WorldWideScience

Sample records for network water-quality models

  1. Water quality modelling and optimisation of wastewater treatment network using mixed integer programming

    CSIR Research Space (South Africa)

    Mahlathi, Christopher

    2016-10-01

    Full Text Available Instream water quality management encompasses field monitoring and utilisation of mathematical models. These models can be coupled with optimisation techniques to determine more efficient water quality management alternatives. Among these activities...

  2. Water quality modeling in the dead end sections of drinking water distribution networks.

    Science.gov (United States)

    Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

    2016-02-01

    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 water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated

  3. Modelling microbiological water quality in the Seine river drainage network: past, present and future situations

    Directory of Open Access Journals (Sweden)

    P. Servais

    2007-09-01

    Full Text Available The Seine river watershed is characterized by a high population density and intense agricultural activities. Data show low microbiological water quality in the main rivers (Seine, Marne, Oise of the watershed. Today, there is an increasing pressure from different social groups to restore microbiological water quality in order to both increase the safety of drinking water production and to restore the possible use of these rivers for bathing and rowing activities, as they were in the past. A model, appended to the hydro-ecological SENEQUE/Riverstrahler model describing the functioning of large river systems, was developed to describe the dynamics of faecal coliforms (FC, the most usual faecal contamination indicator. The model is able to calculate the distribution of FC concentrations in the whole drainage network resulting from land use and wastewater management in the watershed. The model was validated by comparing calculated FC concentrations with available field data for some well-documented situations in different river stretches of the Seine drainage network. Once validated, the model was used to test various predictive scenarios, as, for example, the impact of the modifications in wastewater treatment planned at the 2012 horizon in the Seine watershed in the scope of the implementation of the european water framework directive. The model was also used to investigate past situations. In particular, the variations of the microbiological water quality in the Parisian area due to population increase and modifications in wastewater management were estimated over the last century. It was shown that the present standards for bathing and other aquatic recreational activities are not met in the large tributaries upstream from Paris since the middle of the 1950's, and at least since the middle of the XIXth century in the main branch of the Seine river downstream from Paris. Efforts carried out for improving urban wastewater treatment in terms

  4. Progress and lessons learned from water-quality monitoring networks

    Science.gov (United States)

    Myers, Donna N.; Ludtke, Amy S.

    2017-01-01

    Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

  5. 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....

  6. A water quality index model using stepwise regression and neural networks models for the Piabanha River basin in Rio de Janeiro, Brazil

    Science.gov (United States)

    Villas Boas, M. D.; Olivera, F.; Azevedo, J. S.

    2013-12-01

    The evaluation of water quality through 'indexes' is widely used in environmental sciences. There are a number of methods available for calculating water quality indexes (WQI), usually based on site-specific parameters. In Brazil, WQI were initially used in the 1970s and were adapted from the methodology developed in association with the National Science Foundation (Brown et al, 1970). Specifically, the WQI 'IQA/SCQA', developed by the Institute of Water Management of Minas Gerais (IGAM), is estimated based on nine parameters: Temperature Range, Biochemical Oxygen Demand, Fecal Coliforms, Nitrate, Phosphate, Turbidity, Dissolved Oxygen, pH and Electrical Conductivity. The goal of this study was to develop a model for calculating the IQA/SCQA, for the Piabanha River basin in the State of Rio de Janeiro (Brazil), using only the parameters measurable by a Multiparameter Water Quality Sonde (MWQS) available in the study area. These parameters are: Dissolved Oxygen, pH and Electrical Conductivity. The use of this model will allow to further the water quality monitoring network in the basin, without requiring significant increases of resources. The water quality measurement with MWQS is less expensive than the laboratory analysis required for the other parameters. The water quality data used in the study were obtained by the Geological Survey of Brazil in partnership with other public institutions (i.e. universities and environmental institutes) as part of the project "Integrated Studies in Experimental and Representative Watersheds". Two models were developed to correlate the values of the three measured parameters and the IQA/SCQA values calculated based on all nine parameters. The results were evaluated according to the following validation statistics: coefficient of determination (R2), Root Mean Square Error (RMSE), Akaike information criterion (AIC) and Final Prediction Error (FPE). The first model was a linear stepwise regression between three independent variables

  7. 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.

  8. A software sensor model based on hybrid fuzzy neural network for rapid estimation water quality in Guangzhou section of Pearl River, China.

    Science.gov (United States)

    Zhou, Chunshan; Zhang, Chao; Tian, Di; Wang, Ke; Huang, Mingzhi; Liu, Yanbiao

    2018-01-02

    In order to manage water resources, a software sensor model was designed to estimate water quality using a hybrid fuzzy neural network (FNN) in Guangzhou section of Pearl River, China. The software sensor system was composed of data storage module, fuzzy decision-making module, neural network module and fuzzy reasoning generator module. Fuzzy subtractive clustering was employed to capture the character of model, and optimize network architecture for enhancing network performance. The results indicate that, on basis of available on-line measured variables, the software sensor model can accurately predict water quality according to the relationship between chemical oxygen demand (COD) and dissolved oxygen (DO), pH and NH 4 + -N. Owing to its ability in recognizing time series patterns and non-linear characteristics, the software sensor-based FNN is obviously superior to the traditional neural network model, and its R (correlation coefficient), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 0.8931, 10.9051 and 0.4634, respectively.

  9. 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

  10. 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...

  11. 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.

  12. 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...

  13. 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 ...

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. Topological clustering as a tool for planning water quality monitoring in water distribution networks

    DEFF Research Database (Denmark)

    Kirstein, Jonas Kjeld; Albrechtsen, Hans-Jørgen; Rygaard, Martin

    2015-01-01

    ) identify steady clusters for a part of the network where an actual contamination has occurred; (2) analyze this event by the use of mesh diagrams; and (3) analyze the use of mesh diagrams as a decision support tool for planning water quality monitoring. Initially, the network model was divided...... into strongly and weakly connected clusters for selected time periods and mesh diagrams were used for analysing cluster connections in the Nørrebro district. Here, areas of particular interest for water quality monitoring were identified by including user-information about consumption rates and consumers...... particular sensitive towards water quality deterioration. The analysis revealed sampling locations within steady clusters, which increased samples' comparability over time. Furthermore, the method provided a simplified overview of water movement in complex distribution networks, and could assist...

  19. 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...

  20. 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.

  1. PREDICTION OF WATER QUALITY INDEX USING BACK PROPAGATION NETWORK ALGORITHM. CASE STUDY: GOMBAK RIVER

    Directory of Open Access Journals (Sweden)

    FARIS GORASHI

    2012-08-01

    Full Text Available The aim of this study is to enable prediction of water quality parameters with conjunction to land use attributes and to find a low-end alternative for water quality monitoring techniques, which are typically expensive and tedious. It also aims to ensure sustainable development, which is essentially has effects on water quality. The research approach followed in this study is via using artificial neural networks, and geographical information system to provide a reliable prediction model. Back propagation network algorithm was used for the purpose of this study. The proposed approach minimized most of anomalies associated with prediction methods and provided water quality prediction with precision. The study used 5 hidden nodes in this network. The network was optimized to complete 23145 cycles before it reaches the best error of 0.65. Stations 18 had shown the greatest fluctuation among the three stations as it reflects an area of on-going rapid development of Gombak river watershed. The results had shown a very close prediction with best error of 0.67 in a sensitivity test that was carried afterwards.

  2. 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...

  3. 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.

  4. 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.

  5. 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

  6. Successful integration efforts in water quality from the integrated Ocean Observing System Regional Associations and the National Water Quality Monitoring Network

    Science.gov (United States)

    Ragsdale, R.; Vowinkel, E.; Porter, D.; Hamilton, P.; Morrison, R.; Kohut, J.; Connell, B.; Kelsey, H.; Trowbridge, P.

    2011-01-01

    The Integrated Ocean Observing System (IOOS??) Regional Associations and Interagency Partners hosted a water quality workshop in January 2010 to discuss issues of nutrient enrichment and dissolved oxygen depletion (hypoxia), harmful algal blooms (HABs), and beach water quality. In 2007, the National Water Quality Monitoring Council piloted demonstration projects as part of the National Water Quality Monitoring Network (Network) for U.S. Coastal Waters and their Tributaries in three IOOS Regional Associations, and these projects are ongoing. Examples of integrated science-based solutions to water quality issues of major concern from the IOOS regions and Network demonstration projects are explored in this article. These examples illustrate instances where management decisions have benefited from decision-support tools that make use of interoperable data. Gaps, challenges, and outcomes are identified, and a proposal is made for future work toward a multiregional water quality project for beach water quality.

  7. 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.

  8. 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

  9. 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.

  10. Use of neural networks for monitoring surface water quality changes in a neotropical urban stream.

    Science.gov (United States)

    da Costa, Andréa Oliveira Souza; Silva, Priscila Ferreira; Sabará, Millôr Godoy; da Costa, Esly Ferreira

    2009-08-01

    This paper reports the using of neural networks for water quality analysis in a tropical urban stream before (2002) and after sewerage building and the completion of point-source control-based sanitation program (2003). Mathematical modeling divided water quality data in two categories: (a) input of some in situ water quality variables (temperature, pH, O2 concentration, O2 saturation and electrical conductivity) and (b) water chemical composition (N-NO2(-); N-NO3(-); N-NH4(+) Total-N; P-PO4(3-); K+; Ca2+; Mg+2; Cu2+; Zn2+ and Fe+3) as the output from tested models. Stream water data come from fortnightly sampling in five points along the Ipanema stream (Southeast Brazil, Minas Gerais state) plus two points downstream and upstream Ipanema discharge into Doce River. Once the best models are consistent with variables behavior we suggest that neural networking shows potential as a methodology to enhance guidelines for urban streams restoration, conservation and management.

  11. 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.

  12. 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.

  13. Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

    Science.gov (United States)

    Oliker, Nurit; Ostfeld, Avi

    2015-09-01

    Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. 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

  15. 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

  16. 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....

  17. 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.

  18. Water quality monitoring for high-priority water bodies in the Sonoran Desert network

    Science.gov (United States)

    Terry W. Sprouse; Robert M. Emanuel; Sara A. Strorrer

    2005-01-01

    This paper describes a network monitoring program for “high priority” water bodies in the Sonoran Desert Network of the National Park Service. Protocols were developed for monitoring selected waters for ten of the eleven parks in the Network. Park and network staff assisted in identifying potential locations of testing sites, local priorities, and how water quality...

  19. 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...

  20. 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

  1. 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.

  2. Geostatistical prediction of microbial water quality throughout a stream network using meteorology, land cover, and spatiotemporal autocorrelation.

    Science.gov (United States)

    Holcomb, David Andrew; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R

    2018-06-11

    Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modelled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was >90%, 10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

  3. 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

  4. 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.

  5. Application of a Weighted Regression Model for Reporting Nutrient and Sediment Concentrations, Fluxes, and Trends in Concentration and Flux for the Chesapeake Bay Nontidal Water-Quality Monitoring Network, Results Through Water Year 2012

    Science.gov (United States)

    Chanat, Jeffrey G.; Moyer, Douglas L.; Blomquist, Joel D.; Hyer, Kenneth E.; Langland, Michael J.

    2016-01-13

    In the Chesapeake Bay watershed, estimated fluxes of nutrients and sediment from the bay’s nontidal tributaries into the estuary are the foundation of decision making to meet reductions prescribed by the Chesapeake Bay Total Maximum Daily Load (TMDL) and are often the basis for refining scientific understanding of the watershed-scale processes that influence the delivery of these constituents to the bay. Two regression-based flux and trend estimation models, ESTIMATOR and Weighted Regressions on Time, Discharge, and Season (WRTDS), were compared using data from 80 watersheds in the Chesapeake Bay Nontidal Water-Quality Monitoring Network (CBNTN). The watersheds range in size from 62 to 70,189 square kilometers and record lengths range from 6 to 28 years. ESTIMATOR is a constant-parameter model that estimates trends only in concentration; WRTDS uses variable parameters estimated with weighted regression, and estimates trends in both concentration and flux. WRTDS had greater explanatory power than ESTIMATOR, with the greatest degree of improvement evident for records longer than 25 years (30 stations; improvement in median model R2= 0.06 for total nitrogen, 0.08 for total phosphorus, and 0.05 for sediment) and the least degree of improvement for records of less than 10 years, for which the two models performed nearly equally. Flux bias statistics were comparable or lower (more favorable) for WRTDS for any record length; for 30 stations with records longer than 25 years, the greatest degree of improvement was evident for sediment (decrease of 0.17 in median statistic) and total phosphorus (decrease of 0.05). The overall between-station pattern in concentration trend direction and magnitude for all constituents was roughly similar for both models. A detailed case study revealed that trends in concentration estimated by WRTDS can operationally be viewed as a less-constrained equivalent to trends in concentration estimated by ESTIMATOR. Estimates of annual mean flow

  6. 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.

  7. 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)

  8. The national stream quality accounting network: A flux-basedapproach to monitoring the water quality of large rivers

    Science.gov (United States)

    Hooper, R.P.; Aulenbach, Brent T.; Kelly, V.J.

    2001-01-01

    Estimating the annual mass flux at a network of fixed stations is one approach to characterizing water quality of large rivers. The interpretive context provided by annual flux includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean. Since 1995, the US Geological Survey's National Stream Quality Accounting Network (NASQAN) has employed this approach at a network of 39 stations in four of the largest river basins of the USA: The Mississippi, the Columbia, the Colorado and the Rio Grande. In this paper, the design of NASQAN is described and its effectiveness at characterizing the water quality of these rivers is evaluated using data from the first 3 years of operation. A broad range of constituents was measured by NASQAN, including trace organic and inorganic chemicals, major ions, sediment and nutrients. Where possible, a regression model relating concentration to discharge and season was used to interpolate between chemical observations for flux estimation. For water-quality network design, the most important finding from NASQAN was the importance of having a specific objective (that is, estimating annual mass flux) and, from that, an explicitly stated data analysis strategy, namely the use of regression models to interpolate between observations. The use of such models aided in the design of sampling strategy and provided a context for data review. The regression models essentially form null hypotheses for concentration variation that can be evaluated by the observed data. The feedback between network operation and data collection established by the hypothesis tests places the water-quality network on a firm scientific footing.

  9. 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.

  10. 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...

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  13. 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...

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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

  20. 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...

  1. 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.

  2. 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.

  3. 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

  4. CHARACTERIZING PIPE WALL DEMAND: IMPLICATIONS FOR WATER QUALITY MODELING

    Science.gov (United States)

    It has become generally accepted that water quality can deteriorate in a distribution system through reactions in the bulk phase and/or at the pipe wall. These reactions may be physical, chemical or microbiological in nature. Perhaps one of the most serious aspects of water qua...

  5. 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.

  6. Inverse modeling with RZWQM2 to predict water quality

    Science.gov (United States)

    Nolan, Bernard T.; Malone, Robert W.; Ma, Liwang; Green, Christopher T.; Fienen, Michael N.; Jaynes, Dan B.

    2011-01-01

    This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST in both parameter estimation and predictive analysis modes. The goal of parameter estimation is to identify a unique set of parameters that minimize a weighted least squares objective function, and the goal of predictive analysis is to construct a nonlinear confidence interval for a prediction of interest by finding a set of parameters that maximizes or minimizes the prediction while maintaining the model in a calibrated state. We also describe PEST utilities (PAR2PAR, TSPROC) for maintaining ordered relations among model parameters (e.g., soil root growth factor) and for post-processing of RZWQM2 outputs representing different cropping practices at the Iowa site. Inverse modeling provided reasonable fits to observed water and N fluxes and directly benefitted the modeling through: (i) simultaneous adjustment of multiple parameters versus one-at-a-time adjustment in manual approaches; (ii) clear indication by convergence criteria of when calibration is complete; (iii) straightforward detection of nonunique and insensitive parameters, which can affect the stability of PEST and RZWQM2; and (iv) generation of confidence intervals for uncertainty analysis of parameters and model predictions. Composite scaled sensitivities, which

  7. 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

  8. 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.

  9. 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...

  10. 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.

  11. 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...

  12. 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...

  13. Quality-control design for surface-water sampling in the National Water-Quality Network

    Science.gov (United States)

    Riskin, Melissa L.; Reutter, David C.; Martin, Jeffrey D.; Mueller, David K.

    2018-04-10

    The data-quality objectives for samples collected at surface-water sites in the National Water-Quality Network include estimating the extent to which contamination, matrix effects, and measurement variability affect interpretation of environmental conditions. Quality-control samples provide insight into how well the samples collected at surface-water sites represent the true environmental conditions. Quality-control samples used in this program include field blanks, replicates, and field matrix spikes. This report describes the design for collection of these quality-control samples and the data management needed to properly identify these samples in the U.S. Geological Survey’s national database.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Applying a water quality index model to assess the water quality of the major rivers in the Kathmandu Valley, Nepal.

    Science.gov (United States)

    Regmi, Ram Krishna; Mishra, Binaya Kumar; Masago, Yoshifumi; Luo, Pingping; Toyozumi-Kojima, Asako; Jalilov, Shokhrukh-Mirzo

    2017-08-01

    Human activities during recent decades have led to increased degradation of the river water environment in South Asia. This degradation has led to concerns for the populations of the major cities of Nepal, including those of the Kathmandu Valley. The deterioration of the rivers in the valley is directly linked to the prevalence of poor sanitary conditions, as well as the presence of industries that discharge their effluents into the river. This study aims to investigate the water quality aspect for the aquatic ecosystems and recreation of the major rivers in the Kathmandu Valley using the Canadian Council of Ministers of the Environment water quality index (CCME WQI). Ten physicochemical parameters were used to determine the CCME WQI at 20 different sampling locations. Analysis of the data indicated that the water quality in rural areas ranges from excellent to good, whereas in denser settlements and core urban areas, the water quality is poor. The study results are expected to provide policy-makers with valuable information related to the use of river water by local people in the study area.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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).

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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. ...

  17. 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.

  18. 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

  19. Using genetic algorithms to calibrate a water quality model.

    Science.gov (United States)

    Liu, Shuming; Butler, David; Brazier, Richard; Heathwaite, Louise; Khu, Soon-Thiam

    2007-03-15

    With the increasing concern over the impact of diffuse pollution on water bodies, many diffuse pollution models have been developed in the last two decades. A common obstacle in using such models is how to determine the values of the model parameters. This is especially true when a model has a large number of parameters, which makes a full range of calibration expensive in terms of computing time. Compared with conventional optimisation approaches, soft computing techniques often have a faster convergence speed and are more efficient for global optimum searches. This paper presents an attempt to calibrate a diffuse pollution model using a genetic algorithm (GA). Designed to simulate the export of phosphorus from diffuse sources (agricultural land) and point sources (human), the Phosphorus Indicators Tool (PIT) version 1.1, on which this paper is based, consisted of 78 parameters. Previous studies have indicated the difficulty of full range model calibration due to the number of parameters involved. In this paper, a GA was employed to carry out the model calibration in which all parameters were involved. A sensitivity analysis was also performed to investigate the impact of operators in the GA on its effectiveness in optimum searching. The calibration yielded satisfactory results and required reasonable computing time. The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated. The annual P loss was predicted as 4.4 kg P/ha/yr, which showed a good fitness to the observed value.

  20. 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

  1. 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.

  2. 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

  3. 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)

  4. Uncertainty propagation in urban hydrology water quality modelling

    NARCIS (Netherlands)

    Torres Matallana, Arturo; Leopold, U.; Heuvelink, G.B.M.

    2016-01-01

    Uncertainty is often ignored in urban hydrology modelling. Engineering practice typically ignores uncertainties and uncertainty propagation. This can have large impacts, such as the wrong dimensioning of urban drainage systems and the inaccurate estimation of pollution in the environment caused

  5. 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.

  6. 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...

  7. 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

  8. 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

  9. 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

  10. 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...

  11. 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.

  12. 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

  13. 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.

  14. Solid Waste and Water Quality Management Models for Sagarmatha National Park and Buffer Zone, Nepal.

    NARCIS (Netherlands)

    Manfredi, Emanuela Chiara; Flury, Bastian; Viviano, Gaetano; Thakuri, Sudeep; Khanal, Sanjay Nath; Jha, Pramod Kumar; Maskey, Ramesh Kumar; Kayastha, Rijan Bhakta; Kafle, Kumud Raj; Bhochhibhoya, Silu; Ghimire, Narayan Prasad; Shrestha, Bharat Babu; Chaudhary, Gyanendra; Giannino, Francesco; Carteni, Fabrizio; Mazzoleni, Stefano; Salerno, Franco

    2010-01-01

    The problem of supporting decision- and policy-makers in managing issues related to solid waste and water quality was addressed within the context of a participatory modeling framework in the Sagarmatha National Park and Buffer Zone in Nepal. We present the main findings of management-oriented

  15. Modelling receiving water quality responses to brackishwater shrimp aquaculture farm effluents

    International Nuclear Information System (INIS)

    Roy Chaudhury, R.K.; Ramana Murty, V.; Ravindran, M.

    1999-01-01

    The objective was to perform a waste load allocation and determine the extent of aquaculture that the creeks can sustain, by meeting the water quality criteria for both the creek ecosystem and pond culture. Based on these results, similar assessments may be performed for other sites supporting large scale aquaculture activities. This paper introduces the sampling program and modelling methodology of the study

  16. 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 ...

  17. Practical Application of Sea Water Quality Mathematical Model for the Black Sea Coast of Sochi

    Directory of Open Access Journals (Sweden)

    Oleg A. Burunin

    2013-01-01

    Full Text Available The article deals with an application of the developed model of the sea water quality for forecasting of coastal waters indicators change in the artificial coastal water areas of Sochi. Results of the researches conducted in relation to yacht port «Grand Marina Sochi» are considered.

  18. 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...

  19. Water quality modeling based on landscape analysis: Importance of riparian hydrology

    Science.gov (United States)

    Thomas Grabs

    2010-01-01

    Several studies in high-latitude catchments have demonstrated the importance of near-stream riparian zones as hydrogeochemical hotspots with a substantial influence on stream chemistry. An adequate representation of the spatial variability of riparian-zone processes and characteristics is the key for modeling spatiotemporal variations of stream-water quality. This...

  20. Time-scale Dependence of Response of an Estuarine Water Quality Model to Nutrient Loading

    Science.gov (United States)

    We describe calibration and evaluation of a water quality model being implemented for Narragansett Bay to quantify the response of concentrations of nutrients, phytoplankton chlorophyll a and dissolved oxygen in the Bay to loading rates of nutrients and other boundary conditions....

  1. 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

  2. A Prototype Educational Delivery System Using Water Quality Monitoring as a Model.

    Science.gov (United States)

    Glazer, Richard B.

    This report describes the model educational delivery system used by Ulster County Community College in its water quality monitoring program. The educational delivery system described in the report encompasses the use of behavioral objectives as its foundation and builds upon this foundation to form a complete system whose outcomes can be measured,…

  3. Simulating water quality and ecological status of Lake Vansjø, Norway, under land-use and climate change by linking process-oriented models with a Bayesian network.

    Science.gov (United States)

    Couture, Raoul-Marie; Moe, S Jannicke; Lin, Yan; Kaste, Øyvind; Haande, Sigrid; Lyche Solheim, Anne

    2018-04-15

    Excess nutrient inputs and climate change are two of multiple stressors affecting many lakes worldwide. Lake Vansjø in southern Norway is one such eutrophic lake impacted by blooms of toxic blue-green algae (cyanobacteria), and classified as moderate ecological status under the EU Water Framework Directive. Future climate change may exacerbate the situation. Here we use a set of chained models (global climate model, hydrological model, catchment phosphorus (P) model, lake model, Bayesian Network) to assess the possible future ecological status of the lake, given the set of climate scenarios and storylines common to the EU project MARS (Managing Aquatic Ecosystems and Water Resources under Multiple Stress). The model simulations indicate that climate change alone will increase precipitation and runoff, and give higher P fluxes to the lake, but cause little increase in phytoplankton biomass or changes in ecological status. For the storylines of future management and land-use, however, the model results indicate that both the phytoplankton biomass and the lake ecological status can be positively or negatively affected. Our results also show the value in predicting a biological indicator of lake ecological status, in this case, cyanobacteria biomass with a BN model. For all scenarios, cyanobacteria contribute to worsening the status assessed by phytoplankton, compared to using chlorophyll-a alone. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. Water quality

    Science.gov (United States)

    Aquatic animals are healthiest and grow best when environmental conditions are within certain ranges that define, for a particular species, “good” water quality. From the outset, successful aquaculture requires a high-quality water supply. Water quality in aquaculture systems also deteriorates as an...

  10. 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.

  11. 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.

  12. 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

  13. Design of a water quality monitoring network for the Limpopo River Basin in Mozambique

    Science.gov (United States)

    Chilundo, M.; Kelderman, P.; O´keeffe, J. H.

    The measurement of chemical, physical and biological parameters is important for the characterization of streams health. Thus, cost-effective and targeted water quality (WQ) monitoring programmes are required for proper assessment, restoration and protection of such systems. This research proposes a WQ monitoring network for the Limpopo River Basin (LRB) in Mozambique located in Southern Africa, a region prone to severe droughts. In this Basin both anthropogenic and natural driven processes, exacerbated by the increased water demand by the four riparian countries (Botswana, South Africa, Zimbabwe and Mozambique) are responsible for the degradation of surface waters, impairing their downstream use, either for aquatic ecosystem, drinking, industrial or irrigation. Hence, physico-chemical, biological and microbiological characteristics at 23 sites within the basin were studied in November 2006 and January 2007. The physico-chemical and microbiological samples were analyzed according to American Public Health Association (APHA) standard methods, while the biological monitoring working party method (BMWP) was used for biological assessment. The assessment of the final WQ condition at sampled points was done taking into account appropriate indexes, the Mozambican standards for receiving waters and the WHO guidelines for drinking WQ. The assessed data indicated that sites located at proximities to the border with upstream countries were contaminated with heavy metals. The Elephants subcatchment was found with a relatively better WQ, whereas the Changane subcatchment together with the effluent point discharges in the basin were found polluted as indicated by the low dissolved oxygen and high total dissolved solids, electric conductivity, total hardness, sodium adsorption ratio and low benthic macroinvertebrates taxa. Significant differences ( p < 0.05) were found for some parameters when the concentrations recorded in November and January were tested, therefore, indicating

  14. 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.

  15. Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Baghapour

    2017-07-01

    Full Text Available In developing a specific WQI (Water Quality Index, many water quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi Criteria Decision Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes are considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts are taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. All calculations are carried out by using the expertise software called Group Fuzzy Decision Making (GFDM. The highest and the lowest weight values, 0.999 and 0.073 respectively, are related to Hg and temperature. Regarding the type of consumption that is drinking, the parameters’ weights and ranks are consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement from the decision making group. This study indicates that the weight of parameters in determining water quality largely depends on the experts’ opinions and

  16. 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

  17. Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

    Science.gov (United States)

    Francy, Donna S.; Brady, Amie M.G.; Carvin, Rebecca B.; Corsi, Steven R.; Fuller, Lori M.; Harrison, John H.; Hayhurst, Brett A.; Lant, Jeremiah; Nevers, Meredith B.; Terrio, Paul J.; Zimmerman, Tammy M.

    2013-01-01

    Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches

  18. Hydrodynamic modelling of recreational water quality using Escherichia coli as an indicator of microbial contamination

    Science.gov (United States)

    Eregno, Fasil Ejigu; Tryland, Ingun; Tjomsland, Torulv; Kempa, Magdalena; Heistad, Arve

    2018-06-01

    Microbial contamination of recreational beaches is often at its worst after heavy rainfall events due to storm floods that carry fecal matter and other pollutants from the watershed. Similarly, overflows of untreated sewage from combined sewerage systems may discharge directly into coastal water or via rivers and streams. In order to understand the effect of rainfall events, wind-directions and tides on the recreational water quality, GEMSS, an integrated 3D hydrodynamic model was applied to assess the spreading of Escherichia coli (E. coli) at the Sandvika beaches, located in the Oslo fjord. The model was also used to theoretically investigate the effect of discharges from septic tanks from boats on the water quality at local beaches. The model make use of microbial decay rate as the main input representing the survival of microbial pathogens in the ocean, which vary widely depending on the type of pathogen and environmental stress. The predicted beach water quality was validated against observed data after a heavy rainfall event using Nash-Sutcliffe coefficient (E) and the overall result indicated that the model performed quite well and the simulation was in - good agreement with the observed E. coli concentrations for all beaches. The result of this study indicated that: 1) the bathing water quality was poor according to the EU bathing water directive up to two days after the heavy rainfall event depending on the location of the beach site. 2) The discharge from a boat at 300-meter distance to the beaches slightly increased the E. coli levels at the beaches. 3) The spreading of microbial pathogens from its source to the different beaches depended on the wind speed and the wind direction.

  19. Quantifying effects of hydrological and water quality disturbances on fish with food-web modeling

    Science.gov (United States)

    Zhao, Changsen; Zhang, Yuan; Yang, Shengtian; Xiang, Hua; Sun, Ying; Yang, Zengyuan; Yu, Qiang; Lim, Richard P.

    2018-05-01

    Accurately delineating the effects of hydrological and water quality habitat factors on the aquatic biota will significantly assist the management of water resources and restoration of river ecosystems. However, current models fail to comprehensively consider the effects of multiple habitat factors on the development of fish species. In this study, a dynamic framework for river ecosystems was set up to explore the effects of multiple habitat factors in terms of hydrology and water quality on the fish community in rivers. To achieve this the biomechanical forms of the relationships between hydrology, water quality, and aquatic organisms were determined. The developing processes of the food web without external disturbance were simulated by 208 models, constructed using Ecopath With Ecosim (EWE). These models were then used to analyze changes in biomass (ΔB) of two representative fish species, Opsariichthys bidens and Carassius auratus, which are widely distributed in Asia, and thus have attracted the attention of scholars and stakeholders, due to the consequence of habitat alteration. Results showed that the relationship between the changes in fish biomass and key habitat factors can be expressed in a unified form. T-tests for the unified form revealed that the means of the two data sets of simulated and observed ΔB for these two fish species (O. bidens and C. auratus) were equal at the significance level of 5%. Compared with other ecological dynamic models, our framework includes theories that are easy to understand and has modest requirements for assembly and scientific expertise. Moreover, this framework can objectively assess the influence of hydrological and water quality variance on aquatic biota with simpler theory and little expertise. Therefore, it is easy to be put into practice and can provide a scientific support for decisions in ecological restoration made by river administrators and stakeholders across the world.

  20. Water quality control in Third River Reservoir (Argentina using geographical information systems and linear regression models

    Directory of Open Access Journals (Sweden)

    Claudia Ledesma

    2013-08-01

    Full Text Available Water quality is traditionally monitored and evaluated based upon field data collected at limited locations. The storage capacity of reservoirs is reduced by deposits of suspended matter. The major factors affecting surface water quality are suspended sediments, chlorophyll and nutrients. Modeling and monitoring the biogeochemical status of reservoirs can be done through data from remote sensors. Since the improvement of sensors’ spatial and spectral resolutions, satellites have been used to monitor the interior areas of bodies of water. Water quality parameters, such as chlorophyll-a concentration and secchi disk depth, were found to have a high correlation with transformed spectral variables derived from bands 1, 2, 3 and 4 of LANDSAT 5TM satellite. We created models of estimated responses in regard to values of chlorophyll-a. To do so, we used population models of single and multiple linear regression, whose parameters are associated with the reflectance data of bands 2 and 4 of the sub-image of the satellite, as well as the data of chlorophyll-a obtained in 25 selected stations. According to the physico-chemical analyzes performed, the characteristics of the water in the reservoir of Rio Tercero, correspond to somewhat hard freshwater with calcium bicarbonate. The water was classified as usable as a source of plant treatment, excellent for irrigation because of its low salinity and low residual sodium carbonate content, but unsuitable for animal consumption because of its low salt content.

  1. 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

  2. [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.

  3. 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.

  4. 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.

  5. 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

  6. River water quality model no. 1 (RWQM1): II. Biochemical process equations

    DEFF Research Database (Denmark)

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

    2001-01-01

    In this paper, biochemical process equations are presented as a basis for water quality modelling in rivers under aerobic and anoxic conditions. These equations are not new, but they summarise parts of the development over the past 75 years. The primary goals of the presentation are to stimulate...... transformation processes. This paper is part of a series of three papers. In the first paper, the general modelling approach is described; in the present paper, the biochemical process equations of a complex model are presented; and in the third paper, recommendations are given for the selection of a reasonable...

  7. Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

    Science.gov (United States)

    Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

    2014-05-01

    Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global

  8. Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Baghapour

    2017-07-01

    Full Text Available In developing a specific WQI (Water Quality Index, many quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi-Criteria Decision- Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes were considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts were taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. The highest and the lowest weight values, 0.999 and 0.073 respectively, were related to Hg and temperature. Regarding the type of consumption that was drinking, the parameters’ weights and ranks were consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement with the decision-making group. This study indicated that the weight of parameters in determining water quality largely depends on the experts’ opinions and approaches. Moreover, using the FOWA model provides results accurate and closer- to-reality on the significance of

  9. 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.

  10. Assessing ecosystem effects of reservoir operations using food web-energy transfer and water quality models

    Science.gov (United States)

    Saito, L.; Johnson, B.M.; Bartholow, J.; Hanna, R.B.

    2001-01-01

    We investigated the effects on the reservoir food web of a new temperature control device (TCD) on the dam at Shasta Lake, California. We followed a linked modeling approach that used a specialized reservoir water quality model to forecast operation-induced changes in phytoplankton production. A food web–energy transfer model was also applied to propagate predicted changes in phytoplankton up through the food web to the predators and sport fishes of interest. The food web–energy transfer model employed a 10% trophic transfer efficiency through a food web that was mapped using carbon and nitrogen stable isotope analysis. Stable isotope analysis provided an efficient and comprehensive means of estimating the structure of the reservoir's food web with minimal sampling and background data. We used an optimization procedure to estimate the diet proportions of all food web components simultaneously from their isotopic signatures. Some consumers were estimated to be much more sensitive than others to perturbations to phytoplankton supply. The linked modeling approach demonstrated that interdisciplinary efforts enhance the value of information obtained from studies of managed ecosystems. The approach exploited the strengths of engineering and ecological modeling methods to address concerns that neither of the models could have addressed alone: (a) the water quality model could not have addressed quantitatively the possible impacts to fish, and (b) the food web model could not have examined how phytoplankton availability might change due to reservoir operations.

  11. 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.

  12. 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).

  13. 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

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

    Science.gov (United States)

    Karmakar, Subhankar; Mujumdar, P. P.

    2006-07-01

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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. Application of Water Quality Model of Jordan River to Evaluate Climate Change Effects on Eutrophication

    Science.gov (United States)

    Van Grouw, B.

    2016-12-01

    The Jordan River is a 51 mile long freshwater stream in Utah that provides drinking water to more than 50% of Utah's population. The various point and nonpoint sources introduce an excess of nutrients into the river. This excess induces eutrophication that results in an inhabitable environment for aquatic life is expected to be exacerbated due to climate change. Adaptive measures must be evaluated based on predictions of climate variation impacts on eutrophication and ecosystem processes in the Jordan River. A Water Quality Assessment Simulation Program (WASP) model was created to analyze the data results acquired from a Total Maximum Daily Load (TMDL) study conducted on the Jordan River. Eutrophication is modeled based on levels of phosphates and nitrates from point and nonpoint sources, temperature, and solar radiation. It will simulate the growth of phytoplankton and periphyton in the river. This model will be applied to assess how water quality in the Jordan River is affected by variations in timing and intensity of spring snowmelt and runoff during drought in the valley and the resulting effects on eutrophication in the river.

