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Sample records for network water-quality models

  1. DISCRETE VOLUME-ELEMENT METHOD FOR NETWORK WATER- QUALITY MODELS

    Science.gov (United States)

    An explicit dynamic water-quality modeling algorithm is developed for tracking dissolved substances in water-distribution networks. The algorithm is based on a mass-balance relation within pipes that considers both advective transport and reaction kinetics. Complete mixing of m...

  2. Importance of demand modelling in network water quality models : A review

    NARCIS (Netherlands)

    Blokker, E.J.M.; Vreeburg, J.H.G.; Buchberger, S.G.; Van Dijk, J.C.

    2008-01-01

    Today, there is a growing interest in network water quality modelling. The water quality issues of interest relate to both dissolved and particulate substances. For dissolved substances the main interest is in residual chlorine and (microbiological) contaminant propagation; for particulate

  3. Importance of demand modelling in network water quality models: a review

    Directory of Open Access Journals (Sweden)

    J. C. van Dijk

    2008-09-01

    Full Text Available Today, there is a growing interest in network water quality modelling. The water quality issues of interest relate to both dissolved and particulate substances. For dissolved substances the main interest is in residual chlorine and (microbiological contaminant propagation; for particulate substances it is in sediment leading to discolouration. There is a strong influence of flows and velocities on transport, mixing, production and decay of these substances in the network. This imposes a different approach to demand modelling which is reviewed in this article.

    For the large diameter lines that comprise the transport portion of a typical municipal pipe system, a skeletonised network model with a top-down approach of demand pattern allocation, a hydraulic time step of 1 h, and a pure advection-reaction water quality model will usually suffice. For the smaller diameter lines that comprise the distribution portion of a municipal pipe system, an all-pipes network model with a bottom-up approach of demand pattern allocation, a hydraulic time step of 1 min or less, and a water quality model that considers dispersion and transients may be needed.

    Demand models that provide stochastic residential demands per individual home and on a one-second time scale are available. A stochastic demands based network water quality model needs to be developed and validated with field measurements. Such a model will be probabilistic in nature and will offer a new perspective for assessing water quality in the drinking water distribution system.

  4. Applications of artificial neural networks for microbial water quality modeling

    Energy Technology Data Exchange (ETDEWEB)

    Brion, G.M.; Lingireddy, S. [Univ. of Kentucky, Dept. of Civil Engineering, Lexington, Kentucky (United States)]. E-mail: gbrion@engr.uky.edu

    2002-06-15

    There has been a significant shift in the recent past towards protecting chemical and microbial quality of source waters rather than developing advanced methods to treat heavily polluted water. The key to successful best management practices in protecting the source waters is to identify sources of non-point pollution and their collective impact on the quality of water at the intake. This article presents a few successful applications where artificial neural networks (ANN) have proven to be the useful mathematical tools in correlating the nonlinear relationships between routinely measured parameters (such as rainfall, turbidity, fecal coliforms etc.) and quality of source waters and/or nature of fecal sources. These applications include, prediction of peak concentrations of Giardia and Cryptosporidium, sorting of fecal sources (e.g. agricultural animals vs. urban animals), predicting relative ages of the runoff sources, identifying the potential for sewage contamination. The ability of ANNs to work with complex, inter-related multiparameter databases, and provide superior predictive power in non-linear relationships has been the key for their successful application to microbial water quality studies. (author)

  5. 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...

  6. Water Quality Modeling in Reservoirs Using Multivariate Linear Regression and Two Neural Network Models

    Directory of Open Access Journals (Sweden)

    Wei-Bo Chen

    2015-01-01

    Full Text Available In this study, two artificial neural network models (i.e., a radial basis function neural network, RBFN, and an adaptive neurofuzzy inference system approach, ANFIS and a multilinear regression (MLR model were developed to simulate the DO, TP, Chl a, and SD in the Mingder Reservoir of central Taiwan. The input variables of the neural network and the MLR models were determined using linear regression. The performances were evaluated using the RBFN, ANFIS, and MLR models based on statistical errors, including the mean absolute error, the root mean square error, and the correlation coefficient, computed from the measured and the model-simulated DO, TP, Chl a, and SD values. The results indicate that the performance of the ANFIS model is superior to those of the MLR and RBFN models. The study results show that the neural network using the ANFIS model is suitable for simulating the water quality variables with reasonable accuracy, suggesting that the ANFIS model can be used as a valuable tool for reservoir management in Taiwan.

  7. A Reaction-Based River/Stream Water Quality Model: Reaction Network Decomposition and Model Application

    Directory of Open Access Journals (Sweden)

    Fan Zhang

    2012-01-01

    Full Text Available This paper describes details of an automatic matrix decomposition approach for a reaction-based stream water quality model. The method yields a set of equilibrium equations, a set of kinetic-variable transport equations involving kinetic reactions only, and a set of component transport equations involving no reactions. Partial decomposition of the system of water quality constituent transport equations is performed via Gauss-Jordan column reduction of the reaction network by pivoting on equilibrium reactions to decouple equilibrium and kinetic reactions. This approach minimizes the number of partial differential advective-dispersive transport equations and enables robust numerical integration. Complete matrix decomposition by further pivoting on linearly independent kinetic reactions allows some rate equations to be formulated individually and explicitly enforces conservation of component species when component transport equations are solved. The methodology is demonstrated for a case study involving eutrophication reactions in the Des Moines River in Iowa, USA and for two hypothetical examples to illustrate the ability of the model to simulate sediment and chemical transport with both mobile and immobile water phases and with complex reaction networks involving both kinetic and equilibrium reactions.

  8. Stream Water Quality Model

    Data.gov (United States)

    U.S. Environmental Protection Agency — QUAL2K (or Q2K) is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E (or Q2E) model (Brown and Barnwell 1987).

  9. 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

  10. An integrated model for simulating and diagnosing the water quality based on the system dynamics and Bayesian network.

    Science.gov (United States)

    Wang, Gengzhe; Wang, Shuo; Kang, Qiao; Duan, Haiyan; Wang, Xian'En

    2016-12-01

    An integrated model for simulating and diagnosing water quality based on the system dynamics and Bayesian network (BN) is presented in the paper. The research aims to connect water monitoring downstream with outlet management upstream in order to present an efficiency outlet management strategy. The integrated model was built from two components: the system dynamics were used to simulate the water quality and the BN was applied to diagnose the reason for water quality deterioration according to the water quality simulation. The integrated model was applied in a case study of the Songhua River from the Baiqi section to the Songlin section to prove its reasonability and accuracy. The results showed that the simulation fit to the variation trend of monitoring data, and the average relative error was less than 10%. The water quality deterioration in the Songlin section was mainly found to be caused by the water quality in the upper reach and Hadashan Reservoir drain by using the diagnosis function of the integrated model based on BN. The relevant result revealed that the integrated model could provide reasonable and quantitative support for the basin manager to make a reasonable outlet control strategy to avoid more serious water quality deterioration.

  11. Water Quality Modeling in the Dead End Sections of Drinking Water Distribution Networks

    Science.gov (United States)

    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. Wate...

  12. Water Quality Modeling in the Dead End Sections of Drinking Water Distribution Networks -journal article

    Science.gov (United States)

    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. Wate...

  13. Hydropower Optimization Using Artificial Neural Network Surrogate Models of a High-Fidelity Hydrodynamics and Water Quality Model

    Science.gov (United States)

    Shaw, Amelia R.; Smith Sawyer, Heather; LeBoeuf, Eugene J.; McDonald, Mark P.; Hadjerioua, Boualem

    2017-11-01

    Hydropower operations optimization subject to environmental constraints is limited by challenges associated with dimensionality and spatial and temporal resolution. The need for high-fidelity hydrodynamic and water quality models within optimization schemes is driven by improved computational capabilities, increased requirements to meet specific points of compliance with greater resolution, and the need to optimize operations of not just single reservoirs but systems of reservoirs. This study describes an important advancement for computing hourly power generation schemes for a hydropower reservoir using high-fidelity models, surrogate modeling techniques, and optimization methods. The predictive power of the high-fidelity hydrodynamic and water quality model CE-QUAL-W2 is successfully emulated by an artificial neural network, then integrated into a genetic algorithm optimization approach to maximize hydropower generation subject to constraints on dam operations and water quality. This methodology is applied to a multipurpose reservoir near Nashville, Tennessee, USA. The model successfully reproduced high-fidelity reservoir information while enabling 6.8% and 6.6% increases in hydropower production value relative to actual operations for dissolved oxygen (DO) limits of 5 and 6 mg/L, respectively, while witnessing an expected decrease in power generation at more restrictive DO constraints. Exploration of simultaneous temperature and DO constraints revealed capability to address multiple water quality constraints at specified locations. The reduced computational requirements of the new modeling approach demonstrated an ability to provide decision support for reservoir operations scheduling while maintaining high-fidelity hydrodynamic and water quality information as part of the optimization decision support routines.

  14. Water Quality Modeling in Reservoirs Using Multivariate Linear Regression and Two Neural Network Models

    OpenAIRE

    Wei-Bo Chen; Wen-Cheng Liu

    2015-01-01

    In this study, two artificial neural network models (i.e., a radial basis function neural network, RBFN, and an adaptive neurofuzzy inference system approach, ANFIS) and a multilinear regression (MLR) model were developed to simulate the DO, TP, Chl a, and SD in the Mingder Reservoir of central Taiwan. The input variables of the neural network and the MLR models were determined using linear regression. The performances were evaluated using the RBFN, ANFIS, and MLR models based on statistical ...

  15. Modelling water quality in drinking water distribution networks from real-time direction data

    OpenAIRE

    Nazarovs, S.; Dejus, S.; Juhna, T.

    2012-01-01

    Modelling of contamination spread and location of a contamination source in a water distribution network is an important task. There are several simulation tools developed, however the significant part of them is based on hydraulic models that need node demands as input data that sometimes may result in false negative results and put users at risk. The paper considers applicability of a real-time flow direction data based model for contaminant transport in a distribution network of a city and...

  16. 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.

  17. 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......, 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....

  18. Sensor & Model Enabled Water Quality & Security Assessment System for Situational Awareness of Water Distribution Networks

    Science.gov (United States)

    2010-06-01

    Distribution Networks NDIA Environment , Energy Security & Sustainability Symposium & Exhibition June 14-17,2010 Denver, Colorado Mark Ginsberg...for public release; distribution unlimited 13. SUPPLEMENTARY NOTES Presented at the NDIA Environment , Energy Security & Sustainability (E2S2...Chlorfenvinphos, Formetanate Hydrochloride, Acrolein, Chloropicrin, Sodium chloroacetate, Thyoglycolate medium, Crotoxyphos, Glyphosate , Jimsonweed, Methanol

  19. Energy Efficient Networks for Monitoring Water Quality in Subterranean Rivers

    Directory of Open Access Journals (Sweden)

    Fei Ge

    2016-05-01

    Full Text Available The fresh water in rivers beneath the Earth’s surface is as significant to humans as that on the surface. However, the water quality is difficult to monitor due to its unapproachable nature. In this work, we consider building networks to monitor water quality in subterranean rivers. The network node is designed to have limited functions of floating and staying in these rivers when necessary. We provide the necessary conditions to set up such networks and a topology building method, as well as the communication process between nodes. Furthermore, we provide every an node’s energy consumption model in the network building stage, the data acquiring and transmission stage. The numerical results show that the energy consumption in every node is different, and the node number should be moderate to ensure energy efficiency.

  20. STREAMFLOW AND WATER QUALITY REGRESSION MODELING ...

    African Journals Online (AJOL)

    STREAMFLOW AND WATER QUALITY REGRESSION MODELING OF IMO RIVER SYSTEM: A CASE STUDY. ... Journal of Modeling, Design and Management of Engineering Systems ... Possible sources of contamination of Imo-river system within Nekede and Obigbo hydrological stations watershed were traced.

  1. Water quality modelling of Jadro spring.

    Science.gov (United States)

    Margeta, J; Fistanic, I

    2004-01-01

    Management of water quality in karst is a specific problem. Water generally moves very fast by infiltration processes but far more by concentrated flows through fissures and openings in karst. This enables the entire surface pollution to be transferred fast and without filtration into groundwater springs. A typical example is the Jadro spring. Changes in water quality at the spring are sudden, but short. Turbidity as a major water quality problem for the karst springs regularly exceeds allowable standards. Former practice in problem solving has been reduced to intensive water disinfection in periods of great turbidity without analyses of disinfection by-products risks for water users. The main prerequisite for water quality control and an optimization of water disinfection is the knowledge of raw water quality and nature of occurrence. The analysis of monitoring data and their functional relationship with hydrological parameters enables establishment of a stochastic model that will help obtain better information on turbidity in different periods of the year. Using the model a great number of average monthly and extreme daily values are generated. By statistical analyses of these data possibility of occurrence of high turbidity in certain months is obtained. This information can be used for designing expert system for water quality management of karst springs. Thus, the time series model becomes a valuable tool in management of drinking water quality of the Jadro spring.

  2. 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.

  3. STREAMFLOW AND WATER QUALITY REGRESSION MODELING ...

    African Journals Online (AJOL)

    The upper reaches of Imo-river system between Nekede and Obigbo hydrological stations (a stretch of 24km) have been studied for the purpose of water quality and streamflow modeling. Model's applications on water supply to Nekede and Obigbo communities were equally explored with the development of mass curves.

  4. Robustness of river basin water quality models

    NARCIS (Netherlands)

    de Blois, Chris; Wind, H.G.; de Kok, Jean-Luc; Koppeschaar, K.

    2003-01-01

    In this paper the concept of robustness is introduced and applied to a model for the analysis of the impacts of spatially distributed policy measures on the surface water quality on a river basin scale. In this model the influence of precipitation on emissions and resuspension of pollutants in the

  5. New challenges in integrated water quality modelling

    NARCIS (Netherlands)

    Rode, M.; Arhonditsis, G.; Balin, D.; Kebede, T.; Krysanova, V.; Griensven, A.; Zee, van der S.E.A.T.M.

    2010-01-01

    There is an increasing pressure for development of integrated water quality models that effectively couple catchment and in-stream biogeochemical processes. This need stems from increasing legislative requirements and emerging demands related to contemporary climate and land use changes. Modelling

  6. 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...

  7. Optimum Water Quality Monitoring Network Design for Bidirectional River Systems.

    Science.gov (United States)

    Zhu, Xiaohui; Yue, Yong; Wong, Prudence W H; Zhang, Yixin; Tan, Jianhong

    2018-01-24

    Affected by regular tides, bidirectional water flows play a crucial role in surface river systems. Using optimization theory to design a water quality monitoring network can reduce the redundant monitoring nodes as well as save the costs for building and running a monitoring network. A novel algorithm is proposed to design an optimum water quality monitoring network for tidal rivers with bidirectional water flows. Two optimization objectives of minimum pollution detection time and maximum pollution detection probability are used in our optimization algorithm. We modify the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm and develop new fitness functions to calculate pollution detection time and pollution detection probability in a discrete manner. In addition, the Storm Water Management Model (SWMM) is used to simulate hydraulic characteristics and pollution events based on a hypothetical river system studied in the literature. Experimental results show that our algorithm can obtain a better Pareto frontier. The influence of bidirectional water flows to the network design is also identified, which has not been studied in the literature. Besides that, we also find that the probability of bidirectional water flows has no effect on the optimum monitoring network design but slightly changes the mean pollution detection time.

  8. Optimum Water Quality Monitoring Network Design for Bidirectional River Systems

    Directory of Open Access Journals (Sweden)

    Xiaohui Zhu

    2018-01-01

    Full Text Available Affected by regular tides, bidirectional water flows play a crucial role in surface river systems. Using optimization theory to design a water quality monitoring network can reduce the redundant monitoring nodes as well as save the costs for building and running a monitoring network. A novel algorithm is proposed to design an optimum water quality monitoring network for tidal rivers with bidirectional water flows. Two optimization objectives of minimum pollution detection time and maximum pollution detection probability are used in our optimization algorithm. We modify the Multi-Objective Particle Swarm Optimization (MOPSO algorithm and develop new fitness functions to calculate pollution detection time and pollution detection probability in a discrete manner. In addition, the Storm Water Management Model (SWMM is used to simulate hydraulic characteristics and pollution events based on a hypothetical river system studied in the literature. Experimental results show that our algorithm can obtain a better Pareto frontier. The influence of bidirectional water flows to the network design is also identified, which has not been studied in the literature. Besides that, we also find that the probability of bidirectional water flows has no effect on the optimum monitoring network design but slightly changes the mean pollution detection time.

  9. 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.

  10. Urban Runoff and Water Quality Models

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jong Tae [Kyonggi University, Suwon (Korea)

    1998-12-31

    The characteristics of storm and water quality are investigated based on the measuring data of the test river, the Hongje. The water quality of the test river is generally good comparing to other urban rivers in Seoul, because of the interception of sewer flow. But this system makes the river dry up for 3-4 months in winter. On the other hand, in rainy period the storm from the combined sewer system causes rapid increasing pollutants loads. In order to simulate the urban storm and water quality of the test basin, the models such as SWMM, ILLUDAS, STORM, HEC-1 were applied and the results are compared in its applicability and accuracy aspects. All models discussed here have shown good results and it seems that SWMM is the most effective model in simulating both quantity and quality. Also, regression relations between the water quantity and quality were derived and their applicabilities were discussed. This regression model is a simple effective tool for estimating the pollutant loads in the rainy period, but if the amount of discharge is bigger than measuring range of raw data, the accuracy becomes poor. This model could be supplemented by expanding the range of collecting data and introducing the river characteristics. The HEC-1 would be another effective model to simulate storm runoff of a river basin including urban area. (author). 15 refs., 13 tabs., 13 figs.

  11. 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.

  12. Water Quality Modeling System for Coastal Archipelagos

    Science.gov (United States)

    Tuomi, L.; Miettunen, E.; Lukkari, K.; Puttonen, I.; Ropponen, J.; Tikka, K.; Piiparinen, J.; Lignell, R.

    2016-02-01

    Coastal seas are encountering pressures from eutrophication, fishing, ship emissions and coastal construction. Sustainable development and use of these areas require science-based guidance with high quality data and efficient tools. Our study area, the Archipelago Sea, is located in the northern part of the semi-enclosed and brackish water Baltic Sea. It is a shallow, topographically heterogeneous and eutrophic sub-basin, covered with thousands of small islands and islets. The catchment area is 8950 km2and has ca. 500 000 inhabitants. We are developing a modeling system that can be used by local authorities and in ministry level decision making to evaluate the environmental impacts that may result from decisions and changes made both in the watershed and in the coastal areas. The modeling system consists of 3D hydrodynamic model COHERENS and water quality model FICOS, both applied to the area with high spatial resolution. Models use river discharge and nutrient loading data supplied by watershed model VEMALA and include loading from multiple point sources located in the Archipelago Sea. An easy-to-use interface made specifically to answer the end-user needs, includes possibility to modify the nutrient loadings and perform model simulations to selected areas and time periods. To ensure the quality and performance of the modeling system, comprehensive measurement dataset including hydrographic, nutrient, chlorophyll-a and bottom sediment data, was gathered based on monitoring and research campaigns previously carried out in the Archipelago Sea. Verification showed that hydrodynamic model was able to simulate surface temperature and salinity fields and their seasonal variation with good accuracy in this complex area. However, the dynamics of the deeper layers need to be improved, especially in areas that have sharp bathymetric gradients. The preliminary analysis of the water quality model results showed that the model was able to reproduce the basic characteristics of

  13. 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.

  14. Wireless sensor networks: A survey on monitoring water quality

    Directory of Open Access Journals (Sweden)

    Mompoloki Pule

    2017-12-01

    Full Text Available Diseases related to poor water and sanitation conditions have over 200 million cases reported annually, causing 5–10 million deaths world-wide. Water quality monitoring has thus become essential to the supply of clean and safe water. Conventional monitoring processes involve manual collection of samples from various points in the distribution network, followed by laboratory testing and analysis. This process has proved to be ineffective since it is laborious, time consuming and lacks real-time results to promote proactive response to water contamination. Wireless sensor networks (WSN have since been considered a promising alternative to complement conventional monitoring processes. These networks are relatively affordable and allow measurements to be taken remotely, in real-time and with minimal human intervention. This work surveys the application of WSN in environmental monitoring, with particular emphasis on water quality. Various WSN based water quality monitoring methods suggested by other authors are studied and analyzed, taking into account their coverage, energy and security concerns. The work also compares and evaluates sensor node architectures proposed the various authors in terms of monitored parameters, microcontroller/microprocessor units (MCU and wireless communication standards adopted, localization, data security implementation, power supply architectures, autonomy and potential application scenarios.

  15. 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

  16. Water Quality Modeling in the Dead End Sections of Drinking ...

    Science.gov (United States)

    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 a 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

  17. A Structural Equation Modeling approach to water quality perceptions.

    Science.gov (United States)

    Levêque, Jonas G; Burns, Robert C

    2017-07-15

    Researches on water quality perceptions have used various techniques and models to explain relationships between specific variables. Surprisingly, Structural Equation Modeling (SEM) has received little attention in water quality perceptions studies, and reporting has been inconsistent among existing studies. One objective of this article is to provide readers with a methodological example for conducting and reporting SEM. Another objective is to build a model that explains the different relationships among the diverse factors highlighted by previous studies on water quality perceptions. Our study focuses on the factors influencing people's perceptions of water quality in the Appalachian region. As such, researchers have conducted a survey in a mid-sized city in northcentral West Virginia to assess residents' perceptions of water quality for drinking and recreational purposes. Specifically, we aimed to understand the relationships between perceived water quality, health risk perceptions, organoleptic perceptions, environmental concern, area satisfaction and perceptions of surface water quality. Our model provided a good fit that explained about 50% of the variance in health risk perceptions and 43% of the variance in organoleptic perceptions. Environmental concern, area satisfaction and perceived surface water quality are important factors in explaining these variances. Perceived water quality was dismissed in our analysis due to multicollinearity. Our study demonstrates that risk communication needs to be better addressed by local decision-makers and water managers. Copyright © 2017 Elsevier Ltd. All rights reserved.

  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. Water Quality Models with Different Functions of Exotech Radiometer Bands

    OpenAIRE

    Rao, K. R.; Krishnan, R.; Chakraborty, A. K.; Deekshatulu, B. L.

    1981-01-01

    Surveillance of water quality by remote sensing technique can be pursued with advantage. An attempt has been made in this paper to obtain regional models of water quality of inland tanks and lakes. Stepwise multiple linear regression analysis between water quality parameters and several functions of Exotech radiometer band reflectance values, namely, bands alone, bands and their ratios, and, bands and their products are evaluated with respect to performance of the regression parameters. It is...

  20. Water quality modelling and optimisation of wastewater treatment ...

    African Journals Online (AJOL)

    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, wastewater treatment plays a crucial role. In this work, a ...

  1. Water quality modelling and optimisation of wastewater treatment ...

    African Journals Online (AJOL)

    2016-10-04

    Oct 4, 2016 ... Using this model, it was demonstrated that water quality standards can be met at all monitoring points at a minimum cost by simultaneously optimising treatment levels at each treatment plant. Keywords: instream water quality, mixed integer optimisation, wastewater treatment levels, Streeter-Phelps.

  2. 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.

  3. FIRESTORM: Modelling the water quality risk of wildfire.

    Science.gov (United States)

    Mason, C. I.; Sheridan, G. J.; Smith, H. G.; Jones, O.; Chong, D.; Tolhurst, K.

    2012-04-01

    ,000 pre-processed spatially distributed fire intensity and flame height maps, generated by a fire behaviour simulator. This part of the model predicts the annual risk of the water supply catchment burning and the spatial extent and severity of the burn. These spatial fire severity maps may be combined with vegetation maps and information on soils to determine initial conditions for modelling of sediment and associated contaminant loads delivered to reservoirs. Erosion and water quality models that form part of the overall model framework include a catchment-scale constituent load model to represent widespread rainfall events and a semi-distributed runoff and erosion connectivity model applied at the small catchment scale for convective storm events. Recent work has shown that localised, intense convective storms may also generate debris flows after fire in south-eastern Australia. Therefore, for the application of the model framework to reservoirs supplying Melbourne, an empirical debris flow erosion model is included. For the localised event models, sediment is routed from sub-catchments through the main channel network to the reservoir boundary. These erosion models are modular so that FIRESTORM may be adapted for use in a region of the world that experiences different dominant erosion processes. FIRESTORM will enable water supply managers to estimate the current water quality risk of wildfire and allow scenario testing to explore the effect of mitigation strategies (e.g. planned burning, post-fire erosion control measures) designed to reduce fire impacts and the magnitude of loads entering reservoirs. This model will be a valuable new tool for better decision making to protect future water supplies.

  4. Development of a decision-making methodology to design a water quality monitoring network.

    Science.gov (United States)

    Keum, Jongho; Kaluarachchi, Jagath J

    2015-07-01

    The number of water quality monitoring stations in the USA has decreased over the past few decades. Scarcity of observations can easily produce prediction uncertainty due to unreliable model calibration. An effective water quality monitoring network is important not only for model calibration and water quality prediction but also for resources management. Redundant or improperly located monitoring stations may cause increased monitoring costs without improvement to the understanding of water quality in watersheds. In this work, a decision-making methodology is proposed to design a water quality monitoring network by providing an adequate number of monitoring stations and their approximate locations at the eight-digit hydrologic unit codes (HUC8) scale. The proposed methodology is demonstrated for an example at the Upper Colorado River Basin (UCRB), where salinity is a serious concern. The level of monitoring redundancy or scarcity is defined by an index, station ratio (SR), which represents a monitoring density based on water quality load originated within a subbasin. By comparing the number of stations from a selected target SR with the available number of stations including the actual and the potential stations, the suggested number of stations in each subbasin was decided. If monitoring stations are primarily located in the low salinity loading subbasins, the average actual SR tends to increase, and vice versa. Results indicate that the spatial distribution of monitoring locations in 2011 is concentrated on low salinity loading subbasins, and therefore, additional monitoring is required for the high salinity loading subbasins. The proposed methodology shows that the SR is a simple and a practical indicator for monitoring density.

  5. 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.

  6. Artificial neural networks for defining the water quality determinants of groundwater abstraction in coastal aquifer

    Science.gov (United States)

    Lallahem, S.; Hani, A.

    2017-02-01

    Water sustainability in the lower Seybouse River basin, eastern Algeria, must take into account the importance of water quantity and quality integration. So, there is a need for a better knowledge and understanding of the water quality determinants of groundwater abstraction to meet the municipal and agricultural uses. In this paper, the artificial neural network (ANN) models were used to model and predict the relationship between groundwater abstraction and water quality determinants in the lower Seybouse River basin. The study area chosen is the lower Seybouse River basin and real data were collected from forty five wells for reference year 2006. Results indicate that the feed-forward multilayer perceptron models with back-propagation are useful tools to define and prioritize the important water quality parameters of groundwater abstraction and use. The model evaluation shows that the correlation coefficients are more than 95% for training, verification and testing data. The model aims to link the water quantity and quality with the objective to strengthen the Integrated Water Resources Management approach. It assists water planners and managers to better assess the water quality parameters and progress towards the provision of appropriate quantities of water of suitable quality.

  7. Design and Development of Water Quality Monitoring System Based on Wireless Sensor Network in Aquaculture

    OpenAIRE

    Zhang, Mingfei; Li, Daoliang; Wang, Lianzhi; Ma, Daokun; Ding, Qisheng

    2010-01-01

    International audience; This paper presents a system framework taking the advantages of the WSN for the real-time monitoring on the water quality in aquaculture. We design the structure of the wireless sensor network to collect and continuously transmit data to the monitoring software. Then we accomplish the configuration model in the software that enhances the reuse and facility of the monitoring project. Moreover, the monitoring software developed to represent the monitoring hardware and da...

  8. 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...

  9. Risk assessment of water quality using Monte Carlo simulation and artificial neural network method.

    Science.gov (United States)

    Jiang, Yunchao; Nan, Zhongren; Yang, Sucai

    2013-06-15

    There is always uncertainty in any water quality risk assessment. A Monte Carlo simulation (MCS) is regarded as a flexible, efficient method for characterizing such uncertainties. However, the required computational effort for MCS-based risk assessment is great, particularly when the number of random variables is large and the complicated water quality models have to be calculated by a computationally expensive numerical method, such as the finite element method (FEM). To address this issue, this paper presents an improved method that incorporates an artificial neural network (ANN) into the MCS to enhance the computational efficiency of conventional risk assessment. The conventional risk assessment uses the FEM to create multiple water quality models, which can be time consuming or cumbersome. In this paper, an ANN model was used as a substitute for the iterative FEM runs, and thus, the number of water quality models that must be calculated can be dramatically reduced. A case study on the chemical oxygen demand (COD) pollution risks in the Lanzhou section of the Yellow River in China was taken as a reference. Compared with the conventional risk assessment method, the ANN-MCS-based method can save much computational effort without a loss of accuracy. The results show that the proposed method in this paper is more applicable to assess water quality risks. Because the characteristics of this ANN-MCS-based technique are quite general, it is hoped that the technique can also be applied to other MCS-based uncertainty analysis in the environmental field. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Hydrologic and water quality terminology as applied to modeling

    Science.gov (United States)

    A survey of literature and examination in particular of terminology use in a previous special collection of modeling calibration and validation papers has been conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and val...

  11. Performance measures and criteria for hydrologic and water quality models

    Science.gov (United States)

    Performance measures and criteria are essential for model calibration and validation. This presentation will include a summary of one of the papers that will be included in the 2014 Hydrologic and Water Quality Model Calibration & Validation Guidelines Special Collection of the ASABE Transactions. T...

  12. A qualitative ecological model to support mariculture pond water quality management.

    Science.gov (United States)

    Brown, D J

    1995-12-01

    A qualitative model of the ecology of a mariculture pond is described. The model represents ecological relationships in the form of a network of tableaux of inference rules which are scanned by a deductive reasoning mechanism to compute the values of pond water quality indicators, make forecasts and determine appropriate corrective and/or preventative maintenance actions.

  13. DRAINMOD-GIS: a lumped parameter watershed scale drainage and water quality model

    Science.gov (United States)

    G.P. Fernandez; G.M. Chescheir; R.W. Skaggs; D.M. Amatya

    2006-01-01

    A watershed scale lumped parameter hydrology and water quality model that includes an uncertainty analysis component was developed and tested on a lower coastal plain watershed in North Carolina. Uncertainty analysis was used to determine the impacts of uncertainty in field and network parameters of the model on the predicted outflows and nitrate-nitrogen loads at the...

  14. Assessment and modelling of the influence of man-made networks on the hydrology of a small watershed: implications for fast flow components, water quality and landscape management

    Science.gov (United States)

    Carluer, Nadia; Marsily, Ghislain De

    2004-01-01

    Up to now, most watershed models have been focused on the representation of 'natural' flow and transport processes. In this paper, we discuss the role of man-made networks, such as ditches, roads, hedge rows and hedges, underground drainage by buried pipes, etc. The influence of such features on the hydrology of a watershed may be of particular importance if the aim of the modelling is to predict the effect of landscape management or the fate of contaminants, e.g. pesticides, when a rain event occurs very soon after their spreading on the soil surface. It is likely that such artificial networks may act as conduits or short-circuits for the transport of contaminants, either dissolved or sorbed on soil particles, by-passing some of the retardation mechanisms such as sorption in the soil, retention of surface runoff by grass verges, biodegradation in the unsaturated zone, etc. We first present a small watershed on which the study was conducted, the Kervidy, which is a 5 km 2 'bocage ' catchment in Brittany, France. The man-made networks were observed and their extent and functioning described. We then included the potential hydraulic role of these networks in a distributed watershed model (TOPOG, [J. Hydrol. 150 (1993) 665]). This modified model, ANTHROPOG, was run, for comparison, with and without the man-made network; sensitivity tests were also made to assess the hydrologic importance of these networks. It was shown that they can have a very significant effect on the functioning of a watershed. We conclude on the relevance of the improved distributed model for the management of rural landscapes, and on the type of additional data needed to calibrate the model with parameters representative of the true processes. Bocage is a landscape with grassland, hedges, and occasional trees—often apple trees—typical of Brittany and Normandy.

  15. 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.

  16. Approaches to verification of two-dimensional water quality models

    Energy Technology Data Exchange (ETDEWEB)

    Butkus, S.R. (Tennessee Valley Authority, Chattanooga, TN (USA). Water Quality Dept.)

    1990-11-01

    The verification of a water quality model is the one procedure most needed by decision making evaluating a model predictions, but is often not adequate or done at all. The results of a properly conducted verification provide the decision makers with an estimate of the uncertainty associated with model predictions. Several statistical tests are available for quantifying of the performance of a model. Six methods of verification were evaluated using an application of the BETTER two-dimensional water quality model for Chickamauga reservoir. Model predictions for ten state variables were compared to observed conditions from 1989. Spatial distributions of the verification measures showed the model predictions were generally adequate, except at a few specific locations in the reservoir. The most useful statistics were the mean standard error of the residuals. Quantifiable measures of model performance should be calculated during calibration and verification of future applications of the BETTER model. 25 refs., 5 figs., 7 tabs.

  17. 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.

  18. Hydrologic and water quality modeling: spatial and temporal considerations

    Science.gov (United States)

    Hydrologic and water quality models are used to help manage water resources by investigating the effects of climate, land use, land management, and water management on water resources. Each water-related issue is better investigated at a specific scale, which can vary spatially from point to watersh...

  19. Hydrologic and water quality models: Use, calibration, and validation

    Science.gov (United States)

    This paper introduces a special collection of 22 research articles that present and discuss calibration and validation concepts in detail for hydrologic and water quality models by their developers and presents a broad framework for developing the American Society of Agricultural and Biological Engi...

  20. Hydrologic and water quality models: Performance measures and evaluation criteria

    Science.gov (United States)

    Performance measures and corresponding criteria constitute an important aspect of calibration and validation of any hydrological and water quality (H/WQ) model. As new and improved methods and information are developed, it is essential that performance measures and criteria be updated. Therefore, th...

  1. 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.

  2. 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 re-chlorination points. .... *USEPA (2009a) states 1 NTU when the system uses conventional or direct filtration and 5NTU when the system uses filtration other than the conven- tional or direct ...

  3. 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.

