neogene, and Mesozoic aquifers. The Sr budget of the Oder is primarily controlled by inputs of dissolved Sr from anthropogenic sources, which overprint the natural background, controlled by geology. Thus, about 47.5% of Sr originates from agriculture, industrial, and municipal additions, 31.5% from mine water inputs, and only 21% from natural sources, that is, rock weathering and atmospheric precipitation. Reconstruction of the past Sr chemistry of the Oder reveals that its present‐day Sr isotope composition is temporary and significantly different from that of the preindustrial times.     

Grey fuzzy optimization model for water quality management of a river system

A grey fuzzy optimization model is developed for water quality management of river system to address uncertainty involved in fixing the membership functions for different goals of Pollution Control Agency (PCA) and dischargers. The present model, Grey Fuzzy Waste Load Allocation Model (GFWLAM), has the capability to incorporate the conflicting goals of PCA and dischargers in a deterministic framework. The imprecision associated with specifying the water quality criteria and fractional removal levels are modeled in a fuzzy mathematical framework. To address the imprecision in fixing the lower and upper bounds of membership functions, the membership functions themselves are treated as fuzzy in the model and the membership parameters are expressed as interval grey numbers, a closed and bounded interval with known lower and upper bounds but unknown distribution information. The model provides flexibility for PCA and dischargers to specify their aspirations independently, as the membership parameters for different membership functions, specified for different imprecise goals are interval grey numbers in place of a deterministic real number. In the final solution optimal fractional removal levels of the pollutants are obtained in the form of interval grey numbers. This enhances the flexibility and applicability in decision-making, as the decision-maker gets a range of optimal solutions for fixing the final decision scheme considering technical and economic feasibility of the pollutant treatment levels. Application of the GFWLAM is illustrated with case study of the Tunga–Bhadra river system in India.     

A coupled hierarchical modeling approach to simulating the geomorphic response of river systems to anthropogenic climate change

Anthropogenic climate change is expected to change the discharge and sediment transport regime of river systems. Because rivers adjust their channels to accommodate their typical inputs of water and sediment, changes in these variables can potentially alter river morphology. In this study, a hierarchical modeling approach was developed and applied to examine potential changes in reach‐averaged bedload transport and spatial patterns of erosion and deposition for three snowmelt‐dominated gravel‐bed rivers in the interior Pacific Northwest. The modeling hierarchy was based on discharge and suspended‐sediment load from a basin‐scale hydrologic model driven by a range of downscaled climate‐change scenarios. In the field, channel morphology and sediment grain‐size data for all three rivers were collected. Changes in reach‐averaged bedload transport were estimated using the Bedload Assessment of Gravel‐bedded Streams (BAGS) software, and the Cellular Automaton Evolutionary Slope and River (CAESAR) model was used to simulate the spatial pattern of erosion and deposition within each reach to infer potential changes in channel geometry and planform. The duration of critical discharge was found to control bedload transport. Changes in channel geometry were simulated for the two higher‐energy river reaches, but no significant morphological changes were found for a lower‐energy reach with steep, cohesive banks. Changes in sediment transport and river morphology resulting from climate change could affect the management of river systems for human and ecological uses. Copyright © 2015 John Wiley & Sons, Ltd.     

Simulating and predicting river discharge time series using a wavelet‐neural network hybrid modelling approach

Accurate simulation and prediction of the dynamic behaviour of a river discharge over any time interval is essential for good watershed management. It is difficult to capture the high‐frequency characteristics of a river discharge using traditional time series linear and nonlinear model approaches. Therefore, this study developed a wavelet‐neural network (WNN) hybrid modelling approach for the predication of river discharge using monthly time series data. A discrete wavelet multiresolution method was employed to decompose the time series data of river discharge into sub‐series with low (approximation) and high (details) frequency, and these sub‐series were then used as input data for the artificial neural network (ANN). WNN models with different wavelet decomposition levels were employed to predict river discharge 48 months ahead of time. Comparison of results from the WNN models with those of the ANN models alone indicated that WNN models performed a more accurate prediction. Copyright © 2011 John Wiley & Sons, Ltd.     

World continental modeling for water resources using system dynamics

This research assesses the severity of future water scarcity and its impact on the growth of human civilization through system dynamics modeling of the world at regional level. Six sectors of activities are modeled in each continent to represent the human society. Continental interactions such as migration and trade are also modeled to express the synergy of activities among the various continents. Results of the model simulations from 1960 to 2100 show that water scarcity, unlike other limitations such as nonrenewable resources and persistent pollution, gives severe, detrimental problems within short delays after its occurrence.     

