Collaborative Catchment-Scale Water Quality Management using Integrated Wireless Sensor Networks

Science.gov (United States)

Zia, Huma; Harris, Nick; Merrett, Geoff

2013-04-01

collaborative information sharing can have a direct influence on agricultural practice. We apply a nutrient management scheme to a model of an example catchment with several individual networks. The networks are able to correlate catchment events to events within their zone of influence, allowing them to adapt their monitoring and control strategy in light of wider changes across the catchment. Results indicate that this can lead to significant reductions in nutrient losses (up to 50%) and better reutilization of nutrients amongst farms, having a positive impact on catchment scale water quality and fertilizer costs. 1. EC, E.C., Directive 2000/60/EC establishing a framework for Community action in the field of water policy, 2000. 2. Rivers, M., K. Smettem, and P. Davies. Estimating future scenarios for farm-watershed nutrient fluxes using dynamic simulation modelling-Can on-farm BMPs really do the job at the watershed scale? in Proc.29th Int.Conf System Dynamics Society, 2011. 2010. Washington 3. Liu, C., et al., On-farm evaluation of winter wheat yield response to residual soil nitrate-N in North China Plain. Agronomy Journal, 2008. 100(6): p. 1527-1534. 4. Kotamäki, N., et al., Wireless in-situ sensor network for agriculture and water monitoring on a river basin scale in Southern Finland: Evaluation from a data user's perspective. Sensors, 2009. 9(4): p. 2862-2883.

Coordinating standards and applications for optical water quality sensor networks

Science.gov (United States)

Bergamaschi, B.; Pellerin, B.

2011-01-01

Joint USGS-CUAHSI Workshop: In Situ Optical Water Quality Sensor Networks; Shepherdstown, West Virginia, 8-10 June 2011; Advanced in situ optical water quality sensors and new techniques for data analysis hold enormous promise for advancing scientific understanding of aquatic systems through measurements of important biogeochemical parameters at the time scales over which they vary. High-frequency and real-time water quality data also provide the opportunity for early warning of water quality deterioration, trend detection, and science-based decision support. However, developing networks of optical sensors in freshwater systems that report reliable and comparable data across and between sites remains a challenge to the research and monitoring community. To address this, the U.S. Geological Survey (USGS) and the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), convened a 3-day workshop to explore ways to coordinate development of standards and applications for optical sensors, as well as handling, storage, and analysis of the continuous data they produce.

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Science.gov (United States)

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

Modeling water quality in an urban river using hydrological factors--data driven approaches.

Science.gov (United States)

Chang, Fi-John; Tsai, Yu-Hsuan; Chen, Pin-An; Coynel, Alexandra; Vachaud, Georges

2015-03-15

Contrasting seasonal variations occur in river flow and water quality as a result of short duration, severe intensity storms and typhoons in Taiwan. Sudden changes in river flow caused by impending extreme events may impose serious degradation on river water quality and fateful impacts on ecosystems. Water quality is measured in a monthly/quarterly scale, and therefore an estimation of water quality in a daily scale would be of good help for timely river pollution management. This study proposes a systematic analysis scheme (SAS) to assess the spatio-temporal interrelation of water quality in an urban river and construct water quality estimation models using two static and one dynamic artificial neural networks (ANNs) coupled with the Gamma test (GT) based on water quality, hydrological and economic data. The Dahan River basin in Taiwan is the study area. Ammonia nitrogen (NH3-N) is considered as the representative parameter, a correlative indicator in judging the contamination level over the study. Key factors the most closely related to the representative parameter (NH3-N) are extracted by the Gamma test for modeling NH3-N concentration, and as a result, four hydrological factors (discharge, days w/o discharge, water temperature and rainfall) are identified as model inputs. The modeling results demonstrate that the nonlinear autoregressive with exogenous input (NARX) network furnished with recurrent connections can accurately estimate NH3-N concentration with a very high coefficient of efficiency value (0.926) and a low RMSE value (0.386 mg/l). Besides, the NARX network can suitably catch peak values that mainly occur in dry periods (September-April in the study area), which is particularly important to water pollution treatment. The proposed SAS suggests a promising approach to reliably modeling the spatio-temporal NH3-N concentration based solely on hydrological data, without using water quality sampling data. It is worth noticing that such estimation can be

Modelling raw water quality: development of a drinking water management tool.

Science.gov (United States)

Kübeck, Ch; van Berk, W; Bergmann, A

2009-01-01

Ensuring future drinking water supply requires a tough management of groundwater resources. However, recent practices of economic resource control often does not involve aspects of the hydrogeochemical and geohydraulical groundwater system. In respect of analysing the available quantity and quality of future raw water, an effective resource management requires a full understanding of the hydrogeochemical and geohydraulical processes within the aquifer. For example, the knowledge of raw water quality development within the time helps to work out strategies of water treatment as well as planning finance resources. On the other hand, the effectiveness of planed measurements reducing the infiltration of harmful substances such as nitrate can be checked and optimized by using hydrogeochemical modelling. Thus, within the framework of the InnoNet program funded by Federal Ministry of Economics and Technology, a network of research institutes and water suppliers work in close cooperation developing a planning and management tool particularly oriented on water management problems. The tool involves an innovative material flux model that calculates the hydrogeochemical processes under consideration of the dynamics in agricultural land use. The program integrated graphical data evaluation is aligned on the needs of water suppliers.

Methods for computing water-quality loads at sites in the U.S. Geological Survey National Water Quality Network

Science.gov (United States)

Lee, Casey J.; Murphy, Jennifer C.; Crawford, Charles G.; Deacon, Jeffrey R.

2017-10-24

The U.S. Geological Survey publishes information on concentrations and loads of water-quality constituents at 111 sites across the United States as part of the U.S. Geological Survey National Water Quality Network (NWQN). This report details historical and updated methods for computing water-quality loads at NWQN sites. The primary updates to historical load estimation methods include (1) an adaptation to methods for computing loads to the Gulf of Mexico; (2) the inclusion of loads computed using the Weighted Regressions on Time, Discharge, and Season (WRTDS) method; and (3) the inclusion of loads computed using continuous water-quality data. Loads computed using WRTDS and continuous water-quality data are provided along with those computed using historical methods. Various aspects of method updates are evaluated in this report to help users of water-quality loading data determine which estimation methods best suit their particular application.

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

Science.gov (United States)

Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

2015-09-15

The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

A combined geostatistical-optimization model for the optimal design of a groundwater quality monitoring network

Science.gov (United States)

Kolosionis, Konstantinos; Papadopoulou, Maria P.

2017-04-01

Monitoring networks provide essential information for water resources management especially in areas with significant groundwater exploitation due to extensive agricultural activities. In this work, a simulation-optimization framework is developed based on heuristic optimization methodologies and geostatistical modeling approaches to obtain an optimal design for a groundwater quality monitoring network. Groundwater quantity and quality data obtained from 43 existing observation locations at 3 different hydrological periods in Mires basin in Crete, Greece will be used in the proposed framework in terms of Regression Kriging to develop the spatial distribution of nitrates concentration in the aquifer of interest. Based on the existing groundwater quality mapping, the proposed optimization tool will determine a cost-effective observation wells network that contributes significant information to water managers and authorities. The elimination of observation wells that add little or no beneficial information to groundwater level and quality mapping of the area can be obtain using estimations uncertainty and statistical error metrics without effecting the assessment of the groundwater quality. Given the high maintenance cost of groundwater monitoring networks, the proposed tool could used by water regulators in the decision-making process to obtain a efficient network design that is essential.

Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India).

Science.gov (United States)

Mavukkandy, Musthafa Odayooth; Karmakar, Subhankar; Harikumar, P S

2014-09-01

The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented. Significant multivariate statistical techniques like principal component analysis (PCA) and principal factor analysis (PFA) have been employed to evaluate the efficiency of the surface water quality monitoring network with monitoring stations as the evaluated variables for the interpretation of complex data matrix of the river basin. The main objective is to identify significant monitoring stations that must essentially be included in assessing annual and seasonal variations of river water quality. Moreover, the significance of seasonal redesign of the monitoring network was also investigated to capture valuable information on water quality from the network. Results identified few monitoring stations as insignificant in explaining the annual variance of the dataset. Moreover, the seasonal redesign of the monitoring network through a multivariate statistical framework was found to capture valuable information from the system, thus making the network more efficient. Cluster analysis (CA) classified the sampling sites into different groups based on similarity in water quality characteristics. The PCA/PFA identified significant latent factors standing for different pollution sources such as organic pollution, industrial pollution, diffuse pollution and faecal contamination. Thus, the present study illustrates that various multivariate statistical techniques can be effectively employed in sustainable management of water resources. The effectiveness of existing river water quality monitoring

Two modelling approaches to water-quality simulation in a flooded iron-ore mine (Saizerais, Lorraine, France): a semi-distributed chemical reactor model and a physically based distributed reactive transport pipe network model.

Science.gov (United States)

Hamm, V; Collon-Drouaillet, P; Fabriol, R

2008-02-19

The flooding of abandoned mines in the Lorraine Iron Basin (LIB) over the past 25 years has degraded the quality of the groundwater tapped for drinking water. High concentrations of dissolved sulphate have made the water unsuitable for human consumption. This problematic issue has led to the development of numerical tools to support water-resource management in mining contexts. Here we examine two modelling approaches using different numerical tools that we tested on the Saizerais flooded iron-ore mine (Lorraine, France). A first approach considers the Saizerais Mine as a network of two chemical reactors (NCR). The second approach is based on a physically distributed pipe network model (PNM) built with EPANET 2 software. This approach considers the mine as a network of pipes defined by their geometric and chemical parameters. Each reactor in the NCR model includes a detailed chemical model built to simulate quality evolution in the flooded mine water. However, in order to obtain a robust PNM, we simplified the detailed chemical model into a specific sulphate dissolution-precipitation model that is included as sulphate source/sink in both a NCR model and a pipe network model. Both the NCR model and the PNM, based on different numerical techniques, give good post-calibration agreement between the simulated and measured sulphate concentrations in the drinking-water well and overflow drift. The NCR model incorporating the detailed chemical model is useful when a detailed chemical behaviour at the overflow is needed. The PNM incorporating the simplified sulphate dissolution-precipitation model provides better information of the physics controlling the effect of flow and low flow zones, and the time of solid sulphate removal whereas the NCR model will underestimate clean-up time due to the complete mixing assumption. In conclusion, the detailed NCR model will give a first assessment of chemical processes at overflow, and in a second time, the PNM model will provide more

Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

Science.gov (United States)

Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

2017-12-01

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

Assessment of the water quality monitoring network of the Piabanha River experimental watersheds in Rio de Janeiro, Brazil, using autoassociative neural networks.

Science.gov (United States)

Villas-Boas, Mariana D; Olivera, Francisco; de Azevedo, Jose Paulo S

2017-09-01

Water quality monitoring is a complex issue that requires support tools in order to provide information for water resource management. Budget constraints as well as an inadequate water quality network design call for the development of evaluation tools to provide efficient water quality monitoring. For this purpose, a nonlinear principal component analysis (NLPCA) based on an autoassociative neural network was performed to assess the redundancy of the parameters and monitoring locations of the water quality network in the Piabanha River watershed. Oftentimes, a small number of variables contain the most relevant information, while the others add little or no interpretation to the variability of water quality. Principal component analysis (PCA) is widely used for this purpose. However, conventional PCA is not able to capture the nonlinearities of water quality data, while neural networks can represent those nonlinear relationships. The results presented in this work demonstrate that NLPCA performs better than PCA in the reconstruction of the water quality data of Piabanha watershed, explaining most of data variance. From the results of NLPCA, the most relevant water quality parameter is fecal coliforms (FCs) and the least relevant is chemical oxygen demand (COD). Regarding the monitoring locations, the most relevant is Poço Tarzan (PT) and the least is Parque Petrópolis (PP).

Comparing risk of failure models in water supply networks using ROC curves

International Nuclear Information System (INIS)

Debon, A.; Carrion, A.; Cabrera, E.; Solano, H.

2010-01-01

The problem of predicting the failure of water mains has been considered from different perspectives and using several methodologies in engineering literature. Nowadays, it is important to be able to accurately calculate the failure probabilities of pipes over time, since water company profits and service quality for citizens depend on pipe survival; forecasting pipe failures could have important economic and social implications. Quantitative tools (such as managerial or statistical indicators and reliable databases) are required in order to assess the current and future state of networks. Companies managing these networks are trying to establish models for evaluating the risk of failure in order to develop a proactive approach to the renewal process, instead of using traditional reactive pipe substitution schemes. The main objective of this paper is to compare models for evaluating the risk of failure in water supply networks. Using real data from a water supply company, this study has identified which network characteristics affect the risk of failure and which models better fit data to predict service breakdown. The comparison using the receiver operating characteristics (ROC) graph leads us to the conclusion that the best model is a generalized linear model. Also, we propose a procedure that can be applied to a pipe failure database, allowing the most appropriate decision rule to be chosen.

Comparing risk of failure models in water supply networks using ROC curves

Energy Technology Data Exchange (ETDEWEB)

Debon, A., E-mail: andeau@eio.upv.e [Centro de Gestion de la Calidad y del Cambio, Dpt. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica de Valencia, E-46022 Valencia (Spain); Carrion, A. [Centro de Gestion de la Calidad y del Cambio, Dpt. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica de Valencia, E-46022 Valencia (Spain); Cabrera, E. [Dpto. De Ingenieria Hidraulica Y Medio Ambiente, Instituto Tecnologico del Agua, Universidad Politecnica de Valencia, E-46022 Valencia (Spain); Solano, H. [Universidad Diego Portales, Santiago (Chile)

2010-01-15

The problem of predicting the failure of water mains has been considered from different perspectives and using several methodologies in engineering literature. Nowadays, it is important to be able to accurately calculate the failure probabilities of pipes over time, since water company profits and service quality for citizens depend on pipe survival; forecasting pipe failures could have important economic and social implications. Quantitative tools (such as managerial or statistical indicators and reliable databases) are required in order to assess the current and future state of networks. Companies managing these networks are trying to establish models for evaluating the risk of failure in order to develop a proactive approach to the renewal process, instead of using traditional reactive pipe substitution schemes. The main objective of this paper is to compare models for evaluating the risk of failure in water supply networks. Using real data from a water supply company, this study has identified which network characteristics affect the risk of failure and which models better fit data to predict service breakdown. The comparison using the receiver operating characteristics (ROC) graph leads us to the conclusion that the best model is a generalized linear model. Also, we propose a procedure that can be applied to a pipe failure database, allowing the most appropriate decision rule to be chosen.

Dynamic hydraulic models to study sedimentation in drinking water networks in detail

Directory of Open Access Journals (Sweden)

I. W. M. Pothof

2012-12-01

Full Text Available Sedimentation in drinking water networks can lead to discolouration complaints. A sufficient criterion to prevent sedimentation in the Dutch drinking water networks is a daily maximum velocity of 0.25 m s⁻¹. Flushing experiments have shown that this criterion is a sufficient condition for a clean network, but not a necessary condition. Drinking water networks include many locations with a maximum velocity well below 0.25 m s⁻¹ without accumulated sediments. Other criteria need to be developed to predict which locations are susceptible to sedimentation and to prevent sedimentation in future networks. More distinctive criteria are helpful to prioritise flushing operations and to prevent water quality complaints.

The authors use three different numerical modelling approaches – quasi-steady, rigid column and water hammer – with a temporal discretisation of 1 s in order to assess the influence of unsteady flows on the wall shear stress, causing resuspension of sediment particles. The model predictions are combined with results from flushing experiments in the drinking water distribution system of Purmerend, the Netherlands. The waterhammer model does not result in essentially different flow distribution patterns, compared to the rigid column and quasi-steady modelling approach. The extra information from the waterhammer model is a velocity oscillation of approximately 0.02 m s⁻¹ around the quasi-steady solution. The presence of stagnation zones and multiple flow direction reversals seem to be interesting new parameters to predict sediment accumulation, which are consistent with the observed turbidity data and theoretical considerations on critical shear stresses.

Water quality modeling in the dead end sections of drinking water (Supplement)

Data.gov (United States)

U.S. Environmental Protection Agency — Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to...

A review of hydrological/water-quality models

Directory of Open Access Journals (Sweden)

Liangliang GAO,Daoliang LI

2014-12-01

Full Text Available Water quality models are important in predicting the changes in surface water quality for environmental management. A range of water quality models are wildly used, but every model has its advantages and limitations for specific situations. The aim of this review is to provide a guide to researcher for selecting a suitable water quality model. Eight well known water quality models were selected for this review: SWAT, WASP, QUALs, MIKE 11, HSPF, CE-QUAL-W2, ELCOM-CAEDYM and EFDC. Each model is described according to its intended use, development, simulation elements, basic principles and applicability (e.g., for rivers, lakes, and reservoirs and estuaries. Currently, the most important trends for future model development are: (1 combination models─individual models cannot completely solve the complex situations so combined models are needed to obtain the most appropriate results, (2 application of artificial intelligence and mechanistic models combined with non-mechanistic models will provide more accurate results because of the realistic parameters derived from non-mechanistic models, and (3 integration with remote sensing, geographical information and global position systems (3S ─3S can solve problems requiring large amounts of data.

A Neural Network Model for Prediction of Sound Quality

DEFF Research Database (Denmark)

Nielsen,, Lars Bramsløw

An artificial neural network structure has been specified, implemented and optimized for the purpose of predicting the perceived sound quality for normal-hearing and hearing-impaired subjects. The network was implemented by means of commercially available software and optimized to predict results...... obtained in subjective sound quality rating experiments based on input data from an auditory model. Various types of input data and data representations from the auditory model were used as input data for the chosen network structure, which was a three-layer perceptron. This network was trained by means...... the physical signal parameters and the subjectively perceived sound quality. No simple objective-subjective relationship was evident from this analysis....

STREAMFLOW AND WATER QUALITY REGRESSION MODELING ...

African Journals Online (AJOL)

... downstream Obigbo station show: consistent time-trends in degree of contamination; linear and non-linear relationships for water quality models against total dissolved solids (TDS), total suspended sediment (TSS), chloride, pH and sulphate; and non-linear relationship for streamflow and water quality transport models.

Locations of Sampling Stations for Water Quality Monitoring in Water Distribution Networks.

Science.gov (United States)

Rathi, Shweta; Gupta, Rajesh

2014-04-01

Water quality is required to be monitored in the water distribution networks (WDNs) at salient locations to assure the safe quality of water supplied to the consumers. Such monitoring stations (MSs) provide warning against any accidental contaminations. Various objectives like demand coverage, time for detection, volume of water contaminated before detection, extent of contamination, expected population affected prior to detection, detection likelihood and others, have been independently or jointly considered in determining optimal number and location of MSs in WDNs. "Demand coverage" defined as the percentage of network demand monitored by a particular monitoring station is a simple measure to locate MSs. Several methods based on formulation of coverage matrix using pre-specified coverage criteria and optimization have been suggested. Coverage criteria is defined as some minimum percentage of total flow received at the monitoring stations that passed through any upstream node included then as covered node of the monitoring station. Number of monitoring stations increases with the increase in the value of coverage criteria. Thus, the design of monitoring station becomes subjective. A simple methodology is proposed herein which priority wise iteratively selects MSs to achieve targeted demand coverage. The proposed methodology provided the same number and location of MSs for illustrative network as an optimization method did. Further, the proposed method is simple and avoids subjectivity that could arise from the consideration of coverage criteria. The application of methodology is also shown on a WDN of Dharampeth zone (Nagpur city WDN in Maharashtra, India) having 285 nodes and 367 pipes.

A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

Science.gov (United States)

Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

2016-06-01

There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

Putting people into water quality modelling.

Science.gov (United States)

Strickert, G. E.; Hassanzadeh, E.; Noble, B.; Baulch, H. M.; Morales-Marin, L. A.; Lindenschmidt, K. E.

2017-12-01

Water quality in the Qu'Appelle River Basin, Saskatchewan is under pressure due to nutrient pollution entering the river system from major cities, industrial zones and agricultural areas. Among these stressors, agricultural activities are basin-wide; therefore, they are the largest non-point source of water pollution in this region. The dynamics of agricultural impacts on water quality are complex and stem from decisions and activities of two distinct stakeholder groups, namely grain farmers and cattle producers, which have different business plans, values, and attitudes towards water quality. As a result, improving water quality in this basin requires engaging with stakeholders to: (1) understand their perspectives regarding a range of agricultural Beneficial Management Practices (BMPs) that can improve water quality in the region, (2) show them the potential consequences of their selected BMPs, and (3) work with stakeholders to better understand the barriers and incentives to implement the effective BMPs. In this line, we held a series of workshops in the Qu'Appelle River Basin with both groups of stakeholders to understand stakeholders' viewpoints about alternative agricultural BMPs and their impact on water quality. Workshop participants were involved in the statement sorting activity (Q-sorts), group discussions, as well as mapping activity. The workshop outcomes show that stakeholder had four distinct viewpoints about the BMPs that can improve water quality, i.e., flow and erosion control, fertilizer management, cattle site management, as well as mixed cattle and wetland management. Accordingly, to simulate the consequences of stakeholder selected BMPs, a conceptual water quality model was developed using System Dynamics (SD). The model estimates potential changes in water quality at the farm, tributary and regional scale in the Qu'Appelle River Basin under each and/or combination of stakeholder selected BMPs. The SD model was then used for real

Stochastic model and method of zoning water networks

OpenAIRE

Тевяшев, Андрей Дмитриевич; Матвиенко, Ольга Ивановна

2014-01-01

Water consumption at different time of the day is uneven. The model of steady flow distribution in water-supply networks is calculated for maximum consumption and effectively used in the network design and reconstruction. Quasi-stationary modes, in which the parameters are random variables and vary relative to their mean values are more suitable for operational management and planning of rational network operation modes.Leaks, which sometimes exceed 50 % of the volume of water supplied, are o...

Development of Water Quality Forecasting Models Based on the SOM-ANN on TMDL Unit Watershed in Nakdong River

Science.gov (United States)

KIM, M.; Kim, J.; Baek, J.; Kim, C.; Shin, H.

2013-12-01

It has being happened as flush flood or red/green tide in various natural phenomena due to climate change and indiscreet development of river or land. Especially, water being very important to man should be protected and managed from water quality pollution, and in water resources management, real-time watershed monitoring system is being operated with the purpose of keeping watch and managing on rivers. It is especially important to monitor and forecast water quality in watershed. A study area selected Nak_K as one site among TMDL unit watershed in Nakdong River. This study is to develop a water quality forecasting model connected with making full use of observed data of 8 day interval from Nakdong River Environment Research Center. When forecasting models for each of the BOD, DO, COD, and chlorophyll-a are established considering correlation of various water quality factors, it is needed to select water quality factors showing highly considerable correlation with each water quality factor which is BOD, DO, COD, and chlorophyll-a. For analyzing the correlation of the factors (reservoir discharge, precipitation, air temperature, DO, BOD, COD, Tw, TN, TP, chlorophyll-a), in this study, self-organizing map was used and cross correlation analysis method was also used for comparing results drawn. Based on the results, each forecasting model for BOD, DO, COD, and chlorophyll-a was developed during the short period as 8, 16, 24, 32 days at 8 day interval. The each forecasting model is based on neural network with back propagation algorithm. That is, the study is connected with self-organizing map for analyzing correlation among various factors and neural network model for forecasting of water quality. It is considerably effective to manage the water quality in plenty of rivers, then, it specially is possible to monitor a variety of accidents in water quality. It will work well to protect water quality and to prevent destruction of the environment becoming more and more

System-Aware Smart Network Management for Nano-Enriched Water Quality Monitoring

Directory of Open Access Journals (Sweden)

B. Mokhtar

2016-01-01

Full Text Available This paper presents a comprehensive water quality monitoring system that employs a smart network management, nano-enriched sensing framework, and intelligent and efficient data analysis and forwarding protocols for smart and system-aware decision making. The presented system comprises two main subsystems, a data sensing and forwarding subsystem (DSFS, and Operation Management Subsystem (OMS. The OMS operates based on real-time learned patterns and rules of system operations projected from the DSFS to manage the entire network of sensors. The main tasks of OMS are to enable real-time data visualization, managed system control, and secure system operation. The DSFS employs a Hybrid Intelligence (HI scheme which is proposed through integrating an association rule learning algorithm with fuzzy logic and weighted decision trees. The DSFS operation is based on profiling and registering raw data readings, generated from a set of optical nanosensors, as profiles of attribute-value pairs. As a case study, we evaluate our implemented test bed via simulation scenarios in a water quality monitoring framework. The monitoring processes are simulated based on measuring the percentage of dissolved oxygen and potential hydrogen (PH in fresh water. Simulation results show the efficiency of the proposed HI-based methodology at learning different water quality classes.

Surface Water Quality Trends from EPA's LTM Network

Science.gov (United States)

Funk, C.; Lynch, J. A.

2013-12-01

Surface water chemistry provides direct indicators of the potential effects of anthropogenic impacts, such as acid deposition and climate change, on the overall health of aquatic ecosystems. Long-term surface water monitoring networks provide a host of environmental data that can be used, in conjunction with other networks, to assess how water bodies respond to stressors and if they are potentially at risk (e.g., receiving pollutant deposition beyond its critical load). Two EPA-administered monitoring programs provide information on the effects of acidic deposition on headwater aquatic systems: the Long Term Monitoring (LTM) program and the Temporally Integrated Monitoring of Ecosystems (TIME) program, designed to track the effectiveness of the 1990 Clean Air Act Amendments (CAAA) in reducing the acidity of surface waters in acid sensitive ecoregions of the Northeast and Mid-Atlantic. Here we present regional variability of long term trends in surface water quality in response to substantial reductions in atmospheric deposition. Water quality trends at acid sensitive LTM sites exhibit decreasing concentrations of sulfate at 100% of monitored sites in the Adirondack Mountains and New England, 80% of Northern Appalachian Plateau sites, and yet only 15% of sites in the Ridge and Blue Ridge Provinces over the 1990-2011 period of record. Across all regions, most LTM sites exhibited constant or only slightly declining nitrate concentrations over the same time period. Acid Neutralizing Capacity (ANC) levels improved at 68% and 45% of LTM sites in the Adirondacks and Northern Appalachian Plateau, respectively, but few sites showed increases in New England or the Ridge and Blue Ridge Provinces due to lagging improvements in base cation concentration. The ANC of northeastern TIME lakes was also evaluated from 1991 to 1994 and 2008 to 2011. The percentage of lakes with ANC values below 50 μeq/L, lakes of acute or elevated concern, dropped by about 7%, indicating improvement

Prediction ofWater Quality Parameters (NO3, CL in Karaj Riverby Usinga Combinationof Wavelet Neural Network, ANN and MLRModels

Directory of Open Access Journals (Sweden)

T. Rajaee

2016-10-01

Full Text Available IntroductionThe water quality is an issue of ongoing concern. Evaluation of the quantity and quality of running waters is considerable in hydro-environmental management.The prediction and control of the quality of Karaj river water, as one of the important needed water supply sources of Tehran, possesses great importance. In this study, Performance of Artificial Neural Network (ANN, Wavelet Neural Network combination (WANN and multi linear regression (MLR models, to predict next month the Nitrate (NO3 and Chloride (CL ions of "gate ofBylaqan sluice" station located in Karaj River has been evaluated. Materials and MethodsIn this research two separate ANN models for prediction of NO3 and CL has been expanded. Each one of the parameters for prediction (NO3 / CL has been put related to the past amounts of the same time series (NO3 / CL and its amounts of Q in past months.From astatisticalperiod of10yearswas usedforthe input of the models. Hence 80% of entire data from (96 initial months of data as training set, next 10% of data (12 months and 10% of the end of time series (terminal 12 months were considered as for validation and test of the models, respectively. In WANNcombination model, the real monthly observed time series of river discharge (Q and mentioned qualityparameters(NO3 / CL were decomposed to some sub-time series at different levels by wavelet analysis.Then the decomposed quality parameters to predict and Q time series were used at different levels as inputs to the ANN technique for predicting one-step-ahead Nitrate and Chloride. These time series play various roles in the original time series and the behavior of each is distinct, so the contribution to the original time series varies from each other. In addition, prediction of high NO3 and CL values greater than mean of data that have great importancewere investigated by the models. The capability of the models was evaluated by Coefficient of Efficiency (E and the Root Mean Square

A water-quality monitoring network for Vallecitos Valley, Alameda County, California. Water-resources investigations (final)

International Nuclear Information System (INIS)

Farrar, C.D.

1980-10-01

A water-quality monitoring network is proposed to detect the presence of and trace the movement of radioisotopes in the hydrologic system in the vicinity of the Vallecitos Nuclear Center. The source of the radioisotopes is treated industrial wastewater from the Vallecitos Nuclear Center that is discharged into an unnamed tributary of Vallecitos Creek. The effluent infiltrates the alluvium along the stream course, percolates downward to the water table, and mixes with the native ground water in the subsurface. The average daily discharge of effluent to the hydrologic system in 1978 was about 100,000 gallons. The proposed network consists of four surface-water sampling sites and six wells to sample the ground-water system. Samples collected monthly at each site and analyzed for tritium and for alpha, beta, and gamma radiation would provide adequate data for monitoring

A review on integration of artificial intelligence into water quality modelling.

Science.gov (United States)

Chau, Kwok-wing

2006-07-01

With the development of computing technology, numerical models are often employed to simulate flow and water quality processes in coastal environments. However, the emphasis has conventionally been placed on algorithmic procedures to solve specific problems. These numerical models, being insufficiently user-friendly, lack knowledge transfers in model interpretation. This results in significant constraints on model uses and large gaps between model developers and practitioners. It is a difficult task for novice application users to select an appropriate numerical model. It is desirable to incorporate the existing heuristic knowledge about model manipulation and to furnish intelligent manipulation of calibration parameters. The advancement in artificial intelligence (AI) during the past decade rendered it possible to integrate the technologies into numerical modelling systems in order to bridge the gaps. The objective of this paper is to review the current state-of-the-art of the integration of AI into water quality modelling. Algorithms and methods studied include knowledge-based system, genetic algorithm, artificial neural network, and fuzzy inference system. These techniques can contribute to the integrated model in different aspects and may not be mutually exclusive to one another. Some future directions for further development and their potentials are explored and presented.

Klang River water quality modelling using music

Science.gov (United States)

Zahari, Nazirul Mubin; Zawawi, Mohd Hafiz; Muda, Zakaria Che; Sidek, Lariyah Mohd; Fauzi, Nurfazila Mohd; Othman, Mohd Edzham Fareez; Ahmad, Zulkepply

2017-09-01

Water is an essential resource that sustains life on earth; changes in the natural quality and distribution of water have ecological impacts that can sometimes be devastating. Recently, Malaysia is facing many environmental issues regarding water pollution. The main causes of river pollution are rapid urbanization, arising from the development of residential, commercial, industrial sites, infrastructural facilities and others. The purpose of the study was to predict the water quality of the Connaught Bridge Power Station (CBPS), Klang River. Besides that, affects to the low tide and high tide and. to forecast the pollutant concentrations of the Biochemical Oxygen Demand (BOD) and Total Suspended Solid (TSS) for existing land use of the catchment area through water quality modeling (by using the MUSIC software). Besides that, to identifying an integrated urban stormwater treatment system (Best Management Practice or BMPs) to achieve optimal performance in improving the water quality of the catchment using the MUSIC software in catchment areas having tropical climates. Result from MUSIC Model such as BOD5 at station 1 can be reduce the concentration from Class IV to become Class III. Whereas, for TSS concentration from Class III to become Class II at the station 1. The model predicted a mean TSS reduction of 0.17%, TP reduction of 0.14%, TN reduction of 0.48% and BOD5 reduction of 0.31% for Station 1 Thus, from the result after purposed BMPs the water quality is safe to use because basically water quality monitoring is important due to threat such as activities are harmful to aquatic organisms and public health.

Resource modelling for control: how hydrogeological modelling can support a water quality monitoring infrastructure

Science.gov (United States)

Scozzari, Andrea; Doveri, Marco

2015-04-01

The knowledge of the physical/chemical processes implied with the exploitation of water bodies for human consumption is an essential tool for the optimisation of the monitoring infrastructure. Due to their increasing importance in the context of human consumption (at least in the EU), this work focuses on groundwater resources. In the framework of drinkable water networks, the physical and data-driven modelling of transport phenomena in groundwater can help optimising the sensor network and validating the acquired data. This work proposes the combined usage of physical and data-driven modelling as a support to the design and maximisation of results from a network of distributed sensors. In particular, the validation of physico-chemical measurements and the detection of eventual anomalies by a set of continuous measurements take benefit from the knowledge of the domain from which water is abstracted, and its expected characteristics. Change-detection techniques based on non-specific sensors (presented by quite a large literature during the last two decades) have to deal with the classical issues of maximising correct detections and minimising false alarms, the latter of the two being the most typical problem to be faced, in the view of designing truly applicable monitoring systems. In this context, the definition of "anomaly" in terms of distance from an expected value or feature characterising the quality of water implies the definition of a suitable metric and the knowledge of the physical and chemical peculiarities of the natural domain from which water is exploited, with its implications in terms of characteristics of the water resource.

Optimal spatio-temporal design of water quality monitoring networks for reservoirs: Application of the concept of value of information

Science.gov (United States)

Maymandi, Nahal; Kerachian, Reza; Nikoo, Mohammad Reza

2018-03-01

This paper presents a new methodology for optimizing Water Quality Monitoring (WQM) networks of reservoirs and lakes using the concept of the value of information (VOI) and utilizing results of a calibrated numerical water quality simulation model. With reference to the value of information theory, water quality of every checkpoint with a specific prior probability differs in time. After analyzing water quality samples taken from potential monitoring points, the posterior probabilities are updated using the Baye's theorem, and VOI of the samples is calculated. In the next step, the stations with maximum VOI is selected as optimal stations. This process is repeated for each sampling interval to obtain optimal monitoring network locations for each interval. The results of the proposed VOI-based methodology is compared with those obtained using an entropy theoretic approach. As the results of the two methodologies would be partially different, in the next step, the results are combined using a weighting method. Finally, the optimal sampling interval and location of WQM stations are chosen using the Evidential Reasoning (ER) decision making method. The efficiency and applicability of the methodology are evaluated using available water quantity and quality data of the Karkheh Reservoir in the southwestern part of Iran.

A parsimonious dynamic model for river water quality assessment.

Science.gov (United States)

Mannina, Giorgio; Viviani, Gaspare

2010-01-01

Water quality modelling is of crucial importance for the assessment of physical, chemical, and biological changes in water bodies. Mathematical approaches to water modelling have become more prevalent over recent years. Different model types ranging from detailed physical models to simplified conceptual models are available. Actually, a possible middle ground between detailed and simplified models may be parsimonious models that represent the simplest approach that fits the application. The appropriate modelling approach depends on the research goal as well as on data available for correct model application. When there is inadequate data, it is mandatory to focus on a simple river water quality model rather than detailed ones. The study presents a parsimonious river water quality model to evaluate the propagation of pollutants in natural rivers. The model is made up of two sub-models: a quantity one and a quality one. The model employs a river schematisation that considers different stretches according to the geometric characteristics and to the gradient of the river bed. Each stretch is represented with a conceptual model of a series of linear channels and reservoirs. The channels determine the delay in the pollution wave and the reservoirs cause its dispersion. To assess the river water quality, the model employs four state variables: DO, BOD, NH(4), and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project in which quantity and quality data were gathered. A sensitivity analysis of the model output to the model input or parameters was done based on the Generalised Likelihood Uncertainty Estimation methodology. The results demonstrate the suitability of such a model as a tool for river water quality management.