  4. Modeling Water Quality Parameters Using Data-driven Methods

    Directory of Open Access Journals (Sweden)

    Shima Soleimani

    2017-02-01

    Full Text Available Introduction: Surface water bodies are the most easily available water resources. Increase use and waste water withdrawal of surface water causes drastic changes in surface water quality. Water quality, importance as the most vulnerable and important water supply resources is absolutely clear. Unfortunately, in the recent years because of city population increase, economical improvement, and industrial product increase, entry of pollutants to water bodies has been increased. According to that water quality parameters express physical, chemical, and biological water features. So the importance of water quality monitoring is necessary more than before. Each of various uses of water, such as agriculture, drinking, industry, and aquaculture needs the water with a special quality. In the other hand, the exact estimation of concentration of water quality parameter is significant. Material and Methods: In this research, first two input variable models as selection methods (namely, correlation coefficient and principal component analysis were applied to select the model inputs. Data processing is consisting of three steps, (1 data considering, (2 identification of input data which have efficient on output data, and (3 selecting the training and testing data. Genetic Algorithm-Least Square Support Vector Regression (GA-LSSVR algorithm were developed to model the water quality parameters. In the LSSVR method is assumed that the relationship between input and output variables is nonlinear, but by using a nonlinear mapping relation can create a space which is named feature space in which relationship between input and output variables is defined linear. The developed algorithm is able to gain maximize the accuracy of the LSSVR method with auto LSSVR parameters. Genetic algorithm (GA is one of evolutionary algorithm which automatically can find the optimum coefficient of Least Square Support Vector Regression (LSSVR. The GA-LSSVR algorithm was employed to

  5. 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...

  6. Application of expert systems technology in water-quality modeling

    Energy Technology Data Exchange (ETDEWEB)

    Barnwell, T.O.; Brown, L.C.; Marek, W.

    1989-01-01

    Computerized modeling is becoming an integral part of decision making in water pollution control. Expert Systems is an innovative methodology that can assist in building, using, and interpreting the output of the models. The paper reviews the use and evaluates the potential of expert systems technology in environmental modeling and describes the elements of an expert advisor for the stream water quality model QUAL2E. Some general conclusions are presented about the tools available to develop the system, the level of available technology in knowledge-based engineering, and the value of approaching problems from a knowledge engineering perspective.

  7. Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1980-2015

    Science.gov (United States)

    Deacon, Jeffrey R.; Lee, Casey; Norman, Julia E.; Reutter, David C.

    2016-01-01

    The National Water Quality Network (NWQN) for Rivers and Streams includes 113 surface-water river and stream sites monitored by the U.S. Geological Survey (USGS) National Water Quality Program, National Water-Quality Assessment (NAWQA) Project. The NWQN includes 19 large river coastal sites, 44 large river inland sites, 30 wadeable stream reference sites, 10 wadeable stream urban sites, and 10 wadeable stream agricultural sites. In addition to the 113 NWQN sites, 3 large inland river monitoring sites from the USGS Cooperative Water Program are also included in this annual water-quality reporting Web site to be consistent with previous USGS studies of nutrient transport in the Mississippi-Atchafalaya River Basin. This data release provides streamflow, nutrient, pesticide and sediment data collected and analyzed by NWQN and other historical water-quality networks from 1980-2015. Data from this release are presented at the USGS Tracking Water Quality page: http://cida.usgs.gov/quality/rivers/home.

  8. 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.

  9. Evaluation of multivariate linear regression and artificial neural networks in prediction of water quality parameters.

    Science.gov (United States)

    Zare Abyaneh, Hamid

    2014-01-23

    This paper examined the efficiency of multivariate linear regression (MLR) and artificial neural network (ANN) models in prediction of two major water quality parameters in a wastewater treatment plant. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as well as indirect indicators of organic matters are representative parameters for sewer water quality. Performance of the ANN models was evaluated using coefficient of correlation (r), root mean square error (RMSE) and bias values. The computed values of BOD and COD by model, ANN method and regression analysis were in close agreement with their respective measured values. Results showed that the ANN performance model was better than the MLR model. Comparative indices of the optimized ANN with input values of temperature (T), pH, total suspended solid (TSS) and total suspended (TS) for prediction of BOD was RMSE = 25.1 mg/L, r = 0.83 and for prediction of COD was RMSE = 49.4 mg/L, r = 0.81. It was found that the ANN model could be employed successfully in estimating the BOD and COD in the inlet of wastewater biochemical treatment plants. Moreover, sensitive examination results showed that pH parameter have more effect on BOD and COD predicting to another parameters. Also, both implemented models have predicted BOD better than COD.

  10. Monitoring and modeling of microbial and biological water quality

    Science.gov (United States)

    Microbial and biological water quality informs on the health of water systems and their suitability for uses in irrigation, recreation, aquaculture, and other activities. Indicators of microbial and biological water quality demonstrate high spatial and temporal variability. Therefore, monitoring str...

  11. Water Quality Monitoring and Control for Aquaculture Based on Wireless Sensor Networks

    OpenAIRE

    Daudi S. Simbeye; Shi Feng Yang

    2014-01-01

    We have designed and presented a wireless sensor network monitoring and control system for aquaculture. The system can detect and control water quality parameters of temperature, dissolved oxygen content, pH value, and water level in real-time. The sensor nodes collect the water quality parameters and transmit them to the base station host computer through ZigBee wireless communication standard. The host computer is used for data analysis, processing and presentation using LabVIEW software pl...

  12. Design of water quality monitoring networks with two information scenarios in tropical Andean basins.

    Science.gov (United States)

    Bastidas, Juan Carlos; Vélez, Jorge Julián; Zambrano, Jeannette; Londoño, Adela

    2017-09-01

    Design and redesign of water quality monitoring networks were evaluated for two similarly sized watersheds in the tropical Andes via optimization techniques using geographic information system technology (GIS) and a matter-element analysis of 5-day biological oxygen demand (BOD 5 ) and total suspended solids (TSS). This resulted in a flexible, objectively based design for a 1128-km 2 watershed without prior water quality data (La Miel River), and a network redesign of a 1052-km 2 watershed with historical water quality monitoring (Chinchiná River). Monitoring design for the undocumented basin incorporated mathematical expressions for physical, anthropological, and historical factors-and was based on clear objectives for diagnosis and intervention of water pollution. Network redesign identified network redundancy, which resulted in a 64% reduction in the number of water quality monitoring stations along the channel, and a 78% reduction of stations throughout the basin. Most tropical drainage basins throughout the world have little to no prior water quality data. But even in well-studied drainage basins like the Chinchiná River, which is among the most thoroughly studied basins in Colombia, redesign of historical and existing monitoring networks will become a standard tool to advance the restoration of polluted surface waters, not only in Colombia, but also throughout the world.

  13. 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

  14. 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.

  15. Reduction of Waste Water in Erhai Lake Based on MIKE21 Hydrodynamic and Water Quality Model

    OpenAIRE

    Changjun Zhu; Qinag Liang; Feng Yan; Wenlong Hao

    2013-01-01

    In order to study the ecological water environment in Erhai Lake, different monitoring sections were set to research the change of hydrodynamics and water quality. According to the measured data, MIKE21 Ecolab, the water quality simulation software developed by DHI, is applied to simulate the water quality in Erhai Lake. The hydrodynamics model coupled with water quality is established by MIKE21FM software to simulate the current situation of Erhai Lake. Then through the comparison with the m...

  16. Application of receptor models on water quality data in source apportionment in Kuantan River Basin

    Directory of Open Access Journals (Sweden)

    Nasir Mohd Fahmi Mohd

    2012-12-01

    Full Text Available Abstract Recent techniques in the management of surface river water have been expanding the demand on the method that can provide more representative of multivariate data set. A proper technique of the architecture of artificial neural network (ANN model and multiple linear regression (MLR provides an advance tool for surface water modeling and forecasting. The development of receptor model was applied in order to determine the major sources of pollutants at Kuantan River Basin, Malaysia. Thirteen water quality parameters were used in principal component analysis (PCA and new variables of fertilizer waste, surface runoff, anthropogenic input, chemical and mineral changes and erosion are successfully developed for modeling purposes. Two models were compared in terms of efficiency and goodness-of-fit for water quality index (WQI prediction. The results show that APCS-ANN model gives better performance with high R2 value (0.9680 and small root mean square error (RMSE value (2.6409 compared to APCS-MLR model. Meanwhile from the sensitivity analysis, fertilizer waste acts as the dominant pollutant contributor (59.82% to the basin studied followed by anthropogenic input (22.48%, surface runoff (13.42%, erosion (2.33% and lastly chemical and mineral changes (1.95%. Thus, this study concluded that receptor modeling of APCS-ANN can be used to solve various constraints in environmental problem that exist between water distribution variables toward appropriate water quality management.

  17. Application of Receptor Models on Water Quality Data in Source Apportionment in Kuantan River Basin

    Directory of Open Access Journals (Sweden)

    Mohd Fahmi Mohd Nasir

    2012-12-01

    Full Text Available Recent techniques in the management of surface river water have been expanding the demand on the method that can provide more representative of multivariate data set. A proper technique of the architecture of artificial neural network (ANN model and multiple linear regression (MLR provides an advance tool for surface water modeling and forecasting. The development of receptor model was applied in order to determine the major sources of pollutants at Kuantan River Basin, Malaysia. Thirteen water quality parameters were used in principal component analysis (PCA and new variables of fertilizer waste, surface runoff, anthropogenic input, chemical and mineral changes and erosion are successfully developed for modeling purposes. Two models were compared in terms of efficiency and goodness-of-fit for water quality index (WQI prediction. The results show that APCS-ANN model gives better performance with high R2 value (0.9680 and small root mean square error (RMSE value (2.6409 compared to APCS-MLR model. Meanwhile from the sensitivity analysis, fertilizer waste acts as the dominant pollutant contributor (59.82% to the basin studied followed by anthropogenic input (22.48%, surface runoff (13.42%, erosion (2.33% and lastly chemical and mineral changes (1.95%. Thus, this study concluded that receptor modeling of APCS-ANN can be used to solve various constraints in environmental problem that exist between water distribution variables toward appropriate water quality management.

  18. A Multivariate Model for Coastal Water Quality Mapping Using Satellite Remote Sensing Images.

    Science.gov (United States)

    Su, Yuan-Fong; Liou, Jun-Jih; Hou, Ju-Chen; Hung, Wei-Chun; Hsu, Shu-Mei; Lien, Yi-Ting; Su, Ming-Daw; Cheng, Ke-Sheng; Wang, Yeng-Fung

    2008-10-10

    his study demonstrates the feasibility of coastal water quality mapping using satellite remote sensing images. Water quality sampling campaigns were conducted over a coastal area in northern Taiwan for measurements of three water quality variables including Secchi disk depth, turbidity, and total suspended solids. SPOT satellite images nearly concurrent with the water quality sampling campaigns were also acquired. A spectral reflectance estimation scheme proposed in this study was applied to SPOT multispectral images for estimation of the sea surface reflectance. Two models, univariate and multivariate, for water quality estimation using the sea surface reflectance derived from SPOT images were established. The multivariate model takes into consideration the wavelength-dependent combined effect of individual seawater constituents on the sea surface reflectance and is superior over the univariate model. Finally, quantitative coastal water quality mapping was accomplished by substituting the pixel-specific spectral reflectance into the multivariate water quality estimation model.

  19. Suitability of a Coupled Hydrodynamic Water Quality Model to Predict Changes in Water Quality from Altered Meteorological Boundary Conditions

    Directory of Open Access Journals (Sweden)

    Leon van der Linden

    2015-01-01

    Full Text Available Downscaled climate scenarios can be used to inform management decisions on investment in infrastructure or alternative water sources within water supply systems. Appropriate models of the system components, such as catchments, rivers, lakes and reservoirs, are required. The climatic sensitivity of the coupled hydrodynamic water quality model ELCOM-CAEDYM was investigated, by incrementally altering boundary conditions, to determine its suitability for evaluating climate change impacts. A series of simulations were run with altered boundary condition inputs for the reservoir. Air and inflowing water temperature (TEMP, wind speed (WIND and reservoir inflow and outflow volumes (FLOW were altered to investigate the sensitivity of these key drivers over relevant domains. The simulated water quality variables responded in broadly plausible ways to the altered boundary conditions; sensitivity of the simulated cyanobacteria population to increases in temperature was similar to published values. However the negative response of total chlorophyll-a suggested by the model was not supported by an empirical analysis of climatic sensitivity. This study demonstrated that ELCOM-CAEDYM is sensitive to climate drivers and may be suitable for use in climate impact studies. It is recommended that the influence of structural and parameter derived uncertainty on the results be evaluated. Important factors in determining phytoplankton growth were identified and the importance of inflowing water quality was emphasized.

  20. 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.

  1. 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

  2. Integrated hydro-bacterial modelling for predicting bathing water quality

    Science.gov (United States)

    Huang, Guoxian; Falconer, Roger A.; Lin, Binliang

    2017-03-01

    In recent years health risks associated with the non-compliance of bathing water quality have received increasing worldwide attention. However, it is particularly challenging to establish the source of any non-compliance, due to the complex nature of the source of faecal indicator organisms, and the fate and delivery processes and scarcity of field measured data in many catchments and estuaries. In the current study an integrated hydro-bacterial model, linking a catchment, 1-D model and 2-D model were integrated to simulate the adsorption-desorption processes of faecal bacteria to and from sediment particles in river, estuarine and coastal waters, respectively. The model was then validated using hydrodynamic, sediment and faecal bacteria concentration data, measured in 2012, in the Ribble river and estuary, and along the Fylde coast, UK. Particular emphasis has been placed on the mechanism of faecal bacteria transport and decay through the deposition and resuspension of suspended sediments. The results showed that by coupling the E.coli concentration with the sediment transport processes, the accuracy of the predicted E.coli levels was improved. A series of scenario runs were then carried out to investigate the impacts of different management scenarios on the E.coli concentration levels in the coastal bathing water sites around Liverpool Bay, UK. The model results show that the level of compliance with the new EU bathing water standards can be improved significantly by extending outfalls and/or reducing urban sources by typically 50%.

  3. Emission Control in River Network System of the Taihu Basin for Water Quality Assurance of Water Environmentally Sensitive Areas

    Directory of Open Access Journals (Sweden)

    Xiao Wang

    2017-02-01

    Full Text Available As pollution incidents frequently occurred in the functional water areas of the Taihu Basin, Yangtze Delta, effective emission control to guarantee water quality in the Taihu Basin became the priority for environmental management. In this study, a new total emission control (TEC method was proposed with an emphasis on the concept of water environmentally sensitive areas (WESAs. This method was verified in Wujiang District and the techniques can be concluded in three steps: (1 a 1-D mathematical model for the study area was established and the model was calibrated using field measurement data; (2 based on an analysis of administrative planning and regulations, WESAs were identified as the main controlling objectives for emission control calculations. The weighting coefficient of local pollution sources was investigated to discuss the effectiveness of TEC on water quality improvement at WESAs; and (3 applying the river network mathematical model, water quality along the river segments was simulated under different pollution control plans. The results proved the effectiveness of TEC in the study area and indicated that a 14.6% reduction in the total amount of ammonia-nitrogen (NH3-N, as well as a 31.1% reduction in the total amount of chemical oxygen demand (CODcr, was essential in order to meet the water quality standard in the WESAs.

  4. Climate Change Impacts on US Water Quality Using Two Models: HAWQS and US Basins

    Directory of Open Access Journals (Sweden)

    Charles Fant

    2017-02-01

    Full Text Available 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 Hydrologic and Water Quality System; HAWQS and US Basins, five climate models, and two greenhouse gas (GHG mitigation policies, we assess future water quality in the continental U.S. to 2100 considering four water quality parameters: water temperature, dissolved oxygen, total nitrogen, and total phosphorus. Once these parameters are aggregated into a water quality index, we find that, while the water quality models differ under the baseline, there is more agreement between future projections. In addition, we find that the difference in national-scale economic benefits across climate models is generally larger than the difference between the two water quality models. Both water quality models find that water quality will more likely worsen in the East than in the West. Under the business-as-usual emissions scenario, we find that climate change is likely to cause economic impacts ranging from 1.2 to 2.3 (2005 billion USD/year in 2050 and 2.7 to 4.8 in 2090 across all climate and water quality models.

  5. 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...

  6. 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

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

    Directory of Open Access Journals (Sweden)

    Xiaoci Huang

    2015-11-01

    Full Text Available 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.

  8. 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.

  9. Stormwater Runoff and Water Quality Modeling in Urban Maryland

    Science.gov (United States)

    Wang, J.; Forman, B. A.; Natarajan, P.; Davis, A.

    2015-12-01

    Urbanization significantly affects storm water runoff through the creation of new impervious surfaces such as highways, parking lots, and rooftops. Such changes can adversely impact the downstream receiving water bodies in terms of physical, chemical, and biological conditions. In order to mitigate the effects of urbanization on downstream water bodies, stormwater control measures (SCMs) have been widely used (e.g., infiltration basins, bioswales). A suite of observations from an infiltration basin installed adjacent to a highway in urban Maryland was used to evaluate stormwater runoff attenuation and pollutant removal rates at the well-instrumented SCM study site. In this study, the Storm Water Management Model (SWMM) was used to simulate the performance of the SCM. An automatic, split-sample calibration framework was developed to improve SWMM performance efficiency. The results indicate SWMM can accurately reproduce the hydraulic response of the SCM (in terms of reproducing measured inflow and outflow) during synoptic scale storm events lasting more than one day, but is less accurate during storm events lasting only a few hours. Similar results were found for a suite of modeled (and observed) water quality constituents, including suspended sediment, metals, N, P, and chloride.

  10. Prediction and assessment of drought effects on surface water quality using artificial neural networks: case study of Zayandehrud River, Iran.

    Science.gov (United States)

    Safavi, Hamid R; Malek Ahmadi, Kian

    2015-01-01

    Although drought impacts on water quantity are widely recognized, the impacts on water quality are less known. The Zayandehrud River basin in the west-central part of Iran plateau witnessed an increased contamination during the recent droughts and low flows. The river has been receiving wastewater and effluents from the villages, a number of small and large industries, and irrigation drainage systems along its course. What makes the situation even worse is the drought period the river basin has been going through over the last decade. Therefore, a river quality management model is required to include the adverse effects of industrial development in the region and the destructive effects of droughts which affect the river's water quality and its surrounding environment. Developing such a model naturally presupposes investigations into pollution effects in terms of both quality and quantity to be used in such management tools as mathematical models to predict the water quality of the river and to prevent pollution escalation in the environment. The present study aims to investigate electrical conductivity of the Zayandehrud River as a water quality parameter and to evaluate the effect of this parameter under drought conditions. For this purpose, artificial neural networks are used as a modeling tool to derive the relationship between electrical conductivity and the hydrological parameters of the Zayandehrud River. The models used in this research include multi-layer perceptron and radial basis function. Finally, these two models are compared in terms of their performance using the time series of electrical conductivity at eight monitoring-hydrometric stations during drought periods between the years 1997-2012. Results show that artificial neural networks can be used for modeling the relationship between electrical conductivity and hydrological parameters under drought conditions. It is further shown that radial basis function works better for the upstream stretches

  11. Power analysis and trend detection for water quality monitoring data. An application for the Greater Yellowstone Inventory and Monitoring Network

    Science.gov (United States)

    Irvine, Kathryn M.; Manlove, Kezia; Hollimon, Cynthia

    2012-01-01

    An important consideration for long term monitoring programs is determining the required sampling effort to detect trends in specific ecological indicators of interest. To enhance the Greater Yellowstone Inventory and Monitoring Network’s water resources protocol(s) (O’Ney 2006 and O’Ney et al. 2009 [under review]), we developed a set of tools to: (1) determine the statistical power for detecting trends of varying magnitude in a specified water quality parameter over different lengths of sampling (years) and different within-year collection frequencies (monthly or seasonal sampling) at particular locations using historical data, and (2) perform periodic trend analyses for water quality parameters while addressing seasonality and flow weighting. A power analysis for trend detection is a statistical procedure used to estimate the probability of rejecting the hypothesis of no trend when in fact there is a trend, within a specific modeling framework. In this report, we base our power estimates on using the seasonal Kendall test (Helsel and Hirsch 2002) for detecting trend in water quality parameters measured at fixed locations over multiple years. We also present procedures (R-scripts) for conducting a periodic trend analysis using the seasonal Kendall test with and without flow adjustment. This report provides the R-scripts developed for power and trend analysis, tutorials, and the associated tables and graphs. The purpose of this report is to provide practical information for monitoring network staff on how to use these statistical tools for water quality monitoring data sets.

  12. 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.

  13. Climate Change Impacts on US Water Quality Using Two Models: HAWQS and US Basins

    OpenAIRE

    Charles Fant; Raghavan Srinivasan; Brent Boehlert; Lisa Rennels; Steven C. Chapra; Strzepek, Kenneth M.; Joel Corona; Ashley Allen; Jeremy Martinich

    2016-01-01

    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 Hydrologic and Water Quality System; HAWQS and US Basins), five climate models, and two greenhouse gas (GHG) mitigation policies, we assess future water quality in the continental U.S. to 2100 considering four water quali...

  14. 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

  15. 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...

  16. 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

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

    Science.gov (United States)

    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 tocalibrate 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 variation

  18. 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.

  19. Parameter optimization method for the water quality dynamic model based on data-driven theory.

    Science.gov (United States)

    Liang, Shuxiu; Han, Songlin; Sun, Zhaochen

    2015-09-15

    Parameter optimization is important for developing a water quality dynamic model. In this study, we applied data-driven method to select and optimize parameters for a complex three-dimensional water quality model. First, a data-driven model was developed to train the response relationship between phytoplankton and environmental factors based on the measured data. Second, an eight-variable water quality dynamic model was established and coupled to a physical model. Parameter sensitivity analysis was investigated by changing parameter values individually in an assigned range. The above results served as guidelines for the control parameter selection and the simulated result verification. Finally, using the data-driven model to approximate the computational water quality model, we employed the Particle Swarm Optimization (PSO) algorithm to optimize the control parameters. The optimization routines and results were analyzed and discussed based on the establishment of the water quality model in Xiangshan Bay (XSB). Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. A hybrid evolutionary data driven model for river water quality early warning.

    Science.gov (United States)

    Burchard-Levine, Alejandra; Liu, Shuming; Vince, Francois; Li, Mingming; Ostfeld, Avi

    2014-10-01

    China's fast pace industrialization and growing population has led to several accidental surface water pollution events in the last decades. The government of China, after the 2005 Songhua River incident, has pushed for the development of early warning systems (EWS) for drinking water source protection. However, there are still many weaknesses in EWS in China such as the lack of pollution monitoring and advanced water quality prediction models. The application of Data Driven Models (DDM) such as Artificial Neural Networks (ANN) has acquired recent attention as an alternative to physical models. For a case study in a south industrial city in China, a DDM based on genetic algorithm (GA) and ANN was tested to increase the response time of the city's EWS. The GA-ANN model was used to predict NH3-N, CODmn and TOC variables at station B 2 h ahead of time while showing the most sensitive input variables available at station A, 12 km upstream. For NH3-N, the most sensitive input variables were TOC, CODmn, TP, NH3-N and Turbidity with model performance giving a mean square error (MSE) of 0.0033, mean percent error (MPE) of 6% and regression (R) of 92%. For COD, the most sensitive input variables were Turbidity and CODmn with model performance giving a MSE of 0.201, MPE of 5% and R of 0.87. For TOC, the most sensitive input variables were Turbidity and CODmn with model performance giving a MSE of 0.101, MPE of 2% and R of 0.94. In addition, the GA-ANN model performed better for 8 h ahead of time. For future studies, the use of a GA-ANN modelling technique can be very useful for water quality prediction in Chinese monitoring stations which already measure and have immediately available water quality data. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Designing Groundwater Monitoring Networks for Regional-Scale Water Quality Assessment: A Bayesian Approach

    Science.gov (United States)

    Pinto, M. J.; Wagner, B. J.

    2002-12-01

    The design of groundwater monitoring networks is an important concern of regional-scale water-quality assessment programs because of the high cost of data collection. The work presented here addresses regional-scale design issues using ground-water simulation and optimization set within a Bayesian framework. The regional-scale design approach focuses on reducing the uncertainty associated with a fundamental quantity: the proportion of a subsurface water resource which exceeds a specified threshold concentration, such as a mandated maximum contaminant level. This proportion is hereafter referred to as the threshold proportion. The goal is to identify optimal or near-optimal sampling designs that reduce the threshold proportion uncertainty to an acceptable level. In the Bayesian approach, there is a probability density function (pdf) associated with the unknown threshold proportion before sampling. This function is known as the prior pdf. The form of the prior pdf, which is dependent on the information available regarding the distribution of water quality within the aquifer system, controls the amount of sampling needed. In the absence of information, the form of the prior pdf is uniform; however, if a ground-water flow and transport model is available, a Monte Carlo analysis of ground-water flow and transport simulations can be used to generate a prior pdf which is non-uniform and which contains the information available regarding solute sources, pathways and transport. After sampling, the prior pdf is conditioned on the sampling data. The conditional distribution is known as the posterior pdf. In most cases there is a reduction in uncertainty associated with conditioning. The reduction in uncertainty achieved after collecting samples can be explored for different combinations of prior pdf distribution and sampling method. Three scenarios are considered: (i) uniform prior pdf with random sampling; (ii) non-uniform prior pdf with random sampling; and (iii) non

  2. 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.

  3. 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

  4. 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

  5. Using Remote Sensing Data to Update a Dynamic Regional-Scale Water Quality Model

    Science.gov (United States)

    Smith, R. A.; Nolin, A.; Brakebill, J.; Sproles, E.; Macauley, M.

    2012-04-01

    Regional scale SPARROW models, used by the US Geological Survey, relate watershed characteristics to in stream water quality. SPARROW models are widely used to identify and quantify the sources of contaminants in watersheds and to predict their flux and concentration at specified locations downstream. Conventional SPARROW models are steady-state models and describe the average relationship between sources and stream conditions based on long-term water quality monitoring data and spatially referenced explanatory information. However, many watershed management issues stem from intra- and inter-annual changes in contaminant sources, hydrologic forcing, or other environmental conditions, which cause a temporary imbalance between inputs and stream water quality. Dynamic behavior of the system relating to changes in watershed storage and processing then becomes important. Here, we describe a dynamically calibrated SPARROW model of total nitrogen flux in the Potomac River Basin based on seasonal water quality and watershed input data for 80 monitoring stations over the period 2000 to 2008. One challenge in dynamic modeling of reactive nitrogen is obtaining spatially detailed and sufficiently frequent input data on the phenology of agricultural production and terrestrial vegetation. We use the Enhanced Vegetation Index (EVI) and gross primary productivity data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite to parameterize seasonal uptake and release of nitrogen. The spatial reference frame of the model is a 16,000-reach, 1:100,000-scale stream network, and the computational time step is seasonal. Precipitation and temperature data are from the PRISM gridded data set, augmented with snow frequency derived from MODIS. The model formulation allows for separate storage compartments for nonpoint sources including fertilized cropland, pasture, urban land, and atmospheric deposition. Removal of nitrogen from watershed storage to stream channels

  6. Data from selected U.S. Geological Survey national stream water quality monitoring networks

    Science.gov (United States)

    Alexander, R.B.; Slack, J.R.; Ludtke, A.S.; Fitzgerald, K.K.; Schertz, T.L.

    1998-01-01

    A nationally consistent and well-documented collection of water quality and quantity data compiled during the past 30 years for streams and rivers in the United States is now available on CD-ROM and accessible over the World Wide Web. The data include measurements from two U.S. Geological Survey (USGS) national networks for 122 physical, chemical, and biological properties of water collected at 680 monitoring stations from 1962 to 1995, quality assurance information that describes the sample collection agencies, laboratories, analytical methods, and estimates of laboratory measurement error (bias and variance), and information on selected cultural and natural characteristics of the station watersheds. The data are easily accessed via user-supplied software including Web browser, spreadsheet, and word processor, or may be queried and printed according to user-specified criteria using the supplied retrieval software on CD-ROM. The water quality data serve a variety of scientific uses including research and educational applications related to trend detection, flux estimation, investigations of the effects of the natural environment and cultural sources on water quality, and the development of statistical methods for designing efficient monitoring networks and interpreting water resources data.

  7. 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.

  8. Modeling water-quality loads to the reservoirs of the Upper Trinity River Basin, Texas, USA

    Science.gov (United States)

    Water quality modeling efforts have been conducted for 12 reservoirs in ten watersheds in Upper Trinity River Basin located in north Texas. The reservoirs are being used for water supply to the populated area around the Dallas-Fort Worth Metro and the water quality of some of these reservoirs has b...

  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. Controls of catchments` sub-storage contributions to dynamic water quality patterns in the stream network

    Science.gov (United States)

    Schuetz, Tobias; Maike Hegenauer, Anja

    2016-04-01

    Water quality is usually observed either continuously at a few stations within a catchment or with few snapshot sampling campaigns throughout the whole stream network. Although we know that the depletion of catchment sub-storages can vary throughout the stream network according to their actual water content (spatial variability of actual storage conditions can be caused amongst others by unevenly distributed rainfall, storage size or spatial differences in soil characteristics and land use), we know little about the impact of this process on spatial water quality patterns. For summer low flow recession periods, when stream water composition can be crucial for aquatic ecosystem conditions and the exceedance of water quality thresholds, knowledge on the controls of the dynamic interplay of catchment storages and stream water composition might improve water quality management and the implementation of corresponding mitigation measures. We studied this process throughout the stream network of a first-order agricultural headwater catchment in south-western Germany during two summer low flow recession periods. The underlying geology of the study area is a deep layer of aeolian loess, whilst the dominating soil is a silty calcaric regosol with gleizations in the colluvium. The land use in the catchment is dominated by viniculture (63 %) and arable crops (18 %). Due to the dense drainpipe network within the catchment we could identify 12 sub-catchments contributing during summer low flow recession periods to total stream discharge. We continuously observed discharge, electrical conductivity and water temperatures for 8 of the sub-catchments and at the catchment outlet. This data set was accomplished by 10 snapshot campaigns where we sampled for water temperatures, electrical conductivity, major ions, pH and O2 throughout the stream network. Using either discharge concentration relationships or time dependent functions, we derived continuous export rates for all measures in

  12. GIFMod: A Flexible Modeling Framework For Hydraulic and Water Quality Performance Assessment of Stormwater Green Infrastructure

    Science.gov (United States)

    A flexible framework has been created for modeling multi-dimensional hydrological and water quality processes within stormwater green infrastructures (GIs). The framework models a GI system using a set of blocks (spatial features) and connectors (interfaces) representing differen...

  13. 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...

  14. Impact of rainfall temporal resolution on urban water quality modelling performance and uncertainties.

    Science.gov (United States)

    Manz, Bastian Johann; Rodríguez, Juan Pablo; Maksimović, Cedo; McIntyre, Neil

    2013-01-01

    A key control on the response of an urban drainage model is how well the observed rainfall records represent the real rainfall variability. Particularly in urban catchments with fast response flow regimes, the selection of temporal resolution in rainfall data collection is critical. Furthermore, the impact of the rainfall variability on the model response is amplified for water quality estimates, as uncertainty in rainfall intensity affects both the rainfall-runoff and pollutant wash-off sub-models, thus compounding uncertainties. A modelling study was designed to investigate the impact of altering rainfall temporal resolution on the magnitude and behaviour of uncertainties associated with the hydrological modelling compared with water quality modelling. The case study was an 85-ha combined sewer sub-catchment in Bogotá (Colombia). Water quality estimates showed greater sensitivity to the inter-event variability in rainfall hyetograph characteristics than to changes in the rainfall input temporal resolution. Overall, uncertainties from the water quality model were two- to five-fold those of the hydrological model. However, owing to the intrinsic scarcity of observations in urban water quality modelling, total model output uncertainties, especially from the water quality model, were too large to make recommendations for particular model structures or parameter values with respect to rainfall temporal resolution.

  15. Better understanding of water quality evolution in water distribution networks using data clustering.

    Science.gov (United States)

    Mandel, Pierre; Maurel, Marie; Chenu, Damien

    2015-12-15

    The complexity of water distribution networks raises challenges in managing, monitoring and understanding their behavior. This article proposes a novel methodology applying data clustering to the results of hydraulic simulation to define quality zones, i.e. zones with the same dynamic water origin. The methodology is presented on an existing Water Distribution Network; a large dataset of conductivity measurements measured by 32 probes validates the definition of the quality zones. The results show how quality zones help better understanding the network operation and how they can be used to analyze water quality events. Moreover, a statistical comparison with 158,230 conductivity measurements validates the definition of the quality zones. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Dynamic simulation of water resources in an urban wetland based on coupled water quantity and water quality models.

    Science.gov (United States)

    Zeng, Weibo; Xu, Youpeng; Deng, Xiaojun; Han, Longfei; Zhang, Qianyu

    2015-01-01

    Water quality in wetlands plays a huge role in maintaining the health of the wetland ecosystem. Water quality should be controlled by an appropriate water allocation policy for the protection of the wetlands. In this paper, models of rainfall/runoff, non-point source pollution load, water quantity/quality, and dynamic pollutant-carrying capacity were established to simulate the water quantity/quality of Xixi-wetland river network (in the Taihu basin, China). The simulation results showed a satisfactory agreement with field observations. Furthermore, a 'node-river-node' algorithm that adjusts to the 'Three Steps Method' was adopted to improve the dynamic pollutant-carrying capacity model and simulate the pollutant-carrying capacity in benchmark years. The simulation result shows that the water quality of the river network could reach class III stably all year round if the anthropogenic pollution is reduced to one-third of the current annual amount. Further investigation estimated the minimum amount of water diversion in benchmark years under the reasonable water quantity-regulating rule to keep water quality as class III. With comparison of the designed scale, the water diversion can be reduced by 184 million m3 for a dry year, 191 million m3 for a normal year, and 198 million m3 for a wet year.