  3. Sediment delivery estimates in water quality models altered by resolution and source of topographic data.

    Science.gov (United States)

    Beeson, Peter C; Sadeghi, Ali M; Lang, Megan W; Tomer, Mark D; Daughtry, Craig S T

    2014-01-01

    Moderate-resolution (30-m) digital elevation models (DEMs) are normally used to estimate slope for the parameterization of non-point source, process-based water quality models. These models, such as the Soil and Water Assessment Tool (SWAT), use the Universal Soil Loss Equation (USLE) and Modified USLE to estimate sediment loss. The slope length and steepness factor, a critical parameter in USLE, significantly affects sediment loss estimates. Depending on slope range, a twofold difference in slope estimation potentially results in as little as 50% change or as much as 250% change in the LS factor and subsequent sediment estimation. Recently, the availability of much finer-resolution (∼3 m) DEMs derived from Light Detection and Ranging (LiDAR) data has increased. However, the use of these data may not always be appropriate because slope values derived from fine spatial resolution DEMs are usually significantly higher than slopes derived from coarser DEMs. This increased slope results in considerable variability in modeled sediment output. This paper addresses the implications of parameterizing models using slope values calculated from DEMs with different spatial resolutions (90, 30, 10, and 3 m) and sources. Overall, we observed over a 2.5-fold increase in slope when using a 3-m instead of a 90-m DEM, which increased modeled soil loss using the USLE calculation by 130%. Care should be taken when using LiDAR-derived DEMs to parameterize water quality models because doing so can result in significantly higher slopes, which considerably alter modeled sediment loss. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  4. 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...

  5. Developing an ecosystem model of a floating wetland for water quality improvement on a stormwater pond.

    Science.gov (United States)

    McAndrew, Brendan; Ahn, Changwoo

    2017-11-01

    An ecosystem model was developed to assist with designing and implementing a floating wetland (FW) for water quality management of urban stormwater ponds, focusing on nitrogen (N) removal. The model is comprised of three linked submodels: hydrology, plant growth, and nitrogen. The model was calibrated with the data that resulted from a FW constructed and implemented as part of an interdisciplinary pedagogical project on a university campus, titled "The Rain Project", which raised awareness of stormwater issues while investigating the potential application of green infrastructure for sustainable stormwater management. The FW had been deployed during the summer of 2015 (i.e., May through mid-September) on a major stormwater pond located at the center of the Fairfax Campus of George Mason University near Washington, D.C. We used the model to explore the impact of three design elements of FW (i.e., hydraulic residence time (HRT), surface area coverage, and primary productivity) on the function of FW. Model simulations showed enhanced N removal performance as HRT and surface area coverage increased. The relatively low macrophyte productivity observed indicates that, in the case of our pond and FW, N removal was very limited. The model results suggest that even full pond surface coverage would result in meager N removal (∼6%) at a HRT of one week. A FW with higher plant productivity, more representative of that reported in the literature, would require only 10% coverage to achieve similar N removal efficiency (∼7%). Therefore, macrophyte productivity appears to have a greater impact on FW performance on N removal than surface area coverage or pond HRT. The outcome of the study shows that this model, though limited in scope, may be useful in aiding the design of FW to augment the performance of degraded stormwater ponds in an effort to meet local water quality goals. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. The National Water-Quality Assessment (NAWQA) Program planned monitoring and modeling activities for Texas, 2013–23

    Science.gov (United States)

    Ging, Patricia

    2013-01-01

    The U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Program was established by Congress in 1992 to answer the following question: What is the status of the Nation’s water quality and is it getting better or worse? Since 1992, NAWQA has been a primary source of nationally consistent data and information on the quality of the Nation’s streams and groundwater. Data and information obtained from objective and nationally consistent water-quality monitoring and modeling activities provide answers to where, when, and why the Nation’s water quality is degraded and what can be done to improve and protect it for human and ecosystem needs. For NAWQA’s third decade (2013–23), a new strategic Science Plan has been developed that describes a strategy for building upon and enhancing the USGS’s ongoing assessment of the Nation’s freshwater quality and aquatic ecosystems.

  7. Primer on Water Quality

    Science.gov (United States)

    ... water quality. What do we mean by "water quality"? Water quality can be thought of as a measure ... is suitable for a particular use. How is water quality measured? Some aspects of water quality can be ...

  8. 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

  9. 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

  10. 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.

  11. An Energy Efficient Adaptive Sampling Algorithm in a Sensor Network for Automated Water Quality Monitoring.

    Science.gov (United States)

    Shu, Tongxin; Xia, Min; Chen, Jiahong; Silva, Clarence de

    2017-11-05

    Power management is crucial in the monitoring of a remote environment, especially when long-term monitoring is needed. Renewable energy sources such as solar and wind may be harvested to sustain a monitoring system. However, without proper power management, equipment within the monitoring system may become nonfunctional and, as a consequence, the data or events captured during the monitoring process will become inaccurate as well. This paper develops and applies a novel adaptive sampling algorithm for power management in the automated monitoring of the quality of water in an extensive and remote aquatic environment. Based on the data collected on line using sensor nodes, a data-driven adaptive sampling algorithm (DDASA) is developed for improving the power efficiency while ensuring the accuracy of sampled data. The developed algorithm is evaluated using two distinct key parameters, which are dissolved oxygen (DO) and turbidity. It is found that by dynamically changing the sampling frequency, the battery lifetime can be effectively prolonged while maintaining a required level of sampling accuracy. According to the simulation results, compared to a fixed sampling rate, approximately 30.66% of the battery energy can be saved for three months of continuous water quality monitoring. Using the same dataset to compare with a traditional adaptive sampling algorithm (ASA), while achieving around the same Normalized Mean Error (NME), DDASA is superior in saving 5.31% more battery energy.

  12. An Energy Efficient Adaptive Sampling Algorithm in a Sensor Network for Automated Water Quality Monitoring

    Directory of Open Access Journals (Sweden)

    Tongxin Shu

    2017-11-01

    Full Text Available Power management is crucial in the monitoring of a remote environment, especially when long-term monitoring is needed. Renewable energy sources such as solar and wind may be harvested to sustain a monitoring system. However, without proper power management, equipment within the monitoring system may become nonfunctional and, as a consequence, the data or events captured during the monitoring process will become inaccurate as well. This paper develops and applies a novel adaptive sampling algorithm for power management in the automated monitoring of the quality of water in an extensive and remote aquatic environment. Based on the data collected on line using sensor nodes, a data-driven adaptive sampling algorithm (DDASA is developed for improving the power efficiency while ensuring the accuracy of sampled data. The developed algorithm is evaluated using two distinct key parameters, which are dissolved oxygen (DO and turbidity. It is found that by dynamically changing the sampling frequency, the battery lifetime can be effectively prolonged while maintaining a required level of sampling accuracy. According to the simulation results, compared to a fixed sampling rate, approximately 30.66% of the battery energy can be saved for three months of continuous water quality monitoring. Using the same dataset to compare with a traditional adaptive sampling algorithm (ASA, while achieving around the same Normalized Mean Error (NME, DDASA is superior in saving 5.31% more battery energy.

  13. Using National Coastal Assessment Data to Model Estuarine Water Quality at Large Spatial Scales.

    Science.gov (United States)

    The water quality of the Nation’s estuaries is attracting scrutiny in light of population growth and enhanced nutrient delivery. The USEPA has evaluated water quality in the National Coastal Assessment (NCA) and National Aquatic Resource Surveys (NARS) programs. Here we rep...

  14. Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

    Science.gov (United States)

    Yeo, I.-Y.; Lee, S.; Sadeghi, A. M.; Beeson, P. C.; Hively, W. D.; McCarty, G. W.; Lang, M. W.

    2014-12-01

    Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay watershed (CBW), which is located in the mid-Atlantic US, winter cover crop use has been emphasized, and federal and state cost-share programs are available to farmers to subsidize the cost of cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops to improve water quality at the watershed scale (~ 50 km2) and to identify critical source areas of high nitrate export. A physically based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data to simulate hydrological processes and agricultural nutrient cycling over the period of 1990-2000. To accurately simulate winter cover crop biomass in relation to growing conditions, a new approach was developed to further calibrate plant growth parameters that control the leaf area development curve using multitemporal satellite-based measurements of species-specific winter cover crop performance. Multiple SWAT scenarios were developed to obtain baseline information on nitrate loading without winter cover crops and to investigate how nitrate loading could change under different winter cover crop planting scenarios, including different species, planting dates, and implementation areas. The simulation results indicate that winter cover crops have a negligible impact on the water budget but significantly reduce nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading from agricultural lands was approximately 14 kg ha-1, but decreased to 4.6-10.1 kg ha-1 with cover crops resulting in a reduction rate of 27-67% at the watershed scale. Rye was the most effective species, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of cover crops (~ 30

  15. 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.

  16. Risk-based modelling of surface water quality: a case study of the Charles River, Massachusetts

    Science.gov (United States)

    McIntyre, Neil R.; Wagener, Thorsten; Wheater, Howard S.; Chapra, Steven C.

    2003-04-01

    A model of phytoplankton, dissolved oxygen and nutrients is presented and applied to the Charles River, Massachusetts within a framework of Monte Carlo simulation. The model parameters are conditioned using data from eight sampling stations along a 40 km stretch of the Charles River, during a (supposed) steady-state period in the summer of 1996, and the conditioned model is evaluated using data from later in the same year. Regional multi-objective sensitivity analysis is used to identify the parameters and pollution sources most affecting the various model outputs under the conditions observed during that summer. The effects of Monte Carlo sampling error are included in this analysis, and the observations which have least contributed to model conditioning are indicated. It is shown that the sensitivity analysis can be used to speculate about the factors responsible for undesirable levels of eutrophication, and to speculate about the risk of failure of nutrient reduction interventions at a number of strategic control sections. The analysis indicates that phosphorus stripping at the CRPCD wastewater treatment plant on the Charles River would be a high-risk intervention, especially for controlling eutrophication at the control sections further downstream. However, as the risk reflects the perceived scope for model error, it can only be recommended that more resources are invested in data collection and model evaluation. Furthermore, as the risk is based solely on water quality criteria, rather than broader environmental and economic objectives, the results need to be supported by detailed and extensive knowledge of the Charles River problem.

  17. Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality.

    Science.gov (United States)

    Islam, M M Majedul; Iqbal, Muhammad Shahid; Leemans, Rik; Hofstra, Nynke

    2018-03-01

    Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.

  18. Simplifying dynamic river water quality modelling: A case study of inorganic nitrogen dynamics in the Crocodile River (South Africa).

    CSIR Research Space (South Africa)

    Deksissa, T

    2004-06-01

    Full Text Available Quality Model No. 1, which is one of the most comprehensive basic river water quality models available in literature. The applicability of the simplified model in data limited situations was investigated using a case study of inorganic nitrogen (nitrate...

  19. Evaluating the APEX model for simulating streamflow and water quality on ten agricultural watersheds in the U.S.

    Science.gov (United States)

    Simulation models are increasingly used to assess water quality constituent losses from agricultural systems. Mis-use often gives irrelevant or erroneous answers. The Agricultural Policy Environmental Extender (APEX) model is emerging as one of the premier modeling tools for fields, farms, and agr...

  20. Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

    Science.gov (United States)

    Han, Feng; Zheng, Yi

    2018-06-01

    Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

  1. 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

  2. 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

  3. Water quality monitoring protocol for wadeable streams and rivers in the Northern Great Plains Network

    Science.gov (United States)

    Wilson, Marcia H.; Rowe, Barbara L.; Gitzen, Robert A.; Wilson, Stephen K.; Paintner-Green, Kara J.

    2014-01-01

    Preserving the national parks unimpaired for the enjoyment of future generations is a fundamental purpose of the National Park Service (NPS). To address growing concerns regarding the overall physical, chemical, and biological elements and processes of park ecosystems, the NPS implemented science-based management through “Vital Signs” monitoring in 270 national parks (NPS 2007). The Northern Great Plains Network (NGPN) is among the 32 National Park Service Networks participating in this monitoring effort. The NGPN will develop protocols over the next several years to determine the overall health or condition of resources within 13 parks located in Nebraska, North Dakota, South Dakota, and Wyoming.

  4. Comparing the Performance of Artificial Intelligence Models in Estimating Water Quality Parameters in Periods of Low and High Water Flow

    Directory of Open Access Journals (Sweden)

    majid montaseri

    2017-03-01

    Full Text Available Introduction: A total dissolved solid (TDS is an important indicator for water quality assesment. Since the composition of mineral salts and discharge affects the TDS of water, it is important to understand the relationships of mineral salts composition with TDS. Materials and Methods: In this study, methods of artificial neural networks with five different training algorithm,Levenberg-Marquardt (LM, Scaled Conjugate Gradient (SCG, Fletcher Conjugate Gradient (CGF, One Step Secant (OSS and Gradient descent with adaptive learning rate backpropagation(GDAalgorithm and adaptive Neurofuzzy inference system based on Subtractive Clustering were used to model water quality properties of Zarrineh River Basin, to be developed in total dissolved solids prediction. ANN and ANFIS program code were written in MATLAB language. Here, the ANN with one hidden layer was used and the hidden nodes’ number was determined using trial and error. Different activation functions (logarithm sigmoid, tangent sigmoid and linear were tried for the hidden and output nodes. Therefore, water quality data from seven hydrometer stationswere used during the statistical period of 18years (1993-2010.In this research, the study period was divided into two periods of dry and wet flow, and then in a preliminary statistical analysis, the main parameters affecting the estimation of the TDS are determined and isused for modeling. 75% of data are used for remaining and 25% of the data are used for evaluation of the model, randomly. In this paper, three statistical evaluation criteria, correlation coefficient (R, the root mean square error (RMSE and mean absolute error (MAE were used to assess models’ performances. Results and Discussion: By applying correlation coefficients method between the parameters of water quality and discharge with total dissolved solid in two periods, wet and dry periods, the significant (at 95% level variables entered into the model were Q, HCO3., Cl, So4, Ca

  5. Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

    OpenAIRE

    Yeo, I.-Y.; Lee, S.; Sadeghi, A. M.; Beeson, P. C.; Hively, W. D.; McCarty, G. W.; Lang, M. W.

    2014-01-01

    Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay watershed (CBW), which is located in the mid-Atlantic US, winter cover crop use has been emphasized, and federal and state cost-share programs are available to farmers to subsidize the cost of cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops to improve water quality a...

  6. Mitigation scenario analysis: modelling the impacts of changes in agricultural management practices on surface water quality at the catchment scale

    Science.gov (United States)

    Taylor, Sam; He, Yi; Hiscock, Kevin

    2014-05-01

    Increasing human pressures on the natural environment through the demand for increased agricultural productivity have exacerbated and deteriorated water quality conditions within many environments due to an unbalancing of the nutrient cycle. As a consequence, increased agricultural diffuse water pollution has resulted in elevated concentrations of nutrients within surface water and groundwater bodies. This deterioration in water quality has direct consequences for the health of aquatic ecosystems and biodiversity, human health, and the use of water as a resource for public water supply and recreation. To mitigate these potential impacts and to meet commitments under the EU Drinking Water and Water Framework Directives, there is a need to improve our understanding of the impacts that agricultural land use and management practices have on water quality. Water quality models are one of the tools available which can be used to facilitate this aim. These simplified representations of the physical environment allow a variety of changes to be simulated within a catchment, including for example changes in agricultural land use and management practices, allowing for predictions of the impacts of those measures on water quality to be developed and an assessment to be made of their effectiveness in improving conditions. The aim of this research is to apply the water quality model SWAT (Soil and Water Assessment Tool) to the Wensum catchment (area 650 km2), situated in the East of England, to predict the impacts of potential changes in land use and land management practices on water quality as part of a process to select those measures that in combination will have the greatest potential to improve water quality. Model calibration and validation is conducted at three sites within the catchment against observations of river discharge and nitrate and total phosphorus loads at a monthly time-step using the optimisation algorithm SUFI-2 (Sequential Uncertainty Fitting Version 2

  7. 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.

  8. 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.

  9. Training the next generation of scientists: Modeling Infectious Disease and Water Quality of Montana Streams

    Science.gov (United States)

    Fytilis, N.; Wyman, S.; Lamb, R.; Stevens, L.; Kerans, B.; Rizzo, D. M.

    2010-12-01

    water quality and the presence of these taxa is important in determining stream health. In addition, system dynamics software (STELLA) is used to model the non-linear relationships and feedback between worm prevalence and disease dynamics. These types of collaborations between engineers, biologists, field ecologists and geneticists from secondary, post-secondary and higher institutions proved useful in linking complex geochemical data, worm community structure and molecular genetics to develop the next-generation scientists and better understand disease dynamics.

  10. Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model

    Science.gov (United States)

    Yeo, In-Young; Lee, Sangchui; Sadeghi, Ali M.; Beeson, Peter C.; Hively, W. Dean; McCarty, Greg W.; Lang, Megan W.

    2013-01-01

    Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay Watershed (CBW), which is located in the Mid-Atlantic US, winter cover crop use has been emphasized and federal and state cost-share programs are available to farmers to subsidize the cost of winter cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops at the watershed scale and to identify critical source areas of high nitrate export. A physically-based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data and satellite-based estimates of winter cover crop species performance to simulate hydrological processes and nutrient cycling over the period of 1991–2000. Multiple scenarios were developed to obtain baseline information on nitrate loading without winter cover crops planted and to investigate how nitrate loading could change with different winter cover crop planting scenarios, including different species, planting times, and implementation areas. The results indicate that winter cover crops had a negligible impact on water budget, but significantly reduced nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading was approximately 14 kg ha−1, but it decreased to 4.6–10.1 kg ha−1 with winter cover crops resulting in a reduction rate of 27–67% at the watershed scale. Rye was most effective, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of winter cover crops (~30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~2 kg ha−1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of winter cover crop implementation. Agricultural fields with well-drained soils

  11. 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.

  12. 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.

  13. Southern Phosphorus Indices, Water Quality Data, and Modeling (APEX, APLE, and TBET) Results: A Comparison.

    Science.gov (United States)

    Osmond, Deanna; Bolster, Carl; Sharpley, Andrew; Cabrera, Miguel; Feagley, Sam; Forsberg, Adam; Mitchell, Charles; Mylavarapu, Rao; Oldham, J Larry; Radcliffe, David E; Ramirez-Avila, John J; Storm, Dan E; Walker, Forbes; Zhang, Hailin

    2017-11-01

    Phosphorus (P) Indices in the southern United States frequently produce different recommendations for similar conditions. We compared risk ratings from 12 southern states (Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, and Texas) using data collected from benchmark sites in the South (Arkansas, Georgia, Mississippi, North Carolina, Oklahoma, and Texas). Phosphorus Index ratings were developed using both measured erosion losses from each benchmark site and Revised Universal Soil Loss Equation 2 predictions; mostly, there was no difference in P Index outcome. The derived loss ratings were then compared with measured P loads at the benchmark sites by using equivalent USDA-NRCS P Index ratings and three water quality models (Annual P Loss Estimator [APLE], Agricultural Policy Environmental eXtender [APEX], and Texas Best Management Practice Evaluation Tool [TBET]). Phosphorus indices were finally compared against each other using USDA-NRCS loss ratings model estimate correspondence with USDA-NRCS loss ratings. Correspondence was 61% for APEX, 48% for APLE, and 52% for TBET, with overall P index correspondence at 55%. Additive P Indices (Alabama and Texas) had the lowest USDA-NRCS loss rating correspondence (31%), while the multiplicative (Arkansas, Florida, Louisiana, Mississippi, South Carolina, and Tennessee) and component (Georgia, Kentucky, and North Carolina) indices had similar USDA-NRCS loss rating correspondence-60 and 64%, respectively. Analysis using Kendall's modified Tau suggested that correlations between measured and calculated P-loss ratings were similar or better for most P Indices than the models. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  14. 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.

  15. 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.

  16. Modeling the relationship between landscape characteristics and water quality in a typical highly intensive agricultural small watershed, Dongting lake basin, south central China.

    Science.gov (United States)

    Li, Hongqing; Liu, Liming; Ji, Xiang

    2015-03-01

    Understanding the relationship between landscape characteristics and water quality is critically important for estimating pollution potential and reducing pollution risk. Therefore, this study examines the relationship between landscape characteristics and water quality at both spatial and temporal scales. The study took place in the Jinjing River watershed in 2010; seven landscape types and four water quality pollutions were chosen as analysis parameters. Three different buffer areas along the river were drawn to analyze the relationship as a function of spatial scale. The results of a Pearson's correlation coefficient analysis suggest that "source" landscape, namely, tea gardens, residential areas, and paddy lands, have positive effects on water quality parameters, while forests exhibit a negative influence on water quality parameters because they represent a "sink" landscape and the sub-watershed level is identified as a suitable scale. Using the principal component analysis, tea gardens, residential areas, paddy lands, and forests were identified as the main landscape index. A stepwise multiple regression analysis was employed to model the relationship between landscape characteristics and water quality for each season. The results demonstrate that both landscape composition and configuration affect water quality. In summer and winter, the landscape metrics explained approximately 80.7 % of the variance in the water quality variables, which was higher than that for spring and fall (60.3 %). This study can help environmental managers to understand the relationships between landscapes and water quality and provide landscape ecological approaches for water quality control and land use management.

  17. Water quality improvements from afforestation in an agricultural catchment in Denmark illustrated with the INCA model

    Directory of Open Access Journals (Sweden)

    A. Bastrup-Birk

    2004-01-01

    Full Text Available Intensive agricultural land use across Europe has altered nitrogen (N budget of catchments substantially, causing widespread N pollution of freshwater. Although the N cycle in forests has changed due to increased N deposition, most forest soil waters in Europe have low nitrate concentrations. The protective function of forests on water quality has led to increasing interest in the planting of new forests on arable land as a measure to protect valuable or sensitive freshwater resources. The paper illustrates the effects of afforestation on water and N cycling using the Integrated Nitrogen Catchment (INCA model. The model was calibrated on the Horndrup catchment in the eastern part of Jutland, Denmark, which is dominated by agricultural land use but also covered by 18% of forest land. The dynamics of nitrate concentrations in the stream water were simulated successfully by INCA over a three-year period. The simulation of the dynamics of nitrate concentrations in the soil water is closely linked to the simulation of the hydrological dynamics and especially to the rainfall. The best fit was achieved for both arable and forest land during the wettest year of the study period. The model was then used to simulate the effect of afforestation of a catchment dominated by agriculture on N fluxes with seepage and runoff. Scenarios of whole catchment conversion to forest were run, based on observations of evapotranspiration and N deposition from other Danish sites. The simulated conversion to mature forest reduced runoff by 30–45% and reduced the nitrate concentrations in the soil water by 50–70%. The simulated effect of afforestation on N leaching was an almost direct reflection of the change in the N input: substantial changes in the plant demand and soil N dynamics over the afforestation period were not simulated. To simulate the N dynamics over longer time-scales, appropriate for the study of afforestation, it is suggested that the INCA model be run

  18. Integrating GIS, remote sensing and mathematical modelling for surface water quality management in irrigated watersheds

    NARCIS (Netherlands)

    Azab, A.M.

    2012-01-01

    The intensive uses of limited water resources, the growing population rates and the various increasing human activities put high and continuous stresses on these resources. Major problems affecting the water quality of rivers, streams and lakes may arise from inadequately treated sewage, poor land

  19. Compartment-based hydrodynamics and water quality modeling of a NorthernEverglades Wetland, Florida, USA

    Science.gov (United States)

    The last remaining large remnant of softwater wetlands in the US Florida Everglades lies within the Arthur R. Marshall Loxahatchee National Wildlife Refuge. However, Refuge water quality today is impacted by pumped stormwater inflows to the eutrophic and mineral-enriched 100-km c...

  20. Water Quality Assessment of River Soan (Pakistan) and Source Apportionment of Pollution Sources Through Receptor Modeling.

    Science.gov (United States)

    Nazeer, Summya; Ali, Zeshan; Malik, Riffat Naseem

    2016-07-01

    The present study was designed to determine the spatiotemporal patterns in water quality of River Soan using multivariate statistics. A total of 26 sites were surveyed along River Soan and its associated tributaries during pre- and post-monsoon seasons in 2008. Hierarchical agglomerative cluster analysis (HACA) classified sampling sites into three groups according to their degree of pollution, which ranged from least to high degradation of water quality. Discriminant function analysis (DFA) revealed that alkalinity, orthophosphates, nitrates, ammonia, salinity, and Cd were variables that significantly discriminate among three groups identified by HACA. Temporal trends as identified through DFA revealed that COD, DO, pH, Cu, Cd, and Cr could be attributed for major seasonal variations in water quality. PCA/FA identified six factors as potential sources of pollution of River Soan. Absolute principal component scores using multiple regression method (APCS-MLR) further explained the percent contribution from each source. Heavy metals were largely added through industrial activities (28 %) and sewage waste (28 %), nutrients through agriculture runoff (35 %) and sewage waste (28 %), organic pollution through sewage waste (27 %) and urban runoff (17 %) and macroelements through urban runoff (39 %), and mineralization and sewage waste (30 %). The present study showed that anthropogenic activities are the major source of variations in River Soan. In order to address the water quality issues, implementation of effective waste management measures are needed.

  1. Lessons learned using water quality models to develop numeric nutrient criteria for a Gulf coast estuary

    Science.gov (United States)

    Pensacola Bay is a shallow, mesotrophic estuary located in the north-central coast of the Gulf of Mexico, US. In November 2012, the US Environmental Protection Agency (US EPA) proposed numeric total nitrogen (TN), total phosphorus (TP), and chlorophyll-a (chl-a) water quality cr...

  2. Development of urban runoff model FFC-QUAL for first-flush water-quality analysis in urban drainage basins.

    Science.gov (United States)

    Hur, Sungchul; Nam, Kisung; Kim, Jungsoo; Kwak, Changjae

    2018-01-01

    An urban runoff model that is able to compute the runoff, the pollutant loadings, and the concentrations of water-quality constituents in urban drainages during the first flush was developed. This model, which is referred to as FFC-QUAL, was modified from the existing ILLUDAS model and added for use during the water-quality analysis process for dry and rainy periods. For the dry period, the specifications of the coefficients for the discharge and water quality were used. During rainfall, we used the Clark and time-area methods for the runoff analyses of pervious and impervious areas to consider the effects of the subbasin shape; moreover, four pollutant accumulation methods and the washoff equation for computing the water quality each time were used. According to the verification results, FFC-QUAL provides generally similar output as the measured data for the peak flow, total runoff volume, total loadings, peak concentration, and time of peak concentration for three rainfall events in the Gunja subbasin. In comparison with the ILLUDAS, SWMM, and MOUSE models, there is little difference between these models and the model developed in this study. The proposed model should be useful in urban watersheds because of its simplicity and its capacity to model common pollutants (e.g., biological oxygen demand, chemical oxygen demand, Escherichia coli, suspended solids, and total nitrogen and phosphorous) in runoff. The proposed model can also be used in design studies to determine how changes in infrastructure will affect the runoff and pollution loads. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. CE–QUAL–W2 water-quality model and supporting LOADEST models for Lake St. Croix, Wisconsin and Minnesota, 2013

    Data.gov (United States)

    Department of the Interior — A mechanistic, biophysical water-quality model (CE–QUAL–W2) was developed and calibrated for Lake St. Croix, Wisconsin and Minnesota. The Lake St. Croix CE–QUAL–W2...

  4. 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

  5. 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.)

  6. 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 ...

  7. 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.

  8. Assessment of Dissolved Oxygen Mitigation at Hydropower Dams Using an Integrated Hydrodynamic/Water Quality/Fish Growth Model

    Energy Technology Data Exchange (ETDEWEB)

    Bevelhimer, Mark S [ORNL; Coutant, Charles C [ORNL

    2006-07-01

    Dissolved oxygen (DO) in rivers is a common environmental problem associated with hydropower projects. Approximately 40% of all FERC-licensed projects have requirements to monitor and/or mitigate downstream DO conditions. Most forms of mitigation for increasing DO in dam tailwaters are fairly expensive. One area of research of the Department of Energy's Hydropower Program is the development of advanced turbines that improve downstream water quality and have other environmental benefits. There is great interest in being able to predict the benefits of these modifications prior to committing to the cost of new equipment. In the case of turbine replacement or modification, there is a need for methods that allow us to accurately extrapolate the benefits derived from one or two turbines with better design to the replacement or modification of all turbines at a site. The main objective of our study was to demonstrate a modeling approach that integrates the effects of flow and water quality dynamics with fish bioenergetics to predict DO mitigation effectiveness over long river segments downstream of hydropower dams. We were particularly interested in demonstrating the incremental value of including a fish growth model as a measure of biological response. The models applied are a suite of tools (RMS4 modeling system) originally developed by the Tennessee Valley Authority for simulating hydrodynamics (ADYN model), water quality (RQUAL model), and fish growth (FISH model) as influenced by DO, temperature, and available food base. We parameterized a model for a 26-mile reach of the Caney Fork River (Tennessee) below Center Hill Dam to assess how improvements in DO at the dam discharge would affect water quality and fish growth throughout the river. We simulated different types of mitigation (i.e., at the turbine and in the reservoir forebay) and different levels of improvement. The model application successfully demonstrates how a modeling approach like this one can be

  9. Mathematical Modeling for Water Quality Management under Interval and Fuzzy Uncertainties

    Directory of Open Access Journals (Sweden)

    J. Liu

    2013-01-01

    Full Text Available In this study, an interval fuzzy credibility-constrained programming (IFCP method is developed for river water quality management. IFCP is derived from incorporating techniques of fuzzy credibility-constrained programming (FCP and interval-parameter programming (IPP within a general optimization framework. IFCP is capable of tackling uncertainties presented as interval numbers and possibility distributions as well as analyzing the reliability of satisfying (or the risk of violating system’s constraints. A real-world case for water quality management planning of the Xiangxi River in the Three Gorges Reservoir Region (which faces severe water quality problems due to pollution from point and nonpoint sources is then conducted for demonstrating the applicability of the developed method. The results demonstrate that high biological oxygen demand (BOD discharge is observed at the Baishahe chemical plant and Gufu wastewater treatment plant. For nonpoint sources, crop farming generates large amounts of total phosphorus (TP and total nitrogen (TN. The results are helpful for managers in not only making decisions of effluent discharges from point and nonpoint sources but also gaining insight into the tradeoff between system benefit and environmental requirement.

  10. Application of a water quality model for determining instream aeration station location and operational rules: A case study

    Directory of Open Access Journals (Sweden)

    Charles S. Melching

    2018-01-01

    Full Text Available Instream aeration has been used as a supplement to secondary treatment or a substitute for tertiary treatment for meeting dissolved oxygen (DO standards in rivers. Many studies have used water quality models to determine the number, location, and capacity of instream aeration stations (IASs needed to meet DO standards in combination with other pollution control measures. DO concentrations have been improved in the North Shore Channel and North Branch Chicago River by the Devon Avenue IAS for more than 35 years. A study was initiated to determine whether it was better to rehabilitate or relocate this station and to determine appropriate operational guidance for the IAS at the selected location. A water quality model capable of simulating DO concentrations during unsteady flow was used to evaluate the proper location for an IAS and operational guidance for this IAS. Three test years, a dry year, a wet year, and an extreme year, were considered in the evaluation. The study found that the Devon Avenue IAS should be rehabilitated as this location performed as well as or better than any of 10 alternative locations. According to the new operational guidance for this IAS, the amount of time with blowers operating could be substantially reduced compared to traditional operations while at the same time the attainment of the DO standards could be increased. This study shows that a carefully designed modeling study is key to effective selection, location, and operation of IASs such that attainment of DO standards can be maximized while operation hours of blowers can be minimized. Keywords: Instream aeration, Dissolved oxygen, Water quality modeling, Water quality management, Computer simulation

  11. Multi-objective calibration of a reservoir water quality model in aggregation and non-dominated sorting approaches

    Science.gov (United States)

    Huang, Yongtai

    2014-03-01

    Numerical water quality models are developed to predict contaminant fate and transport in receiving waters such as reservoirs and lakes. They can be helpful tools for water resource management. The objective of this study is to calibrate a water quality model which was set up to simulate the water quality conditions of Pepacton Reservoir, Downsville, New York, USA, using an aggregation hybrid genetic algorithm (AHGA) and a non-dominated sorting hybrid genetic algorithm (NSHGA). Both AHGA and NSHGA use a hybrid genetic algorithm (HGA) as optimization engines but are different in fitness assignment. In the AHGA, a weighted sum of scaled simulation errors is designed as an overall objective function to measure the fitness of solutions (i.e., parameter values). In the NSHGA, a method based on non-dominated sorting and Euclidean distances is proposed to calculate the dummy fitness of solutions. In addition, this study also compares the AHGA and the NSHGA. The purpose of this comparison is to determine whether the objective function values (i.e., simulation errors) and simulated results obtained by the AHGA and the NSHGA are significantly different from each other. The results show that the objective function values from the two HGAs are good compromises between all objective functions, and the calibrated model results match the observed data reasonably well and are comparable to other studies, supporting and justifying the use of multi-objective calibration.

  12. NASA-modified precipitation products to improve USEPA nonpoint source water quality modeling for the Chesapeake Bay.

    Science.gov (United States)

    Nigro, Joseph; Toll, David; Partington, Ed; Ni-Meister, Wenge; Lee, Shihyan; Gutierrez-Magness, Angelica; Engman, Ted; Arsenault, Kristi

    2010-01-01

    The USEPA has estimated that over 20,000 water bodies within the United States do not meet water quality standards. One of the regulations in the Clean Water Act of 1972 requires states to monitor the total maximum daily load, or the amount of pollution that can be carried by a water body before it is determined to be "polluted," for any watershed in the United States (Copeland, 2005). In response to this mandate, the USEPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a decision support tool for assessing pollution and to guide the decision-making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program-Fortran (HSPF), computes continuous streamflow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events, especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA-modified/NOAA precipitation data. Using these data within HSPF, streamflow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better streamflow statistics and, potentially, in improved water quality assessment.

  13. Effects of Changes in Lugu Lake Water Quality on Schizothorax Yunnansis Ecological Habitat Based on HABITAT Model

    Science.gov (United States)

    Huang, Wei; Mynnet, Arthur

    Schizothorax Yunnansis is an unique fish species only existing in Lugu Lake, which is located in the southwestern China. The simulation and research on Schizothorax Yunnansis habitat environment have a vital significance to protect this rare fish. With the development of the tourism industry, there bring more pressure on the environmental protection. The living environment of Schizothorax Yunnansis is destroyed seriously because the water quality is suffering the sustaining pollution of domestic sewage from the peripheral villages. This paper analyzes the relationship between water quality change and Schizothorax Yunnansis ecological habitat and evalutes Schizothorax Yunnansis's ecological habitat impact based on HABITAT model. The results show that when the TP concentration in Lugu Lake does not exceed Schizothorax Yunnansis's survival threshold, Schizothorax Yunnansis can get more nutrients and the suitable habitat area for itself is increased. Conversely, it can lead to TP toxicity in the Schizothorax Yunnansis and even death. Therefore, unsuitable habitat area for Schizothorax Yunnansis is increased. It can be seen from the results that HABITAT model can assist in ecological impact assessment studies by translating results of hydrological, water quality models into effects on the natural environment and human society.

  14. A GIS-based Model for Urban Change and Implications for Water Quality in the Pontchartrain Basin

    Science.gov (United States)

    Carstens, D.; Amer, R. M.