Status of and changes in water quality monitored for the Idaho statewide surface-water-quality network, 1989—2002

Science.gov (United States)

Hardy, Mark A.; Parliman, Deborah J.; O'Dell, Ivalou

2005-01-01

The Idaho statewide surface-water-quality monitoring network consists of 56 sites that have been monitored from 1989 through 2002 to provide data to document status and changes in the quality of Idaho streams. Sampling at 33 sites has covered a wide range of flows and seasons that describe water-quality variations representing both natural conditions and human influences. Targeting additional high- or low-flow sampling would better describe conditions at 20 sites during hydrologic extremes. At the three spring site types, sampling covered the range of flow conditions from 1989 through 2002 well. However, high flows at these sites since 1989 were lower than historical high flows as a result of declining ground-water levels in the Snake River Plain. Summertime stream temperatures at 45 sites commonly exceeded 19 and 22 degrees Celsius, the Idaho maximum daily mean and daily maximum criteria, respectively, for the protection of coldwater aquatic life. Criteria exceedances in stream basins with minimal development suggest that such high temperatures may occur naturally in many Idaho streams. Suspended-sediment concentrations were generally higher in southern Idaho than in central and northern Idaho, and network data suggest that the turbidity criteria are most likely to be exceeded at sites in southern Idaho and other sections of the Columbia Plateaus geomorphic province. This is probably because this province has more fine-grained soils that are subject to erosion and disturbance by land uses than the Northern Rocky Mountains province of northern and central

Global modelling of river water quality under climate change

Science.gov (United States)

van Vliet, Michelle T. H.; Franssen, Wietse H. P.; Yearsley, John R.

2017-04-01

Climate change will pose challenges on the quality of freshwater resources for human use and ecosystems for instance by changing the dilution capacity and by affecting the rate of chemical processes in rivers. Here we assess the impacts of climate change and induced streamflow changes on a selection of water quality parameters for river basins globally. We used the Variable Infiltration Capacity (VIC) model and a newly developed global water quality module for salinity, temperature, dissolved oxygen and biochemical oxygen demand. The modelling framework was validated using observed records of streamflow, water temperature, chloride, electrical conductivity, dissolved oxygen and biochemical oxygen demand for 1981-2010. VIC and the water quality module were then forced with an ensemble of bias-corrected General Circulation Model (GCM) output for the representative concentration pathways RCP2.6 and RCP8.5 to study water quality trends and identify critical regions (hotspots) of water quality deterioration for the 21st century.

Forecasting Models for Some Water Quality Parameters of Shatt Al-Hilla River, Iraq

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Rafa H. Al-Suhili

2017-07-01

Full Text Available This paper provides Artificial Neural Networks model versions for forecasting the monthly averages of some chemical water quality parameters of Shatt Al-Hilla River, which is located at Hilla City, south of Iraq. The water quality parameters investigated were Sulphate, Magnesium, Calcium, Alkalinity, and Total Hardness. Results indicate that for Sulphate and Calcium high correlation coefficients models were observed to be (0.9 and 0.88, while for Magnesium, Alkalinity and Hardness low correlation coefficients model were observed to be (0.48,0.58, and 0.51 respectively. Serial correlation behavior of these variables indicate at that high lag time correlations sequences are observed for the first two variables and low ones for the last three water quality parameters. A serial correlation coefficient analysis was done and indicates that as the variable exhibited weak lag correlation structure, then a successful ANN forecasting model could not be obtained even if many trials were done to enhance it's performance, such as increasing the number of nodes, the lagged input variables, and/or changing the learning rate and the momentum term values, or the use of different types of activation functions. On the other hand, those variables that have a strong lag correlation structure can easily fit successful ANN forecasting models

Multi-Model Prediction for Demand Forecast in Water Distribution Networks

Directory of Open Access Journals (Sweden)

Rodrigo Lopez Farias

2018-03-01

Full Text Available This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus (QMMP+ for demand forecast in water distribution networks. QMMP+ is based on the decomposition of the quantitative and qualitative information of the time-series. The quantitative component (i.e., the daily consumption prediction is forecasted and the pattern mode estimated using a Nearest Neighbor (NN classifier and a Calendar. The patterns are updated via a simple Moving Average scheme. The NN classifier and the Calendar are executed simultaneously every period and the most suited model for prediction is selected using a probabilistic approach. The proposed solution for water demand forecast is compared against Radial Basis Function Artificial Neural Networks (RBF-ANN, the statistical Autoregressive Integrated Moving Average (ARIMA, and Double Seasonal Holt-Winters (DSHW approaches, providing the best results when applied to real demand of the Barcelona Water Distribution Network. QMMP+ has demonstrated that the special modelling treatment of water consumption patterns improves the forecasting accuracy.

Surface-Water Quality Conditions and Long-Term Trends at Selected Sites within the Ambient Water-Quality Monitoring Network in Missouri, Water Years 1993-2008

Science.gov (United States)

Barr, Miya N.; Davis, Jerri V.

2010-01-01

The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, collects data pertaining to the surface-water resources of Missouri. These data are collected as part of the Missouri Ambient Water-Quality Monitoring Network and constitute a valuable source of reliable, impartial, and timely information for developing an improved understanding of water resources in the State. Six sites from the Ambient Water-Quality Monitoring Network, with data available from the 1993 through 2008 water years, were chosen to compare water-quality conditions and long-term trends of dissolved oxygen, selected physical properties, total suspended solids, dissolved nitrate plus nitrite as nitrogen, total phosphorous, fecal indicator bacteria, and selected trace elements. The six sites used in the study were classified in groups corresponding to the physiography, main land use, and drainage basin size, and represent most stream types in Missouri. Long-term trends in this study were analyzed using flow-adjusted and non-flow adjusted models. Highly censored datasets (greater than 5 percent but less than 50 percent censored values) were not flow-adjusted. Trends that were detected can possibly be related to changes in agriculture or urban development within the drainage basins. Trends in nutrients were the most prevalent. Upward flow-adjusted trends in dissolved nitrate plus nitrite (as nitrogen) concentrations were identified at the Elk River site, and in total phosphorus concentrations at the South Fabius and Grand River sites. A downward flow-adjusted trend was identified in total phosphorus concentrations from Wilson Creek, the only urban site in the study. The downward trend in phosphorus possibly was related to a phosphorus reduction system that began operation in 2001 at a wastewater treatment plant upstream from the sampling site. Total suspended solids concentrations indicated an upward non-flow adjusted trend at the two northern sites (South Fabius

Fine-resolution Modeling of Urban-Energy Systems' Water Footprint in River Networks

Science.gov (United States)

McManamay, R.; Surendran Nair, S.; Morton, A.; DeRolph, C.; Stewart, R.

2015-12-01

Characterizing the interplay between urbanization, energy production, and water resources is essential for ensuring sustainable population growth. In order to balance limited water supplies, competing users must account for their realized and virtual water footprint, i.e. the total direct and indirect amount of water used, respectively. Unfortunately, publicly reported US water use estimates are spatially coarse, temporally static, and completely ignore returns of water to rivers after use. These estimates are insufficient to account for the high spatial and temporal heterogeneity of water budgets in urbanizing systems. Likewise, urbanizing areas are supported by competing sources of energy production, which also have heterogeneous water footprints. Hence, a fundamental challenge of planning for sustainable urban growth and decision-making across disparate policy sectors lies in characterizing inter-dependencies among urban systems, energy producers, and water resources. A modeling framework is presented that provides a novel approach to integrate urban-energy infrastructure into a spatial accounting network that accurately measures water footprints as changes in the quantity and quality of river flows. River networks (RNs), i.e. networks of branching tributaries nested within larger rivers, provide a spatial structure to measure water budgets by modeling hydrology and accounting for use and returns from urbanizing areas and energy producers. We quantify urban-energy water footprints for Atlanta, GA and Knoxville, TN (USA) based on changes in hydrology in RNs. Although water intakes providing supply to metropolitan areas were proximate to metropolitan areas, power plants contributing to energy demand in Knoxville and Atlanta, occurred 30 and 90km outside the metropolitan boundary, respectively. Direct water footprints from urban landcover primarily comprised smaller streams whereas indirect footprints from water supply reservoirs and energy producers included

Section 3. The SPARROW Surface Water-Quality Model: Theory, Application and User Documentation

Science.gov (United States)

Schwarz, G.E.; Hoos, A.B.; Alexander, R.B.; Smith, R.A.

2006-01-01

SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling technique for relating water-quality measurements made at a network of monitoring stations to attributes of the watersheds containing the stations. The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and diffuse sources on land to rivers and through the stream and river network. The model predicts contaminant flux, concentration, and yield in streams and has been used to evaluate alternative hypotheses about the important contaminant sources and watershed properties that control transport over large spatial scales. This report provides documentation for the SPARROW modeling technique and computer software to guide users in constructing and applying basic SPARROW models. The documentation gives details of the SPARROW software, including the input data and installation requirements, and guidance in the specification, calibration, and application of basic SPARROW models, as well as descriptions of the model output and its interpretation. The documentation is intended for both researchers and water-resource managers with interest in using the results of existing models and developing and applying new SPARROW models. The documentation of the model is presented in two parts. Part 1 provides a theoretical and practical introduction to SPARROW modeling techniques, which includes a discussion of the objectives, conceptual attributes, and model infrastructure of SPARROW. Part 1 also includes background on the commonly used model specifications and the methods for estimating and evaluating parameters, evaluating model fit, and generating water-quality predictions and measures of uncertainty. Part 2 provides a user's guide to SPARROW, which includes a discussion of the software architecture and details of the model input requirements and output files, graphs, and maps. The text documentation and computer

Pollution source localization in an urban water supply network based on dynamic water demand.

Science.gov (United States)

Yan, Xuesong; Zhu, Zhixin; Li, Tian

2017-10-27

Urban water supply networks are susceptible to intentional, accidental chemical, and biological pollution, which pose a threat to the health of consumers. In recent years, drinking-water pollution incidents have occurred frequently, seriously endangering social stability and security. The real-time monitoring for water quality can be effectively implemented by placing sensors in the water supply network. However, locating the source of pollution through the data detection obtained by water quality sensors is a challenging problem. The difficulty lies in the limited number of sensors, large number of water supply network nodes, and dynamic user demand for water, which leads the pollution source localization problem to an uncertainty, large-scale, and dynamic optimization problem. In this paper, we mainly study the dynamics of the pollution source localization problem. Previous studies of pollution source localization assume that hydraulic inputs (e.g., water demand of consumers) are known. However, because of the inherent variability of urban water demand, the problem is essentially a fluctuating dynamic problem of consumer's water demand. In this paper, the water demand is considered to be stochastic in nature and can be described using Gaussian model or autoregressive model. On this basis, an optimization algorithm is proposed based on these two dynamic water demand change models to locate the pollution source. The objective of the proposed algorithm is to find the locations and concentrations of pollution sources that meet the minimum between the analogue and detection values of the sensor. Simulation experiments were conducted using two different sizes of urban water supply network data, and the experimental results were compared with those of the standard genetic algorithm.

Identifying uncertainty of the mean of some water quality variables along water quality monitoring network of Bahr El Baqar drain

Directory of Open Access Journals (Sweden)

Hussein G. Karaman

2013-10-01

Full Text Available Assigning objectives to the environmental monitoring network is the pillar of the design to these kinds of networks. Conflicting network objectives may affect the adequacy of the design in terms of sampling frequency and the spatial distribution of the monitoring stations which in turn affect the accuracy of the data and the information extracted. The first step in resolving this problem is to identify the uncertainty inherent in the network as the result of the vagueness of the design objective. Entropy has been utilized and adopted over the past decades to identify uncertainty in similar water data sets. Therefore it is used to identify the uncertainties inherent in the water quality monitoring network of Bahr El-Baqar drain located in the Eastern Delta. Toward investigating the applicability of the Entropy methodology, comprehensive analysis at the selected drain as well as their data sets is carried out. Furthermore, the uncertainty calculated by the entropy function will be presented by the means of the geographical information system to give the decision maker a global view to these uncertainties and to open the door to other researchers to find out innovative approaches to lower these uncertainties reaching optimal monitoring network in terms of the spatial distribution of the monitoring stations.

Identification of water quality degradation hotspots in developing countries by applying large scale water quality modelling

Science.gov (United States)

Malsy, Marcus; Reder, Klara; Flörke, Martina

2014-05-01

Decreasing water quality is one of the main global issues which poses risks to food security, economy, and public health and is consequently crucial for ensuring environmental sustainability. During the last decades access to clean drinking water increased, but 2.5 billion people still do not have access to basic sanitation, especially in Africa and parts of Asia. In this context not only connection to sewage system is of high importance, but also treatment, as an increasing connection rate will lead to higher loadings and therefore higher pressure on water resources. Furthermore, poor people in developing countries use local surface waters for daily activities, e.g. bathing and washing. It is thus clear that water utilization and water sewerage are indispensable connected. In this study, large scale water quality modelling is used to point out hotspots of water pollution to get an insight on potential environmental impacts, in particular, in regions with a low observation density and data gaps in measured water quality parameters. We applied the global water quality model WorldQual to calculate biological oxygen demand (BOD) loadings from point and diffuse sources, as well as in-stream concentrations. Regional focus in this study is on developing countries i.e. Africa, Asia, and South America, as they are most affected by water pollution. Hereby, model runs were conducted for the year 2010 to draw a picture of recent status of surface waters quality and to figure out hotspots and main causes of pollution. First results show that hotspots mainly occur in highly agglomerated regions where population density is high. Large urban areas are initially loading hotspots and pollution prevention and control become increasingly important as point sources are subject to connection rates and treatment levels. Furthermore, river discharge plays a crucial role due to dilution potential, especially in terms of seasonal variability. Highly varying shares of BOD sources across

The EDEN-IW ontology model for sharing knowledge and water quality data between heterogenous databases

DEFF Research Database (Denmark)

Stjernholm, M.; Poslad, S.; Zuo, L.

2004-01-01

The Environmental Data Exchange Network for Inland Water (EDEN-IW) project's main aim is to develop a system for making disparate and heterogeneous databases of Inland Water quality more accessible to users. The core technology is based upon a combination of: ontological model to represent...... a Semantic Web based data model for IW; software agents as an infrastructure to share and reason about the IW se-mantic data model and XML to make the information accessible to Web portals and mainstream Web services. This presentation focuses on the Semantic Web or Onto-logical model. Currently, we have...

Development of Water Quality Modeling in the United States

Science.gov (United States)

This presentation describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions. Water quality modeling has a relatively long history in the United States. While its origins lie in the work...

Modelling flow dynamics in water distribution networks using ...

African Journals Online (AJOL)

One such approach is the Artificial Neural Networks (ANNs) technique. The advantage of ANNs is that they are robust and can be used to model complex linear and non-linear systems without making implicit assumptions. ANNs can be trained to forecast flow dynamics in a water distribution network. Such flow dynamics ...

Integrated Supply Network Maturity Model: Water Scarcity Perspective

Directory of Open Access Journals (Sweden)

Ekaterina Yatskovskaya

2018-03-01

Full Text Available Today’s supply chains (SCs are more than ever prone to disruptions caused by natural and man-made events with water scarcity identified as one of the highest impact events among these. Leading businesses, understanding that natural resource scarcity (NRS has become a critical supply chain risk factor, extensively incorporate sustainable water management programmes into their corporate social responsibility and environmental management agenda. The question of how industries can efficiently evaluate the progress of these water scarcity mitigation practices, however, remains open. In order to address this question, the present study proposes a conceptual maturity model. The model is rooted in strategies for water scarcity mitigation using a framework developed by Yatskovskaya and Srai and develops an extensive literature review of recent publications on maturity frameworks in the fields of sustainability and operations management. In order to test the proposed proposed, model an exploratory case study with a leading pharmaceutical company was conducted. The proposed maturity model presents an evaluation tool that allows systematic assessment and visualisation of organisational routines and practices relevant to sustainable manufacturing in the context of water scarcity. This model was designed to help illustrate mitigation capabilities evolution over time, where future state desired capabilities were considered through alternative supply network (SN configurations, network structure, process flow, product architecture, and supply partnerships.

Modeling the future evolution of the virtual water trade network: A combination of network and gravity models

Science.gov (United States)

Sartori, Martina; Schiavo, Stefano; Fracasso, Andrea; Riccaboni, Massimo

2017-12-01

The paper investigates how the topological features of the virtual water (VW) network and the size of the associated VW flows are likely to change over time, under different socio-economic and climate scenarios. We combine two alternative models of network formation -a stochastic and a fitness model, used to describe the structure of VW flows- with a gravity model of trade to predict the intensity of each bilateral flow. This combined approach is superior to existing methodologies in its ability to replicate the observed features of VW trade. The insights from the models are used to forecast future VW flows in 2020 and 2050, under different climatic scenarios, and compare them with future water availability. Results suggest that the current trend of VW exports is not sustainable for all countries. Moreover, our approach highlights that some VW importers might be exposed to "imported water stress" as they rely heavily on imports from countries whose water use is unsustainable.

Water quality assessment and meta model development in Melen watershed - Turkey.

Science.gov (United States)

Erturk, Ali; Gurel, Melike; Ekdal, Alpaslan; Tavsan, Cigdem; Ugurluoglu, Aysegul; Seker, Dursun Zafer; Tanik, Aysegul; Ozturk, Izzet

2010-07-01

Istanbul, being one of the highly populated metropolitan areas of the world, has been facing water scarcity since the past decade. Water transfer from Melen Watershed was considered as the most feasible option to supply water to Istanbul due to its high water potential and relatively less degraded water quality. This study consists of two parts. In the first part, water quality data covering 26 parameters from 5 monitoring stations were analyzed and assessed due to the requirements of the "Quality Required of Surface Water Intended for the Abstraction of Drinking Water" regulation. In the second part, a one-dimensional stream water quality model with simple water quality kinetics was developed. It formed a basic design for more advanced water quality models for the watershed. The reason for assessing the water quality data and developing a model was to provide information for decision making on preliminary actions to prevent any further deterioration of existing water quality. According to the water quality assessment at the water abstraction point, Melen River has relatively poor water quality with regard to NH(4)(+), BOD(5), faecal streptococcus, manganese and phenol parameters, and is unsuitable for drinking water abstraction in terms of COD, PO(4)(3-), total coliform, total suspended solids, mercury and total chromium parameters. The results derived from the model were found to be consistent with the water quality assessment. It also showed that relatively high inorganic nitrogen and phosphorus concentrations along the streams are related to diffuse nutrient loads that should be managed together with municipal and industrial wastewaters. Copyright 2010 Elsevier Ltd. All rights reserved.

Calculation method of water injection forward modeling and inversion process in oilfield water injection network

Science.gov (United States)

Liu, Long; Liu, Wei

2018-04-01

A forward modeling and inversion algorithm is adopted in order to determine the water injection plan in the oilfield water injection network. The main idea of the algorithm is shown as follows: firstly, the oilfield water injection network is inversely calculated. The pumping station demand flow is calculated. Then, forward modeling calculation is carried out for judging whether all water injection wells meet the requirements of injection allocation or not. If all water injection wells meet the requirements of injection allocation, calculation is stopped, otherwise the demand injection allocation flow rate of certain step size is reduced aiming at water injection wells which do not meet requirements, and next iterative operation is started. It is not necessary to list the algorithm into water injection network system algorithm, which can be realized easily. Iterative method is used, which is suitable for computer programming. Experimental result shows that the algorithm is fast and accurate.

Multiscale network model for simulating liquid water and water vapour transfer properties of porous materials

NARCIS (Netherlands)

Carmeliet, J.; Descamps, F.; Houvenaghel, G.

1999-01-01

A multiscale network model is presented to model unsaturated moisture transfer in hygroscopic capillary-porous materials showing a broad pore-size distribution. Both capillary effects and water sorption phenomena, water vapour and liquid water transfer are considered. The multiscale approach is

Evaluation of global water quality - the potential of a data- and model-driven analysis

Science.gov (United States)

Bärlund, Ilona; Flörke, Martina; Alcamo, Joseph; Völker, Jeanette; Malsy, Marcus; Kaus, Andrew; Reder, Klara; Büttner, Olaf; Katterfeld, Christiane; Dietrich, Désirée; Borchardt, Dietrich

2016-04-01

The ongoing socio-economic development presents a new challenge for water quality worldwide, especially in developing and emerging countries. It is estimated that due to population growth and the extension of water supply networks, the amount of waste water will rise sharply. This can lead to an increased risk of surface water quality degradation, if the wastewater is not sufficiently treated. This development has impacts on ecosystems and human health, as well as food security. The United Nations Member States have adopted targets for sustainable development. They include, inter alia, sustainable protection of water quality and sustainable use of water resources. To achieve these goals, appropriate monitoring strategies and the development of indicators for water quality are required. Within the pre-study for a 'World Water Quality Assessment' (WWQA) led by United Nations Environment Programme (UNEP), a methodology for assessing water quality, taking into account the above-mentioned objectives has been developed. The novelty of this methodology is the linked model- and data-driven approach. The focus is on parameters reflecting the key water quality issues, such as increased waste water pollution, salinization or eutrophication. The results from the pre-study show, for example, that already about one seventh of all watercourses in Latin America, Africa and Asia show high organic pollution. This is of central importance for inland fisheries and associated food security. In addition, it could be demonstrated that global water quality databases have large gaps. These must be closed in the future in order to obtain an overall picture of global water quality and to target measures more efficiently. The aim of this presentation is to introduce the methodology developed within the WWQA pre-study and to show selected examples of application in Latin America, Africa and Asia.

A linked hydrodynamic and water quality model for the Salton Sea

Science.gov (United States)

Chung, E.G.; Schladow, S.G.; Perez-Losada, J.; Robertson, Dale M.

2008-01-01

A linked hydrodynamic and water quality model was developed and applied to the Salton Sea. The hydrodynamic component is based on the one-dimensional numerical model, DLM. The water quality model is based on a new conceptual model for nutrient cycling in the Sea, and simulates temperature, total suspended sediment concentration, nutrient concentrations, including PO4-3, NO3-1 and NH4+1, DO concentration and chlorophyll a concentration as functions of depth and time. Existing water temperature data from 1997 were used to verify that the model could accurately represent the onset and breakup of thermal stratification. 1999 is the only year with a near-complete dataset for water quality variables for the Salton Sea. The linked hydrodynamic and water quality model was run for 1999, and by adjustment of rate coefficients and other water quality parameters, a good match with the data was obtained. In this article, the model is fully described and the model results for reductions in external phosphorus load on chlorophyll a distribution are presented. ?? 2008 Springer Science+Business Media B.V.

A general framework for a collaborative water quality knowledge and information network.

Science.gov (United States)

Dalcanale, Fernanda; Fontane, Darrell; Csapo, Jorge

2011-03-01

Increasing knowledge about the environment has brought about a better understanding of the complexity of the issues, and more information publicly available has resulted into a steady shift from centralized decision making to increasing levels of participatory processes. The management of that information, in turn, is becoming more complex. One of the ways to deal with the complexity is the development of tools that would allow all players, including managers, researchers, educators, stakeholders and the civil society, to be able to contribute to the information system, in any level they are inclined to do so. In this project, a search for the available technology for collaboration, methods of community filtering, and community-based review was performed and the possible implementation of these tools to create a general framework for a collaborative "Water Quality Knowledge and Information Network" was evaluated. The main goals of the network are to advance water quality education and knowledge; encourage distribution and access to data; provide networking opportunities; allow public perceptions and concerns to be collected; promote exchange of ideas; and, give general, open, and free access to information. A reference implementation was made available online and received positive feedback from the community, which also suggested some possible improvements.

Groundwater quality data from the National Water-Quality Assessment Project, May 2012 through December 2013

Science.gov (United States)

Arnold, Terri L.; Desimone, Leslie A.; Bexfield, Laura M.; Lindsey, Bruce D.; Barlow, Jeannie R.; Kulongoski, Justin T.; Musgrove, MaryLynn; Kingsbury, James A.; Belitz, Kenneth

2016-06-20

Groundwater-quality data were collected from 748 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program from May 2012 through December 2013. The data were collected from four types of well networks: principal aquifer study networks, which assess the quality of groundwater used for public water supply; land-use study networks, which assess land-use effects on shallow groundwater quality; major aquifer study networks, which assess the quality of groundwater used for domestic supply; and enhanced trends networks, which evaluate the time scales during which groundwater quality changes. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, and radionuclides. These groundwater quality data are tabulated in this report. Quality-control samples also were collected; data from blank and replicate quality-control samples are included in this report.

Modeling complexity in engineered infrastructure system: Water distribution network as an example

Science.gov (United States)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

DeepQA: improving the estimation of single protein model quality with deep belief networks.

Science.gov (United States)

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

Monitoring And Modeling Environmental Water Quality To Support Environmental Water Purchase Decision-making

Science.gov (United States)

Null, S. E.; Elmore, L.; Mouzon, N. R.; Wood, J. R.

2016-12-01

More than 25 million cubic meters (20,000 acre feet) of water has been purchased from willing agricultural sellers for environmental flows in Nevada's Walker River to improve riverine habitat and connectivity with downstream Walker Lake. Reduced instream flows limit native fish populations, like Lahontan cutthroat trout, through warm daily stream temperatures and low dissolved oxygen concentrations. Environmental water purchases maintain instream flows, although effects on water quality are more varied. We use multi-year water quality monitoring and physically-based hydrodynamic and water quality modeling to estimate streamflow, water temperature, and dissolved oxygen concentrations with alternative environmental water purchases. We simulate water temperature and dissolved oxygen changes from increased streamflow to prioritize the time periods and locations that environmental water purchases most enhance trout habitat as a function of water quality. Monitoring results indicate stream temperature and dissolved oxygen limitations generally exist in the 115 kilometers upstream of Walker Lake (about 37% of the study area) from approximately May through September, and this reach acts as a water quality barrier for fish passage. Model results indicate that low streamflows generally coincide with critically warm stream temperatures, water quality refugia exist on a tributary of the Walker River, and environmental water purchases may improve stream temperature and dissolved oxygen conditions for some reaches and seasons, especially in dry years and prolonged droughts. This research supports environmental water purchase decision-making and allows water purchase decisions to be prioritized with other river restoration alternatives.

A stochastic dynamic programming model for stream water quality ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

constraints of the water quality management problem; (ii) a water quality simulation model ... of acceptance and limited implementation of optimisation techniques. .... The response of river system to these sources of pollution can be integrated ...

River water quality model no. 1 (RWQM1): I. Modelling approach

DEFF Research Database (Denmark)

Shanahan, P.; Borchardt, D.; Henze, Mogens

2001-01-01

Successful river water quality modelling requires the specification of an appropriate model structure and process formulation. Both must be related to the compartment structure of running water ecosystems including their longitudinal, vertical, and lateral zonation patterns. Furthermore...

River water quality modelling: II

DEFF Research Database (Denmark)

Shanahan, P.; Henze, Mogens; Koncsos, L.

1998-01-01

The U.S. EPA QUAL2E model is currently the standard for river water quality modelling. While QUAL2E is adequate for the regulatory situation for which it was developed (the U.S. wasteload allocation process), there is a need for a more comprehensive framework for research and teaching. Moreover......, QUAL2E and similar models do not address a number of practical problems such as stormwater-flow events, nonpoint source pollution, and transient streamflow. Limitations in model formulation affect the ability to close mass balances, to represent sessile bacteria and other benthic processes......, and to achieve robust model calibration. Mass balance problems arise from failure to account for mass in the sediment as well as in the water column and due to the fundamental imprecision of BOD as a state variable. (C) 1998 IAWQ Published by Elsevier Science Ltd. All rights reserved....

Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data

Science.gov (United States)

Petkewich, Matthew D.; Daamen, Ruby C.; Roehl, Edwin A.; Conrads, Paul

2016-09-29

The Everglades Depth Estimation Network (EDEN), with over 240 real-time gaging stations, provides hydrologic data for freshwater and tidal areas of the Everglades. These data are used to generate daily water-level and water-depth maps of the Everglades that are used to assess biotic responses to hydrologic change resulting from the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The generation of EDEN daily water-level and water-depth maps is dependent on high quality real-time data from water-level stations. Real-time data are automatically checked for outliers by assigning minimum and maximum thresholds for each station. Small errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the stations. Correcting these small errors in the data often is time consuming and water-level data may not be finalized for several months. To provide daily water-level and water-depth maps on a near real-time basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous water-level data.The Automated Data Assurance and Management (ADAM) software uses inferential sensor technology often used in industrial applications. Rather than installing a redundant sensor to measure a process, such as an additional water-level station, inferential sensors, or virtual sensors, were developed for each station that make accurate estimates of the process measured by the hard sensor (water-level gaging station). The inferential sensors in the ADAM software are empirical models that use inputs from one or more proximal stations. The advantage of ADAM is that it provides a redundant signal to the sensor in the field without the environmental threats associated with field conditions at stations (flood or hurricane, for example). In the

A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality.

Science.gov (United States)

Huang, Xiaoci; Yi, Jianjun; Chen, Shaoli; Zhu, Xiaomin

2015-11-19

Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks.

Trends in Surface-Water Quality at Selected Ambient-Monitoring Network Stations in Kentucky, 1979-2004

Science.gov (United States)

Crain, Angela S.; Martin, Gary R.

2009-01-01

Increasingly complex water-management decisions require water-quality monitoring programs that provide data for multiple purposes, including trend analyses, to detect improvement or deterioration in water quality with time. Understanding surface-water-quality trends assists resource managers in identifying emerging water-quality concerns, planning remediation efforts, and evaluating the effectiveness of the remediation. This report presents the results of a study conducted by the U.S. Geological Survey, in cooperation with the Kentucky Energy and Environment Cabinet-Kentucky Division of Water, to analyze and summarize long-term water-quality trends of selected properties and water-quality constituents in selected streams in Kentucky's ambient stream water-quality monitoring network. Trends in surface-water quality for 15 properties and water-quality constituents were analyzed at 37 stations with drainage basins ranging in size from 62 to 6,431 square miles. Analyses of selected physical properties (temperature, specific conductance, pH, dissolved oxygen, hardness, and suspended solids), for major ions (chloride and sulfate), for selected metals (iron and manganese), for nutrients (total phosphorus, total nitrogen, total Kjeldahl nitrogen, nitrite plus nitrate), and for fecal coliform were compiled from the Commonwealth's ambient water-quality monitoring network. Trend analyses were completed using the S-Plus statistical software program S-Estimate Trend (S-ESTREND), which detects trends in water-quality data. The trend-detection techniques supplied by this software include the Seasonal Kendall nonparametric methods for use with uncensored data or data censored with only one reporting limit and the Tobit-regression parametric method for use with data censored with multiple reporting limits. One of these tests was selected for each property and water-quality constituent and applied to all station records so that results of the trend procedure could be compared among

Modelling flow dynamics in water distribution networks using ...

African Journals Online (AJOL)

DR OKE

was used for modelling the flow and simulate water demand using a Matlab .... This process requires that the neural network compute the error derivative of the .... Furthermore, Matlab was used as a simulation tool; and the first step was ...

Hydrologic and Water Quality Model Development Using Simulink

Directory of Open Access Journals (Sweden)

James D. Bowen

2014-11-01

Full Text Available A stormwater runoff model based on the Soil Conservation Service (SCS method and a finite-volume based water quality model have been developed to investigate the use of Simulink for use in teaching and research. Simulink, a MATLAB extension, is a graphically based model development environment for system modeling and simulation. Widely used for mechanical and electrical systems, Simulink has had less use for modeling of hydrologic systems. The watershed model is being considered for use in teaching graduate-level courses in hydrology and/or stormwater modeling. Simulink’s block (data process and arrow (data transfer object model, the copy and paste user interface, the large number of existing blocks, and the absence of computer code allows students to become model developers almost immediately. The visual depiction of systems, their component subsystems, and the flow of data through the systems are ideal attributes for hands-on teaching of hydrologic and mass balance processes to today’s computer-savvy visual learners. Model development with Simulink for research purposes is also investigated. A finite volume, multi-layer pond model using the water quality kinetics present in CE-QUAL-W2 has been developed using Simulink. The model is one of the first uses of Simulink for modeling eutrophication dynamics in stratified natural systems. The model structure and a test case are presented. One use of the model for teaching a graduate-level water quality modeling class is also described.

Ditch network maintenance in peat-dominated boreal forests: Review and analysis of water quality management options.

Science.gov (United States)

Nieminen, Mika; Piirainen, Sirpa; Sikström, Ulf; Löfgren, Stefan; Marttila, Hannu; Sarkkola, Sakari; Laurén, Ari; Finér, Leena

2018-03-27

The objective of this study was to evaluate the potential of different water management options to mitigate sediment and nutrient exports from ditch network maintenance (DNM) areas in boreal peatland forests. Available literature was reviewed, past data reanalyzed, effects of drainage intensity modeled, and major research gaps identified. The results indicate that excess downstream loads may be difficult to prevent. Water protection structures constructed to capture eroded matter are either inefficient (sedimentation ponds) or difficult to apply (wetland buffers). It may be more efficient to decrease erosion, either by limiting peak water velocity (dam structures) or by adjusting ditch depth and spacing to enable satisfactory drainage without exposing the mineral soil below peat. Future research should be directed towards the effects of ditch breaks and adjusted ditch depth and spacing in managing water quality in DNM areas.

Conceptual design of a regional water quality screening model

International Nuclear Information System (INIS)

Davis, M.J.

1981-01-01

This water quality assessment methodology is intended to predict concentrations at future times and to estimate the impacts on water quality of energy-related activities (including industrial boilers). Estimates of impacts on water quality at future times are based on incremental changes in pollutant inputs to the body water. Important features of the model are: use of measured concentrations to account for existing conditions; consideration of incremental changes in pollutant loads; emphasis on the energy sector and industrial boilers; analysis restricted to streams only; no attempt to fully account for pollutant behavior; and flexible design, so that future improvements can be incorporated. The basic approach is very similar to the one used by Argonne's ARQUAL model but will allow more complex pollutant behavior and more flexibility in use

An Effect of the Co-Operative Network Model for Students' Quality in Thai Primary Schools

Science.gov (United States)

Khanthaphum, Udomsin; Tesaputa, Kowat; Weangsamoot, Visoot

2016-01-01

This research aimed: 1) to study the current and desirable states of the co-operative network in developing the learners' quality in Thai primary schools, 2) to develop a model of the co-operative network in developing the learners' quality, and 3) to examine the results of implementation of the co-operative network model in the primary school.…

Modeling water and hydrogen networks with partitioning regeneration units

Directory of Open Access Journals (Sweden)

W.M. Shehata

2015-03-01

Full Text Available Strict environment regulations in chemical and refinery industries lead to minimize resource consumption by designing utility networks within industrial process plants. The present study proposed a superstructure based optimization model for the synthesis of water and hydrogen networks with partitioning regenerators without mixing the regenerated sources. This method determines the number of partitioning regenerators needed for the regeneration of the sources. The number of the regenerators is based on the number of sources required to be treated for recovery. Each source is regenerated in an individual partitioning regenerator. Multiple regeneration systems can be employed to achieve minimum flowrate and costs. The formulation is linear in the regenerator balance equations. The optimized model is applied for two systems, partitioning regeneration systems of the fixed outlet impurity concentration and partitioning regeneration systems of the fixed impurity load removal ratio (RR for water and hydrogen networks. Several case studies from the literature are solved to illustrate the ease and applicability of the proposed method.

Water quality modelling of an impacted semi-arid catchment using flow data from the WEAP model

Science.gov (United States)

Slaughter, Andrew R.; Mantel, Sukhmani K.