  17. Grid-based water quality simulation at catchment scale: Nitrogen model development and evaluation

    Science.gov (United States)

    Yang, Xiaoqiang; Jomaa, Seifeddine; Rode, Michael

    2017-04-01

    Stream water quality has been changed significantly during last few decades due to changes in human impacts. Accurate and flexible water quality models, which can properly reflect the heterogeneity and long term temporal dynamic of catchment functioning, are still needed. To this end, a new grid-based catchment water quality model was developed based on the mesoscale Hydrological Model (mHM) and the HYdrological Prediction of Environment (HYPE) model. The model structure and parameterization scheme were flexibly designed depending on the spatial heterogeneity of study sites and their specific requirements. Based on that, more detailed spatial information can be provided. Moreover, three main improvements on Nitrate sub-model were implemented: i) nitrate transport processes were conducted in physically connected river networks, allowing time-series point-source inputs added in the exact location of sewage treatment plants; ii) additional retention storage of deep groundwater was included for long term nitrate-N simulation; iii) special design for better taking into account crop rotation was implemented. Those new features can extend the model capability and facilitate the understanding of catchment mechanisms and analysis of future scenarios and measures. The newly developed model was fully verified in the Selke catchment (456 km2), central Germany. Long term discharge and water quality data have been collected at three nested gauging stations (1997-2015). The station Meisdorf, above where 72% of area is occupied by forest, represents the discharge and nutrient exports from forest area. Agricultural land dominates the lower part of the catchment (almost 96% of in-between area of the Meisdorf and the outlet station Hausneindorf) with considerable urban areas. Due to the relatively large number of model parameters, sensitivity analysis was firstly conducted. Subsequently, sensitive parameters were calibrated using stepwise and multi-variable approaches, respectively

  18. Multiscale River Hydraulic and Water Quality Observations Combining Stationary and Mobile Sensor Network Nodes

    Science.gov (United States)

    Harmon, T. C.; Fisher, J. C.; Kaiser, W. J.

    2006-05-01

    Increasing demands on water supplies, non-point source pollution, and water quality-based ecological concerns all point to the need for observing stream flow perturbations and pollutant discharges at higher resolution than was practical in the past. This work presents the results from a test of a rapidly deployable river observational approach consisting of four components: (1) existing geospatial data and federal, state, and private river gauging infrastructure for identifying key river reaches and critical sampling times, (2) human- actuated sensor deployments for broad spatial characterization of the targeted river reach, (3) stationary sensors embedded in the river and its sediments for longer term spatiotemporal observations within the targeted reach, and (4) the robotic Networked Infomechanical System (NIMS RD) for high resolution scanning of spatiotemporal hydraulic and chemical properties at specific points along the reach. The approach is demonstrated for a test bed deployment at the confluence of the Merced and San Joaquin Rivers in Central California. After identifying a suitable reach for the test deployment, a network of on-line gauging stations, accessed through the California Data Exchange Center (CDEC), is used to coordinate the timing of the subsequent three deployment aspects based on flow and river stage forecasts. Kayak-mounted sonar and water quality sensors are used to rapidly survey the test zone bathymetry and basic water quality parameters (temperature, salinity). Results from the rapid survey are then used to guide locations of the sediment- anchored sensor arrays (javelins) which include temperature, water pressure (depth) and water quality sensors distributed vertically at screened intervals. The NIMS RD is comprised of two supporting towers and a suspension cable delivering power and Internet connectivity for controlling and actuating the tram-like NIMS unit. The NIMS unit is capable of raising and lowering a payload of sensors

  19. Three-dimensional Modeling of Water Quality and Ecology in Narragansett Bay

    Science.gov (United States)

    This report presents the methodology to apply, calibrate, and validate the three-dimensional water quality and ecological model provided with the Environmental Fluid Dynamics Code (EFDC). The required advection and dispersion mechanisms are generated simultaneously by the EFDC h...

  20. 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.

  1. ENSIS, Pollution inventory, pollution budget model, water quality model and scenario handling. Functional specification

    OpenAIRE

    Bakken, T.H.; Bjørkenes, A.; Dagestad, K.

    2003-01-01

    Årsliste 2003 This is the functional specification of a complete pollution budget model for water. A crucial improvement of this model is implementation of new pollution sources and modification of existing sources. The specification of a water quality model, based on the results from the pollution budget model is also included. The document is intended to give a cost and time estimate of the programming of the functionality it describes, and will be the guideline for implementation of the...

  2. 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.

  3. Agricultural pesticide use estimates for the USGS National Water Quality Network, 1992-2014

    Science.gov (United States)

    Baker, Nancy T.

    2016-01-01

    The National Water Quality Network (NWQN) for Rivers and Streams includes 113 surface-water river and stream sites monitored by the U.S. Geological Survey (USGS) National Water Quality Program (NWQP). The NWQN represents the consolidation of four historical national networks: the USGS National Water-Quality Assessment (NAWQA) Project, the USGS National Stream Quality Accounting Network (NASQAN), the National Monitoring Network (NMN), and the Hydrologic Benchmark Network (HBN). The NWQN includes 22 large river coastal sites, 41 large river inland sites, 30 wadeable stream reference sites, 10 wadeable stream urban sites, and 10 wadeable stream agricultural sites. In addition to the 113 NWQN sites, 3 large inland river monitoring sites from the USGS Cooperative Matching Funds program are also included in this annual water-quality reporting Web site to be consistent with previous USGS studies of nutrient transport in the Mississippi-Atchafalaya River Basin. This data release provides estimated agricultural pesticide use for 83 NWQN watersheds for 110 pesticide compounds from 1992-2014. Pesticide use was not estimated for the 30 wadeable stream reference sites, or from 3 large river coastal sites (07381590, "Wax Lake Outlet at Calumet, LA3"; 07381600, "Lower Atchafalaya River at Morgan City, LA2"; or 15565477, "Yukon River at Pilot Station, AK"). Use was not estimated for reference sites because pesticides are not monitored at reference water-quality sampling sites. Pesticide use data are not available for Alaska and thus no data is available for the Yukon River site. The other two coastal sites (07381590 and 07381600) where use was not estimated are outflow distributaries into the Gulf of Mexico. This data release provides use estimates for the same pesticide parent compounds sampled in water and analyzed by USGS, National Water Quality Laboratory (NWQL), Schedule 2437: http://wwwnwql.cr.usgs.gov/USGS/catalog/index.cfm. Pesticide use data are not available for

  4. 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

  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

    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...

  7. 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.

  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. Evaluating a 1D and 2D water quality modeling framework: A case study of the lower Bode River, Germany

    Science.gov (United States)

    Sinha, Sumit; Rode, Michael; Borchardt, Dietrich

    2014-05-01

    The Bode River catchment in the Harz Mountain area of central Germany is heavily influenced by anthropogenic factors. 70% of the catchment is dominated by agriculture, 23 % by forest and the rest 7% is urban in nature. The area of the catchment is approximately 3300 km2 and is characterized by sharp gradients in temperature, precipitation and land use. In order to acquire better understanding of the hydrological nature of the catchment and biogeochemical characteristics of the Bode River various monitoring stations have been deployed as a part of the larger earth observation network initiative named Terrestrial Environmental Observatories. One of the major issues with the catchment is the problem of eutrophication due to solute inputs from agriculture. The research presented here evaluated the application and development of 1D and 2D hydrodynamic and water quality models in the downstream area of the Bode River. A stretch of 30 kms between Hadmersleeben and Stassfurt in the downstream area of the Bode River was modeled using 1D model HEC-RAS, the focus of the water quality modeling was transport and uptake of nitrate in the aforementioned modeled stretch. Flood events of varying peak magnitude at different times of the year were modeled. As regards to 2D modeling, TELEMAC-2D model was applied for the same reach. The hydrodynamic simulation results were validated with the help of free surface elevation at Athensleben, 8 kms upstream from the downstream end at Stassfurt. Water quality modeling, focusing on the Nitrate removal for the aforementioned stretch, is applied and developed for both 1D and 2D modeling framework. Results from hydrodynamic and water quality modeling were validated with RMSE (Root Mean Square Error) value of 0.074 and 0.36 for the modeled state variables across various events simulated. For the nutrient-rich reach modeled in this research it was found that the nutrient removal capacity of the stream is directly proportional to the incoming

  10. Better Insight Into Water Resources Management With Integrated Hydrodynamic And Water Quality Models

    Science.gov (United States)

    Debele, B.; Srinivasan, R.; Parlange, J.

    2004-12-01

    Models have long been used in water resources management to guide decision making and improve understanding of the system. Numerous models of different scales -spatial and temporal - are available. Yet, very few models manage to bridge simulations of hydrological and water quality parameters from both upland watershed and riverine system. Most water quality models, such as QUAL2E and EPD-RIV1 concentrate on the riverine system while CE-QUAL-W2 and WASP models focus on larger waterbodies, such as lakes and reservoirs. On the other hand, the original SWAT model, HSPF and other upland watershed hydrological models simulate agricultural (diffuse) pollution sources with limited number of processes incorporated to handle point source pollutions that emanate from industrial sectors. Such limitations, which are common in most hydrodynamic and water quality models undermine better understanding that otherwise could be uncovered by employing integrated hydrological and water quality models for both upland watershed and riverine system. The SWAT model is a well documented and verified hydrological and water quality model that has been developed to simulate the effects of various management scenarios on the health of the environment in terms of water quantity and quality. Recently, the SWAT model has been extended to include the simulation of hydrodynamic and water quality parameters in the river system. The extended SWAT model (ESWAT) has been further extended to run using diurnally varying (hourly) weather data and produce outputs at hourly timescales. This and other improvements in the ESWAT model have been documented in the current work. Besides, the results from two case studies in Texas will be reported.

  11. Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors.

    Science.gov (United States)

    Heddam, Salim; Kisi, Ozgur

    2017-07-01

    -ELM performed the best at one station. The OS-ELM models performed the worst and provided the lowest accuracy; (iii) for predicting DO without water quality variables, the R-ELM performed the best at seven stations followed by the S-ELM in the second place and the OP-ELM performed the worst with low accuracy; (iv) for the final application where training ELM models with validation dataset and testing with training dataset, the OP-ELM provided the best accuracy using water quality variables and the R-ELM performed the best at all eight stations without water quality variables. Fourthly, and finally, we compared the results obtained from different ELM models with those obtained using multiple linear regression (MLR) and multilayer perceptron neural network (MLPNN). Results obtained using MLPNN and MLR models reveal that: (i) using water quality variables as predictors, the MLR performed the worst and provided the lowest accuracy in all stations; (ii) MLPNN was ranked in the second place at two stations, in the third place at four stations, and finally, in the fourth place at two stations, (iii) for predicting DO without water quality variables, MLPNN is ranked in the second place at five stations, and ranked in the third, fourth, and fifth places in the remaining three stations, while MLR was ranked in the last place with very low accuracy at all stations. Overall, the results suggest that the ELM is more effective than the MLPNN and MLR for modelling DO concentration in river ecosystems.

  12. Hyperspectral data modeling for water quality studies in Michigan's inland lakes

    Science.gov (United States)

    Wiangwang, Narumon

    Hyperspectral remote sensing imagery has been used to estimate spatial and temporal variation of water quality, such as chlorophyll a, transparency, and suspended solids, primarily for marine and coastal waters. Although physicochemical properties of marine and inland waters differ, hyperspectral data and modeling may provide an alternative tool for inland lake assessment. However, little has been done to identify the most suitable spectral bands for water quality estimation and there is a lack of quantitative relationship between water quality and hyperspectral data. The primary objectives of this study are to identify optimal spectral bands most sensitive to water quality indicators and to develop improved hyperspectral water quality indicators of inland lakes. The secondary objective is to determine the most effective filters for noise removal in hyperspectral data. To address these objectives, a field campaign was conducted on 42 inland lakes in Michigan in 2004. Radiometric spectra, Secchi disk depth, dissolved oxygen, temperature, and light extinction profile data were collected. Water samples were analyzed for chlorophyll a, suspended solid, total nitrogen, total phosphorus, non-purgable organic carbon, and phytoplankton species composition. Spectral radiances were measured with a hand-held spectrometer (LabSpecRTM Pro) and with an airborne Imaging Spectrometer for Applications (AISA) sensor, to correlate the water quality and hyperspectral data. Principal Component Analysis was used to identify the narrow-wavebands, and derivative analysis used to determine the region-wavebands. Statistical spectral water quality indicators were developed to correlate with Secchi depth, chlorophyll a, total suspended solid, non-purgable organic carbon, diatom biomass, green algal biomass, and bluegreen algal biomass. These relations were validated to suggest that high accuracies were achieved for Secchi depth (R2 0.76--0.84), chlorophyll a (R2 0.70--0.76), and bluegreen

  13. Assessment of the water quality and ecosystem health of the Great Barrier Reef (Australia): conceptual models.

    Science.gov (United States)

    Haynes, David; Brodie, Jon; Waterhouse, Jane; Bainbridge, Zoe; Bass, Deb; Hart, Barry

    2007-12-01

    Run-off containing increased concentrations of sediment, nutrients, and pesticides from land-based anthropogenic activities is a significant influence on water quality and the ecologic conditions of nearshore areas of the Great Barrier Reef World Heritage Area, Australia. The potential and actual impacts of increased pollutant concentrations range from bioaccumulation of contaminants and decreased photosynthetic capacity to major shifts in community structure and health of mangrove, coral reef, and seagrass ecosystems. A detailed conceptual model underpins and illustrates the links between the main anthropogenic pressures or threats (dry-land cattle grazing and intensive sugar cane cropping) and the production of key contaminants or stressors of Great Barrier Reef water quality. The conceptual model also includes longer-term threats to Great Barrier Reef water quality and ecosystem health, such as global climate change, that will potentially confound direct model interrelationships. The model recognises that system-specific attributes, such as monsoonal wind direction, rainfall intensity, and flood plume residence times, will act as system filters to modify the effects of any water-quality system stressor. The model also summarises key ecosystem responses in ecosystem health that can be monitored through indicators at catchment, riverine, and marine scales. Selected indicators include riverine and marine water quality, inshore coral reef and seagrass status, and biota pollutant burdens. These indicators have been adopted as components of a long-term monitoring program to enable assessment of the effectiveness of change in catchment-management practices in improving Great Barrier Reef (and adjacent catchment) water quality under the Queensland and Australian Governments' Reef Water Quality Protection Plan.

  14. Assessment of the Water Quality and Ecosystem Health of the Great Barrier Reef (Australia): Conceptual Models

    Science.gov (United States)

    Haynes, David; Brodie, Jon; Waterhouse, Jane; Bainbridge, Zoe; Bass, Deb; Hart, Barry

    2007-12-01

    Run-off containing increased concentrations of sediment, nutrients, and pesticides from land-based anthropogenic activities is a significant influence on water quality and the ecologic conditions of nearshore areas of the Great Barrier Reef World Heritage Area, Australia. The potential and actual impacts of increased pollutant concentrations range from bioaccumulation of contaminants and decreased photosynthetic capacity to major shifts in community structure and health of mangrove, coral reef, and seagrass ecosystems. A detailed conceptual model underpins and illustrates the links between the main anthropogenic pressures or threats (dry-land cattle grazing and intensive sugar cane cropping) and the production of key contaminants or stressors of Great Barrier Reef water quality. The conceptual model also includes longer-term threats to Great Barrier Reef water quality and ecosystem health, such as global climate change, that will potentially confound direct model interrelationships. The model recognises that system-specific attributes, such as monsoonal wind direction, rainfall intensity, and flood plume residence times, will act as system filters to modify the effects of any water-quality system stressor. The model also summarises key ecosystem responses in ecosystem health that can be monitored through indicators at catchment, riverine, and marine scales. Selected indicators include riverine and marine water quality, inshore coral reef and seagrass status, and biota pollutant burdens. These indicators have been adopted as components of a long-term monitoring program to enable assessment of the effectiveness of change in catchment-management practices in improving Great Barrier Reef (and adjacent catchment) water quality under the Queensland and Australian Governments’ Reef Water Quality Protection Plan.

  15. Using "big data" to optimally model hydrology and water quality across expansive regions

    Science.gov (United States)

    Roehl, E.A.; Cook, J.B.; Conrads, P.A.

    2009-01-01

    This paper describes a new divide and conquer approach that leverages big environmental data, utilizing all available categorical and time-series data without subjectivity, to empirically model hydrologic and water-quality behaviors across expansive regions. The approach decomposes large, intractable problems into smaller ones that are optimally solved; decomposes complex signals into behavioral components that are easier to model with "sub- models"; and employs a sequence of numerically optimizing algorithms that include time-series clustering, nonlinear, multivariate sensitivity analysis and predictive modeling using multi-layer perceptron artificial neural networks, and classification for selecting the best sub-models to make predictions at new sites. This approach has many advantages over traditional modeling approaches, including being faster and less expensive, more comprehensive in its use of available data, and more accurate in representing a system's physical processes. This paper describes the application of the approach to model groundwater levels in Florida, stream temperatures across Western Oregon and Wisconsin, and water depths in the Florida Everglades. ?? 2009 ASCE.

  16. Combined calibration and sensitivity analysis for a water quality model of the Biebrza River, Poland

    NARCIS (Netherlands)

    Perk, van der M.; Bierkens, M.F.P.

    1995-01-01

    A study was performed to quantify the error in results of a water quality model of the Biebrza River, Poland, due to uncertainties in calibrated model parameters. The procedure used in this study combines calibration and sensitivity analysis. Finally,the model was validated to test the model

  17. Watershed boundaries for the U.S. Geological Survey National Water Quality Network

    Science.gov (United States)

    Baker, Nancy T.

    2016-01-01

    The National Water Quality Network (NWQN) for Rivers and Streams includes 113 surface-water river and stream sites monitored by the U.S. Geological Survey (USGS) National Water Quality Program (NWQP). The NWQN represents the consolidation of four historical national networks: the USGS National Water-Quality Assessment (NAWQA) Project, the USGS National Stream Quality Accounting Network (NASQAN), the National Monitoring Network (NMN), and the Hydrologic Benchmark Network (HBN). The NWQN includes 22 large river coastal sites, 41 large river inland sites, 30 wadeable stream reference sites, 10 wadeable stream urban sites, and 10 wadeable stream agricultural sites. In addition to the 113 NWQN sites, 3 large inland river monitoring sites from the USGS Cooperative Matching Funds (Co-op) program are also included in this annual water-quality reporting Web site to be consistent with previous USGS studies of nutrient transport in the Mississippi-Atchafalaya River Basin. This data release contains geo-referenced digital data and associated attributes of watershed boundaries for 113 NWQN and 3 Co-op sites. Two sites, "Wax Lake Outlet at Calumet, LA"; 07381590, and "Lower Atchafalaya River at Morgan City, LA"; 07381600, are outflow distributaries into the Gulf of Mexico. Watershed boundaries were delineated for the portion of the watersheds between "Red River near Alexandria, LA"; 07355500 and "Atchafalaya River at Melville, LA"; 07381495 to the two distributary sites respectively. Drainage area was undetermined for these two distributary sites because the main stream channel outflows into many smaller channels so that streamflow is no longer relative to the watershed area. NWQN watershed boundaries were derived from the Watershed Boundary Dataset-12-digit hydrologic units (WBD-12). The development of the WBD-12 was a coordinated effort between the United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS), the USGS, and the Environmental

  18. Input variable selection and calibration data selection for storm water quality regression models.

    Science.gov (United States)

    Sun, Siao; Bertrand-Krajewski, Jean-Luc

    2013-01-01

    Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

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

    Indian Academy of Sciences (India)

    This paper deals with development of a seasonal fraction-removal policy model for waste load allocation in streams addressing uncertainties due to randomness and fuzziness. A stochastic dynamic programming (SDP) model is developed to arrive at the steady-state seasonal fraction-removal policy. A fuzzy decision model ...

  20. The identifiability of parameters in a water quality model of the Biebrza River, Poland

    NARCIS (Netherlands)

    Perk, van der M.; Bierkens, M.F.P.

    1997-01-01

    The identifiability of model parameters of a steady state water quality model of the Biebrza River and the resulting variation in model results was examined by applying the Monte Carlo method which combines calibration, identifiability analysis, uncertainty analysis, and sensitivity analysis. The

  1. A field test of Root Zone Water Quality Model - pesticide and bromide behavior

    NARCIS (Netherlands)

    Ahuja, L.R.; Ma, Q.L.; Rojas, K.W.; Boesten, J.J.T.I.; Farahani, H.J.

    1996-01-01

    The Root Zone Water Quality Model is a process-based model that integrates physical, chemical and biological processes to simulate the fate and movement of water and agrochemicals over and through the root zone at a representative point in a field with various management practices. The model was

  2. Derivation of a three dimensional numerical water quality model for estuary and continental shelf application

    Science.gov (United States)

    Spaulding, M.

    1973-01-01

    A derivation is given for a three dimensional mass transport equation which is appropriate for numerical modeling of estuary and continental shelf water quality variations for both the time dependent and steady state cases. A finite difference approximation to the derived equation is presented and a solution scheme for the resulting equations outlined. Preliminary results are obtained using the model for the extremely simple problems which have analytical solutions. The numerical model, as presented, will provide a scheme to study water quality problems in coastal waters for both steady state and time dependent cases.

  3. 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

  4. 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

  5. An integrated social and ecological modeling framework - impacts of agricultural conservation practices on water quality

    Directory of Open Access Journals (Sweden)

    Irem Daloğlu

    2014-09-01

    Full Text Available We present a modeling framework that synthesizes social, economic, and ecological aspects of landscape change to evaluate how different agricultural policy and land tenure scenarios and land management preferences affect landscape pattern and downstream water quality. We linked a stylized agent-based model (ABM of farmers' conservation practice adoption decisions with a water quality model, the Soil and Water Assessment Tool (SWAT, to simulate the water quality effects of changing land tenure dynamics and different policies for crop revenue insurance in lieu of commodity payments over 41 years (1970-2010 for a predominantly agricultural watershed of Lake Erie. Results show that non-operator owner involvement in land management decisions yields the highest reduction in sediment and nutrient loads, and crop revenue insurance leads to more homogeneous farmer decisions and a slight increase in sediment and nutrient loads unless cross compliance with expanded conservation requirements is implemented.

  6. A SYSTEM DYNAMICS-BASED CONFLICT RESOLUTION MODEL FOR RIVER WATER QUALITY MANAGEMENT

    Directory of Open Access Journals (Sweden)

    M. Karamouz, M. Akhbari, A. Moridi, R. Kerachian

    2006-07-01

    Full Text Available System dynamics approach by simulating a bargaining process can be used for resolving conflict of interests in water quality management. This approach can be a powerful alternative for traditional approaches for conflict resolution, which often rely on classical game theory. Waste load allocation models for river water quality management determine the optimal monthly waste load allocation to each point load. Most of these approaches are based on the multi-objective optimization models and do not consider the existing conflicts. In this study, a system dynamics-based conflict resolution model is presented for monthly waste load allocation in river systems. In this model, the stakeholders and decision-makers negotiate with each other considering their relative authorities, aspirations and dissatisfactions. System dynamics approach is actually used for simulating the bargaining process among the players. The model incorporates the objectives and preferences of stakeholders and decision-makers of the system in the form of utility functions and could provide a final agreement among the players. To evaluate the spatial and temporal variation of the concentration of the water quality indicator in the system, a water quality simulation model is also linked to the conflict resolution model. In the proposed model, a pre-assigned utility is allocated to different water users and the results are evaluated using a simulation model. The allocated utilities are tested and adjusted in order to provide an agreement between the assumed utilities and the utilities assigned by the model. The proposed model is applied to the Karkheh River system located in the southwest of Iran. The results show that the model can effectively incorporate the preferences of the players in providing a final agreement and the runtime of the proposed model is much less than the classical conflict resolution models. It is also shown that the waste load allocation can significantly reduce

  7. Simulating a thermal water quality trading market for education and model development.

    Science.gov (United States)

    Bier, Asmeret

    2010-12-01

    Thermal water quality trading is an emerging policy tool that allows thermal polluters to comply with effluent restrictions by paying landowners to plant shade trees. A simulation game was created to help participants understand the structure, dynamics, benefits, and drawbacks of thermal water quality trading markets. Simulation participants negotiate to make trades, and their decisions are entered into a system dynamics model that simulates tree growth and water temperature. A debriefing session allows the participants to discuss outcomes and strategies. The exercise has been performed twice and has proven to be a useful teaching tool. These simulations provided valuable insight into decision-making strategies in thermal water quality trading markets, suggesting decision rules that the researchers used for subsequent model development. Copyright © 2010 Elsevier Ltd. All rights reserved.

  8. Modeling and water quality assessment during realisation of the coastal projects in Sochi region (Black sea coast of Russia)

    Science.gov (United States)

    Prokhoda-Shumskikh, L.

    2012-04-01

    Sochi region is the unique subtropical resort on the Black Sea coast of Russia. Nowadays due to Sochi is the capital of the Olympic game 2014, the government of the Russian Federation accepts the special federal program of Black Sea coast development. Program foresees the existing and creation of new coastal recreational and touristic complexes along the Russian Black Sea coast, such as complex of yacht harbors, water centers (aqua-centers), network of port localities and etc. These coastal projects are different, but the main problems of the environmental impact assessment are the same. The environmental impact and the relative damage should be assessed at the stage of construction as well as at the stage of operation. The key problem for the recreation coastal zone is water quality management. The port localities network as example is considered. To increase the accuracy and informative of forecasts for the coastal zone conditions the system-dynamic model has been developed, what allows to estimate the quality of the sea water, including that in the semi-enclosed coastal water areas with the limited water exchange. The model of water quality in the coastal zone includes the equations of deposit concentration changes and chemical substances evolution in the studied areas. The model incorporates joint description of cycles of two biogenic elements - nitrogen and phosphorus. The system is completely defined by the biogeochemical reactions. The sizes of such water areas allow the applying the full mixing and zero-dimensional models of water quality. The circulation of water inside the area is taken into account additionally. Water exchange in the semi-enclosed coastal water areas is defined by the discharge through the open parts of area border. The novelty of the offered model is its adaptation to the specific conditions of semi-enclosed coastal water areas. At the same time, the model contains details of the biogeochemical processes to complete modelling of the

  9. Integrated River and Coastal Flow, Sediment and Escherichia coli Modelling for Bathing Water Quality

    Directory of Open Access Journals (Sweden)

    Guoxian Huang

    2015-09-01

    Full Text Available Due to the increasing economic and cultural value of bathing waters and the shellfish industry in the UK and worldwide, water quality in estuarine and coastal waters has attracted considerable public attention in recent years. To obtain accurate predictions of the concentration distributions of faecal indicator organisms (FIOs in coastal waters for better management of bathing water compliance, it is necessary to build an integrated modelling system to predict the complete diffuse and point source inputs from river and catchment basins. In the present paper, details are given of the development of such an integrated modelling system for simulating the transport and decay processes of FIOs, from catchment areas upstream from the coastal region, in which a distributed catchment module, a 1D river network module and a 2D estuarine and coastal module are linked dynamically by boundary inputs and outputs. Extensive measured data from the catchments, river networks and estuaries have been collated to determine the model parameters. Verification results of the distribution of water levels, flows and velocities, and suspended sediment and Escherichia coli concentrations, at controlled monitoring sites are presented, which show that the integrated model predictions generally agree well with the measurements, although locally appreciable errors can occur. The model results also highlight the importance of including the flux of FIOs via sediments being an important factor in terms of assessing the quality of bathing waters. The main factors influencing the relatively high concentration values in the bathing region are analysed, based on the model predictions and measured data, with four categories of FIO concentration levels being reviewed.

  10. 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

  11. River water quality model no. 1 (RWQM1): III. Biochemical submodel selection

    DEFF Research Database (Denmark)

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

    2001-01-01

    The new River Water Quality Model no.1 introduced in the two accompanying papers by Shanahan et al. and Reichert et al. is comprehensive. Shanahan et al. introduced a six-step decision procedure to select the necessary model features for a certain application. This paper specifically addresses on...

  12. 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

  13. Uncertainty considerations in calibration and validation of hydrologic and water quality models

    Science.gov (United States)

    Hydrologic and water quality models (HWQMs) are increasingly used to support decisions on the state of various environmental issues and policy directions on present and future scenarios, at scales varying from watershed to continental levels. Uncertainty associated with such models may impact the ca...

  14. Three-dimensional numerical modeling of water quality and sediment-associated processes in natural lakes

    Science.gov (United States)

    This chapter presents the development and application of a three-dimensional water quality model for predicting the distributions of nutrients, phytoplankton, dissolved oxygen, etc., in natural lakes. In this model, the computational domain was divided into two parts: the water column and the bed se...

  15. 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

  16. Hydrologic and water quality models: Key calibration and validation topics

    Science.gov (United States)

    As a continuation of efforts to provide a common background and platform for accordant development of calibration and validation (C/V) engineering practices, ASABE members worked to determine critical topics related to model C/V, perform a synthesis of the Moriasi et al. (2012) special collection of...

  17. Hydrodynamic And Water Quality Surrogate Modeling For Reservoir Operation

    NARCIS (Netherlands)

    Aguilar Lopez, J.P.; Andel, Schalk Jan Van; Werner, M; Solomatine, D.P.; Piasecki, M

    2014-01-01

    Data for water management is increasingly easy to access, it has finer spatial and temporal resolution, and it is available from various sources. Precipitation data can be obtained from meteorological stations, radar, satellites and weather models. Land use data is also available from different

  18. Integrated hydrological and water quality model for river management: a case study on Lena River.

    Science.gov (United States)

    Fonseca, André; Botelho, Cidália; Boaventura, Rui A R; Vilar, Vítor J P

    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(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. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. 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.

  20. River water quality modelling under drought situations - the Turia River case

    Science.gov (United States)

    Paredes-Arquiola, Javier; Macián, Javier; Pedro-Monzonís, María; Belda, Edgar; Momblanch, Andrea; Andreu, Joaquín

    2016-10-01

    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.

  1. 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

  2. Uncertainty analysis for complex watershed water quality models: the parameter identifiability problem

    Science.gov (United States)

    Han, F.; Zheng, Y.

    2012-12-01

    Watershed-scale water quality simulation using distributed models like the Soil and Water Assessment Tool (SWAT) usually involves significant uncertainty. The uncertainty needs to be appropriately quantified if the simulation is used to support management practices. Many uncertainty analysis (UA) approaches have been developed for watershed hydrologic models, but their applicability to watershed water quality models, which are more complex, has not been well investigated. This study applied a Markov chain Monte Carlo (MCMC) approach, DiffeRential Evolution Adaptive Metropolis algorithm (DREAM), to the SWAT model. The sediment and total nitrogen pollution in the Newport Bay watershed (Southern California) was used as a case study. Different error assumptions were tested. The major findings include: 1) in the water quality simulation, many parameters are non-identifiable due to different causes; 2) the existence of identifiability seriously reduces the efficiency of the MCMC algorithm, and distorts the posterior distributions of the non-identifiable parameters, although the uncertainty band produced by the algorithm does not change much if enough samples are obtained. It was concluded that a sensitivity analysis (SA) followed by an identifiability analysis is necessary to reduce the non-identifiability, and enhances the applicability of a Bayesian UA approach to complex watershed water quality models. In addition, the analysis on the different causes of non-identifiablity provides insights into model tradeoffs between complexity and performance.

  3. A Hybrid Prediction Model for Monitoring of River Water Quality in the USN System

    OpenAIRE

    Hoontae Kim; Minsoo Kim

    2015-01-01

    River water quality is directly related to the wellness of its neighbors. Because the West Nakdong River has long suffered both from the infiltration of sea water and from the inflow of turbid wastewater, inconsiderate use of this water can cause disastrous result to nearby agricultural areas and neighbors. Busan city in Korea had deployed a pilot USN (ubiquitous sensor network) system that monitors this river and nearby tube wells to properly react to those situations. In this paper, we have...

  4. The spatial structure and temporal synchrony of water quality in stream networks

    Science.gov (United States)

    Abbott, Benjamin; Gruau, Gerard; Zarneske, Jay; Barbe, Lou; Gu, Sen; Kolbe, Tamara; Thomas, Zahra; Jaffrezic, Anne; Moatar, Florentina; Pinay, Gilles

    2017-04-01

    To feed nine billion people in 2050 while maintaining viable aquatic ecosystems will require an understanding of nutrient pollution dynamics throughout stream networks. Most regulatory frameworks such as the European Water Framework Directive and U.S. Clean Water Act, focus on nutrient concentrations in medium to large rivers. This strategy is appealing because large rivers integrate many small catchments and total nutrient loads drive eutrophication in estuarine and oceanic ecosystems. However, there is growing evidence that to understand and reduce downstream nutrient fluxes we need to look upstream. While headwater streams receive the bulk of nutrients in river networks, the relationship between land cover and nutrient flux often breaks down for small catchments, representing an important ecological unknown since 90% of global stream length occurs in catchments smaller than 15 km2. Though continuous monitoring of thousands of small streams is not feasible, what if we could learn what we needed about where and when to implement monitoring and conservation efforts with periodic sampling of headwater catchments? To address this question we performed repeat synoptic sampling of 56 nested catchments ranging in size from 1 to 370 km2 in western France. Spatial variability in carbon and nutrient concentrations decreased non-linearly as catchment size increased, with thresholds in variance for organic carbon and nutrients occurring between 36 and 68 km2. While it is widely held that temporal variance is higher in smaller streams, we observed consistent temporal variance across spatial scales and the ranking of catchments based on water quality showed strong synchrony in the water chemistry response to seasonal variation and hydrological events. We used these observations to develop two simple management frameworks. The subcatchment leverage concept proposes that mitigation and restoration efforts are more likely to succeed when implemented at spatial scales expressing

  5. 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.

  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 ...

  7. 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

  8. 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...

  9. Assessing the radar rainfall estimates in watershed-scale water quality model

    Science.gov (United States)

    Watershed-scale water quality models are effective science-based tools for interpreting change in complex environmental systems that affect hydrology cycle, soil erosion and nutrient fate and transport in watershed. Precipitation is one of the primary input data to achieve a precise rainfall-runoff ...

  10. 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,…

  11. Development of an Interactive Computer-Based Learning Strategy to Assist in Teaching Water Quality Modelling

    Science.gov (United States)

    Zigic, Sasha; Lemckert, Charles J.