    2017-12-01

    The combination of remote sensing techniques and Geographic Information Systems (GIS) to measure water quality allows researchers to monitor changes in various water quality parameters over temporal and spatial scales that are not always readily apparent from in situ measurements. Water has a distinct spectral behavior in comparison to soil, vegetation and urban, and therefore can be distinguished from surrounding environments. This study involves using remote sensing and GIS methods to map urban sprawl and its resulting influences on water quality in the Pontchartrain Basin over the last three decades. Two images of Landsat Thematic Mapper (TM) were taken in October 1985 and two images of Landsat Operational Land Imager (OLI) were taken in 2015 were atmospherically corrected and processed to map urban sprawl and influences on water quality of Pontchartrain Basin in the last three decades. To accomplish this, a normalized difference building index (NDBI) was developed for Landsat images. The NDBI was calculated from (NIR - SWIR) / (NIR + SWIR), where SWIR is the longest wavelength. The normalized difference vegetation index (NDVI), the normalized difference soil index (NDSI), and the normalized difference water index (NDWI) were also calculated for Landsat images. A GIS model was developed by integrating the NDBI, NDVI, NDSI, and NDWI, and yielded urban/non-urban/water boundary maps with 30-m resolution. Results indicate that urban areas have increased approximately from 25,643 km2 to 26,677 km2, which represents about 4.0% change from non-urban to urban in the last 3 decades. The results are in a good agreement with the U.S. Census data, which indicated that there is a 12.25% increase in population over the last 25 years in the 16 parishes of the Pontchartrain Basin. Urban changes were compared with changes of water quality parameters in PONTCHARTRAIN BASIN, which include pH, specific conductance, nitrogen, phosphorous, and dissolved oxygen. The results show that

  15. Hourly Water Quality Dynamics in Rivers Downstream of Urban Areas: Quantifying Seasonal Variation and Modelling Impacts of Urban Growth

    Science.gov (United States)

    Hutchins, M.; McGrane, S. J.; Miller, J. D.; Hitt, O.; Bowes, M.

    2016-12-01

    Continuous monitoring of water flows and quality is invaluable in improving understanding of the influence of urban areas on river health. When used to inform predictive modelling, insights can be gained as to how urban growth may affect the chemical and biological quality of rivers as they flow downstream into larger waterbodies. Water flow and quality monitoring in two urbanising sub-catchments (long term flow records are available, but particular focus is given to monitoring of an extended set of sites during prolonged winter rainfall. In the Ray sub-catchment streams were monitored in which urban cover varied across a range of 7-78%. A rural-urban gradient in DO was apparent in the low flow period prior to the storms. Transient low DO (works (STW). In this respect temperature- and respiration-driven DO sags in summer were at least if not more severe than those driven by the winter storms. Likewise, although winter storm NH4 concentrations violated EU legislation downstream of the STW, they were lower than summer concentrations in pollutant flushes following dry spells. In contrast the predominant phenomenon affecting water quality in the Cut during the storms was dilution. Here, a river water quality model was calibrated and applied over the course of a year to capture the importance of periphyton photosynthesis and respiration cycles in determining water quality and to predict the influence of hypothetical urban growth on downstream river health. The periods monitored intensively, dry spells followed by prolonged rainfall, represent: (i) marked changes in conditions likely to become more prevalent in future, (ii) situations under which water quality in urban areas is likely to be particularly vulnerable, being influenced for example by first flush effects followed by capacity exceedance at STW. Despite this, whilst being somewhat long lasting in places, impacts on DO were not severe.

  16. 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

  17. 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

  18. Adaptation of streeter model - Phelps for water quality modeling in a large semi-arid basin.

    OpenAIRE

    Wagner Josà da Silva Mendes

    2014-01-01

    This paper presents an adaptation of the classical model of Streeter-Phelps modeling of Dissolved Oxygen (DO) and Biochemical Oxygen Demand (BOD) in the basin of the Upper Jaguaribe (25,000 km2), State of Ceara, Brazil. The adaptation of the model consisted of the numerical solution of differential equations Streeter-Phelps, considering the effect of incremental flows and sewage releases over the sections, as well as the variability of the sections of rivers and tributaries. For model calibra...

  19. Framework for Derivation of Water Quality Criteria Using the Biotic Ligand Model: Copper as a Case Study.

    Science.gov (United States)

    Gondek, John C; Gensemer, Robert W; Claytor, Carrie A; Canton, Steven P; Gorsuch, Joseph W

    2018-06-01

    Acceptance of the Biotic Ligand Model (BLM) to derive aquatic life criteria, for metals in general and copper in particular, is growing amongst regulatory agencies worldwide. Thus, it is important to ensure that water quality data are used appropriately and consistently in deriving such criteria. Here we present a suggested BLM implementation framework (hereafter referred to as "the Framework") to help guide the decision-making process when designing sampling and analysis programs for use of the BLM to derive water quality criteria applied on a site-specific basis. Such a framework will help inform stakeholders on the requirements needed to derive BLM-based criteria, and thus, ensure the appropriate types and amount of data are being collected and interpreted. The Framework was developed for calculating BLM-based criteria when data are available from multiple sampling locations on a stream. The Framework aspires to promote consistency when applying the BLM across datasets of disparate water quality, data quantity, and spatial and temporal representativeness, and is meant to be flexible to maximize applicability over a wide range of scenarios. Therefore, the Framework allows for a certain level of interpretation and adjustment to address the issues unique to each dataset. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  20. Stochastic spatio-temporal model of coral cover as a function of herbivorous grazers, water quality, and coral demographics

    Science.gov (United States)

    Neuhausler, R.; Robinson, M.; Bruna, M.

    2017-12-01

    Over the last 60 years we have seen an increased amount of ecological regime shifts in tropical coastal zones, from coral reefs to macroalgae dominated states, as a result of natural and anthropogenic stresses. However, these shifts are not always immediate- macroalgae are generally present in coral reefs, with their distribution regulated by herbivorous fish. This is especially true in Moorea, French Polynesia, where macroalgae are shown to flourish in spaces that provide refuge from roaming herbivores. While there are currently modeling efforts in projecting ecological regime shifts in Moorea, temporal deterministic models have been utilized, which fail to capture metastability between multiple steady states and can have issues when dealing with very small populations. To address these concerns, we build on these models to account for spatial variations and individual organisms, as well as stochasticity. Our model can project the percent cover of coral, macroalgae, and algae turf as a function of herbivorous grazers, water quality, and coral demographics. Grazers, included as individual fish (particles), evolve according to a kinetic model and interact with neighbouring benthic assemblages, represented as nodes. Water quality and coral demographics are input parameters that can vary over time, allowing our model to be run for temporally changing scenarios and to be adjusted for different reefs. We plan to engage with previous Moorea Reef Resilience Models through a comparative analysis of our models' outcomes and existing Moorea data. Coupling projective models with available data is useful for informing environmental policy and advancing the modeling field.

  1. Individual-based modeling of fish: Linking to physical models and water quality.

    Energy Technology Data Exchange (ETDEWEB)

    Rose, K.A.

    1997-08-01

    The individual-based modeling approach for the simulating fish population and community dynamics is gaining popularity. Individual-based modeling has been used in many other fields, such as forest succession and astronomy. The popularity of the individual-based approach is partly a result of the lack of success of the more aggregate modeling approaches traditionally used for simulating fish population and community dynamics. Also, recent recognition that it is often the atypical individual that survives has fostered interest in the individual-based approach. Two general types of individual-based models are distribution and configuration. Distribution models follow the probability distributions of individual characteristics, such as length and age. Configuration models explicitly simulate each individual; the sum over individuals being the population. DeAngelis et al (1992) showed that, when distribution and configuration models were formulated from the same common pool of information, both approaches generated similar predictions. The distribution approach was more compact and general, while the configuration approach was more flexible. Simple biological changes, such as making growth rate dependent on previous days growth rates, were easy to implement in the configuration version but prevented simple analytical solution of the distribution version.

  2. 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

  3. Agricultural practice and water quality on farms registered for derogation : results for 2009 in the derogation monitoring network

    NARCIS (Netherlands)

    Zwart, M.H.; Daatselaar, C.H.G.; Boumans, L.J.M.; Doornewaard, G.J.

    2001-01-01

    This report provides an overview of fertilisation practices in 2009 and of water quality in 2009 and 2010 on grassland farms that are allowed to use more animal manure than the limit set in the European Nitrates Directive (derogation). Data from this research can be used to study the consequences

  4. Agricultural practice and water quality on farms registered for derogation : results for 2007 in the derogation monitoring network

    NARCIS (Netherlands)

    Zwart, M.H.; Doornewaard, G.J.; Boumans, L.J.M.; Leeuwen, van T.C.; Fraters, B.; Reijs, J.W.

    2009-01-01

    This report provides an overview of fertilisation practices and water quality in 2007 on grassland farms that are allowed to use more livestock manure than the limit set in European legislation (derogation). Data in this report can be used to study the consequences of this derogation on the water

  5. Model My Watershed - A Robust Online App to Enable Citizen Scientists to Model Watershed Hydrology and Water Quality at Regulatory-Level Standards

    Science.gov (United States)

    Daniels, M.; Kerlin, S.; Arscott, D.

    2017-12-01

    Citizen-based watershed monitoring has historically lacked scientific rigor and geographic scope due to limitation in access to watershed-level data and the high level skills and resources required to adequately model watershed dynamics. Public access to watershed information is currently routed through a variety of governmental data portals and often requires advanced geospatial skills to collect and present in useable forms. At the same time, tremendous financial resources are being invested in watershed restoration and management efforts, and often these resources pass through local stakeholder groups such as conservation NGO, watershed interest groups, and local municipalities without extensive hydrologic knowledge or access to sophisticated modeling resources. Even governmental agencies struggle to understand how to best steer or prioritize restoration investments. A new app, Model My Watershed, was built to improve access to watershed data and modeling capabilities in a fast, accessible, free web-app format. Working across the contiguous United States, the Model My Watershed app provides land cover, soils, aerial imagery and relief, watershed delineation, and stream network delineation. Users can model watersheds or areas of interest and create management scenarios to evaluate implementation of land cover changes and best management practice implementation with both hydrologic and water quality outputs that meet TMDL regulatory standards.

  6. [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.

  7. NASA-Modified Precipitation Products to Improve EPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

    Science.gov (United States)

    Nigro, Joseph; Toll, David; Partington, Ed; Ni-Meister, Wenge; Lee, Shihyan; Gutierrez-Magness, Angelica; Engman, Ted; Arsenault, Kristi

    2010-01-01

    The Environmental Protection Agency (EPA) has estimated that over 20,000 water bodies within the United States do not meet water quality standards. Ninety percent of the impairments are typically caused by nonpoint sources. One of the regulations in the Clean Water Act of 1972 requires States to monitor the Total Maximum Daily Load (TMDL), or the amount of pollution that can be carried by a water body before it is determined to be "polluted", for any watershed in the U.S.. In response to this mandate, the EPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a Decision Support Tool (DST) for assessing pollution and to guide the decision making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program -- Fortran (HSPF), computes daily stream flow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA modified/NOAA precipitation data. Using these data within HSPF, stream flow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better stream flow statistics and, ultimately, in improved water quality assessment.

  8. Conjunctively optimizing flash flood control and water quality in urban water reservoirs by model predictive control and dynamic emulation

    Science.gov (United States)

    Galelli, Stefano; Goedbloed, Albert; Schmitter, Petra; Castelletti, Andrea

    2014-05-01

    Urban water reservoirs are a viable adaptation option to account for increasing drinking water demand of urbanized areas as they allow storage and re-use of water that is normally lost. In addition, the direct availability of freshwater reduces pumping costs and diversifies the portfolios of drinking water supply. Yet, these benefits have an associated twofold cost. Firstly, the presence of large, impervious areas increases the hydraulic efficiency of urban catchments, with short time of concentration, increased runoff rates, losses of infiltration and baseflow, and higher risk of flash floods. Secondly, the high concentration of nutrients and sediments characterizing urban discharges is likely to cause water quality problems. In this study we propose a new control scheme combining Model Predictive Control (MPC), hydro-meteorological forecasts and dynamic model emulation to design real-time operating policies that conjunctively optimize water quantity and quality targets. The main advantage of this scheme stands in its capability of exploiting real-time hydro-meteorological forecasts, which are crucial in such fast-varying systems. In addition, the reduced computational requests of the MPC scheme allows coupling it with dynamic emulators of water quality processes. The approach is demonstrated on Marina Reservoir, a multi-purpose reservoir located in the heart of Singapore and characterized by a large, highly urbanized catchment with a short (i.e. approximately one hour) time of concentration. Results show that the MPC scheme, coupled with a water quality emulator, provides a good compromise between different operating objectives, namely flood risk reduction, drinking water supply and salinity control. Finally, the scheme is used to assess the effect of source control measures (e.g. green roofs) aimed at restoring the natural hydrological regime of Marina Reservoir catchment.

  9. IMPROVING THE ACCURACY OF EXTRACTING SURFACE WATER QUALITY LEVELS (SWQLs USING REMOTE SENSING AND ARTIFICIAL NEURAL NETWORK: A CASE STUDY IN THE SAINT JOHN RIVER, CANADA

    Directory of Open Access Journals (Sweden)

    E. Sharaf El Din

    2017-09-01

    Full Text Available Delineating accurate surface water quality levels (SWQLs always presents a great challenge to researchers. Existing methods of assessing surface water quality only provide individual concentrations of monitoring stations without providing the overall SWQLs. Therefore, the results of existing methods are usually difficult to be understood by decision-makers. Conversely, the water quality index (WQI can simplify surface water quality assessment process to be accessible to decision-makers. However, in most cases, the WQI reflects inaccurate SWQLs due to the lack of representative water samples. It is very challenging to provide representative water samples because this process is costly and time consuming. To solve this problem, we introduce a cost-effective method which combines the Landsat-8 imagery and artificial intelligence to develop models to derive representative water samples by correlating concentrations of ground truth water samples to satellite spectral information. Our method was validated and the correlation between concentrations of ground truth water samples and predicted concentrations from the developed models reached a high level of coefficient of determination (R2 > 0.80, which is trustworthy. Afterwards, the predicted concentrations over each pixel of the study area were used as an input to the WQI developed by the Canadian Council of Ministers of the Environment to extract accurate SWQLs, for drinking purposes, in the Saint John River. The results indicated that SWQL was observed as 67 (Fair and 59 (Marginal for the lower and middle basins of the river, respectively. These findings demonstrate the potential of using our approach in surface water quality management.

  10. Improving the Accuracy of Extracting Surface Water Quality Levels (SWQLs) Using Remote Sensing and Artificial Neural Network: a Case Study in the Saint John River, Canada

    Science.gov (United States)

    Sammartano, G.; Spanò, A.

    2017-09-01

    Delineating accurate surface water quality levels (SWQLs) always presents a great challenge to researchers. Existing methods of assessing surface water quality only provide individual concentrations of monitoring stations without providing the overall SWQLs. Therefore, the results of existing methods are usually difficult to be understood by decision-makers. Conversely, the water quality index (WQI) can simplify surface water quality assessment process to be accessible to decision-makers. However, in most cases, the WQI reflects inaccurate SWQLs due to the lack of representative water samples. It is very challenging to provide representative water samples because this process is costly and time consuming. To solve this problem, we introduce a cost-effective method which combines the Landsat-8 imagery and artificial intelligence to develop models to derive representative water samples by correlating concentrations of ground truth water samples to satellite spectral information. Our method was validated and the correlation between concentrations of ground truth water samples and predicted concentrations from the developed models reached a high level of coefficient of determination (R2) > 0.80, which is trustworthy. Afterwards, the predicted concentrations over each pixel of the study area were used as an input to the WQI developed by the Canadian Council of Ministers of the Environment to extract accurate SWQLs, for drinking purposes, in the Saint John River. The results indicated that SWQL was observed as 67 (Fair) and 59 (Marginal) for the lower and middle basins of the river, respectively. These findings demonstrate the potential of using our approach in surface water quality management.

  11. Restoring water quality in the polluted Turag-Tongi-Balu river system, Dhaka: Modelling nutrient and total coliform intervention strategies.

    Science.gov (United States)

    Whitehead, Paul; Bussi, Gianbattista; Hossain, Mohammed Abed; Dolk, Michaela; Das, Partho; Comber, Sean; Peters, Rebecca; Charles, Katrina J; Hope, Rob; Hossain, Md Sarwar

    2018-08-01

    River water quality in rapidly urbanising Asian cities threatens to damage the resource base on which human health, economic growth and poverty reduction all depend. Dhaka reflects the challenges and opportunities for balancing these dynamic and complex trade-offs which goals can be achieved through effective policy interventions. There is a serious problem of water pollution in central Dhaka, in the Turag-Tongi-Balu River system in Bangladesh with the river system being one of the most polluted in the world at the moment. A baseline survey of water chemistry and total coliforms has been undertaken and shows dissolved oxygen close to zero in the dry season, high organic loading together with extreme levels of Ammonium-N and total coliform in the water. Models have been applied to assess hydrochemical processes in the river and evaluate alternative strategies for policy and the management of the pollution issues. In particular models of flow, Nitrate-N, Ammonium-N and indicator bacteria (total coliforms) are applied to simulate water quality in the river system. Various scenarios are explored to clean up the river system, including flow augmentation and improved effluent treatment. The model results indicate that improved effluent treatment is likely to have a more significant impact on reducing Ammonium-N and total coliforms than flow augmentation, but a combined strategy would greatly reduce the pollution problems in the Turag-Tongi-Balu River System. Copyright © 2018. Published by Elsevier B.V.

  12. Fecal coliform management using a coupled hydrodynamics and water quality model for the river Ravi in Pakistan

    International Nuclear Information System (INIS)

    Haider, H.; Ali, W.

    2011-01-01

    A Fecal Coliform (FC) management framework is developed incorporating segmentation of river reaches, hydrodynamic and water quality models and FC management under critical winter low flow conditions for a highly polluted River Ravi. FC die-off rate in the river is determined from a field survey of a selected river reach. The travel time calculated with the help of a hydrodynamic model is 0.25 days in the selected reach. FC die-off rate (Kb) was found to be 1.2 day/sup -1/ at 20 degree C. Model calibration with monitoring data set reveals reasonable agreement of the simulation results with the measured field values under low flow conditions. Presently, the river is receiving raw wastewater and the simulation results shows very high fecal coliform levels up to 100 X 10/sup 6/ MPN/100mL in the river water. These levels are much higher than the required recreation and irrigation standards. Simulations are carried out to assess water quality for the future fecal pollution loads in year 2025 and the results reveal that up to 6 log reduction in FC is required at the wastewater out falls, whereas, 5 log reduction would be sufficient for surface drains to meet desired FC standards under low flow conditions. (author)

  13. An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation.

    Science.gov (United States)

    Fan, Chihhao; Ko, Chun-Han; Wang, Wei-Shen

    2009-04-01

    Water quality modeling has been shown to be a useful tool in strategic water quality management. The present study combines the Qual2K model with the HEC-RAS model to assess the water quality of a tidal river in northern Taiwan. The contaminant loadings of biochemical oxygen demand (BOD), ammonia nitrogen (NH(3)-N), total phosphorus (TP), and sediment oxygen demand (SOD) are utilized in the Qual2K simulation. The HEC-RAS model is used to: (i) estimate the hydraulic constants for atmospheric re-aeration constant calculation; and (ii) calculate the water level profile variation to account for concentration changes as a result of tidal effect. The results show that HEC-RAS-assisted Qual2K simulations taking tidal effect into consideration produce water quality indices that, in general, agree with the monitoring data of the river. Comparisons of simulations with different combinations of contaminant loadings demonstrate that BOD is the most import contaminant. Streeter-Phelps simulation (in combination with HEC-RAS) is also performed for comparison, and the results show excellent agreement with the observed data. This paper is the first report of the innovative use of a combination of the HEC-RAS model and the Qual2K model (or Streeter-Phelps equation) to simulate water quality in a tidal river. The combination is shown to provide an alternative for water quality simulation of a tidal river when available dynamic-monitoring data are insufficient to assess the tidal effect of the river.

  14. Water Quality Criteria

    Science.gov (United States)

    EPA develops water quality criteria based on the latest scientific knowledge to protect human health and aquatic life. This information serves as guidance to states and tribes in adopting water quality standards.

  15. Accelerate Water Quality Improvement

    Science.gov (United States)

    EPA is committed to accelerating water quality improvement and minimizing negative impacts to aquatic life from contaminants and other stressors in the Bay Delta Estuary by working with California Water Boards to strengthen water quality improvement plans.

  16. New England SPARROW Water-Quality Modeling to Assist with the Development of Total Maximum Daily Loads in the Connecticut River Basin

    Science.gov (United States)

    Moore, R. B.; Robinson, K. W.; Simcox, A. C.; Johnston, C. M.

    2002-05-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA) and the New England Interstate Water Pollution Control Commission (NEWIPCC), is currently preparing a water-quality model, called SPARROW, to assist in the regional total maximum daily load (TMDL) studies in New England. A model is required to provide estimates of nutrient loads and confidence intervals at unmonitored stream reaches. SPARROW (Spatially Referenced Regressions on Watershed Attributes) is a spatially detailed, statistical model that uses regression equations to relate total phosphorus and nitrogen (nutrient) stream loads to pollution sources and watershed characteristics. These statistical relations are then used to predict nutrient loads in unmonitored streams. The New England SPARROW model is based on a hydrologic network of 42,000 stream reaches and associated watersheds. Point source data are derived from USEPA's Permit Compliance System (PCS). Information about nonpoint sources is derived from data such as fertilizer use, livestock wastes, and atmospheric deposition. Watershed characteristics include land use, streamflow, time-of-travel, stream density, percent wetlands, slope of the land surface, and soil permeability. Preliminary SPARROW results are expected in Spring 2002. The New England SPARROW model is proposed for use in the TMDL determination for nutrients in the Connecticut River Basin, upstream of Connecticut. The model will be used to estimate nitrogen loads from each of the upstream states to Long Island Sound. It will provide estimates and confidence intervals of phosphorus and nitrogen loads, area-weighted yields of nutrients by watershed, sources of nutrients, and the downstream movement of nutrients. This information will be used to (1) understand ranges in nutrient levels in surface waters, (2) identify the environmental factors that affect nutrient levels in streams, (3) evaluate monitoring efforts for better determination of

  17. Modelling and Analysis of Hydrodynamics and Water Quality for Rivers in the Northern Cold Region of China.

    Science.gov (United States)

    Tang, Gula; Zhu, Yunqiang; Wu, Guozheng; Li, Jing; Li, Zhao-Liang; Sun, Jiulin

    2016-04-08

    In this study, the Mudan River, which is the most typical river in the northern cold region of China was selected as the research object; Environmental Fluid Dynamics Code (EFDC) was adopted to construct a new two-dimensional water quality model for the urban sections of the Mudan River, and concentrations of COD(Cr) and NH₃N during ice-covered and open-water periods were simulated and analyzed. Results indicated that roughness coefficient and comprehensive pollutant decay rate were significantly different in those periods. To be specific, the roughness coefficient in the ice-covered period was larger than that of the open-water period, while the decay rate within the former period was smaller than that in the latter. In addition, according to the analysis of the simulated results, the main reasons for the decay rate reduction during the ice-covered period are temperature drop, upstream inflow decrease and ice layer cover; among them, ice sheet is the major contributor of roughness increase. These aspects were discussed in more detail in this work. The model could be generalized to hydrodynamic water quality process simulation researches on rivers in other cold regions as well.

  18. Modelling and Analysis of Hydrodynamics and Water Quality for Rivers in the Northern Cold Region of China

    Directory of Open Access Journals (Sweden)

    Gula Tang

    2016-04-01

    Full Text Available In this study, the Mudan River, which is the most typical river in the northern cold region of China was selected as the research object; Environmental Fluid Dynamics Code (EFDC was adopted to construct a new two-dimensional water quality model for the urban sections of the Mudan River, and concentrations of CODCr and NH3N during ice-covered and open-water periods were simulated and analyzed. Results indicated that roughness coefficient and comprehensive pollutant decay rate were significantly different in those periods. To be specific, the roughness coefficient in the ice-covered period was larger than that of the open-water period, while the decay rate within the former period was smaller than that in the latter. In addition, according to the analysis of the simulated results, the main reasons for the decay rate reduction during the ice-covered period are temperature drop, upstream inflow decrease and ice layer cover; among them, ice sheet is the major contributor of roughness increase. These aspects were discussed in more detail in this work. The model could be generalized to hydrodynamic water quality process simulation researches on rivers in other cold regions as well.

  19. Development of total maximum daily loads for bacteria impaired watershed using the comprehensive hydrology and water quality simulation model.

    Science.gov (United States)

    Kim, Sang M; Brannan, Kevin M; Zeckoski, Rebecca W; Benham, Brian L

    2014-01-01

    The objective of this study was to develop bacteria total maximum daily loads (TMDLs) for the Hardware River watershed in the Commonwealth of Virginia, USA. The TMDL program is an integrated watershed management approach required by the Clean Water Act. The TMDLs were developed to meet Virginia's water quality standard for bacteria at the time, which stated that the calendar-month geometric mean concentration of Escherichia coli should not exceed 126 cfu/100 mL, and that no single sample should exceed a concentration of 235 cfu/100 mL. The bacteria impairment TMDLs were developed using the Hydrological Simulation Program-FORTRAN (HSPF). The hydrology and water quality components of HSPF were calibrated and validated using data from the Hardware River watershed to ensure that the model adequately simulated runoff and bacteria concentrations. The calibrated and validated HSPF model was used to estimate the contributions from the various bacteria sources in the Hardware River watershed to the in-stream concentration. Bacteria loads were estimated through an extensive source characterization process. Simulation results for existing conditions indicated that the majority of the bacteria came from livestock and wildlife direct deposits and pervious lands. Different source reduction scenarios were evaluated to identify scenarios that meet both the geometric mean and single sample maximum E. coli criteria with zero violations. The resulting scenarios required extreme and impractical reductions from livestock and wildlife sources. Results from studies similar to this across Virginia partially contributed to a reconsideration of the standard's applicability to TMDL development.

  20. 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

  1. Assessing Receiving Water Quality Impacts due to Flow Path Alteration in Residential Catchments, using the Stormwater and Wastewater Management Model

    Science.gov (United States)

    Wolosoff, S. E.; Duncan, J.; Endreny, T.

    2001-05-01

    The Croton water supply system, responsible for supplying approximately 10% of New York City's water, provides an opportunity for exploration into the impacts of significant terrestrial flow path alteration upon receiving water quality. Natural flow paths are altered during residential development in order to allow for construction at a given location, reductions in water table elevation in low lying areas and to provide drainage of increased overland flow volumes. Runoff conducted through an artificial drainage system, is prevented from being attenuated by the natural environment, thus the pollutant removal capacity inherent in most natural catchments is often limited to areas where flow paths are not altered by development. By contrasting the impacts of flow path alterations in two small catchments in the Croton system, with different densities of residential development, we can begin to identify appropriate limits to the re-routing of runoff in catchments draining into surface water supplies. The Stormwater and Wastewater Management Model (SWMM) will be used as a tool to predict the runoff quantity and quality generated from two small residential catchments and to simulate the potential benefits of changes to the existing drainage system design, which may improve water quality due to longer residence times.

  2. Water-quality data for the ground-water network in eastern Broward County, Florida, 1983-84

    Science.gov (United States)

    Waller, B.G.; Cannon, F.L.

    1986-01-01

    During 1983-84, groundwater from 63 wells located at 31 sites throughout eastern Broward County, Florida, was sampled and analyzed to determine baseline water quality conditions. The physical and chemical parameters analyzed included field measurements (pH and temperature), physical characteristics (color, turbidity, and specific conductance), major inorganic ions, nutrients, (nitrogen, phosphorus and carbon), selected metals, and total phenolic compounds. Groundwater samples were collected at the end of the dry season (April) and during the wet season (July and September). These data are tabulated, by well, in this report. (USGS)

  3. Stressor-response modeling using the 2D water quality model and regression trees to predict chlorophyll-a in a reservoir system

    Science.gov (United States)

    In order to control algal blooms, stressor-response relationships between water quality metrics, environmental variables, and algal growth should be understood and modeled. Machine-learning methods were suggested to express stressor-response relationships found by application of mechanistic water qu...

  4. Inland-coastal water interaction: Remote sensing application for shallow-water quality and algal blooms modeling

    Science.gov (United States)

    Melesse, Assefa; Hajigholizadeh, Mohammad; Blakey, Tara

    2017-04-01

    In this study, Landsat 8 and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) sensors were used to model the spatiotemporal changes of four water quality parameters: Landsat 8 (turbidity, chlorophyll-a (chl-a), total phosphate, and total nitrogen) and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) (algal blooms). The study was conducted in Florda bay, south Florida and model outputs were compared with in-situ observed data. The Landsat 8 based study found that, the predictive models to estimate chl-a and turbidity concentrations, developed through the use of stepwise multiple linear regression (MLR), gave high coefficients of determination in dry season (wet season) (R2 = 0.86(0.66) for chl-a and R2 = 0.84(0.63) for turbidity). Total phosphate and TN were estimated using best-fit multiple linear regression models as a function of Landsat TM and OLI,127 and ground data and showed a high coefficient of determination in dry season (wet season) (R2 = 0.74(0.69) for total phosphate and R2 = 0.82(0.82) for TN). Similarly, the ability of SeaWIFS for chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels' benthic class was evaluated. Benthic class was determined through satellite image-based classification methods. It was found that benthic class based chl-a modeling algorithm was better than the existing regionally-tuned approach. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Key words: Landsat, SeaWIFS, water quality, Florida bay, Chl-a, turbidity

  5. Water Quality Assessment in the Harbin Reach of the Songhuajiang River (China Based on a Fuzzy Rough Set and an Attribute Recognition Theoretical Model

    Directory of Open Access Journals (Sweden)

    Yan An

    2014-03-01

    Full Text Available A large number of parameters are acquired during practical water quality monitoring. If all the parameters are used in water quality assessment, the computational complexity will definitely increase. In order to reduce the input space dimensions, a fuzzy rough set was introduced to perform attribute reduction. Then, an attribute recognition theoretical model and entropy method were combined to assess water quality in the Harbin reach of the Songhuajiang River in China. A dataset consisting of ten parameters was collected from January to October in 2012. Fuzzy rough set was applied to reduce the ten parameters to four parameters: BOD5, NH3-N, TP, and F. coli (Reduct A. Considering that DO is a usual parameter in water quality assessment, another reduct, including DO, BOD5, NH3-N, TP, TN, F, and F. coli (Reduct B, was obtained. The assessment results of Reduct B show a good consistency with those of Reduct A, and this means that DO is not always necessary to assess water quality. The results with attribute reduction are not exactly the same as those without attribute reduction, which can be attributed to the α value decided by subjective experience. The assessment results gained by the fuzzy rough set obviously reduce computational complexity, and are acceptable and reliable. The model proposed in this paper enhances the water quality assessment system.

  6. Data Model and Relational Database Design for Highway Runoff Water-Quality Metadata

    Science.gov (United States)

    Granato, Gregory E.; Tessler, Steven

    2001-01-01

    A National highway and urban runoff waterquality metadatabase was developed by the U.S. Geological Survey in cooperation with the Federal Highway Administration as part of the National Highway Runoff Water-Quality Data and Methodology Synthesis (NDAMS). The database was designed to catalog available literature and to document results of the synthesis in a format that would facilitate current and future research on highway and urban runoff. This report documents the design and implementation of the NDAMS relational database, which was designed to provide a catalog of available information and the results of an assessment of the available data. All the citations and the metadata collected during the review process are presented in a stratified metadatabase that contains citations for relevant publications, abstracts (or previa), and reportreview metadata for a sample of selected reports that document results of runoff quality investigations. The database is referred to as a metadatabase because it contains information about available data sets rather than a record of the original data. The database contains the metadata needed to evaluate and characterize how valid, current, complete, comparable, and technically defensible published and available information may be when evaluated for application to the different dataquality objectives as defined by decision makers. This database is a relational database, in that all information is ultimately linked to a given citation in the catalog of available reports. The main database file contains 86 tables consisting of 29 data tables, 11 association tables, and 46 domain tables. The data tables all link to a particular citation, and each data table is focused on one aspect of the information collected in the literature search and the evaluation of available information. This database is implemented in the Microsoft (MS) Access database software because it is widely used within and outside of government and is familiar to many

  7. How does higher frequency monitoring data affect the calibration of a process-based water quality model?

    Science.gov (United States)

    Jackson-Blake, Leah; Helliwell, Rachel

    2015-04-01

    Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, spanning all hydrochemical conditions. However, regulatory agencies and research organisations generally only sample at a fortnightly or monthly frequency, even in well-studied catchments, often missing peak flow events. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by a process-based, semi-distributed catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the Markov Chain Monte Carlo - DiffeRential Evolution Adaptive Metropolis (MCMC-DREAM) algorithm. Calibration to daily data resulted in improved simulation of peak TDP concentrations and improved model performance statistics. Parameter-related uncertainty in simulated TDP was large when fortnightly data was used for calibration, with a 95% credible interval of 26 μg/l. This uncertainty is comparable in size to the difference between Water Framework Directive (WFD) chemical status classes, and would therefore make it difficult to use this calibration to predict shifts in WFD status. The 95% credible interval reduced markedly with the higher frequency monitoring data, to 6 μg/l. The number of parameters that could be reliably auto

  8. 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.

  9. Critical review: Radionuclide transport, sediment transport, and water quality mathematical modeling; and radionuclide adsorption/desorption mechanisms

    Energy Technology Data Exchange (ETDEWEB)

    Onishi, Y.; Serne, R.J.; Arnold, E.M.; Cowan, C.E.; Thompson, F.L. [Pacific Northwest Lab., Richland, WA (United States)

    1981-01-01

    This report describes the results of a detailed literature review of radionuclide transport models applicable to rivers, estuaries, coastal waters, the Great Lakes, and impoundments. Some representatives sediment transport and water quality models were also reviewed to evaluate if they can be readily adapted to radionuclide transport modeling. The review showed that most available transport models were developed for dissolved radionuclide in rivers. These models include the mechanisms of advection, dispersion, and radionuclide decay. Since the models do not include sediment and radionuclide interactions, they are best suited for simulating short-term radionuclide migration where: (1) radionuclides have small distribution coefficients; (2) sediment concentrations in receiving water bodies are very low. Only 5 of the reviewed models include full sediment and radionuclide interactions: CHMSED developed by Fields; FETRA SERATRA, and TODAM developed by Onishi et al, and a model developed by Shull and Gloyna. The 5 models are applicable to cases where: (1) the distribution coefficient is large; (2) sediment concentrations are high; or (3) long-term migration and accumulation are under consideration. The report also discusses radionuclide absorption/desorption distribution ratios and addresses adsorption/desorption mechanisms and their controlling processes for 25 elements under surface water conditions. These elements are: Am, Sb, C, Ce, Cm, Co, Cr, Cs, Eu, I, Fe, Mn, Np, P, Pu, Pm, Ra, Ru, Sr, Tc, Th, {sup 3}H, U, Zn and Zr.

  10. Land use change and conversion effects on ground water quality trends: An integration of land change modeler in GIS and a new Ground Water Quality Index developed by fuzzy multi-criteria group decision-making models.

    Science.gov (United States)

    Shooshtarian, Mohammad Reza; Dehghani, Mansooreh; Margherita, Ferrante; Gea, Oliveri Conti; Mortezazadeh, Shima

    2018-04-01

    This study aggregated Land Change Modeller (LCM) as a useful model in GIS with an extended Groundwater Quality Index (GWQI) developed by fuzzy Multi-Criteria Group Decision-Making models to investigate the effect of land use change and conversion on groundwater quality being supplied for drinking. The model's performance was examined through an applied study in Shiraz, Iran, in a five year period (2011 to 2015). Four land use maps including urban, industrial, garden, and bare were employed in LCM model and the impact of change in area and their conversion to each other on GWQI changes was analysed. The correlation analysis indicated that increase in the urban land use area and conversion of bare to the residential/industrial land uses, had a relation with water quality decrease. Integration of LCM and GWQI can accurately and logically provide a numerical analysis of the possible impact of land use change and conversion, as one of the influencing factors, on the groundwater quality. Hence, the methodology could be used in urban development planning and management in macro level. Copyright © 2018. Published by Elsevier Ltd.

  11. Biological Water Quality Criteria

    Science.gov (United States)

    Page contains links to Technical Documents pertaining to Biological Water Quality Criteria, including, technical assistance documents for states, tribes and territories, program overviews, and case studies.