2018-04-01

The continuous decline in water quality in many regions is forcing a shift from quantity-based water resources management to a greater emphasis on water quality management. Water quality models can act as invaluable tools as they facilitate a conceptual understanding of processes affecting water quality and can be used to investigate the water quality consequences of management scenarios. In South Africa, the Water Quality Systems Assessment Model (WQSAM) was developed as a management-focussed water quality model that is relatively simple to be able to utilise the small amount of available observed data. Importantly, WQSAM explicitly links to systems (yield) models routinely used in water resources management in South Africa by using their flow output to drive water quality simulations. Although WQSAM has been shown to be able to represent the variability of water quality in South African rivers, its focus on management from a South African perspective limits its use to within southern African regions for which specific systems model setups exist. Facilitating the use of WQSAM within catchments outside of southern Africa and within catchments for which these systems model setups to not exist would require WQSAM to be able to link to a simple-to-use and internationally-applied systems model. One such systems model is the Water Evaluation and Planning (WEAP) model, which incorporates a rainfall-runoff component (natural hydrology), and reservoir storage, return flows and abstractions (systems modelling), but within which water quality modelling facilities are rudimentary. The aims of the current study were therefore to: (1) adapt the WQSAM model to be able to use as input the flow outputs of the WEAP model and; (2) provide an initial assessment of how successful this linkage was by application of the WEAP and WQSAM models to the Buffalo River for historical conditions; a small, semi-arid and impacted catchment in the Eastern Cape of South Africa. The simulations of

A complex network based model for detecting isolated communities in water distribution networks

Science.gov (United States)

Sheng, Nan; Jia, Youwei; Xu, Zhao; Ho, Siu-Lau; Wai Kan, Chi

2013-12-01

Water distribution network (WDN) is a typical real-world complex network of major infrastructure that plays an important role in human's daily life. In this paper, we explore the formation of isolated communities in WDN based on complex network theory. A graph-algebraic model is proposed to effectively detect the potential communities due to pipeline failures. This model can properly illustrate the connectivity and evolution of WDN during different stages of contingency events, and identify the emerging isolated communities through spectral analysis on Laplacian matrix. A case study on a practical urban WDN in China is conducted, and the consistency between the simulation results and the historical data are reported to showcase the feasibility and effectiveness of the proposed model.

Dealing with uncertainty in modeling intermittent water supply

Science.gov (United States)

Lieb, A. M.; Rycroft, C.; Wilkening, J.

2015-12-01

Intermittency in urban water supply affects hundreds of millions of people in cities around the world, impacting water quality and infrastructure. Building on previous work to dynamically model the transient flows in water distribution networks undergoing frequent filling and emptying, we now consider the hydraulic implications of uncertain input data. Water distribution networks undergoing intermittent supply are often poorly mapped, and household metering frequently ranges from patchy to nonexistent. In the face of uncertain pipe material, pipe slope, network connectivity, and outflow, we investigate how uncertainty affects dynamical modeling results. We furthermore identify which parameters exert the greatest influence on uncertainty, helping to prioritize data collection.

Modeling and optimization of potable water network

Energy Technology Data Exchange (ETDEWEB)

Djebedjian, B.; Rayan, M.A. [Mansoura Univ., El-Mansoura (Egypt); Herrick, A. [Suez Canal Authority, Ismailia (Egypt)

2000-07-01

Software was developed in order to optimize the design of water distribution systems and pipe networks. While satisfying all the constraints imposed such as pipe diameter and nodal pressure, it was based on a mathematical model treating looped networks. The optimum network configuration and cost are determined considering parameters like pipe diameter, flow rate, corresponding pressure and hydraulic losses. It must be understood that minimum cost is relative to the different objective functions selected. The determination of the proper objective function often depends on the operating policies of a particular company. The solution for the optimization technique was obtained by using a non-linear technique. To solve the optimal design of network, the model was derived using the sequential unconstrained minimization technique (SUMT) of Fiacco and McCormick, which decreased the number of iterations required. The pipe diameters initially assumed were successively adjusted to correspond to the existing commercial pipe diameters. The technique was then applied to a two-loop network without pumps or valves. Fed by gravity, it comprised eight pipes, 1000 m long each. The first evaluation of the method proved satisfactory. As with other methods, it failed to find the global optimum. In the future, research efforts will be directed to the optimization of networks with pumps and reservoirs. 24 refs., 3 tabs., 1 fig.

Towards benchmarking an in-stream water quality model

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available A method of model evaluation is presented which utilises a comparison with a benchmark model. The proposed benchmarking concept is one that can be applied to many hydrological models but, in this instance, is implemented in the context of an in-stream water quality model. The benchmark model is defined in such a way that it is easily implemented within the framework of the test model, i.e. the approach relies on two applications of the same model code rather than the application of two separate model codes. This is illustrated using two case studies from the UK, the Rivers Aire and Ouse, with the objective of simulating a water quality classification, general quality assessment (GQA, which is based on dissolved oxygen, biochemical oxygen demand and ammonium. Comparisons between the benchmark and test models are made based on GQA, as well as a step-wise assessment against the components required in its derivation. The benchmarking process yields a great deal of important information about the performance of the test model and raises issues about a priori definition of the assessment criteria.

In situ optical water-quality sensor networks - Workshop summary report

Science.gov (United States)

Pellerin, Brian A.; Bergamaschi, Brian A.; Horsburgh, Jeffery S.

2012-01-01

Advanced in situ optical water-quality sensors and new techniques for data analysis hold enormous promise for furthering scientific understanding of aquatic systems. These sensors measure important biogeochemical parameters for long deployments, enabling the capture of data at time scales over which they vary most meaningfully. The high-frequency, real-time water-quality data they generate provide opportunities for early warning of water-quality deterioration, trend detection, and science-based decision support. However, developing networks of optical sensors in freshwater systems that report reliable and comparable data across and between sites remains a challenge to the research and monitoring community. To address this, the U. S. Geological Survey (USGS) and the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) convened a joint 3-day workshop (June 8-10, 2011) at the National Conservation Training Center in Shepardstown, West Virginia, to explore ways to coordinate development of standards and applications for optical sensors, and improve handling, storing, and analyzing the continuous data they produce. The workshop brought together more than 60 scientists, program managers, and vendors from universities, government agencies, and the private sector. Several important outcomes emerged from the presentations and breakout sessions. There was general consensus that making intercalibrated measurements requires that both manufacturers and users better characterize and calibrate the sensors under field conditions. For example, the influence of suspended particles, highly colored water, and temperature on optical sensors remains poorly understood, but consistently accounting for these factors is critical to successful deployment and for interpreting results in different settings. This, in turn, highlights the lack of appropriate standards for sensor calibrations, field checks, and characterizing interferences, as well as methods for

A One-Dimensional Hydrodynamic and Water Quality Model for a Water Transfer Project with Multihydraulic Structures

Directory of Open Access Journals (Sweden)

Yujun Yi

2017-01-01

Full Text Available The long Middle Route of the South to North Water Transfer Project is composed of complex hydraulic structures (aqueduct, tunnel, control gate, diversion, culvert, and diverted siphon, which generate complex flow patterns. It is vital to simulate the flow patterns through hydraulic structures, but it is a challenging work to protect water quality and maintain continuous water transfer. A one-dimensional hydrodynamic and water quality model was built to understand the flow and pollutant movement in this project. Preissmann four-point partial-node implicit scheme was used to solve the governing equations in this study. Water flow and pollutant movement were appropriately simulated and the results indicated that this water quality model was comparable to MIKE 11 and had a good performance and accuracy. Simulation accuracy and model uncertainty were analyzed. Based on the validated water quality model, six pollution scenarios (Q1 = 10 m3/s, Q2 = 30 m3/s, and Q3 = 60 m3/s for volatile phenol (VOP and contaminant mercury (Hg were simulated for the MRP. Emergent pollution accidents were forecasted and changes of water quality were analyzed according to the simulations results, which helped to guarantee continuously transferring water for a large water transfer project.

Modelling the Impact of Land Use Change on Water Quality in Agricultural Catchments

Science.gov (United States)

Johnes, P. J.; Heathwaite, A. L.

1997-03-01

Export coefficient modelling was used to model the impact of agriculture on nitrogen and phosphorus loading on the surface waters of two contrasting agricultural catchments. The model was originally developed for the Windrush catchment where the highly reactive Jurassic limestone aquifer underlying the catchment is well connected to the surface drainage network, allowing the system to be modelled using uniform export coefficients for each nutrient source in the catchment, regardless of proximity to the surface drainage network. In the Slapton catchment, the hydrological pathways are dominated by surface and lateral shallow subsurface flow, requiring modification of the export coefficient model to incorporate a distance-decay component in the export coefficients. The modified model was calibrated against observed total nitrogen and total phosphorus loads delivered to Slapton Ley from inflowing streams in its catchment. Sensitivity analysis was conducted to isolate the key controls on nutrient export in the modified model. The model was validated against long-term records of water quality, and was found to be accurate in its predictions and sensitive to both temporal and spatial changes in agricultural practice in the catchment. The model was then used to forecast the potential reduction in nutrient loading on Slapton Ley associated with a range of catchment management strategies. The best practicable environmental option (BPEO) was found to be spatial redistribution of high nutrient export risk sources to areas of the catchment with the greatest intrinsic nutrient retention capacity.

Perceptual tools for quality-aware video networks

Science.gov (United States)

Bovik, A. C.

2014-01-01

Monitoring and controlling the quality of the viewing experience of videos transmitted over increasingly congested networks (especially wireless networks) is a pressing problem owing to rapid advances in video-centric mobile communication and display devices that are straining the capacity of the network infrastructure. New developments in automatic perceptual video quality models offer tools that have the potential to be used to perceptually optimize wireless video, leading to more efficient video data delivery and better received quality. In this talk I will review key perceptual principles that are, or could be used to create effective video quality prediction models, and leading quality prediction models that utilize these principles. The goal is to be able to monitor and perceptually optimize video networks by making them "quality-aware."

Dynamic thermo-hydraulic model of district cooling networks

International Nuclear Information System (INIS)

Oppelt, Thomas; Urbaneck, Thorsten; Gross, Ulrich; Platzer, Bernd

2016-01-01

Highlights: • A dynamic thermo-hydraulic model for district cooling networks is presented. • The thermal modelling is based on water segment tracking (Lagrangian approach). • Thus, numerical errors and balance inaccuracies are avoided. • Verification and validation studies proved the reliability of the model. - Abstract: In the present paper, the dynamic thermo-hydraulic model ISENA is presented which can be applied for answering different questions occurring in design and operation of district cooling networks—e.g. related to economic and energy efficiency. The network model consists of a quasistatic hydraulic model and a transient thermal model based on tracking water segments through the whole network (Lagrangian method). Applying this approach, numerical errors and balance inaccuracies can be avoided which leads to a higher quality of results compared to other network models. Verification and validation calculations are presented in order to show that ISENA provides reliable results and is suitable for practical application.

An ANN application for water quality forecasting.

Science.gov (United States)

Palani, Sundarambal; Liong, Shie-Yui; Tkalich, Pavel

2008-09-01

Rapid urban and coastal developments often witness deterioration of regional seawater quality. As part of the management process, it is important to assess the baseline characteristics of the marine environment so that sustainable development can be pursued. In this study, artificial neural networks (ANNs) were used to predict and forecast quantitative characteristics of water bodies. The true power and advantage of this method lie in its ability to (1) represent both linear and non-linear relationships and (2) learn these relationships directly from the data being modeled. The study focuses on Singapore coastal waters. The ANN model is built for quick assessment and forecasting of selected water quality variables at any location in the domain of interest. Respective variables measured at other locations serve as the input parameters. The variables of interest are salinity, temperature, dissolved oxygen, and chlorophyll-alpha. A time lag up to 2Delta(t) appeared to suffice to yield good simulation results. To validate the performance of the trained ANN, it was applied to an unseen data set from a station in the region. The results show the ANN's great potential to simulate water quality variables. Simulation accuracy, measured in the Nash-Sutcliffe coefficient of efficiency (R(2)), ranged from 0.8 to 0.9 for the training and overfitting test data. Thus, a trained ANN model may potentially provide simulated values for desired locations at which measured data are unavailable yet required for water quality models.

Enabling proactive agricultural drainage reuse for improved water quality through collaborative networks and low-complexity data-driven modelling

OpenAIRE

Zia, Huma

2015-01-01

With increasing prevalence of Wireless Sensor Networks (WSNs) in agriculture and hydrology, there exists an opportunity for providing a technologically viable solution for the conservation of already scarce fresh water resources. In this thesis, a novel framework is proposed for enabling a proactive management of agricultural drainage and nutrient losses at farm scale where complex models are replaced by in-situ sensing, communication and low complexity predictive models suited to an autonomo...

Mathematical model for water quality impact assessment and its computer application in coal mine water

International Nuclear Information System (INIS)

Sundararajan, M.; Chakraborty, M.K.; Gupta, J.P.; Saxena, N.C.; Dhar, B.B.

1994-01-01

This paper presents a mathematical model to assess the Water Quality Impact in coal mine or in river system by accurate and rational method. Algorithm, flowchart and computer programme have been developed upon this model to assess the quality of coal mine water. 3 refs., 2 figs., 2 tabs

Model-based leakage localization in drinking water distribution networks using structured residuals

OpenAIRE

Puig Cayuela, Vicenç; Rosich, Albert

2013-01-01

In this paper, a new model based approach to leakage localization in drinking water networks is proposed based on generating a set of structured residuals. The residual evaluation is based on a numerical method based on an enhanced Newton-Raphson algorithm. The proposed method is suitable for water network systems because the non-linearities of the model make impossible to derive analytical residuals. Furthermore, the computed residuals are designed so that leaks are decoupled, which impro...

A method of groundwater quality assessment based on fuzzy network-CANFIS and geographic information system (GIS)

Science.gov (United States)

Gholami, V.; Khaleghi, M. R.; Sebghati, M.

2017-11-01

The process of water quality testing is money/time-consuming, quite important and difficult stage for routine measurements. Therefore, use of models has become commonplace in simulating water quality. In this study, the coactive neuro-fuzzy inference system (CANFIS) was used to simulate groundwater quality. Further, geographic information system (GIS) was used as the pre-processor and post-processor tool to demonstrate spatial variation of groundwater quality. All important factors were quantified and groundwater quality index (GWQI) was developed. The proposed model was trained and validated by taking a case study of Mazandaran Plain located in northern part of Iran. The factors affecting groundwater quality were the input variables for the simulation, whereas GWQI index was the output. The developed model was validated to simulate groundwater quality. Network validation was performed via comparison between the estimated and actual GWQI values. In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned. Therefore, numeric values of each pixel with geographical coordinates were entered to the Fuzzy Network-CANFIS model and thus simulation of groundwater quality was accessed in the study area. Finally, the simulated GWQI indices using the Fuzzy Network-CANFIS model were entered into GIS, and hence groundwater quality map (raster layer) based on the results of the network simulation was earned. The study's results confirm the high efficiency of incorporation of neuro-fuzzy techniques and GIS. It is also worth noting that the general quality of the groundwater in the most studied plain is fairly low.

A New Empirical Sewer Water Quality Model for the Prediction of WWTP Influent Quality

NARCIS (Netherlands)

Langeveld, J.G.; Schilperoort, R.P.S.; Rombouts, P.M.M.; Benedetti, L.; Amerlinck, Y.; de Jonge, J.; Flameling, T.; Nopens, I.; Weijers, S.

2014-01-01

Modelling of the integrated urban water system is a powerful tool to optimise wastewater system performance or to find cost-effective solutions for receiving water problems. One of the challenges of integrated modelling is the prediction of water quality at the inlet of a WWTP. Recent applications

How does network design constrain optimal operation of intermittent water supply?

Science.gov (United States)

Lieb, Anna; Wilkening, Jon; Rycroft, Chris

2015-11-01

Urban water distribution systems do not always supply water continuously or reliably. As pipes fill and empty, pressure transients may contribute to degraded infrastructure and poor water quality. To help understand and manage this undesirable side effect of intermittent water supply--a phenomenon affecting hundreds of millions of people in cities around the world--we study the relative contributions of fixed versus dynamic properties of the network. Using a dynamical model of unsteady transition pipe flow, we study how different elements of network design, such as network geometry, pipe material, and pipe slope, contribute to undesirable pressure transients. Using an optimization framework, we then investigate to what extent network operation decisions such as supply timing and inflow rate may mitigate these effects. We characterize some aspects of network design that make them more or less amenable to operational optimization.

Applying fuzzy analytic network process in quality function deployment model

Directory of Open Access Journals (Sweden)

Mohammad Ali Afsharkazemi

2012-08-01

Full Text Available In this paper, we propose an empirical study of QFD implementation when fuzzy numbers are used to handle the uncertainty associated with different components of the proposed model. We implement fuzzy analytical network to find the relative importance of various criteria and using fuzzy numbers we calculate the relative importance of these factors. The proposed model of this paper uses fuzzy matrix and house of quality to study the products development in QFD and also the second phase i.e. part deployment. In most researches, the primary objective is only on CRs to implement the quality function deployment and some other criteria such as production costs, manufacturing costs etc were disregarded. The results of using fuzzy analysis network process based on the QFD model in Daroupat packaging company to develop PVDC show that the most important indexes are being waterproof, resistant pill packages, and production cost. In addition, the PVDC coating is the most important index in terms of company experts’ point of view.

A decision tree model to estimate the value of information provided by a groundwater quality monitoring network

Science.gov (United States)

Khader, A. I.; Rosenberg, D. E.; McKee, M.

2013-05-01

Groundwater contaminated with nitrate poses a serious health risk to infants when this contaminated water is used for culinary purposes. To avoid this health risk, people need to know whether their culinary water is contaminated or not. Therefore, there is a need to design an effective groundwater monitoring network, acquire information on groundwater conditions, and use acquired information to inform management options. These actions require time, money, and effort. This paper presents a method to estimate the value of information (VOI) provided by a groundwater quality monitoring network located in an aquifer whose water poses a spatially heterogeneous and uncertain health risk. A decision tree model describes the structure of the decision alternatives facing the decision-maker and the expected outcomes from these alternatives. The alternatives include (i) ignore the health risk of nitrate-contaminated water, (ii) switch to alternative water sources such as bottled water, or (iii) implement a previously designed groundwater quality monitoring network that takes into account uncertainties in aquifer properties, contaminant transport processes, and climate (Khader, 2012). The VOI is estimated as the difference between the expected costs of implementing the monitoring network and the lowest-cost uninformed alternative. We illustrate the method for the Eocene Aquifer, West Bank, Palestine, where methemoglobinemia (blue baby syndrome) is the main health problem associated with the principal contaminant nitrate. The expected cost of each alternative is estimated as the weighted sum of the costs and probabilities (likelihoods) associated with the uncertain outcomes resulting from the alternative. Uncertain outcomes include actual nitrate concentrations in the aquifer, concentrations reported by the monitoring system, whether people abide by manager recommendations to use/not use aquifer water, and whether people get sick from drinking contaminated water. Outcome costs

Uncertainty analyses of the calibrated parameter values of a water quality model

Science.gov (United States)

Rode, M.; Suhr, U.; Lindenschmidt, K.-E.

2003-04-01

For river basin management water quality models are increasingly used for the analysis and evaluation of different management measures. However substantial uncertainties exist in parameter values depending on the available calibration data. In this paper an uncertainty analysis for a water quality model is presented, which considers the impact of available model calibration data and the variance of input variables. The investigation was conducted based on four extensive flowtime related longitudinal surveys in the River Elbe in the years 1996 to 1999 with varying discharges and seasonal conditions. For the model calculations the deterministic model QSIM of the BfG (Germany) was used. QSIM is a one dimensional water quality model and uses standard algorithms for hydrodynamics and phytoplankton dynamics in running waters, e.g. Michaelis Menten/Monod kinetics, which are used in a wide range of models. The multi-objective calibration of the model was carried out with the nonlinear parameter estimator PEST. The results show that for individual flow time related measuring surveys very good agreements between model calculation and measured values can be obtained. If these parameters are applied to deviating boundary conditions, substantial errors in model calculation can occur. These uncertainties can be decreased with an increased calibration database. More reliable model parameters can be identified, which supply reasonable results for broader boundary conditions. The extension of the application of the parameter set on a wider range of water quality conditions leads to a slight reduction of the model precision for the specific water quality situation. Moreover the investigations show that highly variable water quality variables like the algal biomass always allow a smaller forecast accuracy than variables with lower coefficients of variation like e.g. nitrate.

Comparison of 2002 Water Year and Historical Water-Quality Data, Upper Gunnison River Basin, Colorado

Science.gov (United States)

Spahr, N.E.

2003-01-01

Introduction: Population growth and changes in land-use practices have the potential to affect water quality and quantity in the upper Gunnison River basin. In 1995, the U.S. Geological Survey (USGS), in cooperation with local sponsors, City of Gunnison, Colorado River Water Conservation District, Crested Butte South Metropolitan District, Gunnison County, Mount Crested Butte Water and Sanitation District, National Park Service, Town of Crested Butte, and Upper Gunnison River Water Conservancy District, established a water-quality monitoring program in the upper Gunnison River basin to characterize current water-quality conditions and to assess the effects of increased urban development and other land-use changes on water quality. The monitoring network has evolved into two groups of stations, stations that are considered as long term and stations that are rotational. The long-term stations are monitored to assist in defining temporal changes in water quality (how conditions have changed over time). The rotational stations are monitored to assist in the spatial definition of water-quality conditions (how conditions differ throughout the basin) and to address local and short term concerns. Another group of stations (rotational group 2) will be chosen and sampled beginning in water year 2004. Annual summaries of the water-quality data from the monitoring network provide a point of reference for discussions regarding water-quality sampling in the upper Gunnison River basin. This summary includes data collected during water year 2002. The introduction provides a map of the sampling locations, definitions of terms, and a one-page summary of selected water-quality conditions at the network stations. The remainder of the summary is organized around the data collected at individual stations. Data collected during water year 2002 are compared to historical data (data collected for this network since 1995), state water-quality standards, and federal water-quality guidelines

Northern Great Plains Network water quality monitoring design for tributaries to the Missouri National Recreational River

Science.gov (United States)

Rowe, Barbara L.; Wilson, Stephen K.; Yager, Lisa; Wilson, Marcia H.

2013-01-01

The National Park Service (NPS) organized more than 270 parks with important natural resources into 32 ecoregional networks to conduct Inventory and Monitoring (I&M) activities for assessment of natural resources within park units. The Missouri National Recreational River (NRR) is among the 13 parks in the NPS Northern Great Plain Network (NGPN). Park managers and NGPN staff identified surface water resources as a high priority vital sign to monitor in park units. The objectives for the Missouri NRR water quality sampling design are to (1) assess the current status and long-term trends of select water quality parameters; and (2) document trends in streamflow at high-priority stream systems. Due to the large size of the Missouri River main stem, the NGPN water quality design for the Missouri NRR focuses on wadeable tributaries within the park unit. To correlate with the NGPN water quality protocols, monitoring of the Missouri NRR consists of measurement of field core parameters including dissolved oxygen, pH, specific conductance, and temperature; and streamflow. The purpose of this document is to discuss factors examined for selection of water quality monitoring on segments of the Missouri River tributaries within the Missouri NRR.Awareness of the complex history of the Missouri NRR aids in the current understanding and direction for designing a monitoring plan. Historical and current monitoring data from agencies and entities were examined to assess potential NGPN monitoring sites. In addition, the U.S. Environmental Protection Agency 303(d) list was examined for the impaired segments on tributaries to the Missouri River main stem. Because major tributaries integrate water quality effects from complex combinations of land use and environmental settings within contributing areas, a 20-mile buffer of the Missouri NRR was used to establish environmental settings that may impact the water quality of tributaries that feed the Missouri River main stem. For selection of

MPC control of water supply networks

DEFF Research Database (Denmark)

Baunsgaard, Kenneth Marx Hoe; Ravn, Ole; Kallesoe, Carsten Skovmose

2016-01-01

This paper investigates the modelling and predictive control of a drinking water supply network with the aim of minimising the energy and economic cost. A model predictive controller, MPC, is applied to a nonlinear model of a drinking water network that follows certain constraints to maintain......, controlling the drinking water supply network with the MPC showed reduction of the energy and the economic cost of running the system. This has been achieved by minimising actuator control effort and by shifting the actuator use towards the night time, where energy prices are lower. Along with energy cost...... consumer pressure desire. A model predictive controller, MPC, is based on a simple model that models the main characteristics of a water distribution network, optimizes a desired cost minimisation, and keeps the system inside specified constraints. In comparison to a logic (on/off) control design...

Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon

Science.gov (United States)

2016-07-01

was used to drive the transport and water quality kinetics for the simulation of 2007–2009. The sand berm, which controlled the opening/closure of...TECHNICAL REPORT 3015 July 2016 Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei...Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei-Fang Wang Chuck Katz Ripan Barua SSC Pacific James

Design of Cycle 3 of the National Water-Quality Assessment Program, 2013-23: Part 2: Science plan for improved water-quality information and management

Science.gov (United States)

Rowe, Gary L.; Belitz, Kenneth; Demas, Charlie R.; Essaid, Hedeff I.; Gilliom, Robert J.; Hamilton, Pixie A.; Hoos, Anne B.; Lee, Casey J.; Munn, Mark D.; Wolock, David W.

2013-01-01

This report presents a science strategy for the third decade of the National Water-Quality Assessment (NAWQA) Program, which since 1991, has been responsible for providing nationally consistent information on the quality of the Nation's streams and groundwater; how water quality is changing over time; and the major natural and human factors that affect current water quality conditions and trends. The strategy is based on an extensive evaluation of the accomplishments of NAWQA over its first two decades, the current status of water-quality monitoring activities by USGS and its partners, and an updated analysis of stakeholder priorities. The plan is designed to address priority issues and national needs identified by NAWQA stakeholders and the National Research Council (2012) irrespective of budget constraints. This plan describes four major goals for the third decade (Cycle 3), the approaches for monitoring, modeling, and scientific studies, key partnerships required to achieve these goals, and products and outcomes that will result from planned assessment activities. The science plan for 2013–2023 is a comprehensive approach to meet stakeholder priorities for: (1) rebuilding NAWQA monitoring networks for streams, rivers, and groundwater, and (2) upgrading models used to extrapolate and forecast changes in water-quality and stream ecosystem condition in response to changing climate and land use. The Cycle 3 plan continues approaches that have been central to the Program’s long-term success, but adjusts monitoring intensities and study designs to address critical information needs and identified data gaps. Restoration of diminished monitoring networks and new directions in modeling and interpretative studies address growing and evolving public and stakeholder needs for water-quality information and improved management, particularly in the face of increasing challenges related to population growth, increasing demands for water, and changing land use and climate

Evaluation of the Current State of Integrated Water Quality Modelling

Science.gov (United States)

Arhonditsis, G. B.; Wellen, C. C.; Ecological Modelling Laboratory

2010-12-01

Environmental policy and management implementation require robust methods for assessing the contribution of various point and non-point pollution sources to water quality problems as well as methods for estimating the expected and achieved compliance with the water quality goals. Water quality models have been widely used for creating the scientific basis for management decisions by providing a predictive link between restoration actions and ecosystem response. Modelling water quality and nutrient transport is challenging due a number of constraints associated with the input data and existing knowledge gaps related to the mathematical description of landscape and in-stream biogeochemical processes. While enormous effort has been invested to make watershed models process-based and spatially-distributed, there has not been a comprehensive meta-analysis of model credibility in watershed modelling literature. In this study, we evaluate the current state of integrated water quality modeling across the range of temporal and spatial scales typically utilized. We address several common modeling questions by providing a quantitative assessment of model performance and by assessing how model performance depends on model development. The data compiled represent a heterogeneous group of modeling studies, especially with respect to complexity, spatial and temporal scales and model development objectives. Beginning from 1992, the year when Beven and Binley published their seminal paper on uncertainty analysis in hydrological modelling, and ending in 2009, we selected over 150 papers fitting a number of criteria. These criteria involved publications that: (i) employed distributed or semi-distributed modelling approaches; (ii) provided predictions on flow and nutrient concentration state variables; and (iii) reported fit to measured data. Model performance was quantified with the Nash-Sutcliffe Efficiency, the relative error, and the coefficient of determination. Further, our

Water quality modelling in the San Antonio River Basin driven by radar rainfall data

OpenAIRE

Almoutaz Elhassan; Hongjie Xie; Ahmed A. Al-othman; James Mcclelland; Hatim O. Sharif

2016-01-01

Continuous monitoring of stream water quality is needed as it has significant impacts on human and ecological health and well-being. Estimating water quality between sampling dates requires model simulation based on the available geospatial and water quality data for a given watershed. Models such as the Soil and Water Assessment Tool (SWAT) can be used to estimate the missing water quality data. In this study, SWAT was used to estimate water quality at a monitoring station near the outlet of...

Coastal Water Quality Modeling in Tidal Lake: Revisited with Groundwater Intrusion

Science.gov (United States)

Kim, C.

2016-12-01

A new method for predicting the temporal and spatial variation of water quality, with accounting for a groundwater effect, has been proposed and applied to a water body partially connected to macro-tidal coastal waters in Korea. The method consists of direct measurement of environmental parameters, and it indirectly incorporates a nutrients budget analysis to estimate the submarine groundwater fluxes. Three-dimensional numerical modeling of water quality has been used with the directly collected data and the indirectly estimated groundwater fluxes. The applied area is Saemangeum tidal lake that is enclosed by 33km-long sea dyke with tidal openings at two water gates. Many investigations of groundwater impact reveal that 10 50% of nutrient loading in coastal waters comes from submarine groundwater, particularly in the macro-tidal flat, as in the west coast of Korea. Long-term monitoring of coastal water quality signals the possibility of groundwater influence on salinity reversal and on the excess mass outbalancing the normal budget in Saemangeum tidal lake. In the present study, we analyze the observed data to examine the influence of submarine groundwater, and then a box model is demonstrated for quantifying the influx and efflux. A three-dimensional numerical model has been applied to reproduce the process of groundwater dispersal and its effect on the water quality of Saemangeum tidal lake. The results show that groundwater influx during the summer monsoon then contributes significantly, 20% more than during dry season, to water quality in the tidal lake.

Ground-water-quality assessment of the Central Oklahoma aquifer, Oklahoma; hydrologic, water-quality, and quality-assurance data 1987-90

Science.gov (United States)

Ferree, D.M.; Christenson, S.C.; Rea, A.H.; Mesander, B.A.

1992-01-01

This report presents data collected from 202 wells between June 1987 and September 1990 as part of the Central Oklahoma aquifer pilot study of the National Water-Quality Assessment Program. The report describes the sampling networks, the sampling procedures, and the results of the ground-water quality and quality-assurance sample analyses. The data tables consist of information about the wells sampled and the results of the chemical analyses of ground water and quality-assurance sampling. Chemical analyses of ground-water samples in four sampling networks are presented: A geochemical network, a low-density survey bedrock network, a low-density survey alluvium and terrace deposits network, and a targeted urban network. The analyses generally included physical properties, major ions, nutrients, trace substances, radionuclides, and organic constituents. The chemical analyses of the ground-water samples are presented in five tables: (1) Physical properties and concentrations of major ions, nutrients, and trace substances; (2) concentrations of radionuclides and radioactivities; (3) carbon isotope ratios and delta values (d-values) of selected isotopes; (4) concentrations of organic constituents; and (5) organic constituents not reported in ground-water samples. The quality of the ground water sampled varied substantially. The sum of constituents (dissolved solids) concentrations ranged from 71 to 5,610 milligrams per liter, with 38 percent of the wells sampled exceeding the Secondary Maximum Contaminant Level of 500 milligrams per liter established under the Safe Drinking Water Act. Values of pH ranged from 5.7 to 9.2 units with 20 percent of the wells outside the Secondary Maximum Contaminant Level of 6.5 to 8.5 units. Nitrite plus nitrate concentrations ranged from less than 0.1 to 85 milligrams per liter with 8 percent of the wells exceeding the proposed Maximum Contaminant Level of 10 milligrams per liter. Concentrations of trace substances were highly variable

Hydraulic Model for Drinking Water Networks, Including Household Connections; Modelo hidraulico para redes de agua potable con tomas domiciliarias

Energy Technology Data Exchange (ETDEWEB)

Guerrero Angulo, Jose Oscar [Universidad Autonoma de Sinaloa (Mexico); Arreguin Cortes, Felipe [Instituto Mexicano de Tecnologia del Agua, Jiutepec, Morelos (Mexico)

2002-03-01

This paper presents a hydraulic simulation model for drinking water networks, including elements that are currently not considered household connections, spatially variable flowrate distribution pipelines, and tee secondary network. This model is determined by solving the equations needed for a conventional model following an indirect procedure for the solution of large equations systems. Household connection performance is considered as dependent of water pressure and the way in which users operate the taps of such intakes. This approach allows a better a acquaintance with the drinking water supply networks performance as well as solving problems that demand a more precise hydraulic simulation, such as water quality variations, leaks in networks, and the influence of home water tanks as regulating devices. [Spanish] Se presenta un modelo de simulacion hidraulica para redes de agua potable en el cual se incluyen elementos que no se toman en cuenta actualmente, como las tomas domiciliarias, los tubos de distribucion con gastos espacialmente variado y la red secundaria, resolviendo el numero de ecuaciones que seria necesario plantear en un modelo convencional mediante un procedimiento indirecto para la solucion de grandes sistemas de ecuaciones. En las tomas domiciliarias se considera que su funcionamiento depende de las presiones y la forma en que los usuarios operan las llaves de las mismas. Este planteamiento permite conocer mejor el funcionamiento de las redes de abastecimiento de agua potable y solucionar problemas que requieren de una simulacion hidraulica mas precisa, como el comportamiento de la calidad del agua, las fugas en las redes y la influencia reguladora de los tinacos de las casas.

Assessment for water quality by artificial neural network in Daya Bay, South China Sea.

Science.gov (United States)

Wu, Mei-Lin; Wang, You-Shao; Gu, Ji-Dong

2015-10-01

In this study, artificial neural network such as a self-organizing map (SOM) was used to assess for the effects caused by climate change and human activities on the water quality in Daya Bay, South China Sea. SOM has identified the anthropogenic effects and seasonal characters of water quality. SOM grouped the four seasons as four groups (winter, spring, summer and autumn). The Southeast Asian monsoons, northeasterly from October to the next April and southwesterly from May to September have also an important influence on the water quality in Daya Bay. Spatial pattern is mainly related to anthropogenic activities and hydrodynamics conditions. In spatial characteristics, the water quality in Daya Bay was divided into two groups by chemometrics. The monitoring stations (S3, S8, S10 and S11) were in these area (Dapeng Ao, Aotou Harbor) and northeast parts of Daya Bay, which are areas of human activity. The thermal pollution has been observed near water body in Daya Bay Nuclear Power Plant (S5). The rest of the monitoring sites were in the south, central and eastern parts of Daya Bay, which are areas that experience water exchanges from South China Sea. The results of this study may provide information on the spatial and temporal patterns in Daya Bay. Further research will be carry out more research concerning functional changes in the bay ecology with respect to changes in climatic factor, human activities and bay morphology in Daya Bay.

A Probabilistic Model for Propagating Ungauged Basin Runoff Prediction Variability and Uncertainty Into Estuarine Water Quality Dynamics and Water Quality-Based Management Decisions

Science.gov (United States)

Anderson, R.; Gronewold, A.; Alameddine, I.; Reckhow, K.