    2007-01-01

    The following paper presents a computer-based learning strategy to assist in introducing and teaching water quality modelling to undergraduate civil engineering students. As part of the learning strategy, an interactive computer-based instructional (CBI) aid was specifically developed to assist students to set up, run and analyse the output from a…

  12. Corn stover harvest increases herbicide movement to subsurface drains – Root Zone Water Quality Model simulations

    Science.gov (United States)

    BACKGROUND: Removal of crop residues for bioenergy production can alter soil hydrologic properties, but there is little information on its impact on transport of herbicides and their degradation products to subsurface drains. The Root Zone Water Quality Model, previously calibrated using measured fl...

  13. 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

  14. EUTROPHICATION MODELING CAPABILITIES FOR WATER QUALITY AND INTEGRATION TOWARDS ECOLOGICAL ENDPOINTS

    Science.gov (United States)

    A primary environmental focus for the use of mathematical models is for characterization of sources of nutrients and sediments and their relative loadings from large river basins, and the impact of land uses from smaller sub-basins on water quality in rivers, lakes, and estuaries...

  15. 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...

  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. 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.

  19. A neural network approach to smarter sensor networks for water quality monitoring.

    Science.gov (United States)

    O'Connor, Edel; Smeaton, Alan F; O'Connor, Noel E; Regan, Fiona

    2012-01-01

    Environmental monitoring is evolving towards large-scale and low-cost sensor networks operating reliability and autonomously over extended periods of time. Sophisticated analytical instrumentation such as chemo-bio sensors present inherent limitations because of the number of samples that they can take. In order to maximize their deployment lifetime, we propose the coordination of multiple heterogeneous information sources. We use rainfall radar images and information from a water depth sensor as input to a neural network (NN) to dictate the sampling frequency of a phosphate analyzer at the River Lee in Cork, Ireland. This approach shows varied performance for different times of the year but overall produces output that is very satisfactory for the application context in question. Our study demonstrates that even with limited training data, a system for controlling the sampling rate of the nutrient sensor can be set up and can improve the efficiency of the more sophisticated nodes of the sensor network.

  20. 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

  1. Empirical Modeling of Stream Water Quality for Complex Coastal-Urban Watersheds

    Science.gov (United States)

    Al-Amin, S.; Abdul-Aziz, O.

    2013-12-01

    This study develops an understanding of the relative influence of land uses, surface hydrology, groundwater, seawater, and upstream contributions on the in-stream water quality of six highly urbanized, complex urban watersheds of South Florida by analyzing seasonal (Winter, Spring, Summer, and Fall) time-series of field data. We first explored the correlations among quality parameters (i.e., total nitrogen, total phosphorus, dissolved oxygen and specific conductance) and their changes with distance and time. Principle component analysis was then conducted to investigate the mutual correlations and potential group formations among the predictor and response variables. The findings were leveraged to develop regression-based non-linear empirical models for explaining stream water quality in relation to internal (land uses and hydrology) and external (upstream contribution, seawater) sources and drivers. In-stream dissolved oxygen and total phosphorus in the watersheds were dictated by internal stressors, while external stressors were dominant for total nitrogen and specific conductance. The research findings provide important insights into the dominant stressors of seasonal stream water quality of complex coastal-urban watersheds under a changing environment. The research tools will be useful for developing proactive monitoring and seasonally exclusive management strategies for urban stream water quality improvement in South Florida and around the world.

  2. 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.

  3. Quantifying Spatial Changes in the Structure of Water Quality Constituents in a Large Prairie River within Two Frameworks of a Water Quality Model

    Directory of Open Access Journals (Sweden)

    Nasim Hosseini

    2016-04-01

    Full Text Available A global sensitivity analysis was carried out on a water quality model to quantify the spatial changes in parameter sensitivity of a model of a large prairie river, the South Saskatchewan River (SSR. The method is used to assess the relative impacts of major nutrient loading sources and a reservoir on the river’s water quality. The river completely freezes over during winter; hence, the sensitivity analysis was carried out seasonally, for winter and summer, to account for the influence of ice-covered conditions on nutrient transformations. Furthermore, the integrity of the river’s aquatic ecosystem was examined through the inter-relationship between variables and comparing hierarchy index values and water quality indices at four locations along the river. Sensitivities of model parameters varied slightly at different locations along the river, with the phytoplankton growth rate being the most influential parameter. Nitrogen and phosphorus transformation processes were more sensitive in winter, while chlorophyll-a and dissolved oxygen parameters showed higher sensitivity in summer. A more complicated correlation between variables was observed downstream of the junction of the Red Deer River. Our results reveal that the lower correlation between variables may suggest a more balanced and healthier system, although further analysis is needed to support this statement.

  4. Use of surrogate indicators for the evaluation of potential health risks due to poor urban water quality: A Bayesian Network approach.

    Science.gov (United States)

    Wijesiri, Buddhi; Deilami, Kaveh; McGree, James; Goonetilleke, Ashantha

    2018-02-01

    Urban water pollution poses risks of waterborne infectious diseases. Therefore, in order to improve urban liveability, effective pollution mitigation strategies are required underpinned by predictions generated using water quality models. However, the lack of reliability in current modelling practices detrimentally impacts planning and management decision making. This research study adopted a novel approach in the form of Bayesian Networks to model urban water quality to better investigate the factors that influence risks to human health. The application of Bayesian Networks was found to enhance the integration of quantitative and qualitative spatially distributed data for analysing the influence of environmental and anthropogenic factors using three surrogate indicators of human health risk, namely, turbidity, total nitrogen and fats/oils. Expert knowledge was found to be of critical importance in assessing the interdependent relationships between health risk indicators and influential factors. The spatial variability maps of health risk indicators developed enabled the initial identification of high risk areas in which flooding was found to be the most significant influential factor in relation to human health risk. Surprisingly, population density was found to be less significant in influencing health risk indicators. These high risk areas in turn can be subjected to more in-depth investigations instead of the entire region, saving time and resources. It was evident that decision making in relation to the design of pollution mitigation strategies needs to account for the impact of landscape characteristics on water quality, which can be related to risk to human health. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. 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...

  6. 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

    2013-01-01

    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, BOD c , organic nitrogen (N o , ammonia nitrogen (N a , nitrite (N i , nitrate (N n , organic and inorganic phosphorus (F o and F i , 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.

  7. 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.

  8. Testing the Transferability of Hydrological Water Quality Model between two Catchments in Central Germany

    Science.gov (United States)

    Jomaa, S.; Jiang, S.; Rode, M.

    2013-12-01

    Several indications showed that changes in land use/cover can influence the hydrological regimes and in consequence river water quality. Hydrological water quality modelling has proven to be an efficient tool to predict how the changes in land cover can affect the discharge of river catchment and its water quality (such as nitrogen and phosphorus) using different land use scenarios. The aim of this study was to test the tranferability of a hydrological water quality model between two catchments with different physiographical charcatctreristics. The HYPE model (HYdrological Predictions for the Environment) was setup in two mesoscale catchments in central Germany. The selected catchments are Selke (463 km2) and Weida (99.5 km2), which are two small tributaries of Elbe river basin and are located in Saxony-Anhalt and Thuringian states, respectively. The predominant land use classes of the Selke catchment are arable land (≈ 50%) located mainly in the lowland area and forest (35%), which is situated in low montain area. Howover, the dominating land use classes of the Weida catchment are agricultural land (40%), forest (29%) and grassland (26%), which are all located in low-montain range (elevation between 357-552m). First, The HYPE model was setup for the Selke catchment. Second, the model was used to predict the measured discharge and nutrient concentration of the Weida catchment using the same corresponding optimized paramter values obtained from calibration in the Selke catchment. Therefore, the feasability of HYPE model-parameter transferability between catchments with different physiographic characteristics and new regionalization schemes were investigated. The HYPE model was then used to predict the impact of different bionergy scanarios on the river discharge and nutrient emission. The preliminary results of this study will be presented and discussed.

  9. 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.

  10. 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

  11. 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

  12. 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.

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

    OpenAIRE

    Youn Shik Park; Bernie A. Engel

    2016-01-01

    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 ...

  14. 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

  15. 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....../or an incomplete formulation of the involved varied processes. But in this introduction to a debate it is argued that the explanation usually lies in the high complexity of the models in relation to the limited data available for the calibration of model constants. Two examples are given....

  16. Applying high-frequency surrogate measurements and a wavelet-ANN model to provide early warnings of rapid surface water quality anomalies.

    Science.gov (United States)

    Shi, Bin; Wang, Peng; Jiang, Jiping; Liu, Rentao

    2018-01-01

    It is critical for surface water management systems to provide early warnings of abrupt, large variations in water quality, which likely indicate the occurrence of spill incidents. In this study, a combined approach integrating a wavelet artificial neural network (wavelet-ANN) model and high-frequency surrogate measurements is proposed as a method of water quality anomaly detection and warning provision. High-frequency time series of major water quality indexes (TN, TP, COD, etc.) were produced via a regression-based surrogate model. After wavelet decomposition and denoising, a low-frequency signal was imported into a back-propagation neural network for one-step prediction to identify the major features of water quality variations. The precisely trained site-specific wavelet-ANN outputs the time series of residual errors. A warning is triggered when the actual residual error exceeds a given threshold, i.e., baseline pattern, estimated based on long-term water quality variations. A case study based on the monitoring program applied to the Potomac River Basin in Virginia, USA, was conducted. The integrated approach successfully identified two anomaly events of TP variations at a 15-minute scale from high-frequency online sensors. A storm event and point source inputs likely accounted for these events. The results show that the wavelet-ANN model is slightly more accurate than the ANN for high-frequency surface water quality prediction, and it meets the requirements of anomaly detection. Analyses of the performance at different stations and over different periods illustrated the stability of the proposed method. By combining monitoring instruments and surrogate measures, the presented approach can support timely anomaly identification and be applied to urban aquatic environments for watershed management. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. [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.

  18. On the value of water quality data and informative flow states in karst modelling

    Science.gov (United States)

    Hartmann, Andreas; Barberá, Juan Antonio; Andreo, Bartolomé

    2017-11-01

    If properly applied, karst hydrological models are a valuable tool for karst water resource management. If they are able to reproduce the relevant flow and storage processes of a karst system, they can be used for prediction of water resource availability when climate or land use are expected to change. A common challenge to apply karst simulation models is the limited availability of observations to identify their model parameters. In this study, we quantify the value of information when water quality data (NO3- and SO42-) is used in addition to discharge observations to estimate the parameters of a process-based karst simulation model at a test site in southern Spain. We use a three-step procedure to (1) confine an initial sample of 500 000 model parameter sets by discharge and water quality observations, (2) identify alterations of model parameter distributions through the confinement, and (3) quantify the strength of the confinement for the model parameters. We repeat this procedure for flow states, for which the system discharge is controlled by the unsaturated zone, the saturated zone, and the entire time period including times when the spring is influenced by a nearby river. Our results indicate that NO3- provides the most information to identify the model parameters controlling soil and epikarst dynamics during the unsaturated flow state. During the saturated flow state, SO42- and discharge observations provide the best information to identify the model parameters related to groundwater processes. We found reduced parameter identifiability when the entire time period is used as the river influence disturbs parameter estimation. We finally show that most reliable simulations are obtained when a combination of discharge and water quality date is used for the combined unsaturated and saturated flow states.

  19. 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

  20. 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.

  1. Temporal evolution modeling of hydraulic and water quality performance of permeable pavements

    Science.gov (United States)

    Huang, Jian; He, Jianxun; Valeo, Caterina; Chu, Angus

    2016-02-01

    A mathematical model for predicting hydraulic and water quality performance in both the short- and long-term is proposed based on field measurements for three types of permeable pavements: porous asphalt (PA), porous concrete (PC), and permeable inter-locking concrete pavers (PICP). The model was applied to three field-scale test sites in Calgary, Alberta, Canada. The model performance was assessed in terms of hydraulic parameters including time to peak, peak flow and water balance and a water quality variable (the removal rate of total suspended solids). A total of 20 simulated storm events were used for model calibration and verification processes. The proposed model can simulate the outflow hydrographs with a coefficient of determination (R2) ranging from 0.762 to 0.907, and normalized root-mean-square deviation (NRMSD) ranging from 13.78% to 17.83%. Comparison of the time to peak flow, peak flow, runoff volume and TSS removal rates between the measured and modeled values in model verification phase had a maximum difference of 11%. The results demonstrate that the proposed model is capable of capturing the temporal dynamics of the pavement performance. Therefore, the model has great potential as a practical modeling tool for permeable pavement design and performance assessment.

  2. 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

  3. Evaluation of water quality parameters for the Mamasin dam in Aksaray City in the central Anatolian part of Turkey by means of artificial neural networks

    Science.gov (United States)

    Elhatip, Hatim; Kömür, M. Aydin

    2008-01-01

    Sustaining the human ecological benefits of surface water requires carefully planned strategies for reducing the cumulative risks posed by diverse human activities. The municipality of Aksaray city plays a key role in developing solutions to surface water management and protection in the central Anatolian part of Turkey. The responsibility to provide drinking water and sewage works, regulate the use of private land and protect public health provides the mandate and authority to take action. The present approach discusses the main sources of contamination and the result of direct wastewater discharges into the Melendiz and Karasu rivers, which recharge the Mamasın dam sites by the use of artificial neural network (ANN) modeling techniques. The present study illustrates the ability to predict and/or approve the output values of previously measured water quality parameters of the recharge and discharge areas at the Mamasin dam site by means of ANN techniques. Using the ANN model is appreciated in such environmental research. Here, the ANN is used for estimating if the field parameters are agreeable to the results of this model or not. The present study simulates a situation in the past by means of ANN. But in case any field measurements of some relative parameters at the outlet point “discharge area” have been missed, it could be possible to predict the approximate output values from the detailed periodical water quality parameters. Because of the high variance and the inherent non-linear relationship of the water quality parameters in time series, it is difficult to produce a reliable model with conventional modeling approaches. In this paper, the ANN modeling technique is used to establish a model for evaluating the change in electrical conductivity (EC) and dissolved oxygen (DO) values in recharge (input) and discharge (output) areas of the dam water under pollution risks. A general ANN modeling scheme is also recommended for the water parameters. The modeling

  4. Applying global sensitivity analysis to the modelling of flow and water quality in sewers.

    Science.gov (United States)

    Gamerith, Valentin; Neumann, Marc B; Muschalla, Dirk

    2013-09-01

    While several approaches for global sensitivity analysis (GSA) have been proposed in literature, only few applications exist in urban drainage modelling. This contribution discusses two GSA methods applied to a sewer flow and sewer water quality model: Standardised Regression Coefficients (SRCs) using Monte-Carlo simulation as well as the Morris Screening method. For selected model variables we evaluate how the sensitivities are influenced by the choice of the rainfall event. The aims are to i) compare both methods concerning the similarity of results and their applicability, ii) discuss the implications for factor fixing (identifying non-influential parameters) and factor prioritisation (identifying important parameters) and iii) rank the important parameters for the investigated model. It was shown that both methods lead to similar results for the hydraulic model. Parameter interactions and non-linearity were identified for the water quality model and the parameter ranking differs between the methods. For the investigated model the results allow a sound choice of output variables and rainfall events in view of detailed uncertainty analysis or model calibration. We advocate the simultaneous use of both methods for a first model assessment as they allow answering both factor fixing and factor prioritisation at low computational cost. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. An empirical model of water quality for use in rapid management strategy evaluation in Southeast Queensland, Australia.

    Science.gov (United States)

    de la Mare, William; Ellis, Nick; Pascual, Ricardo; Tickell, Sharon

    2012-04-01

    Simulation models have been widely adopted in fisheries for management strategy evaluation (MSE). However, in catchment management of water quality, MSE is hampered by the complexity of both decision space and the hydrological process models. Empirical models based on monitoring data provide a feasible alternative to process models; they run much faster and, by conditioning on data, they can simulate realistic responses to management actions. Using 10 years of water quality indicators from Queensland, Australia, we built an empirical model suitable for rapid MSE that reproduces the water quality variables' mean and covariance structure, adjusts the expected indicators through local management effects, and propagates effects downstream by capturing inter-site regression relationships. Empirical models enable managers to search the space of possible strategies using rapid assessment. They provide not only realistic responses in water quality indicators but also variability in those indicators, allowing managers to assess strategies in an uncertain world. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Selection of relevant input variables in storm water quality modeling by multiobjective evolutionary polynomial regression paradigm

    Science.gov (United States)

    Creaco, E.; Berardi, L.; Sun, Siao; Giustolisi, O.; Savic, D.

    2016-04-01

    The growing availability of field data, from information and communication technologies (ICTs) in "smart" urban infrastructures, allows data modeling to understand complex phenomena and to support management decisions. Among the analyzed phenomena, those related to storm water quality modeling have recently been gaining interest in the scientific literature. Nonetheless, the large amount of available data poses the problem of selecting relevant variables to describe a phenomenon and enable robust data modeling. This paper presents a procedure for the selection of relevant input variables using the multiobjective evolutionary polynomial regression (EPR-MOGA) paradigm. The procedure is based on scrutinizing the explanatory variables that appear inside the set of EPR-MOGA symbolic model expressions of increasing complexity and goodness of fit to target output. The strategy also enables the selection to be validated by engineering judgement. In such context, the multiple case study extension of EPR-MOGA, called MCS-EPR-MOGA, is adopted. The application of the proposed procedure to modeling storm water quality parameters in two French catchments shows that it was able to significantly reduce the number of explanatory variables for successive analyses. Finally, the EPR-MOGA models obtained after the input selection are compared with those obtained by using the same technique without benefitting from input selection and with those obtained in previous works where other data-modeling techniques were used on the same data. The comparison highlights the effectiveness of both EPR-MOGA and the input selection procedure.

  7. Model design for predicting extreme precipitation event impacts on water quality in a water supply reservoir

    Science.gov (United States)

    Hagemann, M.; Jeznach, L. C.; Park, M. H.; Tobiason, J. E.

    2016-12-01

    Extreme precipitation events such as tropical storms and hurricanes are by their nature rare, yet have disproportionate and adverse effects on surface water quality. In the context of drinking water reservoirs, common concerns of such events include increased erosion and sediment transport and influx of natural organic matter and nutrients. As part of an effort to model the effects of an extreme precipitation event on water quality at the reservoir intake of a major municipal water system, this study sought to estimate extreme-event watershed responses including streamflow and exports of nutrients and organic matter for use as inputs to a 2-D hydrodynamic and water quality reservoir model. Since extreme-event watershed exports are highly uncertain, we characterized and propagated predictive uncertainty using a quasi-Monte Carlo approach to generate reservoir model inputs. Three storm precipitation depths—corresponding to recurrence intervals of 5, 50, and 100 years—were converted to streamflow in each of 9 tributaries by volumetrically scaling 2 storm hydrographs from the historical record. Rating-curve models for concentratoin, calibrated using 10 years of data for each of 5 constituents, were then used to estimate the parameters of a multivariate lognormal probability model of constituent concentrations, conditional on each scenario's storm date and streamflow. A quasi-random Halton sequence (n = 100) was drawn from the conditional distribution for each event scenario, and used to generate input files to a calibrated CE-QUAL-W2 reservoir model. The resulting simulated concentrations at the reservoir's drinking water intake constitute a low-discrepancy sample from the estimated uncertainty space of extreme-event source water-quality. Limiting factors to the suitability of this approach include poorly constrained relationships between hydrology and constituent concentrations, a high-dimensional space from which to generate inputs, and relatively long run

  8. 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.

  9. 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.

  10. 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

  11. Improved first-order uncertainty method for water-quality modeling

    Science.gov (United States)

    Melching, C.S.; Anmangandla, S.

    1992-01-01

    Uncertainties are unavoidable in water-quality modeling and subsequent management decisions. Monte Carlo simulation and first-order uncertainty analysis (involving linearization at central values of the uncertain variables) have been frequently used to estimate probability distributions for water-quality model output due to their simplicity. Each method has its drawbacks: Monte Carlo simulation's is mainly computational time; and first-order analysis are mainly questions of accuracy and representativeness, especially for nonlinear systems and extreme conditions. An improved (advanced) first-order method is presented, where the linearization point varies to match the output level whose exceedance probability is sought. The advanced first-order method is tested on the Streeter-Phelps equation to estimate the probability distribution of critical dissolved-oxygen deficit and critical dissolved oxygen using two hypothetical examples from the literature. The advanced first-order method provides a close approximation of the exceedance probability for the Streeter-Phelps model output estimated by Monte Carlo simulation using less computer time - by two orders of magnitude - regardless of the probability distributions assumed for the uncertain model parameters.

  12. Wet weather water quality modelling of a Portuguese urban catchment: difficulties and benefits.

    Science.gov (United States)

    David, L M; Matos, R S

    2002-01-01

    This paper discusses the use of water quality deterministic modelling together with an integrated approach to assess the impact of urban stormwater discharges into ephemeral watercourses, based on the study of a Portuguese catchment. The description of the main aspects, difficulties and benefits found during data collection and model calibration and verification is presented, and the associated uncertainties and errors discussed. Experimental results showed a strong short- and long-term impact of sewer discharges on rivers, and confirmed deposition, resuspension and transport of pollutants as important processes for the water quality. However, the resuspension of riverbed sediment pollutants during storms was probably more significant than the direct impact of the urban discharges. The HydroWorks model was used since it allows for the calculation of pollutant build-up on catchment surfaces and in gully pots, their wash-off, and the deposition and erosion of sediments in sewers. However, it uses several constants, which could not be independently calibrated, increasing the uncertainty already associated with the data. River flows have quite different magnitude from the sewer system overflows, which, together with the difficulties in evaluating river flow rates, makes the integrated modelling approach rather complex and costly.

  13. Modeling Water-Quality Loads to the Reservoirs of the Upper Trinity River Basin, Texas, USA

    Directory of Open Access Journals (Sweden)

    Taesoo Lee

    2015-10-01

    Full Text Available The Upper Trinity River Basin (TRB is the most populated river basin and one of the largest water suppliers in Texas. However, sediment and nutrient loads are reducing the capacity of reservoirs and degrading water quality. The objectives of this study are to calibrate and validate the Soil and Water Assessment Tool (SWAT model for ten study watersheds within the Upper TRB in order to assess nutrient loads into major reservoirs in the basin and to predict the effects of point source elimination and urbanization on nutrient loads through scenario analyses. SWAT performed reasonably well for the current condition except for two out of five tributaries in the Eagle Mountain watershed and total phosphorous OPEN ACCESS Water 2015, 7 5690 in Richland-Chambers. The impacts of simulated scenarios varied within watersheds. Point-source elimination achieved reductions ranging from 0.3% to 24% in total phosphorus and 1% to 56% in total nitrogen received by the reservoirs. Population and development projections were used to examine the impacts of urbanization on each watershed. Projected urbanization in 2030 had large effects on simulated total phosphorus loads in some watersheds, ranging from a reduction of 1% to an increase of 111%. Projected urbanization also affected simulated total nitrogen loads, from a reduction of 3% to an increase of 24%. One limitation of this study is the lack of long-term, up-to-date water quality data due to discontinued water-quality monitoring stations. Although careful considerations were given to the adjustment of parameter values reflecting various aspects of the nutrient processes, further data collection will enhance modeling study for assessment of these watersheds’ water resources and environmental problem.

  14. Expert advisor for the QUAL2E water-quality model

    Energy Technology Data Exchange (ETDEWEB)

    Barnwell, T.O.; Brown, L.C.; Marek, W.

    1987-12-01

    Computer modeling is becoming an integral part of decision making in water-pollution control. Problems increasingly involve complex interactions among elements of the environment and large, multi-media modeling systems must be built to understand these interactions. Expert systems is an innovative methodology that can assist in building, using, and interpreting the output of these models. The paper reviews the use and evaluates the potential of expert systems technology in environmental modeling and describes elements of an expert advisor for the stream water-quality model QUAL2E. QUAL2E has a long history of use both in the United States and worldwide and is a proven, effective modeling tool for analyzing the dissolved oxygen balance in a stream or river. Because of the widespread usage, a body of experience and empirical knowledge about the computer program has been gained that is ideal for codification in an expert system.

  15. Predicting water quality at Santa Monica Beach: evaluation of five different models for public notification of unsafe swimming conditions.

    Science.gov (United States)

    Thoe, W; Gold, M; Griesbach, A; Grimmer, M; Taggart, M L; Boehm, A B

    2014-12-15

    Bathing beaches are monitored for fecal indicator bacteria (FIB) to protect swimmers from unsafe conditions. However, FIB assays take ∼24 h and water quality conditions can change dramatically in that time, so unsafe conditions cannot presently be identified in a timely manner. Statistical, data-driven predictive models use information on environmental conditions (i.e., rainfall, turbidity) to provide nowcasts of FIB concentrations. Their ability to predict real time FIB concentrations can make them more accurate at identifying unsafe conditions than the current method of using day or older FIB measurements. Predictive models are used in the Great Lakes, Hong Kong, and Scotland for beach management, but they are presently not used in California - the location of some of the world's most popular beaches. California beaches are unique as point source pollution has generally been mitigated, the summer bathing season receives little to no rainfall, and in situ measurements of turbidity and salinity are not readily available. These characteristics may make modeling FIB difficult, as many current FIB models rely heavily on rainfall or salinity. The current study investigates the potential for FIB models to predict water quality at a quintessential California Beach: Santa Monica Beach. This study compares the performance of five predictive models, multiple linear regression model, binary logistic regression model, partial least square regression model, artificial neural network, and classification tree, to predict concentrations of summertime fecal coliform and enterococci concentrations. Past measurements of bacterial concentration, storm drain condition, and tide level are found to be critical factors in the predictive models. The models perform better than the current beach management method. The classification tree models perform the best; for example they correctly predict 42% of beach postings due to fecal coliform exceedances during model validation, as compared

  16. 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.

  17. 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.

  18. Automatic buffer capacity model building for the purpose of water quality monitoring.

    Science.gov (United States)

    Van Vooren, L; Van de Steene, M; Ottoy, J P; Vanrolleghem, P A

    2001-01-01

    In this paper, buffer capacity profiles are used in the framework of automatic monitoring of water quality. The aim of the proposed methodology is to automatically and stepwise build buffer capacity models for each particular titrated sample, and to quantify the individual buffer systems that constitute the total buffer capacity. An automatic and robust model building algorithm has been developed and applied to many titration curves of effluent and river water samples. It is illustrated that the application of automatically built buffer capacity models mostly results in similar or better estimations of ammonium and ortho-phosphate in the samples compared to a priori fixed buffer capacity models. The automatic modelling approach is also advantageous for alarm generating purposes on e.g. river waters, because unexpected buffers are easily detected.

  19. National level water quality simulation and climate change scenarios in Finland with WSFS-Vemala model

    Science.gov (United States)

    Huttunen, M.; Huttunen, I.; Seppänen, V.; Vehviläinen, B.

    2012-04-01

    WSFS-Vemala model have been developed for water quality simulation and scenarios for Finland. The model consists of sub-models for hydrological cycle, nutrient leaching and transport in rivers and lakes. Simulation of total phosphorus, total nitrogen, suspended solids and total organic carbon is included. Hydrological simulation is based on WSFS system, which simulates the hydrological cycle by one day time step using standard meteorological data. The system covers the whole land area of Finland, including cross-border watersheds, total of 390 000 km2. The meteorological inputs of the model are daily precipitation and temperature and the simulated components are snow accumulation and melt, soil moisture, evaporation, ground water, runoff and discharges and water levels of rivers and lakes. The remote sensing data used in the model includes satellite data of snow coverage and snow water equivalent and precipitation from weather radars. In the hydrological simulation Finland is divided into 6200 50-100 km2 sub-basin. All lakes larger than one hectar are simulated, which is about 58 000 lakes. The large number of lakes is characteristics for Finland and especially for water quality simulation the lake processes are important and therefore all lakes are included. Since agriculture is the main source of nutrient loading, fields are described in detail. Slope profile, crop and soil type data for each 1 100 000 fields in Finland are described, which covers 2 450 000 hectares of fields. For phosphorus leaching and erosion simulation the field level Icecream model is applied. In the Icecream model farming practicies, fertilization, crop growth, phosphorus cycle in the soil and finally leaching and erosion are simulated on daily timestep. For nitrogen simulation in fields a similar process based model is applied on sub-basin level and field scale nitrogen simulation with Icecream model is under development. Point loads, atmospheric deposition and load from settlements are

  20. Assessment of uncertainty sources in water quality modeling in the Niagara River

    Science.gov (United States)

    Franceschini, Samuela; Tsai, Christina W.

    2010-04-01

    This paper presents a framework to quantify the overall variability of the model estimations of Total Polychlorinated Biphenyls (Total PCBs) concentrations in the Niagara River on the basis of the uncertainty of few model parameters and the natural variability embedded in some of the model input variables. The results of the uncertainty analysis are used to understand the importance of stochastic model components and their effect on the overall reliability of the model output and to evaluate multiple sources of uncertainty that might need to be further studied. The uncertainty analysis is performed using a newly developed point estimate method, the Modified Rosenblueth method. The water quality along the Niagara River is simulated by coupling two numerical models the Environmental Fluid Dynamic Code (EFDC) - for the hydrodynamic portion of the study and the Water Quality Analysis and Simulation Program (WASP) - for the fate and transport of contaminants. For the monitoring period from May 1995 to March 1997, the inflow Total PCBs concentration from Lake Erie is the stochastic component that most influences the variability of the modeling results for the simulated concentrations at the exit of the Niagara River. Other significant stochastic components in order are as follows: the suspended sediments concentration, the point source loadings and to a minor degree the atmospheric deposition, the flow and the non-point source loadings. Model results that include estimates of uncertainty provide more comprehensive information about the variability of contaminant concentrations, such as confidence intervals, and, in general offer a better approach to compare model results with measured data.

  1. Development of a three dimensional numerical water quality model for continental shelf applications

    Science.gov (United States)

    Spaulding, M.; Hunter, D.

    1975-01-01

    A model to predict the distribution of water quality parameters in three dimensions was developed. The mass transport equation was solved using a non-dimensional vertical axis and an alternating-direction-implicit finite difference technique. The reaction kinetics of the constituents were incorporated into a matrix method which permits computation of the interactions of multiple constituents. Methods for the computation of dispersion coefficients and coliform bacteria decay rates were determined. Numerical investigations of dispersive and dissipative effects showed that the three-dimensional model performs as predicted by analysis of simpler cases. The model was then applied to a two dimensional vertically averaged tidal dynamics model for the Providence River. It was also extended to a steady state application by replacing the time step with an iteration sequence. This modification was verified by comparison to analytical solutions and applied to a river confluence situation.

  2. Hydrological and water quality processes simulation by the integrated MOHID model

    Science.gov (United States)

    Epelde, Ane; Antiguedad, Iñaki; Brito, David; Eduardo, Jauch; Neves, Ramiro; Sauvage, Sabine; Sánchez-Pérez, José Miguel

    2016-04-01

    Different modelling approaches have been used in recent decades to study the water quality degradation caused by non-point source pollution. In this study, the MOHID fully distributed and physics-based model has been employed to simulate hydrological processes and nitrogen dynamics in a nitrate vulnerable zone: the Alegria River watershed (Basque Country, Northern Spain). The results of this study indicate that the MOHID code is suitable for hydrological processes simulation at the watershed scale, as the model shows satisfactory performance at simulating the discharge (with NSE: 0.74 and 0.76 during calibration and validation periods, respectively). The agronomical component of the code, allowed the simulation of agricultural practices, which lead to adequate crop yield simulation in the model. Furthermore, the nitrogen exportation also shows satisfactory performance (with NSE: 0.64 and 0.69 during calibration and validation periods, respectively). While the lack of field measurements do not allow to evaluate the nutrient cycling processes in depth, it has been observed that the MOHID model simulates the annual denitrification according to general ranges established for agricultural watersheds (in this study, 9 kg N ha-1 year-1). In addition, the model has simulated coherently the spatial distribution of the denitrification process, which is directly linked to the simulated hydrological conditions. Thus, the model has localized the highest rates nearby the discharge zone of the aquifer and also where the aquifer thickness is low. These results evidence the strength of this model to simulate watershed scale hydrological processes as well as the crop production and the agricultural activity derived water quality degradation (considering both nutrient exportation and nutrient cycling processes).

  3. Lake Peipsi's eutrophication issue: new insights into large scale water quality modeling

    Science.gov (United States)

    Fink, Gabriel; Flörke, Martina

    2017-04-01

    The large and shallow European Lake Peipsi was polluted with phosphorus loadings from different point and diffuse sources over decades. The lake's trophic state changed from mesotrophic to eutrophic and hypertrophic. In the 1990s phosphorus pollution dropped significantly. However, more than twenty years later the lake is still eutrophic (L. Peipsi s.s.) and hypertrophic (L. Pihkva). It has been determined that internal loadings from a large nutrient pool in the lake's sediments play an important role in the actual phosphorus balance. For a pursuing and comprehensive understanding, there is a need for detailed and integrated water quality data. This is necessary to assess the current state as well as the younger lake nutrient history. However, in-situ data are scarce and difficult to access. To overcome this data sparse situation the global integrated modeling framework WaterGAP3 was applied (i) to test the applicability of a global scale (5 arc minutes resolution) water quality model in a local scale eutrophication study, and (ii) to provide a detailed local analysis of the eutrophication issue for Lake Peipsi. In this setting WaterGAP3 provides a detailed description of phosphorus sources, loadings and concentrations. Furthermore the newly implemented two box eutrophication module provides a long term description of total phosphorus (TP) concentrations in lakes, the consequent potential for toxic algae blooms, and the TP balance components such as the sediment storage. The WaterGAP3 global results such as river discharge, TP loads from different sectors, TP concentration in the lake and in the catchments river system cover a period of 1990-2010. Our model results indicate that the agricultural sector (diffuse source) is the primary source of TP pollution in the Lake Peipsi catchment (45%) followed by background sources (diffuse sources) such as atmospheric deposition and weathering (33%), and domestic point sources (19%). The model results confirm the reported

  4. 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.

  5. 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.