  12. Modeling Relationships between Surface Water Quality and Landscape Metrics Using the Adaptive Neuro-Fuzzy Inference System, A Case Study in Mazandaran Province

    Directory of Open Access Journals (Sweden)

    mohsen Mirzayi

    2016-03-01

    Full Text Available Landscape indices can be used as an approach for predicting water quality changes to monitor non-point source pollution. In the present study, the data collected over the period from 2012 to 2013 from 81 water quality stations along the rivers flowing in Mazandaran Province were analyzed. Upstream boundries were drawn and landscape metrics were extracted for each of the sub-watersheds at class and landscape levels. Principal component analysis was used to single out the relevant water quality parameters and forward linear regression was employed to determine the optimal metrics for the description of each parameter. The first five components were able to describe 96.61% of the variation in water quality in Mazandaran Province. Adaptive Neuro-fuzzy Inference System (ANFIS and multiple linear regression were used to model the relationship between landscape metrics and water quality parameters. The results indicate that multiple regression was able to predict SAR, TDS, pH, NO3‒, and PO43‒ in the test step, with R2 values equal to 0.81, 0.56, 0.73, 0.44. and 0.63, respectively. The corresponding R2 value of ANFIS in the test step were 0.82, 0.79, 0.82, 0.31, and 0.36, respectively. Clearly, ANFIS exhibited a better performance in each case than did the linear regression model. This indicates a nonlinear relationship between the water quality parameters and landscape metrics. Since different land cover/uses have considerable impacts on both the outflow water quality and the available and dissolved pollutants in rivers, the method can be reasonably used for regional planning and environmental impact assessment in development projects in the region.

  13. Water quality modeling for urban reach of Yamuna river, India (1999-2009), using QUAL2Kw

    Science.gov (United States)

    Sharma, Deepshikha; Kansal, Arun; Pelletier, Greg

    2017-06-01

    The study was to characterize and understand the water quality of the river Yamuna in Delhi (India) prior to an efficient restoration plan. A combination of collection of monitored data, mathematical modeling, sensitivity, and uncertainty analysis has been done using the QUAL2Kw, a river quality model. The model was applied to simulate DO, BOD, total coliform, and total nitrogen at four monitoring stations, namely Palla, Old Delhi Railway Bridge, Nizamuddin, and Okhla for 10 years (October 1999-June 2009) excluding the monsoon seasons (July-September). The study period was divided into two parts: monthly average data from October 1999-June 2004 (45 months) were used to calibrate the model and monthly average data from October 2005-June 2009 (45 months) were used to validate the model. The R2 for CBODf and TN lies within the range of 0.53-0.75 and 0.68-0.83, respectively. This shows that the model has given satisfactory results in terms of R2 for CBODf, TN, and TC. Sensitivity analysis showed that DO, CBODf, TN, and TC predictions are highly sensitive toward headwater flow and point source flow and quality. Uncertainty analysis using Monte Carlo showed that the input data have been simulated in accordance with the prevalent river conditions.

  14. Development and assessment of an integrated ecological modelling framework to assess the effect of investments in wastewater treatment on water quality.

    Science.gov (United States)

    Holguin-Gonzalez, Javier E; Boets, Pieter; Everaert, Gert; Pauwels, Ine S; Lock, Koen; Gobeyn, Sacha; Benedetti, Lorenzo; Amerlinck, Youri; Nopens, Ingmar; Goethals, Peter L M

    2014-01-01

    Worldwide, large investments in wastewater treatment are made to improve water quality. However, the impacts of these investments on river water quality are often not quantified. To assess water quality, the European Water Framework Directive (WFD) requires an integrated approach. The aim of this study was to develop an integrated ecological modelling framework for the River Drava (Croatia) that includes physical-chemical and hydromorphological characteristics as well as the ecological river water quality status. The developed submodels and the integrated model showed accurate predictions when comparing the modelled results to the observations. Dissolved oxygen and nitrogen concentrations (ammonium and organic nitrogen) were the most important variables in determining the ecological water quality (EWQ). The result of three potential investment scenarios of the wastewater treatment infrastructure in the city of Varaždin on the EWQ of the River Drava was assessed. From this scenario-based analysis, it was concluded that upgrading the existing wastewater treatment plant with nitrogen and phosphorus removal will be insufficient to reach a good EWQ. Therefore, other point and diffuse pollution sources in the area should also be monitored and remediated to meet the European WFD standards.

  15. APEX model simulation of edge-of-field water quality benefits from upland buffers

    Science.gov (United States)

    For maximum usefulness, simulation models must be able to estimate the effectiveness of management practices not represented in the dataset used for model calibration. This study focuses on the ability of the Agricultural Policy Environmental eXtender (APEX) to simulate upland buffer effectiveness f...

  16. Establishment and calibration of consensus process model for nitrous oxide dynamics in water quality engineering

    DEFF Research Database (Denmark)

    Domingo-Felez, Carlos

    that enhance cost and energy efficiency in BNR, while maintaining effluent quali-ty. Now, increasing attention is placed on direct emissions of nitrous oxide (N2O) as by-product of BNR; N2O is a greenhouse gas (GHG) with a high warming potential and also an ozone depleting chemical compound. Several N2O...... process modelling efforts aim to reproduce ex-perimental data with mathematical equations, structuring our understanding of the system. Various mechanistic models with different structures describ-ing N2O production have been proposed, but no consensus exists between researchers. Hence, the existing plant......-wide GHG models still lack a complete biological process model that can be integrated in a methodology that assess-es N2O emissions and their impact on overall plant performance. A mathematical model structure that describes N2O production during biological nitrogen removal is proposed. Two autotrophic...

  17. Road traffic impact on urban water quality: a step towards integrated traffic, air and stormwater modelling.

    Science.gov (United States)

    Fallah Shorshani, Masoud; Bonhomme, Céline; Petrucci, Guido; André, Michel; Seigneur, Christian

    2014-04-01

    Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.

  18. Integrated Urban Water Quality Management

    DEFF Research Database (Denmark)

    Rauch, W.; Harremoës, Poul

    1995-01-01

    The basic features of integrated urban water quality management by means of deterministic modeling are outlined. Procedures for the assessment of the detrimental effects in the recipient are presented as well as the basic concepts of an integrated model. The analysis of a synthetic urban drainage...... system provides useful information for water quality management. It is possible to identify the system parameters that contain engineering significance. Continuous simulation of the system performance indicates that the combined nitrogen loading is dominated by the wastewater treatment plant during dry...

  19. Kansas environmental and resource study: A Great Plains model. Monitoring fresh water resources. [water quality of reservoirs

    Science.gov (United States)

    Yarger, H. L. (Principal Investigator); Mccauley, J. R.

    1974-01-01

    The author has identified the following significant results. Processing and analysis of CCT's for numerous ground truth supported passes over Kansas reservoirs has demonstrated that sun angle and atmospheric conditions are strong influences on water reflectance levels as detected by ERTS-1 and can suppress the contributions of true water quality factors. Band ratios, on the other hand, exhibit very little dependence on sun angle and sky conditions and thus are more directly related to water quality. Band ratio levels can be used to reliably determine suspended load. Other water quality indicators appear to have little or no affect on reflectance levels.

  20. Urban water-quality modelling: implementing an extension to Multi-Hydro platform for real case studies

    Science.gov (United States)

    Hong, Yi; Giangola-Murzyn, Agathe; Bonhomme, Celine; Chebbo, Ghassan; Schertzer, Daniel

    2015-04-01

    During the last few years, the physically based and fully distributed numerical platform Multi-Hydro (MH) has been developed to simulate hydrological behaviours in urban/peri-urban areas (El-Tabach et al. , 2009 ; Gires et al., 2013 ; Giangola-Murzyn et al., 2014). This hydro-dynamical platform is open-access and has a modular structure, which is designed to be easily scalable and transportable, in order to simulate the dynamics and complex interactions of the water cycle processes in urban or peri-urban environment (surface hydrology, urban groundwater infrastructures and infiltration). Each hydrological module relies on existing and widely validated open source models, such as TREX model (Velleux, 2005) for the surface module, SWMM model (Rossman, 2010) for the drainage module and VS2DT model (Lappala et al., 1987) for the soil module. In our recent studies, an extension of MH has been set up by connecting the already available water-quality computational components among different modules, to introduce a pollutant transport modelling into the hydro-dynamical platform. As for the surface module in two-dimensions, the concentration of particles in flow is expressed by sediment advection equation, the settling of suspended particles is calculated with a simplified settling velocity formula, while the pollutant wash-off from a given land-use is represented as a mass rate of particle removal from the bottom boundary over time, based on transport capacity, which is computed by a modified form of Universal Soil Loss Equation (USLE). Considering that the USLE is originally conceived to predict soil losses caused by runoff in agriculture areas, several adaptations were needed to use it for urban areas, such as the alterations of USLE parameters according to different criterions, the definition of the appropriate initial dust thickness corresponding to various land-uses, etc. Concerning the drainage module, water quality routing within pipes assumes that the conduit

  1. Modeling Benthic Sediment Processes to Predict Water Quality and Ecology in Narragansett Bay

    Science.gov (United States)

    The benthic sediment acts as a huge reservoir of particulate and dissolved material (within interstitial water) which can contribute to loading of contaminants and nutrients to the water column. A benthic sediment model is presented in this report to predict spatial and temporal ...

  2. Data assimilation in optimizing and integrating soil and water quality water model predictions at different scales

    Science.gov (United States)

    Relevant data about subsurface water flow and solute transport at relatively large scales that are of interest to the public are inherently laborious and in most cases simply impossible to obtain. Upscaling in which fine-scale models and data are used to predict changes at the coarser scales is the...

  3. Storm Water Management Model Reference Manual Volume III – Water Quality

    Science.gov (United States)

    SWMM is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and gene...

  4. MODELING THE RELATIONSHIP BETWEEN SHRIMP MARICULTURE AND WATER QUALITY IN THE RIO CHONE ESTUARY, ECUADOR

    Science.gov (United States)

    The Rio Chone estuary in Ecuador has been heavily altered by the conversion of over 90% of the original mangrove forest to shrimp ponds. We carried out computational experiments using both hydrodynamic and shrimp pond models to investigate factors leading to declines in estuarine...

  5. A bottom-up approach of stochastic demand allocation in water quality modelling

    NARCIS (Netherlands)

    Blokker, E.J.M.; Vreeburg, J.H.G.; Beverloo, H.; Klein Arfman, M.; Van Dijk, J.C.

    2010-01-01

    An “all pipes” hydraulic model of a drinking water distribution system was constructed with two types of demand allocations. One is constructed with the conventional top-down approach, i.e. a demand multiplier pattern from the booster station is allocated to all demand nodes with a correction factor

  6. Predicting the Effects of Water Quality on the Growth of Thalassia testudinum in Tampa Bay with a Dynamic Simile-Based Model Tool

    Science.gov (United States)

    We describe a seagrass growth (SGG) model that is coupled to a water quality (WQ) model that includes the effects of phytoplankton (chlorophyll), colored dissolved organic matter (CDOM) and suspended solids (TSS) on water clarity. Phytoplankton growth was adjusted daily for PAR (...

  7. 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...

  8. Modeling water quality in the middle segment of the Luyano River

    International Nuclear Information System (INIS)

    Valcarcel Rojas, Lino; Alberro Macias, Nancy; Rodriguez GonzalesZahilys; Herrero, Maydel; Borroto Portela, Jorge; Rodrigues Garcez, Anel; Dominguez Catases, Judith; Griffith Martinez, Jose; Derivet Zarzabal, Milagros; Flores Juan, Pedro; Cuesta Borges, Jaime

    2010-01-01

    The methodology for the modelling of three parameters that characterize the quality of water: Biochemical Oxygen Demand, Dissolved Oxygen and ammonium in a stretch of Luyano river using the software RIOSep v.2.0. The procedure combined the use of radiotracer techniques for estimating the hydrodynamic parameters of the current with physicochemical techniques for the determination of its basic parameters. The lifting of the hydrodynamic parameters in the current was conducted with the use of 99mTc as a radiotracer. Simultaneously with flow determination, water was sampled at five stations in the main channel and two tributaries, in order to determine the physicochemical parameters of interest. The result was a model that describes accurately the Biochemical Oxygen Demand and Dissolved Oxygen behaviour (more than 90%), and showed good result for ammonium, so it adequately characterizes the processes of purification and oxygen balance in the water. (Author)

  9. Evaluation of Marsh/Estuarine Water Quality and Ecological Models: An Interim Guide

    Science.gov (United States)

    1982-01-01

    benthic oxygen demand, benthic scour and deposition, photosynthesis and respiration of aquatic plants, and nitrification (Dobbins 1964; O’Connor 1967... photosynthesis , algal respiration, decom- position, and mixing processes play dominant roles, the understanding and characterization of significant pro...Adams, S. M. 1979. "A Mathematical Model of Trophic Dynamics in Estuarine Seagrass Communities," Marsh-Estuarine Systems Simulation, Dame, R. F., ed

  10. Spatial and temporal changes of water quality, and SWAT modeling of Vosvozis river basin, North Greece.

    Science.gov (United States)

    Boskidis, Ioannis; Gikas, Georgios D; Pisinaras, Vassilios; Tsihrintzis, Vassilios A

    2010-09-01

    The results of an investigation of the quantitative and qualitative characteristics of Vosvozis river in Northern Greece is presented. For the purposes of this study, three gaging stations were installed along Vosvozis river, where water quantity and quality measurements were conducted for the period August 2005 to November 2006. Water discharge, temperature, pH, dissolved oxygen (DO) and electrical conductivity (EC) were measured in situ using appropriate equipment. The collected water samples were analyzed in the laboratory for the determination of nitrate, nitrite and ammonium nitrogen, total Kjeldalh nitrogen (TKN), orthophosphate (OP), total phosphorus (TP), COD, and BOD. Agricultural diffuse sources provided the major source of nitrate nitrogen loads during the wet period. During the dry period (from June to October), the major nutrient (N, P) and COD, BOD sources were point sources. The trophic status of Vosvozis river during the monitoring period was determined as eutrophic, based on Dodds classification scheme. Moreover, the SWAT model was used to simulate hydrographs and nutrient loads. SWAT was validated with the measured data. Predicted hydrographs and pollutographs were plotted against observed values and showed good agreement. The validated model was used to test eight alternative scenarios concerning different cropping management approaches. The results of these scenarios indicate that nonpoint source pollution is the prevailing type of pollution in the study area. The SWAT model was found to satisfactorily simulate processes in ephemeral river basins and is an effective tool in water resources management.

  11. Modeling discharge and water quality in a temporary river basin using SWAT model: A case-study on the Ardila river

    OpenAIRE

    Durão, Anabela; Serafim, António; Brito, David; Morais, Manuela

    2012-01-01

    Temporary rivers have a hydrologic variability, which are characterized by long drought periods and short floods events, that influences water quality. Analysis of river flow generated in the Ardila river basin (temporary regime) using precipitation data (from 1931 to 2003) from a weather station, located within the basin, at the Portuguese side (which represents only 22% of the study area) showed a discrepancy between the modeled and observed runoff since 1981. It was also revealed a satisfa...

  12. Effects of soil data resolution on SWAT model stream flow and water quality predictions.

    Science.gov (United States)

    Geza, Mengistu; McCray, John E

    2008-08-01

    The prediction accuracy of agricultural nonpoint source pollution models such as Soil and Water Assessment Tool (SWAT) depends on how well model input spatial parameters describe the characteristics of the watershed. The objective of this study was to assess the effects of different soil data resolutions on stream flow, sediment and nutrient predictions when used as input for SWAT. SWAT model predictions were compared for the two US Department of Agriculture soil databases with different resolution, namely the State Soil Geographic database (STATSGO) and the Soil Survey Geographic database (SSURGO). Same number of sub-basins was used in the watershed delineation. However, the number of HRUs generated when STATSGO and SSURGO soil data were used is 261 and 1301, respectively. SSURGO, with the highest spatial resolution, has 51 unique soil types in the watershed distributed in 1301 HRUs, while STATSGO has only three distributed in 261 HRUS. As a result of low resolution STATSGO assigns a single classification to areas that may have different soil types if SSURGO were used. SSURGO included Hydrologic Response Units (HRUs) with soil types that were generalized to one soil group in STATSGO. The difference in the number and size of HRUs also has an effect on sediment yield parameters (slope and slope length). Thus, as a result of the discrepancies in soil type and size of HRUs stream flow predicted was higher when SSURGO was used compared to STATSGO. SSURGO predicted less stream loading than STATSGO in terms of sediment and sediment-attached nutrients components, and vice versa for dissolved nutrients. When compared to mean daily measured flow, STATSGO performed better relative to SSURGO before calibration. SSURGO provided better results after calibration as evaluated by R(2) value (0.74 compared to 0.61 for STATSGO) and the Nash-Sutcliffe coefficient of Efficiency (NSE) values (0.70 and 0.61 for SSURGO and STATSGO, respectively) although both are in the same satisfactory

  13. MODELING THE IMPACTS OF LAND USE CHANGE ON HYDROLOGY AND WATER QUALITY OF A PACIFIC NORTHWEST WATERSHED

    Science.gov (United States)

    In many parts of the world, aquatic ecosystems are threatened by hydrological and water quality alterations due to extraction and conversion of natural resources for agriculture, urban development, forestry, mining, transportation, and water resources development. To evaluate the...

  14. Evaluating the effectiveness of management practices on hydrology and water quality at watershed scale with a rainfall-runoff model.

    Science.gov (United States)

    Liu, Yaoze; Bralts, Vincent F; Engel, Bernard A

    2015-04-01

    The adverse influence of urban development on hydrology and water quality can be reduced by applying best management practices (BMPs) and low impact development (LID) practices. This study applied green roof, rain barrel/cistern, bioretention system, porous pavement, permeable patio, grass strip, grassed swale, wetland channel, retention pond, detention basin, and wetland basin, on Crooked Creek watershed. The model was calibrated and validated for annual runoff volume. A framework for simulating BMPs and LID practices at watershed scales was created, and the impacts of BMPs and LID practices on water quantity and water quality were evaluated with the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model for 16 scenarios. The various levels and combinations of BMPs/LID practices reduced runoff volume by 0 to 26.47%, Total Nitrogen (TN) by 0.30 to 34.20%, Total Phosphorus (TP) by 0.27 to 47.41%, Total Suspended Solids (TSS) by 0.33 to 53.59%, Lead (Pb) by 0.30 to 60.98%, Biochemical Oxygen Demand (BOD) by 0 to 26.70%, and Chemical Oxygen Demand (COD) by 0 to 27.52%. The implementation of grass strips in 25% of the watershed where this practice could be applied was the most cost-efficient scenario, with cost per unit reduction of $1m3/yr for runoff, while cost for reductions of two pollutants of concern was $445 kg/yr for Total Nitrogen (TN) and $4871 kg/yr for Total Phosphorous (TP). The scenario with very high levels of BMP and LID practice adoption (scenario 15) reduced runoff volume and pollutant loads from 26.47% to 60.98%, and provided the greatest reduction in runoff volume and pollutant loads among all scenarios. However, this scenario was not as cost-efficient as most other scenarios. The L-THIA-LID 2.1 model is a valid tool that can be applied to various locations to help identify cost effective BMP/LID practice plans at watershed scales. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

    Science.gov (United States)

    Jackson-Blake, L. A.; Sample, J. E.; Wade, A. J.; Helliwell, R. C.; Skeffington, R. A.

    2017-07-01

    Catchment-scale water quality models are increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we developed a parsimonious phosphorus model, SimplyP, incorporating a rainfall-runoff model and a biogeochemical model able to simulate daily streamflow, suspended sediment, and particulate and dissolved phosphorus dynamics. The model's complexity was compared to one popular nutrient model, INCA-P, and the performance of the two models was compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP parameters must be determined through calibration, the rest may be based on measurements, while INCA-P has around 40 unmeasurable parameters. Despite substantially simpler process-representation, SimplyP performed comparably to INCA-P in both calibration and validation and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate among the water quality modeling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated.

  16. Multiple linear regression models for predicting chronic aluminum toxicity to freshwater aquatic organisms and developing water quality guidelines.

    Science.gov (United States)

    DeForest, David K; Brix, Kevin V; Tear, Lucinda M; Adams, William J

    2018-01-01

    The bioavailability of aluminum (Al) to freshwater aquatic organisms varies as a function of several water chemistry parameters, including pH, dissolved organic carbon (DOC), and water hardness. We evaluated the ability of multiple linear regression (MLR) models to predict chronic Al toxicity to a green alga (Pseudokirchneriella subcapitata), a cladoceran (Ceriodaphnia dubia), and a fish (Pimephales promelas) as a function of varying DOC, pH, and hardness conditions. The MLR models predicted toxicity values that were within a factor of 2 of observed values in 100% of the cases for P. subcapitata (10 and 20% effective concentrations [EC10s and EC20s]), 91% of the cases for C. dubia (EC10s and EC20s), and 95% (EC10s) and 91% (EC20s) of the cases for P. promelas. The MLR models were then applied to all species with Al toxicity data to derive species and genus sensitivity distributions that could be adjusted as a function of varying DOC, pH, and hardness conditions (the P. subcapitata model was applied to algae and macrophytes, the C. dubia model was applied to invertebrates, and the P. promelas model was applied to fish). Hazardous concentrations to 5% of the species or genera were then derived in 2 ways: 1) fitting a log-normal distribution to species-mean EC10s for all species (following the European Union methodology), and 2) fitting a triangular distribution to genus-mean EC20s for animals only (following the US Environmental Protection Agency methodology). Overall, MLR-based models provide a viable approach for deriving Al water quality guidelines that vary as a function of DOC, pH, and hardness conditions and are a significant improvement over bioavailability corrections based on single parameters. Environ Toxicol Chem 2018;37:80-90. © 2017 SETAC. © 2017 SETAC.

  17. Application of Large-Scale, Multi-Resolution Watershed Modeling Framework Using the Hydrologic and Water Quality System (HAWQS

    Directory of Open Access Journals (Sweden)

    Haw Yen

    2016-04-01

    Full Text Available In recent years, large-scale watershed modeling has been implemented broadly in the field of water resources planning and management. Complex hydrological, sediment, and nutrient processes can be simulated by sophisticated watershed simulation models for important issues such as water resources allocation, sediment transport, and pollution control. Among commonly adopted models, the Soil and Water Assessment Tool (SWAT has been demonstrated to provide superior performance with a large amount of referencing databases. However, it is cumbersome to perform tedious initialization steps such as preparing inputs and developing a model with each changing targeted study area. In this study, the Hydrologic and Water Quality System (HAWQS is introduced to serve as a national-scale Decision Support System (DSS to conduct challenging watershed modeling tasks. HAWQS is a web-based DSS developed and maintained by Texas A & M University, and supported by the U.S. Environmental Protection Agency. Three different spatial resolutions of Hydrologic Unit Code (HUC8, HUC10, and HUC12 and three temporal scales (time steps in daily/monthly/annual are available as alternatives for general users. In addition, users can specify preferred values of model parameters instead of using the pre-defined sets. With the aid of HAWQS, users can generate a preliminarily calibrated SWAT project within a few minutes by only providing the ending HUC number of the targeted watershed and the simulation period. In the case study, HAWQS was implemented on the Illinois River Basin, USA, with graphical demonstrations and associated analytical results. Scientists and/or decision-makers can take advantage of the HAWQS framework while conducting relevant topics or policies in the future.

  18. [Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

    Science.gov (United States)

    Xi, Qing; Li, Zhao-Fu; Luo, Chuan

    2014-05-01

    Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

  19. A Bayesian approach for evaluation of the effect of water quality model parameter uncertainty on TMDLs: A case study of Miyun Reservoir

    International Nuclear Information System (INIS)

    Liang, Shidong; Jia, Haifeng; Xu, Changqing; Xu, Te; Melching, Charles

    2016-01-01

    Facing increasingly serious water pollution, the Chinese government is changing the environmental management strategy from solely pollutant concentration control to a Total Maximum Daily Load (TMDL) program, and water quality models are increasingly being applied to determine the allowable pollutant load in the TMDL. Despite the frequent use of models, few studies have focused on how parameter uncertainty in water quality models affect the allowable pollutant loads in the TMDL program, particularly for complicated and high-dimension water quality models. Uncertainty analysis for such models is limited by time-consuming simulation and high-dimensionality and nonlinearity in parameter spaces. In this study, an allowable pollutant load calculation platform was established using the Environmental Fluid Dynamics Code (EFDC), which is a widely applied hydrodynamic-water quality model. A Bayesian approach, i.e. the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, which is a high-efficiency, multi-chain Markov Chain Monte Carlo (MCMC) method, was applied to assess the effects of parameter uncertainty on the water quality model simulations and its influence on the allowable pollutant load calculation in the TMDL program. Miyun Reservoir, which is the most important surface drinking water source for Beijing, suffers from eutrophication and was selected as a case study. The relations between pollutant loads and water quality indicators are obtained through a graphical method in the simulation platform. Ranges of allowable pollutant loads were obtained according to the results of parameter uncertainty analysis, i.e. Total Organic Carbon (TOC): 581.5–1030.6 t·yr"−"1; Total Phosphorus (TP): 23.3–31.0 t·yr"−"1; and Total Nitrogen (TN): 480–1918.0 t·yr"−"1. The wide ranges of allowable pollutant loads reveal the importance of parameter uncertainty analysis in a TMDL program for allowable pollutant load calculation and margin of safety (MOS

  20. Development, calibration, and analysis of a hydrologic and water-quality model of the Delaware Inland Bays watershed

    Science.gov (United States)

    Gutierrez-Magness, Angelica L.; Raffensperger, Jeff P.

    2003-01-01

    Excessive nutrients and sediment are among the most significant environmental stressors in the Delaware Inland Bays (Rehoboth, Indian River, and Little Assawoman Bays). Sources of nutrients, sediment, and other contaminants within the Inland Bays watershed include point-source discharges from industries and wastewater-treatment plants, runoff and infiltration to ground water from agricultural fields and poultry operations, effluent from on-site wastewater disposal systems, and atmospheric deposition. To determine the most effective restoration methods for the Inland Bays, it is necessary to understand the relative distribution and contribution of each of the possible sources of nutrients, sediment, and other contaminants. A cooperative study involving the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was initiated in 2000 to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed that can be used as a water-resources planning and management tool. The model code Hydrological Simulation Program - FORTRAN (HSPF) was used. The 719-square-kilometer watershed was divided into 45 model segments, and the model was calibrated using streamflow and water-quality data for January 1999 through April 2000 from six U.S. Geological Survey stream-gaging stations within the watershed. Calibration for some parameters was accomplished using PEST, a model-independent parameter estimator. Model parameters were adjusted systematically so that the discrepancies between the simulated values and the corresponding observations were minimized. Modeling results indicate that soil and aquifer permeability, ditching, dominant land-use class, and land-use practices affect the amount of runoff, the mechanism or flow path (surface flow, interflow, or base flow), and the loads of sediment and nutrients. In general, the edge-of-stream total suspended solids yields in the Inland Bays

  1. Application of a simulation model of water quality in the improvement of high basin of Rio Negro - Antioquia

    International Nuclear Information System (INIS)

    Molina Perez, Francisco; Wills Toro, Alvaro; Ramirez Cardona, Juan F

    1995-01-01

    The present article consigns the application of a model of water quality: QUAL2E, of the high basin of the Rio Negro in the East Antioquia. The system Rio Negro was divided in 16 homogeneous tracts, in which 15 seating capacity stations and sampling were located, this way 5 in the Rio Negro and 10 in the main flowing gulches. In the period October of 1993 to May of 1994, they were carried out 10 samplings of quality of the water, coupling this way, the basic data for the hydrological scenarios of summer, intermission and winter. Later on it was carried out the calibration of the pattern for the summer and the validation for winter; the parameters were refined especially suspended solids, dissolved oxygen and DBO5. The use of the pattern allows carrying out the prospective for the quality of the water in the region facilitating a better one taking of decisions in the related with the use of the resource and actions of prevention and control

  2. Using spatially detailed water-quality data and solute-transport modeling to improve support total maximum daily load development

    Science.gov (United States)

    Walton-Day, Katherine; Runkel, Robert L.; Kimball, Briant A.

    2012-01-01

    Spatially detailed mass-loading studies and solute-transport modeling using OTIS (One-dimensional Transport with Inflow and Storage) demonstrate how natural attenuation and loading from distinct and diffuse sources control stream water quality and affect load reductions predicted in total maximum daily loads (TMDLs). Mass-loading data collected during low-flow from Cement Creek (a low-pH, metal-rich stream because of natural and mining sources, and subject to TMDL requirements) were used to calibrate OTIS and showed spatially variable effects of natural attenuation (instream reactions) and loading from diffuse (groundwater) and distinct sources. OTIS simulations of the possible effects of TMDL-recommended remediation of mine sites showed less improvement to dissolved zinc load and concentration (14% decrease) than did the TMDL (53-63% decrease). The TMDL (1) assumed conservative transport, (2) accounted for loads removed by remediation by subtracting them from total load at the stream mouth, and (3) did not include diffuse-source loads. In OTIS, loads were reduced near their source; the resulting concentration was decreased by natural attenuation and increased by diffuse-source loads during downstream transport. Thus, by not including natural attenuation and loading from diffuse sources, the TMDL overestimated remediation effects at low flow. Use of the techniques presented herein could improve TMDLs by incorporating these processes during TMDL development.

  3. Calibration of a water-quality model for low-flow conditions on the Red River of the North at Fargo, North Dakota, and Moorhead, Minnesota, 2003

    Science.gov (United States)

    Lundgren, Robert F.; Nustad, Rochelle A.

    2008-01-01

    A time-of-travel and reaeration-rate study was conducted by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, the Minnesota Pollution Control Agency, and the cities of Fargo, North Dakota, and Moorhead, Minnesota, to provide information to calibrate a water-quality model for streamflows of less than 150 cubic feet per second. Data collected from September 24 through 27, 2003, were used to develop and calibrate the U.S. Environmental Protection Agency Water Quality Analysis Simulation Program model (hereinafter referred to as the Fargo WASP water-quality model) for a 19.2-mile reach of the Red River of the North. The Fargo WASP water-quality model was calibrated for the transport of dye by fitting simulated time-concentration dye curves to measured time-concentration dye curves. Simulated peak concentrations were within 10 percent of measured concentrations. Simulated traveltimes of the dye cloud centroid were within 7 percent of measured traveltimes. The variances of the simulated dye concentrations were similar to the variances of the measured dye concentrations, indicating dispersion was reproduced reasonably well. Average simulated dissolved-oxygen concentrations were within 6 percent of average measured concentrations. Average simulated ammonia concentrations were within the range of measured concentrations. Simulated dissolved-oxygen and ammonia concentrations were affected by the specification of a single nitrification rate in the Fargo WASP water-quality model. Data sets from August 1989 and August 1990 were used to test traveltime and simulation of dissolved oxygen and ammonia. For streamflows that ranged from 60 to 407 cubic feet per second, simulated traveltimes were within 7 percent of measured traveltimes. Measured dissolved-oxygen concentrations were underpredicted by less than 15 percent for both data sets. Results for ammonia were poor; measured ammonia concentrations were underpredicted by as much as 70 percent

  4. Hydrologic and Water-Quality Characterization and Modeling of the Onondaga Lake Basin, Onondaga County, New York

    Science.gov (United States)

    Coon, William F.; Reddy, James E.

    2008-01-01

    Onondaga Lake in Onondaga County, New York, has been identified as one of the Nation?s most contaminated lakes as a result of industrial and sanitary-sewer discharges and stormwater nonpoint sources, and has received priority cleanup status under the national Water Resources Development Act of 1990. A basin-scale precipitation-runoff model of the Onondaga Lake basin was identified as a desirable water-resources management tool to better understand the processes responsible for the generation of loads of sediment and nutrients that are transported to Onondaga Lake. During 2003?07, the U.S. Geological Survey (USGS) developed a model based on the computer program, Hydrological Simulation Program?FORTRAN (HSPF), which simulated overland flow to, and streamflow in, the major tributaries of Onondaga Lake, and loads of sediment, phosphorus, and nitrogen transported to the lake. The simulation period extends from October 1997 through September 2003. The Onondaga Lake basin was divided into 107 subbasins and within these subbasins, the land area was apportioned among 19 pervious and impervious land types on the basis of land use and land cover, hydrologic soil group (HSG), and aspect. Precipitation data were available from three sources as input to the model. The model simulated streamflow, water temperature, concentrations of dissolved oxygen, and concentrations and loads of sediment, orthophosphate, total phosphorus, nitrate, ammonia, and organic nitrogen in the four major tributaries to Onondaga Lake?Onondaga Creek, Harbor Brook, Ley Creek, and Ninemile Creek. Simulated flows were calibrated to data from nine USGS streamflow-monitoring sites; simulated nutrient concentrations and loads were calibrated to data collected at six of the nine streamflow-monitoring sites. Water-quality samples were collected, processed, and analyzed by personnel from the Onondaga County Department of Water Environment Protection. Several time series of flow, and sediment and nutrient loads

  5. Water Quality Protection Charges

    Data.gov (United States)

    Montgomery County of Maryland — The Water Quality Protection Charge (WQPC) is a line item on your property tax bill. WQPC funds many of the County's clean water initiatives including: • Restoration...

  6. Water Quality Data (WQX)

    Science.gov (United States)

    The STORET (short for STOrage and RETrieval) Data Warehouse is a repository for water quality, biological, and physical data and is used by state environmental agencies, EPA and other federal agencies, universities, private citizens, and many others.

  7. Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida.

    Science.gov (United States)

    Haji Gholizadeh, Mohammad; Melesse, Assefa M; Reddi, Lakshmi

    2016-10-01

    In this study, principal component analysis (PCA), factor analysis (FA), and the absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling technique were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, 15years (2000-2014) dataset of 12 water quality variables covering 16 monitoring stations, and approximately 35,000 observations was used. The PCA/FA method identified five and four potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules and causes were explained. The APCS-MLR apportioned their contributions to each water quality variable. Results showed that the point source pollution discharges from anthropogenic factors due to the discharge of agriculture waste and domestic and industrial wastewater were the major sources of river water contamination. Also, the studied variables were categorized into three groups of nutrients (total kjeldahl nitrogen, total phosphorus, total phosphate, and ammonia-N), water murkiness conducive parameters (total suspended solids, turbidity, and chlorophyll-a), and salt ions (magnesium, chloride, and sodium), and average contributions of different potential pollution sources to these categories were considered separately. The data matrix was also subjected to PMF receptor model using the EPA PMF-5.0 program and the two-way model described was performed for the PMF analyses. Comparison of the obtained results of PMF and APCS-MLR models showed that there were some significant differences in estimated contribution for each potential pollution source, especially in the wet season. Eventually, it was concluded that the APCS-MLR receptor modeling approach appears to be more physically plausible for the current study. It is believed that the results of apportionment could be very useful to the local authorities for the control and

  8. The impact of agricultural activities on water quality: a case for collaborative catchment-scale management using integrated wireless sensor networks

    OpenAIRE

    Zia, Huma; Harris, Nick; Merrett, Geoff V.; Rivers, Mark; Coles, Neil

    2013-01-01

    The challenge of improving water quality is a growing global concern, typified by the European Commission Water Framework Directive and the United States Clean Water Act. The main drivers of poor water quality are economics, poor water management, agricultural practices and urban development. This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions. Water quality monitoring (WQM) is cu...

  9. A three-dimensional water quality modeling approach for exploring the eutrophication responses to load reduction scenarios in Lake Yilong (China)

    International Nuclear Information System (INIS)

    Zhao, Lei; Li, Yuzhao; Zou, Rui; He, Bin; Zhu, Xiang; Liu, Yong; Wang, Junsong; Zhu, Yongguan

    2013-01-01

    Lake Yilong in Southwestern China has been under serious eutrophication threat during the past decades; however, the lake water remained clear until sudden sharp increase in Chlorophyll a (Chl a) and turbidity in 2009 without apparent change in external loading levels. To investigate the causes as well as examining the underlying mechanism, a three-dimensional hydrodynamic and water quality model was developed, simulating the flow circulation, pollutant fate and transport, and the interactions between nutrients, phytoplankton and macrophytes. The calibrated and validated model was used to conduct three sets of scenarios for understanding the water quality responses to various load reduction intensities and ecological restoration measures. The results showed that (a) even if the nutrient loads is reduced by as much as 77%, the Chl a concentration decreased only by 50%; and (b) aquatic vegetation has strong interaction with phytoplankton, therefore requiring combined watershed and in-lake management for lake restoration. -- Highlights: ► We quantitatively investigated the non-linear lake responses to load reduction. ► The aquatic ecological condition had a great impact on algal blooms. ► Only water quality improvement cannot ensure the aquatic ecology restoration. -- The lake water quality responds to watershed load reduction in a nonlinear way, which requires combined watershed and in-lake management for lake restoration

  10. Collaborative networks: Reference modeling

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

  11. 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.