2008-12-01

The latest official assessment of United States (US) surface water quality indicates that pathogens are a leading cause of coastal shoreline water quality standard violations. Rainfall-runoff and hydrodynamic water quality models are commonly used to predict fecal indicator bacteria (FIB) concentrations in these waters and to subsequently identify climate change, land use, and pollutant mitigation scenarios which might improve water quality and lead to reinstatement of a designated use. While decay, settling, and other loss kinetics dominate FIB fate and transport in freshwater systems, previous authors identify tidal advection as a dominant fate and transport process in coastal estuaries. As a result, acknowledging hydrodynamic model input (e.g. watershed runoff) variability and parameter (e.g tidal dynamics parameter) uncertainty is critical to building a robust coastal water quality model. Despite the widespread application of watershed models (and associated model calibration procedures), we find model inputs and parameters are commonly encoded as deterministic point estimates (as opposed to random variables), an approach which effectively ignores potential sources of variability and uncertainty. Here, we present an innovative approach to building, calibrating, and propagating uncertainty and variability through a coupled data-based mechanistic (DBM) rainfall-runoff and tidal prism water quality model. While we apply the model to an ungauged tributary of the Newport River Estuary (one of many currently impaired shellfish harvesting waters in Eastern North Carolina), our model can be used to evaluate water quality restoration scenarios for coastal waters with a wide range of designated uses. We begin by calibrating the DBM rainfall-runoff model, as implemented in the IHACRES software package, using a regionalized calibration approach. We then encode parameter estimates as random variables (in the rainfall-runoff component of our comprehensive model) via the

Joint physical and numerical modeling of water distribution networks.

Energy Technology Data Exchange (ETDEWEB)

Zimmerman, Adam; O' Hern, Timothy John; Orear, Leslie Jr.; Kajder, Karen C.; Webb, Stephen Walter; Cappelle, Malynda A.; Khalsa, Siri Sahib; Wright, Jerome L.; Sun, Amy Cha-Tien; Chwirka, J. Benjamin; Hartenberger, Joel David; McKenna, Sean Andrew; van Bloemen Waanders, Bart Gustaaf; McGrath, Lucas K.; Ho, Clifford Kuofei

2009-01-01

This report summarizes the experimental and modeling effort undertaken to understand solute mixing in a water distribution network conducted during the last year of a 3-year project. The experimental effort involves measurement of extent of mixing within different configurations of pipe networks, measurement of dynamic mixing in a single mixing tank, and measurement of dynamic solute mixing in a combined network-tank configuration. High resolution analysis of turbulence mixing is carried out via high speed photography as well as 3D finite-volume based Large Eddy Simulation turbulence models. Macroscopic mixing rules based on flow momentum balance are also explored, and in some cases, implemented in EPANET. A new version EPANET code was developed to yield better mixing predictions. The impact of a storage tank on pipe mixing in a combined pipe-tank network during diurnal fill-and-drain cycles is assessed. Preliminary comparison between dynamic pilot data and EPANET-BAM is also reported.

Modeling Water Clarity and Light Quality in Oceans

Directory of Open Access Journals (Sweden)

Mohamed A. Abdelrhman

2016-11-01

Full Text Available Phytoplankton is a primary producer of organic compounds, and it forms the base of the food chain in ocean waters. The concentration of phytoplankton in the water column controls water clarity and the amount and quality of light that penetrates through it. The availability of adequate light intensity is a major factor in the health of algae and phytoplankton. There is a strong negative coupling between light intensity and phytoplankton concentration (e.g., through self-shading by the cells, which reduces available light and in return affects the growth rate of the cells. Proper modeling of this coupling is essential to understand primary productivity in the oceans. This paper provides the methodology to model light intensity in the water column, which can be included in relevant water quality models. The methodology implements relationships from bio-optical models, which use phytoplankton chlorophyll a (chl-a concentration as a surrogate for light attenuation, including absorption and scattering by other attenuators. The presented mathematical methodology estimates the reduction in light intensity due to absorption by pure seawater, chl-a pigment, non-algae particles (NAPs and colored dissolved organic matter (CDOM, as well as backscattering by pure seawater, phytoplankton particles and NAPs. The methods presented facilitate the prediction of the effects of various environmental and management scenarios (e.g., global warming, altered precipitation patterns, greenhouse gases on the wellbeing of phytoplankton communities in the oceans as temperature-driven chl-a changes take place.

Water hammer research in networks

Directory of Open Access Journals (Sweden)

Anželika Jurkienė

2015-10-01

Full Text Available Formation of water hammer, its consequences and possible protection measures are rarely topics, however the problem is significant. Water hammer can form in water supply and pressurized sewage networks, for various reasons. The article presents short theory of water hammer and methodology for calculation of specific parameters. Research of water hammer was performed in real water supply and sewer networks of country. Simulation of water hammer was carried out by turning on and off water pumps in pumping station. Successful measurement of water hammer depends on accuracy of the measurement equipment, therefore during the research surge wave fluctuations were measured with especially high resolution pressure meters. Detailed analysis of water hammer and selection of protecting equipment hydraulic model of water supply network was created. Protection against water hammer helps to avoid breaking of the water network and extend operation time.

Modeling of Water Quality 'Almendares River'

International Nuclear Information System (INIS)

Domínguez Catasús, Judith

2005-01-01

The river Almendares, one of the most important water bodies of the Havana City, is very polluted. The analysis of parameters as dissolved oxygen and biochemical oxygen demand is very helpful for the studies aimed to the recovery of the river. There is a growing recognition around the word that the water quality models are very useful tools to plan sanitary strategies for the handling of the contamination. In the present work, the advective, steady- state Streeter and Phelps model was validated to simulate the effect of the multiple-point and distributed sources on the carbonaceous oxygen demand, NH4 and dissolved oxygen. For modeling purposes the section of the river located between the point where the waste water treatment station Maria del Carmen discharges to the river and the Bridge El Bosque, was divided in 11 segments. The use of the 99mTc and the Rodamine WT as tracers allowed determining the hydrodynamic parameters necessary for modeling purposes. The validated model allows to predict the effect of the sanitary strategies on the water quality of the river. The main conclusions are: 1. The model Streeter and Phelps calibrated and validated in the Almendares between the confluence of the channel 'María del Carmen' and bridge the Forest of Havana, described in more than 90% The behavior of the dissolved oxygen and BODn (in terms of ammonia), and more than 85%, the carbonaceous demand oxygen, which characterizes the process of purification. 2. Model validation Streeter and Phelps, indicates that implicit conceptual model is appropriate. This refers primarily to the considerations relating to the calculation of the kinetic constants and the DOS, the segmentation used, to the location of the discharges and the Standing been about them, to the river morphology and hydrodynamic parameters . 3. The calibration procedure Streeter and Phelps model that determines the least-squares Kr-Kd pair that best fits the OD and uses this Kr to model BOD gets four% increase in

Hydraulic Network Modelling of Small Community Water Distribution ...

African Journals Online (AJOL)

Prof Anyata

... design of a small community (Sakwa) water distribution network in North Eastern geopolitical region of Nigeria using ..... self cleansing drinking water distribution system is set at 0.4m/s, .... distribution network offers advantages over manual ...

Multi-agent modelling framework for water, energy and other resource networks

Science.gov (United States)

Knox, S.; Selby, P. D.; Meier, P.; Harou, J. J.; Yoon, J.; Lachaut, T.; Klassert, C. J. A.; Avisse, N.; Mohamed, K.; Tomlinson, J.; Khadem, M.; Tilmant, A.; Gorelick, S.

2015-12-01

Bespoke modelling tools are often needed when planning future engineered interventions in the context of various climate, socio-economic and geopolitical futures. Such tools can help improve system operating policies or assess infrastructure upgrades and their risks. A frequently used approach is to simulate and/or optimise the impact of interventions in engineered systems. Modelling complex infrastructure systems can involve incorporating multiple aspects into a single model, for example physical, economic and political. This presents the challenge of combining research from diverse areas into a single system effectively. We present the Pynsim 'Python Network Simulator' framework, a library for building simulation models capable of representing, the physical, institutional and economic aspects of an engineered resources system. Pynsim is an open source, object oriented code aiming to promote integration of different modelling processes through a single code library. We present two case studies that demonstrate important features of Pynsim's design. The first is a large interdisciplinary project of a national water system in the Middle East with modellers from fields including water resources, economics, hydrology and geography each considering different facets of a multi agent system. It includes: modelling water supply and demand for households and farms; a water tanker market with transfer of water between farms and households, and policy decisions made by government institutions at district, national and international level. This study demonstrates that a well-structured library of code can provide a hub for development and act as a catalyst for integrating models. The second focuses on optimising the location of new run-of-river hydropower plants. Using a multi-objective evolutionary algorithm, this study analyses different network configurations to identify the optimal placement of new power plants within a river network. This demonstrates that Pynsim can be

Groundwater-quality data from the National Water-Quality Assessment Project, January through December 2014 and select quality-control data from May 2012 through December 2014

Science.gov (United States)

Arnold, Terri L.; Bexfield, Laura M.; Musgrove, MaryLynn; Lindsey, Bruce D.; Stackelberg, Paul E.; Barlow, Jeannie R.; Desimone, Leslie A.; Kulongoski, Justin T.; Kingsbury, James A.; Ayotte, Joseph D.; Fleming, Brandon J.; Belitz, Kenneth

2017-10-05

Groundwater-quality data were collected from 559 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program from January through December 2014. The data were collected from four types of well networks: principal aquifer study networks, which are used to assess the quality of groundwater used for public water supply; land-use study networks, which are used to assess land-use effects on shallow groundwater quality; major aquifer study networks, which are used to assess the quality of groundwater used for domestic supply; and enhanced trends networks, which are used to evaluate the time scales during which groundwater quality changes. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some constituents of special interest (arsenic speciation, chromium [VI] and perchlorate). These groundwater-quality data, along with data from quality-control samples, are tabulated in this report and in an associated data release.

Water quality in irrigation and drainage networks of Thessaloniki plain in Greece related to land use, water management, and agroecosystem protection.

Science.gov (United States)

Litskas, Vassilis D; Aschonitis, Vassilis G; Antonopoulos, Vassilis Z

2010-04-01

A representative agricultural area of 150 ha located in a protected ecosystem (Axios River Delta, Thermaikos Gulf-N. Aegean, Greece) was selected in order to investigate water quality parameters [pH, electrical conductivity (EC(w)), NO(3)-N, NH(4)-N, total phosphorus (TP)] in irrigation and drainage water. In the study area, the cultivated crops are mainly rice, maize, cotton, and fodder. Surface irrigation methods are applied using open channels network, and irrigation water is supplied by Axios River, which is facing pollution problems. The return flow from surface runoff and the surplus of irrigation water are collected to drainage network and disposed to Thermaikos Gulf. A 2-year study (2006-2007) was conducted in order to evaluate the effects of land use and irrigation water management on the drainage water quality. The average pH and NO(3)-N concentration was higher in the irrigation water (8.0 and 1.3 mg/L, respectively) than that in the drainage water (7.6 and 1.0 mg/L, respectively). The average EC(W), NH(4)-N, and TP concentration was higher in the drainage water (1,754 muS/cm, 90.3 microg/L, and 0.2 mg/L, respectively) than that in the irrigation water (477.1 muS/cm, 46.7 microg/L, and 0.1 mg/L, respectively). Average irrigation efficiency was estimated at 47% and 51% in 2006 and 2007 growing seasons (April-October), respectively. The loads of NO(3)-N in both seasons were higher in the irrigation water (35.1 kg/ha in 2006 and 24.9 kg/ha in 2007) than those in the drainage water (8.1 kg/ha in 2006 and 7.6 kg/ha in 2007). The load of TP was higher in the irrigation water in season 2006 (2.8 kg/ha) than that in the drainage water (1.1 kg/ha). Total phosphorus load in 2007 was equal in irrigation and drainage water (1.2 kg/ha). Wetland conditions, due to rice irrigation regime, drainage network characteristics, and the crop distribution in the study area, affect the drainage water ending in the protected ecosystem of Thermaikos Gulf.

Projection pursuit water quality evaluation model based on chicken swam algorithm

Science.gov (United States)

Hu, Zhe

2018-03-01

In view of the uncertainty and ambiguity of each index in water quality evaluation, in order to solve the incompatibility of evaluation results of individual water quality indexes, a projection pursuit model based on chicken swam algorithm is proposed. The projection index function which can reflect the water quality condition is constructed, the chicken group algorithm (CSA) is introduced, the projection index function is optimized, the best projection direction of the projection index function is sought, and the best projection value is obtained to realize the water quality evaluation. The comparison between this method and other methods shows that it is reasonable and feasible to provide decision-making basis for water pollution control in the basin.

Design of environmental decision support system and its application to water quality management

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

EDSS is a comprehensive software system for water quality management in tidal river networks in general and for the Pearl River Delta in particular. Its purpose is to provide a practical tool that could assist government agencies in decision making for the efficient management of water resources in terms of both quantity and quality. By combining the capabilities of geographical information system (GIS), database management system (DBMS), model base management system (MBMS) and expert system, the aim is to improve the quality of decision making in what is becoming an increasingly complex area. This paper first outlines the basic concepts and philosophy adopted in developing EDSS, the system architecture, design features, implementation techniques and facilities provided. Thereafter, the core part of the system the hydrodynamic and water quality models are described briefly. The final contribution in this paper describes the application of EDSS to the Pearl River Delta, which has the most complicated tidal river network patterns as well as the fastest economic development in the world. Examples are given of the real-world problems that can be addressed using the system, including cross-boundary water pollution analysis, regional drinking water take-up site selection, screening of important polluters, environmental impact assessment, and water quality zoning and planning. It is illustrated that EDSS can provide efficient and scientific analytical tools for planning and decision-making purposes in the information era.

Monitoring surface-water quality in Arizona: the fixed-station network

Science.gov (United States)

Tadayon, Saeid

2000-01-01

Arizona is an arid State in which economic development is influenced largely by the quantity and quality of water and the location of adequate water supplies. In 1995, surface water supplied about 58 percent of total withdrawals in Arizona. Of the total amount of surface water used in 1995, about 89 percent was for agriculture, 10 percent for public supply, and 1 percent for industrial supply (including mining and thermoelectric; Solley and others, 1998). As a result of rapid population growth in Arizona, historic agricultural lands in the Phoenix (Maricopa County) and Tucson (Pima County) areas are now being developed for residential and commercial use; thus, the amount of water used for public supply is increasing. The Clean Water Act was established by U.S. Congress (1972) in response to public concern about water-pollution control. The act defines a process by which the United States Congress and the citizens are informed of the Nation’s progress in restoring and maintaining the quality of our waters. The Arizona Department of Environmental Quality (ADEQ) is the State-designated agency for this process and, as a result, has developed a monitoring program to assess water quality in Arizona. The ADEQ is required to submit a water-quality assessment report to the United States Environmental Protection Agency (USEPA) every 2 years. The USEPA summarizes the reports from each State and submits a report to the Congress characterizing water quality in the United States. These reports serve to inform Congress and the public of the Nation’s progress toward the restoration and maintenance of water quality in the United States (Arizona Department of Environmental Quality, 1998).

Tracing disturbance impacts on water quantity and quality through a stream network

Science.gov (United States)

Ross, Matthew; Nippgen, Fabian; McGlynn, Brian; Bernhardt, Emily

2017-04-01

By dismantling and redistributing 100s of meters of bedrock to mine coal from the surface, mountaintop mining with valley fills has dramatically changed catchment hydrology and biogeochemistry over more than 5,000 km2 in Central Appalachia. Throughout this expansive coal region, mining operators deposit tens of millions of m3 of crushed bedrock into headwater valleys, creating valley fills, which have substantial subsurface water storage potential. Streams draining mines have reduced peakflows, elevated baseflows, and lower event runoff ratios on average. The water stored in and percolating through valley fills drives the dissolution and oxidation of pyrite into sulfuric acid which reacts with carbonate-rich materials to rapidly weather out a suite of elements including Ca2+, Mg2+, K+, SO42-, HCO3-, and the pollutant Selenium. Together these ions increase the average specific conductance of mined streams from 60 to 1,500 µS/cm, 25-times higher than unmined streams, exporting 45-times more total dissolved solids. Together, the increased catchment storage, consequent elevated baseflow, and elevated weathering rates from mining have the potential to lower water quality throughout river networks in Central Appalachia, especially during the summer low flow period. To better understand the water quality impacts of mining at the river network scale, we used the paired catchment approach. Working in the Mud River, West Virginia, we instrumented a 4th order catchment 35 km2, that was 46% mined. Within the large catchment we instrumented 8 additional 1st-3rd order sub-catchments that varied in catchment size, mining cover, mine size, and mine age. At each site we measured stream discharge and specific conductance (SC). Using SC as a trace for mining we did simple hydrograph separations at our largest catchments, partitioning the hydrograph between mined and unmined water. Our results suggest that on an annual scale, mine water contributes a disproportionate percentage of

Video Quality Prediction Models Based on Video Content Dynamics for H.264 Video over UMTS Networks

Directory of Open Access Journals (Sweden)

Asiya Khan

2010-01-01

Full Text Available The aim of this paper is to present video quality prediction models for objective non-intrusive, prediction of H.264 encoded video for all content types combining parameters both in the physical and application layer over Universal Mobile Telecommunication Systems (UMTS networks. In order to characterize the Quality of Service (QoS level, a learning model based on Adaptive Neural Fuzzy Inference System (ANFIS and a second model based on non-linear regression analysis is proposed to predict the video quality in terms of the Mean Opinion Score (MOS. The objective of the paper is two-fold. First, to find the impact of QoS parameters on end-to-end video quality for H.264 encoded video. Second, to develop learning models based on ANFIS and non-linear regression analysis to predict video quality over UMTS networks by considering the impact of radio link loss models. The loss models considered are 2-state Markov models. Both the models are trained with a combination of physical and application layer parameters and validated with unseen dataset. Preliminary results show that good prediction accuracy was obtained from both the models. The work should help in the development of a reference-free video prediction model and QoS control methods for video over UMTS networks.

Effect of the spatiotemporal variability of rainfall inputs in water quality integrated catchment modelling for dissolved oxygen concentrations

Science.gov (United States)

Moreno Ródenas, Antonio Manuel; Cecinati, Francesca; ten Veldhuis, Marie-Claire; Langeveld, Jeroen; Clemens, Francois

2016-04-01

Maintaining water quality standards in highly urbanised hydrological catchments is a worldwide challenge. Water management authorities struggle to cope with changing climate and an increase in pollution pressures. Water quality modelling has been used as a decision support tool for investment and regulatory developments. This approach led to the development of integrated catchment models (ICM), which account for the link between the urban/rural hydrology and the in-river pollutant dynamics. In the modelled system, rainfall triggers the drainage systems of urban areas scattered along a river. When flow exceeds the sewer infrastructure capacity, untreated wastewater enters the natural system by combined sewer overflows. This results in a degradation of the river water quality, depending on the magnitude of the emission and river conditions. Thus, being capable of representing these dynamics in the modelling process is key for a correct assessment of the water quality. In many urbanised hydrological systems the distances between draining sewer infrastructures go beyond the de-correlation length of rainfall processes, especially, for convective summer storms. Hence, spatial and temporal scales of selected rainfall inputs are expected to affect water quality dynamics. The objective of this work is to evaluate how the use of rainfall data from different sources and with different space-time characteristics affects modelled output concentrations of dissolved oxygen in a simplified ICM. The study area is located at the Dommel, a relatively small and sensitive river flowing through the city of Eindhoven (The Netherlands). This river stretch receives the discharge of the 750,000 p.e. WWTP of Eindhoven and from over 200 combined sewer overflows scattered along its length. A pseudo-distributed water quality model has been developed in WEST (mikedhi.com); this is a lumped-physically based model that accounts for urban drainage processes, WWTP and river dynamics for several

Water quality modeling of the Medellin river in the Aburrá Valley

OpenAIRE

Giraldo-B., Lina Claudia; Palacio, Carlos Alberto; Molina, Rubén; Agudelo, Rubén Alberto

2015-01-01

Water quality modeling intends to represent a water body in order to assess their status and project the effects of different measures taken for their protection. This paper presents the results obtained from the Qual2kw model implementation in the first 50 kilometers of the Aburrá-Medellín River, in their most critical conditions of water quality, which correspond to low flow rates. After the model calibration, three recovery scenarios (short-term, medium-term and long-term) were evaluated. ...

Root zone water quality model (RZWQM2): Model use, calibration and validation

Science.gov (United States)

Ma, Liwang; Ahuja, Lajpat; Nolan, B.T.; Malone, Robert; Trout, Thomas; Qi, Z.

2012-01-01

The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.

Real Time Assessment of Potable Water Quality in Distribution Network based on Low Cost Multi-Sensor Array

Science.gov (United States)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Khatri, Punit

2018-03-01

New concepts and techniques are replacing traditional methods of water quality parameters measurement systems. This paper proposed a new way of potable water quality assessment in distribution network using Multi Sensor Array (MSA). Extensive research suggests that following parameters i.e. pH, Dissolved Oxygen (D.O.), Conductivity, Oxygen Reduction Potential (ORP), Temperature and Salinity are most suitable to detect overall quality of potable water. Commonly MSA is not an integrated sensor array on some substrate, but rather comprises a set of individual sensors measuring simultaneously different water parameters all together. Based on research, a MSA has been developed followed by signal conditioning unit and finally, an algorithm for easy user interfacing. A dedicated part of this paper also discusses the platform design and significant results. The Objective of this proposed research is to provide simple, efficient, cost effective and socially acceptable means to detect and analyse water bodies regularly and automatically.

Comparison of Water Years 2004-05 and Historical Water-Quality Data, Upper Gunnison River Basin, Colorado

Science.gov (United States)

Spahr, Norman E.; Hartle, David M.; Diaz, Paul

2008-01-01

Population growth and changes in land use have the potential to affect water quality and quantity in the upper Gunnison River Basin. In 1995, the U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, City of Gunnison, Colorado River Water Conservation District, Crested Butte South Metropolitan District, Gunnison County, Hinsdale County, Mount Crested Butte Water and Sanitation District, National Park Service, Town of Crested Butte, Upper Gunnison River Water Conservancy District, and Western State College, established a water-quality monitoring program in the upper Gunnison River Basin to characterize current water-quality conditions and to assess the effects of increased urban development and other land-use changes on water quality. The monitoring network has evolved into two groups of stations - stations that are considered long term and stations that are considered rotational. The long-term stations are monitored to assist in defining temporal changes in water quality (how conditions may change over time). The rotational stations are monitored to assist in the spatial definition of water-quality conditions (how conditions differ throughout the basin) and to address local and short-term concerns. Some stations in the rotational group were changed beginning in water year 2007. Annual summaries of the water-quality data from the monitoring network provide a point of reference for discussions regarding water-quality monitoring in the upper Gunnison River Basin. This summary includes data collected during water years 2004 and 2005. The introduction provides a map of the sampling sites, definitions of terms, and a one-page summary of selected water-quality conditions at the network stations. The remainder of the summary is organized around the data collected at individual stations. Data collected during water years 2004 and 2005 are compared to historical data, State water-quality standards, and Federal water-quality guidelines. Data were

Bayesian Belief Networks for predicting drinking water distribution system pipe breaks

International Nuclear Information System (INIS)

Francis, Royce A.; Guikema, Seth D.; Henneman, Lucas

2014-01-01

In this paper, we use Bayesian Belief Networks (BBNs) to construct a knowledge model for pipe breaks in a water zone. To the authors’ knowledge, this is the first attempt to model drinking water distribution system pipe breaks using BBNs. Development of expert systems such as BBNs for analyzing drinking water distribution system data is not only important for pipe break prediction, but is also a first step in preventing water loss and water quality deterioration through the application of machine learning techniques to facilitate data-based distribution system monitoring and asset management. Due to the difficulties in collecting, preparing, and managing drinking water distribution system data, most pipe break models can be classified as “statistical–physical” or “hypothesis-generating.” We develop the BBN with the hope of contributing to the “hypothesis-generating” class of models, while demonstrating the possibility that BBNs might also be used as “statistical–physical” models. Our model is learned from pipe breaks and covariate data from a mid-Atlantic United States (U.S.) drinking water distribution system network. BBN models are learned using a constraint-based method, a score-based method, and a hybrid method. Model evaluation is based on log-likelihood scoring. Sensitivity analysis using mutual information criterion is also reported. While our results indicate general agreement with prior results reported in pipe break modeling studies, they also suggest that it may be difficult to select among model alternatives. This model uncertainty may mean that more research is needed for understanding whether additional pipe break risk factors beyond age, break history, pipe material, and pipe diameter might be important for asset management planning. - Highlights: • We show Bayesian Networks for predictive and diagnostic management of water distribution systems. • Our model may enable system operators and managers to prioritize system

Model-based monitoring techniques for leakage localization in distribution water networks

OpenAIRE

Meseguer Amela, Jordi; Mirats Tur, Josep Maria; Cembrano Gennari, Gabriela; Puig Cayuela, Vicenç

2015-01-01

This is an open access article under the CC BY-NC-ND license This paper describes an integrated model-based monitoring framework for leakage localization in district-metered areas (DMA) of water distribution networks, which takes advantage of the availability of a hydraulic model of the network. The leakage localization methodology is based on the use of flow and pressure sensors at the DMA inlets and a limited number of pressure sensors deployed inside the DMA. The placement of these sens...

Accounting for and predicting the influence of spatial autocorrelation in water quality modeling

Science.gov (United States)

Miralha, L.; Kim, D.

2017-12-01

Although many studies have attempted to investigate the spatial trends of water quality, more attention is yet to be paid to the consequences of considering and ignoring the spatial autocorrelation (SAC) that exists in water quality parameters. Several studies have mentioned the importance of accounting for SAC in water quality modeling, as well as the differences in outcomes between models that account for and ignore SAC. However, the capacity to predict the magnitude of such differences is still ambiguous. In this study, we hypothesized that SAC inherently possessed by a response variable (i.e., water quality parameter) influences the outcomes of spatial modeling. We evaluated whether the level of inherent SAC is associated with changes in R-Squared, Akaike Information Criterion (AIC), and residual SAC (rSAC), after accounting for SAC during modeling procedure. The main objective was to analyze if water quality parameters with higher Moran's I values (inherent SAC measure) undergo a greater increase in R² and a greater reduction in both AIC and rSAC. We compared a non-spatial model (OLS) to two spatial regression approaches (spatial lag and error models). Predictor variables were the principal components of topographic (elevation and slope), land cover, and hydrological soil group variables. We acquired these data from federal online sources (e.g. USGS). Ten watersheds were selected, each in a different state of the USA. Results revealed that water quality parameters with higher inherent SAC showed substantial increase in R² and decrease in rSAC after performing spatial regressions. However, AIC values did not show significant changes. Overall, the higher the level of inherent SAC in water quality variables, the greater improvement of model performance. This indicates a linear and direct relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. Therefore, our study suggests that the inherent level of

BOD-DO modeling and water quality analysis of a waste water outfall off Kochi, west coast of India

Digital Repository Service at National Institute of Oceanography (India)

Babu, M.T.; Das, V.K.; Vethamony, P.

Water quality scenarios around an offshore outfall off Kochi were simulated using MIKE21 water quality model, assuming a high Biochemical Oxygen Demand (BOD=50 mgl sup(-1)) effluent discharge. The discharge is introduced into the model through...

Terminology and methodology in modelling for water quality management

DEFF Research Database (Denmark)

Carstensen, J.; Vanrolleghem, P.; Rauch, W.

1997-01-01

There is a widespread need for a common terminology in modelling for water quality management. This paper points out sources of confusion in the communication between researchers due to misuse of existing terminology or use of unclear terminology. The paper attempts to clarify the context...... of the most widely used terms for characterising models and within the process of model building. It is essential to the ever growing society of researchers within water quality management, that communication is eased by establishing a common terminology. This should not be done by giving broader definitions...... of the terms, but by stressing the use of a stringent terminology. Therefore, the goal of the paper is to advocate the use of such a well defined and clear terminology. (C) 1997 IAWQ. Published by Elsevier Science Ltd....

[Review on HSPF model for simulation of hydrology and water quality processes].

Science.gov (United States)

Li, Zhao-fu; Liu, Hong-Yu; Li, Yan

2012-07-01

Hydrological Simulation Program-FORTRAN (HSPF), written in FORTRAN, is one ol the best semi-distributed hydrology and water quality models, which was first developed based on the Stanford Watershed Model. Many studies on HSPF model application were conducted. It can represent the contributions of sediment, nutrients, pesticides, conservatives and fecal coliforms from agricultural areas, continuously simulate water quantity and quality processes, as well as the effects of climate change and land use change on water quantity and quality. HSPF consists of three basic application components: PERLND (Pervious Land Segment) IMPLND (Impervious Land Segment), and RCHRES (free-flowing reach or mixed reservoirs). In general, HSPF has extensive application in the modeling of hydrology or water quality processes and the analysis of climate change and land use change. However, it has limited use in China. The main problems with HSPF include: (1) some algorithms and procedures still need to revise, (2) due to the high standard for input data, the accuracy of the model is limited by spatial and attribute data, (3) the model is only applicable for the simulation of well-mixed rivers, reservoirs and one-dimensional water bodies, it must be integrated with other models to solve more complex problems. At present, studies on HSPF model development are still undergoing, such as revision of model platform, extension of model function, method development for model calibration, and analysis of parameter sensitivity. With the accumulation of basic data and imorovement of data sharing, the HSPF model will be applied more extensively in China.

One multi-media environmental system with linkage between meteorology/ hydrology/ air quality models and water quality model

Science.gov (United States)

Tang, C.; Lynch, J. A.; Dennis, R. L.

2016-12-01

The biogeochemical processing of nitrogen and associated pollutants is driven by meteorological and hydrological processes in conjunction with pollutant loading. There are feedbacks between meteorology and hydrology that will be affected by land-use change and climate change. Changes in meteorology will affect pollutant deposition. It is important to account for those feedbacks and produce internally consistent simulations of meteorology, hydrology, and pollutant loading to drive the (watershed/water quality) biogeochemical models. In this study, the ecological response to emission reductions in streams in the Potomac watershed was evaluated. Firstly, we simulated the deposition by using the fully coupled Weather Research & Forecasting (WRF) model and the Community Multiscale Air Quality (CAMQ) model; secondly, we created the hydrological data by the offline linked Variable Infiltration Capacity (VIC) model and the WRF model. Lastly, we investigated the water quality by one comprehensive/environment model, namely the linkage of CMAQ, WRF, VIC and the Model of Acidification of Groundwater In Catchment (MAGIC) model from 2002 to 2010.The simulated results (such as NO3, SO4, and SBC) fit well to the observed values. The linkage provides a generally accurate, well-tested tool for evaluating sensitivities to varying meteorology and environmental changes on acidification and other biogeochemical processes, with capability to comprehensively explore strategic policy and management design.

Advanced Water Quality Modelling in Marine Systems: Application to the Wadden Sea, the Netherlands

Science.gov (United States)

Boon, J.; Smits, J. G.

2006-12-01

There is an increasing demand for knowledge and models that arise from water management in relation to water quality, sediment quality (ecology) and sediment accumulation (ecomorphology). Recently, models for sediment diagenesis and erosion developed or incorporated by Delft Hydraulics integrates the relevant physical, (bio)chemical and biological processes for the sediment-water exchange of substances. The aim of the diagenesis models is the prediction of both sediment quality and the return fluxes of substances such as nutrients and micropollutants to the overlying water. The resulting so-called DELWAQ-G model is a new, generic version of the water and sediment quality model of the DELFT3D framework. One set of generic water quality process formulations is used to calculate process rates in both water and sediment compartments. DELWAQ-G involves the explicit simulation of sediment layers in the water quality model with state-of-the-art process kinetics. The local conditions in a water layer or sediment layer such as the dissolved oxygen concentration determine if and how individual processes come to expression. New processes were added for sulphate, sulphide, methane and the distribution of the electron-acceptor demand over dissolved oxygen, nitrate, sulphate and carbon dioxide. DELWAQ-G also includes the dispersive and advective transport processes in the sediment and across the sediment-water interface. DELWAQ-G has been applied for the Wadden Sea. A very dynamic tidal and ecologically active estuary with a complex hydrodynamic behaviour located at the north of the Netherlands. The predicted profiles in the sediment reflect the typical interactions of diagenesis processes.

Optimal Intermittent Operation of Water Distribution Networks under Water Shortage

Directory of Open Access Journals (Sweden)

mohamad Solgi

2017-07-01

Full Text Available Under water shortage conditions, it is necessary to exercise water consumption management practices in water distribution networks (WDN. Intermittent supply of water is one such practice that makes it possible to supply consumption nodal demands with the required pressure via water cutoff to some consumers during certain hours of the day. One of the most important issues that must be observed in this management practice is the equitable and uniform water distribution among the consumers. In the present study, uniformity in water distribution and minimum supply of water to all consumers are defined as justice and equity, respectively. Also, an optimization model has been developed to find an optimal intermittent supply schedule that ensures maximum number of demand nodes are supplied with water while the constraints on the operation of water distribution networks are also observed. To show the efficiency of the proposed model, it has been used in the Two-Loop distribution network under several different scenarios of water shortage. The optimization model has been solved using the honey bee mating optimization algorithm (HBMO linked to the hydraulic simulator EPANET. The results obtained confirm the efficiency of the proposed model in achieving an optimal intermittent supply schedule. Moreover, the model is found capable of distributing the available water in an equitable and just manner among all the consumers even under severe water shoratges.

Application of ann for predicting water quality parameters in the mediterranean sea along gaza-palestine

International Nuclear Information System (INIS)

Zaqoot, H.A.; Unar, M.A.

2008-01-01

Seawater pollution problems are gaining interest world wide because of their health impacts and other environmental issues. Intense human activities in areas surrounding enclosed and semi-enclosed seas such as the Mediterranean Sea always produce in the long term a strong environmental impact in the form of coastal and marine degradation. This paper is concerned with the use of ANNs (Artificial Neural Networks) MLP ( Multilayer Perceptron) model for the prediction of pH and EC (Electrical Conductivity) in water quality parameters along Gaza city coast. MLP neural networks are trained and developed with reference to three major oceanographic parameters (water temperature, wind speed and turbidity) to predict the values of pH and EC; these parameters are considered as inputs of the neural network. The data collected comprised of four years and collected from nine locations along Gaza coastline. Results show that the model has high capability and accuracy in predicting both parameters. The network performance has been validated with different data sets and the results show satisfactory performance. Results of the developed model have been compared with multiple regression statistical models and found that MLP predictions are slightly better than the conventional methods. Prediction results prove that the proposed approach is suitable for modeling the water quality in the Mediterranean Sea along Gaza. (author)

Surface Water Quality Evaluation Based on a Game Theory-Based Cloud Model

Directory of Open Access Journals (Sweden)

Bing Yang

2018-04-01

Full Text Available Water quality evaluation is an essential measure to analyze water quality. However, excessive randomness and fuzziness affect the process of evaluation, thus reducing the accuracy of evaluation. Therefore, this study proposed a cloud model for evaluating the water quality to alleviate this problem. Analytic hierarchy process and entropy theory were used to calculate the subjective weight and objective weight, respectively, and then they were coupled as a combination weight (CW via game theory. The proposed game theory-based cloud model (GCM was then applied to the Qixinggang section of the Beijiang River. The results show that the CW ranks fecal coliform as the most important factor, followed by total nitrogen and total phosphorus, while biochemical oxygen demand and fluoride were considered least important. There were 19 months (31.67% at grade I, 39 months (65.00% at grade II, and one month at grade IV and grade V during 2010–2014. A total of 52 months (86.6% of GCM were identical to the comprehensive evaluation result (CER. The obtained water quality grades of GCM are close to the grades of the analytic hierarchy process weight (AHPW due to the weight coefficient of AHPW set to 0.7487. Generally, one or two grade gaps exist among the results of the three groups of weights, suggesting that the index weight is not particularly sensitive to the cloud model. The evaluated accuracy of water quality can be improved by modifying the quantitative boundaries. This study could provide a reference for water quality evaluation, prevention, and improvement of water quality assessment and other applications.