  6. Estimation of Water Quality Parameters in Lake Erie from MERIS Using Linear Mixed Effect Models

    Directory of Open Access Journals (Sweden)

    Kiana Zolfaghari

    2016-06-01

    Full Text Available Linear Mixed Effect (LME models are applied to the CoastColour atmospherically-corrected Medium Resolution Imaging Spectrometer (MERIS reflectance, L2R full resolution product, to derive chlorophyll-a (chl-a concentration and Secchi disk depth (SDD in Lake Erie, which is considered as a Case II water (i.e., turbid and productive. A LME model considers the correlation that exists in the field measurements which have been performed repeatedly in space and time. In this study, models are developed based on the relation between the logarithmic scale of the water quality parameters and band ratios: B07:665 nm to B09:708.75 nm for log10chl-a and B06:620 nm to B04:510 nm for log10SDD. Cross validation is performed on the models. The results show good performance of the models, with Root Mean Square Errors (RMSE and Mean Bias Errors (MBE of 0.31 and 0.018 for log10chl-a, and 0.19 and 0.006 for log10SDD, respectively. The models are then applied to a time series of MERIS images acquired over Lake Erie from 2004–2012 to investigate the spatial and temporal variations of the water quality parameters. Produced maps reveal distinct monthly patterns for different regions of Lake Erie that are in agreement with known biogeochemical properties of the lake. The Detroit River and Maumee River carry sediments and nutrients to the shallow western basin. Hence, the shallow western basin of Lake Erie experiences the most intense algal blooms and the highest turbidity compared to the other sections of the lake. Maumee Bay, Sandusky Bay, Rondeau Bay and Long Point Bay are estimated to have prolonged intense algal bloom.

  7. Multiple-response Bayesian calibration of watershed water quality models with significant input and model structure errors

    Science.gov (United States)

    Han, Feng; Zheng, Yi

    2016-02-01

    While watershed water quality (WWQ) models have been widely used to support water quality management, their profound modeling uncertainty remains an unaddressed issue. Data assimilation via Bayesian calibration is a promising solution to the uncertainty, but has been rarely practiced for WWQ modeling. This study applied multiple-response Bayesian calibration (MRBC) to SWAT, a classic WWQ model, using the nitrate pollution in the Newport Bay Watershed (southern California, USA) as the study case. How typical input and model structure errors would impact modeling uncertainty, parameter identification and management decision-making was systematically investigated through both synthetic and real-situation modeling cases. The main study findings include: (1) with an efficient sampling scheme, MRBC is applicable to WWQ modeling in characterizing its parametric and predictive uncertainties; (2) incorporating hydrology responses, which are less susceptible to input and model structure errors than water quality responses, can improve the Bayesian calibration results and benefit potential modeling-based management decisions; and (3) the value of MRBC to modeling-based decision-making essentially depends on pollution severity, management objective and decision maker's risk tolerance.

  8. Using QUAL2K Model and river pollution index for water quality management in Mahmoudia Canal, Egypt

    Directory of Open Access Journals (Sweden)

    Ehab A. Elsayed

    2014-08-01

    Full Text Available The Mahmoudia Canal is the main source of municipal and industrial water supply for Alexandria (the second largest city in Egypt and many other towns and villages. In recent years, considerable water quality degradation has been observed in the Mahmoudia Canal. This problem has attracted increasing attention from both the public and the Egyptian government. As a result, this study aims at assessing the current seasonal variations in water quality in the Mahmoudia Canal and simulating various water quality management scenarios for the canal. The present research involves the application of the water quality model, QUAL2K, to predict water quality along the Mahmoudia Canal on a seasonal basis for the considered scenarios. Based on the QUAL2K simulations, the River Pollution Index (RPI was used to appraise the conditions of water pollution at the intakes of the twelve water treatment plants (WTPs located along Mahmoudia Canal. The results showed that the QUAL2K model is successfully applied to simulate the water quantity and quality parameters of the Mahmoudia Canal in different seasons. For the current status of the canal, it was found that the highest pollution level occurred in autumn in which effluent water quality at all WTPs along the Mahmoudia Canal was classified as moderately polluted. In the other seasons, effluent water quality was categorized as moderately polluted at most WTPs in the Beheira governorate and negligibly polluted at all WTPs in the Alexandria governorate. Moreover, it was concluded that controlling the Rahawy drain discharge or treating its pollution loads before mixing with the Rosetta Branch may solve water quality problems of the Mahmoudia Canal and allow re-running of the Edko re-use pump station in summer, winter, and spring. However in autumn, additional measures will be required to mitigate pollution levels in the canal.

  9. Spatiotemporal Variability of Lake Water Quality in the Context of Remote Sensing Models

    Directory of Open Access Journals (Sweden)

    Carly Hyatt Hansen

    2017-04-01

    Full Text Available This study demonstrates a number of methods for using field sampling and observed lake characteristics and patterns to improve techniques for development of algae remote sensing models and applications. As satellite and airborne sensors improve and their data are more readily available, applications of models to estimate water quality via remote sensing are becoming more practical for local water quality monitoring, particularly of surface algal conditions. Despite the increasing number of applications, there are significant concerns associated with remote sensing model development and application, several of which are addressed in this study. These concerns include: (1 selecting sensors which are suitable for the spatial and temporal variability in the water body; (2 determining appropriate uses of near-coincident data in empirical model calibration; and (3 recognizing potential limitations of remote sensing measurements which are biased toward surface and near-surface conditions. We address these issues in three lakes in the Great Salt Lake surface water system (namely the Great Salt Lake, Farmington Bay, and Utah Lake through sampling at scales that are representative of commonly used sensors, repeated sampling, and sampling at both near-surface depths and throughout the water column. The variability across distances representative of the spatial resolutions of Landsat, SENTINEL-2 and MODIS sensors suggests that these sensors are appropriate for this lake system. We also use observed temporal variability in the system to evaluate sensors. These relationships proved to be complex, and observed temporal variability indicates the revisit time of Landsat may be problematic for detecting short events in some lakes, while it may be sufficient for other areas of the system with lower short-term variability. Temporal variability patterns in these lakes are also used to assess near-coincident data in empirical model development. Finally, relationships

  10. A three-dimensional water quality model to evaluate the environmental capacity of nitrogen and phosphorus in Jiaozhou Bay, China.

    Science.gov (United States)

    Li, Keqiang; Zhang, Li; Li, Yan; Zhang, Longjun; Wang, Xiulin

    2015-02-15

    Jiaozhou Bay has recently suffered from serious problems with pollution and eutrophication. Thus, land-based pollutant load must be reduced through a national control program. In this study, we developed a 3D water quality model to determine the environmental capacity of nitrogen and phosphorus in Jiaozhou Bay. A 3D hydrodynamic model (the estuarine, coastal, and ocean modeling system with sediments) was coupled with a water quality model, which was adapted from the dynamic model of nitrogen and phosphorus for a mesocosm near Jiaozhou Bay. The water quality model is divided into seven components: dissolved inorganic nitrogen, phosphate, phytoplankton, zooplankton, detritus, dissolved organic nitrogen, and dissolved organic phosphorus. Furthermore, it was calibrated based on data collected from Jiaozhou Bay in 2003. The proposed model effectively reproduced the spatiotemporal variability in nutrient concentration, thus suggesting that a reasonable numerical representation of the prototype system must be developed for further evaluation of environmental capacity. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Field measurements and neural network modeling of water quality parameters.

    Science.gov (United States)

    Haghiabi, Amir Hamzeh

    2017-01-28

    This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Evaluating a microbial water quality prediction model for beach management under the revised EU Bathing Water Directive.

    Science.gov (United States)

    Bedri, Zeinab; Corkery, Aisling; O'Sullivan, John J; Deering, Louise A; Demeter, Katalin; Meijer, Wim G; O'Hare, Gregory; Masterson, Bartholomew

    2016-02-01

    The revised Bathing Water Directive (2006/7/EC) requires EU member states to minimise the risk to public health from faecal pollution at bathing waters through improved monitoring and management approaches. While increasingly sophisticated measurement methods (such as microbial source tracking) assist in the management of bathing water resources, the use of deterministic predictive models for this purpose, while having the potential to provide decision making support, remains less common. This study explores an integrated, deterministic catchment-coastal hydro-environmental model as a decision-making tool for beach management which, based on advance predictions of bathing water quality, can inform beach managers on appropriate management actions (to prohibit bathing or advise the public not to bathe) in the event of a poor water quality forecast. The model provides a 'moving window' five-day forecast of Escherichia coli levels at a bathing water compliance point off the Irish coast and the accuracy of bathing water management decisions were investigated for model predictions under two scenarios over the period from the 11th August to the 5th September, 2012. Decisions for Scenario 1 were based on model predictions where rainfall forecasts from a meteorological source (www.yr.no) were used to drive the rainfall-runoff processes in the catchment component of the model, and for Scenario 2, were based on predictions that were improved by incorporating real-time rainfall data from a sensor network within the catchment into the forecasted meteorological input data. The accuracy of the model in the decision-making process was assessed using the contingency table and its metrics. The predictive model gave reasonable outputs to support appropriate decision making for public health protection. Scenario 1 provided real-time predictions that, on 77% of instances during the study period where both predicted and E. coli concentrations were available, would correctly inform a

  13. Application of the SUSTAIN Model to a Watershed-Scale Case for Water Quality Management

    Directory of Open Access Journals (Sweden)

    Chi-Feng Chen

    2014-11-01

    Full Text Available Low impact development (LID is a relatively new concept in land use management that aims to maintain hydrological conditions at a predevelopment level without deteriorating water quality during land development. The United States Environmental Protection Agency (USEPA developed the System for Urban Stormwater Treatment and Analysis Integration model (SUSTAIN to evaluate the performance of LID practices at different spatial scales; however, the application of this model has been limited relative to LID modeling. In this study, the SUSTAIN model was applied to a Taiwanese watershed. Model calibration and verification were performed, and different types of LID facilities were evaluated. The model simulation process and the verified model parameters could be used in other cases. Four LID scenarios combining bioretention ponds, grass swales, and pervious pavements were designed based on the land characteristics. For the SUSTAIN model simulation, the results showed that pollution reduction was mainly due to water quantity reduction, infiltration was the dominant mechanism and plant interception had a minor effect on the treatment. The simulation results were used to rank the primary areas for nonpoint source pollution and identify effective LID practices. In addition to the case study, a sensitivity analysis of the model parameters was performed, showing that the soil infiltration rate was the most sensitive parameter affecting the LID performance. The objectives of the study are to confirm the applicability of the SUSTAIN model and to assess the effectiveness of LID practices in the studied watershed.

  14. Modelling threats to water quality from fire suppression chemicals and post-fire erosion

    Science.gov (United States)

    Hyde, Kevin; Ziemniak, Chris; Elliot, William; Samuels, William

    2014-05-01

    Misapplication of fire retardant chemicals into streams and rivers may threaten aquatic life. The possible threat depends on the contaminant concentration that, in part, is controlled by dispersion within flowing water. In the event of a misapplication, methods are needed to rapidly estimate the chemical mass entering the waterway and the dispersion and transport within the system. Here we demonstrate a new tool that calculates the chemical mass based on aircraft delivery system, fire chemical type, and stream and intersect geometry. The estimated mass is intended to be transferred into a GIS module that uses real-time stream data to map and simulate the dispersion and transport downstream. This system currently accounts only for aqueous transport. We envision that the GIS module can be modified to incorporate sediment transport, specifically to model movement of sediments from post-fire erosion. This modification could support assessment of threats of post-fire erosion to water quality and water supply systems.

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

    Science.gov (United States)

    Background/Question/MethodThe water quality of the Nation’s estuaries is attracting increasing scrutiny in light of burgeoning coastal population growth and enhanced delivery of nutrients via riverine flux. The USEPA has evaluated water quality in US estuaries in the Nation...

  16. 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.

  17. 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.

  18. Evaluating, interpreting, and communicating performance of hydrologic/water quality models considering intended use: A review and recommendations

    Science.gov (United States)

    Previous publications have outlined recommended practices for hydrologic and water quality (H/WQ) modeling, but none have formulated comprehensive guidelines for the final stage of modeling applications, namely evaluation, interpretation, and communication of model results and the consideration of t...

  19. Computer program documentation for the enhanced stream-water quality model QUAL2E. Final report, August 1984-June 1985

    Energy Technology Data Exchange (ETDEWEB)

    Brown, L.C.; Barnwell, T.O.

    1985-08-01

    Presented in the manual are recent modifications and improvements to the widely used stream water quality model QUAL-II. Called QUAL2E, the enhanced model incorporates improvements in eight areas: (1) algal, nitrogen, phosphorus, and dissolved oxygen interactions; (2) algal growth rate; (3) temperature; (4) dissolved oxygen; (5) arbitrary non-conservative constituents; (6) hydraulics; (7) downstream boundary concentrations; and (8) input/output modifications. QUAL2E, which can be operated either as a steady-state or as a dynamic model, is intended for use as a water-quality planning tool.

  20. Testing the Spatio-temporal Transferability of a Hydrological Water Quality Model in Central Germany

    Science.gov (United States)

    Jomaa, Seifeddine; Jiang, Sanyuan; Rode, Michael

    2014-05-01

    Numerous studies have shown that the changes in land cover/use affect significantly the hydrological regime, which in turn influence the surface water quality. It is known that, at the catchment scale, hydrological modelling is a favourable tool for discharge and nutrients transport (such as Nitrogen and Phosphorus) predictions. The semi-distributed hydrological water quality HYPE (Hydrological Predictions for the Environment) model, has been evaluated for different catchments, and has been shown to reliably reproduce the measured data. The aim of this study was to test the spatio-temporal transferability of the HYPE model in Central Germany. First, the spatial transferability of the HYPE model was tested using two mesoscale catchments with different physiographical characteristics. To achieve our gaols, the Selke (463 km²) and Weida (99.5 km²) catchments, which are two small tributaries of the Elbe river basin were utilized. Second, the temporal transferability of the HYPE model was tested in the Weida catchment using different periods, where different patterns of nitrogen leaching were measured due to two considerable shifts in land use intensities and fertilizers application rates in 1990 and 1997. For Selke, the HYPE model reproduced reasonably well the discharge and IN monthly loads (with lowest NSE of 0.86 and 0.69 for discharge and IN loads, respectively). Also, results showed that only a NSE of 0.30 was obtained for the Weida catchment, in situations where the same best-optimized values from Selke was utilized, reflecting the controlling factors of land use and topography on the runoff generation. However, when the physiographical characteristics of the Weida catchment were considered during the calibration and validation phases (1997-2000 and 2001-2004, respectively, daily data), the HYPE model could reasonably predict the measured discharge and IN concentrations with similar performance as the Selke. In addition, the temporal transferability of the HYPE

  1. Reactive transport modeling of secondary water quality impacts due to anaerobic bioremediation

    Science.gov (United States)

    Ng, G. H. C.; Bekins, B. A.; Kent, D. B.; Borden, R. C.; Tillotson, J.

    2014-12-01

    Bioremediation using electron donor addition produces reducing conditions in an aquifer that promote the anaerobic biodegradation of contaminants such as chlorinated solvents. There is growing concern about secondary water quality impacts (SWQIs) triggered by the injection of electron donors, due to redox reactions with electron acceptors other than the target contaminant. Secondary plumes, including those with elevated concentrations of Mn(II), Fe(II), and CH4, may create long-lasting impairment of water quality. Understanding conditions that control the production and attenuation of SWQIs is needed for guiding responsible bioremediation strategies that limit unintended consequences. Using a reactive transport model developed with data from long-term anaerobic biodegradation monitoring sites, we simulate diverse geochemical scenarios to examine the sensitivity of secondary plume extent and persistence to a range of aquifer properties and treatment implementations. Data compiled from anaerobic bioremediation sites, which include variable physical and geochemical relationships, provide the basis for the conditions evaluated. Our simulations show that reduced metal and CH4 plumes may be significantly attenuated due to immobilization (through sorption and/or precipitation) and outgassing, respectively, and that recovery time to background conditions depends strongly on the chemical forms of reduced metals on sediments. Unsurprisingly, scenarios that do not easily allow outgassing (e.g. deeper injections) led to higher CH4 concentrations, and scenarios with higher hydraulic conductivity produced more dilute concentrations of secondary species. Results are sensitive to the assumed capacity for Fe(II) sorption and reductive dissolution rates of Fe(III) oxides, which control Fe(II) concentrations. Simulations also demonstrated the potential importance of chemical reactions between different secondary components. For example, limited CH4 loss from outgassing and Fe

  2. Regional risk assessment for point source pollution based on a water quality model of the Taipu River, China.

    Science.gov (United States)

    Yao, Hong; Qian, Xin; Yin, Hong; Gao, Hailong; Wang, Yulei

    2015-02-01

    Point source pollution is one of the main threats to regional environmental health. Based on a water quality model, a methodology to assess the regional risk of point source pollution is proposed. The assessment procedure includes five parts: (1) identifying risk source units and estimating source emissions using Monte Carlo algorithms; (2) observing hydrological and water quality data of the assessed area, and evaluating the selected water quality model; (3) screening out the assessment endpoints and analyzing receptor vulnerability with the Choquet fuzzy integral algorithm; (4) using the water quality model introduced in the second step to predict pollutant concentrations for various source emission scenarios and analyzing hazards of risk sources; and finally, (5) using the source hazard values and receptor vulnerability scores to estimate overall regional risk. The proposed method, based on the Water Quality Analysis Simulation Program (WASP), was applied in the region of the Taipu River, which is in the Taihu Basin, China. Results of source hazard and receptor vulnerability analysis allowed us to describe aquatic ecological, human health, and socioeconomic risks individually, and also integrated risks in the Taipu region, from a series of risk curves. Risk contributions of sources to receptors were ranked, and the spatial distribution of risk levels was presented. By changing the input conditions, we were able to estimate risks for a range of scenarios. Thus, the proposed procedure may also be used by decisionmakers for long-term dynamic risk prediction. © 2014 Society for Risk Analysis.

  3. A coastal three-dimensional water quality model of nitrogen in Jiaozhou Bay linking field experiments with modelling.

    Science.gov (United States)

    Lu, Dongliang; Li, Keqiang; Liang, Shengkang; Lin, Guohong; Wang, Xiulin

    2017-01-15

    With anthropogenic changes, the structure and quantity of nitrogen nutrients have changed in coastal ocean, which has dramatically influenced the water quality. Water quality modeling can contribute to the necessary scientific grounding of coastal management. In this paper, some of the dynamic functions and parameters of nitrogen were calibrated based on coastal field experiments covering the dynamic nitrogen processes in Jiaozhou Bay (JZB), including phytoplankton growth, respiration, and mortality; particulate nitrogen degradation; and dissolved organic nitrogen remineralization. The results of the field experiments and box model simulations showed good agreement (RSD=20%±2% and SI=0.77±0.04). A three-dimensional water quality model of nitrogen (3DWQMN) in JZB was improved and the dynamic parameters were updated according to field experiments. The 3DWQMN was validated based on observed data from 2012 to 2013, with good agreement (RSD=27±4%, SI=0.68±0.06, and K=0.48±0.04), which testifies to the model's credibility. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. 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

  5. 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

  6. Development of a storm surge driven water quality model to simulate spills during hurricanes.

    Science.gov (United States)

    Kiaghadi, Amin; Rifai, Hanadi S; Burleson, Daniel W

    2017-11-02

    Hurricanes can cause widespread environmental pollution that has yet to be fully articulated. This study develops a predictive water quality model to forecast potential contamination resulting from buckled or ruptured storage tanks in coastal industrialized areas when subjected to storm surge. The developed EFDC-Storm Surge model (EFDC-SS) couples EPA's EFDC code with the SWAN-ADCIRC hurricane simulation model. EFDC-SS is demonstrated using the Houston Ship Channel in Texas as a testbed and hurricane Ike as a model hurricane. Conservative and decaying dye runs evaluated various hurricane scenarios, combined with spills released at different locations and release times. Results showed that tank locations with shorter distances to the main waterbody and lower ground elevations have a higher risk of inundation and rapid spill mass transport. It was also determined that hurricane strength and landfall location, the location of the spill, and the spill release time relative to peak surge were interdependent. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    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.

  8. 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

  9. 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

  10. Quantitative evaluation of lake eutrophication responses under alternative water diversion scenarios: a water quality modeling based statistical analysis approach.

    Science.gov (United States)

    Liu, Yong; Wang, Yilin; Sheng, Hu; Dong, Feifei; Zou, Rui; Zhao, Lei; Guo, Huaicheng; Zhu, Xiang; He, Bin

    2014-01-15

    China is confronting the challenge of accelerated lake eutrophication, where Lake Dianchi is considered as the most serious one. Eutrophication control for Lake Dianchi began in the mid-1980s. However, decision makers have been puzzled by the lack of visible water quality response to past efforts given the tremendous investment. Therefore, decision makers desperately need a scientifically sound way to quantitatively evaluate the response of lake water quality to proposed management measures and engineering works. We used a water quality modeling based scenario analysis approach to quantitatively evaluate the eutrophication responses of Lake Dianchi to an under-construction water diversion project. The primary analytic framework was built on a three-dimensional hydrodynamic, nutrient fate and transport, as well as algae dynamics model, which has previously been calibrated and validated using historical data. We designed 16 scenarios to analyze the water quality effects of three driving forces, including watershed nutrient loading, variations in diverted inflow water, and lake water level. A two-step statistical analysis consisting of an orthogonal test analysis and linear regression was then conducted to distinguish the contributions of various driving forces to lake water quality. The analysis results show that (a) the different ways of managing the diversion projects would result in different water quality response in Lake Dianchi, though the differences do not appear to be significant; (b) the maximum reduction in annual average and peak Chl-a concentration from the various ways of diversion project operation are respectively 11% and 5%; (c) a combined 66% watershed load reduction and water diversion can eliminate the lake hypoxia volume percentage from the existing 6.82% to 3.00%; and (d) the water diversion will decrease the occurrence of algal blooms, and the effect of algae reduction can be enhanced if diverted water are seasonally allocated such that wet

  11. A model for assessing water quality risk in catchments prone to wildfire

    Science.gov (United States)

    Langhans, Christoph; Smith, Hugh; Chong, Derek; Nyman, Petter; Lane, Patrick; Sheridan, Gary

    2017-04-01

    Post-fire debris flows can have erosion rates up to three orders of magnitude higher than background rates. They are major sources of fine suspended sediment, which is critical to the safety of water supply from forested catchments. Fire can cover parts or all of these large catchments and burn severity is often heterogeneous. The probability of spatial and temporal overlap of fire disturbance and rainfall events, and the susceptibility of hillslopes to severe erosion determine the risk to water quality. Here we present a model to calculate recurrence intervals of high magnitude sediment delivery from runoff-generated debris flows to a reservoir in a large catchment (>100 km2) accounting for heterogeneous burn conditions. Debris flow initiation was modelled with indicators of surface runoff and soil surface erodibility. Debris flow volume was calculated with an empirical model, and fine sediment delivery was calculated using simple, expert-based assumptions. In a Monte-Carlo simulation, wildfire was modelled with a fire spread model using historic data on weather and ignition probabilities for a forested catchment in central Victoria, Australia. Multiple high intensity storms covering the study catchment were simulated using Intensity-Frequency-Duration relationships, and the runoff indicator calculated with a runoff model for hillslopes. A sensitivity analysis showed that fine sediment is most sensitive to variables related to the texture of the source material, debris flow volume estimation, and the proportion of fine sediment transported to the reservoir. As a measure of indirect validation, denudation rates of 4.6 - 28.5 mm ka-1 were estimated and compared well to other studies in the region. From the results it was extrapolated that in the absence of fire management intervention the critical sediment concentrations in the studied reservoir could be exceeded in intervals of 18 - 124 years.

  12. Lake Diefenbaker: Water Quality Assessment and Modeling for Management under Environmental Change

    Science.gov (United States)

    Sereda, J.; Wheater, H. S.; Hudson, J.; Doig, L.; Liber, K.; Jones, P.; Giesy, J.; Bharadwaj, L.

    2011-12-01

    Preliminary results are presented for a comprehensive inter-disciplinary study on Lake Diefenbaker initiated by the Global Institute for Water Security to understand the physical and biogeochemical processes affecting water quality under climate change and their policy implications. Lake Diefenbaker is a large reservoir (surface area ~500km2 and Zmean ~33m) located in Southern Saskatchewan, Canada and is a critically-important water resource for Saskatchewan. It receives nearly all of its flow from the South Saskatchewan River, which flows through some of the most urbanized and intense agricultural lands of southern Alberta. As a result these waters contain high levels of nutrients [nitrogen (N) and phosphorus (P)] along with a variety of chemical contaminants characteristic of anthropogenic activity. In addition, riparian and in-lake activities provide local sources of nutrients, from domestic sewage, agriculture and fish farming. The South Saskatchewan River has been identified by the World Wildlife Fund (2009) as Canada's most threatened river in terms of environmental flow. Lake Diefenbaker has numerous large deep embayments (depth >20m) and an annual water level fluctuation of ~6m. A deep thermocline (~25m) forms infrequently. Stratification does not occur throughout the lake. Anecdotal information suggests that the frequency and severity of algal blooms are increasing; although blooms have been sporadic and localized. This localized eutrophication may be related to local stratification patterns, point source nutrient loading, and/or internal lake processes (i.e., internal nutrient loading). A paleolimnological reconstruction has begun to assess historical nutrient and contaminant loading to Lake Diefenbaker and hence the trajectory of water quality in the lake. Major point sources and diffuse sources of N and P are also under investigation. In addition, the type (N versus P) and degree of nutrient limitation of bacteria and algae are being assessed (spatially

  13. 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.

  14. 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

  15. Modeling of eutrophication and strategies for improvement of water quality in reservoirs.

    Science.gov (United States)

    Shourian, Mojtaba; Moridi, Ali; Kaveh, Mohammad

    2016-09-01

    The purpose of this study is to survey the thermal regime and eutrophication states in Ilam reservoir in Iran as the case study. For this purpose and to find solutions for improving the water's quality in the reservoir, two general strategies for reducing the entering pollution loads and water depletions from the reservoir's outlets were analyzed by use of the CE-QUAL-W2 model. Results of the simulation of the present situation show the existence of thermal stratification during summer, which results in the qualitative stratification in the reservoir. According to the qualitative criteria, the Ilam reservoir's state is between mesotrophic and eutrophic. Results of the scenarios of reduction of the nutrients show that in the scenario of 50% reduction of the phosphorus and nitrogen loads into the reservoir, the state of the reservoir would recover from eutrophic to semi-eutrophic. Also, release of water from the reservoir during September, October and November would cause the restoration of the quality of water in the reservoir. To avoid the occurrence of critical eutrophication in the reservoir, reducing the ponding time in the reservoir by fast depletion, preventing entrance of the upstream villages' sewage and agricultural drained waters, which are sources of nitrate and phosphate contamination into the rivers, and also management of the usage of agricultural fertilizers have been suggested.

  16. 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.

  17. A Modified Hopfield Neural Network Algorithm (MHNNA Using ALOS Image for Water Quality Mapping

    Directory of Open Access Journals (Sweden)

    Ahmed Asal Kzar

    2015-12-01

    Full Text Available Decreasing water pollution is a big problem in coastal waters. Coastal health of ecosystems can be affected by high concentrations of suspended sediment. In this work, a Modified Hopfield Neural Network Algorithm (MHNNA was used with remote sensing imagery to classify the total suspended solids (TSS concentrations in the waters of coastal Langkawi Island, Malaysia. The adopted remote sensing image is the Advanced Land Observation Satellite (ALOS image acquired on 18 January 2010. Our modification allows the Hopfield neural network to convert and classify color satellite images. The samples were collected from the study area simultaneously with the acquiring of satellite imagery. The sample locations were determined using a handheld global positioning system (GPS. The TSS concentration measurements were conducted in a lab and used for validation (real data, classification, and accuracy assessments. Mapping was achieved by using the MHNNA to classify the concentrations according to their reflectance values in band 1, band 2, and band 3. The TSS map was color-coded for visual interpretation. The efficiency of the proposed algorithm was investigated by dividing the validation data into two groups. The first group was used as source samples for supervisor classification via the MHNNA. The second group was used to test the MHNNA efficiency. After mapping, the locations of the second group in the produced classes were detected. Next, the correlation coefficient (R and root mean square error (RMSE were calculated between the two groups, according to their corresponding locations in the classes. The MHNNA exhibited a higher R (0.977 and lower RMSE (2.887. In addition, we test the MHNNA with noise, where it proves its accuracy with noisy images over a range of noise levels. All results have been compared with a minimum distance classifier (Min-Dis. Therefore, TSS mapping of polluted water in the coastal Langkawi Island, Malaysia can be performed using the

  18. Statistical Analysis and water Quality Modeling for a Drinking Water Source Watershed for the City of Houston, Texas

    Science.gov (United States)

    Teague, A.; Bedient, P.; Vieux, B. E.

    2009-12-01

    Water quality is a problem in Lake Houston, the primary source of drinking water for the City of Houston, due to pollutant loads coming from the influent watersheds, including Cypress Creek. Water quality issues in the watershed that are of concern for the lake include nutrient enrichment bacterial impairment, both of which present operational challenges for the drinking water treatment plant operations. Statistical analysis of the historic water quality data was developed in order to understand the source characterization and seasonality of the watershed. Multivariate analysis including principal component, cluster, and discriminant analysis provided a unique seasonal assessment of the watershed leading to refined loading curves have been analyzed using data collected by the USGS at 3 sites in Cypress Creek with corresponding City of Houston water quality data at the sites for the past 5 years to characterize the behavior of the pollutant source and watershed. A VfloTM hydrologic model from Vieux & Assoc., Inc for the watershed of the influent stream Cypress Creek was developed to predict the watershed flows into Lake Houston. A distributed model of a large scale watershed, it uses finite element analysis to solve the kinematic wave equation. The model incorporates land use relationships to predict runoff from Radar rainfall data. Continuous VfloTM was run for storm events and the distributed discharge of the watershed simulated. From the spatial discharge output, nutrient wash-off and convective transport was simulated. The simulated nutrient transport was then compared to storm sampling data at a downstream location to assess the water quality model and determine needed future refinements.

  19. 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.

  20. Examining spatially varying relationships between land use and water quality using geographically weighted regression I: model design and evaluation.

    Science.gov (United States)

    Tu, Jun; Xia, Zong-Guo

    2008-12-15

    Traditional regression techniques such as ordinary least squares (OLS) can hide important local variations in the model parameters, and are not able to deal with spatial autocorrelations existing in the variables. A recently developed technique, geographically weighted regression (GWR), is used to examine the relationships between land use and water quality in eastern Massachusetts, USA. GWR models make great improvements of model performance over OLS models, which is proved by F-test and comparisons of model R2 and corrected Akaike Information Criterion (AICc) from both GWR and OLS. GWR models also improve the reliabilities of the relationships by reducing spatial autocorrelations. The application of GWR models finds that the relationships between land use and water quality are not constant over space but show great spatial non-stationarity. GWR models are able to reveal the information previously ignored by OLS models on the local causes of water pollution, and so improve the model ability to explain local situation of water quality. The results of this study suggest that GWR technique has the potential to serve as a useful tool for environmental research and management at watershed, regional, national and even global scales.

  1. Water Quality and Quantity Modeling for Hydrologic and Policy Decision Making

    Science.gov (United States)

    Rubiano, J.; Giron, E.; Quintero, M.; O'Brien, R.

    2004-12-01

    -funding schemes designed with the private and public stakeholders having a role in the study area. The significance of this research is clearly depicted by the results of the different models applying here for the assessment of water quality parameters and for modeling upper catchments terrain surface change in the study area. Application of the methodology is presented for the Fuquene Lake Basin in Cundinamarca, Colombia. Additional research needs and limitations of the methodology are highlighted.

  2. 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.

  3. Modeling Hydrodynamics and Heat Transport in Upper Klamath Lake, Oregon, and Implications for Water Quality

    Science.gov (United States)

    Wood, Tamara M.; Cheng, Ralph T.; Gartner, Jeffrey W.; Hoilman, Gene R.; Lindenberg, Mary K.; Wellman, Roy E.

    2008-01-01

    The three-dimensional numerical model UnTRIM was used to model hydrodynamics and heat transport in Upper Klamath Lake, Oregon, between mid-June and mid-September in 2005 and between mid-May and mid-October in 2006. Data from as many as six meteorological stations were used to generate a spatially interpolated wind field to use as a forcing function. Solar radiation, air temperature, and relative humidity data all were available at one or more sites. In general, because the available data for all inflows and outflows did not adequately close the water budget as calculated from lake elevation and stage-capacity information, a residual inflow or outflow was used to assure closure of the water budget. Data used for calibration in 2005 included lake elevation at 3 water-level gages around the lake, water currents at 5 Acoustic Doppler Current Profiler (ADCP) sites, and temperature at 16 water-quality monitoring locations. The calibrated model accurately simulated the fluctuations of the surface of the lake caused by daily wind patterns. The use of a spatially variable surface wind interpolated from two sites on the lake and four sites on the shoreline generally resulted in more accurate simulation of the currents than the use of a spatially invariant surface wind as observed at only one site on the lake. The simulation of currents was most accurate at the deepest site (ADCP1, where the velocities were highest) using a spatially variable surface wind; the mean error (ME) and root mean square error (RMSE) for the depth-averaged speed over a 37-day simulation from July 26 to August 31, 2005, were 0.50 centimeter per second (cm/s) and 3.08 cm/s, respectively. Simulated currents at the remaining sites were less accurate and, in general, underestimated the measured currents. The maximum errors in simulated currents were at a site near the southern end of the trench at the mouth of Howard Bay (ADCP7), where the ME and RMSE in the depth-averaged speed were 3.02 and 4.38 cm

  4. 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

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

    African Journals Online (AJOL)

    2009-02-06

    Feb 6, 2009 ... ter drains which mostly consist of culverts and an underground ... Runoff coefficient of impervious areas. 0.85 ... *RWQO are defined as numeric or descriptive instream water quality .... with downspout disconnection in medium- and low-density .... This method estimates the average annual pollution load.

  6. 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

  7. 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.

  8. Valuing Water Quality As a Functionof Water Quality Measures

    OpenAIRE

    Egan, Kevin J.; Joseph A. Herriges; Catherine L. Kling; Downing, John A.

    2004-01-01

    This paper incorporates a rich set of physical water quality attributes, as well as site and household characteristics, into a model of recreational lake usage in Iowa. Our analysis shows individuals are responsive to physical water quality measures. Willingness-to-pay estimates are reported based on improvements in these measures.

  9. 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 ...