  12. 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.

  13. Water Quality Assessment and Management

    Science.gov (United States)

    Overview of Clean Water Act (CWA) restoration framework including; water quality standards, monitoring/assessment, reporting water quality status, TMDL development, TMDL implementation (point & nonpoint source control)

  14. Operational monitoring and forecasting of bathing water quality through exploiting satellite Earth observation and models: The AlgaRisk demonstration service

    Science.gov (United States)

    Shutler, J. D.; Warren, M. A.; Miller, P. I.; Barciela, R.; Mahdon, R.; Land, P. E.; Edwards, K.; Wither, A.; Jonas, P.; Murdoch, N.; Roast, S. D.; Clements, O.; Kurekin, A.

    2015-04-01

    Coastal zones and shelf-seas are important for tourism, commercial fishing and aquaculture. As a result the importance of good water quality within these regions to support life is recognised worldwide and a number of international directives for monitoring them now exist. This paper describes the AlgaRisk water quality monitoring demonstration service that was developed and operated for the UK Environment Agency in response to the microbiological monitoring needs within the revised European Union Bathing Waters Directive. The AlgaRisk approach used satellite Earth observation to provide a near-real time monitoring of microbiological water quality and a series of nested operational models (atmospheric and hydrodynamic-ecosystem) provided a forecast capability. For the period of the demonstration service (2008-2013) all monitoring and forecast datasets were processed in near-real time on a daily basis and disseminated through a dedicated web portal, with extracted data automatically emailed to agency staff. Near-real time data processing was achieved using a series of supercomputers and an Open Grid approach. The novel web portal and java-based viewer enabled users to visualise and interrogate current and historical data. The system description, the algorithms employed and example results focussing on a case study of an incidence of the harmful algal bloom Karenia mikimotoi are presented. Recommendations and the potential exploitation of web services for future water quality monitoring services are discussed.

  15. Economic Time Series Modeling to Determine the Feasibility of Incorporating Drinking Water Treatment in Water Quality Trading

    Science.gov (United States)

    The critical steps required to evaluating the feasiblity of establishing a water quality trading market in a testbed watershed is described. Focus is given toward describing the problem of thin markets as a specifi barrier to successful trading. Economic theory for considering an...

  16. A Systems Approach to Manage Drinking Water Quality through Integrated Model Projections, Adaptive Monitoring and Process Optimization - abstract

    Science.gov (United States)

    Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate...

  17. A Systems Approach to Manage Drinking Water Quality through Integrated Model Projections, Adaptive Monitoring and Process Optimization

    Science.gov (United States)

    Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate...

  18. Prediction of harmful water quality parameters combining weather, air quality and ecosystem models with in situ measurement

    Science.gov (United States)

    The ability to predict water quality in lakes is important since lakes are sources of water for agriculture, drinking, and recreational uses. Lakes are also home to a dynamic ecosystem of lacustrine wetlands and deep waters. They are sensitive to pH changes and are dependent on d...

  19. Sediment transport, light and algal growth in the Markermeer : a two-dimensional water quality model for a shallow lake

    NARCIS (Netherlands)

    Duin, van E.H.S.

    1992-01-01

    This thesis reports on a study of the water quality in the Markermeer, focusing on the relationships between sediment transport, the light field and the growth of Oscillatoria agardhii . The study comprises two aspects: an extensive data collection program with the data

  20. Can There Ever Be Enough to Impact Water Quality? Evaluating BMPs in Elliot Ditch, Indiana Using the LTHIA-LID Model

    Science.gov (United States)

    Rahman, M. S.; Hoover, F. A.; Bowling, L. C.

    2017-12-01

    Elliot Ditch is an urban/urbanizing watershed located in the city of Lafayette, IN, USA. The city continues to struggle with stormwater management and combined sewer overflow (CSO) events. Several best-management practices (BMP) such as rain gardens, green roofs, and bioswales have been implemented in the watershed, but the level of adoption needed to achieve meaningful impact is currently unknown. This study's goal is to determine what level of BMP coverage is needed to impact water quality, whether meaningful impact is determined by achieving water quality targets or statistical significance. A power analysis was performed using water quality data for total suspended solids (TSS), E.coli, total phosphorus (TP) and nitrate (NO3-N) from Elliot Ditch from 2011 to 2015. The minimum detectable difference (MDD) was calculated as the percent reduction in load needed to detect a significant change in the watershed. The water quality targets were proposed by stakeholders as part of a watershed management planning process. The water quality targets and the MDD percentages were then compared to simulated load reductions due to BMP implementation using the Long-term Hydrologic Impact Assessment-Low Impact Development (LTHIA-LID) model. Seven baseline model scenarios were simulated by implementing the maximum number of each of six types of BMPs (rain barrels, permeable patios, green roofs, grassed swale/bioswales, bioretention/rain gardens, and porous pavement), as well as all the practices combined in the watershed. These provide the baseline for targeted implementation scenarios designed to determine if statistically and physically meaningful load reductions can be achieved through BMP implementation alone.

  1. The role of pesticide fate modelling in a prevention-led approach to potable water quality management

    Science.gov (United States)

    Dolan, Tom; Pullan, Stephanie; Whelan, Mick; Parsons, David

    2013-04-01

    Diffuse inputs from agriculture are commonly the main source of pesticide contamination in surface water and may have implications for the quality of treated drinking water. After privatisation in 1991, UK water companies primarily focused on the provision of sufficient water treatment to reduce the risk of non-compliance with the European Drinking Water Directive (DWD), under which all pesticide concentrations must be below 0.1µg/l and UK Water Supply Regulations for the potable water they supply. Since 2000, Article 7 of the Water Framework Directive (WFD) has begun to drive a prevention-led approach to compliance with the DWD. As a consequence water companies are now more interested in the quality of 'raw' (untreated) water at the point of abstraction. Modelling (based upon best available estimates of cropping, pesticide use, weather conditions, pesticide characteristics, and catchment characteristics) and monitoring of raw water quality can both help to determine the compliance risks associated with the quality of this 'raw' water resource. This knowledge allows water companies to prioritise active substances for action in their catchments, and is currently used in many cases to support the design of monitoring programmes for pesticide active substances. Additional value can be provided if models are able to help to identify the type and scale of catchment management interventions required to achieve DWD compliance for pesticide active substances through pollution prevention at source or along transport pathways. These questions were explored using a simple catchment-scale pesticide fate and transport model. The model employs a daily time-step and is semi-lumped with calculations performed for soil type and crop combinations, weighted by their proportions within the catchment. Soil properties are derived from the national soil database and the model can, therefore, be applied to any catchment in England and Wales. Various realistic catchment management

  2. Results of Geoenvironmental Studies (2013-2014) Applied to a Monitoring Water Quality Network in Real Time in the Atoyac River (upstream) Puebla, Mexico.

    Science.gov (United States)

    Rodriguez-Espinosa, P. F.; Tavera, E. M.; Morales-Garcia, S. S.; Muñoz-Sevilla, N. P.

    2014-12-01

    Results of geoenvironment studies, referents to geochemistry, weathering, size, mineral composition, and metals contained in sediments and physicochemical parameters of water in urban rivers associated with dam are presented. Emphasis on the interpretation of these results, was detect environmental susceptibility areas associated at the water quality in Upper basin of Atoyac River, Puebla, Mexico. The environmental sub secretary of the state government of Puebla, Mexico has initiated actions to clean up the urban Atoyac River, with measurements of physicochemical parameters associated of the water quality in real-time monitoring and sampling network along the river. The results identified an important role in the rivers, not only to receive and transport the contaminants associated with sedimentological and geochemical conditions, but magnified the effects of pollutant discharges. A significant concentration of hazardous metals in sediments of the dam, reflecting the geo-environmental conditions of anthropogenic Valsequillo Dam induction was determined. For example, a moderately contaminated Pb contaminated extreme class, and Cu and Zn contaminated with moderate to heavy contaminated under geoenvironment class index. Large concentration of clay minerals with larger surface areas was found there in the study, the minerals are definitely the fittest in nature to accept on their surfaces constitution of metals, metalloids and other contaminants which were reflected in the Geoenvironmental index. The results of the studies performed here enable us to locate monitoring stations and sampling network to physicochemical parameters in real time, in the areas of higher contamination found in geoenvironmental studies Atoyac High River Basin. Similarly, we can elucidate the origin of pollutants and monitoring agents reflected in BOD5 (223 mg / l) and COD (610 mg / l), suspended solids totals (136 mg / l) and dissolved solids totals (840 mg / l), in others. Recent hydrometric

  3. Minerals Policy Monitoring Programme : : results for 2006 on water quality and fertilisation practices : within the framework of the derogation monitoring network

    NARCIS (Netherlands)

    Fraters, B.; Reijs, J.W.; Leeuwen, van T.C.; Bouwmans, L.J.M.

    2008-01-01

    This report provides an overview of fertilisation practices and water quality in 2006 on grassland farms using more animal manure than the limit set in European legislation. Water quality measured in 2006 is related to agricultural practices in previous years, and the reported values do not reveal

  4. Modeling the cadmium balance in Australian agricultural systems in view of potential impacts on food and water quality

    International Nuclear Information System (INIS)

    Vries, W. de; McLaughlin, M.J.

    2013-01-01

    The historical build up and future cadmium (Cd) concentrations in top soils and in crops of four Australian agricultural systems are predicted with a mass balance model, focusing on the period 1900–2100. The systems include a rotation of dryland cereals, a rotation of sugarcane and peanuts/soybean, intensive dairy production and intensive horticulture. The input of Cd to soil is calculated from fertilizer application and atmospheric deposition and also examines options including biosolid and animal manure application in the sugarcane rotation and dryland cereal production systems. Cadmium output from the soil is calculated from leaching to deeper horizons and removal with the harvested crop or with livestock products. Parameter values for all Cd fluxes were based on a number of measurements on Australian soil–plant systems. In the period 1900–2000, soil Cd concentrations were predicted to increase on average between 0.21 mg kg −1 in dryland cereals, 0.42 mg kg −1 in intensive agriculture and 0.68 mg kg −1 in dairy production, which are within the range of measured increases in soils in these systems. Predicted soil concentrations exceed critical soil Cd concentrations, based on food quality criteria for Cd in crops during the simulation period in clay-rich soils under dairy production and intensive horticulture. Predicted dissolved Cd concentrations in soil pore water exceed a ground water quality criterion of 2 μg l −1 in light textured soils, except for the sugarcane rotation due to large water leaching fluxes. Results suggest that the present fertilizer Cd inputs in Australia are in excess of the long-term critical loads in heavy-textured soils for dryland cereals and that all other systems are at low risk. Calculated critical Cd/P ratios in P fertilizers vary from 1000 mg Cd kg P −1 for the different soil, crop and environmental conditions applied. - Highlights: • Cadmium concentrations in soils and plants are predicted with a mass balance

  5. Modeling the cadmium balance in Australian agricultural systems in view of potential impacts on food and water quality

    Energy Technology Data Exchange (ETDEWEB)

    Vries, W. de, E-mail: wim.devries@wur.nl [Alterra-Wageningen University and Research Centre, PO Box 47, 6700 AA Wageningen (Netherlands); Environmental Systems Analysis Group, Wageningen University, PO Box 47, 6700 AA Wageningen (Netherlands); McLaughlin, M.J. [CSIRO Sustainable Agriculture Flagship, CSIRO Land and Water, PMB 2, Glen Osmond, South Australia 5064 (Australia); University of Adelaide, PMB 1, Glen Osmond, South Australia 5064 (Australia)

    2013-09-01

    The historical build up and future cadmium (Cd) concentrations in top soils and in crops of four Australian agricultural systems are predicted with a mass balance model, focusing on the period 1900–2100. The systems include a rotation of dryland cereals, a rotation of sugarcane and peanuts/soybean, intensive dairy production and intensive horticulture. The input of Cd to soil is calculated from fertilizer application and atmospheric deposition and also examines options including biosolid and animal manure application in the sugarcane rotation and dryland cereal production systems. Cadmium output from the soil is calculated from leaching to deeper horizons and removal with the harvested crop or with livestock products. Parameter values for all Cd fluxes were based on a number of measurements on Australian soil–plant systems. In the period 1900–2000, soil Cd concentrations were predicted to increase on average between 0.21 mg kg{sup −1} in dryland cereals, 0.42 mg kg{sup −1} in intensive agriculture and 0.68 mg kg{sup −1} in dairy production, which are within the range of measured increases in soils in these systems. Predicted soil concentrations exceed critical soil Cd concentrations, based on food quality criteria for Cd in crops during the simulation period in clay-rich soils under dairy production and intensive horticulture. Predicted dissolved Cd concentrations in soil pore water exceed a ground water quality criterion of 2 μg l{sup −1} in light textured soils, except for the sugarcane rotation due to large water leaching fluxes. Results suggest that the present fertilizer Cd inputs in Australia are in excess of the long-term critical loads in heavy-textured soils for dryland cereals and that all other systems are at low risk. Calculated critical Cd/P ratios in P fertilizers vary from < 50 to > 1000 mg Cd kg P{sup −1} for the different soil, crop and environmental conditions applied. - Highlights: • Cadmium concentrations in soils and plants

  6. Stable isotopes and mercury in a model estuarine fish: Multibasin comparisons with water quality, community structure, and available prey base

    Energy Technology Data Exchange (ETDEWEB)

    Adams, Douglas H., E-mail: Doug.Adams@MyFWC.com; Paperno, Richard

    2012-01-01

    Stable-isotope ratios ({delta}{sup 13}C and {delta}{sup 15}N) and mercury in a model predator, and associated prey community assessments were used to make inferences regarding food web relationships and how these relationships are influenced by habitat variability and anthropogenic factors. Although interconnected, the three major basins of the Indian River Lagoon system on the Atlantic coast of Florida comprise noticeably different available habitat types with spatially distinct faunal communities and available prey for spotted seatrout, Cynoscion nebulosus, a model predatory fish species. Water quality, degree of urbanization, human population density, and levels of nitrogen enrichment clearly differ between these representative estuarine basins. The differences can influence feeding ecology and therefore result in different mercury concentrations and different stable-isotope signatures of spotted seatrout between basins. Mercury concentrations in spotted seatrout were greatest in Mosquito Lagoon (ML) and least in the Indian River Lagoon proper (IRL), although concentrations were low for all basins. Spotted seatrout from IRL were carbon-depleted and nitrogen-enriched compared with those from the other basins; this suggests either that the fish's primary source of carbon in IRL is an algae- or phytoplankton-based food web or that the pathway through the food web is shorter there. The {delta}{sup 15}N values of IRL spotted seatrout were greater than those in the Banana River Lagoon or ML, suggesting slightly different trophic positioning of fish in these basins. The greater {delta}{sup 15}N values in IRL spotted seatrout may also reflect the greater human population density and resultant anthropogenic inputs (e.g., observed higher total nitrogen levels) in IRL compared with the other more pristine basins examined. Understanding species' responses to broad-scale habitat heterogeneity in estuaries and knowing basin-specific differences in stable isotopes

  7. Macrophyte and pH buffering updates to the Klamath River water-quality model upstream of Keno Dam, Oregon

    Science.gov (United States)

    Sullivan, Annett B.; Rounds, Stewart A.; Asbill-Case, Jessica R.; Deas, Michael L.

    2013-01-01

    A hydrodynamic, water temperature, and water-quality model of the Link River to Keno Dam reach of the upper Klamath River was updated to account for macrophytes and enhanced pH buffering from dissolved organic matter, ammonia, and orthophosphorus. Macrophytes had been observed in this reach by field personnel, so macrophyte field data were collected in summer and fall (June-October) 2011 to provide a dataset to guide the inclusion of macrophytes in the model. Three types of macrophytes were most common: pondweed (Potamogeton species), coontail (Ceratophyllum demersum), and common waterweed (Elodea canadensis). Pondweed was found throughout the Link River to Keno Dam reach in early summer with densities declining by mid-summer and fall. Coontail and common waterweed were more common in the lower reach near Keno Dam and were at highest density in summer. All species were most dense in shallow water (less than 2 meters deep) near shore. The highest estimated dry weight biomass for any sample during the study was 202 grams per square meter for coontail in August. Guided by field results, three macrophyte groups were incorporated into the CE-QUAL-W2 model for calendar years 2006-09. The CE-QUAL-W2 model code was adjusted to allow the user to initialize macrophyte populations spatially across the model grid. The default CE-QUAL-W2 model includes pH buffering by carbonates, but does not include pH buffering by organic matter, ammonia, or orthophosphorus. These three constituents, especially dissolved organic matter, are present in the upper Klamath River at concentrations that provide substantial pH buffering capacity. In this study, CE-QUAL-W2 was updated to include this enhanced buffering capacity in the simulation of pH. Acid dissociation constants for ammonium and phosphoric acid were taken from the literature. For dissolved organic matter, the number of organic acid groups and each group's acid dissociation constant (Ka) and site density (moles of sites per mole of

  8. A hydro-optical model for deriving water quality variables from satellite images (HydroSat): A case study of the Nile River demonstrating the future Sentinel-2 capabilities

    NARCIS (Netherlands)

    Salama, M.; Radwan, M.; van der Velde, R.

    2012-01-01

    This paper describes a hydro-optical model for deriving water quality variables from satellite images, hereafter HydroSat. HydroSat corrects images for atmospheric interferences and simultaneously retrieves water quality variables. An application of HydroSat to Landsat Enhanced Thematic Mapper (ETM)

  9. Hydrodynamic modelling of the influence of stormwater and combined sewer overflows on receiving water quality: Benzo(a)pyrene and copper risks to recreational water.

    Science.gov (United States)

    Björklund, Karin; Bondelind, Mia; Karlsson, Anna; Karlsson, Dick; Sokolova, Ekaterina

    2018-02-01

    The risk from chemical substances in surface waters is often increased during wet weather, due to surface runoff, combined sewer overflows (CSOs) and erosion of contaminated land. There are strong incentives to improve the quality of surface waters affected by human activities, not only from ecotoxicity and ecosystem health perspectives, but also for drinking water and recreational purposes. The aim of this study is to investigate the influence of urban stormwater discharges and CSOs on receiving water in the context of chemical health risks and recreational water quality. Transport of copper (Cu) and benzo[a]pyrene (BaP) in the Göta River (Sweden) was simulated using a hydrodynamic model. Within the 16 km modelled section, 35 CSO and 16 urban stormwater point discharges, as well as the effluent from a major wastewater treatment plant, were included. Pollutant concentrations in the river were simulated for two rain events and investigated at 13 suggested bathing sites. The simulations indicate that water quality guideline values for Cu are exceeded at several sites, and that stormwater discharges generally give rise to higher Cu and BaP concentrations than CSOs. Due to the location of point discharges and the river current inhibiting lateral mixing, the north shore of the river is better suited for bathing. Peak concentrations have a short duration; increased concentrations of the pollutants may however be present for several days after a rain event. Monitoring of river water quality indicates that simulated Cu and BaP concentrations are in the same order of magnitude as measured concentrations. It is concluded that hydrodynamic modelling is a useful tool for identifying suitable bathing sites in urban surface waters and areas of concern where mitigation measures should be implemented to improve water quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Water Quality and Sedimentation Data of the Coastal Intensive Site Network (CISNet) Long Term Monitoring Sites in Kaneohe Bay, Oahu, Hawaii from 1998 to 2001 (NODC Accession 0001473)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A long term project to monitor water quality and sediment processes in Kaneohe Bay was initiated in November 1998 and continued through July 2001. Four primary sites...

  11. Use of Multiple Linear Regression Models for Setting Water Quality Criteria for Copper: A Complementary Approach to the Biotic Ligand Model.

    Science.gov (United States)

    Brix, Kevin V; DeForest, David K; Tear, Lucinda; Grosell, Martin; Adams, William J

    2017-05-02

    Biotic Ligand Models (BLMs) for metals are widely applied in ecological risk assessments and in the development of regulatory water quality guidelines in Europe, and in 2007 the United States Environmental Protection Agency (USEPA) recommended BLM-based water quality criteria (WQC) for Cu in freshwater. However, to-date, few states have adopted BLM-based Cu criteria into their water quality standards on a state-wide basis, which appears to be due to the perception that the BLM is too complicated or requires too many input variables. Using the mechanistic BLM framework to first identify key water chemistry parameters that influence Cu bioavailability, namely dissolved organic carbon (DOC), pH, and hardness, we developed Cu criteria using the same basic methodology used by the USEPA to derive hardness-based criteria but with the addition of DOC and pH. As an initial proof of concept, we developed stepwise multiple linear regression (MLR) models for species that have been tested over wide ranges of DOC, pH, and hardness conditions. These models predicted acute Cu toxicity values that were within a factor of ±2 in 77% to 97% of tests (5 species had adequate data) and chronic Cu toxicity values that were within a factor of ±2 in 92% of tests (1 species had adequate data). This level of accuracy is comparable to the BLM. Following USEPA guidelines for WQC development, the species data were then combined to develop a linear model with pooled slopes for each independent parameter (i.e., DOC, pH, and hardness) and species-specific intercepts using Analysis of Covariance. The pooled MLR and BLM models predicted species-specific toxicity with similar precision; adjusted R 2 and R 2 values ranged from 0.56 to 0.86 and 0.66-0.85, respectively. Graphical exploration of relationships between predicted and observed toxicity, residuals and observed toxicity, and residuals and concentrations of key input parameters revealed many similarities and a few key distinctions between the

  12. A spatially distributed model for assessment of the effects of changing land use and climate on urban stream quality: Development of a Spatially Distributed Urban Water Quality Model

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Ning [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Pacific Northwest National Laboratory, Richland WA USA; Yearsley, John [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Baptiste, Marisa [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Cao, Qian [Department of Geography, University of California Los Angeles, Los Angeles CA USA; Lettenmaier, Dennis P. [Department of Geography, University of California Los Angeles, Los Angeles CA USA; Nijssen, Bart [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA

    2016-08-22

    While the effects of land use change in urban areas have been widely examined, the combined effects of climate and land use change on the quality of urban and urbanizing streams have received much less attention. We describe a modeling framework that is applicable to the evaluation of potential changes in urban water quality and associated hydrologic changes in response to ongoing climate and landscape alteration. The grid-based spatially distributed model, DHSVM-WQ, is an outgrowth of the Distributed Hydrology-Soil-Vegetation Model (DHSVM) that incorporates modules for assessing hydrology and water quality in urbanized watersheds at a high spatial and temporal resolution. DHSVM-WQ simulates surface runoff quality and in-stream processes that control the transport of nonpoint-source (NPS) pollutants into urban streams. We configure DHSVM-WQ for three partially urbanized catchments in the Puget Sound region to evaluate the water quality responses to current conditions and projected changes in climate and/or land use over the next century. Here we focus on total suspended solids (TSS) and total phosphorus (TP) from nonpoint sources (runoff), as well as stream temperature. The projection of future land use is characterized by a combination of densification in existing urban or partially urban areas, and expansion of the urban footprint. The climate change scenarios consist of individual and concurrent changes in temperature and precipitation. Future precipitation is projected to increase in winter and decrease in summer, while future temperature is projected to increase throughout the year. Our results show that urbanization has a much greater effect than climate change on both the magnitude and seasonal variability of streamflow, TSS and TP loads largely due to substantially increased streamflow, and particularly winter flow peaks. Water temperature is more sensitive to climate warming scenarios than to urbanization and precipitation changes. Future urbanization and

  13. Purified water quality study

    International Nuclear Information System (INIS)

    Spinka, H.; Jackowski, P.

    2000-01-01

    Argonne National Laboratory (HEP) is examining the use of purified water for the detection medium in cosmic ray sensors. These sensors are to be deployed in a remote location in Argentina. The purpose of this study is to provide information and preliminary analysis of available water treatment options and associated costs. This information, along with the technical requirements of the sensors, will allow the project team to determine the required water quality to meet the overall project goals

  14. Water Quality Monitoring

    Science.gov (United States)

    2002-01-01

    With the backing of NASA, researchers at Michigan State University, the University of Minnesota, and the University of Wisconsin have begun using satellite data to measure lake water quality and clarity of the lakes in the Upper Midwest. This false color IKONOS image displays the water clarity of the lakes in Eagan, Minnesota. Scientists measure the lake quality in satellite data by observing the ratio of blue to red light in the satellite data. When the amount of blue light reflecting off of the lake is high and the red light is low, a lake generally had high water quality. Lakes loaded with algae and sediments, on the other hand, reflect less blue light and more red light. In this image, scientists used false coloring to depict the level of clarity of the water. Clear lakes are blue, moderately clear lakes are green and yellow, and murky lakes are orange and red. Using images such as these along with data from the Landsat satellites and NASA's Terra satellite, the scientists plan to create a comprehensive water quality map for the entire Great Lakes region in the next few years. For more information, read: Testing the Waters (Image courtesy Upper Great Lakes Regional Earth Science Applications Center, based on data copyright Space Imaging)

  15. Uncertainty estimation of a complex water quality model: The influence of Box-Cox transformation on Bayesian approaches and comparison with a non-Bayesian method

    Science.gov (United States)

    Freni, Gabriele; Mannina, Giorgio

    In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised Likelihood Uncertainty Estimation (GLUE). One crucial point in the application of Bayesian method is the formulation of a likelihood function that is conditioned by the hypotheses made regarding model residuals. Statistical transformations, such as the use of Box-Cox equation, are generally used to ensure the homoscedasticity of residuals. However, this practice may affect the reliability of the analysis leading to a wrong uncertainty estimation. The present paper aims to explore the influence of the Box-Cox equation for environmental water quality models. To this end, five cases were considered one of which was the “real” residuals distributions (i.e. drawn from available data). The analysis was applied to the Nocella experimental catchment (Italy) which is an agricultural and semi-urbanised basin where two sewer systems, two wastewater treatment plants and a river reach were monitored during both dry and wet weather periods. The results show that the uncertainty estimation is greatly affected by residual transformation and a wrong assumption may also affect the evaluation of model uncertainty. The use of less formal methods always provide an overestimation of modelling uncertainty with respect to Bayesian method but such effect is reduced if a wrong assumption is made regarding the

  16. Model documentation for relations between continuous real-time and discrete water-quality constituents in Cheney Reservoir near Cheney, Kansas, 2001--2009

    Science.gov (United States)

    Stone, Mandy L.; Graham, Jennifer L.; Gatotho, Jackline W.

    2013-01-01

    Cheney Reservoir, located in south-central Kansas, is one of the primary water supplies for the city of Wichita, Kansas. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station in Cheney Reservoir since 2001; continuously measured physicochemical properties include specific conductance, pH, water temperature, dissolved oxygen, turbidity, fluorescence (wavelength range 650 to 700 nanometers; estimate of total chlorophyll), and reservoir elevation. Discrete water-quality samples were collected during 2001 through 2009 and analyzed for sediment, nutrients, taste-and-odor compounds, cyanotoxins, phytoplankton community composition, actinomycetes bacteria, and other water-quality measures. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physicochemical properties to compute concentrations of constituents that are not easily measured in real time. The water-quality information in this report is important to the city of Wichita because it allows quantification and characterization of potential constituents of concern in Cheney Reservoir. This report updates linear regression models published in 2006 that were based on data collected during 2001 through 2003. The update uses discrete and continuous data collected during May 2001 through December 2009. Updated models to compute dissolved solids, sodium, chloride, and suspended solids were similar to previously published models. However, several other updated models changed substantially from previously published models. In addition to updating relations that were previously developed, models also were developed for four new constituents, including magnesium, dissolved phosphorus, actinomycetes bacteria, and the cyanotoxin microcystin. In addition, a conversion factor of 0.74 was established to convert the Yellow Springs Instruments (YSI) model 6026 turbidity sensor measurements to the newer YSI

  17. Development and implementation of a regression model for predicting recreational water quality in the Cuyahoga River, Cuyahoga Valley National Park, Ohio 2009-11

    Science.gov (United States)

    Brady, Amie M.G.; Plona, Meg B.

    2012-01-01

    The Cuyahoga River within Cuyahoga Valley National Park (CVNP) is at times impaired for recreational use due to elevated concentrations of Escherichia coli (E. coli), a fecal-indicator bacterium. During the recreational seasons of mid-May through September during 2009–11, samples were collected 4 days per week and analyzed for E. coli concentrations at two sites within CVNP. Other water-quality and environ-mental data, including turbidity, rainfall, and streamflow, were measured and (or) tabulated for analysis. Regression models developed to predict recreational water quality in the river were implemented during the recreational seasons of 2009–11 for one site within CVNP–Jaite. For the 2009 and 2010 seasons, the regression models were better at predicting exceedances of Ohio's single-sample standard for primary-contact recreation compared to the traditional method of using the previous day's E. coli concentration. During 2009, the regression model was based on data collected during 2005 through 2008, excluding available 2004 data. The resulting model for 2009 did not perform as well as expected (based on the calibration data set) and tended to overestimate concentrations (correct responses at 69 percent). During 2010, the regression model was based on data collected during 2004 through 2009, including all of the available data. The 2010 model performed well, correctly predicting 89 percent of the samples above or below the single-sample standard, even though the predictions tended to be lower than actual sample concentrations. During 2011, the regression model was based on data collected during 2004 through 2010 and tended to overestimate concentrations. The 2011 model did not perform as well as the traditional method or as expected, based on the calibration dataset (correct responses at 56 percent). At a second site—Lock 29, approximately 5 river miles upstream from Jaite, a regression model based on data collected at the site during the recreational

  18. National Recommended Water Quality Criteria

    Data.gov (United States)

    U.S. Environmental Protection Agency — The National Recommended Water Quality Criteria is a compilation of national recommended water quality criteria for the protection of aquatic life and human health...

  19. 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

  20. Modeling framework for representing long-term effectiveness of best management practices in addressing hydrology and water quality problems: Framework development and demonstration using a Bayesian method

    Science.gov (United States)

    Liu, Yaoze; Engel, Bernard A.; Flanagan, Dennis C.; Gitau, Margaret W.; McMillan, Sara K.; Chaubey, Indrajeet; Singh, Shweta

    2018-05-01

    Best management practices (BMPs) are popular approaches used to improve hydrology and water quality. Uncertainties in BMP effectiveness over time may result in overestimating long-term efficiency in watershed planning strategies. To represent varying long-term BMP effectiveness in hydrologic/water quality models, a high level and forward-looking modeling framework was developed. The components in the framework consist of establishment period efficiency, starting efficiency, efficiency for each storm event, efficiency between maintenance, and efficiency over the life cycle. Combined, they represent long-term efficiency for a specific type of practice and specific environmental concern (runoff/pollutant). An approach for possible implementation of the framework was discussed. The long-term impacts of grass buffer strips (agricultural BMP) and bioretention systems (urban BMP) in reducing total phosphorus were simulated to demonstrate the framework. Data gaps were captured in estimating the long-term performance of the BMPs. A Bayesian method was used to match the simulated distribution of long-term BMP efficiencies with the observed distribution with the assumption that the observed data represented long-term BMP efficiencies. The simulated distribution matched the observed distribution well with only small total predictive uncertainties. With additional data, the same method can be used to further improve the simulation results. The modeling framework and results of this study, which can be adopted in hydrologic/water quality models to better represent long-term BMP effectiveness, can help improve decision support systems for creating long-term stormwater management strategies for watershed management projects.

  1. Modeling Network Interdiction Tasks

    Science.gov (United States)

    2015-09-17

    118 xiii Table Page 36 Computation times for weighted, 100-node random networks for GAND Approach testing in Python ...in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 38 Accuracy measures for weighted, 100-node random networks for GAND...networks [15:p. 1]. A common approach to modeling network interdiction is to formulate the problem in terms of a two-stage strategic game between two

  2. Hydrochemical modelling of water quality in terms of emerging micropollutants in Mpumalanga, Gauteng and North West Provinces

    Science.gov (United States)

    Wanda, Elijah M. M.; Mamba, Bhekie B.; Msagati, Titus A. M.

    2017-08-01

    Emerging micropollutants (EMPs) are ubiquitous in aquatic systems and are associated with a wide range of eco-toxicological effects worldwide. There remains a lack of scientific understanding of the major underlying hydrochemical factors behind variations in concentration heterogeneities of EMPs in time and space. This study was therefore conducted to determine major hydrochemical processes controlling water quality and the occurrence of EMPs mainly, carbamazepine (CBZ), tonalide (AHTN), galaxolide (HHCB), caffeine (CAF), technical 4-nonylphenol (NP) and bisphenol A (BPA) in water from Mpumalanga, Gauteng and North West Provinces in South Africa. Grab water samples were collected bi-monthly between June 2014 and April 2016 from 44 water sources using standard sampling procedures. BPA, NP, CAF, HHCB, AHTN, CBZ were extracted, cleaned and enriched using autotrace-SPE at neutral pH and analyzed using GC × GC-TOFMS. Kruskal Wallis-test was used to test for temporal variations in occurrence of the analytes. The Geochemist's Workbench® Release 11 software, Surfer Golden Graphics for surface mapping, PHREEQC software and bivariate ion plots were used determine the major hydrogeochemical processes. The mean concentrations of EMPs varied from 3.48 μg/L for CAF to 421.53 μg/L for HHCB. Although the Kruskal Wallis test revealed no any statistically significant temporal variations in concentrations of the analytes in water samples at 95% confidence level, their occurrence and distribution vary spatially with BPA being the most widely distributed EMP and was present in 62% of the sampled sites. Municipal waste water inputs, agricultural pollution, ion-exchange reactions, carbonate and silicate weathering were the major processes controlling water quality in the study area. This study may assist water resource managers to ably address and manage water pollution resulting from a number of natural and anthropogenic hydrochemical processes in the study area.

  3. Integrated application of river water quality modelling and cost-benefit analysis to optimize the environmental economical value based on various aquatic waste load reduction strategies

    Science.gov (United States)

    Wu, Chen-Yu; Fan, Chihhao

    2017-04-01

    To assure the river water quality, the Taiwan government establishes many pollution control strategies and expends huge monetary investment. Despite all these efforts, many rivers still suffer from severe pollution because of massive discharges of domestic and industrial wastewater without proper treatment. A comprehensive evaluation tool seems required to assess the suitability of water pollution control strategies. Therefore, the purpose of this study is to quantify the potential strategic benefits by applying the water quality modelling integrated with cost-benefit analysis to simulating scenarios based on regional development planning. The Erhjen Creek is selected as the study example because it is a major river in southern Taiwan, and its riverine environment impacts a great deal to the neighboring people. For strategy assessment, we established QUAL2k model of Erhjen Creek and conducted the cost-benefit analyses according the proposed strategies. In the water quality simulation, HEC-RAS was employed to calculate the hydraulic parameters and dilution impact of tidal effect in the downstream section. Daily pollution loadings were obtained from the Water Pollution Control Information System maintained by Taiwan EPA, and the wastewater delivery ratios were calculated by comparing the occurrence of pollution loadings with the monitoring data. In the cost-benefit analysis, we adopted the market valuation method, setting a period of 65 years for analysis and discount rate at 2.59%. Capital investments were the costs of design, construction, operation and maintenance for each project in Erhjen Creek catchment. In model calibration and model verification, the mean absolute percentage errors (MAPEs) were calculated to be 21.4% and 25.5%, respectively, which met the prescribed acceptable criteria of 50%. This model was applied to simulating water quality based on implementing various pollution control policies and engineering projects in the Erhjen Creek. The overall

  4. Building Adaptive Capacity with the Delphi Method and Mediated Modeling for Water Quality and Climate Change Adaptation in Lake Champlain Basin

    Science.gov (United States)

    Coleman, S.; Hurley, S.; Koliba, C.; Zia, A.; Exler, S.