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

Science.gov (United States)

Bhardwaj, Jyotirmoy; Gupta, Karunesh K.; Gupta, Rajiv

2018-02-01

New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS) approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

MODELING NITRATE CONCENTRATION IN GROUND WATER USING REGRESSION AND NEURAL NETWORKS

OpenAIRE

Ramasamy, Nacha; Krishnan, Palaniappa; Bernard, John C.; Ritter, William F.

2003-01-01

Nitrate concentration in ground water is a major problem in specific agricultural areas. Using regression and neural networks, this study models nitrate concentration in ground water as a function of iron concentration in ground water, season and distance of the well from a poultry house. Results from both techniques are comparable and show that the distance of the well from a poultry house has a significant effect on nitrate concentration in groundwater.

Water quality diagnosis system

International Nuclear Information System (INIS)

Nagase, Makoto; Asakura, Yamato; Sakagami, Masaharu

1989-01-01

By using a model representing a relationship between the water quality parameter and the dose rate in primary coolant circuits of a water cooled reactor, forecasting for the feature dose rate and abnormality diagnosis for the water quality are conducted. The analysis model for forecasting the reactor water activity or the dose rate receives, as the input, estimated curves for the forecast Fe, Ni, Co concentration in feedwater or reactor water pH, etc. from the water quality data in the post and forecasts the future radioactivity or dose rate in the reactor water. By comparing the result of the forecast and the setting value such as an aimed value, it can be seen whether the water quality at present or estimated to be changed is satisfactory or not. If the quality is not satisfactory, it is possible to take an early countermeasure. Accordingly, the reactor water activity and the dose rate can be kept low. Further, the basic system constitution, diagnosis algorithm, indication, etc. are identical between BWR and PWR reactors, except for only the difference in the mass balance. (K.M.)

Studies on kinetics of water quality factors to establish water transparency model in Neijiang River, China.

Science.gov (United States)

Li, Ronghui; Pan, Wei; Guo, Jinchuan; Pang, Yong; Wu, Jianqiang; Li, Yiping; Pan, Baozhu; Ji, Yong; Ding, Ling

2014-05-01

The basis for submerged plant restoration in surface water is to research the complicated dynamic mechanism of water transparency. In this paper, through the impact factor analysis of water transparency, the suspended sediment, dissolved organic matter, algae were determined as three main impactfactors for water transparency of Neijiang River in Eastern China. And the multiple regression equation of water transparency and sediment concentration, permanganate index, chlorophyll-a concentration was developed. Considering the complicated transport and transformation of suspended sediment, dissolved organic matter and algae, numerical model of them were developed respectively for simulating the dynamic process. Water transparency numerical model was finally developed by coupling the sediment, water quality, and algae model. These results showed that suspended sediment was a key factor influencing water transparency of Neijiang River, the influence of water quality indicated by chemical oxygen demand and algal concentration indicated by chlorophyll a were indeterminate when their concentrations were lower, the influence was more obvious when high concentrations are available, such three factors showed direct influence on water transparency.

A One-Dimensional Hydrodynamic and Water Quality Model for a Water Transfer Project with Multihydraulic Structures

OpenAIRE

Yujun Yi; Caihong Tang; Zhifeng Yang; Shanghong Zhang; Cheng Zhang

2017-01-01

The long Middle Route of the South to North Water Transfer Project is composed of complex hydraulic structures (aqueduct, tunnel, control gate, diversion, culvert, and diverted siphon), which generate complex flow patterns. It is vital to simulate the flow patterns through hydraulic structures, but it is a challenging work to protect water quality and maintain continuous water transfer. A one-dimensional hydrodynamic and water quality model was built to understand the flow and pollutant movem...

Quality assurance and quality control for Hydro-Quebec's ambient air monitoring networks

International Nuclear Information System (INIS)

Lambert, M.; Varfalvy, L.

1993-01-01

Hydro Quebec has three ambient air monitoring networks to determine the contribution of some of its thermal plants to ambient air quality. They are located in Becancour (gas turbines), Iles-de-la-Madeleine (diesel), and Tracy (conventional oil-fired). To ensure good quality results and consistency between networks, a quality assurance/quality control program was set up. A description is presented of the ambient air quality monitoring network and the quality assurance/quality control program. A guide has been created for use by the network operators, discussing objectives of the individual network, a complete description of each network, field operation for each model of instrument in use, treatment of data for each data logger in use, global considerations regarding quality assurance and control, and reports. A brief overview is presented of the guide's purpose and contents, focusing on the field operation section and the sulfur dioxide and nitrogen oxide monitors. 6 figs., 1 tab

Comparison of 2006-2007 Water Years and Historical Water-Quality Data, Upper Gunnison River Basin, Colorado

Science.gov (United States)

Solberg, P.A.; Moore, Bryan; Smits, Dennis

2009-01-01

Population growth and changes in land use have the potential to affect water quality and quantity in the upper Gunnison River basin. In 1995, the U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, City of Gunnison, Colorado River Water Conservation District, Crested Butte South Metropolitan District, Gunnison County, Hinsdale County, Mount Crested Butte Water and Sanitation District, National Park Service, Town of Crested Butte, Upper Gunnison River Water Conservancy District, and Western State College established a water-quality monitoring program in the upper Gunnison River basin to characterize current water-quality conditions and to assess the effects of increased urban development and other land-use changes on water quality. The monitoring network has evolved into two groups of stations - stations that are considered long term and stations that are considered rotational. The long-term stations are monitored to assist in defining temporal changes in water quality (how conditions may change over time). The rotational stations are monitored to assist in the spatial definition of water-quality conditions (how conditions differ throughout the basin) and to address local and short-term concerns. Some stations in the rotational group were changed beginning in water year 2007. Annual summaries of the water-quality data from the monitoring network provide a point of reference for discussions regarding water-quality monitoring in the upper Gunnison River basin. This summary includes data collected during water years 2006 and 2007. The introduction provides a map of the sampling sites, definitions of terms, and a one-page summary of selected water-quality conditions at the network stations. The remainder of the summary is organized around the data collected at individual stations. Data collected during water years 2006 and 2007 are compared to historical data, State water-quality standards, and Federal water-quality guidelines. Data were

Trends in surface-water quality at selected National Stream Quality Accounting Network (NASQAN) stations, in Michigan

Science.gov (United States)

Syed, Atiq U.; Fogarty, Lisa R.

2005-01-01

To demonstrate the value of long-term, water-quality monitoring, the Michigan Department of Environmental Quality (MDEQ), in cooperation with the U.S. Geological Survey (USGS), initiated a study to evaluate potential trends in water-quality constituents for selected National Stream Quality Accounting Network (NASQAN) stations in Michigan. The goal of this study is to assist the MDEQ in evaluating the effectiveness of water-pollution control efforts and the identification of water-quality concerns. The study included a total of nine NASQAN stations in Michigan. Approximately 28 constituents were analyzed for trend tests. Station selection was based on data availability, land-use characteristics, and station priority for the MDEQ Water Chemistry Monitoring Project. Trend analyses were completed using the uncensored Seasonal Kendall Test in the computer program Estimate Trend (ESTREND), a software program for the detection of trends in water-quality data. The parameters chosen for the trend test had (1) at least a 5-year period of record (2) about 5 percent of the observations censored at a single reporting limit, and (3) 40 percent of the values within the beginning one-fifth and ending one-fifth of the selected period. In this study, a negative trend indicates a decrease in concentration of a particular constituent, which generally means an improvement in water quality; whereas a positive trend means an increase in concentration and possible degradation of water quality. The results of the study show an overall improvement in water quality at the Clinton River at Mount Clemens, Manistee River at Manistee, and Pigeon River near Caseville. The detected trend for these stations show decreases in concentrations of various constituents such as nitrogen compounds, conductance, sulfate, fecal coliform bacteria, and fecal streptococci bacteria. The negative trend may indicate an overall improvement in agricultural practices, municipal and industrial wastewater

Entropy Applications to Water Monitoring Network Design: A Review

Directory of Open Access Journals (Sweden)

Jongho Keum

2017-11-01

Full Text Available Having reliable water monitoring networks is an essential component of water resources and environmental management. A standardized process for the design of water monitoring networks does not exist with the exception of the World Meteorological Organization (WMO general guidelines about the minimum network density. While one of the major challenges in the design of optimal hydrometric networks has been establishing design objectives, information theory has been successfully adopted to network design problems by providing measures of the information content that can be deliverable from a station or a network. This review firstly summarizes the common entropy terms that have been used in water monitoring network designs. Then, this paper deals with the recent applications of the entropy concept for water monitoring network designs, which are categorized into (1 precipitation; (2 streamflow and water level; (3 water quality; and (4 soil moisture and groundwater networks. The integrated design method for multivariate monitoring networks is also covered. Despite several issues, entropy theory has been well suited to water monitoring network design. However, further work is still required to provide design standards and guidelines for operational use.

Comparison of 2008-2009 water years and historical water-quality data, upper Gunnison River Basin, Colorado

Science.gov (United States)

Solberg, Patricia A.; Moore, Bryan; Blacklock, Ty D.

2012-01-01

Population growth and changes in land use have the potential to affect water quality and quantity in the upper Gunnison River Basin. In 1995, the U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management, City of Gunnison, Colorado River Water Conservation District, Crested Butte South Metropolitan District, Gunnison County, Hinsdale County, Mount Crested Butte Water and Sanitation District, National Park Service, Town of Crested Butte, U.S. Forest Service, Upper Gunnison River Water Conservancy District, and Western State College, established a water-quality monitoring program in the upper Gunnison River Basin to characterize current water-quality conditions and to assess the effects of increased urban development and other land-use changes on water quality. The monitoring network has evolved into two groups of sites: (1) sites that are considered long term and (2) sites that are considered rotational. Data from the long-term sites assist in defining temporal changes in water quality (how conditions may change over time). The rotational sites assist in the spatial definition of water-quality conditions (how conditions differ throughout the basin) and address local and short-term concerns. Biannual summaries of the water-quality data from the monitoring network provide a point of reference for stakeholder discussions regarding the location and purpose of water-quality monitoring sites in the upper Gunnison River Basin. This report compares and summarizes the data collected during water years 2008 and 2009 to the historical data available at these sites. The introduction provides a map of the sampling sites, definitions of terms, and a one-page summary of selected water-quality conditions at the network sites. The remainder of the report is organized around the data collected at individual sites. Data collected during water years 2008 and 2009 are compared to historical data, State water-quality standards, and Federal water-quality guidelines

User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data

Science.gov (United States)

Petkewich, Matthew D.; Daamen, Ruby C.; Roehl, Edwin A.; Conrads, Paul

2016-09-29

The generation of Everglades Depth Estimation Network (EDEN) daily water-level and water-depth maps is dependent on high quality real-time data from over 240 water-level stations. To increase the accuracy of the daily water-surface maps, the Automated Data Assurance and Management (ADAM) tool was created by the U.S. Geological Survey as part of Greater Everglades Priority Ecosystems Science. The ADAM tool is used to provide accurate quality-assurance review of the real-time data from the EDEN network and allows estimation or replacement of missing or erroneous data. This user’s manual describes how to install and operate the ADAM software. File structure and operation of the ADAM software is explained using examples.

New Markov-Shannon Entropy models to assess connectivity quality in complex networks: from molecular to cellular pathway, Parasite-Host, Neural, Industry, and Legal-Social networks.

Science.gov (United States)

Riera-Fernández, Pablo; Munteanu, Cristian R; Escobar, Manuel; Prado-Prado, Francisco; Martín-Romalde, Raquel; Pereira, David; Villalba, Karen; Duardo-Sánchez, Aliuska; González-Díaz, Humberto

2012-01-21

Graph and Complex Network theory is expanding its application to different levels of matter organization such as molecular, biological, technological, and social networks. A network is a set of items, usually called nodes, with connections between them, which are called links or edges. There are many different experimental and/or theoretical methods to assign node-node links depending on the type of network we want to construct. Unfortunately, the use of a method for experimental reevaluation of the entire network is very expensive in terms of time and resources; thus the development of cheaper theoretical methods is of major importance. In addition, different methods to link nodes in the same type of network are not totally accurate in such a way that they do not always coincide. In this sense, the development of computational methods useful to evaluate connectivity quality in complex networks (a posteriori of network assemble) is a goal of major interest. In this work, we report for the first time a new method to calculate numerical quality scores S(L(ij)) for network links L(ij) (connectivity) based on the Markov-Shannon Entropy indices of order k-th (θ(k)) for network nodes. The algorithm may be summarized as follows: (i) first, the θ(k)(j) values are calculated for all j-th nodes in a complex network already constructed; (ii) A Linear Discriminant Analysis (LDA) is used to seek a linear equation that discriminates connected or linked (L(ij)=1) pairs of nodes experimentally confirmed from non-linked ones (L(ij)=0); (iii) the new model is validated with external series of pairs of nodes; (iv) the equation obtained is used to re-evaluate the connectivity quality of the network, connecting/disconnecting nodes based on the quality scores calculated with the new connectivity function. This method was used to study different types of large networks. The linear models obtained produced the following results in terms of overall accuracy for network reconstruction

Hydraulic Network Modelling of Small Community Water Distribution ...

African Journals Online (AJOL)

Prof Anyata

community (Sakwa) water distribution network in North Eastern geopolitical region of Nigeria using. WaterCAD ..... Table 1: Criteria Relating Population to Water Demand (NWSP, 2000) ..... timely manner ... Department, Middle East Technical.

Using additional external inputs to forecast water quality with an artificial neural network for contamination event detection in source water

Science.gov (United States)

Schmidt, F.; Liu, S.

2016-12-01

Source water quality plays an important role for the safety of drinking water and early detection of its contamination is vital to taking appropriate countermeasures. However, compared to drinking water, it is more difficult to detect contamination events because its environment is less controlled and numerous natural causes contribute to a high variability of the background values. In this project, Artificial Neural Networks (ANNs) and a Contamination Event Detection Process (CED Process) were used to identify events in river water. The ANN models the response of basic water quality sensors obtained in laboratory experiments in an off-line learning stage and continuously forecasts future values of the time line in an on-line forecasting step. During this second stage, the CED Process compares the forecast to the measured value and classifies it as regular background or event value, which modifies the ANN's continuous learning and influences its forecasts. In addition to this basic setup, external information is fed to the CED Process: A so-called Operator Input (OI) is provided to inform about unusual water quality levels that are unrelated to the presence of contamination, for example due to cooling water discharge from a nearby power plant. This study's primary goal is to evaluate how well the OI fits into the design of the combined forecasting ANN and CED Process and to understand its effects on the online forecasting stage. To test this, data from laboratory experiments conducted previously at the School of Environment, Tsinghua University, have been used to perform simulations highlighting features and drawbacks of this method. Applying the OI has been shown to have a positive influence on the ANN's ability to handle a sudden change in background values, which is unrelated to contamination. However, it might also mask the presence of an event, an issue that underlines the necessity to have several instances of the algorithm run in parallel. Other difficulties

Maximum solid concentrations of coal water slurries predicted by neural network models

Energy Technology Data Exchange (ETDEWEB)

Cheng, Jun; Li, Yanchang; Zhou, Junhu; Liu, Jianzhong; Cen, Kefa

2010-12-15

The nonlinear back-propagation (BP) neural network models were developed to predict the maximum solid concentration of coal water slurry (CWS) which is a substitute for oil fuel, based on physicochemical properties of 37 typical Chinese coals. The Levenberg-Marquardt algorithm was used to train five BP neural network models with different input factors. The data pretreatment method, learning rate and hidden neuron number were optimized by training models. It is found that the Hardgrove grindability index (HGI), moisture and coalification degree of parent coal are 3 indispensable factors for the prediction of CWS maximum solid concentration. Each BP neural network model gives a more accurate prediction result than the traditional polynomial regression equation. The BP neural network model with 3 input factors of HGI, moisture and oxygen/carbon ratio gives the smallest mean absolute error of 0.40%, which is much lower than that of 1.15% given by the traditional polynomial regression equation. (author)

SIMULATION OF NEGATIVE PRESSURE WAVE PROPAGATION IN WATER PIPE NETWORK

Directory of Open Access Journals (Sweden)

Tang Van Lam

2017-11-01

Full Text Available Subject: factors such as pipe wall roughness, mechanical properties of pipe materials, physical properties of water affect the pressure surge in the water supply pipes. These factors make it difficult to analyze the transient problem of pressure evolution using simple programming language, especially in the studies that consider only the magnitude of the positive pressure surge with the negative pressure phase being neglected. Research objectives: determine the magnitude of the negative pressure in the pipes on the experimental model. The propagation distance of the negative pressure wave will be simulated by the valve closure scenarios with the help of the HAMMER software and it is compared with an experimental model to verify the quality the results. Materials and methods: academic version of the Bentley HAMMER software is used to simulate the pressure surge wave propagation due to closure of the valve in water supply pipe network. The method of characteristics is used to solve the governing equations of transient process of pressure change in the pipeline. This method is implemented in the HAMMER software to calculate the pressure surge value in the pipes. Results: the method has been applied for water pipe networks of experimental model, the results show the affected area of negative pressure wave from valve closure and thereby we assess the largest negative pressure that may appear in water supply pipes. Conclusions: the experiment simulates the water pipe network with a consumption node for various valve closure scenarios to determine possibility of appearance of maximum negative pressure value in the pipes. Determination of these values in real-life network is relatively costly and time-consuming but nevertheless necessary for identification of the risk of pipe failure, and therefore, this paper proposes using the simulation model by the HAMMER software. Initial calibration of the model combined with the software simulation results and

Water quality effects of intermittent water supply in Arraiján, Panama.

Science.gov (United States)

Erickson, John J; Smith, Charlotte D; Goodridge, Amador; Nelson, Kara L

2017-05-01

Intermittent drinking water supply is common in low- and middle-income countries throughout the world and can cause water quality to degrade in the distribution system. In this study, we characterized water quality in one study zone with continuous supply and three zones with intermittent supply in the drinking water distribution network in Arraiján, Panama. Low or zero pressures occurred in all zones, and negative pressures occurred in the continuous zone and two of the intermittent zones. Despite hydraulic conditions that created risks for backflow and contaminant intrusion, only four of 423 (0.9%) grab samples collected at random times were positive for total coliform bacteria and only one was positive for E. coli. Only nine of 496 (1.8%) samples had turbidity >1.0 NTU and all samples had ≥0.2 mg/L free chlorine residual. In contrast, water quality was often degraded during the first-flush period (when supply first returned after an outage). Still, routine and first-flush water quality under intermittent supply was much better in Arraiján than that reported in a previous study conducted in India. Better water quality in Arraiján could be due to better water quality leaving the treatment plant, shorter supply outages, higher supply pressures, a more consistent and higher chlorine residual, and fewer contaminant sources near pipes. The results illustrate that intermittent supply and its effects on water quality can vary greatly between and within distribution networks. The study also demonstrated that monitoring techniques designed specifically for intermittent supply, such as continuous pressure monitoring and sampling the first flush, can detect water quality threats and degradation that would not likely be detected with conventional monitoring. Copyright © 2017 Elsevier Ltd. All rights reserved.

Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT.

Science.gov (United States)

Luo, Yuzhou; Zhang, Minghua

2009-12-01

The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed.

Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model

Science.gov (United States)

Arumugam, S.; Libera, D.

2017-12-01

Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.

Assessment of domestic water quality: case study, Beirut, Lebanon.

Science.gov (United States)

Korfali, Samira Ibrahim; Jurdi, Mey

2007-12-01

In urban cities, the environmental services are the responsibility of the public sector, where piped water supply is the norm for urban household. Likewise, in Beirut City (capital of Lebanon) official water authorities are the main supplier of domestic water through a network of piping system that leaks in many areas. Beirut City and its suburbs are overpopulated since it is the residence of 1/3 of the Lebanese citizens. Thus, Beirut suffers deficiency in meeting its water demand. Water rationing, as a remedial action, is firmly established since four decades by the Lebanese Water Authorities. Consumers resorted then to private wells to supplement their domestic water needs. Consequently, household water quality is influenced by external factors relating to well water characteristics and internal factors depending on the types of the pipes of the distribution network and cross connections to sewer pipes. These factors could result in chemical and microbial contamination of drinking water. The objective of this study is to investigate domestic water quality variation in Beirut City emerging form the aforementioned factors. The presented work encircles a typical case study of Beirut City (Ras Beirut). Results showed deterioration pattern in domestic water quality. The predicted metal species and scales within the water pipes of distribution network depended on water pH, hardness, sulfate, chloride, and iron. The corrosion of iron pipes mainly depended on Mg hardness.

A study of electrical power network of renewable energies and water desalination research center using power quality phenomena and indices

International Nuclear Information System (INIS)

Segayer, Ali Mehemmed

2008-08-01

Renewable energies and water distillation research center (REWDRC) is a very strategic research facility and contains many important and critical industrial and electrical loads that must to be operated as a group to fulfill the requirements and the needs of the center in the operation of the main research facility of the center which a 10 MW reactor. Faults on the electrical or the industrial system can occur on many ways such as a malfunction in the questioned system, power quality related problem, or a failure of any of the loads (such as central ventilation or water circulation system or one of the substations) have a great diverse effect on the operation of the main research facility (reactor). In this research common problems due to power quality phenomena were studied, assessed through a assigning some power quality indices to the electrical network of the center so that the operational condition of the REWDRC electrical and industrial network could be evaluated. power quality indices (PQI) were assigned based on results of real time measurements at the points of common coupling of the network (PCC) and the initial power quality survey report. indices analysis was done using three methods which were the normalization method, method of comparing to the limit value and analysis of measurement data time function profile. As a result of this research a recommendation for safe operation against power quality disturbances was pointed out through a continuous monitoring of assigned power quality indices. (Author)

Water Quality Analysis Simulation

Data.gov (United States)

U.S. Environmental Protection Agency — The Water Quality analysis simulation Program, an enhancement of the original WASP. This model helps users interpret and predict water quality responses to natural...

The role of headwater streams in downstream water quality

Science.gov (United States)

Alexander, R.B.; Boyer, E.W.; Smith, R.A.; Schwarz, G.E.; Moore, R.B.

2007-01-01

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and

Puget Sound Dissolved Oxygen Modeling Study: Development of an Intermediate Scale Water Quality Model

Energy Technology Data Exchange (ETDEWEB)

Khangaonkar, Tarang; Sackmann, Brandon S.; Long, Wen; Mohamedali, Teizeen; Roberts, Mindy

2012-10-01

The Salish Sea, including Puget Sound, is a large estuarine system bounded by over seven thousand miles of complex shorelines, consists of several subbasins and many large inlets with distinct properties of their own. Pacific Ocean water enters Puget Sound through the Strait of Juan de Fuca at depth over the Admiralty Inlet sill. Ocean water mixed with freshwater discharges from runoff, rivers, and wastewater outfalls exits Puget Sound through the brackish surface outflow layer. Nutrient pollution is considered one of the largest threats to Puget Sound. There is considerable interest in understanding the effect of nutrient loads on the water quality and ecological health of Puget Sound in particular and the Salish Sea as a whole. The Washington State Department of Ecology (Ecology) contracted with Pacific Northwest National Laboratory (PNNL) to develop a coupled hydrodynamic and water quality model. The water quality model simulates algae growth, dissolved oxygen, (DO) and nutrient dynamics in Puget Sound to inform potential Puget Sound-wide nutrient management strategies. Specifically, the project is expected to help determine 1) if current and potential future nitrogen loadings from point and non-point sources are significantly impairing water quality at a large scale and 2) what level of nutrient reductions are necessary to reduce or control human impacts to DO levels in the sensitive areas. The project did not include any additional data collection but instead relied on currently available information. This report describes model development effort conducted during the period 2009 to 2012 under a U.S. Environmental Protection Agency (EPA) cooperative agreement with PNNL, Ecology, and the University of Washington awarded under the National Estuary Program

The aquatic real-time monitoring network; in-situ optical sensors for monitoring the nation's water quality

Science.gov (United States)

Pellerin, Brian A.; Bergamaschi, Brian A.; Murdoch, Peter S.; Downing, Bryan D.; Saraceno, John Franco; Aiken, George R.; Striegl, Robert G.

2011-01-01

Floods, hurricanes, and longer-term changes in climate and land use can have profound effects on water quality due to shifts in hydrologic flow paths, water residence time, precipitation patterns, connectivity between rivers and uplands, and many other factors. In order to understand and respond to changes in hydrology and water quality, resource managers and policy makers have a need for accurate and early indicators, as well as the ability to assess possible mechanisms and likely outcomes. In-situ optical sensors-those making continuous measurements of constituents by absorbance or fluorescence properties in the environment at timescales of minutes to years-have a long history in oceanography for developing highly resolved concentrations and fluxes, but are not commonly used in freshwater systems. The United States Geological Survey (USGS) has developed the Aquatic Real-Time Monitoring Network, with high-resolution optical data collection for organic carbon, nutrients, and sediment in large coastal rivers, along with continuous measurements of discharge, water temperature, and dissolved inorganic carbon. The collecting of continuous water-quality data in the Nation?s waterways has revealed temporal trends and spatial patterns in constituents that traditional sampling approaches fail to capture, and will serve a critical role in monitoring, assessment and decision-making in a rapidly changing landscape.

Water quality modelling in the San Antonio River Basin driven by radar rainfall data

Directory of Open Access Journals (Sweden)

Almoutaz Elhassan

2016-05-01

Full Text Available Continuous monitoring of stream water quality is needed as it has significant impacts on human and ecological health and well-being. Estimating water quality between sampling dates requires model simulation based on the available geospatial and water quality data for a given watershed. Models such as the Soil and Water Assessment Tool (SWAT can be used to estimate the missing water quality data. In this study, SWAT was used to estimate water quality at a monitoring station near the outlet of the San Antonio River. Precipitation data from both rain gauges and weather radar were used to force the SWAT simulations. Virtual rain gauges which were based on weather radar data were created in the approximate centres of the 163 sub-watersheds of the San Antonio River Basin for SWAT simulations. This method was first tested in a smaller watershed in the middle of the Guadalupe River Basin resulting in increased model efficiency in simulating surface run-off. The method was then applied to the San Antonio River watershed and yielded good simulations for surface run-off (R2 = 0.7, nitrate (R2 = 0.6 and phosphate (R2 = 0.5 at the watershed outlet (Goliad, TX – USGS (United States Geological Survey gauge as compared to observed data. The study showed that the proper use of weather radar precipitation in SWAT model simulations improves the estimation of missing water quality data.

Water Quality Assessment of Ayeyarwady River in Myanmar

Science.gov (United States)

Thatoe Nwe Win, Thanda; Bogaard, Thom; van de Giesen, Nick

2015-04-01

Myanmar's socio-economic activities, urbanisation, industrial operations and agricultural production have increased rapidly in recent years. With the increase of socio-economic development and climate change impacts, there is an increasing threat on quantity and quality of water resources. In Myanmar, some of the drinking water coverage still comes from unimproved sources including rivers. The Ayeyarwady River is the main river in Myanmar draining most of the country's area. The use of chemical fertilizer in the agriculture, the mining activities in the catchment area, wastewater effluents from the industries and communities and other development activities generate pollutants of different nature. Therefore water quality monitoring is of utmost importance. In Myanmar, there are many government organizations linked to water quality management. Each water organization monitors water quality for their own purposes. The monitoring is haphazard, short term and based on individual interest and the available equipment. The monitoring is not properly coordinated and a quality assurance programme is not incorporated in most of the work. As a result, comprehensive data on the water quality of rivers in Myanmar is not available. To provide basic information, action is needed at all management levels. The need for comprehensive and accurate assessments of trends in water quality has been recognized. For such an assessment, reliable monitoring data are essential. The objective of our work is to set-up a multi-objective surface water quality monitoring programme. The need for a scientifically designed network to monitor the Ayeyarwady river water quality is obvious as only limited and scattered data on water quality is available. However, the set-up should also take into account the current socio-economic situation and should be flexible to adjust after first years of monitoring. Additionally, a state-of-the-art baseline river water quality sampling program is required which

Towards a cyber-physical era: soft computing framework based multi-sensor array for water quality monitoring

Directory of Open Access Journals (Sweden)

J. Bhardwaj

2018-02-01

Full Text Available New concepts and techniques are replacing traditional methods of water quality parameter measurement systems. This paper introduces a cyber-physical system (CPS approach for water quality assessment in a distribution network. Cyber-physical systems with embedded sensors, processors and actuators can be designed to sense and interact with the water environment. The proposed CPS is comprised of sensing framework integrated with five different water quality parameter sensor nodes and soft computing framework for computational modelling. Soft computing framework utilizes the applications of Python for user interface and fuzzy sciences for decision making. Introduction of multiple sensors in a water distribution network generates a huge number of data matrices, which are sometimes highly complex, difficult to understand and convoluted for effective decision making. Therefore, the proposed system framework also intends to simplify the complexity of obtained sensor data matrices and to support decision making for water engineers through a soft computing framework. The target of this proposed research is to provide a simple and efficient method to identify and detect presence of contamination in a water distribution network using applications of CPS.

Comparison of computer models for estimating hydrology and water quality in an agricultural watershed

Science.gov (United States)

Various computer models, ranging from simple to complex, have been developed to simulate hydrology and water quality from field to watershed scales. However, many users are uncertain about which model to choose when estimating water quantity and quality conditions in a watershed. This study compared...

River water quality modelling under drought situations – the Turia River case

Directory of Open Access Journals (Sweden)

J. Paredes-Arquiola

2016-10-01

Full Text Available Drought and water shortage effects are normally exacerbated due to collateral impacts on water quality, since low streamflow affects water quality in rivers and water uses depend on it. One of the most common problems during drought conditions is maintaining a good water quality while securing the water supply to demands. This research analyses the case of the Turia River Water Resource System located in Eastern Spain. Its main water demand comes as urban demand from Valencia City, which intake is located in the final stretch of the river, where streamflow may become very low during droughts. As a result, during drought conditions concentrations of pathogens and other contaminants increase, compromising the water supply to Valencia City. In order to define possible solutions for the above-mentioned problem, we have developed an integrated model for simulating water management and water quality in the Turia River Basin to propose solutions for water quality problems under water scarcity. For this purpose, the Decision Support System Shell AQUATOOL has been used. The results demonstrate the importance of applying environmental flows as a measure of reducing pollutant's concentration depending on the evolution of a drought event and the state of the water resources system.

Effectiveness of the stormwater quality devices to improve water quality at Putrajaya

International Nuclear Information System (INIS)

Sidek, L M; Basri, H; Puad, A H Mohd; Noh, M N Md; Ainan, A

2013-01-01

Development of Putrajaya has changed the character of the natural landform by covering the land with impervious surfaces. Houses, office buildings, commercial place and shopping centres have provided places to live and work. The route between buildings is facilitated and encouraged by a complex network of roads and car parks. However, this change from natural landforms and vegetative cover to impervious surfaces has major effect on stormwater which are water quality (non-point source pollution). This paper describes the effectiveness of the stormwater quality devices to improve water quality at selected Putrajaya for demonstration in order to evaluate low cost storm inlet type devices in the Putrajaya Catchment. Five stormwater quality devices were installed and monitored during the study. The devices include Ultra Drain Guard Recycle model, Ultra Curb Guard Plus, Ultra Grate Guard, Absorbent Tarp and Ultra Passive Skimmer. This paper will provide information on the benefits and costs of these devices, including operations and maintenance requirements. Applicability of these devices in gas stations, small convenience stores, residential and small parking lots in the catchment are possible due to their low cost.

Water Quality Analysis Simulation

Science.gov (United States)

The Water Quality analysis simulation Program, an enhancement of the original WASP. This model helps users interpret and predict water quality responses to natural phenomena and man-made pollution for variious pollution management decisions.

Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT

International Nuclear Information System (INIS)

Luo Yuzhou; Zhang Minghua

2009-01-01

The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed. - Selected structural BMPs are recommended for reducing loads of OP pesticides.

Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT

Energy Technology Data Exchange (ETDEWEB)

Luo Yuzhou [University of California, Davis, CA 95616 (United States); Wenzhou Medical College, Wenzhou 325035 (China); Zhang Minghua, E-mail: mhzhang@ucdavis.ed [University of California, Davis, CA 95616 (United States); Wenzhou Medical College, Wenzhou 325035 (China)

2009-12-15

The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed. - Selected structural BMPs are recommended for reducing loads of OP pesticides.

Modeling, Optimization & Control of Hydraulic Networks

DEFF Research Database (Denmark)

Tahavori, Maryamsadat

2014-01-01

. The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...

Modeling the Liquid Water Transport in the Gas Diffusion Layer for Polymer Electrolyte Membrane Fuel Cells Using a Water Path Network

Directory of Open Access Journals (Sweden)

Dietmar Gerteisen

2013-09-01

Full Text Available In order to model the liquid water transport in the porous materials used in polymer electrolyte membrane (PEM fuel cells, the pore network models are often applied. The presented model is a novel approach to further develop these models towards a percolation model that is based on the fiber structure rather than the pore structure. The developed algorithm determines the stable liquid water paths in the gas diffusion layer (GDL structure and the transitions from the paths to the subsequent paths. The obtained water path network represents the basis for the calculation of the percolation process with low calculation efforts. A good agreement with experimental capillary pressure-saturation curves and synchrotron liquid water visualization data from other literature sources is found. The oxygen diffusivity for the GDL with liquid water saturation at breakthrough reveals that the porosity is not a crucial factor for the limiting current density. An algorithm for condensation is included into the model, which shows that condensing water is redirecting the water path in the GDL, leading to an improved oxygen diffusion by a decreased breakthrough pressure and changed saturation distribution at breakthrough.

Work Plan for a Water Quality Model of Florida Bay

National Research Council Canada - National Science Library

Dortch, Mark

1997-01-01

.... The model is required to address issues pertaining to nutrient inputs and associated impacts on water quality and sea grass, particularly as related to changes in freshwater inflows from south...

High Resolution Sensing and Control of Urban Water Networks

Science.gov (United States)

Bartos, M. D.; Wong, B. P.; Kerkez, B.

2016-12-01

We present a framework to enable high-resolution sensing, modeling, and control of urban watersheds using (i) a distributed sensor network based on low-cost cellular-enabled motes, (ii) hydraulic models powered by a cloud computing infrastructure, and (iii) automated actuation valves that allow infrastructure to be controlled in real time. This platform initiates two major advances. First, we achieve a high density of measurements in urban environments, with an anticipated 40+ sensors over each urban area of interest. In addition to new measurements, we also illustrate the design and evaluation of a "smart" control system for real-world hydraulic networks. This control system improves water quality and mitigates flooding by using real-time hydraulic models to adaptively control releases from retention basins. We evaluate the potential of this platform through two ongoing deployments: (i) a flood monitoring network in the Dallas-Fort Worth metropolitan area that detects and anticipates floods at the level of individual roadways, and (ii) a real-time hydraulic control system in the city of Ann Arbor, MI—soon to be one of the most densely instrumented urban watersheds in the United States. Through these applications, we demonstrate that distributed sensing and control of water infrastructure can improve flash flood predictions, emergency response, and stormwater contaminant mitigation.