  10. 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

  11. Hydrodynamics and water quality modelling in a regulated river segment: application on the instream flow definition

    OpenAIRE

    Lopes, Luis Filipe Gomes; Carmo, José S. Antunes Do; Cortes, Rui Manuel Vitor; de Oliveira, Daniel

    2004-01-01

    The aim of this paper is to present a global study on the hydrodynamics, water quality and their influence on aquatic fauna. The case study was conducted on a segment of the Lima river (North Portugal), downstream of the Touvedo dam, which was mainly constructed for hydroelectric power production. http://www.sciencedirect.com/science/article/B6VBS-4BHVGYD-7/1/7765917f49c0a6b3764cf34a8227cfc2

  12. A basic model to predict water quality changes in the Vaal Dam

    OpenAIRE

    2012-01-01

    M.Sc. The Vaal Dam (South Africa) and its tributaries have been extensively affected by domestic, mining, agricultural and industrial activities, as well as the release of effluents. These practices have contributed to large-scale algal blooms that have caused serious ecological, aesthetic, water purification and water distribution problems. This study addresses the need to develop a system that enables forecasts to be made regarding potential changes in the water quality ofthe Vaal Dam, e...

  13. 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.

  14. 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.

  15. 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.

  16. 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 (pollutant first flushes was particularly apparent in urban streams but this was followed by a rapid recovery. Chronic effects lasting for three to four weeks were only seen downstream of a sewage treatment 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.

  17. 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

  18. Sensitivity analysis for the total nitrogen pollution of the Danjiangkou Reservoir based on a 3-D water quality model

    Science.gov (United States)

    Chen, Libin; Yang, Zhifeng; Liu, Haifei

    2017-06-01

    Inter-basin water transfers containing a great deal of nitrogen are great threats to human health, biodiversity, and air and water quality in the recipient area. Danjiangkou Reservoir, the source reservoir for China's South-to-North Water Diversion Middle Route Project, suffers from total nitrogen pollution and threatens the water transfer to a number of metropolises including the capital, Beijing. To locate the main source of nitrogen pollution into the reservoir, especially near the Taocha canal head, where the intake of water transfer begins, we constructed a 3-D water quality model. We then used an inflow sensitivity analysis method to analyze the significance of inflows from each tributary that may contribute to the total nitrogen pollution and affect water quality. The results indicated that the Han River was the most significant river with a sensitivity index of 0.340, followed by the Dan River with a sensitivity index of 0.089, while the Guanshan River and the Lang River were not significant, with the sensitivity indices of 0.002 and 0.001, respectively. This result implies that the concentration and amount of nitrogen inflow outweighs the geographical position of the tributary for sources of total nitrogen pollution to the Taocha canal head of the Danjiangkou Reservoir.

  19. Sensitivity analysis for the total nitrogen pollution of the Danjiangkou Reservoir based on a 3-D water quality model

    Science.gov (United States)

    Chen, Libin; Yang, Zhifeng; Liu, Haifei

    2017-12-01

    Inter-basin water transfers containing a great deal of nitrogen are great threats to human health, biodiversity, and air and water quality in the recipient area. Danjiangkou Reservoir, the source reservoir for China's South-to-North Water Diversion Middle Route Project, suffers from total nitrogen pollution and threatens the water transfer to a number of metropolises including the capital, Beijing. To locate the main source of nitrogen pollution into the reservoir, especially near the Taocha canal head, where the intake of water transfer begins, we constructed a 3-D water quality model. We then used an inflow sensitivity analysis method to analyze the significance of inflows from each tributary that may contribute to the total nitrogen pollution and affect water quality. The results indicated that the Han River was the most significant river with a sensitivity index of 0.340, followed by the Dan River with a sensitivity index of 0.089, while the Guanshan River and the Lang River were not significant, with the sensitivity indices of 0.002 and 0.001, respectively. This result implies that the concentration and amount of nitrogen inflow outweighs the geographical position of the tributary for sources of total nitrogen pollution to the Taocha canal head of the Danjiangkou Reservoir.

  20. Application of the two coupled models for water quality management: facultative pond cum constructed wetland models

    Science.gov (United States)

    Mashauri, D. A.; Kayombo, S.

    Recent work has emphasized the potential importance of the constructed wetland systems for purification of effluents from secondary biological treatment plants for prevention of pollution to the receiving water bodies. A model for transformation of organic carbon in facultative pond (FP) was formulated and was coupled with a model of organic carbon transformation in the constructed wetland (CW) for downstream water resources management. The main essence of coupling the model was to have simultaneous simulation of PFP and CW processes. Simultaneous run of the two models imply that the disturbance on parameters in PFP will have a direct effect on CW processes. The model was formulated on the basis fundamental principle that the growth of active biomass in the system defines the transformation of organic carbon. The growth rate of microorganisms was model based on the Monod kinetic equation. The forcing functions to the model were formulated based on multiplicative function. The removal of organic carbon in the FP based on the unfiltered sample was 66% with an average concentration of 206 mg COD/l in the effluent. The removal of organic carbon in the CW was 87.5% with an average concentration of 40 mg COD/l in the effluent. The overall performance of the coupled model was 93%. The main processes of organic carbon removal in the FP and CW were due to uptake by heterotrophic bacteria followed by oxidation. It was found that 80% of the total organic carbon in the CW was due to the biological growth. Oxidation of organic carbon in the PFP was a source of high growth of algae. The constants and coefficients obtained after validation of the model reflect the simultaneous performance of the coupled model of PFP and CW.

  1. Empirical Sewer Water Quality Model for Generating Influent Data for WWTP Modelling

    NARCIS (Netherlands)

    Langeveld, J.G.; van Daal-Rombouts, P.M.M.; Schilperoort, Remy; Nopens, Ingmar; Flameling, Tony; Weijers, Stefan

    2017-01-01

    Wastewater treatment plants (WWTP) typically have a service life of several decades. During this service life, external factors, such as changes in the effluent standards or the loading of the WWTP may change, requiring WWTP performance to be optimized. WWTP modelling is widely accepted as a means

  2. [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.

  3. 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.

  4. A modeling study of the impacts of Mississippi River diversion and sea-level rise on water quality of a deltaic estuary

    Science.gov (United States)

    Wang, Hongqing; Chen, Qin; Hu, Kelin; LaPeyre, Megan K.

    2017-01-01

    Freshwater and sediment management in estuaries affects water quality, particularly in deltaic estuaries. Furthermore, climate change-induced sea-level rise (SLR) and land subsidence also affect estuarine water quality by changing salinity, circulation, stratification, sedimentation, erosion, residence time, and other physical and ecological processes. However, little is known about how the magnitudes and spatial and temporal patterns in estuarine water quality variables will change in response to freshwater and sediment management in the context of future SLR. In this study, we applied the Delft3D model that couples hydrodynamics and water quality processes to examine the spatial and temporal variations of salinity, total suspended solids, and chlorophyll-α concentration in response to small (142 m3 s−1) and large (7080 m3 s−1) Mississippi River (MR) diversions under low (0.38 m) and high (1.44 m) relative SLR (RSLR = eustatic SLR + subsidence) scenarios in the Breton Sound Estuary, Louisiana, USA. The hydrodynamics and water quality model were calibrated and validated via field observations at multiple stations across the estuary. Model results indicate that the large MR diversion would significantly affect the magnitude and spatial and temporal patterns of the studied water quality variables across the entire estuary, whereas the small diversion tends to influence water quality only in small areas near the diversion. RSLR would also play a significant role on the spatial heterogeneity in estuary water quality by acting as an opposite force to river diversions; however, RSLR plays a greater role than the small-scale diversion on the magnitude and spatial pattern of the water quality parameters in this deltaic estuary.

  5. Laurentian Great Lakes Phytoplankton and Their Water Quality Characteristics, Including a Diatom-Based Model for Paleoreconstruction of Phosphorus

    Science.gov (United States)

    Reavie, Euan D.; Heathcote, Adam J.; Shaw Chraïbi, Victoria L.

    2014-01-01

    Recent shifts in water quality and food web characteristics driven by anthropogenic impacts on the Laurentian Great Lakes warranted an examination of pelagic primary producers as tracers of environmental change. The distributions of the 263 common phytoplankton taxa were related to water quality variables to determine taxon-specific responses that may be useful in indicator models. A detailed checklist of taxa and their environmental optima are provided. Multivariate analyses indicated a strong relationship between total phosphorus (TP) and patterns in the diatom assemblages across the Great Lakes. Of the 118 common diatom taxa, 90 (76%) had a directional response along the TP gradient. We further evaluated a diatom-based transfer function for TP based on the weighted-average abundance of taxa, assuming unimodal distributions along the TP gradient. The r2 between observed and inferred TP in the training dataset was 0.79. Substantial spatial and environmental autocorrelation within the training set of samples justified the need for further model validation. A randomization procedure indicated that the actual transfer function consistently performed better than functions based on reshuffled environmental data. Further, TP was minimally confounded by other environmental variables, as indicated by the relatively large amount of unique variance in the diatoms explained by TP. We demonstrated the effectiveness of the transfer function by hindcasting TP concentrations using fossil diatom assemblages in a Lake Superior sediment core. Passive, multivariate analysis of the fossil samples against the training set indicated that phosphorus was a strong determinant of historical diatom assemblages, verifying that the transfer function was suited to reconstruct past TP in Lake Superior. Collectively, these results showed that phytoplankton coefficients for water quality can be robust indicators of Great Lakes pelagic condition. The diatom-based transfer function can be used in

  6. 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.

  7. 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.

  8. 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.

  9. Development of the Hydrodynamic Model for Long-Term Simulation of Water Quality Processes of the Tidal James River, Virginia

    Directory of Open Access Journals (Sweden)

    Jian Shen

    2016-11-01

    Full Text Available Harmful algal blooms (HABs have frequently occurred in the James River. The State has convened a Scientific Advisory Panel (SAP to review the James River chlorophyll-a standards. The SAP will conduct a scientific study to review the basis for setting the chlorophyll-a standards. To support the SAP study of chlorophyll-a standards, the State of Virginia has decided to develop a numerical modeling system that is capable of simulating phytoplankton and HABs. The modeling system includes a watershed model, a three-dimensional hydrodynamic model and water quality models. The focus of this study will be on the development and verification of the hydrodynamic model. In order to simulate the complex geometry of the James River, a high-resolution model has been implemented. The model has been calibrated for a long-term period of 23 years. A series of model experiments was conducted to evaluate the impact of forcings on dynamic simulation and transport time. It was found that freshwater discharge is the most sensitive for an accurate simulation of salinity and transport time. The water age predicted by the model in the tidal freshwater region represents the fluctuation of transport processes, and it has a good correlation with the algal bloom, while at the downstream, the transport time simulation agrees with the delay of the HAB in the mesohaline of the James after the HAB occurred in the Elizabeth River due to the transport processes. The results indicate that the hydrodynamic model is capable of simulating the dynamic processes of the James and driving water quality models in the James River.

  10. Using LiDAR datasets to improve HSPF water quality modeling in the Red River of the North Basin

    Science.gov (United States)

    Burke, M. P.; Foreman, C. S.

    2013-12-01

    The Red River of the North Basin (RRB), located in the lakebed of ancient glacial Lake Agassiz, comprises one of the flattest landscapes in North America. The topography of the basin, coupled with the Red River's direction of flow from south to north results in a system that is highly susceptible to flooding. The magnitude and frequency of flood events in the RRB has prompted several multijurisdictional projects and mitigation efforts. In response to the devastating 1997 flood, an International Joint Commission sponsored task force established the need for accurate elevation data to help improve flood forecasting and better understand risks. This led to the International Water Institute's Red River Basin Mapping Initiative, and the acquisition LiDAR Data for the entire US portion of the RRB. The resulting 1 meter bare earth digital elevation models have been used to improve hydraulic and hydrologic modeling within the RRB, with focus on flood prediction and mitigation. More recently, these LiDAR datasets have been incorporated into Hydrological Simulation Program-FORTRAN (HSPF) model applications to improve water quality predictions in the MN portion of the RRB. RESPEC is currently building HSPF model applications for five of MN's 8-digit HUC watersheds draining to the Red River, including: the Red Lake River, Clearwater River, Sandhill River, Two Rivers, and Tamarac River watersheds. This work is being conducted for the Minnesota Pollution Control Agency (MPCA) as part of MN's statewide watershed approach to restoring and protecting water. The HSPF model applications simulate hydrology (discharge, stage), as well as a number of water quality constituents (sediment, temperature, organic and inorganic nitrogen, total ammonia, organic and inorganic phosphorus, dissolved oxygen and biochemical oxygen demand, and algae) continuously for the period 1995-2009 and are formulated to provide predictions at points of interest within the watersheds, such as observation gages

  11. 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.

  12. Water Quality Monitoring Sites

    Data.gov (United States)

    Vermont Center for Geographic Information — Water Quality Monitoring Site identifies locations across the state of Vermont where water quality data has been collected, including habitat, chemistry, fish and/or...

  13. Water Quality Monitoring

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Our water quality sampling program is to determine the quality of Moosehorn's lakes and a limited number of streams. Water quality is a measure of the body of water,...

  14. 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.

  15. 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.

  16. Reactive transport modeling of geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN

    Science.gov (United States)

    Ng, Gene-Hua Crystal.; Bekins, Barbara A.; Cozzarelli, Isabelle M.; Baedecker, Mary Jo; Bennett, Philip C.; Amos, Richard T.; Herkelrath, William N.

    2015-01-01

    Anaerobic biodegradation of organic amendments and contaminants in aquifers can trigger secondary water quality impacts that impair groundwater resources. Reactive transport models help elucidate how diverse geochemical reactions control the spatiotemporal evolution of these impacts. Using extensive monitoring data from a crude oil spill site near Bemidji, Minnesota (USA), we implemented a comprehensive model that simulates secondary plumes of depleted dissolved O2 and elevated concentrations of Mn2+, Fe2+, CH4, and Ca2+ over a two-dimensional cross section for 30 years following the spill. The model produces observed changes by representing multiple oil constituents and coupled carbonate and hydroxide chemistry. The model includes reactions with carbonates and Fe and Mn mineral phases, outgassing of CH4 and CO2 gas phases, and sorption of Fe, Mn, and H+. Model results demonstrate that most of the carbon loss from the oil (70%) occurs through direct outgassing from the oil source zone, greatly limiting the amount of CH4 cycled down-gradient. The vast majority of reduced Fe is strongly attenuated on sediments, with most (91%) in the sorbed form in the model. Ferrous carbonates constitute a small fraction of the reduced Fe in simulations, but may be important for furthering the reduction of ferric oxides. The combined effect of concomitant redox reactions, sorption, and dissolved CO2 inputs from source-zone degradation successfully reproduced observed pH. The model demonstrates that secondary water quality impacts may depend strongly on organic carbon properties, and impacts may decrease due to sorption and direct outgassing from the source zone.

  17. Modelling water quality and quantity with the influence of inter-basin water diversion projects and cascade reservoirs in the Middle-lower Hanjiang River

    Science.gov (United States)

    Wang, Yonggui; Zhang, Wanshun; Zhao, Yanxin; Peng, Hong; Shi, Yingyuan

    2016-10-01

    The effects of inter-basin water diversion projects and cascade reservoirs are typically complex and challenging, as the uncertain temporal-spatial variation of both water quality and quantity. The purpose of this paper is to propose a coupled 1D hydrodynamic model with water-quality model to analyze the effects of current and future inter-basin water diversion projects, i.e., South-to-North Water Diversion Project (SNWD) and Yangtze-Hanjiang Water Diversion Project (YHWD), and cascade reservoirs (CRS) on water quantity and quality in the middle-lower Hanjiang River. Considering water use and pollution contribution, the middle-lower Hanjaing River basin is generalized and divided into 18 land use units with tributaries, reservoirs and water exchanges. Each unit is considered with the processes of lateral inflow, point and non-point pollution loads, irrigation return flow, and stream-aquifer exchanges in the model. The long-term time series from 1956 to 1998 of water quality and quantity with four engineering scenarios is collected. The validation of results shows that the relative errors between the simulated and observed values at certain control sections are within 5% for water levels and 20% for water quality. The water level will be decreased by 0.38-0.65 m (decreasing rate 0.44-2.68%), the annual runoff will be significantly decreased over 4 billion m3 and the water quality will be changed after the SNWD. As a compensation project, the YHWD partly offsets the negative effects of the SNWD in water flow rate, but at the same time it rises the water level and reduces the flow velocity. This, together with the effect of cascade reservoirs, leads to water quality concentration increasing and deteriorating to Grade IV of the Chinese Surface Water Quality Criteria. The water resource reduction and water quality problems in the Middle-lower Hanjiang River require attention after these projects.

  18. 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...

  19. 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.

  20. 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

  1. Modelling the water quality in dams within the Umgeni Water operational area with emphasis on algal relations / Philip Mark Graham

    OpenAIRE

    Graham, Philip Mark

    2007-01-01

    Based on many years of water quality (including algal) and water treatment cost data, available at Umgeni Water, a study was undertaken to better understand the water quality relationships in man made lakes within the company's operational area, and to investigate how water quality affected the cost of treating water from these lakes. The broad aims to the study were to: identify the key environmental variables that were affecting algal populations in lakes; and if these wer...

  2. 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

  3. Analysis of parameter sensitivity and identifiability of root zone water quality model (RZWQM) for dryland sugerbeet modeling

    Science.gov (United States)

    Sugarbeet is being considered as one of the most viable feedstock alternatives to corn for biofuel production since herbicide resistant energy beets were deregulated by USDA in 2012. Growing sugarbeets for biofuel production may have significant impacts on soil health and water quality in the north-...

  4. Calibration, verification, and use of a water-quality model to simulate effects of discharging treated wastewater to the Red River of the North at Fargo, North Dakota

    Science.gov (United States)

    Wesolowski, E.A.

    1994-01-01

    A 30.8-mile reach of the Red River of the North receives treated wastewater from plants at Fargo, North Dakota, and Moorhead, Minnesota, and streamflows from the Sheyenne River. A one-dimensional, steady-state, stream water-quality model, the Enhanced Stream Water Quality Model (QUAL2E), was calibrated and verified for summer stream flow conditions to simulate some of the biochemical processes that result from discharging treated wastewater into this reach of the river. Data obtained to define the river's transport conditions are measurements of channel geometry, streamflow, traveltime, specific conductance, and temperature. Data obtained to define the river's water-quality conditions are measurements of concentrations of selected water-quality constituents and estimates of various reaction coefficients. Most of the water-quality data used to calibrate and verify the model were obtained during two synoptic samplings in August 1989 and August 1990. The water-quality model simulates specific conductance, water temperature, dissolved oxygen, ultimate carbonaceous biochemical oxygen demand, total nitrite plus nitrate as nitrogen, total ammonia as nitrogen, total organic nitrogen as nitrogen, total phosphorus as phosphorus, and algal biomass as chlorophyll a. Of the nine properties and constituents that the calibrated model simulates, all except algae were verified. When increases in dissolved-oxygen concentration are considered, model sensitivity analyses indicate that dissolved-oxygen concentration is most sensitive to maximum specific algal growth rate. When decreases in dissolved-oxygen concentration are considered, model sensitivity analyses indicate that dissolved-oxygen concentration is most sensitive to point-source ammonia. Model simulations indicate nitrification and sediment oxygen demand consume most of the dissolved oxygen in the study reach. The Red River at Fargo Water-Quality Model and the verification data set, including associated reaction

  5. Modeling of nonpoint-source water quality in urban and non-urban areas

    Energy Technology Data Exchange (ETDEWEB)

    Donigian, A.S.; Huber, W.C.

    1991-06-01

    Nonpoint source assessment procedures and modeling techniques are reviewed and discussed for both urban and non-urban land areas. Detailed reviews of specific methodologies and models are presented, along with overview discussions focusing on urban methods and models, and on non-urban (primarily agricultural) methods and models. Simple procedures, such as constant concentration, regression, statistical, and loading function approaches are described, along with complex models such as SWMM, HSPF, STORM, CREAMS, SWRRB, and others. Brief case studies of ongoing and recently completed modeling efforts are described. Recommendations for nonpoint runoff quality modeling are presented to elucidate expected directions of future modeling efforts.

  6. Model documentation for relations between continuous real-time and discrete water-quality constituents in Indian Creek, Johnson County, Kansas, June 2004 through May 2013

    Science.gov (United States)

    Stone, Mandy L.; Graham, Jennifer L.

    2014-01-01

    Johnson County is the fastest growing county in Kansas, with a population of about 560,000 people in 2012. Urban growth and development can have substantial effects on water quality, and streams in Johnson County are affected by nonpoint-source pollutants from stormwater runoff and point-source discharges such as municipal wastewater effluent. Understanding of current (2014) water-quality conditions and the effects of urbanization is critical for the protection and remediation of aquatic resources in Johnson County, Kansas and downstream reaches located elsewhere. The Indian Creek Basin is 194 square kilometers and includes parts of Johnson County, Kansas and Jackson County, Missouri. Approximately 86 percent of the Indian Creek Basin is located in Johnson County, Kansas. The U.S. Geological Survey, in cooperation with Johnson County Wastewater, operated a series of six continuous real-time water-quality monitoring stations in the Indian Creek Basin during June 2011 through May 2013; one of these sites has been operating since February 2004. Five monitoring sites were located on Indian Creek and one site was located on Tomahawk Creek. The purpose of this report is to document regression models that establish relations between continuously measured water-quality properties and discretely collected water-quality constituents. Continuously measured water-quality properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, turbidity, and nitrate. Discrete water-quality samples were collected during June 2011 through May 2013 at five new sites and June 2004 through May 2013 at a long-term site and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to estimate concentrations of those constituents of interest that are not easily measured in real time

  7. A grid enabled Monte Carlo hyperspectral synthetic image remote sensing model (GRID-MCHSIM) for coastal water quality algorithm

    Science.gov (United States)

    Chiang, Gen-Tao; Dove, Martin; Ballard, Stuart; Bostater, Charles; Frame, Ian

    2006-09-01

    Previous studies indicate that parallel computing for hyperspectral remote sensing image generation is feasible. However, due to the limitation of computing ability within single cluster, one can only generate three bands and a 1000*1000 pixels image in a reasonable time. In this paper, we discuss the capability of using Grid computing where the so-called eScience or cyberinfrastructure is utilized to integrate distributed computing resources to act as a single virtual computer with huge computational abilities and storage spaces. The technique demonstrated in this paper demonstrates the feasibility of a Grid-Enabled Monte Carlo Hyperspectral Synthetic Image Remote Sensing Model (GRID-MCHSIM) for coastal water quality algorithm.

  8. 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

    in the Pareja Limno-reservoir and a switch from an oligo-mesotrophic to a mesotrophic state, which may threaten the maintenance of a favourable water quality. Our model framework may help water managers to assess and manage how climate change affects aquatic ecosystems.......Water scarcity and water pollution constitute a big challenge for water managers in the Mediterranean region today and will exacerbate in a projected future warmer world, making a holistic approach for water resources management at the catchment scale essential. We expanded the Soil and Water...... 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...

  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. A review of sediment and nutrient concentration data from Australia for use in catchment water quality models.

    Science.gov (United States)

    Bartley, Rebecca; Speirs, William J; Ellis, Tim W; Waters, David K

    2012-01-01

    Land use (and land management) change is seen as the primary factor responsible for changes in sediment and nutrient delivery to water bodies. Understanding how sediment and nutrient (or constituent) concentrations vary with land use is critical to understanding the current and future impact of land use change on aquatic ecosystems. Access to appropriate land-use based water quality data is also important for calculating reliable load estimates using water quality models. This study collated published and unpublished runoff, constituent concentration and load data for Australian catchments. Water quality data for total suspended sediments (TSS), total nitrogen (TN) and total phosphorus (TP) were collated from runoff events with a focus on catchment areas that have a single or majority of the contributing area under one land use. Where possible, information on the dissolved forms of nutrients were also collated. For each data point, information was included on the site location, land use type and condition, contributing catchment area, runoff, laboratory analyses, the number of samples collected over the hydrograph and the mean constituent concentration calculation method. A total of ∼750 entries were recorded from 514 different geographical sites covering 13 different land uses. We found that the nutrient concentrations collected using "grab" sampling (without a well defined hydrograph) were lower than for sites with gauged auto-samplers although this data set was small and no statistical analysis could be undertaken. There was no statistically significant difference (pland use. This is most likely due to differences in land condition over-shadowing the effects of spatial scale. There was, however, a significant difference in the concentration value for constituent samples collected from sites where >90% of the catchment was represented by a single land use, compared to sites with land use. This highlights the need for more single land use water quality data

  11. 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

    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...

  12. Estuarine water quality in parks of the Northeast Coastal and Barrier Network: vital signs estuarine nutrient-enrichment monitoring, 2006-11

    Science.gov (United States)

    Caldwell, James M.; Nixon, Matthew E.; Neckles, Hilary A.; Pooler, Penelope S.

    2015-01-01

    This report summarizes results of water-quality monitoring within estuaries of the National Park Service Northeast Coastal and Barrier Network (NCBN) from 2006 through 2011. Data collection formed part of the NCBN Vital Signs Monitoring Program implemented to detect threats of estuarine nutrient enrichment. Data included here were collected from six parks at predetermined intervals: Cape Cod National Seashore, Massachusetts (2007, 2008, 2009, 2010, 2011); Fire Island National Seashore, New York (2009, 2011); Gateway National Recreation Area, New York and New Jersey (2010); Assateague Island National Seashore, Maryland and Virginia (2006, 2008, 2010); George Washington Birthplace National Monument, Virginia (2009, 2011); and Colonial National Historic Park, Virginia (2008, 2010). Monitoring variables consisted of dissolved-oxygen concentration, chlorophyll a concentration, attenuation of downwelling photosynthetically available radiation (PAR), turbidity, water temperature, and salinity. All monitoring was conducted during four-week summer index periods. The monitoring design incorporated data collection at multiple, complementary spatial and temporal scales. Within each park, a spatial survey was conducted once during the index period following a probability design using a grid of tessellated hexagons as the basis for sample site selection. The spatial survey was supplemented with weekly measurements at a subset of sites and continuous monitoring at a single reference site. Within parks, data were reported as area-weighted water-quality conditions during each index period, the location and extent of estuarine area within condition categories, and spatial and temporal trends. In addition, we used a repeated measures analysis of variance to determine the extent to which variability in three water quality metrics (chlorophyll a in surface water, dissolved oxygen in bottom water, and water clarity expressed by PAR attenuation) was explained by year to year changes in

  13. A component-based, integrated spatially distributed hydrologic/water quality model: AgroEcoSystem-Watershed (AgES-W) overview and application

    Science.gov (United States)

    AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality simulation components. The AgES-W model was previously evaluated for streamflow and recently has been enhanced with the addition of nitrogen (N) and sediment modeling compo...

  14. Scaling up food production in the Upper Mississippi river basin: modeling impacts on water quality and nutrient cycling

    Science.gov (United States)

    Bowen, E. E.; Martin, P. A.; Schuble, T. J.; Yan, E.; Demissie, Y.

    2010-12-01

    Agricultural production imposes significant environmental stress on the landscape, both in the intensity and extent of agricultural activities. Among the most significant impacts, agriculture dominates the natural reactive nitrogen cycle, with excess reactive nitrogen leading to the degraded quality of inland and coastal waters. In the U.S., policymakers and stakeholders nationwide continue to debate strategies for decreasing environmental degradation from agricultural lands. Such strategies aim to optimize the balance among competing demands for food, fuel and ecosystem services. One such strategy increasingly discussed in the national debate is that of localizing food production around urban areas, developing what some have recently called “foodsheds”. However, the environmental impacts of localizing food production around population centers are not well-understood given the hard-to-generalize variety seen in management practices currently employed among local farms marketing food crops directly to consumers. As a first, landscape level study of potential impacts from scaling up this type of agriculture, we use the USDA Soil and Water Assessment Tool (SWAT) model to quantify environmental impacts from developing foodsheds for all population centers in the Upper Mississippi river basin. Specifically, we focus on nutrient cycling and water quality impacts determining direct greenhouse gas emissions and changes to nutrient runoff from increased food production in this watershed. We investigate a variety of scenarios in which food production is scaled up to the regional level using different types of farm management practices, ranging from conventional production of fruits and vegetables, to production of these products from small-scale, diversified systems integrating conservation easements. In addition to impacts on nutrient cycling and water quality, we also characterize relative levels of productivity in conjunction with overall demand for food associated

  15. Water age prediction and its potential impacts on water quality using a hydrodynamic model for Poyang Lake, China.

    Science.gov (United States)

    Qi, Hengda; Lu, Jianzhong; Chen, Xiaoling; Sauvage, Sabine; Sanchez-Pérez, José-Miguel

    2016-07-01

    The water quality in Poyang Lake, the largest freshwater lake in China, has deteriorated steadily in recent years and local governments have made efforts to manage the potential eutrophication. In order to investigate the transport and retention processes of dissolved substances, the hydrodynamic model, Environmental Fluid Dynamics Code (EFDC) was applied by using the concept of water age. The simulated results showed agreement with the measured water level, discharge, and inundation area. The water age in Poyang Lake was significantly influenced by the variations of hydrological conditions. The annual analysis revealed that the largest averaged water age was observed during the wet year (2010) with 28.4 days at Hukou, the junction of the Yangtze River and Poyang Lake. In the normal season (April), the youngest age with 9.1 days was found. The spatial distribution of water quality derived from the remote sensing images suggested that a higher chlorophyll-a concentration, lower turbidity, and smaller water age in the eastern area of Poyang Lake might threaten the regional aquatic health. The particle tracking simulation reproduced the trajectories of the dissolved substances, indicating that the water mass with greater nutrient loading would further lead to potential environmental problems in the east lake. Moreover, the water transfer ability would be weakened due to dam (Poyang Project) construction resulting in the rising water levels in periods of regulation. Generally, this study quantified an indicative transport timescale, which could help to better understand the complex hydrodynamic processes and manage wetland ecosystems similar to Poyang Lake.

  16. 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.

  17. Water Quality Research Program. A Model of Manganese and Iron Fluxes from Sediments

    Science.gov (United States)

    1994-07-01

    set equal to s = SODIO 2(0), the ratio of the sediment oxygen demand and the overlying water dissolved oxygen concentration, as in the previous models...seasonal variations are reproduced up to 32X. Since the manganese model requires the surface mass transfer coefficient: s = SODIO 2(0), it is important

  18. COMPUTER MODELING OF SELECTED WATER QUALITY PARAMETERS IN WATER DISTRIBUTION SYSTEMS

    Directory of Open Access Journals (Sweden)

    Wojciech Kruszyński

    2016-06-01

    Full Text Available The paper presents the results of computer modeling of flowsand the age of the water in two rural communi-ties province Podlasie - Rutka and Jeleniewo. The model is made using Epanet. In the study, a series of variants of models simulating the behavior of existing distribution systems and water analyzes were performed century. Analysis of the age of the water in water works modeled showed areas where standing water is aging, not having the estuary and not giving way to fresh. Age of water in the pipes is an important indicator of its quality and shelf life. The longer standing water in the aqueduct, the more likely that it will develop dangerous bacteria and produce deposits which remain on the walls of the ducts.

  19. Application of the Root Zone Water Quality Model (RZWQM) to pesticide fate and transport: an overview.

    Science.gov (United States)

    Malone, Robert W; Ahuja, Lajpat R; Ma, Liwang; Wauchope, R Don; Ma, Qingli; Rojas, Kenneth W

    2004-03-01

    Pesticide transport models are tools used to develop improved pesticide management strategies, study pesticide processes under different conditions (management, soils, climates, etc) and illuminate aspects of a system in need of more field or laboratory study. This paper briefly overviews RZWQM history and distinguishing features, overviews key RZWQM components and reviews RZWQM validation studies. RZWQM is a physically based agricultural systems model that includes sub-models to simulate: infiltration, runoff, water distribution and chemical movement in the soil; macropore flow and chemical movement through macropores; evapotranspiration (ET); heat transport; plant growth; organic matter/nitrogen cycling; pesticide processes; chemical transfer to runoff; and the effect of agricultural management practices on these processes. Research to date shows that if key input parameters are calibrated, RZWQM can adequately simulate the processes involved with pesticide transport (ET, soil-water content, percolation and runoff, plant growth and pesticide fate). A review of the validation studies revealed that (1) accurate parameterization of restricting soil layers (low permeability horizons) may improve simulated soil-water content; (2) simulating pesticide sorption kinetics may improve simulated soil pesticide concentration with time (persistence) and depth and (3) calibrating the pesticide half-life is generally necessary for accurate pesticide persistence simulations. This overview/review provides insight into the processes involved with the RZWQM pesticide component and helps identify model weaknesses, model strengths and successful modeling strategies.

  20. 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.

  1. 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

  2. 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.

  3. Stochastic runoff connectivity (SRC) equations: integration with erosion models for water quality prediction

    Science.gov (United States)

    Sheridan, G.; Jones, O. D.; Smith, H.; Cawson, J.; Lane, P. J.

    2009-04-01

    In a companion paper at this conference a single-event steady-state rainfall-runoff model (including runoff-runon phenomena) is derived that quantifies the effect of the random spatial arrangement of rainfall and soil properties on i) infiltration-excess runoff delivery at a downslope boundary, and ii) the distribution of the "connected length" (the upslope length with a continuous runoff pathway adjacent to the stream boundary). The accumulation and loss of runoff down a slope is represented as a first-in first-out (FIFO) GI/G/1 queuing system. Runoff rate at a downslope boundary is analogous to the waiting time in the queue in this representation. The distribution of connected length can be represented analytically as a FIFO M/M/1 queuing system, and the mean and variance is derived for this property. Together these distributions characterise the degree of connectivity of the overland flow pathway (and by extension its associated pollutant load) for a given set of rainfall and soil conditions. In this poster, the stochastic runoff connectivity (SRC) model is developed further. We show how the probabilistic SRC model outputs i) and ii) above can be integrated with physically based hillslope scale surface erosion models to predict the probability distribution of constituent (sediment, phosphorous, etc) delivery to the stream boundary. The performance of the model is compared to 2 years of multi-length erosion plot data, and 3 years of continuous small catchment export data from SE Australian forests.

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

    DEFF Research Database (Denmark)

    Bastrup-Birk, A.; Gundersen, P.

    2004-01-01

    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...... (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...

  5. 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...