    2014-12-01

    Eutrophication and nutrient pollution of surface waters occur within complex governance, social, hydrologic and biophysical basin contexts. The pervasive and perennial nutrient pollution in Lake Champlain Basin, despite decades of efforts, exemplifies problems found across the world's surface waters. Stakeholders with diverse values, interests, and forms of explicit and tacit knowledge determine water quality impacts through land use, agricultural and water resource decisions. Uncertainty, ambiguity and dynamic feedback further complicate the ability to promote the continual provision of water quality and ecosystem services. Adaptive management of water resources and land use requires mechanisms to allow for learning and integration of new information over time. The transdisciplinary Research on Adaptation to Climate Change (RACC) team is working to build regional adaptive capacity in Lake Champlain Basin while studying and integrating governance, land use, hydrological, and biophysical systems to evaluate implications for adaptive management. The RACC team has engaged stakeholders through mediated modeling workshops, online forums, surveys, focus groups and interviews. In March 2014, CSS2CC.org, an interactive online forum to source and identify adaptive interventions from a group of stakeholders across sectors was launched. The forum, based on the Delphi Method, brings forward the collective wisdom of stakeholders and experts to identify potential interventions and governance designs in response to scientific uncertainty and ambiguity surrounding the effectiveness of any strategy, climate change impacts, and the social and natural systems governing water quality and eutrophication. A Mediated Modeling Workshop followed the forum in May 2014, where participants refined and identified plausible interventions under different governance, policy and resource scenarios. Results from the online forum and workshop can identify emerging consensus across scales and sectors

  5. Comment on “Modeling Miscanthus in the Soil and Water Assessment Tool (SWAT) to Simulate Its Water Quality Effects As a Bioenergy Crop”

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Xuesong; Izaurralde, Roberto C.; Arnold, J. G.; Sammons, N. B.; Manowitz, David H.; Thomson, Allison M.; Williams, J.R.

    2011-07-01

    In this paper, the authors comment on several mistakes made in a journal paper "Modeling Miscanthus in the Soil and Water Assessment Tool (SWAT) to Simulate Its Water Quality Effects As a Bioenergy Crop" published on Environmental Scienece & Technology, based on field measurements from Great Lakes Bioenergy Research Center, Carbon Sequestration in Terrestrial Ecosystems, and published literature. Our comment has led to the development of another version of SWAT to include better process based description of radiation use efficiency and root-shoot growth.

  6. Simulating the Effects of Agricultural Management on Water Quality Dynamics in Rice Paddies for Sustainable Rice Production—Model Development and Validation

    Directory of Open Access Journals (Sweden)

    Soon-Kun Choi

    2017-11-01

    Full Text Available The Agricultural Policy/Environmental eXtender (APEX model is widely used for evaluating agricultural conservation efforts and their effects on soil and water. A key component of APEX application in Korea is simulating the water quality impacts of rice paddies because rice agriculture claims the largest cropland area in the country. In this study, a computational module called APEX-Paddy (National Academy of Agricultural Sciences, Wanju, Korea is developed to simulate water quality with considering pertinent paddy management practices, such as puddling and flood irrigation management. Data collected at two experimental paddy sites in Korea were used to calibrate and validate the model. Results indicate that APEX-Paddy performs well in predicting runoff discharge rate and nitrogen yield while the original APEX highly overestimates runoff rates and nitrogen yields on large storm events. With APEX-Paddy, simulated and observed flow and mineral nitrogen yield (QN are found to be highly correlated after calibration (Nash & Sutcliffe Efficiency (NSE = 0.87 and Percent Bias (PBIAS = −14.6% for flow; NSE = 0.68 and PBIAS = 2.1% for QN. Consequently, the APEX-Paddy showed a greater accuracy in flow and QN prediction than the original APEX modeling practice using the SCS-CN (Soil Conservation Service-Curve Number method.

  7. Summarized water quality criteria

    International Nuclear Information System (INIS)

    Kempster, P.L.; Hattingh, W.H.J.; Van Vliet, H.R.

    1980-08-01

    The available world literature from 27 sources on existing water quality criteria are summarized for the 15 main uses of water. The minimum, median and maximum specified values for 96 different determinands are included. Under each water use the criteria are grouped according to the functional significance of the determinands e.g. aesthetic/physical effects, high toxic potential, low toxic potential etc. A synopsis is included summarizing salient facts for each determinand such as the conditions under which it is toxic and its relationship to other determinands. The significance of the criteria is briefly discussed and the importance of considering functional interactions between determinands emphasized in evaluating the potential for toxic or beneficial effects. From the source literature it appears that the toxic potential, in addition to being determined by concentration, is also affected by the origin of the substance concerned, i.e. whether from natural sources or from anthropogenic pollution

  8. The challenges of modelling phosphorus in a headwater catchment: Applying a 'limits of acceptability' uncertainty framework to a water quality model

    Science.gov (United States)

    Hollaway, M. J.; Beven, K. J.; Benskin, C. McW. H.; Collins, A. L.; Evans, R.; Falloon, P. D.; Forber, K. J.; Hiscock, K. M.; Kahana, R.; Macleod, C. J. A.; Ockenden, M. C.; Villamizar, M. L.; Wearing, C.; Withers, P. J. A.; Zhou, J. G.; Barber, N. J.; Haygarth, P. M.

    2018-03-01

    There is a need to model and predict the transfer of phosphorus (P) from land to water, but this is challenging because of the large number of complex physical and biogeochemical processes involved. This study presents, for the first time, a 'limits of acceptability' approach of the Generalized Likelihood Uncertainty Estimation (GLUE) framework to the Soil and Water Assessment Tool (SWAT), in an application to a water quality problem in the Newby Beck catchment (12.5 km2), Cumbria, United Kingdom (UK). Using high frequency outlet data (discharge and P), individual evaluation criteria (limits of acceptability) were assigned to observed discharge and P loads for all evaluation time steps, identifying where the model was performing well/poorly and to infer which processes required improvement in the model structure. Initial limits of acceptability were required to be relaxed by a substantial amount (by factors of between 5.3 and 6.7 on a normalized scale depending on the evaluation criteria used) in order to gain a set of behavioral simulations (1001 and 1016, respectively out of 5,000,000). Of the 39 model parameters tested, the representation of subsurface processes and associated parameters, were consistently shown as critical to the model not meeting the evaluation criteria, irrespective of the chosen evaluation metric. It is therefore concluded that SWAT is not an appropriate model to guide P management in this catchment. This approach highlights the importance of high frequency monitoring data for setting robust model evaluation criteria. It also raises the question as to whether it is possible to have sufficient input data available to drive such models so that we can have confidence in their predictions and their ability to inform catchment management strategies to tackle the problem of diffuse pollution from agriculture.

  9. Agricultural drainage water quality

    International Nuclear Information System (INIS)

    Madani, A.; Gordon, R.

    2002-01-01

    'Full text:' Agricultural drainage systems have been identified as potential contributors of non-point source pollution. Two of the major concerns have been with nitrate-nitrogen (NO3 - -N) concentrations and bacteria levels exceeding the Maximum Acceptable Concentration in drainage water. Heightened public awareness of environmental issues has led to greater pressure to maintain the environmental quality of water systems. In an ongoing field study, three experiment sites, each with own soil properties and characteristics, are divided into drainage plots and being monitored for NO3 - -N and fecal coliforms contamination. The first site is being used to determine the impact of the rate of manure application on subsurface drainage water quality. The second site is being used to determine the difference between hog manure and inorganic fertilizer in relation to fecal coliforms and NO3-N leaching losses under a carrot rotation system. The third site examines the effect of timing of manure application on water quality, and is the only site equipped with a surface drainage system, as well as a subsurface drainage system. Each of the drains from these fields lead to heated outflow buildings to allow for year-round measurements of flow rates and water samples. Tipping buckets wired to data-loggers record the outflow from each outlet pipe on an hourly basis. Water samples, collected from the flowing drains, are analyzed for NO3 - -N concentrations using the colorimetric method, and fecal coliforms using the Most Probable Number (MPN) method. Based on this information, we will be able better positioned to assess agricultural impacts on water resources which will help towards the development on industry accepted farming practices. (author)

  10. Drinking water quality assessment.

    Science.gov (United States)

    Aryal, J; Gautam, B; Sapkota, N

    2012-09-01

    Drinking water quality is the great public health concern because it is a major risk factor for high incidence of diarrheal diseases in Nepal. In the recent years, the prevalence rate of diarrhoea has been found the highest in Myagdi district. This study was carried out to assess the quality of drinking water from different natural sources, reservoirs and collection taps at Arthunge VDC of Myagdi district. A cross-sectional study was carried out using random sampling method in Arthunge VDC of Myagdi district from January to June,2010. 84 water samples representing natural sources, reservoirs and collection taps from the study area were collected. The physico-chemical and microbiological analysis was performed following standards technique set by APHA 1998 and statistical analysis was carried out using SPSS 11.5. The result was also compared with national and WHO guidelines. Out of 84 water samples (from natural source, reservoirs and tap water) analyzed, drinking water quality parameters (except arsenic and total coliform) of all water samples was found to be within the WHO standards and national standards.15.48% of water samples showed pH (13) higher than the WHO permissible guideline values. Similarly, 85.71% of water samples showed higher Arsenic value (72) than WHO value. Further, the statistical analysis showed no significant difference (Pwater for collection taps water samples of winter (January, 2010) and summer (June, 2010). The microbiological examination of water samples revealed the presence of total coliform in 86.90% of water samples. The results obtained from physico-chemical analysis of water samples were within national standard and WHO standards except arsenic. The study also found the coliform contamination to be the key problem with drinking water.

  11. Modelling computer networks

    International Nuclear Information System (INIS)

    Max, G

    2011-01-01

    Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

  12. A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model

    Science.gov (United States)

    Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.

    2015-05-01

    A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.

  13. 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.

  14. Modeling the citation network by network cosmology.

    Science.gov (United States)

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  15. Water quality sensor

    International Nuclear Information System (INIS)

    Ishizuka, Keiko; Takahashi, Masanori; Watanabe, Atsushi; Ibe, Hidefumi.

    1994-01-01

    The sensor of the present invention can directly measure oxygen/hydrogen peroxide concentrations in reactor water under radiation irradiation condition, and it has a long life time. Namely, an oxygen sensor comprises electrodes attached on both sides of high temperature/radiation resistant ion conductive material in which ions are sufficiently diffused within a temperature range of from a room temperature to 300degC. It has a performance for measuring electromotive force caused by the difference of a partial pressure between a reference gas and a gas to be measured contained in the high temperature/radiation resistant material. A hydrogen peroxide sensor has the oxygen sensor described above, to which a filter for causing decomposition of hydrogen peroxide is attached. The sensor of the present invention can directly measure oxygen/hydrogen peroxide concentrations in a reactor water of a BWR type reactor under high temperature/radiation irradiation condition. Accordingly, accurate water quality environment in the reactor water can be recognized. As a result, determination of incore corrosion environment is established thereby enabling to attain reactor integrity, safety and long life. (I.S.)

  16. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  17. Real-time water quality monitoring and providing water quality ...

    Science.gov (United States)

    EPA and the U.S. Geological Survey (USGS) have initiated the “Village Blue” research project to provide real-time water quality monitoring data to the Baltimore community and increase public awareness about local water quality in Baltimore Harbor and the Chesapeake Bay. The Village Blue demonstration project complements work that a number of state and local organizations are doing to make Baltimore Harbor “swimmable and fishable” 2 by 2020. Village Blue is designed to build upon EPA’s “Village Green” project which provides real-time air quality information to communities in six locations across the country. The presentation, “Real-time water quality monitoring and providing water quality information to the Baltimore Community”, summarizes the Village Blue real-time water quality monitoring project being developed for the Baltimore Harbor.

  18. Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015

    Science.gov (United States)

    Foster, Guy M.; Graham, Jennifer L.

    2016-04-06

    The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Source-water supplies are treated by a combination of chemical and physical processes to remove contaminants before distribution. Advanced notification of changing water-quality conditions and cyanobacteria and associated toxin and taste-and-odor compounds provides drinking-water treatment facilities time to develop and implement adequate treatment strategies. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas State Water Plan Fund), and the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One, began a study in July 2012 to develop statistical models at two Kansas River sites located upstream from drinking-water intakes. Continuous water-quality monitors have been operated and discrete-water quality samples have been collected on the Kansas River at Wamego (USGS site number 06887500) and De Soto (USGS site number 06892350) since July 2012. Continuous and discrete water-quality data collected during July 2012 through June 2015 were used to develop statistical models for constituents of interest at the Wamego and De Soto sites. Logistic models to continuously estimate the probability of occurrence above selected thresholds were developed for cyanobacteria, microcystin, and geosmin. Linear regression models to continuously estimate constituent concentrations were developed for major ions, dissolved solids, alkalinity, nutrients (nitrogen and phosphorus species), suspended sediment, indicator bacteria (Escherichia coli, fecal coliform, and enterococci), and actinomycetes bacteria. These models will be used to provide real-time estimates of the probability that cyanobacteria and associated compounds exceed thresholds and of the concentrations of other water-quality constituents in the Kansas River. The models documented in this report are useful for characterizing changes

  19. Modeling Epidemic Network Failures

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2013-01-01

    This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....

  20. A study on the applicability of the ecosystem model on water quality prediction in urban river outer moats of Yedo Castle, Nihonbashi River

    Science.gov (United States)

    Kakinuma, Daiki; Tsushima, Yuki; Ohdaira, Kazunori; Yamada, Tadashi

    2015-04-01

    The objective of the study is to elucidate the waterside environment in the outer moats of Yedo Castle and the downstream of Nihonbashi River in Tokyo. Scince integrated sewage system has been installed in the area around the outer moats of Yedo Castle and the Nihon River basin, when rainfall exceeds more than the sewage treatment capacity, overflowed untreated wastewater is released into the moats and the river. Because the moats is a closed water body, pollutants are deposited to the bottom without outflowing. While reeking offensive odors due to the decomposition, blue-green algae outbreaks affected by the residence time and eluted nutrient causes problems. Scince the Nihonbashi River is a typical tidal river in urban area, the water pollution problems in the river is complicated. This study clarified the characteristics of the water quality in terms of dissolved oxygen saturation through on-site observations. In particular, dissolved oxygen saturation in summer, it is clarified that variations from a supersaturated state due to the variations of horizontal insolation intensity and water temperature up to hypoxic water conditions in the moats. According to previous studies on the water quality of Nihonbashi River, it is clarified that there are three types of variations of dissolved oxygen which desided by rainfall scale. The mean value of dissolved oxygen saturation of all layers has decreased by about 20% at the spring tide after dredging, then it recoveres gradually and become the value before dredging during about a year. Further more, in places where sewage inflows, it is important to developed a ecosystem medel and the applicability of the model. 9 variables including cell quota (intracellular nutrients of phytoplankton) of phosphorus and nitrogen with considerring the nitrification of ammonia nitrogen are used in the model. This model can grasp the sections (such as oxygen production by photosynthesis of phytoplankton, oxygen consumption by respiration of

  1. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  2. Assessment of water quality

    International Nuclear Information System (INIS)

    Qureshi, I.H.

    2002-01-01

    Water is the most essential component of all living things and it supports the life process. Without water, it would not have been possible to sustain life on this planet. The total quantity of water on earth is estimated to be 1.4 trillion cubic meter. Of this, less than 1 % water, present in rivers and ground resources is available to meet our requirement. These resources are being contaminated with toxic substances due to ever increasing environmental pollution. To reduce this contamination, many countries have established standards for the discharge of municipal and industrial waste into water streams. We use water for various purposes and for each purpose we require water of appropriate quality. The quality of water is assessed by evaluating the physical chemical, biological and radiological characteristics of water. Water for drinking and food preparation must be free from turbidity, colour, odour and objectionable tastes, as well as from disease causing organisms and inorganic and organic substances, which may produce adverse physiological effects, Such water is referred to as potable water and is produced by treatment of raw water, involving various unit operations. The effectiveness of the treatment processes is checked by assessing the various parameters of water quality, which involves sampling and analysis of water and comparison with the National Quality Standards or WHO standards. Water which conforms to these standards is considered safe and palatable for human consumption. Periodic assessment of water is necessary, to ensure the quality of water supplied to the public. This requires proper sampling at specified locations and analysis of water, employing reliable analytical techniques. (author)

  3. Gap-filling of dry weather flow rate and water quality measurements in urban catchments by a time series modelling approach

    DEFF Research Database (Denmark)

    Sandoval, Santiago; Vezzaro, Luca; Bertrand-Krajewski, Jean-Luc

    2016-01-01

    seeks to evaluate the potential of the Singular Spectrum Analysis (SSA), a time-series modelling/gap-filling method, to complete dry weather time series. The SSA method is tested by reconstructing 1000 artificial discontinuous time series, randomly generated from real flow rate and total suspended......Flow rate and water quality dry weather time series in combined sewer systems might contain an important amount of missing data due to several reasons, such as failures related to the operation of the sensor or additional contributions during rainfall events. Therefore, the approach hereby proposed...... solids (TSS) online measurements (year 2007, 2 minutes time-step, combined system, Ecully, Lyon, France). Results show up the potential of the method to fill gaps longer than 0.5 days, especially between 0.5 days and 1 day (mean NSE > 0.6) in the flow rate time series. TSS results still perform very...

  4. Water quality assessment and catchment-scale nutrient flux modeling in the Ramganga River Basin in north India: An application of INCA model.

    Science.gov (United States)

    Pathak, Devanshi; Whitehead, Paul G; Futter, Martyn N; Sinha, Rajiv

    2018-03-07

    The present study analyzes the water quality characteristics of the Ramganga (a major tributary of the Ganga river) using long-term (1991-2009) monthly data and applies the Integrated Catchment Model of Nitrogen (INCA-N) and Phosphorus (INCA-P) to the catchment. The models were calibrated and validated using discharge (1993-2011), phosphate (1993-2010) and nitrate (2007-2010) concentrations. The model results were assessed based on Pearson's correlation, Nash-Sutcliffe and Percentage bias statistics along with a visual inspection of the outputs. The seasonal variation study shows high nutrient concentrations in the pre-monsoon season compared to the other seasons. High nutrient concentrations in the low flows period pose a serious threat to aquatic life of the river although the concentrations are lowered during high flows because of the dilution effect. The hydrological model is satisfactorily calibrated with R 2 and NS values ranging between 0.6-0.8 and 0.4-0.8, respectively. INCA-N and INCA-P successfully capture the seasonal trend of nutrient concentrations with R 2 >0.5 and PBIAS within ±17% for the monthly averages. Although, high concentrations are detected in the low flows period, around 50% of the nutrient load is transported by the monsoonal high flows. The downstream catchments are characterized by high nutrient transport through high flows where additional nutrient supply from industries and agricultural practices also prevail. The seasonal nitrate (R 2 : 0.88-0.94) and phosphate (R 2 : 0.62-0.95) loads in the catchment are calculated using model results and ratio estimator load calculation technique. On average, around 548tonnes of phosphorus (as phosphate) and 77,051tonnes of nitrogen (as nitrate) are estimated to be exported annually from the Ramganga River to the Ganga. Overall, the model has been able to successfully reproduce the catchment dynamics in terms of seasonal variation and broad-scale spatial variability of nutrient fluxes in the

  5. The role of hydrological and water quality models in the application of the ecosystem services framework for the EU Water Framework Directive

    Science.gov (United States)

    Hallouin, Thibault; Bruen, Michael; Feeley, Hugh B.; Christie, Michael; Bullock, Craig; Kelly, Fiona; Kelly-Quinn, Mary

    2017-04-01

    The hydrological cycle is intimately linked with environmental processes that are essential for human welfare in many regards including, among others, the provision of safe water from surface and subsurface waterbodies, rain-fed agricultural production, or the provision of aquatic-sourced food. As well as being a receiver of these natural benefits, the human population is also a manager of the water and other natural resources and, as such, can affect their future sustainable provision. With global population growth and climate change, both the dependence of the human population on water resources and the threat they pose to these resources are likely to intensify so that the sustainability of the coupled natural and human system is threatened. In the European Union, the Water Framework Directive is driving policy and encouraging member states to manage their water resources wisely in order to maintain or restore ecological quality. To this end, the ecosystem services framework can be a useful tool to link the requirements in terms of ecological status into more tangible descriptors, that is the ecosystem services. In the ESManage Project, existing environmental system models such as hydrological models and water quality models are used as the basis to quantify the provision of many hydrological and aquatic ecosystem services by constructing indicators for the ecosystem services from the modelled environmental variables. By allowing different management options and policies to be compared, these models can be a valuable source of information for policy makers when they are used for climate and land use scenario analyses. Not all hydrological models developed for flood forecasting are suitable for this application and inappropriate models can lead to questionable conclusions. This paper demonstrates the readily available capabilities of a specially developed catchment hydrological model coupled with a water quality model to quantify a wide range of biophysically

  6. Analysis and Model Based Assessment of Water Quality in European Mesoscale Forest Catchments with Different Management Strategies (a Climatic Gradient Approach)

    Science.gov (United States)

    Tavares, Filipa; Schwaerzel, Kai; Nunes, João. Pedro; Feger, Karl-Heinz

    2010-05-01

    Forestry activities affect the environmental conditions of river basins by modifying soil properties and vegetation cover, leading to changes in e.g. runoff generation and routing, water yield or the trophic status of water bodies. Climate change is directly linked to forestry, since site-adapted sustainable forest management can buffer negative climate change impacts in river basins, while practices leading to over-harvesting or increasing wildfires can exacerbate these impacts. While studies relating hydrological processes with forestry practices or climate change have already been conducted, the combined impacts of both are rarely discussed. The main objective of the proposed work is to study the interactions between forest management and climate change and the effects of these upon water fluxes and water quality at the catchment scale, over medium to long-term periods and following an East-West climate gradient. Additional objectives are to increase knowledge about the relations between forest, water quality and soil conservation/degradation; and to improve the modelling of hydrological and matter transport processes in managed forests. The present poster shows a conceptual approach to understand this combined interaction by analysing an East-West climatic gradient (Ukraine-Germany-Portugal), with contrasting forestry practices and climate vulnerabilities. The activities within this workplan, to take place during the period 2010 - 2014, will be developed in close collaboration with several ongoing research projects in the host institution at the Dresden University of Technology (TUD) and in the University of Aveiro (UA). The Institute of Soil Science and Site-Ecology (ISSE) at TUD has an internationally renowned research tradition in forest hydrological topics using methods and findings from various (sub)disciplines in a multidisplinary approach. The measurement and simulation of forest catchments has also been a point of research at the Centre for

  7. Nutrient and pesticide contamination bias estimated from field blanks collected at surface-water sites in U.S. Geological Survey Water-Quality Networks, 2002–12

    Science.gov (United States)

    Medalie, Laura; Martin, Jeffrey D.

    2017-08-14

    Potential contamination bias was estimated for 8 nutrient analytes and 40 pesticides in stream water collected by the U.S. Geological Survey at 147 stream sites from across the United States, and representing a variety of hydrologic conditions and site types, for water years 2002–12. This study updates previous U.S. Geological Survey evaluations of potential contamination bias for nutrients and pesticides. Contamination is potentially introduced to water samples by exposure to airborne gases and particulates, from inadequate cleaning of sampling or analytic equipment, and from inadvertent sources during sample collection, field processing, shipment, and laboratory analysis. Potential contamination bias, based on frequency and magnitude of detections in field blanks, is used to determine whether or under what conditions environmental data might need to be qualified for the interpretation of results in the context of comparisons with background levels, drinking-water standards, aquatic-life criteria or benchmarks, or human-health benchmarks. Environmental samples for which contamination bias as determined in this report applies are those from historical U.S. Geological Survey water-quality networks or programs that were collected during the same time frame and according to the same protocols and that were analyzed in the same laboratory as field blanks described in this report.Results from field blanks for ammonia, nitrite, nitrite plus nitrate, orthophosphate, and total phosphorus were partitioned by analytical method; results from the most commonly used analytical method for total phosphorus were further partitioned by date. Depending on the analytical method, 3.8, 9.2, or 26.9 percent of environmental samples, the last of these percentages pertaining to all results from 2007 through 2012, were potentially affected by ammonia contamination. Nitrite contamination potentially affected up to 2.6 percent of environmental samples collected between 2002 and 2006 and

  8. Water Quality Monitoring Manual.

    Science.gov (United States)

    Mason, Fred J.; Houdart, Joseph F.

    This manual is designed for students involved in environmental education programs dealing with water pollution problems. By establishing a network of Environmental Monitoring Stations within the educational system, four steps toward the prevention, control, and abatement of water pollution are proposed. (1) Train students to recognize, monitor,…

  9. Sensitivity Analysis in Agent-Based Models of Socio-Ecological Systems: An Example in Agricultural Land Conservation for Lake Water Quality Improvement

    Science.gov (United States)

    Ligmann-Zielinska, A.; Kramer, D. B.; Spence Cheruvelil, K.; Soranno, P.

    2012-12-01

    Socio-ecological systems are dynamic and nonlinear. To account for this complexity, we employ agent-based models (ABMs) to study macro-scale phenomena resulting from micro-scale interactions among system components. Because ABMs typically have many parameters, it is challenging to identify which parameters contribute to the emerging macro-scale patterns. In this paper, we address the following question: What is the extent of participation in agricultural land conservation programs given heterogeneous landscape, economic, social, and individual decision making criteria in complex lakesheds? To answer this question, we: [1] built an ABM for our model system; [2] simulated land use change resulting from agent decision making, [3] estimated the uncertainty of the model output, decomposed it and apportioned it to each of the parameters in the model. Our model system is a freshwater socio-ecological system - that of farmland and lake water quality within a region containing a large number of lakes and high proportions of agricultural lands. Our study focuses on examining how agricultural land conversion from active to fallow reduces freshwater nutrient loading and improves water quality. Consequently, our ABM is composed of farmer agents who make decisions related to participation in a government-sponsored Conservation Reserve Program (CRP) managed by the Farm Service Agency (FSA). We also include an FSA agent, who selects enrollment offers made by farmers and announces the signup results leading to land use change. The model is executed in a Monte Carlo simulation framework to generate a distribution of maps of fallow lands that are used for calculating nutrient loading to lakes. What follows is a variance-based sensitivity analysis of the results. We compute sensitivity indices for individual parameters and their combinations, allowing for identification of the most influential as well as the insignificant inputs. In the case study, we observe that farmland

  10. Effects of selected low-impact-development (LID) techniques on water quality and quantity in the Ipswich River Basin, Massachusetts-Field and modeling studies

    Science.gov (United States)

    Zimmerman, Marc J.; Barbaro, Jeffrey R.; Sorenson, Jason R.; Waldron, Marcus C.

    2010-01-01

    During the months of August and September, flows in the Ipswich River, Massachusetts, dramatically decrease largely due to groundwater withdrawals needed to meet increased residential and commercial water demands. In the summer, rates of groundwater recharge are lower than during the rest of the year, and water demands are higher. From 2005 to 2008, the U.S. Geological Survey, in a cooperative funding agreement with the Massachusetts Department of Conservation and Recreation, monitored small-scale installations of low-impact-development (LID) enhancements designed to diminish the effects of storm runoff on the quantity and quality of surface water and groundwater. Funding for the studies also was contributed by the U.S. Environmental Protection Agency's Targeted Watersheds Grant Program through a financial assistance agreement with Massachusetts Department of Conservation and Recreation. The monitoring studies examined the effects of (1) replacing an impervious parking lot surface with a porous surface on groundwater quality, (2) installing rain gardens and porous pavement in a neighborhood of 3 acres on the quantity and quality of stormwater runoff, and (3) installing a 3,000-square foot (ft2) green roof on the quantity and quality of stormwater runoff. In addition, the effects of broad-scale implementation of LID techniques, reduced water withdrawals, and water-conservation measures on streamflow in large areas of the basin were simulated using the U.S. Geological Survey's Ipswich River Basin model. From June 2005 to 2007, groundwater quality was monitored at the Silver Lake town beach parking lot in Wilmington, MA, prior to and following the replacement of the conventional, impervious-asphalt surface with a porous surface consisting primarily of porous asphalt and porous pavers. Changes in the concentrations of the water-quality constituents, phosphorus, nitrogen, cadmium, chromium, copper, lead, nickel, zinc, and total petroleum hydrocarbons, were monitored

  11. Higher energy efficiency and better water quality by using model predictive flow control at water supply systems

    NARCIS (Netherlands)

    Bakker, M.; Verberk, J.Q.J.C.; Palmen, L.J.; Sperber, V.; Bakker, G.

    2011-01-01

    Half of all water supply systems in the Netherlands are controlled by model predictive flow control; the other half are controlled by conventional level based control. The differences between conventional level based control and model predictive control were investigated in experiments at five full

  12. Developing an integrated 3D-hydrodynamic and emerging contaminant model for assessing water quality in a Yangtze Estuary Reservoir.

    Science.gov (United States)

    Xu, Cong; Zhang, Jingjie; Bi, Xiaowei; Xu, Zheng; He, Yiliang; Gin, Karina Yew-Hoong

    2017-12-01

    An integrated 3D-hydrodynamic and emerging contaminant model was developed for better understanding of the fate and transport of emerging contaminants in Qingcaosha Reservoir. The reservoir, which supplies drinking water for nearly half of Shanghai's population, is located in Yangtze Delta. The integrated model was built by Delft3D suite, a fully integrated multidimensional modeling software. Atrazine and Bisphenol A (BPA) were selected as two representative emerging contaminants for the study in this reservoir. The hydrodynamic model was calibrated and validated against observations from 2011 to 2015 while the integrated model was calibrated against observations from 2014 to 2015 and then applied to explore the potential risk of high atrazine concentrations in the reservoir driven by agriculture activities. Our results show that the model is capable of describing the spatial and temporal patterns of water temperature, salinity and the dynamic distributions of two representative emerging contaminants (i.e. atrazine and BPA) in the reservoir. The physical and biodegradation processes in this study were found to play a crucial role in determining the fate and transport of atrazine and BPA in the reservoir. The model also provides an insight into the potential risk of emerging contaminants and possible mitigation thresholds. The integrated approach can be a very useful tool to support policy-makers in the future management of Qingcaosha Reservoir. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Estimation of Water Quality

    International Nuclear Information System (INIS)

    Vetrinskaya, N.I.; Manasbayeva, A.B.

    1998-01-01

    cases where the quantity of radionuclides are insignificant. Differences in speed of ions going out began about 30 minutes after start of measurement. Later (1-24 hours) the difference between control and experience samples were more visible. In chronic test, when elodea was incubated in toxic water for 30 days, morphological modification are expressed very well. There were brown and discolored leaves and interruption of sprout growth. After 60 days the plants did not renew formation of new sprouts in most of the test's variants. The plants died in 2 variants and in others its begin was adapted. It has been established that the degree of morphological difference depends on the intensity of β radiation in test samples of water. By conducting the investigation this way, the possibility of rapid determination of water quality in ecological aspects by biophysics methods with use of living organisms of different taxonomic groups, such as test-objects, is shown. This approach may be used also for inspection aims for sites where nuclear explosions were possibly conducted

  14. Water quality status and trends in agriculture dominated headwaters; a national monitoring network for assessing the effectiveness of national and European manure legislation in The Netherlands

    Science.gov (United States)

    Rozemeijer, J.; Klein, J.

    2016-12-01

    Large nutrient losses to groundwater and surface waters are a major drawback of the highly productive agricultural sector in The Netherlands. The resulting high nutrient concentrations in water resources threaten their ecological, industrial, and recreational functions. To mitigate eutrophication problems, legislation on nutrient application in agriculture was enforced in 1986 in The Netherlands. The objective of this study was to evaluate this manure policy by assessing the water quality status and trends in agriculture dominated headwaters. We used datasets from 5 agricultural test catchments and from 167 existing monitoring locations in agricultural headwaters. Trend analysis for these locations showed a fast reduction of nutrient concentrations after the enforcement of the manure legislation (median slopes of -0.55 mg/L per decade for total nitrogen (N-tot) and -0.020 mg/L per decade for total phosphorus (P-tot)). Still, up to 76% of the selected locations currently do not comply with either the environmental quality standards (EQSs) for nitrogen (N-tot) or phosphorus (P-tot). This indicates that further improvement of agricultural water quality is needed. We observed that weather-related variations in nutrient concentrations strongly influence the compliance testing results, both for individual locations and for the aggregated results at the national scale. Another important finding is that testing compliance for nutrients based on summer average concentrations may underestimate the agricultural impact on ecosystem health. The focus on summer concentrations does not account for the environmental impact of high winter loads from agricultural headwaters towards downstream water bodies.

  15. An inexact log-normal distribution-based stochastic chance-constrained model for agricultural water quality management

    Science.gov (United States)

    Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

    2018-05-01

    In this study, an inexact log-normal-based stochastic chance-constrained programming model was developed for solving the non-point source pollution issues caused by agricultural activities. Compared to the general stochastic chance-constrained programming model, the main advantage of the proposed model is that it allows random variables to be expressed as a log-normal distribution, rather than a general normal distribution. Possible deviations in solutions caused by irrational parameter assumptions were avoided. The agricultural system management in the Erhai Lake watershed was used as a case study, where critical system factors, including rainfall and runoff amounts, show characteristics of a log-normal distribution. Several interval solutions were obtained under different constraint-satisfaction levels, which were useful in evaluating the trade-off between system economy and reliability. The applied results show that the proposed model could help decision makers to design optimal production patterns under complex uncertainties. The successful application of this model is expected to provide a good example for agricultural management in many other watersheds.

  16. An integrated modeling framework for exploring flow regime and water quality changes with increasing biofuel crop production in the U.S. Corn Belt

    Science.gov (United States)

    Yaeger, Mary A.; Housh, Mashor; Cai, Ximing; Sivapalan, Murugesu

    2014-12-01

    To better address the dynamic interactions between human and hydrologic systems, we develop an integrated modeling framework that employs a System of Systems optimization model to emulate human development decisions which are then incorporated into a watershed model to estimate the resulting hydrologic impacts. The two models are run interactively to simulate the coevolution of coupled human-nature systems, such that reciprocal feedbacks between hydrologic processes and human decisions (i.e., human impacts on critical low flows and hydrologic impacts on human decisions on land and water use) can be assessed. The framework is applied to a Midwestern U.S. agricultural watershed, in the context of proposed biofuels development. This operation is illustrated by projecting three possible future coevolution trajectories, two of which use dedicated biofuel crops to reduce annual watershed nitrate export while meeting ethanol production targets. Imposition of a primary external driver (biofuel mandate) combined with different secondary drivers (water quality targets) results in highly nonlinear and multiscale responses of both the human and hydrologic systems, including multiple tradeoffs, impacting the future coevolution of the system in complex, heterogeneous ways. The strength of the hydrologic response is sensitive to the magnitude of the secondary driver; 45% nitrate reduction target leads to noticeable impacts at the outlet, while a 30% reduction leads to noticeable impacts that are mainly local. The local responses are conditioned by previous human-hydrologic modifications and their spatial relationship to the new biofuel development, highlighting the importance of past coevolutionary history in predicting future trajectories of change.

  17. Evaluation of stream water quality data generated from MODIS images in modeling total suspended solid emission to a freshwater lake.