Using QMRAcatch - a stochastic hydrological water quality and infection risk model - to identify sustainable management options for long term drinking water resource planning

Science.gov (United States)

Derx, J.; Demeter, K.; Schijven, J. F.; Sommer, R.; Zoufal-Hruza, C. M.; Kromp, H.; Farnleitner, A.; Blaschke, A. P.

2017-12-01

River water resources in urban environments play a critical role in sustaining human health and ecosystem services, as they are used for drinking water production, bathing and irrigation. In this study the hydrological water quality model QMRAcatch was used combined with measured concentrations of human enterovirus and human-associated genetic fecal markers. The study area is located at a river/floodplain area along the Danube which is used for drinking water production by river bank filtration and further disinfection. QMRAcatch was previously developed to support long term planning of water resources in accordance with a public infection protection target (Schijven et al., 2015). Derx et al. 2016 previously used QMRAcatch for evaluating the microbiological quality and required virus-reduction targets at the study area for the current and robust future "crisis" scenarios, i.e. for the complete failure of wastewater treatment plants and infection outbreaks. In contrast, the aim of this study was to elaborate future scenarios based on projected climate and population changes in collaboration with urban water managers. The identified scenarios until 2050 include increased wastewater discharge rates due to the projected urban population growth and more frequent storm and overflow events of urban sewer systems following forecasted changes in climate and hydrology. Based on the simulation results for the developed scenarios sustainable requirements of the drinking water treatment system for virus reductions were re-evaluated to achieve the health risk target. The model outcomes are used to guide practical and scientifically sound management options for long term water resource planning. This paper was supported by FWF (Vienna Doctoral Program on Water Resource Systems W1219-N22) and the GWRS project (Vienna Water) as part of the "(New) Danube-Lower Lobau Network Project" funded by the Government of Austria and Vienna, and the European Agricultural Fund for Rural

Integrated Modelling on Flow and Water Quality Under the Impacts of Climate Change and Agricultural Activities

Science.gov (United States)

SHI, J.

2014-12-01

Climate change is expected to have a significant impact on flooding in the UK, inducing more intense and prolonged storms. Frequent flooding due to climate change already exacerbates catchment water quality. Land use is another contributing factor to poor water quality. For example, the move to intensive farming could cause an increase in faecal coliforms entering the water courses. In an effort to understand better the effects on water quality from land use and climate change, the hydrological and estuarine processes are being modelled using SWAT (Soil and Water Assessment Tool), linked to a 2-D hydrodynamic model DIVAST(Depth Integrated Velocity and Solute Transport). The coupled model is able to quantify how much of each pollutant from the catchment reaches the harbour and the impact on water quality within the harbour. The work is focused on the transportation and decay of faecal coliforms from agricultural runoff into the rivers Frome and Piddle in the UK. The impact from the agricultural land use and activities on the catchment river hydrology and water quality are evaluated. The coupled model calibration and validation showed the good model performance on flow and faecal coliform in the watershed and estuary.

Digital Hydrologic Networks Supporting Applications Related to Spatially Referenced Regression Modeling

Science.gov (United States)

Brakebill, J.W.; Wolock, D.M.; Terziotti, S.E.

2011-01-01

Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based/statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

Flexible quality of service model for wireless body area sensor networks.

Science.gov (United States)

Liao, Yangzhe; Leeson, Mark S; Higgins, Matthew D

2016-03-01

Wireless body area sensor networks (WBASNs) are becoming an increasingly significant breakthrough technology for smart healthcare systems, enabling improved clinical decision-making in daily medical care. Recently, radio frequency ultra-wideband technology has developed substantially for physiological signal monitoring due to its advantages such as low-power consumption, high transmission data rate, and miniature antenna size. Applications of future ubiquitous healthcare systems offer the prospect of collecting human vital signs, early detection of abnormal medical conditions, real-time healthcare data transmission and remote telemedicine support. However, due to the technical constraints of sensor batteries, the supply of power is a major bottleneck for healthcare system design. Moreover, medium access control (MAC) needs to support reliable transmission links that allow sensors to transmit data safely and stably. In this Letter, the authors provide a flexible quality of service model for ad hoc networks that can support fast data transmission, adaptive schedule MAC control, and energy efficient ubiquitous WBASN networks. Results show that the proposed multi-hop communication ad hoc network model can balance information packet collisions and power consumption. Additionally, wireless communications link in WBASNs can effectively overcome multi-user interference and offer high transmission data rates for healthcare systems.

Hyperspectral water quality retrieval model: taking Malaysia inshore sea area as an example

Science.gov (United States)

Cui, Tingwei; Zhang, Jie; Ma, Yi; Li, Jing; Lim, Boonleong; Roslinah, Samad

2007-11-01

Remote sensing technique provides the possibility of rapid and synchronous monitoring in a large area of the water quality, which is an important element for the aquatic ecosystem quality assessment of islands and coastal zones, especially for the nearshore and tourism sea area. Tioman Island of Malaysia is regarded as one of ten of the best islands in the world and attracts tourists from all over the world for its clear sea, beautiful seashore and charming scenery. In this paper, on the basis of in situ dataset in the study area, distribution discipline of water quality parameters is analyzed to find that phytoplankton pigment, rather than suspended sediment is the main water quality parameter in the study area; seawater there is clean but not very oligotrophic; seawater spectra contains distinct features. Then water quality hyperspectral retrieval models are developed based on in situ data to calculate the chlorophyll a concentration ([chl-a]), transparency (SD) with satisfactory performance. It's suggested that model precision should be validated further using more in-situ data.

Developing hydrological model for water quality in Iraq marshes zone using Landsat-TM

Science.gov (United States)

Marghany, Maged; Hasab, Hashim Ali; Mansor, Shattri; Shariff, Abdul Rashid Bin Mohamed

2016-06-01

The Mesopotamia marshlands constitute the largest wetland ecosystem in the Middle East and Western Eurasia. These wetlands are located at the confluence of the Tigris and Euphrates Rivers in southern Iraq. However, there are series reductions in the wetland zones because of neighbor countries, i.e. Turkey, Syria built dams upstream of Tigris and Euphrates Rivers. In addition, the first Gulf war of the 1980s had damaged majority of the marches resources. In fact,the marshes had been reduced in size to less than 7% since 1973 and had deteriorated in water quality parameters. The study integrates Hydrological Model of RMA-2 with Geographic Information System, and remote sensing techniques to map the water quality in the marshlands south of Iraq. This study shows that RMA-2 shows the two dimensional water flow pattern and water quality quantities in the marshlands. It can be said that the integration between Hydrological Model of RMA-2, Geographic Information System, and remote sensing techniques can be used to monitor water quality in the marshlands south of Iraq.

Numerical and Qualitative Contrasts of Two Statistical Models for Water Quality Change in Tidal Waters

Science.gov (United States)

Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and...

An experimental study on the influence of water stagnation and temperature change on water quality in a full-scale domestic drinking water system

NARCIS (Netherlands)

Zlatanović, Lj; Hoek, van der J.P.; Vreeburg, J.H.G.

2017-01-01

The drinking water quality changes during the transport through distribution systems. Domestic drinking water systems (DDWSs), which include the plumbing between the water meter and consumer's taps, are the most critical points in which water quality may be affected. In distribution networks, the

A sediment resuspension and water quality model of Lake Okeechobee

Science.gov (United States)

James, R.T.; Martin, J.; Wool, T.; Wang, P.-F.

1997-01-01

The influence of sediment resuspension on the water quality of shallow lakes is well documented. However, a search of the literature reveals no deterministic mass-balance eutrophication models that explicitly include resuspension. We modified the Lake Okeeehobee water quality model - which uses the Water Analysis Simulation Package (WASP) to simulate algal dynamics and phosphorus, nitrogen, and oxygen cycles - to include inorganic suspended solids and algorithms that: (1) define changes in depth with changes in volume; (2) compute sediment resuspension based on bottom shear stress; (3) compute partition coefficients for ammonia and ortho-phosphorus to solids; and (4) relate light attenuation to solids concentrations. The model calibration and validation were successful with the exception of dissolved inorganic nitrogen species which did not correspond well to observed data in the validation phase. This could be attributed to an inaccurate formulation of algal nitrogen preference and/or the absence of nitrogen fixation in the model. The model correctly predicted that the lake is lightlimited from resuspended solids, and algae are primarily nitrogen limited. The model simulation suggested that biological fluxes greatly exceed external loads of dissolved nutrients; and sedimentwater interactions of organic nitrogen and phosphorus far exceed external loads. A sensitivity analysis demonstrated that parameters affecting resuspension, settling, sediment nutrient and solids concentrations, mineralization, algal productivity, and algal stoichiometry are factors requiring further study to improve our understanding of the Lake Okeechobee ecosystem.

Recurrent neural network-based modeling of gene regulatory network using elephant swarm water search algorithm.

Science.gov (United States)

Mandal, Sudip; Saha, Goutam; Pal, Rajat Kumar

2017-08-01

Correct inference of genetic regulations inside a cell from the biological database like time series microarray data is one of the greatest challenges in post genomic era for biologists and researchers. Recurrent Neural Network (RNN) is one of the most popular and simple approach to model the dynamics as well as to infer correct dependencies among genes. Inspired by the behavior of social elephants, we propose a new metaheuristic namely Elephant Swarm Water Search Algorithm (ESWSA) to infer Gene Regulatory Network (GRN). This algorithm is mainly based on the water search strategy of intelligent and social elephants during drought, utilizing the different types of communication techniques. Initially, the algorithm is tested against benchmark small and medium scale artificial genetic networks without and with presence of different noise levels and the efficiency was observed in term of parametric error, minimum fitness value, execution time, accuracy of prediction of true regulation, etc. Next, the proposed algorithm is tested against the real time gene expression data of Escherichia Coli SOS Network and results were also compared with others state of the art optimization methods. The experimental results suggest that ESWSA is very efficient for GRN inference problem and performs better than other methods in many ways.

Instruments for integrated water resources management : water quality modeling for sustainable wastewater management

NARCIS (Netherlands)

Barjoveanu, George; Teodosiu, Carmen; Cojocariu, Claudia; Augustijn, Dionysius C.M.; Craciun, Ioan

2013-01-01

This study presents the development and use of a hydraulic-coupled water quality model for the simulation of Biochemical Oxygen Demand (BOD) concentrations in the Bahlui River, a small river located in northeastern Romania. This river experiences the typical pollution problems for many Romanian

Multiobjecitve Sampling Design for Calibration of Water Distribution Network Model Using Genetic Algorithm and Neural Network

Directory of Open Access Journals (Sweden)

Kourosh Behzadian

2008-03-01

Full Text Available In this paper, a novel multiobjective optimization model is presented for selecting optimal locations in the water distribution network (WDN with the aim of installing pressure loggers. The pressure data collected at optimal locations will be used later on in the calibration of the proposed WDN model. Objective functions consist of maximization of calibrated model prediction accuracy and minimization of the total cost for sampling design. In order to decrease the model run time, an optimization model has been developed using multiobjective genetic algorithm and adaptive neural network (MOGA-ANN. Neural networks (NNs are initially trained after a number of initial GA generations and periodically retrained and updated after generation of a specified number of full model-analyzed solutions. Trained NNs are replaced with the fitness evaluation of some chromosomes within the GA progress. Using cache prevents objective function evaluation of repetitive chromosomes within GA. Optimal solutions are obtained through pareto-optimal front with respect to the two objective functions. Results show that jointing NNs in MOGA for approximating portions of chromosomes’ fitness in each generation leads to considerable savings in model run time and can be promising for reducing run-time in optimization models with significant computational effort.

Water quantity and quality optimization modeling of dams operation based on SWAT in Wenyu River Catchment, China.

Science.gov (United States)

Zhang, Yongyong; Xia, Jun; Chen, Junfeng; Zhang, Minghua

2011-02-01

Water quantity and quality joint operation is a new mode in the present dams' operation research. It has become a hot topic in governmental efforts toward integrated basin improvement. This paper coupled a water quantity and quality joint operation model (QCmode) and genetic algorithm with Soil and Water Assessment Tool (SWAT). Together, these tools were used to explore a reasonable operation of dams and floodgates at the basin scale. Wenyu River Catchment, a key area in Beijing, was selected as the case study. Results showed that the coupled water quantity and quality model of Wenyu River Catchment more realistically simulates the process of water quantity and quality control by dams and floodgates. This integrated model provides the foundation for research of water quantity and quality optimization on dam operation in Wenyu River Catchment. The results of this modeling also suggest that current water quality of Wenyu River will improve following the implementation of the optimized operation of the main dams and floodgates. By pollution control and water quantity and quality joint operation of dams and floodgates, water quality of Wenyu river will change significantly, and the available water resources will increase by 134%, 32%, 17%, and 82% at the downstream sites of Sha River Reservoir, Lutong Floodgate, Xinpu Floodgate, and Weigou Floodgate, respectively. The water quantity and quality joint operation of dams will play an active role in improving water quality and water use efficiency in Wenyu River Basin. The research will provide the technical support for water pollution control and ecological restoration in Wenyu River Catchment and could be applied to other basins with large number of dams. Its application to the Wenyu River Catchment has a great significance for the sustainable economic development of Beijing City.

Integrity Model Application: A Quality Support System for Decision-makers on Water Quality Assessment and Improvement

Science.gov (United States)

Mirauda, D.; Ostoich, M.; Di Maria, F.; Benacchio, S.; Saccardo, I.

2018-03-01

In this paper, a mathematical model has been applied to a river in North-East Italy to describe vulnerability scenarios due to environmental pollution phenomena. Such model, based on the influence diagrams theory, allowed identifying the extremely critical factors, such as wastewater discharges, drainage of diffuse pollution from agriculture and climate changes, which might affect the water quality of the river. The obtained results underlined how the water quality conditions have improved thanks to the continuous controls on the territory, following the application of Water Framework Directive 2000/60/EC. Nevertheless, some fluvial stretches did not reach the “good ecological status” by 2015, because of the increasing population in urban areas recorded in the last years and the high presence of tourists during the summer months, not balanced by a treatment plants upgrade.

Modelling a water purification process for quality monitoring

NARCIS (Netherlands)

Meulen, van der F.H.; Luca, S.; Overal, G.; Dubbeldam, J.L.A.; Di Bucchianico, A.; Jongbloed, G.; Dubbeldam, J.; Groenevelt, W.; Heemink, A.W.; Lahaye, D.; Meerman, C.; Meulen, van der F.

2014-01-01

This paper deals with a quality engineering problem introduced by ‘Waterlaboratorium Noord’ (WLN) situated at the Netherlands. In-terest lies in determining an optimal sampling frequency that provides suÿcient information on the water quality in a drinking water purifica-tion plant. The water

Modeling hydrodynamics, water temperature, and water quality in the Klamath River upstream of Keno Dam, Oregon, 2006-09

Science.gov (United States)

Sullivan, Annett B.; Rounds, Stewart A.; Deas, Michael L.; Asbill, Jessica R.; Wellman, Roy E.; Stewart, Marc A.; Johnston, Matthew W.; Sogutlugil, I. Ertugrul

2011-01-01

A hydrodynamic, water temperature, and water-quality model was constructed for a 20-mile reach of the Klamath River downstream of Upper Klamath Lake, from Link River to Keno Dam, for calendar years 2006-09. The two-dimensional, laterally averaged model CE-QUAL-W2 was used to simulate water velocity, ice cover, water temperature, specific conductance, dissolved and suspended solids, dissolved oxygen, total nitrogen, ammonia, nitrate, total phosphorus, orthophosphate, dissolved and particulate organic matter, and three algal groups. The Link-Keno model successfully simulated the most important spatial and temporal patterns in the measured data for this 4-year time period. The model calibration process provided critical insights into water-quality processes and the nature of those inputs and processes that drive water quality in this reach. The model was used not only to reproduce and better understand water-quality conditions that occurred in 2006-09, but also to test several load-reduction scenarios that have implications for future water-resources management in the river basin. The model construction and calibration process provided results concerning water quality and transport in the Link-Keno reach of the Klamath River, ranging from interesting circulation patterns in the Lake Ewauna area to the nature and importance of organic matter and algae. These insights and results include: * Modeled segment-average water velocities ranged from near 0.0 to 3.0 ft/s in 2006 through 2009. Travel time through the model reach was about 4 days at 2,000 ft3/s and 12 days at 700 ft3/s flow. Flow direction was aligned with the upstream-downstream channel axis for most of the Link-Keno reach, except for Lake Ewauna. Wind effects were pronounced at Lake Ewauna during low-flow conditions, often with circulation in the form of a gyre that rotated in a clockwise direction when winds were towards the southeast and in a counterclockwise direction when winds were towards the northwest

Addressing water incidents by using pipe network models

CSIR Research Space (South Africa)

Yoyo, Sonwabiso

2016-05-01

Full Text Available quantities like flow rate and pressure with water meters. Such an approach provides a highly exact and realistic understanding, but is potentially very expensive to implement. This is especially so in view of the large number water infrastructure networks...

QUAL-NET, a high temporal-resolution eutrophication model for large hydrographic networks

Science.gov (United States)

Minaudo, Camille; Curie, Florence; Jullian, Yann; Gassama, Nathalie; Moatar, Florentina

2018-04-01

To allow climate change impact assessment of water quality in river systems, the scientific community lacks efficient deterministic models able to simulate hydrological and biogeochemical processes in drainage networks at the regional scale, with high temporal resolution and water temperature explicitly determined. The model QUALity-NETwork (QUAL-NET) was developed and tested on the Middle Loire River Corridor, a sub-catchment of the Loire River in France, prone to eutrophication. Hourly variations computed efficiently by the model helped disentangle the complex interactions existing between hydrological and biological processes across different timescales. Phosphorus (P) availability was the most constraining factor for phytoplankton development in the Loire River, but simulating bacterial dynamics in QUAL-NET surprisingly evidenced large amounts of organic matter recycled within the water column through the microbial loop, which delivered significant fluxes of available P and enhanced phytoplankton growth. This explained why severe blooms still occur in the Loire River despite large P input reductions since 1990. QUAL-NET could be used to study past evolutions or predict future trajectories under climate change and land use scenarios.

QUAL-NET, a high temporal-resolution eutrophication model for large hydrographic networks

Directory of Open Access Journals (Sweden)

C. Minaudo

2018-04-01

Full Text Available To allow climate change impact assessment of water quality in river systems, the scientific community lacks efficient deterministic models able to simulate hydrological and biogeochemical processes in drainage networks at the regional scale, with high temporal resolution and water temperature explicitly determined. The model QUALity-NETwork (QUAL-NET was developed and tested on the Middle Loire River Corridor, a sub-catchment of the Loire River in France, prone to eutrophication. Hourly variations computed efficiently by the model helped disentangle the complex interactions existing between hydrological and biological processes across different timescales. Phosphorus (P availability was the most constraining factor for phytoplankton development in the Loire River, but simulating bacterial dynamics in QUAL-NET surprisingly evidenced large amounts of organic matter recycled within the water column through the microbial loop, which delivered significant fluxes of available P and enhanced phytoplankton growth. This explained why severe blooms still occur in the Loire River despite large P input reductions since 1990. QUAL-NET could be used to study past evolutions or predict future trajectories under climate change and land use scenarios.

Climate Change Impacts on US Water Quality using two Models: HAWQS and US Basins

Science.gov (United States)

Climate change and freshwater quality are well-linked. Changes in climate result in changes in streamflow and rising water temperatures, which impact biochemical reaction rates and increase stratification in lakes and reservoirs. Using two water quality modeling systems (the Hydr...

Congestion Prediction Modeling for Quality of Service Improvement in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Ga-Won Lee

2014-04-01

Full Text Available Information technology (IT is pushing ahead with drastic reforms of modern life for improvement of human welfare. Objects constitute “Information Networks” through smart, self-regulated information gathering that also recognizes and controls current information states in Wireless Sensor Networks (WSNs. Information observed from sensor networks in real-time is used to increase quality of life (QoL in various industries and daily life. One of the key challenges of the WSNs is how to achieve lossless data transmission. Although nowadays sensor nodes have enhanced capacities, it is hard to assure lossless and reliable end-to-end data transmission in WSNs due to the unstable wireless links and low hard ware resources to satisfy high quality of service (QoS requirements. We propose a node and path traffic prediction model to predict and minimize the congestion. This solution includes prediction of packet generation due to network congestion from both periodic and event data generation. Simulation using NS-2 and Matlab is used to demonstrate the effectiveness of the proposed solution.

Use of tracer to calibrate water quality models in the river Almendares

International Nuclear Information System (INIS)

Dominguez Catasus, Judith; Borroto Portela, Jorge; Perez Machado, Esperanza; Hernandez Garces, Anel

2003-01-01

The Almendares river, one of the most important water bodies of the Havana City, is very polluted. The analysis of parameters as dissolved oxygen and biochemical oxygen demand is very helpful for the studies aimed to the recovery of the river. There is a growing recognition around the word that the water quality models are very useful tools to plan sanitary strategies for the management of wastewater contamination to predict the effectiveness of control options to improve water quality to desired levels. In the present work, the advective, steady- state Streeter and Phelps model was calibrated and validated to simulate the effect of multiple-point and distributed sources on the carbonaceous oxygen demand and dissolved oxygen. The use of the 99mTc and the Rodamine WT as tracers allowed determining the hydrodynamic parameters necessary for modeling purposes

A regional neural network model for predicting mean daily river water temperature

Science.gov (United States)

Wagner, Tyler; DeWeber, Jefferson Tyrell

2014-01-01

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate

Explore the impacts of river flow and quality on biodiversity for water resources management by AI techniques

Science.gov (United States)

Chang, Fi-John; Tsai Tsai, Wen-Ping; Chang, Li-Chiu

2016-04-01

Water resources development is very challenging in Taiwan due to her diverse geographic environment and climatic conditions. To pursue sustainable water resources development, rationality and integrity is essential for water resources planning. River water quality and flow regimes are closely related to each other and affect river ecosystems simultaneously. This study aims to explore the complex impacts of water quality and flow regimes on fish community in order to comprehend the situations of the eco-hydrological system in the Danshui River of northern Taiwan. To make an effective and comprehensive strategy for sustainable water resources management, this study first models fish diversity through implementing a hybrid artificial neural network (ANN) based on long-term observational heterogeneity data of water quality, stream flow and fish species in the river. Then we use stream flow to estimate the loss of dissolved oxygen based on back-propagation neural networks (BPNNs). Finally, the non-dominated sorting genetic algorithm II (NSGA-II) is established for river flow management over the Shihmen Reservoir which is the main reservoir in this study area. In addition to satisfying the water demands of human beings and ecosystems, we also consider water quality for river flow management. The ecosystem requirement takes the form of maximizing fish diversity, which can be estimated by the hybrid ANN. The human requirement is to provide a higher satisfaction degree of water supply while the water quality requirement is to reduce the loss of dissolved oxygen in the river among flow stations. The results demonstrate that the proposed methodology can offer diversified alternative strategies for reservoir operation and improve reservoir operation strategies for producing downstream flows that could better meet both human and ecosystem needs as well as maintain river water quality. Keywords: Artificial intelligence (AI), Artificial neural networks (ANNs), Non

Propagating Water Quality Analysis Uncertainty Into Resource Management Decisions Through Probabilistic Modeling

Science.gov (United States)

Gronewold, A. D.; Wolpert, R. L.; Reckhow, K. H.

2007-12-01

Most probable number (MPN) and colony-forming-unit (CFU) are two estimates of fecal coliform bacteria concentration commonly used as measures of water quality in United States shellfish harvesting waters. The MPN is the maximum likelihood estimate (or MLE) of the true fecal coliform concentration based on counts of non-sterile tubes in serial dilution of a sample aliquot, indicating bacterial metabolic activity. The CFU is the MLE of the true fecal coliform concentration based on the number of bacteria colonies emerging on a growth plate after inoculation from a sample aliquot. Each estimating procedure has intrinsic variability and is subject to additional uncertainty arising from minor variations in experimental protocol. Several versions of each procedure (using different sized aliquots or different numbers of tubes, for example) are in common use, each with its own levels of probabilistic and experimental error and uncertainty. It has been observed empirically that the MPN procedure is more variable than the CFU procedure, and that MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the observed variability in, and discrepancy between, MPN and CFU measurements. We then explore how this variability and uncertainty might propagate into shellfish harvesting area management decisions through a two-phased modeling strategy. First, we apply our probabilistic model in a simulation-based analysis of future water quality standard violation frequencies under alternative land use scenarios, such as those evaluated under guidelines of the total maximum daily load (TMDL) program. Second, we apply our model to water quality data from shellfish harvesting areas which at present are closed (either conditionally or permanently) to shellfishing, to determine if alternative laboratory analysis procedures might have led to different

Assessment of water quality in distribution networks through the lens ...

African Journals Online (AJOL)

2016-04-02

Apr 2, 2016 ... method, which identifies the regions with relatively poor water quality and highlights the potential locations for ... intelligent decision-making based on the results and the imple- ... A water supply system where water is treated.

MODELING OF WATER DISTRIBUTION SYSTEM PARAMETERS AND THEIR PARTICULAR IMPORTANCE IN ENVIRONMENT ENGINEERING PROCESSES

Directory of Open Access Journals (Sweden)

Agnieszka Trębicka

2016-05-01

Full Text Available The object of this study is to present a mathematical model of water-supply network and the analysis of basic parameters of water distribution system with a digital model. The reference area is Kleosin village, municipality Juchnowiec Kościelny in podlaskie province, located at the border with Białystok. The study focused on the significance of every change related to the quality and quantity of water delivered to WDS through modeling the basic parameters of water distribution system in different variants of work in order to specify new, more rational ways of exploitation (decrease in pressure value and to define conditions for development and modernization of the water-supply network, with special analysis of the scheme, in frames of specification of the most dangerous places in the network. The analyzed processes are based on copying and developing the existing state of water distribution sub-system (the WDS with the use of mathematical modeling that includes the newest accessible computer techniques.

Industrial pollution and the management of river water quality: a model of Kelani River, Sri Lanka.

Science.gov (United States)

Gunawardena, Asha; Wijeratne, E M S; White, Ben; Hailu, Atakelty; Pandit, Ram

2017-08-19

Water quality of the Kelani River has become a critical issue in Sri Lanka due to the high cost of maintaining drinking water standards and the market and non-market costs of deteriorating river ecosystem services. By integrating a catchment model with a river model of water quality, we developed a method to estimate the effect of pollution sources on ambient water quality. Using integrated model simulations, we estimate (1) the relative contribution from point (industrial and domestic) and non-point sources (river catchment) to river water quality and (2) pollutant transfer coefficients for zones along the lower section of the river. Transfer coefficients provide the basis for policy analyses in relation to the location of new industries and the setting of priorities for industrial pollution control. They also offer valuable information to design socially optimal economic policy to manage industrialized river catchments.

Integrated hydrological and water quality model for river management: A case study on Lena River

Energy Technology Data Exchange (ETDEWEB)

Fonseca, André, E-mail: andrerd@gmail.com; Botelho, Cidália; Boaventura, Rui A.R.; Vilar, Vítor J.P., E-mail: vilar@fe.up.pt

2014-07-01

The Hydrologic Simulation Program FORTRAN (HSPF) model was used to assess the impact of wastewater discharges on the water quality of a Lis River tributary (Lena River), a 176 km{sup 2} watershed in Leiria region, Portugal. The model parameters obtained in this study, could potentially serve as reference values for the calibration of other watersheds in the area or with similar climatic characteristics, which don't have enough data for calibration. Water quality constituents modeled in this study included temperature, fecal coliforms, dissolved oxygen, biochemical oxygen demand, total suspended solids, nitrates, orthophosphates and pH. The results were found to be close to the average observed values for all parameters studied for both calibration and validation periods with percent bias values between − 26% and 23% for calibration and − 30% and 51% for validation for all parameters, with fecal coliforms showing the highest deviation. The model revealed a poor water quality in Lena River for the entire simulation period, according to the Council Directive concerning the surface water quality intended for drinking water abstraction in the Member States (75/440/EEC). Fecal coliforms, orthophosphates and nitrates were found to be 99, 82 and 46% above the limit established in the Directive. HSPF was used to predict the impact of point and nonpoint pollution sources on the water quality of Lena River. Winter and summer scenarios were also addressed to evaluate water quality in high and low flow conditions. A maximum daily load was calculated to determine the reduction needed to comply with the Council Directive 75/440/EEC. The study showed that Lena River is fairly polluted calling for awareness at behavioral change of waste management in order to prevent the escalation of these effects with especially attention to fecal coliforms. - Highlights: • An integrated hydrological and water quality model for river management is presented. • An insight into the

The simple modelling method for storm- and grey-water quality ...

African Journals Online (AJOL)

The simple modelling method for storm- and grey-water quality management applied to Alexandra settlement. ... objectives optimally consist of educational programmes, erosion and sediment control, street sweeping, removal of sanitation system overflows, impervious cover reduction, downspout disconnections, removal of ...

Modeling Climate and Management Change Impacts on Water Quality and In-Stream Processes in the Elbe River Basin

Directory of Open Access Journals (Sweden)

Cornelia Hesse

2016-01-01

Full Text Available Eco-hydrological water quality modeling for integrated water resources management of river basins should include all necessary landscape and in-stream nutrient processes as well as possible changes in boundary conditions and driving forces for nutrient behavior in watersheds. The study aims to assess possible impacts of the changing climate (ENSEMBLES climate scenarios and/or land use conditions on resulting river water quantity and quality in the large-scale Elbe river basin by applying a semi-distributed watershed model of intermediate complexity (SWIM with implemented in-stream nutrient (N+P turnover and algal growth processes. The calibration and validation results revealed the ability of SWIM to satisfactorily simulate nutrient behavior at the watershed scale. Analysis of 19 climate scenarios for the whole Elbe river basin showed a projected increase in temperature (+3 °C and precipitation (+57 mm on average until the end of the century, causing diverse changes in river discharge (+20%, nutrient loads (NO3-N: −5%; NH4-N: −24%; PO4-P: +5%, phytoplankton biomass (−4% and dissolved oxygen concentration (−5% in the watershed. In addition, some changes in land use and nutrient management were tested in order to reduce nutrient emissions to the river network.

Leakage detection algorithm integrating water distribution networks hydraulic model

CSIR Research Space (South Africa)

Adedeji, K

2017-06-01

Full Text Available Water loss through leaking pipes is inexorable in water distribution networks (WDNs) and has been recognized as a major challenge facing the operation of municipal water services. This is strongly linked with financial costs due to economic loss...

A Hybrid Interval-Robust Optimization Model for Water Quality Management.

Science.gov (United States)

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-05-01

In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

A Hybrid Interval–Robust Optimization Model for Water Quality Management

Science.gov (United States)

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-01-01

Abstract In water quality management problems, uncertainties may exist in many system components and pollution-related processes (i.e., random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval–robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements. PMID:23922495

Biological instability in a chlorinated drinking water distribution network.

Science.gov (United States)

Nescerecka, Alina; Rubulis, Janis; Vital, Marius; Juhna, Talis; Hammes, Frederik

2014-01-01

The purpose of a drinking water distribution system is to deliver drinking water to the consumer, preferably with the same quality as when it left the treatment plant. In this context, the maintenance of good microbiological quality is often referred to as biological stability, and the addition of sufficient chlorine residuals is regarded as one way to achieve this. The full-scale drinking water distribution system of Riga (Latvia) was investigated with respect to biological stability in chlorinated drinking water. Flow cytometric (FCM) intact cell concentrations, intracellular adenosine tri-phosphate (ATP), heterotrophic plate counts and residual chlorine measurements were performed to evaluate the drinking water quality and stability at 49 sampling points throughout the distribution network. Cell viability methods were compared and the importance of extracellular ATP measurements was examined as well. FCM intact cell concentrations varied from 5×10(3) cells mL(-1) to 4.66×10(5) cells mL(-1) in the network. While this parameter did not exceed 2.1×10(4) cells mL(-1) in the effluent from any water treatment plant, 50% of all the network samples contained more than 1.06×10(5) cells mL(-1). This indisputably demonstrates biological instability in this particular drinking water distribution system, which was ascribed to a loss of disinfectant residuals and concomitant bacterial growth. The study highlights the potential of using cultivation-independent methods for the assessment of chlorinated water samples. In addition, it underlines the complexity of full-scale drinking water distribution systems, and the resulting challenges to establish the causes of biological instability.

Optimum Layout for Sensors in Water Distribution Networks through Ant Colony Algorithm: A Dual Use Vision

Directory of Open Access Journals (Sweden)

Seyed Mehdi Miri

2014-07-01

Full Text Available The accidental or intentional entry of contaminants or self-deterioration of the water quality within the network itself can severely harm public health. Efficient water quality monitoring is one of the most important tools to guarantee a reliable potable water supply to consumers of drinking water distribution systems. Considering the high purchase, installation and maintenance cost of sensors in water distribution networks deploying two independent sensor networks within one distribution system is not only bounded by physical constraints but also is not a cost-effective approach. Therefore, need for combining different objectives and designing sensor network to simultaneity satisfying these objectives is felt. Sensors should comply with dual use benefits. Sensor locations and types should be integrated not only for achieving water security goals but also for accomplishing other water utility objectives, such as satisfying regulatory monitoring requirements or collecting information to solve water quality problems. In this study, a dual use vision for the sensor layout problem in the municipal water networks, is formulated and solved with the ant colony algorithm.

Application of HEC-RAS water quality model to estimate contaminant spreading in small stream

Energy Technology Data Exchange (ETDEWEB)

Halaj, Peter; Bárek, Viliam; Halajová, Anna Báreková; Halajová, Denisa [Slovak University of Agriculture in Nitra, Nitra (Slovakia)

2013-07-01

The paper presents study of some aspects of HEC-RAS water quality model connected to simulation of contaminant transport in small stream. Authors mainly focused on one of the key tasks in process of pollutant transport modelling in streams - determination of the dispersion characteristics represented by longitudinal dispersion coefficient D. Different theoretical and empirical formulas have been proposed for D value determination and they have revealed that the coefficient is variable parameter that depends on hydraulic and morphometric characteristics of the stream reaches. Authors compare the results of several methods of coefficient D assessment, assuming experimental data obtained by tracer studies and compare them with results optimized by HEC-RAS water quality model. The analyses of tracer study and computation outputs allow us to outline the important aspects of longitudinal dispersion coefficient set up in process of the HEC-RAS model use. Key words: longitudinal dispersion coefficient, HEC-RAS, water quality modeling.

Representativeness of air quality monitoring networks

NARCIS (Netherlands)

Duyzer, J.; Hout, D. van den; Zandveld, P.; Ratingen, S. van

2015-01-01

The suitability of European networks to check compliance with air quality standards and to assess exposure of the population was investigated. An air quality model (URBIS) was applied to estimate and compare the spatial distribution of the concentration of nitrogen dioxide (NO2) in ambient air in

Risk-based water resources planning: Coupling water allocation and water quality management under extreme droughts

Science.gov (United States)

Mortazavi-Naeini, M.; Bussi, G.; Hall, J. W.; Whitehead, P. G.

2016-12-01

The main aim of water companies is to have a reliable and safe water supply system. To fulfil their duty the water companies have to consider both water quality and quantity issues and challenges. Climate change and population growth will have an impact on water resources both in terms of available water and river water quality. Traditionally, a distinct separation between water quality and abstraction has existed. However, water quality can be a bottleneck in a system since water treatment works can only treat water if it meets certain standards. For instance, high turbidity and large phytoplankton content can increase sharply the cost of treatment or even make river water unfit for human consumption purposes. It is vital for water companies to be able to characterise the quantity and quality of water under extreme weather events and to consider the occurrence of eventual periods when water abstraction has to cease due to water quality constraints. This will give them opportunity to decide on water resource planning and potential changes to reduce the system failure risk. We present a risk-based approach for incorporating extreme events, based on future climate change scenarios from a large ensemble of climate model realisations, into integrated water resources model through combined use of water allocation (WATHNET) and water quality (INCA) models. The annual frequency of imposed restrictions on demand is considered as measure of reliability. We tested our approach on Thames region, in the UK, with 100 extreme events. The results show increase in frequency of imposed restrictions when water quality constraints were considered. This indicates importance of considering water quality issues in drought management plans.