Dynamic attribution of global water demand to surface water and groundwater resources: Effects of abstractions and return flows on river discharges

As human water demand is increasing worldwide, pressure on available water resources grows and their sustainable exploitation is at risk. To mimic changes in exploitation intensity and the connecting feedbacks between surface water and groundwater systems, a dynamic attribution of demand to water resources is necessary. However, current global-scale hydrological models lack the ability to do so. This study explores the dynamic attribution of water demand to simulated water availability. It accounts for essential feedbacks, such as return flows of unconsumed water and riverbed infiltration. Results show that abstractions and feedbacks strongly affect water allocation over time, particularly in irrigated areas. Also residence time of water is affected, as shown by changes in low flow magnitude, frequency, and timing. The dynamic representation of abstractions and feedbacks makes the model a suitable tool for assessing spatial and temporal impacts of changing global water demand on hydrology and water resources.     

Water quality along a river continuum subject to point and diffuse sources

The water quality along the River Kennet, in the Thames basin of southern England, was examined in terms of the influence of point- and diffuse-nutrient inputs. The river is supplied mainly from a Cretaceous Chalk aquifer and hence the waters are of a calcium bicarbonate type. The nitrate largely comes from agricultural sources, with concentrations decreasing downstream due to plant uptake and probable denitrification. In contrast, soluble reactive phosphorus (SRP) is largely associated with sewage inputs and concentrations increase downstream in line with effluents from major towns such as Newbury and Reading. Adjacent to the river in the lower half of the catchment is the Kennet and Avon Canal and the two are in places hydrologically connected. The canal inputs may influence calcium carbonate (calcite) precipitation and increase suspended sediment and particulate phosphorus concentrations in the river. Monitoring upstream and downstream of Marlborough sewage treatment works (STW) showed that SRP concentrations in the effluent were highly variable due to variable efficiency of P stripping and still sufficiently concentrated to dominate downstream river SRP with potential impacts on stream ecology. Biological recovery in this river following P stripping at STWs is complex and controlling those spikes in SRP that are above a threshold of 100 μg l⁻¹ may be a critical requirement. More stringent effluent targets than are currently recommended may be needed (less than 800 μg RP l⁻¹) to achieve good ecological status in this river depending on SRP concentrations upstream.     

Protein‐like fluorescence intensity as a possible tool for determining river water quality

The results of a comparison between chemical water quality determinants and river water fluorescence on the River Tyne, NE England, demonstrate that tryptophan‐like fluorescence intensity shows statistically significant relationships between nitrate, phosphate, ammonia, biochemical oxygen demand (BOD) and dissolved oxygen. Tryptophan‐like fluorescence intensity at the 280 nm excitation/350 nm emission wavelength fluorescence centre correlates with both phosphate (r = 0·80) and nitrate (r = 0·87), whereas tryptophan‐like fluorescence intensity at the 220 nm excitation/350 nm emission wavelength centre correlates with BOD (r = 0·85), ammonia (r = 0·70) and dissolved oxygen (r = ?0·65). The strongest correlations are between tryptophan‐like fluorescence intensity and nitrate and phosphate, which in the Tyne catchment derive predominantly from point and diffuse source sewage inputs. The correlation between BOD and the tryptophan‐like fluorescence intensity suggests that this fluorescence centre is related to the bioavailable or labile dissolved organic matter pool. The weakest correlations are observed between tryptophan‐like fluorescence intensity and ammonia concentration and dissolved oxygen. The weaker correlation with ammonia is due to removal of the ammonia signal by wastewater treatment, and that with dissolved oxygen due to the natural aeration of the river such that this is not a good indicator of water quality. The observed correlations only hold true when treated sewage, sewerage overflows or cross connections, or agricultural organic pollutants dominate the water quality—this is not true for two sites where airport deicer (propylene glycol, which is non‐fluorescent) or landfill leachate (which contains high concentrations of humic and fulvic‐like fluorescent DOM) dominate the dissolved organic matter in the river. Mean annual tryptophan‐like fluorescence intensity agrees well with the General Water Quality Assessment as determined by the England and Wales environmental regulators, the Environment Agency. Copyright © 2004 John Wiley & Sons, Ltd.