    Science.gov (United States)

    Ayana, Essayas K; Worqlul, Abeyou W; Steenhuis, Tammo S

    2015-08-01

    Modeling of suspended sediment emission into freshwater lakes is challenging due to data gaps in developing countries. Existing models simulate sediment concentration at a gauging station upstream and none of these studies had modeled total suspended solids (TSS) emissions by inflowing rivers to freshwater lakes as there are no TSS measurements at the river mouth in the upper Blue Nile basin. In this study a 10year TSS time series data generated from remotely sensed MODIS/Terra images using established empirical relationship is applied to calibrate and validate a hydrology model for Lake Tana in Upper Blue Nile Basin. The result showed that at a monthly time scale TSS at the river mouth can be replicated with Nash-Sutcliffe efficiency (NS) of 0.34 for calibration and 0.21 for validation periods. Percent bias (PBIAS) and ratio of the root-mean-square error to the standard deviation of measured data (RSR) are all within range. Given the inaccessibility and costliness to measure TSS at river mouths to a lake the results found here are considered useful for suspended sediment budget studies in water bodies of the basin. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. 5 Water Quality.cdr

    African Journals Online (AJOL)

    Administrator

    The water quality assessment conducted in the Densu, Birim and Ayensu Basins of Ghana in the Okyeman area ... All the mean nutrient values for Densu, Birim and Ayensu were not significantly .... variability in the composition of the river.

  19. Better Water Demand and Pipe Description Improve the Distribution Network Modeling Results

    Science.gov (United States)

    Distribution system modeling simplifies pipe network in skeletonization and simulates the flow and water quality by using generalized water demand patterns. While widely used, the approach has not been examined fully on how it impacts the modeling fidelity. This study intends to ...

  20. VALUING BENEFITS FROM WATER QUALITY IMPROVEMENTS USING KUHN TUCKER MODEL - A COMPARATIVE ANALYSIS ON UTILITY FUNCTIONAL FORMS-

    Science.gov (United States)

    Okuyama, Tadahiro

    Kuhn-Tucker model, which has studied in recent years, is a benefit valuation technique using the revealed-preference data, and the feature is to treatvarious patterns of corner solutions flexibly. It is widely known for the benefit calculation using the revealed-preference data that a value of a benefit changes depending on a functional form. However, there are little studies which examine relationship between utility functions and values of benefits in Kuhn-Tucker model. The purpose of this study is to analysis an influence of the functional form to the value of a benefit. Six types of utility functions are employed for benefit calculations. The data of the recreational activity of 26 beaches of Miyagi Prefecture were employed. Calculation results indicated that Phaneuf and Siderelis (2003) and Whitehead et al.(2010)'s functional forms are useful for benefit calculations.

  1. Demonstration of a Model-Based Technology for Monitoring Water Quality and Corrosion in Water-Distribution systems

    Science.gov (United States)

    2016-12-01

    that Fort Drum uses water from two sources: (1) treated groundwater from its on-post wells and (2) treated surface water supplied by the Development...Complete replacement of distribution system piping $21 million Year 10 and Year 30 Leak repair $40,000 Annual Bottled water for drinking $20,000 per...about effects of the instal- lation’s dual water supplies on operation of the water -distribution system. 5.2 Recommendations 5.2.1 Applicability Model

  2. Applications of MIDAS regression in analysing trends in water quality

    Science.gov (United States)

    Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

    2014-04-01

    We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

  3. Improved Algorithms for Blending Dam Releases to Meet Downstream Water-Temperature Targets in the CE-QUAL-W2 Water-Quality Model

    Science.gov (United States)

    Rounds, S. A.; Buccola, N. L.

    2014-12-01

    The two-dimensional (longitudinal, vertical) water-quality model CE-QUAL-W2, version 3.7, was enhanced with new features to help dam operators and managers efficiently explore and optimize potential solutions for temperature management downstream of thermally stratified reservoirs. Such temperature management often is accomplished by blending releases from multiple dam outlets that access water of different temperatures at different depths in the reservoir. The original blending algorithm in this version of the model was limited to mixing releases from two outlets at a time, and few constraints could be imposed. The new enhanced blending algorithm allows the user to (1) specify a time-series of target release temperatures, (2) designate from 2 to 10 floating or fixed-elevation outlets for blending, (3) impose maximum head constraints as well as minimum and maximum flow constraints for any blended outlet, and (4) set a priority designation for each outlet that allows the model to choose which outlets to use and how to balance releases among them. The modified model was tested against a previously calibrated model of Detroit Lake on the North Santiam River in northwestern Oregon, and the results compared well. The enhanced model code is being used to evaluate operational and structural scenarios at multiple dam/reservoir systems in the Willamette River basin in Oregon, where downstream temperature management for endangered fish is a high priority for resource managers and dam operators. These updates to the CE-QUAL-W2 blending algorithm allow scenarios involving complicated dam operations and/or hypothetical outlet structures to be evaluated more efficiently with the model, with decreased need for multiple/iterative model runs or preprocessing of model inputs to fully characterize the operational constraints.

  4. Modelling the impacts of climate change on hydrology and water quality in a mediterranean limno-reservoir

    DEFF Research Database (Denmark)

    Molina-Navarro, Euginio; Trolle, Dennis; Martinez-Pérez, Silvia

    Assessment Tool (SWAT) model developed for a small Mediterranean catchment to quantify the potential effects of various climate change scenarios on catchment hydrology as well as the trophic state of a new kind of waterbody, a limno-reservoir (Pareja Limno-reservoir), created for environmental...... and recreational purposes. Simulations showed a noticeable impact of climate change in the river flow regime and consequently the water level of the limno-reservoir, especially during summer, complicating the fulfillment of its purposes. All the scenarios predicted a deterioration of trophic conditions...

  5. Application of some models of water quality in two places located in the reservoir The Penol, Guatape (Antioquia, Colombia)

    International Nuclear Information System (INIS)

    Aguirre, Nestor; Palacio, Jaime; Ramirez, John Jairo

    2002-01-01

    The dynamic behavior of two stations in El Penol-Guatape reservoir was studied during a year. The station one was located to the entrance of the Nare River (main tributary to the reservoir) and the station two in the area denominated Sun Island (with mainly lentic characteristics). In each station monthly samplings were done with the purpose of calculating two hydro biologics parameters and some models of loads of nutritients and of eutrophication were applied. According to the study, it was established that in the in the station one the rate assimilation of nutritious by microorganisms and the sedimentation rate of chlorophylled organisms were more elevated that in the station two. In general, it was found that the primary production in the station one was limited by the phosphorous and there were limitations for nitrogen during five months and seven months by the phosphorous in the station two. Starting from the model of prediction of the eutrophycation, in tropical warm lakes, it was found that El Penol Guatape reservoir is oligo productive

  6. Modeling Miscanthus in the soil and water assessment tool (SWAT) to simulate its water quality effects as a bioenergy crop.

    Science.gov (United States)

    Ng, Tze Ling; Eheart, J Wayland; Cai, Ximing; Miguez, Fernando

    2010-09-15

    There is increasing interest in perennial grasses as a renewable source of bioenergy and feedstock for second-generation cellulosic biofuels. The primary objective of this study is to estimate the potential effects on riverine nitrate load of cultivating Miscanthus x giganteus in place of conventional crops. In this study, the Soil and Water Assessment Tool (SWAT) is used to model miscanthus growth and streamwater quality in the Salt Creek watershed in Illinois. SWAT has a built-in crop growth component, but, as miscanthus is relatively new as a potentially commercial crop, data on the SWAT crop growth parameters for the crop are lacking. This leads to the second objective of this study, which is to estimate those parameters to facilitate the modeling of miscanthus in SWAT. Results show a decrease in nitrate load that depends on the percent land use change to miscanthus and the amount of nitrogen fertilizer applied to the miscanthus. Specifically, assuming a nitrogen fertilization rate for miscanthus of 90 kg-N/ha, a 10%, 25%, and 50% land use change to miscanthus will lead to decreases in nitrate load of about 6.4%, 16.5%, and 29.6% at the watershed outlet, respectively. Likewise, nitrate load may be reduced by lowering the fertilizer application rate, but not proportionately. When fertilization drops from 90 to 30 kg-N/ha the difference in nitrate load decrease is less than 1% when 10% of the watershed is miscanthus and less than 6% when 50% of the watershed is miscanthus. It is also found that the nitrate load decrease from converting less than half the watershed to miscanthus from corn and soybean in 1:1 rotation surpasses that from converting the whole watershed to just soybean.

  7. Mass imbalances in EPANET water-quality simulations

    Science.gov (United States)

    Davis, Michael J.; Janke, Robert; Taxon, Thomas N.

    2018-04-01

    EPANET is widely employed to simulate water quality in water distribution systems. However, in general, the time-driven simulation approach used to determine concentrations of water-quality constituents provides accurate results only for short water-quality time steps. Overly long time steps can yield errors in concentration estimates and can result in situations in which constituent mass is not conserved. The use of a time step that is sufficiently short to avoid these problems may not always be feasible. The absence of EPANET errors or warnings does not ensure conservation of mass. This paper provides examples illustrating mass imbalances and explains how such imbalances can occur because of fundamental limitations in the water-quality routing algorithm used in EPANET. In general, these limitations cannot be overcome by the use of improved water-quality modeling practices. This paper also presents a preliminary event-driven approach that conserves mass with a water-quality time step that is as long as the hydraulic time step. Results obtained using the current approach converge, or tend to converge, toward those obtained using the preliminary event-driven approach as the water-quality time step decreases. Improving the water-quality routing algorithm used in EPANET could eliminate mass imbalances and related errors in estimated concentrations. The results presented in this paper should be of value to those who perform water-quality simulations using EPANET or use the results of such simulations, including utility managers and engineers.

  8. Assessing the impacts of sustainable agricultural practices for water quality improvements in the Vouga catchment (Portugal) using the SWAT model.

    Science.gov (United States)

    Rocha, João; Roebeling, Peter; Rial-Rivas, María Ermitas

    2015-12-01

    The extensive use of fertilizers has become one of the most challenging environmental issues in agricultural catchment areas. In order to reduce the negative impacts from agricultural activities and to accomplish the objectives of the European Water Framework Directive we must consider the implementation of sustainable agricultural practices. In this study, we assess sustainable agricultural practices based on reductions in N-fertilizer application rates (from 100% to 0%) and N-application methods (single, split and slow-release) across key agricultural land use classes in the Vouga catchment, Portugal. The SWAT model was used to relate sustainable agricultural practices, agricultural yields and N-NO3 water pollution deliveries. Results show that crop yields as well as N-NO3 exportation rates decrease with reductions in N-application rates and single N-application methods lead to lower crop yields and higher N-NO3 exportation rates as compared to split and slow-release N-application methods. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Evaluating Water Quality in a Suburban Environment

    Science.gov (United States)

    Thomas, S. M.; Garza, N.

    2008-12-01

    A water quality analysis and modeling study is currently being conducted on the Martinez Creek, a small catchment within Cibolo watershed, a sub-basin of the San Antonio River, Texas. Several other major creeks, such as Salatrillo, Escondido, and Woman Hollering merge with Martinez Creek. Land use and land cover analysis shows that the major portion of the watershed is dominated by residential development with average impervious cover percentage of approximately 40% along with a some of agricultural areas and brushlands. This catchment is characterized by the presence of three small wastewater treatment plants. Previous site visits and sampling of water quality indicate the presence of algae and fecal coliform bacteria at levels well above state standards at several locations in the catchment throughout the year. Due to the presence of livestock, residential development and wastewater treatment plants, a comprehensive understanding of water quality is important to evaluate the sources and find means to control pollution. As part of the study, a spatial and temporal water quality analyses of conventional parameters as well as emerging contaminants, such as veterinary pharmaceuticals and microbial pathogens is being conducted to identify critical locations and sources. Additionally, the Hydrologic Simulation Program FORTRAN (HSPF) will be used to identify best management practices that can be incorporated given the projected growth and development and feasibility.

  10. Spatial prediction of water quality variables along a main river channel, in presence of pollution hotspots.

    Science.gov (United States)

    Rizo-Decelis, L D; Pardo-Igúzquiza, E; Andreo, B

    2017-12-15

    In order to treat and evaluate the available data of water quality and fully exploit monitoring results (e.g. characterize regional patterns, optimize monitoring networks, infer conditions at unmonitored locations, etc.), it is crucial to develop improved and efficient methodologies. Accordingly, estimation of water quality along fluvial ecosystems is a frequent task in environment studies. In this work, a particular case of this problem is examined, namely, the estimation of water quality along a main stem of a large basin (where most anthropic activity takes place), from observational data measured along this river channel. We adapted topological kriging to this case, where each watershed contains all the watersheds of the upstream observed data ("nested support effect"). Data analysis was additionally extended by taking into account the upstream distance to the closest contamination hotspot as an external drift. We propose choosing the best estimation method by cross-validation. The methodological approach in spatial variability modeling may be used for optimizing the water quality monitoring of a given watercourse. The methodology presented is applied to 28 water quality variables measured along the Santiago River in Western Mexico. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Use of ocean color scanner data in water quality mapping

    Science.gov (United States)

    Khorram, S.

    1981-01-01

    Remotely sensed data, in combination with in situ data, are used in assessing water quality parameters within the San Francisco Bay-Delta. The parameters include suspended solids, chlorophyll, and turbidity. Regression models are developed between each of the water quality parameter measurements and the Ocean Color Scanner (OCS) data. The models are then extended to the entire study area for mapping water quality parameters. The results include a series of color-coded maps, each pertaining to one of the water quality parameters, and the statistical analysis of the OCS data and regression models. It is found that concurrently collected OCS data and surface truth measurements are highly useful in mapping the selected water quality parameters and locating areas having relatively high biological activity. In addition, it is found to be virtually impossible, at least within this test site, to locate such areas on U-2 color and color-infrared photography.

  12. Survival of brown trout during spring flood in DOC-rich streams in northern Sweden: the effect of present acid deposition and modelled pre-industrial water quality

    International Nuclear Information System (INIS)

    Laudon, Hjalmar; Poleo, Antonio B.S.; Voellestad, Leif Asbjoern; Bishop, Kevin

    2005-01-01

    Mortality and physiological responses in brown trout (Salmo trutta) were studied during spring snow melt in six streams in northern Sweden that differed in concentrations of dissolved organic carbon (DOC) and pH declines. Data from these streams were used to create an empirical model for predicting fish responses (mortality and physiological disturbances) in DOC-rich streams using readily accessible water chemistry parameters. The results suggest that fish in these systems can tolerate higher acidity and inorganic aluminium levels than fish in low DOC streams. But even with the relatively low contemporary deposition load, anthropogenic deposition can cause fish mortality in the most acid-sensitive surface waters in northern Sweden during spring flood. However, the results suggests that it is only in streams with high levels of organically complexed aluminium in combination with a natural pH decline to below 5.0 during the spring where current sulphur deposition can cause irreversible damage to brown trout in the region. This study support earlier studies suggesting that DOC has an ameliorating effect on physiological disturbances in humic waters but the study also shows that surviving fish recover physiologically when the water quality returns to less toxic conditions following a toxic high flow period. The physiological response under natural, pre-industrial conditions was also estimated. - High levels of complexed aluminum, at pH levels below 5.0, predisposes brown trout to sulfur-caused damage in the spring

  13. Survival of brown trout during spring flood in DOC-rich streams in northern Sweden: the effect of present acid deposition and modelled pre-industrial water quality

    Energy Technology Data Exchange (ETDEWEB)

    Laudon, Hjalmar [Department of Forest Ecology, Swedish University of Agricultural Sciences, SE-901 83 Umeaa (Sweden)]. E-mail: hjalmar.laudon@sek.slu.se; Poleo, Antonio B.S. [Department of Biology, University of Oslo, P.O. Box 1066 Blindern, N-0316 Oslo (Norway); Voellestad, Leif Asbjoern [Department of Biology, University of Oslo, P.O. Box 1066 Blindern, N-0316 Oslo (Norway); Bishop, Kevin [Department of Environmental Assessment, Swedish University of Agricultural Sciences, SE-750 07 Uppsala (Sweden)

    2005-05-01

    Mortality and physiological responses in brown trout (Salmo trutta) were studied during spring snow melt in six streams in northern Sweden that differed in concentrations of dissolved organic carbon (DOC) and pH declines. Data from these streams were used to create an empirical model for predicting fish responses (mortality and physiological disturbances) in DOC-rich streams using readily accessible water chemistry parameters. The results suggest that fish in these systems can tolerate higher acidity and inorganic aluminium levels than fish in low DOC streams. But even with the relatively low contemporary deposition load, anthropogenic deposition can cause fish mortality in the most acid-sensitive surface waters in northern Sweden during spring flood. However, the results suggests that it is only in streams with high levels of organically complexed aluminium in combination with a natural pH decline to below 5.0 during the spring where current sulphur deposition can cause irreversible damage to brown trout in the region. This study support earlier studies suggesting that DOC has an ameliorating effect on physiological disturbances in humic waters but the study also shows that surviving fish recover physiologically when the water quality returns to less toxic conditions following a toxic high flow period. The physiological response under natural, pre-industrial conditions was also estimated. - High levels of complexed aluminum, at pH levels below 5.0, predisposes brown trout to sulfur-caused damage in the spring.

  14. 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...

  15. 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.

  16. Spatial variability analysis of combining the water quality and groundwater flow model to plan groundwater and surface water management in the Pingtung plain

    Science.gov (United States)

    Chen, Ching-Fang; Chen, Jui-Sheng; Jang, Cheng-Shin

    2014-05-01

    As a result of rapid economic growth in the Pingtung Plain, the use of groundwater resources has changed dramatically. The groundwater is quite rich in the Pingtung plain and the most important water sources. During the several decades, a substantial amount of groundwater has been pumped for the drinking, irrigation and aquaculture water supplies. However, because the sustainable use concept of groundwater resources is lack, excessive pumping of groundwater causes the occurrence of serious land subsidence and sea water intrusion. Thus, the management and conservation of groundwater resources in the Pingtung plain are considerably critical. This study aims to assess the conjunct use effect of groundwater and surface water in the Pingtung plain on recharge by reducing the amount of groundwater extraction. The groundwater quality variability and groundwater flow models are combined to spatially analyze potential zones of groundwater used for multi-purpose in the Pingtung Plain. First, multivariate indicator kriging (MVIK) is used to analyze spatial variability of groundwater quality based on drinking, aquaculture and irrigation water quality standards, and probabilistically delineate suitable zones in the study area. Then, the groundwater flow model, Processing MODFLOW (PMWIN), is adopted to simulate groundwater flow. The groundwater flow model must be conducted by the calibration and verification processes, and the regional groundwater recovery is discussed when specified water rights are replaced by surface water in the Pingtung plain. Finally, the most suitable zones of reducing groundwater use are determined for multi-purpose according to combining groundwater quality and quantity. The study results can establish a sound and low-impact management plan of groundwater resources utilization for the multi-purpose groundwater use, and prevent decreasing ground water tables, and the occurrence of land subsidence and sea water intrusion in the Pingtung plain.

  17. 流域水质管理优化决策模型研究%Watershed optimal decision models for water-quality management

    Institute of Scientific and Technical Information of China (English)

    盛虎; 向男; 郭怀成; 刘永

    2013-01-01

    针对目前流域水污染难以有效控制的局面,依据已有的流域水文、水动力、水质、水生态相关机理模拟模型的研究,在考虑了流域社会经济发展条件的基础上,构建了流域水质管理优化决策模型框架体系.基于该框架体系,本文从简单流域系统优化模型、模拟与优化联合模型和时空尺度复杂优化模型3个方面对流域优化决策模型的研究发展历程进行综述,并指出其各自在发展过程中所出现的问题.最后,提出了优化决策模型面临的瓶颈问题,并从模型结构简化和适应性管理两个方面提出了相关的解决思路.%In light of the difficulties in effective water pollution control, this study formulated a watershed optimal management decision model framework based on relevant researches on mechanistic modeling of watershed hydrology, hydrodynamics, water quality and aquatic ecology. The decision model framework also took into account the existing socio-economic development status in watersheds. Based on this framework, we reviewed the history and current status of watershed optimal decision support models from three different aspects; simple systematic optimization models, coupled simulation-optimization model, and complicated optimization models on different temporal and spatial scales. Meanwhile, the problems during the development of watershed optimization models were identified. Finally, in order to solve the bottle-neck of computation for watershed optimization models, simplification of the structure of simulation models and adaptive management were recommended.

  18. Optical sensors for water quality

    Science.gov (United States)

    Pellerin, Brian A.; Bergamaschi, Brian A.

    2014-01-01

    Shifts in land use, population, and climate have altered hydrologic systems in the United States in ways that affect water quality and ecosystem function. Water diversions, detention in reservoirs, increased channelization, and changes in rainfall and snowmelt are major causes, but there are also more subtle causes such as changes in soil temperature, atmospheric deposition, and shifting vegetation patterns. The effects on water quality are complex and interconnected, and occur at timeframes of minutes (e.g., flash floods) to decades (e.g., evolving management practices).

  19. Scoping Assessment for Developing a Water Quality Monitoring Plan to Support Application of the CE-QUAL-W2 Hydrodynamic and Water Quality Model to the Lower Missouri River downstream of Gavins Point Dam

    Science.gov (United States)

    2010-04-01

    setting up input geometry for the Missouri River : 1) channel geometry will be obtained from previous HEC - RAS modeling of the lower Missouri River , and 2...stage-discharge rating curves developed for USGS and USACE gaging stations on the Missouri River . HEC - RAS (Hydrologic Engineering Center- River ...adjusted to better match the “project” table. For the lower Missouri River , initial cell widths will be derived from past HEC - RAS modeling

  20. Evaluation of Bayesian estimation of a hidden continuous-time Markov chain model with application to threshold violation in water-quality indicators

    Science.gov (United States)

    Deviney, Frank A.; Rice, Karen; Brown, Donald E.

    2012-01-01

    Natural resource managers require information concerning  the frequency, duration, and long-term probability of occurrence of water-quality indicator (WQI) violations of defined thresholds. The timing of these threshold crossings often is hidden from the observer, who is restricted to relatively infrequent observations. Here, a model for the hidden process is linked with a model for the observations, and the parameters describing duration, return period, and long-term probability of occurrence are estimated using Bayesian methods. A simulation experiment is performed to evaluate the approach under scenarios based on the equivalent of a total monitoring period of 5-30 years and an observation frequency of 1-50 observations per year. Given constant threshold crossing rate, accuracy and precision of parameter estimates increased with longer total monitoring period and more-frequent observations. Given fixed monitoring period and observation frequency, accuracy and precision of parameter estimates increased with longer times between threshold crossings. For most cases where the long-term probability of being in violation is greater than 0.10, it was determined that at least 600 observations are needed to achieve precise estimates.  An application of the approach is presented using 22 years of quasi-weekly observations of acid-neutralizing capacity from Deep Run, a stream in Shenandoah National Park, Virginia. The time series also was sub-sampled to simulate monthly and semi-monthly sampling protocols. Estimates of the long-term probability of violation were unbiased despite sampling frequency; however, the expected duration and return period were over-estimated using the sub-sampled time series with respect to the full quasi-weekly time series.

  1. 43 CFR 414.5 - Water quality.

    Science.gov (United States)

    2010-10-01

    ... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Water quality. 414.5 Section 414.5 Public... APPORTIONMENT IN THE LOWER DIVISION STATES Water Quality and Environmental Compliance § 414.5 Water quality. (a) Water Quality is not guaranteed. The Secretary does not warrant the quality of water released or...

  2. 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)

  3. Solid Wastes and Water Quality.

    Science.gov (United States)

    DeWalle, F. B.; Chian, E. S. K.

    1978-01-01

    Presents a literature review of solid wastes and water quality, covering publications of 1976-77. This review covers areas such as: (1) environmental impacts and health aspects for waste disposal, and (2) processed and hazardous wastes. A list of 80 references is also presented. (HM)

  4. Water Quality Monitoring by Satellite

    Science.gov (United States)

    Journal of Chemical Education, 2004

    2004-01-01

    The availability of abundant water resources in the Upper Midwest of the United States is nullified by their contamination through heavy commercial and industrial activities. Scientists have taken the responsibility of detecting the water quality of these resources through remote-sensing satellites to develop a wide-ranging water purification plan…

  5. 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

  6. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  7. SIMONI (smart integrated monitoring) as a novel bioanalytical strategy for water quality assessment : Part i–model design and effect-based trigger values

    NARCIS (Netherlands)

    van der Oost, Ron; Sileno, Giulia; Suárez-Muñoz, Maria; Nguyen, Mai Thao; Besselink, Harrie; Brouwer, Abraham

    2017-01-01

    It is virtually impossible to reliably assess water quality with target chemical analyses only. Therefore, a complementary effect-based risk assessment by bioanalyses on mixtures of bioavailable micropollutants is proposed: the Smart Integrated Monitoring (SIMONI) strategy. The goal of this strategy

  8. Modeling framework for representing long-term effectiveness of best management practices in addressing hydrology and water quality problems: Framework development and demonstraton using a Bayesian method

    Science.gov (United States)

    Best management practices (BMPs) are popular approaches used to improve hydrology and water quality. Uncertainties in BMP effectiveness over time may result in overestimating long-term efficiency in watershed planning strategies. To represent varying long-term BMP effectiveness in hydrologic/water q...

  9. 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.

  10. Estimating and Predicting Metal Concentration Using Online Turbidity Values and Water Quality Models in Two Rivers of the Taihu Basin, Eastern China.

    Science.gov (United States)

    Yao, Hong; Zhuang, Wei; Qian, Yu; Xia, Bisheng; Yang, Yang; Qian, Xin

    2016-01-01

    Turbidity (T) has been widely used to detect the occurrence of pollutants in surface water. Using data collected from January 2013 to June 2014 at eleven sites along two rivers feeding the Taihu Basin, China, the relationship between the concentration of five metals (aluminum (Al), titanium (Ti), nickel (Ni), vanadium (V), lead (Pb)) and turbidity was investigated. Metal concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). The linear regression of metal concentration and turbidity provided a good fit, with R(2) = 0.86-0.93 for 72 data sets collected in the industrial river and R(2) = 0.60-0.85 for 60 data sets collected in the cleaner river. All the regression presented good linear relationship, leading to the conclusion that the occurrence of the five metals are directly related to suspended solids, and these metal concentration could be approximated using these regression equations. Thus, the linear regression equations were applied to estimate the metal concentration using online turbidity data from January 1 to June 30 in 2014. In the prediction, the WASP 7.5.2 (Water Quality Analysis Simulation Program) model was introduced to interpret the transport and fates of total suspended solids; in addition, metal concentration downstream of the two rivers was predicted. All the relative errors between the estimated and measured metal concentration were within 30%, and those between the predicted and measured values were within 40%. The estimation and prediction process of metals' concentration indicated that exploring the relationship between metals and turbidity values might be one effective technique for efficient estimation and prediction of metal concentration to facilitate better long-term monitoring with high temporal and spatial density.

  11. seasonal variation in water quality of orle river basin, sw nigeria.

    African Journals Online (AJOL)

    LUCY

    The seasonal variation of water quality of Orle River and its tributatries in S.W. Nigeria was investigated forthnightly or two ... KEYWORD: water quality, river basin, wet and dry seasons; pollution. ..... Environmental Modeling and Software,.

  12. Estimation of the fate of microbial water-quality contaminants in a South-African river

    CSIR Research Space (South Africa)

    Hohls, D

    1995-01-01

    Full Text Available The aim of this study was to evaluate the validity of assumptions, regarding assimilative capacity for microbial contaminants, implicit in microbial water quality management in South Africa. A one dimensional steady state stream water quality model...

  13. Estimation of Constituent Concentrations, Loads, and Yields in Streams of Johnson County, Northeast Kansas, Using Continuous Water-Quality Monitoring and Regression Models, October 2002 through December 2006

    Science.gov (United States)

    Rasmussen, Teresa J.; Lee, Casey J.; Ziegler, Andrew C.

    2008-01-01

    Johnson County is one of the most rapidly developing counties in Kansas. Population growth and expanding urban land use affect the quality of county streams, which are important for human and environmental health, water supply, recreation, and aesthetic value. This report describes estimates of streamflow and constituent concentrations, loads, and yields in relation to watershed characteristics in five Johnson County streams using continuous in-stream sensor measurements. Specific conductance, pH, water temperature, turbidity, and dissolved oxygen were monitored in five watersheds from October 2002 through December 2006. These continuous data were used in conjunction with discrete water samples to develop regression models for continuously estimating concentrations of other constituents. Continuous regression-based concentrations were estimated for suspended sediment, total suspended solids, dissolved solids and selected major ions, nutrients (nitrogen and phosphorus species), and fecal-indicator bacteria. Continuous daily, monthly, seasonal, and annual loads were calculated from concentration estimates and streamflow. The data are used to describe differences in concentrations, loads, and yields and to explain these differences relative to watershed characteristics. Water quality at the five monitoring sites varied according to hydrologic conditions; contributing drainage area; land use (including degree of urbanization); relative contributions from point and nonpoint constituent sources; and human activity within each watershed. Dissolved oxygen (DO) concentrations were less than the Kansas aquatic-life-support criterion of 5.0 mg/L less than 10 percent of the time at all sites except Indian Creek, which had DO concentrations less than the criterion about 15 percent of the time. Concentrations of suspended sediment, chloride (winter only), indicator bacteria, and pesticides were substantially larger during periods of increased streamflow. Suspended

  14. Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water.

    Science.gov (United States)

    Salari, Marjan; Salami Shahid, Esmaeel; Afzali, Seied Hosein; Ehteshami, Majid; Conti, Gea Oliveri; Derakhshan, Zahra; Sheibani, Solmaz Nikbakht

    2018-04-22

    Today, due to the increase in the population, the growth of industry and the variety of chemical compounds, the quality of drinking water has decreased. Five important river water quality properties such as: dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (ALK) and turbidity (TU) were estimated by parameters such as: electric conductivity (EC), temperature (T), and pH that could be measured easily with almost no costs. Simulate water quality parameters were examined with two methods of modeling include mathematical and Artificial Neural Networks (ANN). Mathematical methods are based on polynomial fitting with least square method and ANN modeling algorithms are feed-forward networks. All conditions/circumstances covered by neural network modeling were tested for all parameters in this study, except for Alkalinity. All optimum ANN models developed to simulate water quality parameters had precision value as R-value close to 0.99. The ANN model extended to simulate alkalinity with R-value equals to 0.82. Moreover, Surface fitting techniques were used to refine data sets. Presented models and equations are reliable/useable tools for studying water quality parameters at similar rivers, as a proper replacement for traditional water quality measuring equipment's. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Water Quality Vocabulary Development and Deployment

    Science.gov (United States)

    Simons, B. A.; Yu, J.; Cox, S. J.

    2013-12-01

    Semantic descriptions of observed properties and associated units of measure are fundamental to understanding of environmental observations, including groundwater, surface water and marine water quality. Semantic descriptions can be captured in machine-readable ontologies and vocabularies, thus providing support for the annotation of observation values from the disparate data sources with appropriate and accurate metadata, which is critical for achieving semantic interoperability. However, current stand-alone water quality vocabularies provide limited support for cross-system comparisons or data fusion. To enhance semantic interoperability, the alignment of water-quality properties with definitions of chemical entities and units of measure in existing widely-used vocabularies is required. Modern ontologies and vocabularies are expressed, organized and deployed using Semantic Web technologies. We developed an ontology for observed properties (i.e. a model for expressing appropriate controlled vocabularies) which extends the NASA/TopQuadrant QUDT ontology for Unit and QuantityKind with two additional classes and two properties (see accompanying paper by Cox, Simons and Yu). We use our ontology to populate the Water Quality vocabulary with a set of individuals of each of the four key classes (and their subclasses), and add appropriate relationships between these individuals. This ontology is aligned with other relevant stand-alone Water Quality vocabularies and domain ontologies. Developing the Water Quality vocabulary involved two main steps. First, the Water Quality vocabulary was populated with individuals of the ObservedProperty class, which was determined from a census of existing datasets and services. Each ObservedProperty individual relates to other individuals of Unit and QuantityKind (taken from QUDT where possible), and to IdentifiedObject individuals. As a large fraction of observed water quality data are classified by the chemical substance involved, the

  16. Water quality index for assessment of water quality of river ravi at ...

    African Journals Online (AJOL)

    Water quality of River Ravi, a tributary of Indus River System was evaluated by Water Quality Index (WQI) technique. A water quality index provides a single number that expresses overall water quality at a certain location and time based on several water quality parameters. The objective of an index is to turn complex water ...

  17. Water quality relationships and evaluation using a new water quality index

    International Nuclear Information System (INIS)

    Said, A.; Stevens, D.; Sehlke, G.

    2002-01-01

    Water quality is dependent on a variety of measures, including dissolved oxygen, microbial contamination, turbidity, nutrients, temperature, pH, and other constituents. Determining relationships between water quality parameters can improve water quality assessment, and watershed management. In addition, these relationships can be very valuable in case of evaluating water quality in watersheds that have few water quality data. (author)

  18. 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

  19. 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

  20. Modeling the Environmental Fate of Graphene Oxide and Its Phototransformation Products in Brier Creek Watershed Using the Water Quality Analysis Simulation Program 8 (WASP8)

    Science.gov (United States)

    Han, Y.; Bouchard, D.; Chang, X.; Hsieh, H. S.; Knightes, C. D.; Spear, J.; Zepp, R. G.

    2017-12-01

    The production of graphene-family nanoparticles (GFNs) appreciably increased in recent years. Among GFNs, graphene oxide (GO) is one of the most highly studied members due to its inexpensive synthesis cost compared to graphene, its stability in aqueous media and its broad application. However, GO also has been found to be the most toxic among GFNs. Lab studies showed that GO undergoes phototransformation in surface waters, resulting in products that include reduced GO (rGO) and polycyclic aromatic hydrocarbons (PAHs). Due to technical and analytical limitations, it is still difficult to conduct in-situ measurement of GO and rGO concentrations released in the environment, and it is of utmost importance to establish a model that can predict their environmental exposure concentrations in the environment. In this study, we develop a fate and transport model to predict time-dependent environmental exposure concentrations of GO for the Brier Creek Watershed in the GA coastal plain. We investigate the influence of sunlight radiation on the distribution of GO and its phototransformation products in the watershed over a 20-year period using the most updated Water Quality Analysis Simulation Program (WASP8). Flow rate, sediment transport data and sunlight radiation data are input into WASP8, and WASP8 is used to internally calculate a GO phototransformation rate and productions of rGO and PAHs. Heteroaggregation coefficients of GO and rGO with suspended solids were measured in an EPA laboratory, and then input into WASP8. GO and rGO concentrations in the watershed are calculated by WASP8. Mass fraction results show that GO is the predominant species among GO derived species, which account for 99% of the mass throughout the whole watershed of interest, while rGO species, including free rGO and rGO heteroaggregated to suspended solids, only account for 1%. We also found that almost all free GO and rGO are present in water column due to their extremely low settling velocity. r

  1. Water quality criteria for lead

    Energy Technology Data Exchange (ETDEWEB)

    Nagpal, N.K.

    1987-01-01

    This report is one in a series that establishes water quality criteria for British Columbia. The report sets criteria for lead to protect a number of water uses, including drinking water, freshwater and marine aquatic life, wildlife, livestock, irrigation, and recreation. The criteria are set as either maximum concentrations of total lead that should not be exceeded at any time, or average concentrations that should not be exceeded over a 30-day period. Actual values are summarized.

  2. Portable water quality monitoring system

    Science.gov (United States)

    Nizar, N. B.; Ong, N. R.; Aziz, M. H. A.; Alcain, J. B.; Haimi, W. M. W. N.; Sauli, Z.

    2017-09-01

    Portable water quality monitoring system was a developed system that tested varied samples of water by using different sensors and provided the specific readings to the user via short message service (SMS) based on the conditions of the water itself. In this water quality monitoring system, the processing part was based on a microcontroller instead of Lead and Copper Rule (LCR) machines to receive the results. By using four main sensors, this system obtained the readings based on the detection of the sensors, respectively. Therefore, users can receive the readings through SMS because there was a connection between Arduino Uno and GSM Module. This system was designed to be portable so that it would be convenient for users to carry it anywhere and everywhere they wanted to since the processor used is smaller in size compared to the LCR machines. It was also developed to ease the user to monitor and control the water quality. However, the ranges of the sensors' detection still a limitation in this study.