Water quality management for Lake Mariout

Directory of Open Access Journals (Sweden)

N. Donia

2016-06-01

Full Text Available A hydrodynamic and water quality model was used to study the current status of the Lake Mariout subject to the pollution loadings from the agricultural drains and the point sources discharging directly to the Lake. The basic water quality modelling component simulates the main water quality parameters including the oxygen compounds (BOD, COD, DO, nutrients compounds (NH4, TN, TP, and finally the temperature, salinity and inorganic matter. Many scenarios have been conducted to improve the circulation and the water quality in the lake and to assess the spreading and mixing of the discharge effluents and its impact on the water quality of the main basin. Several pilot interventions were applied through the model in the Lake Mariout together with the upgrades of the East and West Waste Water Treatment Plants in order to achieve at least 5% reduction in the pollution loads entering the Mediterranean Sea through Lake Mariout in order to improve the institutional mechanisms for sustainable coastal zone management in Alexandria in particular to reduce land-based pollution to the Mediterranean Sea.

[Development and application of a multi-species water quality model for water distribution systems with EPANET-MSX].

Science.gov (United States)

Sun, Fu; Chen, Ji-ning; Zeng, Si-yu

2008-12-01

A conceptual multi-species water quality model for water distribution systems was developed on the basis of the toolkit of the EPANET-MSX software. The model divided the pipe segment into four compartments including pipe wall, biofilm, boundary layer and bulk liquid. The involved processes were substrate utilization and microbial growth, decay and inactivation of microorganisms, mass transfer of soluble components through the boundary layer, adsorption and desorption of particular components between bulk liquid and biofilm, oxidation and halogenation of organic matter by residual chlorine, and chlorine consumption by pipe wall. The fifteen simulated variables included the seven common variables both in the biofilm and in the bulk liquid, i.e. soluble organic matter, particular organic matter, ammonia nitrogen, residual chlorine, heterotrophic bacteria, autotrophic bacteria and inert solids, as well as biofilm thickness on the pipe wall. The model was validated against the data from a series of pilot experiments, and the simulation accuracy for residual chlorine and turbidity were 0.1 mg/L and 0.3 NTU respectively. A case study showed that the model could reasonably reflect the dynamic variation of residual chlorine and turbidity in the studied water distribution system, while Monte Carlo simulation, taking into account both the variability of finished water from the waterworks and the uncertainties of model parameters, could be performed to assess the violation risk of water quality in the water distribution system.

Potential impacts of changing supply-water quality on drinking water distribution: A review.

Science.gov (United States)

Liu, Gang; Zhang, Ya; Knibbe, Willem-Jan; Feng, Cuijie; Liu, Wentso; Medema, Gertjan; van der Meer, Walter

2017-06-01

Driven by the development of water purification technologies and water quality regulations, the use of better source water and/or upgraded water treatment processes to improve drinking water quality have become common practices worldwide. However, even though these elements lead to improved water quality, the water quality may be impacted during its distribution through piped networks due to the processes such as pipe material release, biofilm formation and detachment, accumulation and resuspension of loose deposits. Irregular changes in supply-water quality may cause physiochemical and microbiological de-stabilization of pipe material, biofilms and loose deposits in the distribution system that have been established over decades and may harbor components that cause health or esthetical issues (brown water). Even though it is clearly relevant to customers' health (e.g., recent Flint water crisis), until now, switching of supply-water quality is done without any systematic evaluation. This article reviews the contaminants that develop in the water distribution system and their characteristics, as well as the possible transition effects during the switching of treated water quality by destabilization and the release of pipe material and contaminants into the water and the subsequent risks. At the end of this article, a framework is proposed for the evaluation of potential transition effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

WaterNet: The NASA water cycle solutions network - Danubian regional applications

International Nuclear Information System (INIS)

Matthews, Dave; Brilly, Mitja; Kobold, Mira; Zagar, Mark; Houser, Paul

2008-01-01

WaterNet is a new international network of researchers, stakeholders, and end-users of remote sensing tools that will benefit the water resources management community. This paper provides an overview and it discusses the concept of solutions networks focusing on the WaterNet. It invites Danubian research and applications teams to join our WaterNet network. The NASA Water cycle Solutions Network's goal is to improve and optimize the sustained ability of water cycle researchers, stakeholders, organizations and networks to interact, identify, harness, and extend NASA research results to augment decision support tools and meet national needs. Our team will develop WaterNet by engaging relevant NASA water cycle research resources and community-of-practice organizations, to develop what we term an 'actionable database' that can be used to communicate and connect NASA Water cycle research Results (NWRs) towards the improvement of water-related Decision Support Tools (DSTs). Recognizing that the European Commission and European Space Agency have also developed many related Water Research products (EWRs), we seek to learn about these and network with the EU teams to include their information in the WaterNet actionable data base and Community of Practice. WaterNet will then develop strategies to connect researchers and decision-makers via innovative communication strategies, improved user access to NASA and EU - Danubian resources, improved water cycle research community appreciation for user requirements, improved policymaker, management and stakeholder knowledge of research and application products, and improved identification of pathways for progress. Finally, WaterNet will develop relevant benchmarking and metrics, to understand the network's characteristics, to optimize its performance, and to establish sustainability. This paper provides examples of several NASA products based on remote sensing and land data assimilation systems that integrate remotely sensed and in

Maui Citizen Science Coastal Water Quality Data

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — A network of citizen science volunteers periodically monitors water quality at several beaches across the island of Maui in the State of Hawaii. This community-based...

Hydrogeology and water quality of the shallow ground-water system in eastern York County, Virginia. Water resources investigation

International Nuclear Information System (INIS)

1993-01-01

The report describes the hydrogeology and water quality of the shallow ground-water system in the eastern part of York County, Va. The report includes a discussion of (1) the aquifers and confining units, (2) the flow of ground water, and (3) the quality of ground water. The report is an evaluation of the shallow ground-water system and focuses on the first 200 ft of sediments below land surface. Historical water-level and water-quality data were not available for the study area; therefore, a network of observation wells was constructed for the study. Water levels were measured to provide an understanding of the flow of ground water through the multiaquifer system. Water samples were collected and analyzed for major inorganic constituents, nutrients, and metals. The report presents maps that show the regional distribution of chloride and iron concentrations. Summary statistics and graphical summaries of selected chemical constituents provide a general assessment of the ground-water quality

Voice Quality Estimation in Combined Radio-VoIP Networks for Dispatching Systems

Directory of Open Access Journals (Sweden)

Jiri Vodrazka

2016-01-01

Full Text Available The voice quality modelling assessment and planning field is deeply and widely theoretically and practically mastered for common voice communication systems, especially for the public fixed and mobile telephone networks including Next Generation Networks (NGN - internet protocol based networks. This article seeks to contribute voice quality modelling assessment and planning for dispatching communication systems based on Internet Protocol (IP and private radio networks. The network plan, correction in E-model calculation and default values for the model are presented and discussed.

Water quality and management of private drinking water wells in Pennsylvania.

Science.gov (United States)

Swistock, Bryan R; Clemens, Stephanie; Sharpe, William E; Rummel, Shawn

2013-01-01

Pennsylvania has over three million rural residents using private water wells for drinking water supplies but is one of the few states that lack statewide water well construction or management standards. The study described in this article aimed to determine the prevalence and causes of common health-based pollutants in water wells and evaluate the need for regulatory management along with voluntary educational programs. Water samples were collected throughout Pennsylvania by Master Well Owner Network volunteers trained by Penn State Extension. Approximately 40% of the 701 water wells sampled failed at least one health-based drinking water standard. The prevalence of most water quality problems was similar to past studies although both lead and nitrate-N were reduced over the last 20 years. The authors' study suggests that statewide water well construction standards along with routine water testing and educational programs to assist water well owners would result in improved drinking water quality for private well owners in Pennsylvania.

Application of regression model on stream water quality parameters

International Nuclear Information System (INIS)

Suleman, M.; Maqbool, F.; Malik, A.H.; Bhatti, Z.A.

2012-01-01

Statistical analysis was conducted to evaluate the effect of solid waste leachate from the open solid waste dumping site of Salhad on the stream water quality. Five sites were selected along the stream. Two sites were selected prior to mixing of leachate with the surface water. One was of leachate and other two sites were affected with leachate. Samples were analyzed for pH, water temperature, electrical conductivity (EC), total dissolved solids (TDS), Biological oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO) and total bacterial load (TBL). In this study correlation coefficient r among different water quality parameters of various sites were calculated by using Pearson model and then average of each correlation between two parameters were also calculated, which shows TDS and EC and pH and BOD have significantly increasing r value, while temperature and TDS, temp and EC, DO and BL, DO and COD have decreasing r value. Single factor ANOVA at 5% level of significance was used which shows EC, TDS, TCL and COD were significantly differ among various sites. By the application of these two statistical approaches TDS and EC shows strongly positive correlation because the ions from the dissolved solids in water influence the ability of that water to conduct an electrical current. These two parameters significantly vary among 5 sites which are further confirmed by using linear regression. (author)

Quality-assurance plan for groundwater activities, U.S. Geological Survey, Washington Water Science Center

Science.gov (United States)

Kozar, Mark D.; Kahle, Sue C.

2013-01-01

This report documents the standard procedures, policies, and field methods used by the U.S. Geological Survey’s (USGS) Washington Water Science Center staff for activities related to the collection, processing, analysis, storage, and publication of groundwater data. This groundwater quality-assurance plan changes through time to accommodate new methods and requirements developed by the Washington Water Science Center and the USGS Office of Groundwater. The plan is based largely on requirements and guidelines provided by the USGS Office of Groundwater, or the USGS Water Mission Area. Regular updates to this plan represent an integral part of the quality-assurance process. Because numerous policy memoranda have been issued by the Office of Groundwater since the previous groundwater quality assurance plan was written, this report is a substantial revision of the previous report, supplants it, and contains significant additional policies not covered in the previous report. This updated plan includes information related to the organization and responsibilities of USGS Washington Water Science Center staff, training, safety, project proposal development, project review procedures, data collection activities, data processing activities, report review procedures, and archiving of field data and interpretative information pertaining to groundwater flow models, borehole aquifer tests, and aquifer tests. Important updates from the previous groundwater quality assurance plan include: (1) procedures for documenting and archiving of groundwater flow models; (2) revisions to procedures and policies for the creation of sites in the Groundwater Site Inventory database; (3) adoption of new water-level forms to be used within the USGS Washington Water Science Center; (4) procedures for future creation of borehole geophysics, surface geophysics, and aquifer-test archives; and (5) use of the USGS Multi Optional Network Key Entry System software for entry of routine water-level data

Florida's ground water quality monitoring program: background hydrogeochemistry

OpenAIRE

Maddox, Gary; Upchurch, Sam; Lloyd, Jacqueline; Scott, Tom

1992-01-01

The purpose of this report is to present the results of the initial quantification of background water quality in each of the state's major potable aquifer systems. Results are presented and interpreted in light of the influencing factors which locally and regionally affect ambient ground-water quality. This initial data will serve as a baseline from which future sampling results can be compared. Future sampling of the Network will indicate the extent to which Flori...

A versatile and interoperable network sensors for water resources monitoring

Science.gov (United States)

Ortolani, Alberto; Brandini, Carlo; Costantini, Roberto; Costanza, Letizia; Innocenti, Lucia; Sabatini, Francesco; Gozzini, Bernardo

2010-05-01

Monitoring systems to assess water resources quantity and quality require extensive use of in-situ measurements, that have great limitations like difficulties to access and share data, and to customise and easy reconfigure sensors network to fulfil end-users needs during monitoring or crisis phases. In order to address such limitations Sensor Web Enablement technologies for sensors management have been developed and applied to different environmental context under the EU-funded OSIRIS project (Open architecture for Smart and Interoperable networks in Risk management based on In-situ Sensors, www.osiris-fp6.eu). The main objective of OSIRIS was to create a monitoring system to manage different environmental crisis situations, through an efficient data processing chain where in-situ sensors are connected via an intelligent and versatile network infrastructure (based on web technologies) that enables end-users to remotely access multi-domain sensors information. Among the project application, one was focused on underground fresh-water monitoring and management. With this aim a monitoring system to continuously and automatically check water quality and quantity has been designed and built in a pilot test, identified as a portion of the Amiata aquifer feeding the Santa Fiora springs (Grosseto, Italy). This aquifer present some characteristics that make it greatly vulnerable under some conditions. It is a volcanic aquifer with a fractured structure. The volcanic nature in Santa Fiora causes levels of arsenic concentrations that normally are very close to the threshold stated by law, but that sometimes overpass such threshold for reasons still not fully understood. The presence of fractures makes the infiltration rate very inhomogeneous from place to place and very high in correspondence of big fractures. In case of liquid-pollutant spills (typically hydrocarbons spills from tanker accidents or leakage from house tanks containing fuel for heating), these fractures can act

Optimal design of monitoring networks for multiple groundwater quality parameters using a Kalman filter: application to the Irapuato-Valle aquifer.

Science.gov (United States)

Júnez-Ferreira, H E; Herrera, G S; González-Hita, L; Cardona, A; Mora-Rodríguez, J

2016-01-01

A new method for the optimal design of groundwater quality monitoring networks is introduced in this paper. Various indicator parameters were considered simultaneously and tested for the Irapuato-Valle aquifer in Mexico. The steps followed in the design were (1) establishment of the monitoring network objectives, (2) definition of a groundwater quality conceptual model for the study area, (3) selection of the parameters to be sampled, and (4) selection of a monitoring network by choosing the well positions that minimize the estimate error variance of the selected indicator parameters. Equal weight for each parameter was given to most of the aquifer positions and a higher weight to priority zones. The objective for the monitoring network in the specific application was to obtain a general reconnaissance of the water quality, including water types, water origin, and first indications of contamination. Water quality indicator parameters were chosen in accordance with this objective, and for the selection of the optimal monitoring sites, it was sought to obtain a low-uncertainty estimate of these parameters for the entire aquifer and with more certainty in priority zones. The optimal monitoring network was selected using a combination of geostatistical methods, a Kalman filter and a heuristic optimization method. Results show that when monitoring the 69 locations with higher priority order (the optimal monitoring network), the joint average standard error in the study area for all the groundwater quality parameters was approximately 90 % of the obtained with the 140 available sampling locations (the set of pilot wells). This demonstrates that an optimal design can help to reduce monitoring costs, by avoiding redundancy in data acquisition.

Water-quality models to assess algal community dynamics, water quality, and fish habitat suitability for two agricultural land-use dominated lakes in Minnesota, 2014

Science.gov (United States)

Smith, Erik A.; Kiesling, Richard L.; Ziegeweid, Jeffrey R.

2017-07-20

Fish habitat can degrade in many lakes due to summer blue-green algal blooms. Predictive models are needed to better manage and mitigate loss of fish habitat due to these changes. The U.S. Geological Survey (USGS), in cooperation with the Minnesota Department of Natural Resources, developed predictive water-quality models for two agricultural land-use dominated lakes in Minnesota—Madison Lake and Pearl Lake, which are part of Minnesota’s sentinel lakes monitoring program—to assess algal community dynamics, water quality, and fish habitat suitability of these two lakes under recent (2014) meteorological conditions. The interaction of basin processes to these two lakes, through the delivery of nutrient loads, were simulated using CE-QUAL-W2, a carbon-based, laterally averaged, two-dimensional water-quality model that predicts distribution of temperature and oxygen from interactions between nutrient cycling, primary production, and trophic dynamics.The CE-QUAL-W2 models successfully predicted water temperature and dissolved oxygen on the basis of the two metrics of mean absolute error and root mean square error. For Madison Lake, the mean absolute error and root mean square error were 0.53 and 0.68 degree Celsius, respectively, for the vertical temperature profile comparisons; for Pearl Lake, the mean absolute error and root mean square error were 0.71 and 0.95 degree Celsius, respectively, for the vertical temperature profile comparisons. Temperature and dissolved oxygen were key metrics for calibration targets. These calibrated lake models also simulated algal community dynamics and water quality. The model simulations presented potential explanations for persistently large total phosphorus concentrations in Madison Lake, key differences in nutrient concentrations between these lakes, and summer blue-green algal bloom persistence.Fish habitat suitability simulations for cool-water and warm-water fish indicated that, in general, both lakes contained a large

Real-time dynamic hydraulic model for water distribution networks: steady state modelling

CSIR Research Space (South Africa)

Osman, Mohammad S

2016-09-01

Full Text Available equipment (pipes, reservoirs, pumps, valves, etc.) was used as a pilot WDN. Further information of the various other DHM components has been published [1]. The steady-state hydraulic model calculates the network hydraulic variables at a particular... from the abstraction point to the two low-level concrete reservoirs. On this pipeline there is a 2” tie-off to an alternate consumer as well as another 2” tie-off (5 m length) to the pump station sump. Water from the pump station is pumped to two...

Identifying the Correlation between Water Quality Data and LOADEST Model Behavior in Annual Sediment Load Estimations

Directory of Open Access Journals (Sweden)

Youn Shik Park

2016-08-01

Full Text Available Water quality samples are typically collected less frequently than flow since water quality sampling is costly. Load Estimator (LOADEST, provided by the United States Geological Survey, is used to predict water quality concentration (or load on days when flow data are measured so that the water quality data are sufficient for annual pollutant load estimation. However, there is a need to identify water quality data requirements for accurate pollutant load estimation. Measured daily sediment data were collected from 211 streams. Estimated annual sediment loads from LOADEST and subsampled data were compared to the measured annual sediment loads (true load. The means of flow for calibration data were correlated to model behavior. A regression equation was developed to compute the required mean of flow in calibration data to best calibrate the LOADEST regression model coefficients. LOADEST runs were performed to investigate the correlation between the mean flow in calibration data and model behaviors as daily water quality data were subsampled. LOADEST calibration data used sediment concentration data for flows suggested by the regression equation. Using the mean flow calibrated by the regression equation reduced errors in annual sediment load estimation from −39.7% to −10.8% compared to using all available data.

Risk analysis of emergent water pollution accidents based on a Bayesian Network.

Science.gov (United States)

Tang, Caihong; Yi, Yujun; Yang, Zhifeng; Sun, Jie

2016-01-01

To guarantee the security of water quality in water transfer channels, especially in open channels, analysis of potential emergent pollution sources in the water transfer process is critical. It is also indispensable for forewarnings and protection from emergent pollution accidents. Bridges above open channels with large amounts of truck traffic are the main locations where emergent accidents could occur. A Bayesian Network model, which consists of six root nodes and three middle layer nodes, was developed in this paper, and was employed to identify the possibility of potential pollution risk. Dianbei Bridge is reviewed as a typical bridge on an open channel of the Middle Route of the South to North Water Transfer Project where emergent traffic accidents could occur. Risk of water pollutions caused by leakage of pollutants into water is focused in this study. The risk for potential traffic accidents at the Dianbei Bridge implies a risk for water pollution in the canal. Based on survey data, statistical analysis, and domain specialist knowledge, a Bayesian Network model was established. The human factor of emergent accidents has been considered in this model. Additionally, this model has been employed to describe the probability of accidents and the risk level. The sensitive reasons for pollution accidents have been deduced. The case has also been simulated that sensitive factors are in a state of most likely to lead to accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Monthly water quality forecasting and uncertainty assessment via bootstrapped wavelet neural networks under missing data for Harbin, China.

Science.gov (United States)

Wang, Yi; Zheng, Tong; Zhao, Ying; Jiang, Jiping; Wang, Yuanyuan; Guo, Liang; Wang, Peng

2013-12-01

In this paper, bootstrapped wavelet neural network (BWNN) was developed for predicting monthly ammonia nitrogen (NH(4+)-N) and dissolved oxygen (DO) in Harbin region, northeast of China. The Morlet wavelet basis function (WBF) was employed as a nonlinear activation function of traditional three-layer artificial neural network (ANN) structure. Prediction intervals (PI) were constructed according to the calculated uncertainties from the model structure and data noise. Performance of BWNN model was also compared with four different models: traditional ANN, WNN, bootstrapped ANN, and autoregressive integrated moving average model. The results showed that BWNN could handle the severely fluctuating and non-seasonal time series data of water quality, and it produced better performance than the other four models. The uncertainty from data noise was smaller than that from the model structure for NH(4+)-N; conversely, the uncertainty from data noise was larger for DO series. Besides, total uncertainties in the low-flow period were the biggest due to complicated processes during the freeze-up period of the Songhua River. Further, a data missing-refilling scheme was designed, and better performances of BWNNs for structural data missing (SD) were observed than incidental data missing (ID). For both ID and SD, temporal method was satisfactory for filling NH(4+)-N series, whereas spatial imputation was fit for DO series. This filling BWNN forecasting method was applied to other areas suffering "real" data missing, and the results demonstrated its efficiency. Thus, the methods introduced here will help managers to obtain informed decisions.

Water Quality Analysis Simulation Program (WASP)

Science.gov (United States)

The Water Quality Analysis Simulation Program (WASP) model helps users interpret and predict water quality responses to natural phenomena and manmade pollution for various pollution management decisions.

Model development of a participatory Bayesian network for coupling ecosystem services into integrated water resources management

Science.gov (United States)

Xue, Jie; Gui, Dongwei; Lei, Jiaqiang; Zeng, Fanjiang; Mao, Donglei; Zhang, Zhiwei

2017-11-01

There is an increasing consensus on the importance of coupling ecosystem services (ES) into integrated water resource management (IWRM), due to a wide range of benefits to human from the ES. This paper proposes an ES-based IWRM framework within which a participatory Bayesian network (BN) model is developed to assist with the coupling between ES and IWRM. The framework includes three steps: identifying water-related services of ecosystems; analysis of the tradeoff and synergy among users of water; and ES-based IWRM implementation using the participatory BN model. We present the development, evaluation and application of the participatory BN model with the involvement of four participant groups (stakeholders, water manager, water management experts, and research team) in Qira oasis area, Northwest China. As a typical catchment-scale region, the Qira oasis area is facing severe water competition between the demands of human activities and natural ecosystems. Results demonstrate that the BN model developed provides effective integration of ES into a quantitative IWMR framework via public negotiation and feedback. The network results, sensitivity evaluation, and management scenarios are broadly accepted by the participant groups. The intervention scenarios from the model conclude that any water management measure remains unable to sustain the ecosystem health in water-related ES. Greater cooperation among the stakeholders is highly necessary for dealing with such water conflicts. In particular, a proportion of the agricultural water saved through improving water-use efficiency should be transferred to natural ecosystems via water trade. The BN model developed is appropriate for areas throughout the world in which there is intense competition for water between human activities and ecosystems.

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

Energy Technology Data Exchange (ETDEWEB)

Cid, Fabricio D., E-mail: fabricio.cid@gmail.com [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Anton, Rosa I. [Department of Analytical Chemistry, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Pardo, Rafael; Vega, Marisol [Department of Analytical Chemistry, Facultad de Ciencias, Universidad de Valladolid, Valladolid (Spain); Caviedes-Vidal, Enrique [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina)

2011-10-31

Highlights: {yields} Water quality of an Argentinean reservoir has been investigated by N-way PCA. {yields} PARAFAC mode modelled spatial and seasonal variations of water composition. {yields} Two factors related with organic and lead pollution have been identified. {yields} The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

International Nuclear Information System (INIS)

Cid, Fabricio D.; Anton, Rosa I.; Pardo, Rafael; Vega, Marisol; Caviedes-Vidal, Enrique

2011-01-01

Highlights: → Water quality of an Argentinean reservoir has been investigated by N-way PCA. → PARAFAC mode modelled spatial and seasonal variations of water composition. → Two factors related with organic and lead pollution have been identified. → The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the spatial and

SWANN: The Snow Water Artificial Neural Network Modelling System

Science.gov (United States)

Broxton, P. D.; van Leeuwen, W.; Biederman, J. A.

2017-12-01

Snowmelt from mountain forests is important for water supply and ecosystem health. Along Arizona's Mogollon Rim, snowmelt contributes to rivers and streams that provide a significant water supply for hydro-electric power generation, agriculture, and human consumption in central Arizona. In this project, we are building a snow monitoring system for the Salt River Project (SRP), which supplies water and power to millions of customers in the Phoenix metropolitan area. We are using process-based hydrological models and artificial neural networks (ANNs) to generate information about both snow water equivalent (SWE) and snow cover. The snow-cover data is generated with ANNs that are applied to Landsat and MODIS satellite reflectance data. The SWE data is generated using a combination of gridded SWE estimates generated by process-based snow models and ANNs that account for variations in topography, forest cover, and solar radiation. The models are trained and evaluated with snow data from SNOTEL stations as well as from aerial LiDAR and field data that we collected this past winter in northern Arizona, as well as with similar data from other sites in the Southwest US. These snow data are produced in near-real time, and we have built a prototype decision support tool to deliver them to SRP. This tool is designed to provide daily-to annual operational monitoring of spatial and temporal changes in SWE and snow cover conditions over the entire Salt River Watershed (covering 17,000 km2), and features advanced web mapping capabilities and watershed analytics displayed as graphical data.

Use of Nutrient Balances in Comprehensive Watershed Water Quality Modeling of Chesapeake Bay

National Research Council Canada - National Science Library

Donigian, Anthony

1998-01-01

... state of-the-art watershed modeling capability that includes detailed soil process simulation for agricultural areas, linked to an instream water quality and nutrient model capable of representing...

Hydrodynamics and water quality models applied to Sepetiba Bay

Science.gov (United States)

Cunha, Cynara de L. da N.; Rosman, Paulo C. C.; Ferreira, Aldo Pacheco; Carlos do Nascimento Monteiro, Teófilo

2006-10-01

A coupled hydrodynamic and water quality model is used to simulate the pollution in Sepetiba Bay due to sewage effluent. Sepetiba Bay has a complicated geometry and bottom topography, and is located on the Brazilian coast near Rio de Janeiro. In the simulation, the dissolved oxygen (DO) concentration and biochemical oxygen demand (BOD) are used as indicators for the presence of organic matter in the body of water, and as parameters for evaluating the environmental pollution of the eastern part of Sepetiba Bay. Effluent sources in the model are taken from DO and BOD field measurements. The simulation results are consistent with field observations and demonstrate that the model has been correctly calibrated. The model is suitable for evaluating the environmental impact of sewage effluent on Sepetiba Bay from river inflows, assessing the feasibility of different treatment schemes, and developing specific monitoring activities. This approach has general applicability for environmental assessment of complicated coastal bays.

Flood impacts on a water distribution network

Science.gov (United States)

Arrighi, Chiara; Tarani, Fabio; Vicario, Enrico; Castelli, Fabio

2017-12-01

Floods cause damage to people, buildings and infrastructures. Water distribution systems are particularly exposed, since water treatment plants are often located next to the rivers. Failure of the system leads to both direct losses, for instance damage to equipment and pipework contamination, and indirect impact, since it may lead to service disruption and thus affect populations far from the event through the functional dependencies of the network. In this work, we present an analysis of direct and indirect damages on a drinking water supply system, considering the hazard of riverine flooding as well as the exposure and vulnerability of active system components. The method is based on interweaving, through a semi-automated GIS procedure, a flood model and an EPANET-based pipe network model with a pressure-driven demand approach, which is needed when modelling water distribution networks in highly off-design conditions. Impact measures are defined and estimated so as to quantify service outage and potential pipe contamination. The method is applied to the water supply system of the city of Florence, Italy, serving approximately 380 000 inhabitants. The evaluation of flood impact on the water distribution network is carried out for different events with assigned recurrence intervals. Vulnerable elements exposed to the flood are identified and analysed in order to estimate their residual functionality and to simulate failure scenarios. Results show that in the worst failure scenario (no residual functionality of the lifting station and a 500-year flood), 420 km of pipework would require disinfection with an estimated cost of EUR 21 million, which is about 0.5 % of the direct flood losses evaluated for buildings and contents. Moreover, if flood impacts on the water distribution network are considered, the population affected by the flood is up to 3 times the population directly flooded.

Propagation of crises in the virtual water trade network

Science.gov (United States)

Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2015-04-01

The international trade of agricultural goods is associated to the displacement of the water used to produce such goods and embedded in trade as a factor of production. Water virtually exchanged from producing to consuming countries, named virtual water, defines flows across an international network of 'virtual water trade' which enable the assessment of environmental forcings and implications of trade, such as global water savings or country dependencies on foreign water resources. Given the recent expansion of commodity (and virtual water) trade, in both displaced volumes and network structure, concerns have been raised about the exposure to crises of individuals and societies. In fact, if one country had to markedly decrease its export following a socio-economical or environmental crisis, such as a war or a drought, many -if not all- countries would be affected due to a cascade effect within the trade network. The present contribution proposes a mechanistic model describing the propagation of a local crisis into the virtual water trade network, accounting for the network structure and the virtual water balance of all countries. The model, built on data-based assumptions, is tested on the real case study of the Argentinean crisis in 2008-09, when the internal agricultural production (measured as virtual water volume) decreased by 26% and the virtual water export of Argentina dropped accordingly. Crisis propagation and effects on the virtual water trade are correctly captured, showing the way forward to investigations of crises impact and country vulnerability based on the results of the model proposed.

Simultaneous optimization of water and heat exchange networks

Energy Technology Data Exchange (ETDEWEB)

Chen, Zhiyou; Hou, Yanlong; Li, Xiaoduan; Wang, Jingtao [Tianjin University, Tianjin (China)

2014-04-15

This paper focuses on the simultaneous optimization of the heat-integrated water allocation networks. A mathematic model is established to illustrate the modified state-space representation of this problem. An easy logical method is employed to help identify the streams of hot or cold ones. In this model, the water exchange networks (WEN), heat exchange networks (HEN), and the interactions between the WEN and HEN combine together as one unity. Thus, the whole network can be solved at one time, which enhances the possibility to get a global optimal result. Examples from the literature and a PVC plant are analyzed to illustrate the accuracy and applicability of this method.

Research on Holographic Evaluation of Service Quality in Power Data Network

Science.gov (United States)

Wei, Chen; Jing, Tao; Ji, Yutong

2018-01-01

With the rapid development of power data network, the continuous development of the Power data application service system, more and more service systems are being put into operation. Following this, the higher requirements for network quality and service quality are raised, in the actual process for the network operation and maintenance. This paper describes the electricity network and data network services status. A holographic assessment model was presented to achieve a comprehensive intelligence assessment on the power data network and quality of service in the operation and maintenance on the power data network. This evaluation method avoids the problems caused by traditional means which performs a single assessment of network performance quality. This intelligent Evaluation method can improve the efficiency of network operation and maintenance guarantee the quality of real-time service in the power data network..

Using a Content Management System for Integrated Water Quantity, Quality and Instream Flows Modeling

Science.gov (United States)

Burgholzer, R.; Brogan, C. O.; Scott, D.; Keys, T.

2017-12-01

With increased population and water demand, in-stream flows can become depleted by consumptive uses and dilution of permitted discharges may be compromised. Reduced flows downstream of water withdrawals may increase the violation rate of bacterial concentrations from direct deposition by livestock and wildlife. Water storage reservoirs are constructed and operated to insure more stable supplies for consumptive demands and dilution flows, however their use comes at the cost of increased evaporative losses, potential for thermal pollution, interrupted fish migration, and reduced flooding events that are critical to maintain habitat and water quality. Due to this complex interrelationship between water quantity, quality and instream habitat comprehensive multi-disciplinary models must be developed to insure long-term sustainability of water resources and to avoid conflicts between drinking water, food and energy production, and aquatic biota. The Commonwealth of Virginia funded the expansion of the Chesapeake Bay Program Phase 5 model to cover the entire state, and has been using this model to evaluate water supply permit and planning since 2009. This integrated modeling system combines a content management system (Drupal and PHP) for model input data and leverages the modularity of HSPF with the custom segmentation and parameterization routines programmed by modelers working with the Chesapeake Bay Program. The model has been applied to over 30 Virginia Water Permits, instream flows and aquatic habitat models and a Virginias 30 year water supply demand projections. Future versions will leverage the Bay Model auto-calibration routines for adding small-scale water supply and TMDL models, utilize climate change scenarios, and integrate Virginia's reservoir management modules into the Chesapeake Bay watershed model, feeding projected demand and operational changes back up to EPA models to improve the realism of future Bay-wide simulations.

DESIGN AND ANALYSIS OF THE SNS CCL HOT MODEL WATER COOLING SYSTEM USING THE SINDA/FLUINT NETWORK MODELING TOOL

Energy Technology Data Exchange (ETDEWEB)

C. AMMERMAN; J. BERNARDIN

1999-11-01

This report presents results for design and analysis of the hot model water cooling system for the Spallation Neutron Source (SNS) coupled-cavity linac (CCL). The hot model, when completed, will include segments for both the CCL and coupled-cavity drift-tube linac (CCDTL). The scope of this report encompasses the modeling effort for the CCL portion of the hot model. This modeling effort employed the SINDA/FLUINT network modeling tool. This report begins with an introduction of the SNS hot model and network modeling using SINDA/FLUINT. Next, the development and operation of the SINDA/FLUINT model are discussed. Finally, the results of the SINDA/FLUINT modeling effort are presented and discussed.

Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts

Science.gov (United States)

Irby, Isaac David

Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts. First, a set of eight water quality models is used to establish a model mean and assess model skill. All models were found to exhibit similar skill in resolving dissolved oxygen concentrations as well as a number of dissolved oxygen-influencing variables (temperature, salinity, stratification, chlorophyll and nitrate) and the model mean exhibited the highest individual skill. The location of stratification within the water column was found to be a limiting factor in the models' ability to adequately simulate habitat compression resulting from low-oxygen conditions. Second, two of the previous models underwent the regulatory Chesapeake Bay pollution diet mandated by the Environmental Protection Agency. Both models exhibited a similar relative improvement in dissolved oxygen concentrations as a result of the reduction of nutrients stipulated in the pollution diet. A Confidence Index was developed to identify the locations of the Bay where the models are in agreement and disagreement regarding the impacts of the pollution diet. The models were least certain in the deep part of the upper main stem of the Bay and the uncertainty primarily stemmed from the post-processing methodology. Finally, by projecting the impacts of climate change in 2050 on the Bay, the potential success of the

Urban Hydrology and Water Quality Modeling - Resolution Modeling Comparison for Water Quantity and Quality

Science.gov (United States)

Fry, T. J.; Maxwell, R. M.

2014-12-01

Urbanization presents challenging water resource problems for communities worldwide. The hydromodifications associated with urbanization results in increased runoff rates and volumes and increased peak flows. These hydrologic changes can lead to increased erosion and stream destabilization, decreased evapotranspiration, decreased ground water recharge, increases in pollutant loading, and localized anthropogenic climate change or Urban Heat Islands. Stormwater represents a complex and dynamic component of the urban water cycle that requires careful mitigation. With the implementation of Phase II rules under the CWA, stormwater management is shifting from a drainage-efficiency focus to a natural systems focus. The natural system focus, referred to as Low Impact Development (LID), or Green Infrastructure, uses best management practices (BMPs) to reduce the impacts caused by urbanization hydromodification. Large-scale patterns of stormwater runoff from urban environments are complex and it is unclear what the large-scale impacts of green infrastructure are on the water cycle. High resolution physically based hydrologic models can be used to more accurately simulate the urban hydrologic cycle. These types of models tend to be more dynamic and allow for greater flexibility in evaluating and accounting for various hydrologic processes in the urban environment that may be lost with lower resolution conceptual models. We propose to evaluate the effectiveness of high resolution models to accurately represent and determine the urban hydrologic cycle with the overall goal of being able to accurately assess the impacts of LID BMPs in urban environments. We propose to complete a rigorous model intercomparison between ParFlow and FLO-2D. Both of these models can be scaled to higher resolutions, allow for rainfall to be spatially and temporally input, and solve the shallow water equations. Each model is different in the way it accounts for infiltration, initial abstraction losses

Estimation of contribution ratios of pollutant sources to a specific section based on an enhanced water quality model.