  6. 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

  7. 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 DMA-sized drinking water distribution system was onstructed with two types of demand allocations. One is constructed with the conventional op-down approach, i.e. a demand multiplier pattern from the booster station is llocated to all demand nodes with a correction

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

    African Journals Online (AJOL)

    2009-02-06

    Feb 6, 2009 ... A spreadsheet-based model was developed in this study specifically to assist in ..... application of removal efficiency of RB intervention to the total ... The product of the sediment load and the efficiency of control measures yields the loads reduced. Rainwater tanks (RT) intervention: Use of rainwater tanks.

  9. 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...

  10. 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...

  11. 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...

  12. Risk Assessment of New Chemical Substances. Applicability of EXAMS II as an advanced Water Quality Model

    NARCIS (Netherlands)

    de Nijs ACM; Burns LA

    1990-01-01

    In the cluster project "Risk Assessment of New Chemical Substances methods are developed to systematically predict and assess the hazards for man and environment. After the basic screening of a substance has been carried out, a more extensive study can be performed using models adhered to the

  13. 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...... consumption (endogenous activity, nitrite and ammonium oxidation) and N2O production (NN, ND and HD pathway contributions). To estimate parameters of the N2O model a rigorous procedure is presented as a case study. The calibrated model predicts the NO and N2O dynamics at varying ammonium, nitrite...... and dissolved oxygen levels in two independent systems: (a) an AOB-enriched biomass and (b) activated sludge (AS) mixed liquor biomass. A total of ten (a) and seventeen (b) parameters are identified with high accuracy (coefficients of variation

  14. A river water quality model for time varying BOD discharge concentration

    Directory of Open Access Journals (Sweden)

    Oppenheimer Seth F.

    1999-01-01

    Full Text Available We consider a model for biochemical oxygen demand (BOD in a semi-infinite river where the BOD is prescribed by a time varying function at the left endpoint. That is, we study the problem with a time varying boundary loading. We obtain the well-posedness for the model when the boundary loading is smooth in time. We also obtain various qualitative results such as ordering, positivity, and boundedness. Of greatest interest, we show that a periodic loading function admits a unique asymptotically attracting periodic solution. For non-smooth loading functions, we obtain weak solutions. Finally, for certain special cases, we show how to obtain explicit solutions in the form of infinite series.

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

    Science.gov (United States)

    2016-07-01

    anthropogenic pollutants. WASP-Eutro simulates the biogeochemical processes of aquatic plant growth and their response to nutrients (nitrogen and phosphorous...of the EFDC model was to ensure that the simulated water surface elevation, salinity , and temperature are in agreement with the corresponding data...freshwater sources and tidal exchange with the ocean. The salinity and temperatures data measured at Del Mar by Scripps Institution of Oceanography

  16. Application of a Water Quality Model to Mississippi Sound to Evaluate Impacts of Freshwater Diversions

    Science.gov (United States)

    2007-09-01

    prepared this report. Dortch served as the model study POC, and Dr. Barbara Kleiss of the Wetlands and Coastal Ecology Branch, Ecosystem Evaluation...dunes, seawalls, and levees onshore; development of surge mitigation measures; wetland and ecosystem restoration; barrier island and beach restoration...ortho- phosphate phosphorus ( PO4 ), and total suspended solids (TSS). ERDC/EL TR-07-20 10 All variables were not available for all sampling dates

  17. 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...

  18. Uncertainty assessment of water quality modeling for a small-scale urban catchment using the GLUE methodology: a case study in Shanghai, China.

    Science.gov (United States)

    Zhang, Wei; Li, Tian; Dai, Meihong

    2015-06-01

    There is often great uncertainty in water quality modeling for urban drainage systems because water quality variation in systems is complex and affected by many factors. The stormwater management model (SWMM) was applied to a small-scale urban catchment with a simple and well-maintained stormwater drainage system without illicit connections. This was done to assess uncertainty in build-up and wash-off modeling of pollutants within the generalized likelihood uncertainty estimation (GLUE) methodology, based on a well-calibrated water quantity model. The results indicated great uncertainty of water quality modeling within the GLUE methodology. Comparison of uncertainties in various pollutant build-up and wash-off models that were available in SWMM indicated that those uncertainties varied slightly. This may be a consequence of the specific characteristics of rainfall events and experimental sites used in the study. The uncertainty analysis of water quality parameters in SWMM is conducive to effectively evaluating model reliability, and provides an experience base for similar research and applications.

  19. 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.

  20. The Huaihe Basin Water Resource and Water Quality Management Platform Implemented with a Spatio-Temporal Data Model

    Science.gov (United States)

    Liu, Y.; Zhang, W.; Yan, C.

    2012-07-01

    Presently, planning and assessment in maintenance, renewal and decision-making for watershed hydrology, water resource management and water quality assessment are evolving toward complex, spatially explicit regional environmental assessments. These problems have to be addressed with object-oriented spatio-temporal data models that can restore, manage, query and visualize various historic and updated basic information concerning with watershed hydrology, water resource management and water quality as well as compute and evaluate the watershed environmental conditions so as to provide online forecasting to police-makers and relevant authorities for supporting decision-making. The extensive data requirements and the difficult task of building input parameter files, however, has long been an obstacle to use of such complex models timely and effectively by resource managers. Success depends on an integrated approach that brings together scientific, education and training advances made across many individual disciplines and modified to fit the needs of the individuals and groups who must write, implement, evaluate, and adjust their watershed management plans. The centre for Hydro-science Research, Nanjing University, in cooperation with the relevant watershed management authorities, has developed a WebGIS management platform to facilitate this complex process. Improve the management of watersheds over the Huaihe basin through the development, promotion and use of a web-based, user-friendly, geospatial watershed management data and decision support system (WMDDSS) involved many difficulties for the development of this complicated System. In terms of the spatial and temporal characteristics of historic and currently available information on meteorological, hydrological, geographical, environmental and other relevant disciplines, we designed an object-oriented spatiotemporal data model that combines spatial, attribute and temporal information to implement the management

  1. THE HUAIHE BASIN WATER RESOURCE AND WATER QUALITY MANAGEMENT PLATFORM IMPLEMENTED WITH A SPATIO-TEMPORAL DATA MODEL

    Directory of Open Access Journals (Sweden)

    Y. Liu

    2012-07-01

    Full Text Available Presently, planning and assessment in maintenance, renewal and decision-making for watershed hydrology, water resource management and water quality assessment are evolving toward complex, spatially explicit regional environmental assessments. These problems have to be addressed with object-oriented spatio-temporal data models that can restore, manage, query and visualize various historic and updated basic information concerning with watershed hydrology, water resource management and water quality as well as compute and evaluate the watershed environmental conditions so as to provide online forecasting to police-makers and relevant authorities for supporting decision-making. The extensive data requirements and the difficult task of building input parameter files, however, has long been an obstacle to use of such complex models timely and effectively by resource managers. Success depends on an integrated approach that brings together scientific, education and training advances made across many individual disciplines and modified to fit the needs of the individuals and groups who must write, implement, evaluate, and adjust their watershed management plans. The centre for Hydro-science Research, Nanjing University, in cooperation with the relevant watershed management authorities, has developed a WebGIS management platform to facilitate this complex process. Improve the management of watersheds over the Huaihe basin through the development, promotion and use of a web-based, user-friendly, geospatial watershed management data and decision support system (WMDDSS involved many difficulties for the development of this complicated System. In terms of the spatial and temporal characteristics of historic and currently available information on meteorological, hydrological, geographical, environmental and other relevant disciplines, we designed an object-oriented spatiotemporal data model that combines spatial, attribute and temporal information to implement

  2. Improving catchment scale water quality modelling with continuous high resolution monitoring of metals in runoff

    Science.gov (United States)

    Saari, Markus; Rossi, Pekka; Blomberg von der Geest, Kalle; Mäkinen, Ari; Postila, Heini; Marttila, Hannu

    2017-04-01

    High metal concentrations in natural waters is one of the key environmental and health problems globally. Continuous in-situ analysis of metals from runoff water is technically challenging but essential for the better understanding of processes which lead to pollutant transport. Currently, typical analytical methods for monitoring elements in liquids are off-line laboratory methods such as ICP-OES (Inductively Coupled Plasma Optical Emission Spectroscopy) and ICP-MS (ICP combined with a mass spectrometer). Disadvantage of the both techniques is time consuming sample collection, preparation, and off-line analysis at laboratory conditions. Thus use of these techniques lack possibility for real-time monitoring of element transport. We combined a novel high resolution on-line metal concentration monitoring with catchment scale physical hydrological modelling in Mustijoki river in Southern Finland in order to study dynamics of processes and form a predictive warning system for leaching of metals. A novel on-line measurement technique based on micro plasma emission spectroscopy (MPES) is tested for on-line detection of selected elements (e.g. Na, Mg, Al, K, Ca, Fe, Ni, Cu, Cd and Pb) in runoff waters. The preliminary results indicate that MPES can sufficiently detect and monitor metal concentrations from river water. Water and Soil Assessment Tool (SWAT) catchment scale model was further calibrated with high resolution metal concentration data. We show that by combining high resolution monitoring and catchment scale physical based modelling, further process studies and creation of early warning systems, for example to optimization of drinking water uptake from rivers, can be achieved.

  3. A model for predicting daily peak visitation and implications for recreation management and water quality: evidence from two rivers in Puerto Rico.

    Science.gov (United States)

    Santiago, Luis E; Gonzalez-Caban, Armando; Loomis, John

    2008-06-01

    Visitor use surveys and water quality data indicates that high visitor use levels of two rivers in Puerto Rico does not appear to adversely affect several water quality parameters. Optimum visitor use to maximize visitor defined satisfaction is a more constraining limit on visitor use than water quality. Our multiple regression analysis suggests that visitor use of about 150 visitors per day yields the highest level of visitor reported satisfaction, a level that does not appear to affect turbidity of the river. This high level of visitor use may be related to the gregarious nature of Puerto Ricans and their tolerance for crowding on this densely populated island. The daily peak visitation model indicates that regulating the number of parking spaces may be the most effective way to keep visitor use within the social carrying capacity.

  4. 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.

  5. Identification and uncertainty analysis of a hydrological water quality model with varying input data information content

    Science.gov (United States)

    Jiang, Sanyuan; Jomaa, Seifeddine; Rode, Michael

    2013-04-01

    The rivers in central Germany are moderately to heavily polluted by nutrient inputs from point and diffuse sources. The objectives of this study are (i) to assess the new HYPE model (HYdrological Predictions for the Environment) for simulating runoff and inorganic nitrogen (IN) emissions at nested and spatially heterogeneous mesoscale catchments; (ii) to investigate the temporal and spatial variations of IN leaching and (iii) to investigate effects of calibration data on hydrological parameter identification. A multi-site and multi-objective calibration approach with help of Markov chain Monte Carlo (MCMC) was employed for parameter optimisation and uncertainty analysis. Results showed that parameters related to evapotranspiration were most sensitive in runoff simulation, while the nitrogen processes were mainly controlled by plant uptake and denitrification. Runoff was reproduced quite well for both calibration (1994-1999) and validation (1999-2004) periods (including the extreme dry year of 2003) at all three gauge stations, with a lowest Nash-Sutcliffe (NSE) of 0.86. The dynamics of soil moisture during extreme climatological events were well captured. Corresponding to spatial variability of hydrological regimes and land use, IN concentrations showed an increase in magnitude and a decrease in dynamics from upstream to downstream, reflecting the combined effects of increasing nutrient inputs and decreasing IN in-stream retention. The IN load was simulated well at monthly time intervals, with a lowest NSE of 0.69. Results revealed high IN emissions in winter and low values in summer; the area-weighted IN emission load decreased along the stream channel. Therefore, it is concluded that the IN emission is mainly controlled by runoff in this study catchment. From the preliminary result, we found that the 95% parameter confidence intervals of hydrological parameters decreased when IN concentration observations were included in hydrological parameter calibration. In

  6. [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.

  7. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Shidong, E-mail: emblembl@sina.com [School of Environment, Tsinghua University, 1 Qinghuayuan, Haidian District, Beijing 100084 (China); Jia, Haifeng, E-mail: jhf@tsinghua.edu.cn [School of Environment, Tsinghua University, 1 Qinghuayuan, Haidian District, Beijing 100084 (China); Xu, Changqing, E-mail: 2008changqing@163.com [School of Environment, Tsinghua University, 1 Qinghuayuan, Haidian District, Beijing 100084 (China); Xu, Te, E-mail: xt_lichking@qq.com [School of Environment, Tsinghua University, 1 Qinghuayuan, Haidian District, Beijing 100084 (China); Melching, Charles, E-mail: steve.melching17@gmail.com [Melching Water Solutions, 4030 W. Edgerton Avenue, Greenfield, WI 53221 (United States)

    2016-08-01

    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{sup −1}; Total Phosphorus (TP): 23.3–31.0 t·yr{sup −1}; and Total Nitrogen (TN): 480–1918.0 t·yr{sup −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

  9. The impact of considering uncertainty in measured calibration/validation data during auto-calibration of hydrologic and water quality models

    Science.gov (United States)

    The importance of uncertainty inherent in measured calibration/validation data is frequently stated in literature, but it is not often considered in calibrating and evaluating hydrologic and water quality models. This is due to the limited amount of data available to support relevant research and t...

  10. Inferring land use and land cover impact on stream water quality using a Bayesian hierarchical modeling approach in the Xitiaoxi River Watershed, China.

    Science.gov (United States)

    Wan, Rongrong; Cai, Shanshan; Li, Hengpeng; Yang, Guishan; Li, Zhaofu; Nie, Xiaofei

    2014-01-15

    Lake eutrophication has become a very serious environmental problem in China. If water pollution is to be controlled and ultimately eliminated, it is essential to understand how human activities affect surface water quality. A recently developed technique using the Bayesian hierarchical linear regression model revealed the effects of land use and land cover (LULC) on stream water quality at a watershed scale. Six LULC categories combined with watershed characteristics, including size, slope, and permeability were the variables that were studied. The pollutants of concern were nutrient concentrations of total nitrogen (TN) and total phosphorus (TP), common pollutants found in eutrophication. The monthly monitoring data at 41 sites in the Xitiaoxi Watershed, China during 2009-2010 were used for model demonstration. The results showed that the relationships between LULC and stream water quality are so complicated that the effects are varied over large areas. The models suggested that urban and agricultural land are important sources of TN and TP concentrations, while rural residential land is one of the major sources of TN. Certain agricultural practices (excessive fertilizer application) result in greater concentrations of nutrients in paddy fields, artificial grasslands, and artificial woodlands. This study suggests that Bayesian hierarchical modeling is a powerful tool for examining the complicated relationships between land use and water quality on different scales, and for developing land use and water management policies. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. 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

  12. Use of environmental sensors and sensor networks to develop water and salinity budgets for seasonal wetland real-time water quality management

    Energy Technology Data Exchange (ETDEWEB)

    Quinn, N.W.T.; Ortega, R.; Rahilly, P.J.A,; Royer, C.W.

    2009-10-01

    Successful management of river salt loads in complex and highly regulated river basins such as the San Joaquin of California presents significant challenges to Information Technology. Models are used as means of simulating major hydrologic processes in the basin which affect water quality and can be useful as tools for organizing basin information in a structured and readily accessible manner. Models can also be used to extrapolate the results of system monitoring since it is impossible to collect data for every point and non-point source of a pollutant in the Basin. Fundamental to every model is the concept of mass balance. This paper describes the use of state-of-the-art sensor technologies deployed in concert to obtain the first water and salinity budgets for a 60,000 hectare tract of seasonally managed wetlands in the San Joaquin Basin of California.

  13. 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.

  14. 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...

  15. Tsunamis: Water Quality

    Science.gov (United States)

    ... Transmission in Pet Shelters Protect Your Pets Tsunamis: Water Quality Language: English Español (Spanish) Recommend on Facebook ... about testing should be directed to local authorities. Water for Drinking, Cooking, and Personal Hygiene Safe water ...

  16. 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

  17. 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

  18. Effect of water quality on mercury toxicity to Photobacterium phosphoreum: Model development and its application in natural waters.

    Science.gov (United States)

    Wang, Xinghao; Qu, Ruijuan; Wei, Zhongbo; Yang, Xi; Wang, Zunyao

    2014-06-01

    Mercury (Hg) compounds are widely distributed toxic environmental and industrial pollutants and they may bring danger to growth and development of aquatic organisms. The distribution of Hg species in the 3 percent NaCl solution was calculated using the chemical equilibrium model Visual MINTEQ, which demonstrated that Hg was mainly complexed by chlorides in the pH range 5.0-9.0 and the proportions of HgCl4(2-), HgCl3(-) and HgCl2(aq) reached to 95 percent of total Hg. Then the effects of cations (Ca(2+), Mg(2+), K(+) and H(+)), anions (HCO3(-), NO3(-), SO4(2-) and HPO4(2-)) and complexing agents (ethylene diamine tetraacetic acid (EDTA) and dissolved organic matter (DOM)) on Hg toxicity to Photobacterium phosphoreum were evaluated in standardized 15min acute toxicity tests. The significant increase of 6.3-fold in EC50 data with increasing pH was observed over the tested pH range of 5.0-8.0, which suggested the possible competition between hydroxyl and the negatively charged chloro-complex. By contrast, it was found that major cations (Ca(2+), Mg(2+) and K(+)) have little effect on Hg toxicity to P. phosphoreum. An interesting finding was that the addition of HPO4(2-) significantly increased Hg toxicity, which may imply that the addition of phosphate increased the soluble Hg-chloro complex species. Additions of complexing agents (EDTA and DOM) into the exposure water increased Hg bioavailability via complexation of Hg. Finally, a model which incorporated the effect of pH, HPO4(2-), HCO3(-), SO4(2-) and DOM on Hg toxicity was developed to predict acute Hg toxicity for P. phosphoreum, which may be a useful tool in setting realistic water quality criteria for different types of water. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. Evaluating the relationship between temporal changes in land use and resulting water quality.

    Science.gov (United States)

    Wijesiri, Buddhi; Deilami, Kaveh; Goonetilleke, Ashantha

    2017-12-02

    Changes in land use have a direct impact on receiving water quality. Effective mitigation strategies require the accurate prediction of water quality in order to enhance community well-being and ecosystem health. The research study employed Bayesian Network modelling to investigate the validity of using cross-sectional and longitudinal data on water quality and land use for predicting water quality in a mixed use catchment and the role it plays in the generation of blue-green algae in the receiving marine environment. Bayesian Network modelling showed that cross-sectional and longitudinal data analyses generate contrasting information about the influence of different land uses on surface water pollution. The modelling outcomes highlighted the lack of reliability in cross-sectional data analysis, based on the indication of spurious relationships between water quality and land use. On the other hand, the longitudinal data analysis, which accounted for changes in water quality and land use over a ten-year period, informed how catchment water quality varies in response to temporal changes in land use. The longitudinal data analysis further revealed that the types of anthropogenic activities have a more significant influence on pollutant generation than the change in the area extent of different land uses over time. Therefore, the careful interpretation of the findings derived solely from cross-sectional data analysis is important in the design of long-term strategies for pollution mitigation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Water Quality and Geochemical Modeling of Water at an Abandoned Coal Mine Reclaimed With Coal Combustion By-Products

    Science.gov (United States)

    Haefner, Ralph J.

    2002-01-01

    An abandoned coal mine in eastern Ohio was reclaimed with 125 tons per acre of pressurized fluidized bed combustion (PFBC) by-product. Water quality at the site (known as the Fleming site) was monitored for 7 years after reclamation; samples included water from soil-suction lysimeters (interstitial water), wells, and spring sites established downgradient of the application area. This report presents a summary of data collected at the Fleming site during the period September 1994 through June 2001. Additionally, results of geochemical modeling are included in this report to evaluate the potential fate of elements derived from the PFBC by-product. Chemical analyses of samples of interstitial waters within the PFBC by-product application area indicated elevated levels of pH and specific conductance and elevated concentrations of boron, calcium, chloride, fluoride, magnesium, potassium, strontium, and sulfate compared to water samples collected in a control area where traditional reclamation methods were used. Magnesium-to-calcium (Mg:Ca) mole ratios and sulfur-isotope ratios were used to trace the PFBC by-product leachate and showed that little, if any, leachate reached ground water. Concentrations of most constituents in interstitial waters in the application-area decreased during the seven sampling rounds and approached background concentrations observed in the control area; however, median pH in the application area remained above 6, indicating that some acid-neutralizing capacity was still present. Although notable changes in water quality were observed in interstitial waters during the study period, quality of ground water and spring water remained poor. Water from the Fleming site was not potable, given exceedances of primary and secondary Maximum Contaminant Levels (MCLs) for inorganic constituents in drinking water set by the U.S. Environmental Protection Agency. Only fluoride and sulfate, which were found in higher concentrations in application

  1. Great Lakes Water Quality Agreement (GLWQA)

    Science.gov (United States)

    The Great Lakes Water Quality Agreement between the U.S. and Canada addresses critical environmental health issues in the Great Lakes region. It's a model of binational cooperation to protect water quality. It was first signed in 1972 and amended in 2012.

  2. 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)

  3. 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...

  4. 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

  5. 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...

  6. Development of An Empirical Water Quality Model for Stormwater Based on Watershed Land Use in Puget Sound

    Energy Technology Data Exchange (ETDEWEB)

    Cullinan, Valerie I.; May, Christopher W.; Brandenberger, Jill M.; Judd, Chaeli; Johnston, Robert K.

    2007-03-29

    The Sinclair and Dyes Inlet watershed is located on the west side of Puget Sound in Kitsap County, Washington, U.S.A. (Figure 1). The Puget Sound Naval Shipyard (PSNS), U.S Environmental Protection Agency (USEPA), the Washington State Department of Ecology (WA-DOE), Kitsap County, City of Bremerton, City of Bainbridge Island, City of Port Orchard, and the Suquamish Tribe have joined in a cooperative effort to evaluate water-quality conditions in the Sinclair-Dyes Inlet watershed and correct identified problems. A major focus of this project, known as Project ENVVEST, is to develop Water Clean-up (TMDL) Plans for constituents listed on the 303(d) list within the Sinclair and Dyes Inlet watershed. Segments within the Sinclair and Dyes Inlet watershed were listed on the State of Washington’s 1998 303(d) because of fecal coliform contamination in marine water, metals in sediment and fish tissue, and organics in sediment and fish tissue (WA-DOE 2003). Stormwater loading was identified by ENVVEST as one potential source of sediment contamination, which lacked sufficient data for a contaminant mass balance calculation for the watershed. This paper summarizes the development of an empirical model for estimating contaminant concentrations in all streams discharging into Sinclair and Dyes Inlets based on watershed land use, 18 storm events, and wet/dry season baseflow conditions between November 2002 and May 2005. Stream pollutant concentrations along with estimates for outfalls and surface runoff will be used in estimating the loading and ultimately in establishing a Water Cleanup Plan (TMDL) for the Sinclair-Dyes Inlet watershed.

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

    Science.gov (United States)

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

    2016-08-01

    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): 581.5-1030.6t·yr(-1); Total Phosphorus (TP): 23.3-31.0t·yr(-1); and Total Nitrogen (TN): 480-1918.0t·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) determination. The sources

  8. 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

  9. 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

  10. Comparison of field measurements to predicted reaeration coefficients, k2, in the application of a water quality model, QUAL2E, to a tropical river.

    Science.gov (United States)

    Mohamed, M; Stednick, J D; Smith, F M

    2002-01-01

    Some of the many tools used for watershed management are mathematical and computer models for wasteload allocations. QUAL2E is one of the most popular water quality models used for such purposes. The question arises as to whether the model is applicable in a different climate such as that in the tropics. In this study, QUAL2E was used to model Sg. Selangor River in Malaysia using the predictive equations for reaeration coefficient (k2) within the model and the measured reaeration coefficients for the river. The study results indicated that use of the reaeration coefficient (k2) measured at Sg. Selangor River did give the lowest standard error (SE) for the simulation of water quality during the 7Q10 low-flow period which is considered as the worst scene scenario in water quality modeling. But during calibration and validation using actual low-flow discharge data, the measured reaeration coefficients did not give the lowest standard error (SE). In conclusion, the results indicated that QUAL2E is applicable in tropical rivers when used with the modeled river parameters (i.e. hydraulic parameters, meteorological conditions etc.). Measured reaeration coefficients produced good results and several predictive equations also produced comparatively good results.

  11. Modification, calibration and verification of the IWA River Water Quality Model to simulate a pilot-scale high rate algal pond.

    Science.gov (United States)

    Broekhuizen, Niall; Park, Jason B K; McBride, Graham B; Craggs, Rupert J

    2012-06-01

    We implemented the IWA River Water Quality Model No. 1 (Reichert et al., 2001. River Water Quality Model No. 1, IWA Scientific & Technical Report No. 12) to simulate water-quality characteristics in two pilot-scale High Rate Algal Ponds. Simulation results were compared with two years' of data from the ponds. The first year's data from one pond were used for model calibration; the remaining data were used for validation. As originally formulated and parameterized, the model consistently yielded summer-time algal biomass concentrations which were too low - with consequent failures in its reproduction of dissolved oxygen, pH and nutrient dynamics. We experimented with various structural/parametric changes to improve the model's performance. The most effective strategy was to greatly increase the respiratory losses suffered by the heterotrophic osmotrophs (thereby giving the algae access to a larger fraction of the incoming dissolved organic carbon and nitrogen). This suggests that CO(2)-bubbling alone cannot entirely preclude resource-limitation of algal production. We doubt that our parameterization of heterotrophic osmotrophs is correct and infer that the algae derive a large fraction of their nutrition by direct osmotrophic uptake of dissolved organic matter. This inference is supported by the literature concerning the physiology of the dominant algal species in our ponds. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Integrated Urban Water Quality Management

    DEFF Research Database (Denmark)

    Rauch, W.; Harremoës, Poul

    1995-01-01

    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......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...... weather, while the overflow from the combined sewer system plays a minor role. Oxygen depletion in urban rivers is caused by intermittent discharges from both sewer system and wastewater treatment plant. Neglecting one of them in the evaluation of the environmental impact gives a wrong impression of total...

  13. 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

  14. 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

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

    Science.gov (United States)

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

    2013-06-01

    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. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. A study of a matching pixel by pixel (MPP) algorithm to establish an empirical model of water quality mapping, as based on unmanned aerial vehicle (UAV) images

    Science.gov (United States)

    Su, Tung-Ching

    2017-06-01

    Linear regression models are a popular choice for the relationships between water quality parameters and bands (or band ratios) of remote sensing data. However, this research regards the phenomena of mixed pixels, specular reflection, and water fluidity as the challenges to establish a robust regression model. Based on the data of measurements in situ and remote sensing data, this study presents an enumeration-based algorithm, called matching pixel by pixel (MPP), and tests its performance in an empirical model of water quality mapping. Four small reservoirs, which cover a mere several hundred-thousand m2, in Kinmen, Taiwan, are selected as the study sites. The multispectral sensors, carried on an unmanned aerial vehicle (UAV), are adopted to acquire remote sensing data regarding water quality parameters, including chlorophyll-a (Chl-a), Secchi disk depth (SDD), and turbidity in the reservoirs. The experimental results indicate that, while MPP can reduce the influence of specular reflection on regression model establishment, specular reflection does hamper the correction of thematic map production. Due to water fluidity, sampling in situ should be followed by UAV imaging as soon as possible. Excluding turbidity, the obtained estimation accuracy can satisfy the national standard.

  17. 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)

  18. 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...

  19. 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

  20. Work Plan for Three-Dimensional Time-Varying, Hydrodynamic and Water Quality Model of Chesapeake Bay

    Science.gov (United States)

    1988-08-01

    for the past 30 years exists. How can hydrology be projected into the future? The "best- case " scenario is that hydrodynamics and water quality are not...TOXIcant Water Analysis Simulation Program (Ambrose et al., 1983) was developed by the USEPA by modifying, and in some cases simplifying, the kinetic...Technical DirectorI WES Oversight Group Dr. J. Harrison, C/EL Mr. F. Herrmann, C/HL Dr. J. Houston. C/CERC I EStudy ManagerMr. D. L. Robey Ms. C. Rogers

  1. 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

  2. Purified water quality study

    Energy Technology Data Exchange (ETDEWEB)

    Spinka, H.; Jackowski, P.

    2000-04-03

    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.

  3. 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

  4. Reducing epistemic errors in water quality modelling through high-frequency data and stakeholder collaboration: the case of an industrial spill

    Science.gov (United States)

    Krueger, Tobias; Inman, Alex; Paling, Nick

    2014-05-01

    Catchment management, as driven by legislation such as the EU WFD or grassroots initiatives, requires the apportionment of in-stream pollution to point and diffuse sources so that mitigation measures can be targeted and costs and benefits shared. Source apportionment is typically done via modelling. Given model imperfections and input data errors, it has become state-of-the-art to employ an uncertainty framework. However, what is not easily incorporated in such a framework, and currently much discussed in hydrology, are epistemic uncertainties, i.e. those uncertainties that relate to lack of knowledge about processes and data. For example, what if an otherwise negligible source suddenly matters because of an accidental pollution incident? In this paper we present such a case of epistemic error, an industrial spill ignored in a water quality model, demonstrate the bias of the resulting model simulations, and show how the error was discovered somewhat incidentally by auxiliary high-frequency data and finally corrected through the collective intelligence of a stakeholder network. We suggest that accidental pollution incidents like this are a wide-spread, though largely ignored, problem. Hence our discussion will reflect on the practice of catchment monitoring, modelling and management in general. The case itself occurred as part of ongoing modelling support in the Tamar catchment, one of the priority catchments of the UK government's new approach to managing water resources more decentralised and collaboratively. An Extended Export Coefficient Model (ECM+) had been developed with stakeholders to simulate transfers of nutrients (N & P), sediment and Faecal Coliforms from land to water and down the river network as a function of sewage treatment options, land use, livestock densities and farm management practices. In the process of updating the model for the hydrological years 2008-2012 an over-prediction of the annual average P concentration by the model was found at

  5. A fuzzy risk approach for seasonal water quality management of a river system.

    OpenAIRE

    Mujumdar, PP; K Sasikumar

    2002-01-01

    A fuzzy optimization model is developed for the seasonal water quality management of river systems. The model addresses the uncertainty in a water quality system in a fuzzy probability framework. The occurrence of low water quality is treated as a fuzzy event. Randomness associated with the water quality indicator is linked to this fuzzy event using the concept of probability of a fuzzy event. In most water quality management models the risk level for violation of a water quality standard is ...

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. Use of remotely-sensed observations and a data assimilating marine biogeochemical model to determine water quality on the Great Barrier Reef.

    Science.gov (United States)

    Baird, Mark; Jones, Emlyn; Wozniak, Monika; Mongin, Mathieu; Skerratt, Jennifer; Margvelashvilli, Nugzar; Wild-Allen, Karen; Robson, Barbara; Rizwi, Farhan; Schroeder, Thomas; Steven, Andy

    2017-04-01

    The health of the Great Barrier Reef is presently assessed using the water column concentration of chlorophyll and suspended solids, and measured light penetration. Quantifying these water column properties over 2,000 km of often cloud-covered, sparsely sampled, and highly variable coastal waters is problematic. To provide the best estimate of water quality, we assimilating satellite remote-sensing reflectance (the ratio of water-leaving radiance versus water-entering irradiance) using an in-water optical model to produce an equivalent simulated remote-sensing reflectance, and calculate the mis-match between the observed and simulated quantities to constrain a complex biogeochemical model (eReefs) with a Deterministic Ensemble Kalman Filter (DEnKF). We compare the water quality properties of the data assimilating model with in-situ observations, as well as with withheld remote-sensed observations. As a final step, we consider whether withheld observations can be combined with the data-assimilation generated chlorophyll fields to provide the best estimate of the chlorophyll concentration given all the available information.

  12. A Mass-balance nitrate model for predicting the effects of land use on ground-water quality in municipal wellhead-protection areas

    Science.gov (United States)

    Frimpter, M.H.; Donohue, J.J.; Rapacz, M.V.; Beye, H.G.

    1990-01-01

    A mass-balance accounting model can be used to guide the management of septic systems and fertilizers to control the degradation of groundwater quality in zones of an aquifer that contributes water to public supply wells. The nitrate nitrogen concentration of the mixture in the well can be predicted for steady-state conditions by calculating the concentration that results from the total weight of nitrogen and total volume of water entering the zone of contribution to the well. These calculations will allow water-quality managers to predict the nitrate concentrations that would be produced by different types and levels of development, and to plan development accordingly. Computations for different development schemes provide a technical basis for planners and managers to compare water quality effects and to select alternatives that limit nitrate concentration in wells. Appendix A contains tables of nitrate loads and water volumes from common sources for use with the accounting model. Appendix B describes the preparation of a spreadsheet for the nitrate loading calculations with a software package generally available for desktop computers. (USGS)

  13. 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.

  14. 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.

  15. Hydrologic and Water Quality System (HAWQS)

    Science.gov (United States)

    The Hydrologic and Water Quality System (HAWQS) is a web-based interactive water quantity and quality modeling system that employs as its core modeling engine the Soil and Water Assessment Tool (SWAT), an internationally-recognized public domain model. HAWQS provides users with i...

  16. 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.

  17. Modeling the citation network by network cosmology.

    Directory of Open Access Journals (Sweden)

    Zheng Xie

    Full Text Available 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.

  18. 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.

  19. 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

  20. 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...

  1. Statistics for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater runoff best management practices (BMPs)

    Science.gov (United States)

    Granato, Gregory E.