  3. Water quality for liquid wastes

    International Nuclear Information System (INIS)

    Mizuniwa, Fumio; Maekoya, Chiaki; Iwasaki, Hitoshi; Yano, Hiroaki; Watahiki, Kazuo.

    1985-01-01

    Purpose: To facilitate the automation of the operation for a liquid wastes processing system by enabling continuous analysis for the main ingredients in the liquid wastes accurately and rapidly. Constitution: The water quality monitor comprises a sampling pipeway system for taking out sample water for the analysis of liquid wastes from a pipeway introducing liquid wastes to the liquid wastes concentrator, a filter for removing suspended matters in the sample water and absorption photometer as a water quality analyzer. A portion of the liquid wastes is passed through the suspended matter filter by a feedpump. In this case, sulfate ions and chloride ions in the sample are retained in the upper portion of a separation color and, subsequently, the respective ingredients are separated and leached out by eluting solution. Since the leached out ingredients form ferric ions and yellow complexes respectively, their concentrations can be detected by the spectrum photometer. Accordingly, concentration for the sodium sulfate and sodium chloride in the liquid wastes can be analyzed rapidly, accurately and repeatedly by which the water quality can be determined rapidly and accurately. (Yoshino, Y.)

  4. Hydroeconomic optimization of reservoir management under downstream water quality constraints

    DEFF Research Database (Denmark)

    Davidsen, Claus; Liu, Suxia; Mo, Xingguo

    2015-01-01

    water quantity and water quality management and minimizes the total costs over a planning period assuming stochastic future runoff. The outcome includes cost-optimal reservoir releases, groundwater pumping, water allocation, wastewater treatments and water curtailments. The optimization model uses......), and the resulting minimum dissolved oxygen (DO) concentration is computed with the Streeter-Phelps equation and constrained to match Chinese water quality targets. The baseline water scarcity and operational costs are estimated to 15.6. billion. CNY/year. Compliance to water quality grade III causes a relatively...

  5. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim

    2014-12-03

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  6. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.

    2014-01-01

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  7. Water quality issues and status in Pakistan

    International Nuclear Information System (INIS)

    Kahlown, M.A.; Tahir, M. A.; Ashraf, M.

    2005-01-01

    Per capita water availability in Pakistan has dropped drastically during the last fifty years. Recent extended droughts have further aggravated the situation. In order to meet the shortage and crop water requirements, groundwater is being used extensively in the Indus Basin. Groundwater is also the main source of water for drinking and industrial uses. This increased pressure on groundwater has lowered the water table in many cities. It is reported that water table has dropped by more than 3 m in many cities. This excessive use of groundwater has seriously affected the quality of groundwater and has increased the incidences of water-borne diseases many folds. A recent water quality study has shown that out of 560,000 tube wells of Indus Basin, about 70 percent are pumping sodic water. The use of sodic water has in turn affected the soil health and crop yields. This situation is being further aggravated due to changes in climate and rainfall patterns. To monitor changes in surface and groundwater quality and groundwater levels, Pakistan Council of Research in Water Resources has undertaken a countrywide programme of water quality monitoring. This programme covers twenty-one cities from the four provinces, five rivers, 10 storage reservoirs and lakes and two main drains of Pakistan. Under this programme a permanent monitoring network is established from where water samples are collected and analyzed once every year. The collected water samples are analyzed for aesthetic, chemical and bacteriological parameters to determine their suitability for agricultural, domestic and industrial uses. The results of the present study indicate serious contamination in many cities. Excessive levels of arsenic, fluoride and sodium have been detected in many cities. This paper highlights the major water quality issues and briefly presents the preliminary results of the groundwater analysis for major cities of Pakistan. (author)

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

    Science.gov (United States)

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

    2017-02-01

    xml:id="wrcr22485-sec-1001" numbered="no">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.

  9. 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.

  10. Control options for river water quality improvement: a case study of ...

    African Journals Online (AJOL)

    Using a simple conceptual dynamic river water quality model, the effects of different basin-wide water quality management options on downstream water quality improvements in a semi-arid river, the Crocodile River (South Africa) were investigated. When a river is impacted by high rates of freshwater withdrawal (in its ...

  11. Modeling online social signed networks

    Science.gov (United States)

    Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

    2018-04-01

    People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

  12. San Francisco Bay Water Quality Improvement Fund

    Science.gov (United States)

    EPAs grant program to protect and restore San Francisco Bay. The San Francisco Bay Water Quality Improvement Fund (SFBWQIF) has invested in 58 projects along with 70 partners contributing to restore wetlands, water quality, and reduce polluted runoff.,

  13. Assessing water quality in Lake Naivasha

    NARCIS (Netherlands)

    Ndungu, J.N.

    2014-01-01

    Water quality in aquatic systems is important because it maintains the ecological processes that support biodiversity. However, declining water quality due to environmental perturbations threatens the stability of the biotic integrity and therefore hinders the ecosystem services and functions of

  14. National Water Quality Standards Database (NWQSD)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The National Water Quality Standards Database (WQSDB) provides access to EPA and state water quality standards (WQS) information in text, tables, and maps. This data...

  15. R2 Water Quality Portal Monitoring Stations

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Water Quality Data Portal (WQP) provides an easy way to access data stored in various large water quality databases. The WQP provides various input parameters on...

  16. Water quality and water rights in Colorado

    International Nuclear Information System (INIS)

    MacDonnell, L.J.

    1989-07-01

    The report begins with a review of early Colorado water quality law. The present state statutory system of water quality protection is summarized. Special attention is given to those provisions of Colorado's water quality law aimed at protecting water rights. The report then addresses several specific issues which involve the relationship between water quality and water use. Finally, recommendations are made for improving Colorado's approach to integrating quality and quantity concerns

  17. A neighbourhood evolving network model

    International Nuclear Information System (INIS)

    Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.

    2006-01-01

    Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development

  18. [Drinking water quality and safety].

    Science.gov (United States)

    Gómez-Gutiérrez, Anna; Miralles, Maria Josepa; Corbella, Irene; García, Soledad; Navarro, Sonia; Llebaria, Xavier

    2016-11-01

    The purpose of drinking water legislation is to guarantee the quality and safety of water intended for human consumption. In the European Union, Directive 98/83/EC updated the essential and binding quality criteria and standards, incorporated into Spanish national legislation by Royal Decree 140/2003. This article reviews the main characteristics of the aforementioned drinking water legislation and its impact on the improvement of water quality against empirical data from Catalonia. Analytical data reported in the Spanish national information system (SINAC) indicate that water quality in Catalonia has improved in recent years (from 88% of analytical reports in 2004 finding drinking water to be suitable for human consumption, compared to 95% in 2014). The improvement is fundamentally attributed to parameters concerning the organoleptic characteristics of water and parameters related to the monitoring of the drinking water treatment process. Two management experiences concerning compliance with quality standards for trihalomethanes and lead in Barcelona's water supply are also discussed. Finally, this paper presents some challenges that, in the opinion of the authors, still need to be incorporated into drinking water legislation. It is necessary to update Annex I of Directive 98/83/EC to integrate current scientific knowledge, as well as to improve consumer access to water quality data. Furthermore, a need to define common criteria for some non-resolved topics, such as products and materials in contact with drinking water and domestic conditioning equipment, has also been identified. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

  19. Characterization (environmental Signature) and Function of the Main Instrumented (monitoring Water Quality Network in Real Time) Rivers Atoyac and Zahuapan in High Atoyac Basin; in Dry, Rain and Winter Season 2013-2014; Puebla-Tlaxcala Mexico

    Science.gov (United States)

    Tavera, E. M.; Rodriguez-Espinosa, P. F.; Morales-Garcia, S. S.; Muñoz-Sevilla, N. P.

    2014-12-01

    The Zahuapan and Atoyac rivers were characterized in the Upper Atoyac through the integration of physical and chemical parameters (environmental firm) determining the behavior and function of the basin as a tool for measuring and monitoring the quality and management of water resources of the water in one of the most polluted rivers in Mexico. For the determination of the environmental signature proceeded to characterize the water through 11 physicochemical parameters: temperature (T), potential hydrogen (pH), dissolved oxygen (DO), spectral absorption coefficient (SAC), the reduction of oxide potential (ORP), turbidity (Turb), conductivity (l), biochemical oxygen demand in 5 days (BOD5), chemical oxygen demand (COD), total suspended solids (TSS) and total dissolved solids (TDS ), which were evaluated in 49 sites in the dry season, 47 for the rainy season and 23 for the winter season in the basin and Atoyac Zahuapan Alto Atoyac, Puebla-Tlaxcala, Mexico river; finding a mathematical algorithm to assimilate and better represent the information obtained. The algorithm allows us to estimate correlation greater than 0.85. The results allow us to propose the algorithm used in the monitoring stations for purposes of processing information assimilated form.This measurement and monitoring of water quality supports the project, the monitoring network in real time and the actions to clean up Atoyac River, in the urban area of the city of Puebla.

  20. Dam water quality study. Report to Congress

    International Nuclear Information System (INIS)

    1989-05-01

    The objective of the report is to identify water quality effects attributable to the impoundment of water by dams as required by Section 524 of the Water Quality Act of 1987. The document presents a study of water quality effects associated with impoundments in the U.S.A

  1. 9 CFR 3.106 - Water quality.

    Science.gov (United States)

    2010-01-01

    ... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Water quality. 3.106 Section 3.106... Mammals Animal Health and Husbandry Standards § 3.106 Water quality. (a) General. The primary enclosure... additives (e.g. chlorine and copper) that are added to the water to maintain water quality standards...

  2. 18 CFR 801.7 - Water quality.

    Science.gov (United States)

    2010-04-01

    ... 18 Conservation of Power and Water Resources 2 2010-04-01 2010-04-01 false Water quality. 801.7... POLICIES § 801.7 Water quality. (a) The signatory States have the primary responsibility in the basin for water quality management and control. However, protection of the water resources of the basin from...

  3. Part 2: Surface water quality

    International Nuclear Information System (INIS)

    1997-01-01

    In 1996 the surface water quality measurements were performed, according to the Agreement, at 8 profiles on the Hungarian territory and at 15 profiles on the Slovak territory. Basic physical and chemical parameters (as water temperature, pH values, conductivity, suspended solids, cations and anions (nitrates, ammonium ion, nitrites, total nitrogen, phosphates, total phosphorus, oxygen and organic carbon regime parameters), metals (iron, manganese and heavy metals), biological and microbiological parameters (coliform bacteria, chlorophyll-a, saprobity index and other biological parameters) and quality of sediment were measured

  4. 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...

  5. Statistical Framework for Recreational Water Quality Criteria and Monitoring

    DEFF Research Database (Denmark)

    Halekoh, Ulrich

    2008-01-01

    recreational governmental authorities controlling water quality. The book opens with a historical account of water quality criteria in the USA between 1922 and 2003. Five chapters are related to sampling strategies and decision rules. Chapter 2 discusses the dependence of decision-making rules on short...... modeling exploiting additional information like meteorological data can support the decision process as shown in Chapter 10. The question of which information to extract from water sample analyses is closely related to the task of risk assessment for human health. Beach-water quality is often measured......Administrators of recreational waters face the basic tasks of surveillance of water quality and decisions on beach closure in case of unacceptable quality. Monitoring and subsequent decisions are based on sampled water probes and fundamental questions are which type of data to extract from...

  6. Review on water quality sensors

    Science.gov (United States)

    Kruse, Peter

    2018-05-01

    Terrestrial life may be carbon-based, but most of its mass is made up of water. Access to clean water is essential to all aspects of maintaining life. Mainly due to human activity, the strain on the water resources of our planet has increased substantially, requiring action in water management and purification. Water quality sensors are needed in order to quantify the problem and verify the success of remedial actions. This review summarizes the most common chemical water quality parameters, and current developments in sensor technology available to monitor them. Particular emphasis is on technologies that lend themselves to reagent-free, low-maintenance, autonomous and continuous monitoring. Chemiresistors and other electrical sensors are discussed in particular detail, while mechanical, optical and electrochemical sensors also find mentioning. The focus here is on the physics of chemical signal transduction in sensor elements that are in direct contact with the analyte. All other sensing methods, and all other elements of sampling, sample pre-treatment as well as the collection, transmission and analysis of the data are not discussed here. Instead, the goal is to highlight the progress and remaining challenges in the development of sensor materials and designs for an audience of physicists and materials scientists.

  7. Combination Use of Water Quality Modelling and Cost-Effective Analysis to Assess Environmental Benefit of a Watershed - A Case Study of Various Engineering and Management Strategy Arrangements in Taiwan

    Science.gov (United States)

    Fan, C.; Wu, C. Y.

    2017-12-01

    This study aimed to evaluate the potential environmental benefits using the water quality modelling integrated with cost-effective analysis to assess several proposed scenarios of engineering and management arrangements based on regional development planning and pollution mitigation strategy. The QUAL2Kw models of Erhjen river and its major tributary, Sanye creek, were established to simulate the river pollution indices of dissolved oxygen (DO), biochemical oxygen demand (BOD), suspended solids (SS) and ammonia nitrogen (NH3-N). The HEC-RAS was employed to calculate the hydraulic parameters and dilution impact of tidal effect in the downstream section. The verified integrated model was applied to estimating the water quality variations for several given scenarios considering the possible re-arrangement of projected pollution mitigation implementations, such as sewage system construction facilitation, additional on-site treatment facilities establishment and pig-manure anaerobic fermentation for biogas power generation in the Erhjen river watershed. As a result, the water quality of the Sanye creek was apparently improved after the completion of sewage system construction. The ammonia nitrogen concentration reduced from the level 6 to 10 times above severely-polluted standard to the merely-above level. By ignoring the impact of ammonia nitrogen on river pollution index calculation, the water quality of the lower section of the Sanye creek was improved to slightly-polluted or non-polluted level. In the scenario of anaerobic fermentation promotion, if manure anaerobic fermentation facilities were installed in all the pig farms with livestock number more than 2000, water quality was estimated to be improved slightly only. Furthermore, if all the manure waste from pig-farms is collected for subsequent electricity generation in the investigated watershed, the river pollution index is estimated to improve to moderately-polluted category for all the length of Erhjen river

  8. R2 Water Quality Portal Monitoring Stations

    Science.gov (United States)

    The Water Quality Data Portal (WQP) provides an easy way to access data stored in various large water quality databases. The WQP provides various input parameters on the form including location, site, sampling, and date parameters to filter and customize the returned results. The The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA) and the National Water Quality Monitoring Council (NWQMC) that integrates publicly available water quality data from the USGS National Water Information System (NWIS) the EPA STOrage and RETrieval (STORET) Data Warehouse, and the USDA ARS Sustaining The Earth??s Watersheds - Agricultural Research Database System (STEWARDS).

  9. Drinking water quality of Sukkur municipal corporation

    International Nuclear Information System (INIS)

    Kandhar, I.A.; Ansari, A.K.

    2002-01-01

    SMC (Sukkur Municipal Corporation) supply the (filtered/settled) water for domestic purpose to the consumers, through intermittent water supply, from Phases I to IV. The water supply distribution network is underground and at most places pass parallel to sewerage lines. The grab sampling technique was followed for collecting representative samples. The official US-EPA and standard methods of water analysis have been used for drinking water quality analysis. DR/2000 spectrophotometer has been used for monitoring: Nitrates, Fluorides, Sulfates, Copper, Chromium, Iron and manganese. The trace metals Cr/sup 6/, Fe/sup 2+/ and other contaminants like; Turbidity and TSS (Total Suspended Solids) have been found higher than World Health Organization (WHO-1993) guideline values. (author)

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

    Institute of Scientific and Technical Information of China (English)

    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.

  11. 78 FR 20252 - Water Quality Standards; Withdrawal of Certain Federal Water Quality Criteria Applicable to...

    Science.gov (United States)

    2013-04-04

    ... Water Quality Standards; Withdrawal of Certain Federal Water Quality Criteria Applicable to California... aquatic life water quality criteria applicable to waters of New Jersey, Puerto Rico, and California's San Francisco Bay. In 1992, EPA promulgated the National Toxics Rule or NTR to establish numeric water quality...

  12. 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)

  13. Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

    Science.gov (United States)

    Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

    2017-07-01

    Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

  14. The water quality of the LOCAR Pang and Lambourn catchments

    Directory of Open Access Journals (Sweden)

    C. Neal

    2004-01-01

    Full Text Available The water quality of the Pang and Lambourn, tributaries of the River Thames, in south-eastern England, is described in relation to spatial and temporal dimensions. The river waters are supplied mainly from Chalk-fed aquifer sources and are, therefore, of a calcium-bicarbonate type. The major, minor and trace element chemistry of the rivers is controlled by a combination of atmospheric and pollutant inputs from agriculture and sewage sources superimposed on a background water quality signal linked to geological sources. Water quality does not vary greatly over time or space. However, in detail, there are differences in water quality between the Pang and Lambourn and between sites along the Pang and the Lambourn. These differences reflect hydrological processes, water flow pathways and water quality input fluxes. The Pang’s pattern of water quality change is more variable than that of the Lambourn. The flow hydrograph also shows both a cyclical and 'uniform pattern' characteristic of aquifer drainage with, superimposed, a series of 'flashier' spiked responses characteristic of karstic systems. The Lambourn, in contrast, shows simpler features without the 'flashier' responses. The results are discussed in relation to the newly developed UK community programme LOCAR dealing with Lowland Catchment Research. A descriptive and box model structure is provided to describe the key features of water quality variations in relation to soil, unsaturated and groundwater flows and storage both away from and close to the river. Keywords: water quality, nitrate, ammonium, phosphorus, pH, alkalinity, nutrients, major elements, trace elements, rainfall, river, Pang, Lambourn, LOCAR

  15. Stochastic water demand modelling for a better understanding of hydraulics in water distribution networks

    NARCIS (Netherlands)

    Blokker, E.J.M.

    2010-01-01

    In the water distribution network water quality process take place influenced by de flow velocity and residence time of the water in the network. In order to understand how the water quality changes in the water distribution network, a good understanding of hydraulics is required. Specifically in

  16. Columbia River water quality monitoring

    International Nuclear Information System (INIS)

    Anon.

    1983-01-01

    Waste water from Hanford activities is discharged at eight points along the Hanford reach of the Columbia River. These discharges consist of backwash water from water intake screens, cooling water, river bank springs, water storage tank overflow, and fish laboratory waste water. Each discharge point is identified in an existing National Pollutant Discharge Elimination System (NPDES) permit issued by the EPA. Effluents from each of these outfalls are routinely monitored and reported by the operating contractors as required by their NPDES permits. Measurements of several Columbia River water quality parameters were conducted routinely during 1982 both upstream and downstream of the Hanford Site to monitor any effects on the river that may be attributable to Hanford discharges and to determine compliance with the Class A designation requirements. The measurements indicated that Hanford operations had a minimal, if any, impact on the quality of the Columbia River water

  17. Developing Personal Network Business Models

    DEFF Research Database (Denmark)

    Saugstrup, Dan; Henten, Anders

    2006-01-01

    The aim of the paper is to examine the issue of business modeling in relation to personal networks, PNs. The paper builds on research performed on business models in the EU 1ST MAGNET1 project (My personal Adaptive Global NET). The paper presents the Personal Network concept and briefly reports...

  18. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

    2013-01-01

    methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more

  19. Complex Networks in Psychological Models

    Science.gov (United States)

    Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

    We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

  20. Water quality control system and water quality control method

    International Nuclear Information System (INIS)

    Itsumi, Sachio; Ichikawa, Nagayoshi; Uruma, Hiroshi; Yamada, Kazuya; Seki, Shuji

    1998-01-01

    In the water quality control system of the present invention, portions in contact with water comprise a metal material having a controlled content of iron or chromium, and the chromium content on the surface is increased than that of mother material in a state where compression stresses remain on the surface by mechanical polishing to form an uniform corrosion resistant coating film. In addition, equipments and/or pipelines to which a material controlling corrosion potential stably is applied on the surface are used. There are disposed a cleaning device made of a material less forming impurities, and detecting intrusion of impurities and removing them selectively depending on chemical species and/or a cleaning device for recovering drain from various kinds of equipment to feedwater, connecting a feedwater pipeline and a condensate pipeline and removing impurities and corrosion products. Then, water can be kept to neutral purified water, and the concentrations of oxygen and hydrogen in water are controlled within an optimum range to suppress occurrence of corrosion products. (N.H.)

  1. 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

  2. Strategies for improving the surveillance of drinking water quality in distribution networks : application of emerging modeling approaches

    OpenAIRE

    Francisque, Alex

    2009-01-01

    Cette thèse est consacrée à l'amélioration de la surveillance de la qualité de l'eau potable en réseau de distribution (RD) et à son. Le principal RD de la ville de Québec (Canada) est étudié. La thèse comporte quatre chapitres. Le premier porte sur la qualité microbiologique de l'eau. Il introduit de nouvelles approches statistiques pour modéliser les comptes de bactéries hétérotrophes anaérobies et aérobies facultatives (BHAA) utilisées comme indicateur de la variabilité de la qualité de l'...

  3. A model of coauthorship networks

    Science.gov (United States)

    Zhou, Guochang; Li, Jianping; Xie, Zonglin

    2017-10-01

    A natural way of representing the coauthorship of authors is to use a generalization of graphs known as hypergraphs. A random geometric hypergraph model is proposed here to model coauthorship networks, which is generated by placing nodes on a region of Euclidean space randomly and uniformly, and connecting some nodes if the nodes satisfy particular geometric conditions. Two kinds of geometric conditions are designed to model the collaboration patterns of academic authorities and basic researches respectively. The conditions give geometric expressions of two causes of coauthorship: the authority and similarity of authors. By simulation and calculus, we show that the forepart of the degree distribution of the network generated by the model is mixture Poissonian, and the tail is power-law, which are similar to these of some coauthorship networks. Further, we show more similarities between the generated network and real coauthorship networks: the distribution of cardinalities of hyperedges, high clustering coefficient, assortativity, and small-world property

  4. Post-fire Water Quality Response and Associated Physical Drivers

    Science.gov (United States)

    Rust, A.; Saxe, S.; Hogue, T. S.; McCray, J. E.; Rhoades, C.

    2017-12-01

    . Ultimately, improved understanding of post-fire response and related drivers will advance potential mitigation and treatment strategies as well as aid in the parametrization of post-fire models of water quality.

  5. Studies of Columbia River water quality

    International Nuclear Information System (INIS)

    Onishi, Y.; Johanson, P.A.; Baca, R.G.; Hilty, E.L.

    1976-01-01

    The program to study the water quality of the Columbia River consists of two separate segments: sediment and radionuclide transport and temperature analysis. Quasi-two dimensional (longitudinal and vertical directions) mathematical simulation models were developed for determining radionuclide inventories, their variations with time, and movements of sediments and individual radionuclides in the freshwater region of the Columbia River below Priest Rapids Dam. These codes are presently being applied to the river reach between Priest Rapids and McNary Dams for the initial sensitivity analysis. In addition, true two-dimensional (longitudinal and lateral directions) models were formulated and are presently being programmed to provide more detailed information on sediment and radionuclide behavior in the river. For the temperature analysis program, river water temperature data supplied by the U. S. Geological Survey for six ERDA-sponsored temperature recording stations have been analyzed and cataloged on storage devices associated with ERDA's CDC 6600 located at Richland, Washington

  6. Telecommunications network modelling, planning and design

    CERN Document Server

    Evans, Sharon

    2003-01-01

    Telecommunication Network Modelling, Planning and Design addresses sophisticated modelling techniques from the perspective of the communications industry and covers some of the major issues facing telecommunications network engineers and managers today. Topics covered include network planning for transmission systems, modelling of SDH transport network structures and telecommunications network design and performance modelling, as well as network costs and ROI modelling and QoS in 3G networks.

  7. Estimating risks for water-quality exceedances of total-copper from highway and urban runoff under predevelopment and current conditions with the Stochastic Empirical Loading and Dilution Model (SELDM)

    Science.gov (United States)

    Granato, Gregory E.; Jones, Susan C.; Dunn, Christopher N.; Van Weele, Brian

    2017-01-01

    The stochastic empirical loading and dilution model (SELDM) was used to demonstrate methods for estimating risks for water-quality exceedances of event-mean concentrations (EMCs) of total-copper. Monte Carlo methods were used to simulate stormflow, total-hardness, suspended-sediment, and total-copper EMCs as stochastic variables. These simulations were done for the Charles River Basin upstream of Interstate 495 in Bellingham, Massachusetts. The hydrology and water quality of this site were simulated with SELDM by using data from nearby, hydrologically similar sites. Three simulations were done to assess the potential effects of the highway on receiving-water quality with and without highway-runoff treatment by a structural best-management practice (BMP). In the low-development scenario, total copper in the receiving stream was simulated by using a sediment transport curve, sediment chemistry, and sediment-water partition coefficients. In this scenario, neither the highway runoff nor the BMP effluent caused concentration exceedances in the receiving stream that exceed the once in three-year threshold (about 0.54 percent). In the second scenario, without the highway, runoff from the large urban areas in the basin caused exceedances in the receiving stream in 2.24 percent of runoff events. In the third scenario, which included the effects of the urban runoff, neither the highway runoff nor the BMP effluent increased the percentage of exceedances in the receiving stream. Comparison of the simulated geometric mean EMCs with data collected at a downstream monitoring site indicates that these simulated values are within the 95-percent confidence interval of the geometric mean of the measured EMCs.

  8. Campus network security model study

    Science.gov (United States)

    Zhang, Yong-ku; Song, Li-ren

    2011-12-01

    Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.

  9. Oxycline formation induced by Fe(II) oxidation in a water reservoir affected by acid mine drainage modeled using a 2D hydrodynamic and water quality model - CE-QUAL-W2.

    Science.gov (United States)

    Torres, Ester; Galván, Laura; Cánovas, Carlos Ruiz; Soria-Píriz, Sara; Arbat-Bofill, Marina; Nardi, Albert; Papaspyrou, Sokratis; Ayora, Carlos

    2016-08-15

    The Sancho reservoir is an acid mine drainage (AMD)-contaminated reservoir located in the Huelva province (SW Spain) with a pH close to 3.5. The water is only used for a refrigeration system of a paper mill. The Sancho reservoir is holomictic with one mixing period per year in the winter. During this mixing period, oxygenated water reaches the sediment, while under stratified conditions (the rest of the year) hypoxic conditions develop at the hypolimnion. A CE-QUAL-W2 model was calibrated for the Sancho Reservoir to predict the thermocline and oxycline formation, as well as the salinity, ammonium, nitrate, phosphorous, algal, chlorophyll-a, and iron concentrations. The version 3.7 of the model does not allow simulating the oxidation of Fe(II) in the water column, which limits the oxygen consumption of the organic matter oxidation. However, to evaluate the impact of Fe(II) oxidation on the oxycline formation, Fe(II) has been introduced into the model based on its relationship with labile dissolved organic matter (LDOM). The results show that Fe oxidation is the main factor responsible for the oxygen depletion in the hypolimnion of the Sancho Reservoir. The limiting factors for green algal growth have also been studied. The model predicted that ammonium, nitrate, and phosphate were not limiting factors for green algal growth. Light appeared to be one of the limiting factors for algal growth, while chlorophyll-a and dissolved oxygen concentrations could not be fully described. We hypothesize that dissolved CO2 is one of the limiting nutrients due to losses by the high acidity of the water column. The sensitivity tests carried out support this hypothesis. Two different remediation scenarios have been tested with the calibrated model: 1) an AMD passive treatment plant installed at the river, which removes completely Fe, and 2) different depth water extractions. If no Fe was introduced into the reservoir, water quality would significantly improve in only two years

  10. Generalized Network Psychometrics : Combining Network and Latent Variable Models

    NARCIS (Netherlands)

    Epskamp, S.; Rhemtulla, M.; Borsboom, D.

    2017-01-01

    We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

  11. Principles and Practices of Water Quality Monitoring

    Science.gov (United States)

    J.L. Michael

    2001-01-01

    There are many activities in forest management that may affect water quality, i.e., timber harvestine, road building,mechanical and chemical site preparation, release operations, fuel reduction,wildlife opening maintenance, etc. How severely they affect water quality depends on how well the person in charge of the operation understands the activity itself, the...

  12. 40 CFR 240.204 - Water quality.

    Science.gov (United States)

    2010-07-01

    ... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Water quality. 240.204 Section 240.204 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES GUIDELINES FOR THE THERMAL PROCESSING OF SOLID WASTES Requirements and Recommended Procedures § 240.204 Water quality. ...

  13. Water quality assessment of bioenergy production

    Science.gov (United States)

    Rocio Diaz-Chavez; Goran Berndes; Dan Neary; Andre Elia Neto; Mamadou Fall

    2011-01-01

    Water quality is a measurement of the biological, chemical, and physical characteristics of water against certain standards set to ensure ecological and/or human health. Biomass production and conversion to fuels and electricity can impact water quality in lakes, rivers, and aquifers with consequences for aquatic ecosystem health and also human water uses. Depending on...

  14. Neural network modeling of emotion

    Science.gov (United States)

    Levine, Daniel S.

    2007-03-01

    This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.

  15. Modeling of fluctuating reaction networks

    International Nuclear Information System (INIS)

    Lipshtat, A.; Biham, O.

    2004-01-01

    Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press

  16. U.S. Midwestern Residents Perceptions of Water Quality

    Directory of Open Access Journals (Sweden)

    Lois Wright Morton

    2011-02-01

    Full Text Available The plurality of conservation and environmental viewpoints often challenge community leaders and government agency staff as they seek to engage citizens and build partnerships around watershed planning and management to solve complex water quality issues. The U.S. Midwest Heartland region (covering the states of Missouri, Kansa, Iowa, and Nebraska is dominated by row crop production and animal agriculture, where an understanding of perceptions held by residents of different locations (urban, rural non-farm, and rural farm towards water quality and the environment can provide a foundation for public deliberation and decision making. A stratified random sample mail survey of 1,042 Iowa, Kansas, Missouri, and Nebraska residents (54% response rate reveals many areas of agreement among farm, rural non-farm, and those who live in towns on the importance of water issues including the importance and use of water resources; beliefs about water quality and perceptions of impaired water quality causality; beliefs about protecting local waters; and environmental attitudes. With two ordinal logistic models, we also found that respondents with strong environmental attitudes have the least confidence in ground and surface water quality. The findings about differences and areas of agreement among the residents of different sectors can provide a communication bridge among divergent viewpoints and assist local leaders and agency staff as they seek to engage the public in discussions which lead to negotiating solutions to difficult water issues.

  17. Spectral Band Characterization for Hyperspectral Monitoring of Water Quality

    Science.gov (United States)

    Vermillion, Stephanie C.; Raqueno, Rolando; Simmons, Rulon

    2001-01-01

    A method for selecting the set of spectral characteristics that provides the smallest increase in prediction error is of interest to those using hyperspectral imaging (HSI) to monitor water quality. The spectral characteristics of interest to these applications are spectral bandwidth and location. Three water quality constituents of interest that are detectable via remote sensing are chlorophyll (CHL), total suspended solids (TSS), and colored dissolved organic matter (CDOM). Hyperspectral data provides a rich source of information regarding the content and composition of these materials, but often provides more data than an analyst can manage. This study addresses the spectral characteristics need for water quality monitoring for two reasons. First, determination of the greatest contribution of these spectral characteristics would greatly improve computational ease and efficiency. Second, understanding the spectral capabilities of different spectral resolutions and specific regions is an essential part of future system development and characterization. As new systems are developed and tested, water quality managers will be asked to determine sensor specifications that provide the most accurate and efficient water quality measurements. We address these issues using data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and a set of models to predict constituent concentrations.

  18. Heavy Water Quality Management in HANARO

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Ho Chul; Lee, Mun; Kim, Hi Gon; Park, Chan Young; Choi, Ho Young; Hur, Soon Ock; Ahn, Guk Hoon

    2008-12-15

    Heavy water quality management in the reflector tank is a very important element to maintain the good thermal neutron flux and to ensure the performance of reflector cooling system. This report is written to provide a guidance for the future by describing the history of the heavy water quality management during HANARO operation. The heavy water quality in the reflector tank has been managed by measuring the electrical conductivity at the inlet and outlet of the ion exchanger and by measuring pH of the heavy water. In this report, the heavy water quality management activities performed in HANARO from 1996 to 2007 ere described including a basic theory of the heavy water quality management, exchanging history of used resin in the reflector cooling system, measurement data of the pH and the electrical conductivity, and operation history of the reflector cooling system.

  19. Coral skeletal geochemistry as a monitor of inshore water quality

    International Nuclear Information System (INIS)

    Saha, Narottam; Webb, Gregory E.; Zhao, Jian-Xin

    2016-01-01

    Coral reefs maintain extraordinary biodiversity and provide protection from tsunamis and storm surge, but inshore coral reef health is degrading in many regions due to deteriorating water quality. Deconvolving natural and anthropogenic changes to water quality is hampered by the lack of long term, dated water quality data but such records are required for forward modelling of reef health to aid their management. Reef corals provide an excellent archive of high resolution geochemical (trace element) proxies that can span hundreds of years and potentially provide records used through the Holocene. Hence, geochemical proxies in corals hold great promise for understanding changes in ancient water quality that can inform broader oceanographic and climatic changes in a given region. This article reviews and highlights the use of coral-based trace metal archives, including metal transported from rivers to the ocean, incorporation of trace metals into coral skeletons and the current ‘state of the art’ in utilizing coral trace metal proxies as tools for monitoring various types of local and regional source-specific pollution (river discharge, land use changes, dredging and dumping, mining, oil spills, antifouling paints, atmospheric sources, sewage). The three most commonly used coral trace element proxies (i.e., Ba/Ca, Mn/Ca, and Y/Ca) are closely associated with river runoff in the Great Barrier Reef, but considerable uncertainty remains regarding their complex biogeochemical cycling and controlling mechanisms. However, coral-based water quality reconstructions have suffered from a lack of understanding of so-called vital effects and early marine diagenesis. The main challenge is to identify and eliminate the influence of extraneous local factors in order to allow accurate water quality reconstructions and to develop alternate proxies to monitor water pollution. Rare earth elements have great potential as they are self-referencing and reflect basic terrestrial input

  20. Coral skeletal geochemistry as a monitor of inshore water quality

    Energy Technology Data Exchange (ETDEWEB)

    Saha, Narottam, E-mail: n.saha@uq.edu.au; Webb, Gregory E.; Zhao, Jian-Xin

    2016-10-01

    Coral reefs maintain extraordinary biodiversity and provide protection from tsunamis and storm surge, but inshore coral reef health is degrading in many regions due to deteriorating water quality. Deconvolving natural and anthropogenic changes to water quality is hampered by the lack of long term, dated water quality data but such records are required for forward modelling of reef health to aid their management. Reef corals provide an excellent archive of high resolution geochemical (trace element) proxies that can span hundreds of years and potentially provide records used through the Holocene. Hence, geochemical proxies in corals hold great promise for understanding changes in ancient water quality that can inform broader oceanographic and climatic changes in a given region. This article reviews and highlights the use of coral-based trace metal archives, including metal transported from rivers to the ocean, incorporation of trace metals into coral skeletons and the current ‘state of the art’ in utilizing coral trace metal proxies as tools for monitoring various types of local and regional source-specific pollution (river discharge, land use changes, dredging and dumping, mining, oil spills, antifouling paints, atmospheric sources, sewage). The three most commonly used coral trace element proxies (i.e., Ba/Ca, Mn/Ca, and Y/Ca) are closely associated with river runoff in the Great Barrier Reef, but considerable uncertainty remains regarding their complex biogeochemical cycling and controlling mechanisms. However, coral-based water quality reconstructions have suffered from a lack of understanding of so-called vital effects and early marine diagenesis. The main challenge is to identify and eliminate the influence of extraneous local factors in order to allow accurate water quality reconstructions and to develop alternate proxies to monitor water pollution. Rare earth elements have great potential as they are self-referencing and reflect basic terrestrial input

  1. Socioeconomic dynamics of water quality in the Egyptian Nile

    Science.gov (United States)

    Malik, Maheen; Nisar, Zainab; Karakatsanis, Georgios

    2016-04-01

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