Science.gov (United States)

Cao, Bibo; Li, Chuan; Liu, Yan; Zhao, Yue; Sha, Jian; Wang, Yuqiu

2015-05-01

Because water quality monitoring sections or sites could reflect the water quality status of rivers, surface water quality management based on water quality monitoring sections or sites would be effective. For the purpose of improving water quality of rivers, quantifying the contribution ratios of pollutant resources to a specific section is necessary. Because physical and chemical processes of nutrient pollutants are complex in water bodies, it is difficult to quantitatively compute the contribution ratios. However, water quality models have proved to be effective tools to estimate surface water quality. In this project, an enhanced QUAL2Kw model with an added module was applied to the Xin'anjiang Watershed, to obtain water quality information along the river and to assess the contribution ratios of each pollutant source to a certain section (the Jiekou state-controlled section). Model validation indicated that the results were reliable. Then, contribution ratios were analyzed through the added module. Results show that among the pollutant sources, the Lianjiang tributary contributes the largest part of total nitrogen (50.43%), total phosphorus (45.60%), ammonia nitrogen (32.90%), nitrate (nitrite + nitrate) nitrogen (47.73%), and organic nitrogen (37.87%). Furthermore, contribution ratios in different reaches varied along the river. Compared with pollutant loads ratios of different sources in the watershed, an analysis of contribution ratios of pollutant sources for each specific section, which takes the localized chemical and physical processes into consideration, was more suitable for local-regional water quality management. In summary, this method of analyzing the contribution ratios of pollutant sources to a specific section based on the QUAL2Kw model was found to support the improvement of the local environment.

Application of water quality models to rivers in Johor

Science.gov (United States)

Chii, Puah Lih; Rahman, Haliza Abd.

2017-08-01

River pollution is one the most common hazard in many countries in the world, which includes Malaysia. Many rivers have been polluted because of the rapid growth in industrialization to support the country's growing population and economy. Domestic and industrial sewage, agricultural wastes have polluted the rivers and will affect the water quality. Based on the Malaysia Environment Quality Report 2007, the Department of Environment (DOE) has described that one of the major pollutants is Biochemical Oxygen Demand (BOD). Data from DOE in 2004, based on BOD, 18 river basins were classified polluted, 37 river basins were slightly polluted and 65 river basins were in clean condition. In this paper, two models are fitted the data of rivers in Johor state namely Streeter-Phelps model and nonlinear regression (NLR) model. The BOD concentration data for the two rivers in Johor state from year 1981 to year 1990 is analyzed. To estimate the parameters for the Streeter-Phelps model and NLR model, this study focuses on the weighted least squares and Gauss-Newton method respectively. Based on the value of Mean Square Error, NLR model is a better model compared to Streeter-Phelps model.

Bio-economic modeling of water quality improvements using a dynamic applied general equilibrium approach

NARCIS (Netherlands)

Dellink, R.; Brouwer, R.; Linderhof, V.G.M.; Stone, K.

2011-01-01

An integrated bio-economic model is developed to assess the impacts of pollution reduction policies on water quality and the economy. Emission levels of economic activities to water are determined based on existing environmental accounts. These emission levels are built into a dynamic economic model

Design and Optimization of Capacitated Supply Chain Networks Including Quality Measures

Directory of Open Access Journals (Sweden)

Krystel K. Castillo-Villar

2014-01-01

Full Text Available This paper presents (1 a novel capacitated model for supply chain network design which considers manufacturing, distribution, and quality costs (named SCND-COQ model and (2 five combinatorial optimization methods, based on nonlinear optimization, heuristic, and metaheuristic approaches, which are used to solve realistic instances of practical size. The SCND-COQ model is a mixed-integer nonlinear problem which can be used at a strategic planning level to design a supply chain network that maximizes the total profit subject to meeting an overall quality level of the final product at minimum costs. The SCND-COQ model computes the quality-related costs for the whole supply chain network considering the interdependencies among business entities. The effectiveness of the proposed solution approaches is shown using numerical experiments. These methods allow solving more realistic (capacitated supply chain network design problems including quality-related costs (inspections, rework, opportunity costs, and others within a reasonable computational time.

Refining models for quantifying the water quality benefits of improved animal management for use in water quality trading

Science.gov (United States)

Water quality trading (WQT) is a market-based approach that allows point sources of water pollution to meet their water quality obligations by purchasing credits from the reduced discharges from other point or nonpoint sources. Non-permitted animal operations and fields of permitted animal operatio...

MATHEMATICAL MODEL FOR THE SIMULATION OF WATER QUALITY IN RIVERS USING THE VENSIM PLE® SOFTWARE

Directory of Open Access Journals (Sweden)

Julio Cesar de S. I. Gonçalves

2013-06-01

Full Text Available Mathematical modeling of water quality in rivers is an important tool for the planning and management of water resources. Nevertheless, the available models frequently show structural and functional limitations. With the objective of reducing these drawbacks, a new model has been developed to simulate water quality in rivers under unsteady conditions; this model runs on the Vensim PLE® software and can also be operated for steady-state conditions. The following eighteen water quality variables can be simulated: DO, BODc, organic nitrogen (No, ammonia nitrogen (Na, nitrite (Ni, nitrate (Nn, organic and inorganic phosphorus (Fo and Fi, respectively, inorganic solids (Si, phytoplankton (F, zooplankton (Z, bottom algae (A, detritus (D, total coliforms (TC, alkalinity (Al., total inorganic carbon (TIC, pH, and temperature (T. Methane as well as nitrogen and phosphorus compounds that are present in the aerobic and anaerobic layers of the sediment can also be simulated. Several scenarios were generated for computational simulations produced using the new model by using the QUAL2K program, and, when possible, analytical solutions. The results obtained using the new model strongly supported the results from the QUAL family and analytical solutions.

Household's willingness to pay for heterogeneous attributes of drinking water quality and services improvement: an application of choice experiment

Science.gov (United States)

Dauda, Suleiman Alhaji; Yacob, Mohd Rusli; Radam, Alias

2015-09-01

The service of providing good quality of drinking water can greatly improve the lives of the community and maintain a normal health standard. For a large number of population in the world, specifically in the developing countries, the availability of safe water for daily sustenance is none. Damaturu is the capital of Yobe State, Nigeria. It hosts a population of more than two hundred thousand, yet only 45 % of the households are connected to the network of Yobe State Water Corporation's pipe borne water services; this has led people to source for water from any available source and thus, exposed them to the danger of contracting waterborne diseases. In order to address the problem, Yobe State Government has embarked on the construction of a water treatment plant with a capacity and facility to improve the water quality and connect the town with water services network. The objectives of this study are to assess the households' demand preferences of the heterogeneous water attributes in Damaturu, and to estimate their marginal willingness to pay, using mixed logit model in comparison with conditional logit model. A survey of 300 households randomly sampled indicated that higher education greatly influenced the households' WTP decisions. The most significant variable from both of the models is TWQ, which is MRS that rates the water quality from the level of satisfactory to very good. 219 % in simple model is CLM, while 126 % is for the interaction model. As for MLM, 685 % is for the simple model and 572 % is for the interaction model. Estimate of MLM has more explanatory powers than CLM. Essentially, this finding can help the government in designing cost-effective management and efficient tariff structure.

Modeling and Optimization for Management of Intermittent Water Supply

Science.gov (United States)

Lieb, A. M.; Wilkening, J.; Rycroft, C.

2014-12-01

In many urban areas, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. These consequences include degradation of distribution system components, compromised water quality, and inequitable water availability. The goal of this work is to model the important dynamics and identify operating conditions that mitigate certain negative effects of intermittent water supply. Specifically, we will look at controlling valve parameters occurring as boundary conditions in a network model of transient, transition flow through closed pipes. Gradient-based optimization will be used to find boundary values to minimize pressure gradients and ensure equitable water availability at system endpoints.

Conceptual design of a regional water quality screening model. [RFF; Reach; HANFORD; ARQUAL; SEAS; NASQUAN

Energy Technology Data Exchange (ETDEWEB)

Davis, M J

1981-01-01

This water quality assessment methodology is intended to predict concentrations at future times and to estimate the impacts on water quality of energy-related activities (including industrial boilers). Estimates of impacts on water quality at future times are based on incremental changes in pollutant inputs to the body water. Important features of the model are: use of measured concentrations to account for existing conditions; consideration of incremental changes in pollutant loads; emphasis on the energy sector and industrial boilers; analysis restricted to streams only; no attempt to fully account for pollutant behavior; and flexible design, so that future improvements can be incorporated. The basic approach is very similar to the one used by Argonne's ARQUAL model but will allow more complex pollutant behavior and more flexibility in use. (PSB)

Satellite remote sensing for modeling and monitoring of water quality in the Great Lakes

Science.gov (United States)

Coffield, S. R.; Crosson, W. L.; Al-Hamdan, M. Z.; Barik, M. G.

2017-12-01

Consistent and accurate monitoring of the Great Lakes is critical for protecting the freshwater ecosystems, quantifying the impacts of climate change, understanding harmful algal blooms, and safeguarding public health for the millions who rely on the Lakes for drinking water. While ground-based monitoring is often hampered by limited sampling resolution, satellite data provide surface reflectance measurements at much more complete spatial and temporal scales. In this study, we implemented NASA data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to build robust water quality models. We developed and validated models for chlorophyll-a, nitrogen, phosphorus, and turbidity based on combinations of the six MODIS Ocean Color bands (412, 443, 488, 531, 547, and 667nm) for 2003-2016. Second, we applied these models to quantify trends in water quality through time and in relation to changing land cover, runoff, and climate for six selected coastal areas in Lakes Michigan and Erie. We found strongest models for chlorophyll-a in Lake Huron (R2 = 0.75), nitrogen in Lake Ontario (R2=0.66), phosphorus in Lake Erie (R2=0.60), and turbidity in Lake Erie (R2=0.86). These offer improvements over previous efforts to model chlorophyll-a while adding nitrogen, phosphorus, and turbidity. Mapped water quality parameters showed high spatial variability, with nitrogen concentrated largely in Superior and coastal Michigan and high turbidity, phosphorus, and chlorophyll near urban and agricultural areas of Erie. Temporal analysis also showed concurrence of high runoff or precipitation and nitrogen in Lake Michigan offshore of wetlands, suggesting that water quality in these areas is sensitive to changes in climate.

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

Science.gov (United States)

Yang, X.; Jin, W.

2010-01-01

Nonpoint source pollution is the leading cause of the U.S.'s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO3NO2-N concentration and predict NO3NO2-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO3NO2-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO3NO2-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO3NO2-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution. ?? 2010 Elsevier Ltd.

Integrated Hydrologic Science and Environmental Engineering Observatory: CLEANER's Vision for the WATERS Network

Science.gov (United States)

Montgomery, J. L.; Minsker, B. S.; Schnoor, J.; Haas, C.; Bonner, J.; Driscoll, C.; Eschenbach, E.; Finholt, T.; Glass, J.; Harmon, T.; Johnson, J.; Krupnik, A.; Reible, D.; Sanderson, A.; Small, M.; van Briesen, J.

2006-05-01

With increasing population and urban development, societies grow more and more concerned over balancing the need to maintain adequate water supplies with that of ensuring the quality of surface and groundwater resources. For example, multiple stressors such as overfishing, runoff of nutrients from agricultural fields and confined animal feeding lots, and pathogens in urban stormwater can often overwhelm a single water body. Mitigating just one of these problems often depends on understanding how it relates to others and how stressors can vary in temporal and spatial scales. Researchers are now in a position to answer questions about multiscale, spatiotemporally distributed hydrologic and environmental phenomena through the use of remote and embedded networked sensing technologies. It is now possible for data streaming from sensor networks to be integrated by a rich cyberinfrastructure encompassing the innovative computing, visualization, and information archiving strategies needed to cope with the anticipated onslaught of data, and to turn that data around in the form of real-time water quantity and quality forecasting. Recognizing this potential, NSF awarded $2 million to a coalition of 12 institutions in July 2005 to establish the CLEANER Project Office (Collaborative Large-Scale Engineering Analysis Network for Environmental Research; http://cleaner.ncsa.uiuc.edu). Over the next two years the project office, in coordination with CUAHSI (Consortium of Universities for the Advancement of Hydrologic Science, Inc.; http://www.cuahsi.org), will work together to develop a plan for a WATer and Environmental Research Systems Network (WATERS Network), which is envisioned to be a collaborative scientific exploration and engineering analysis network, using high performance tools and infrastructure, to transform our scientific understanding of how water quantity, quality, and related earth system processes are affected by natural and human-induced changes to the environment

Some Remarks on the Calibration and Validation of Numerical Water Quality Models

DEFF Research Database (Denmark)

Larsen, Torben

1997-01-01

It is a general experience that complete deterministic water quality models for aquatic systems most often show surprisingly poor agreement when it comes to comparison between model estimates and measurement in the actual system. Often this discrepancy is misunderstood as a lack of complexity and...

Communicating water quality risk

International Nuclear Information System (INIS)

Scherer, C.W.

1990-01-01

Technology for detecting and understanding water quality problems and the impacts of activities on long-range groundwater quality has advanced considerably. In the past a technical solution was considered adequate but today one must consider a wide range of both technical and social factors in evaluating technical alternatives that are also acceptable social solutions. Policies developed and implemented with limited local participation generally are resisted and become ineffective if public cooperation is necessary for effective implementation. The public, the experts and the policymakers all must understand and appreciate the different perspectives present in risk policymaking. The typical model used to involve the public in policy decisions is a strategy described as the decide-announce-defend-approach. Much more acceptable to the public, but also more difficult to implement, is a strategy that calls for free flow of information within the community about the problem, policies and potential solutions. Communication about complex issues will be more successful if the communication is substantial; if it takes advantage of existing interpersonal networks and mass media; if it pays particular attention to existing audience knowledge, interest and behaviors; and if it clearly targets messages to various segments of the audience

Variations in statewide water quality of New Jersey streams, water years 1998-2009

Science.gov (United States)

Heckathorn, Heather A.; Deetz, Anna C.

2012-01-01

Statistical analyses were conducted for six water-quality constituents measured at 371 surface-water-quality stations during water years 1998-2009 to determine changes in concentrations over time. This study examined year-round concentrations of total dissolved solids, dissolved nitrite plus nitrate, dissolved phosphorus, total phosphorus, and total nitrogen; concentrations of dissolved chloride were measured only from January to March. All the water-quality data analyzed were collected by the New Jersey Department of Environmental Protection and the U.S. Geological Survey as part of the cooperative Ambient Surface-Water-Quality Monitoring Network. Stations were divided into groups according to the 1-year or 2-year period that the stations were part of the Ambient Surface-Water-Quality Monitoring Network. Data were obtained from the eight groups of Statewide Status stations for water years 1998, 1999, 2000, 2001-02, 2003-04, 2005-06, 2007-08, and 2009. The data from each group were compared to the data from each of the other groups and to baseline data obtained from Background stations unaffected by human activity that were sampled during the same time periods. The Kruskal-Wallis test was used to determine whether median concentrations of a selected water-quality constituent measured in a particular 1-year or 2-year group were different from those measured in other 1-year or 2-year groups. If the median concentrations were found to differ among years or groups of years, then Tukey's multiple comparison test on ranks was used to identify those years with different or equal concentrations of water-quality constituents. A significance level of 0.05 was selected to indicate significant changes in median concentrations of water-quality constituents. More variations in the median concentrations of water-quality constituents were observed at Statewide Status stations (randomly chosen stations scattered throughout the State of New Jersey) than at Background stations

3D Printing-Based Integrated Water Quality Sensing System

Directory of Open Access Journals (Sweden)

Muinul Banna

2017-06-01

Full Text Available The online and accurate monitoring of drinking water supply networks is critically in demand to rapidly detect the accidental or deliberate contamination of drinking water. At present, miniaturized water quality monitoring sensors developed in the laboratories are usually tested under ambient pressure and steady-state flow conditions; however, in Water Distribution Systems (WDS, both the pressure and the flowrate fluctuate. In this paper, an interface is designed and fabricated using additive manufacturing or 3D printing technology—material extrusion (Trade Name: fused deposition modeling, FDM and material jetting—to provide a conduit for miniaturized sensors for continuous online water quality monitoring. The interface is designed to meet two main criteria: low pressure at the inlet of the sensors and a low flowrate to minimize the water bled (i.e., leakage, despite varying pressure from WDS. To meet the above criteria, a two-dimensional computational fluid dynamics model was used to optimize the geometry of the channel. The 3D printed interface, with the embedded miniaturized pH and conductivity sensors, was then tested at different temperatures and flowrates. The results show that the response of the pH sensor is independent of the flowrate and temperature. As for the conductivity sensor, the flowrate and temperature affect only the readings at a very low conductivity (4 µS/cm and high flowrates (30 mL/min, and a very high conductivity (460 µS/cm, respectively.

Detection of water-quality contamination events based on multi-sensor fusion using an extented Dempster–Shafer method

International Nuclear Information System (INIS)

Hou, Dibo; He, Huimei; Huang, Pingjie; Zhang, Guangxin; Loaiciga, Hugo

2013-01-01

This study presents a method for detecting contamination events of sources of drinking water based on the Dempster–Shafer (D-S) evidence theory. The detection method has the purpose of protecting water supply systems against accidental and intentional contamination events. This purpose is achieved by first predicting future water-quality parameters using an autoregressive (AR) model. The AR model predicts future water-quality parameters using recent measurements of these parameters made with automated (on-line) water-quality sensors. Next, a probabilistic method assigns probabilities to the time series of residuals formed by comparing predicted water-quality parameters with threshold values. Finally, the D-S fusion method searches for anomalous probabilities of the residuals and uses the result of that search to determine whether the current water quality is normal (that is, free of pollution) or contaminated. The D-S fusion method is extended and improved in this paper by weighted averaging of water-contamination evidence and by the analysis of the persistence of anomalous probabilities of water-quality parameters. The extended D-S fusion method makes determinations that have a high probability of being correct concerning whether or not a source of drinking water has been contaminated. This paper's method for detecting water-contamination events was tested with water-quality time series from automated (on-line) water quality sensors. In addition, a small-scale, experimental, water-pipe network was tested to detect water-contamination events. The two tests demonstrated that the extended D-S fusion method achieves a low false alarm rate and high probabilities of detecting water contamination events. (paper)

An integrated system dynamics model developed for managing lake water quality at the watershed scale.

Science.gov (United States)

Liu, Hui; Benoit, Gaboury; Liu, Tao; Liu, Yong; Guo, Huaicheng

2015-05-15

A reliable system simulation to relate socioeconomic development with water environment and to comprehensively represent a watershed's dynamic features is important. In this study, after identifying lake watershed system processes, we developed a system dynamics modeling framework for managing lake water quality at the watershed scale. Two reinforcing loops (Development and Investment Promotion) and three balancing loops (Pollution, Resource Consumption, and Pollution Control) were constituted. Based on this work, we constructed Stock and Flow Diagrams that embedded a pollutant load model and a lake water quality model into a socioeconomic system dynamics model. The Dianchi Lake in Yunnan Province, China, which is the sixth largest and among the most severely polluted freshwater lakes in China, was employed as a case study to demonstrate the applicability of the model. Water quality parameters considered in the model included chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The business-as-usual (BAU) scenario and three alternative management scenarios on spatial adjustment of industries and population (S1), wastewater treatment capacity construction (S2), and structural adjustment of agriculture (S3), were simulated to assess the effectiveness of certain policies in improving water quality. Results showed that S2 is most effective scenario, and the COD, TN, and TP concentrations in Caohai in 2030 are 52.5, 10.9, and 0.8 mg/L, while those in Waihai are 9.6, 1.2, and 0.08 mg/L, with sustained development in the watershed. Thus, the model can help support the decision making required in development and environmental protection strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessing the effects of regional payment for watershed services program on water quality using an intervention analysis model.

Science.gov (United States)

Lu, Yan; He, Tian

2014-09-15

Much attention has been recently paid to ex-post assessments of socioeconomic and environmental benefits of payment for ecosystem services (PES) programs on poverty reduction, water quality, and forest protection. To evaluate the effects of a regional PES program on water quality, we selected chemical oxygen demand (COD) and ammonia-nitrogen (NH3-N) as indicators of water quality. Statistical methods and an intervention analysis model were employed to assess whether the PES program produced substantial changes in water quality at 10 water-quality sampling stations in the Shaying River watershed, China during 2006-2011. Statistical results from paired-sample t-tests and box plots of COD and NH3-N concentrations at the 10 stations showed that the PES program has played a positive role in improving water quality and reducing trans-boundary water pollution in the Shaying River watershed. Using the intervention analysis model, we quantitatively evaluated the effects of the intervention policy, i.e., the watershed PES program, on water quality at the 10 stations. The results suggest that this method could be used to assess the environmental benefits of watershed or water-related PES programs, such as improvements in water quality, seasonal flow regulation, erosion and sedimentation, and aquatic habitat. Copyright © 2014 Elsevier B.V. All rights reserved.

Forecasting Water Levels Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Shreenivas N. Londhe

2011-06-01

Full Text Available For all Ocean related activities it is necessary to predict the actual water levels as accurate as possible. The present work aims at predicting the water levels with a lead time of few hours to a day using the technique of artificial neural networks. Instead of using the previous and current values of observed water level time series directly as input and output the water level anomaly (difference between the observed water level and harmonically predicted tidal level is calculated for each hour and the ANN model is developed using this time series. The network predicted anomaly is then added to harmonic tidal level to predict the water levels. The exercise is carried out at six locations, two in The Gulf of Mexico, two in The Gulf of Maine and two in The Gulf of Alaska along the USA coastline. The ANN models performed reasonably well for all forecasting intervals at all the locations. The ANN models were also run in real time mode for a period of eight months. Considering the hurricane season in Gulf of Mexico the models were also tested particularly during hurricanes.

Proactive modeling of water quality impacts of extreme precipitation events in a drinking water reservoir.

Science.gov (United States)

Jeznach, Lillian C; Hagemann, Mark; Park, Mi-Hyun; Tobiason, John E

2017-10-01

Extreme precipitation events are of concern to managers of drinking water sources because these occurrences can affect both water supply quantity and quality. However, little is known about how these low probability events impact organic matter and nutrient loads to surface water sources and how these loads may impact raw water quality. This study describes a method for evaluating the sensitivity of a water body of interest from watershed input simulations under extreme precipitation events. An example application of the method is illustrated using the Wachusett Reservoir, an oligo-mesotrophic surface water reservoir in central Massachusetts and a major drinking water supply to metropolitan Boston. Extreme precipitation event simulations during the spring and summer resulted in total organic carbon, UV-254 (a surrogate measurement for reactive organic matter), and total algae concentrations at the drinking water intake that exceeded recorded maximums. Nutrient concentrations after storm events were less likely to exceed recorded historical maximums. For this particular reservoir, increasing inter-reservoir transfers of water with lower organic matter content after a large precipitation event has been shown in practice and in model simulations to decrease organic matter levels at the drinking water intake, therefore decreasing treatment associated oxidant demand, energy for UV disinfection, and the potential for formation of disinfection byproducts. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Contribution of GIS to Display and Analyze the Water Quality Data Collected by a Wireless Sensor Network: Case of Bouregreg Catchment, Morocco

Science.gov (United States)

Boubakri, S.; Rhinane, H.

2017-11-01

The monitoring of water quality is, in most cases, managed in the laboratory and not on real time bases. Besides this process being lengthy, it doesn't provide the required specifications to describe the evolution of the quality parameters that are of interest. This study presents the integration of Geographic Information Systems (GIS) with wireless sensor networks (WSN) aiming to create a system able to detect the parameters like temperature, salinity and conductivity in a Moroccan catchment scale and transmit information to the support station. This Information is displayed and evaluated in a GIS using maps and spatial dashboard to monitor the water quality in real time.

THE CONTRIBUTION OF GIS TO DISPLAY AND ANALYZE THE WATER QUALITY DATA COLLECTED BY A WIRELESS SENSOR NETWORK: CASE OF BOUREGREG CATCHMENT, MOROCCO

Directory of Open Access Journals (Sweden)

S. Boubakri

2017-11-01

Full Text Available The monitoring of water quality is, in most cases, managed in the laboratory and not on real time bases. Besides this process being lengthy, it doesn’t provide the required specifications to describe the evolution of the quality parameters that are of interest. This study presents the integration of Geographic Information Systems (GIS with wireless sensor networks (WSN aiming to create a system able to detect the parameters like temperature, salinity and conductivity in a Moroccan catchment scale and transmit information to the support station. This Information is displayed and evaluated in a GIS using maps and spatial dashboard to monitor the water quality in real time.

Water quality data for national-scale aquatic research: The Water Quality Portal

Science.gov (United States)

Read, Emily K.; Carr, Lindsay; DeCicco, Laura; Dugan, Hilary; Hanson, Paul C.; Hart, Julia A.; Kreft, James; Read, Jordan S.; Winslow, Luke

2017-01-01

Aquatic systems are critical to food, security, and society. But, water data are collected by hundreds of research groups and organizations, many of which use nonstandard or inconsistent data descriptions and dissemination, and disparities across different types of water observation systems represent a major challenge for freshwater research. To address this issue, the Water Quality Portal (WQP) was developed by the U.S. Environmental Protection Agency, the U.S. Geological Survey, and the National Water Quality Monitoring Council to be a single point of access for water quality data dating back more than a century. The WQP is the largest standardized water quality data set available at the time of this writing, with more than 290 million records from more than 2.7 million sites in groundwater, inland, and coastal waters. The number of data contributors, data consumers, and third-party application developers making use of the WQP is growing rapidly. Here we introduce the WQP, including an overview of data, the standardized data model, and data access and services; and we describe challenges and opportunities associated with using WQP data. We also demonstrate through an example the value of the WQP data by characterizing seasonal variation in lake water clarity for regions of the continental U.S. The code used to access, download, analyze, and display these WQP data as shown in the figures is included as supporting information.

Geospatial distribution modeling and determining suitability of groundwater quality for irrigation purpose using geospatial methods and water quality index (WQI) in Northern Ethiopia

Science.gov (United States)

Gidey, Amanuel

2018-06-01

Determining suitability and vulnerability of groundwater quality for irrigation use is a key alarm and first aid for careful management of groundwater resources to diminish the impacts on irrigation. This study was conducted to determine the overall suitability of groundwater quality for irrigation use and to generate their spatial distribution maps in Elala catchment, Northern Ethiopia. Thirty-nine groundwater samples were collected to analyze and map the water quality variables. Atomic absorption spectrophotometer, ultraviolet spectrophotometer, titration and calculation methods were used for laboratory groundwater quality analysis. Arc GIS, geospatial analysis tools, semivariogram model types and interpolation methods were used to generate geospatial distribution maps. Twelve and eight water quality variables were used to produce weighted overlay and irrigation water quality index models, respectively. Root-mean-square error, mean square error, absolute square error, mean error, root-mean-square standardized error, measured values versus predicted values were used for cross-validation. The overall weighted overlay model result showed that 146 km2 areas are highly suitable, 135 km2 moderately suitable and 60 km2 area unsuitable for irrigation use. The result of irrigation water quality index confirms 10.26% with no restriction, 23.08% with low restriction, 20.51% with moderate restriction, 15.38% with high restriction and 30.76% with the severe restriction for irrigation use. GIS and irrigation water quality index are better methods for irrigation water resources management to achieve a full yield irrigation production to improve food security and to sustain it for a long period, to avoid the possibility of increasing environmental problems for the future generation.

Water Distribution Network Modelling of a Small Community using ...

African Journals Online (AJOL)

... of a small community (Sakwa) water distribution network in North Eastern geopolitical region of Nigeria using WaterCAD simulator. The analysis included a review of pressures, velocities and head loss gradients under steady state average day demand, maximum day demand conditions, and fire flow under maximum day ...

Voice Quality Estimation in Wireless Networks

Directory of Open Access Journals (Sweden)

Petr Zach

2015-01-01

Full Text Available This article deals with the impact of Wireless (Wi-Fi networks on the perceived quality of voice services. The Quality of Service (QoS metrics must be monitored in the computer network during the voice data transmission to ensure proper voice service quality the end-user has paid for, especially in the wireless networks. In addition to the QoS, research area called Quality of Experience (QoE provides metrics and methods for quality evaluation from the end-user’s perspective. This article focuses on a QoE estimation of Voice over IP (VoIP calls in the wireless networks using network simulator. Results contribute to voice quality estimation based on characteristics of the wireless network and location of a wireless client.

ECONOMETRIC MODELLING OD THE INFLUENCE OF LAKE WATER QUALITY CHANGES ON FISHING ECONOMY

Directory of Open Access Journals (Sweden)

Marek Antoni Ramczyk

2017-06-01

Full Text Available The econometric model can be a precise instrument for the analysis of the impact of the natural environment's degradation on fishing economy. This paper aims at analysing the influence of the water quality changes in lake Charzykowskie on the fishing economy. This dissertation present the results of a research on the lake water pollution's impact on fishing economy. The economic-ecological models have been constructed, explaining the changes of economic effects of the lake fishery in the conditions of an increasing water pollution in the epilimnion on the example of the catch of Rutilus rutilus, Abramis brama, Blicca bjoerkna, Coregonus albula, Coregonus lavaretus, Anguilla anguilla and Esox lucius in Lake Charzykowskie. Performed empirical research looked into the influence of the environmental factors on the size of fish catch. Calculations and analysis show clearly that though the habitat factors do influence the catch size of each studied fish species, they do it with different intensity and in various combinations. Both lake water quality and climate factors changes cause measurable effects on fishing industry of lake Charzykowskie. Among all the examined Rutilus rutilus, Abramis brama and Blicca bjoerkna the highest environmental requirements concerning water quality has Blicca bjoerkna. Whereas Abramis brama has slightly higher environmental requirements than Rutilus rutilus. Empirical calculations showed as well that Coregonus albula and Coregonus lavaretus have considerably higher water cleanness requirements than Rutilus rutilus, Abramis brama and Blicca bjoerkna. While when talking about Rutilus rutilus, Abramis brama and Blicca bjoerkna, most water characteristics still rather stimulated these species' development, when it comes to Coregonus albula and Coregonus lavaretus, in general they suppressed their development. The model has also proved quite high habitat requierements of Anquilla anquilla and correctness of the thesis that

Impact of Water Quality on Chlorine Demand of Corroding Copper

Science.gov (United States)

Copper is the most widely used material in drinking water premise plumbing systems. In buildings such as hospitals, large and complicated plumbing networks make it difficult to maintain good water quality. Sustaining safe disinfectant residuals throughout a building to protect ag...

Quantifying tap-to-household water quality deterioration in urban communities in Vellore, India: The impact of spatial assumptions.

Science.gov (United States)

Alarcon Falconi, Tania M; Kulinkina, Alexandra V; Mohan, Venkata Raghava; Francis, Mark R; Kattula, Deepthi; Sarkar, Rajiv; Ward, Honorine; Kang, Gagandeep; Balraj, Vinohar; Naumova, Elena N

2017-01-01

Municipal water sources in India have been found to be highly contaminated, with further water quality deterioration occurring during household storage. Quantifying water quality deterioration requires knowledge about the exact source tap and length of water storage at the household, which is not usually known. This study presents a methodology to link source and household stored water, and explores the effects of spatial assumptions on the association between tap-to-household water quality deterioration and enteric infections in two semi-urban slums of Vellore, India. To determine a possible water source for each household sample, we paired household and tap samples collected on the same day using three spatial approaches implemented in GIS: minimum Euclidean distance; minimum network distance; and inverse network-distance weighted average. Logistic and Poisson regression models were used to determine associations between water quality deterioration and household-level characteristics, and between diarrheal cases and water quality deterioration. On average, 60% of households had higher fecal coliform concentrations in household samples than at source taps. Only the weighted average approach detected a higher risk of water quality deterioration for households that do not purify water and that have animals in the home (RR=1.50 [1.03, 2.18], p=0.033); and showed that households with water quality deterioration were more likely to report diarrheal cases (OR=3.08 [1.21, 8.18], p=0.02). Studies to assess contamination between source and household are rare due to methodological challenges and high costs associated with collecting paired samples. Our study demonstrated it is possible to derive useful spatial links between samples post hoc; and that the pairing approach affects the conclusions related to associations between enteric infections and water quality deterioration. Copyright © 2016 Elsevier GmbH. All rights reserved.

Water-Quality Data

Science.gov (United States)

... Water Quality? [1.7MB PDF] Past featured science... Water Quality Data Today's Water Conditions Get continuous real- ... list of USGS water-quality data resources . USGS Water Science Areas Water Resources Groundwater Surface Water Water ...

Evaluating Water Supply and Water Quality Management Options for Las Vegas Valley

Science.gov (United States)

Ahmad, S.

2007-05-01

The ever increasing population in Las Vegas is generating huge demand for water supply on one hand and need for infrastructure to collect and treat the wastewater on the other hand. Current plans to address water demand include importing water from Muddy and Virgin Rivers and northern counties, desalination of seawater with trade- payoff in California, water banking in Arizona and California, and more intense water conservation efforts in the Las Vegas Valley (LVV). Water and wastewater in the LVV are intrinsically related because treated wastewater effluent is returned back to Lake Mead, the drinking water source for the Valley, to get a return credit thereby augmenting Nevada's water allocation from the Colorado River. The return of treated wastewater however, is a major contributor of nutrients and other yet unregulated pollutants to Lake Mead. Parameters that influence the quantity of water include growth of permanent and transient population (i.e., tourists), indoor and outdoor water use, wastewater generation, wastewater reuse, water conservation, and return flow credits. The water quality of Lake Mead and the Colorado River is affected by the level of treatment of wastewater, urban runoff, groundwater seepage, and a few industrial inputs. We developed an integrated simulation model, using system dynamics modeling approach, to account for both water quantity and quality in the LVV. The model captures the interrelationships among many variables that influence both, water quantity and water quality. The model provides a valuable tool for understanding past, present and future pathways of water and its constituents in the LVV. The model is calibrated and validated using the available data on water quantity (flows at water and wastewater treatment facilities and return water credit flow rates) and water quality parameters (TDS and phosphorus concentrations). We used the model to explore important questions: a)What would be the effect of the water transported from

Modelling the impact of Water Sensitive Urban Design technologies on the urban water cycle

DEFF Research Database (Denmark)

Locatelli, Luca

Alternative stormwater management approaches for urban developments, also called Water Sensitive Urban Design (WSUD), are increasingly being adopted with the aims of providing flood control, flow management, water quality improvements and opportunities to harvest stormwater for non-potable uses....... To model the interaction of infiltration based WSUDs with groundwater. 4. To assess a new combination of different WSUD techniques for improved stormwater management. 5. To model the impact of a widespread implementation of multiple soakaway systems at the catchment scale. 6. Test the models by simulating...... the hydrological performance of single devices relevant for urban drainage applications. Moreover, the coupling of soakaway and detention storages is also modeled to analyze the benefits of combining different local stormwater management systems. These models are then integrated into urban drainage network models...