    2014-01-01

    The U.S. Geological Survey (USGS) developed the Stochastic Empirical Loading and Dilution Model (SELDM) in cooperation with the Federal Highway Administration (FHWA) to indicate the risk for stormwater concentrations, flows, and loads to be above user-selected water-quality goals and the potential effectiveness of mitigation measures to reduce such risks. SELDM models the potential effect of mitigation measures by using Monte Carlo methods with statistics that approximate the net effects of structural and nonstructural best management practices (BMPs). In this report, structural BMPs are defined as the components of the drainage pathway between the source of runoff and a stormwater discharge location that affect the volume, timing, or quality of runoff. SELDM uses a simple stochastic statistical model of BMP performance to develop planning-level estimates of runoff-event characteristics. This statistical approach can be used to represent a single BMP or an assemblage of BMPs. The SELDM BMP-treatment module has provisions for stochastic modeling of three stormwater treatments: volume reduction, hydrograph extension, and water-quality treatment. In SELDM, these three treatment variables are modeled by using the trapezoidal distribution and the rank correlation with the associated highway-runoff variables. This report describes methods for calculating the trapezoidal-distribution statistics and rank correlation coefficients for stochastic modeling of volume reduction, hydrograph extension, and water-quality treatment by structural stormwater BMPs and provides the calculated values for these variables. This report also provides robust methods for estimating the minimum irreducible concentration (MIC), which is the lowest expected effluent concentration from a particular BMP site or a class of BMPs. These statistics are different from the statistics commonly used to characterize or compare BMPs. They are designed to provide a stochastic transfer function to approximate

  2. 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

  3. 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. .

  4. Assessing river water quality using water quality index in Lake Taihu Basin, China.

    Science.gov (United States)

    Wu, Zhaoshi; Wang, Xiaolong; Chen, Yuwei; Cai, Yongjiu; Deng, Jiancai

    2018-01-15

    Lake Taihu Basin, one of the most developed regions in China, has received considerable attention due to its severe pollution. Our study provides a clear understanding of the water quality in the rivers of Lake Taihu Basin based on basin-scale monitoring and a water quality index (WQI) method. From September 2014 to January 2016, four samplings across four seasons were conducted at 96 sites along main rivers. Fifteen parameters, including water temperature, pH, dissolved oxygen (DO), conductivity, turbidity (tur), permanganate index (CODMn), total nitrogen, total phosphorus, ammonium (NH4-N), nitrite, nitrate (NO3-N), calcium, magnesium, chloride, and sulfate, were measured to calculate the WQI. The average WQI value during our study period was 59.33; consequently, the water quality was considered as generally "moderate". Significant differences in WQI values were detected among the 6 river systems, with better water quality in the Tiaoxi and Nanhe systems. The water quality presented distinct seasonal variation, with the highest WQI values in autumn, followed by spring and summer, and the lowest values in winter. The minimum WQI (WQImin), which was developed based on a stepwise linear regression analysis, consisted of five parameters: NH4-N, CODMn, NO3-N, DO, and tur. The model exhibited excellent performance in representing the water quality in Lake Taihu Basin, especially when weights were fully considered. Our results are beneficial for water quality management and could be used for rapid and low-cost water quality evaluation in Lake Taihu Basin. Additionally, we suggest that weights of environmental parameters should be fully considered in water quality assessments when using the WQImin method. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Assessing landscape and contaminant point-sources as spatial determinants of water quality in the Vermilion River System, Ontario, Canada.

    Science.gov (United States)

    Strangway, Carrie; Bowman, Michelle F; Kirkwood, Andrea E

    2017-08-14

    The Vermilion River and major tributaries (VRMT) are located in the Vermilion watershed (4272 km(2)) in north-central Ontario, Canada. This watershed not only is dominated by natural land-cover but also has a legacy of mining and other development activities. The VRMT receive various point (e.g., sewage effluent) and non-point (e.g., mining activity runoff) inputs, in addition to flow regulation features. Further development in the Vermilion watershed has been proposed, raising concerns about cumulative impacts to ecosystem health in the VRMT. Due to the lack of historical assessments on riverine-health in the VRMT, a comprehensive suite of water quality parameters was collected monthly at 28 sites during the ice-free period of 2013 and 2014. Canadian water quality guidelines and objectives were not met by an assortment of water quality parameters, including nutrients and metals. This demonstrates that the VRMT is an impacted system with several pollution hotspots, particularly downstream of wastewater treatment facilities. Water quality throughout the river system appeared to be influenced by three distinct land-cover categories: forest, barren, and agriculture. Three spatial pathway models (geographical, topographical, and river network) were employed to assess the complex interactions between spatial pathways, stressors, and water quality condition. Topographical landscape analyses were performed at five different scales, where the strongest relationships between water quality and land-use occurred at the catchment scale. Sites on the main stem of Junction Creek, a tributary impacted by industrial and urban development, had above average concentrations for the majority of water quality parameters measured, including metals and nitrogen. The river network pathway (i.e., asymmetric eigenvector map (AEM)) and topographical feature (i.e., catchment land-use) models explained most of the variation in water quality (62.2%), indicating that they may be useful tools in

  6. 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

  7. Artificial neural network modeling of dissolved oxygen in reservoir.

    Science.gov (United States)

    Chen, Wei-Bo; Liu, Wen-Cheng

    2014-02-01

    The water quality of reservoirs is one of the key factors in the operation and water quality management of reservoirs. Dissolved oxygen (DO) in water column is essential for microorganisms and a significant indicator of the state of aquatic ecosystems. In this study, two artificial neural network (ANN) models including back propagation neural network (BPNN) and adaptive neural-based fuzzy inference system (ANFIS) approaches and multilinear regression (MLR) model were developed to estimate the DO concentration in the Feitsui Reservoir of northern Taiwan. The input variables of the neural network are determined as water temperature, pH, conductivity, turbidity, suspended solids, total hardness, total alkalinity, and ammonium nitrogen. The performance of the ANN models and MLR model was assessed through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated DO values. The results reveal that ANN estimation performances were superior to those of MLR. Comparing to the BPNN and ANFIS models through the performance criteria, the ANFIS model is better than the BPNN model for predicting the DO values. Study results show that the neural network particularly using ANFIS model is able to predict the DO concentrations with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.

  8. Water-quality variability and constituent transport and processes in streams of Johnson County, Kansas, using continuous monitoring and regression models, 2003-11

    Science.gov (United States)

    Rasmussen, Teresa; Gatotho, Jackline

    2014-01-01

    The population of Johnson County, Kansas increased by about 24 percent between 2000 and 2012, making it one of the most rapidly developing areas of Kansas. The U.S. Geological Survey, in cooperation with the Johnson County Stormwater Management Program, began a comprehensive study of Johnson County streams in 2002 to evaluate and monitor changes in stream quality. The purpose of this report is to describe water-quality variability and constituent transport for streams representing the five largest watersheds in Johnson County, Kansas during 2003 through 2011. The watersheds ranged in urban development from 98.3 percent urban (Indian Creek) to 16.7 percent urban (Kill Creek). Water-quality conditions are quantified among the watersheds of similar size (50.1 square miles to 65.7 square miles) using continuous, in-stream measurements, and using regression models developed from continuous and discrete data. These data are used to quantify variability in concentrations and loads during changing streamflow and seasonal conditions, describe differences among sites, and assess water quality relative to water-quality standards and stream management goals. Water quality varied relative to streamflow conditions, urbanization in the upstream watershed, and contributions from wastewater treatment facilities and storm runoff. Generally, as percent impervious surface (a measure of urbanization) increased, streamflow yield increased. Water temperature of Indian Creek, the most urban site which is also downstream from wastewater facility discharges, was higher than the other sites about 50 percent of the time, particularly during winter months. Dissolved oxygen concentrations were less than the Kansas Department of Health and Environment minimum criterion of 5 milligrams per liter about 15 percent of the time at the Indian Creek site. Dissolved oxygen concentrations were less than the criterion about 10 percent of the time at the rural Blue River and Kill Creek sites, and less than

  9. Development of communication networks and water quality early warning detection systems at drinking water utilities in the Ohio River Valley Basin.

    Science.gov (United States)

    Schulte, J G; Vicory, A H

    2005-01-01

    Source water quality is of major concern to all drinking water utilities. The accidental introduction of contaminants to their source water is a constant threat to utilities withdrawing water from navigable or industrialized rivers. The events of 11 September, 2001 in the United States have heightened concern for drinking water utility security as their source water and finished water may be targets for terrorist acts. Efforts are underway in several parts of the United States to strengthen early warning capabilities. This paper will focus on those efforts in the Ohio River Valley Basin.

  10. Real-time remote monitoring system for aquaculture water quality

    National Research Council Canada - National Science Library

    Luo Hongpin; Li Guanglin; Peng Weifeng; Song Jie; Bai Qiuwei

    2015-01-01

      A multi-parameters monitoring system based on wireless network was set up to achieve remote real-time monitoring of aquaculture water quality, in order to improve the quality of aquaculture products...

  11. Fertilizer Use and Water Quality.

    Science.gov (United States)

    Reneau, Fred; And Others

    This booklet presents informative materials on fertilizer use and water quality, specifically in regard to environmental pollution and protection in Illinois. The five chapters cover these topics: Fertilizer and Water Quality, Fertilizer Use, Fertilizers and the Environment, Safety Practices, and Fertilizer Management Practices. Key questions are…

  12. 5 Water Quality.cdr

    African Journals Online (AJOL)

    Administrator

    the basins cause an acceleration of the. Water Quality Assessment of Densu, Birim and Ayensu. Rivers in the Okyeman Area. 1. 2. O. D. Ansa-Asare * and C. ... The aim of this paper is to develop an understanding of the spatial water quality throughout the basins and also identify the main sources of contaminants within the ...

  13. 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

    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...... 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...... 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...

  14. Modeling network technology deployment rates with different network models

    OpenAIRE

    Chung, Yoo

    2011-01-01

    To understand the factors that encourage the deployment of a new networking technology, we must be able to model how such technology gets deployed. We investigate how network structure influences deployment with a simple deployment model and different network models through computer simulations. The results indicate that a realistic model of networking technology deployment should take network structure into account.

  15. 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

  16. Model documentation for relations between continuous real-time and discrete water-quality constituents in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999--2009

    Science.gov (United States)

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

    2013-01-01

    Cheney Reservoir in south-central Kansas is one of the primary sources of water for the city of Wichita. The North Fork Ninnescah River is the largest contributing tributary to Cheney Reservoir. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station since 1998 on the North Fork Ninnescah River. Continuously measured water-quality physical properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, and turbidity. Discrete water-quality samples were collected during 1999 through 2009 and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to estimate concentrations of those constituents of interest that are not easily measured in real time because of limitations in sensor technology and fiscal constraints. Regression models were published in 2006 that were based on a different dataset collected during 1997 through 2003. This report updates those models using discrete and continuous data collected during January 1999 through December 2009. Models also were developed for five new constituents, including additional nutrient species and indicator bacteria. The water-quality information in this report is important to the city of Wichita because it allows the concentrations of many potential pollutants of interest, including nutrients and sediment, to be estimated in real time and characterized over conditions and time scales that would not be possible otherwise.

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

    OpenAIRE

    Haw Yen; Prasad Daggupati; Michael J. White; Raghavan Srinivasan; Arndt Gossel; David Wells; Jeffrey G. Arnold

    2016-01-01

    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...

  18. Monitoring water quality and quantity of national watersheds in Turkey.

    Science.gov (United States)

    Odemis, Berkant; Evrendilek, Fatih

    2007-10-01

    National data from the hydrological network for 38 rivers out of 25 watersheds were used to detect spatial and temporal trends in water quality and quantity characteristics between 1995 and 2002. Assessment of water quality and quantity included flow rate, water temperature, pH, electrical conductivity, sodium adsorption rate, Na, K, Ca+Mg, CO(3), HCO(3), Cl, SO(4), and boron. Among the major ions assessed on a watershed basis, Turkish river waters are relatively high in Ca+Mg, Na and HCO(3), and low in K and CO(3). The watersheds in Turkey experienced a general trend of 16% decrease in flow rates between 1995 and 2002 at a mean annual rate of about 4 m(3) s(-1), with a considerable spatial variation. Similarly, there appeared to be an increasing trend in river water temperature, at a mean annual rate of about 0.2 degrees C. A substantial proportion of watersheds experienced an increase in pH, in particular, after 1997, with a maximum increase from 8.1 to 8.4 observed in Euphrates (P Big Menderes watersheds where intensive agricultural activities take place. Such continued levels may threaten biotic integrity and both drinking and irrigation water quality of rivers. Best multiple linear regression (MLR) models constructed both annually and monthly differed in R (2) values in accounting for variations of pH and water temperature only. The findings of the study can provide a useful assessment of controls over water quality and quantity and assist in devising integrated and sustainable management practices for watersheds at the regional scale in Turkey.

  19. 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

  20. Application of large-scale, multi-resolution watershed modeling framework using the Hydrologic and Water Quality System (HAWQS)

    Science.gov (United States)

    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 all...

  1. 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

  2. Capacity of semi-parametric regression models to predict extreme-event water quality in the Northeastern US

    Science.gov (United States)

    Hagemann, Mark; Park, Mi-Hyun

    2017-04-01

    This study assessed the capacity of semi-parametric regression models to predict riverine solute concentrations during extreme high-flow hydrologic events, when such events are absent from the models' calibration data. Using a large dataset from 459 monitoring stations across the US Northeast, the models showed a tendency to overpredict extreme-event concentrations, with increasing bias and variance for increasingly extreme hydrologic conditions. The validation framework in this study effectively compared model performance across disparate hydrologic regimes and constituents, yet can be used to estimate individual model performance under an unobserved extreme-flow condition, regardless of whether any extreme-flow data are available for that model. The validation procedure can further be generalized to explore model performance in an arbitrarily defined extreme condition for a broad range of model types. Despite an overall increase in uncertainty for extreme-event concentration estimates, estimates under extreme hydrologic conditions could be improved by taking into account the observed bias in the aggregated regional database.

  3. High-Performance Integrated Control of water quality and quantity in urban water reservoirs by dynamic emulation and model predictive control

    Science.gov (United States)

    Castelletti, A.; Galelli, S.; Goedbloed, A.

    2015-12-01

    Retention basins and urban reservoirs are increasingly used to support drinking water supply in large metropolitan contexts, since they make use of a resource, i.e., stormwater, that would be otherwise wasted, thus limiting the amount of water extracted from natural systems or produced with energy-intensive techniques. Yet, the operation of these infrastructures faces a twofold challenge. First, the presence of large impervious areas in urban catchments results in high discharge peaks and runoff volumes and a fast runoff response to rainfall, with consequent very short times of concentration. Second, stormwater transports large amount of pollutants to the receiving water bodies. This paper contributes a novel High-Performance Integrated Control framework to support the real-time operation of urban water supply storages affected by water quality problems. We use a 3D hydrodynamic, high-fidelity, simulation model to predict the main water quality dynamics and inform a real-time controller based on Model Predictive Control. We integrate the simulation model into the control scheme by a model reduction process, where the high-fidelity simulator is first used to identify and then replaced by a low-order dynamic emulator, which runs orders of magnitude faster. The framework is used to design the hourly operation of Marina Reservoir, a 3.2 Mm3 stormwater-fed reservoir located in the centre of Singapore operated for drinking water supply and flood control. Because of its recent formation from a former estuary, the reservoir suffers from high salinity levels, whose dynamics is modelled with Delft3D-FLOW. Results show that the real-time operation designed by our framework drops the minimum salinity levels of nearly 30% while reducing the average annual deficit of drinking water supply by about two times the active storage of the reservoir. Such a win-win solution is obtained by means of a model reduction process that reduced the dimensionality of Delft3D-FLOW by three orders

  4. 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.

  5. 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...

  6. Decay of Bacteroidales genetic markers in relation to traditional fecal indicators for water quality modeling of drinking water sources.

    Science.gov (United States)

    Sokolova, Ekaterina; Aström, Johan; Pettersson, Thomas J R; Bergstedt, Olof; Hermansson, Malte

    2012-01-17

    The implementation of microbial fecal source tracking (MST) methods in drinking water management is limited by the lack of knowledge on the transport and decay of host-specific genetic markers in water sources. To address these limitations, the decay and transport of human (BacH) and ruminant (BacR) fecal Bacteroidales 16S rRNA genetic markers in a drinking water source (Lake Rådasjön in Sweden) were simulated using a microbiological model coupled to a three-dimensional hydrodynamic model. The microbiological model was calibrated using data from outdoor microcosm trials performed in March, August, and November 2010 to determine the decay of BacH and BacR markers in relation to traditional fecal indicators. The microcosm trials indicated that the persistence of BacH and BacR in the microcosms was not significantly different from the persistence of traditional fecal indicators. The modeling of BacH and BacR transport within the lake illustrated that the highest levels of genetic markers at the raw water intakes were associated with human fecal sources (on-site sewers and emergency sewer overflow). This novel modeling approach improves the interpretation of MST data, especially when fecal pollution from the same host group is released into the water source from different sites in the catchment.

  7. Confirmation of the Water Quality Model CE-QUAL-R1 Using Data from Eau Galle Reservoir, Wisconsin.

    Science.gov (United States)

    1985-10-01

    should not be " changed. Flux Predictions % 61. Wlosinski (1979), Scavia (1980), Chapra et al. (1983), and Collins and Wlosinski (1984) have shown the...34 Technical Report H-73-4, US Army Engineer Waterways AL. Experiment Station, Vicksburg, Miss. - . Chapra , S. C., Scavia, D., Lang, G. A., and Reckhow...K. H. 1983. " "’’ ’ "Nutrient/Food Chain Models" in "Engineering Approaches for Lake Manage- ment, Vol 2: Mechanistic Modeling," S. C. Chapra and K

  8. A CASE STUDY USING THE EPA'S WATER QUALITY MODELING SYSTEM, THE WINDOWS INTERFACE FOR SIMULATING PLUMES (WISP)

    Science.gov (United States)

    Wisp, the Windows Interface for Simulating Plumes, is designed to be an easy-to-use windows platform program for aquatic modeling. Wisp inherits many of its capabilities from its predecessor, the DOS-based PLUMES (Baumgartner, Frick, Roberts, 1994). These capabilities have been ...

  9. Biokinetic food chain modeling of waterborne selenium pulses into aquatic food chains: Implications for water quality criteria.

    Science.gov (United States)

    DeForest, David K; Pargee, Suzanne; Claytor, Carrie; Canton, Steven P; Brix, Kevin V

    2016-04-01

    We evaluated the use of biokinetic models to predict selenium (Se) bioaccumulation into model food chains after short-term pulses of selenate or selenite into water. Both periphyton- and phytoplankton-based food chains were modeled, with Se trophically transferred to invertebrates and then to fish. Whole-body fish Se concentrations were predicted based on 1) the background waterborne Se concentration, 2) the magnitude of the Se pulse, and 3) the duration of the Se pulse. The models were used to evaluate whether the US Environmental Protection Agency's (USEPA's) existing acute Se criteria and their recently proposed intermittent Se criteria would be protective of a whole-body fish Se tissue-based criterion of 8.1 μg g(-1) dry wt. Based on a background waterborne Se concentration of 1 μg L(-1) and pulse durations of 1 d and 4 d, the Se pulse concentrations predicted to result in a whole-body fish Se concentration of 8.1 μg g(-1) dry wt in the most conservative model food chains were 144 and 35 μg L(-1), respectively, for selenate and 57 and 16 μg L(-1), respectively, for selenite. These concentrations fall within the range of various acute Se criteria recommended by the USEPA based on direct waterborne toxicity, suggesting that these criteria may not always be protective against bioaccumulation-based toxicity that could occur after short-term pulses. Regarding the USEPA's draft intermittent Se criteria, the biokinetic modeling indicates that they may be overly protective for selenate pulses but potentially underprotective for selenite pulses. Predictions of whole-body fish Se concentrations were highly dependent on whether the food chain was periphyton- or phytoplankton-based, because the latter had much greater Se uptake rate constants. Overall, biokinetic modeling provides an approach for developing acute Se criteria that are protective against bioaccumulation-based toxicity after trophic transfer, and it is also a useful tool for evaluating averaging

  10. Recreational Water Quality Criteria Limits

    Science.gov (United States)

    This set of Frequently Asked Questions (FAQ) provides an overview of NPDES permitting applicable to continuous dischargers (such as POTWs) based on water quality standards for pathogens and pathogen indicators associated with fecal contamination.

  11. Water Quality Assessment Tool 2014

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — The Water Quality Assessment Tool project was developed to assess the potential for water-borne contaminants to adversely affect biota and habitats on Service lands.

  12. Chesapeake Bay Program Water Quality Database

    Science.gov (United States)

    The Chesapeake Information Management System (CIMS), designed in 1996, is an integrated, accessible information management system for the Chesapeake Bay Region. CIMS is an organized, distributed library of information and software tools designed to increase basin-wide public access to Chesapeake Bay information. The information delivered by CIMS includes technical and public information, educational material, environmental indicators, policy documents, and scientific data. Through the use of relational databases, web-based programming, and web-based GIS a large number of Internet resources have been established. These resources include multiple distributed on-line databases, on-demand graphing and mapping of environmental data, and geographic searching tools for environmental information. Baseline monitoring data, summarized data and environmental indicators that document ecosystem status and trends, confirm linkages between water quality, habitat quality and abundance, and the distribution and integrity of biological populations are also available. One of the major features of the CIMS network is the Chesapeake Bay Program's Data Hub, providing users access to a suite of long- term water quality and living resources databases. Chesapeake Bay mainstem and tidal tributary water quality, benthic macroinvertebrates, toxics, plankton, and fluorescence data can be obtained for a network of over 800 monitoring stations.

  13. The Application of Wireless Sensor in Aquaculture Water Quality Monitoring

    OpenAIRE

    Ding, Wen; Ma, Yinchi

    2011-01-01

    Part 1: Simulation, Optimization, Monitoring and Control Technology; International audience; The current means for aquaculture water quality monitoring have a weak infrastructure. We research to use wireless sensor technology, embedded computing technology, MEMS technology, distributing information processing technology and wireless communication technology to build the wireless network sensor network system. This system is a digital, networked, intelligent real-time dynamic for monitoring th...

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

    Science.gov (United States)

    2016-12-01

    16 4.2 Projected return on investment (ROI) ............................................................. 17 5 Conclusions and Recommendations...ERDC was COL Bryan S. Green and the Director was Dr. Jeffery P. Holland. ERDC/CERL TR-16-25 vii Unit Conversion Factors Multiply By To Obtain...models are typically built using a combination of GIS data, engineering design specifications, inventory/capital invest - ment data, water-usage records

  15. Modelling the impacts of altered management practices, land use and climate changes on the water quality of the Millbrook catchment-reservoir system in South Australia.

    Science.gov (United States)

    Nguyen, Hong Hanh; Recknagel, Friedrich; Meyer, Wayne; Frizenschaf, Jacqueline; Shrestha, Manoj Kumar

    2017-11-01

    Sustainable management of drinking water reservoirs requires taking into account the potential effects of their catchments' development. This study is an attempt to estimate the daily patterns of nutrients transport in the catchment - reservoir systems through the application of the ensemble of complementary models SWAT-SALMO. SWAT quantifies flow, nitrate and phosphate loadings originating in catchments before entering downstream reservoirs meanwhile SALMO determines phosphate, nitrate, and chlorophyll-a concentrations within the reservoirs. The study applies to the semi-arid Millbrook catchment-reservoir system that supplies drinking water to north-eastern suburbs of Adelaide, South Australia. The catchment hosts viti- and horticultural land uses. The warm-monomictic, mesotrophic reservoir is artificially aerated in summer. After validating the simulation results for both Millbrook catchment and reservoir, a comprehensive scenario analysis has been conducted to reveal cascading effects of altered management practices, land uses and climate conditions on water quality in the reservoir. Results suggest that the effect on reservoir condition in summer would be severe, most likely resulting in chlorophyll-a concentrations of greater than 40 μg/l if the artificial destratification was not applied from early summer. A 50% curbing of water diversion from an external pipeline to the catchment will slightly limit chlorophyll-a concentrations by 1.22% as an effect of reduced inflow phosphate loads. The simulation of prospective land use scenarios converting 50% of present pasture in the Millbrook catchment into residential and orchards areas indicates an increase of summer chlorophyll-a concentrations by 9.5-107.9%, respectively in the reservoir. Global warming scenarios based on the high emission simulated by SWAT-SALMO did result in earlier growth of chlorophyll-a but overall the effects on water quality in the Millbrook reservoir was not significant. However scenarios

  16. Sensor and Video Monitoring of Water Quality at Bristol Floating Harbour

    Science.gov (United States)

    Chen, Yiheng; Han, Dawei

    2017-04-01

    Water system is an essential component in a smart city for its sustainability and resilience. The harbourside is a focal area of​ ​Bristol with new buildings and features redeveloped in the last ten years, attracting numerous visitors by the diversity of attractions and beautiful views. There is a strong​ ​relationship between the satisfactory of the visitors and local people with the water quality in the Harbour. The freshness and beauty of the water body would please people as well as benefit the aquatic ecosystems. As we are entering a data-rich era, this pilot project aims to explore the concept of using​ ​ video cameras and smart sensors to collect and monitor water quality condition at the Bristol harbourside. The video cameras and smart sensors are connected to the Bristol Is Open network, an open programmable city platform. This will be the​ first​ attempt to collect water quality data in real time in the​ ​Bristol urban area with the wireless network. The videos and images of the water body collected by the cameras will be correlated with the in-situ water quality parameters for research​ ​purposes. The successful implementation of the sensors can attract more academic researchers and industrial partners to expand the sensor network to multiple locations​ ​around the city covering the other parts of the Harbour and River Avon, leading to a new generation of urban system infrastructure model.

  17. Assessment of the Spatial and Temporal Variations of Water Quality for Agricultural Lands with Crop Rotation in China by Using a HYPE Model.

    Science.gov (United States)

    Yin, Yunxing; Jiang, Sanyuan; Pers, Charlotta; Yang, Xiaoying; Liu, Qun; Yuan, Jin; Yao, Mingxing; He, Yi; Luo, Xingzhang; Zheng, Zheng

    2016-03-18

    Many water quality models have been successfully used worldwide to predict nutrient losses from anthropogenically impacted catchments, but hydrological and nutrient simulations with limited data are difficult considering the transfer of model parameters and complication of model calibration and validation. This study aims: (i) to assess the performance capabilities of a new and relatively more advantageous model, namely, Hydrological Predictions for the Environment (HYPE), that simulates stream flow and nutrient load in agricultural areas by using a multi-site and multi-objective parameter calibration method and (ii) to investigate the temporal and spatial variations of total nitrogen (TN) and total phosphorous (TP) concentrations and loads with crop rotation by using the model for the first time. A parameter estimation tool (PEST) was used to calibrate parameters. Results show that the parameters related to the effective soil porosity were highly sensitive to hydrological modeling. N balance was largely controlled by soil denitrification processes. P balance was influenced by the sedimentation rate and production/decay of P in rivers and lakes. The model reproduced the temporal and spatial variations of discharge and TN/TP relatively well in both calibration (2006-2008) and validation (2009-2010) periods. Among the obtained data, the lowest Nash-Suttclife efficiency of discharge, daily TN load, and daily TP load were 0.74, 0.51, and 0.54, respectively. The seasonal variations of daily TN concentrations in the entire simulation period were insufficient, indicated that crop rotation changed the timing and amount of N output. Monthly TN and TP simulation yields revealed that nutrient outputs were abundant in summer in terms of the corresponding discharge. The area-weighted TN and TP load annual yields in five years showed that nutrient loads were extremely high along Hong and Ru rivers, especially in agricultural lands.

  18. Assessment of the Spatial and Temporal Variations of Water Quality for Agricultural Lands with Crop Rotation in China by Using a HYPE Model

    Directory of Open Access Journals (Sweden)

    Yunxing Yin

    2016-03-01

    Full Text Available Many water quality models have been successfully used worldwide to predict nutrient losses from anthropogenically impacted catchments, but hydrological and nutrient simulations with limited data are difficult considering the transfer of model parameters and complication of model calibration and validation. This study aims: (i to assess the performance capabilities of a new and relatively more advantageous model, namely, Hydrological Predictions for the Environment (HYPE, that simulates stream flow and nutrient load in agricultural areas by using a multi-site and multi-objective parameter calibration method and (ii to investigate the temporal and spatial variations of total nitrogen (TN and total phosphorous (TP concentrations and loads with crop rotation by using the model for the first time. A parameter estimation tool (PEST was used to calibrate parameters. Results show that the parameters related to the effective soil porosity were highly sensitive to hydrological modeling. N balance was largely controlled by soil denitrification processes. P balance was influenced by the sedimentation rate and production/decay of P in rivers and lakes. The model reproduced the temporal and spatial variations of discharge and TN/TP relatively well in both calibration (2006–2008 and validation (2009–2010 periods. Among the obtained data, the lowest Nash-Suttclife efficiency of discharge, daily TN load, and daily TP load were 0.74, 0.51, and 0.54, respectively. The seasonal variations of daily TN concentrations in the entire simulation period were insufficient, indicated that crop rotation changed the timing and amount of N output. Monthly TN and TP simulation yields revealed that nutrient outputs were abundant in summer in terms of the corresponding discharge. The area-weighted TN and TP load annual yields in five years showed that nutrient loads were extremely high along Hong and Ru rivers, especially in agricultural lands.

  19. 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.

  20. 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.

  1. Water Quality Index Assessment of Pogradec Water- Supply, in Albania

    OpenAIRE

    , P. Icka; , R. Damo

    2016-01-01

    In this paper is applied for the first time in Albania Water Quality Index (WQI) of the Canadian Council of Ministries of the Environment (CCME) for assessment of water quality of water supply network on Pogradec city. CCME WQI, a technique of rating water quality, is an effective tool to assess spatial and temporal changes on the quality of any water body. Calculations of the index are based on a combination of three factors: scope - the number of variables whose objectives are not met; freq...

  2. A novel integrated modelling framework to assess the impacts of climate and socio-economic drivers on land use and water quality.

    Science.gov (United States)

    Zessner, Matthias; Schönhart, Martin; Parajka, Juraj; Trautvetter, Helene; Mitter, Hermine; Kirchner, Mathias; Hepp, Gerold; Blaschke, Alfred Paul; Strenn, Birgit; Schmid, Erwin

    2017-02-01

    Changes in climatic conditions will directly affect the quality and quantity of water resources. Further on, they will affect them indirectly through adaptation in land use which ultimately influences diffuse nutrient emissions to rivers and therefore potentially the compliance with good ecological status according to the EU Water Framework Directive (WFD). We present an integrated impact modelling framework (IIMF) to track and quantify direct and indirect pollution impacts along policy-economy-climate-agriculture-water interfaces. The IIMF is applied to assess impacts of climatic and socio-economic drivers on agricultural land use (crop choices, farming practices and fertilization levels), river flows and the risk for exceedance of environmental quality standards for determination of the ecological water quality status in Austria. This article also presents model interfaces as well as validation procedures and results of single models and the IIMF with respect to observed state variables such as land use, river flow and nutrient river loads. The performance of the IIMF for calculations of river nutrient loads (120 monitoring stations) shows a Nash-Sutcliffe Efficiency of 0.73 for nitrogen and 0.51 for phosphorus. Most problematic is the modelling of phosphorus loads in the alpine catchments dominated by forests and mountainous landscape. About 63% of these catchments show a deviation between modelled and observed loads of 30% and more. In catchments dominated by agricultural production, the performance of the IIMF is much better as only 30% of cropland and 23% of permanent grassland dominated areas have a deviation of >30% between modelled and observed loads. As risk of exceedance of environmental quality standards is mainly recognized in catchments dominated by cropland, the IIMF is well suited for assessing the nutrient component of the WFD ecological status. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

  3. 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.

  4. 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.

    Science.gov (United States)

    Laudon, Hjalmar; Poléo, Antonio B S; Vøllestad, Leif Asbjørn; Bishop, Kevin

    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.

  5. Models of educational institutions' networking

    OpenAIRE

    Shilova Olga Nikolaevna

    2015-01-01

    The importance of educational institutions' networking in modern sociocultural conditions and a definition of networking in education are presented in the article. The results of research levels, methods and models of educational institutions' networking are presented and substantially disclosed.

  6. 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).

  7. 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.

  8. 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...

  9. Attenuation coefficients for water quality trading

    OpenAIRE

    Keller, AA; Chen, X.; Fox, J; Fulda, M; Dorsey, R.; Seapy, B; Glenday, J; E Bray

    2014-01-01

    Water quality trading has been proposed as a cost-effective approach for reducing nutrient loads through credit generation from agricultural or point source reductions sold to buyers facing costly options. We present a systematic approach to determine attenuation coefficients and their uncertainty. Using a process-based model, we determine attenuation with safety margins at many watersheds for total nitrogen (TN) and total phosphorus (TP) loads as they transport from point of load reduction t...

  10. Estimation of urban runoff and water quality using remote sensing and artificial intelligence.

    Science.gov (United States)

    Ha, S R; Park, S Y; Park, D H

    2003-01-01

    Water quality and quantity of runoff are strongly dependent on the landuse and landcover (LULC) criteria. In this study, we developed a more improved parameter estimation procedure for the environmental model using remote sensing (RS) and artificial intelligence (AI) techniques. Landsat TM multi-band (7bands) and Korea Multi-Purpose Satellite (KOMPSAT) panchromatic data were selected for input data processing. We employed two kinds of artificial intelligence techniques, RBF-NN (radial-basis-function neural network) and ANN (artificial neural network), to classify LULC of the study area. A bootstrap resampling method, a statistical technique, was employed to generate the confidence intervals and distribution of the unit load. SWMM was used to simulate the urban runoff and water quality and applied to the study watershed. The condition of urban flow and non-point contaminations was simulated with rainfall-runoff and measured water quality data. The estimated total runoff, peak time, and pollutant generation varied considerably according to the classification accuracy and percentile unit load applied. The proposed procedure would efficiently be applied to water quality and runoff simulation in a rapidly changing urban area.

  11. Techniques for Modelling Network Security

    OpenAIRE

    Lech Gulbinovič

    2012-01-01

    The article compares modelling techniques for network security, including the theory of probability, Markov processes, Petri networks and application of stochastic activity networks. The paper introduces the advantages and disadvantages of the above proposed methods and accepts the method of modelling the network of stochastic activity as one of the most relevant. The stochastic activity network allows modelling the behaviour of the dynamic system where the theory of probability is inappropri...

  12. Predicting the Effect of Changing Precipitation Extremes and Land Cover Change on Urban Water Quality

    Science.gov (United States)

    SUN, N.; Yearsley, J. R.; Lettenmaier, D. P.

    2013-12-01

    Recent research shows that precipitation extremes in many of the largest U.S. urban areas have increased over the last 60 years. These changes have important implications for stormwater runoff and water quality, which in urban areas are dominated by the most extreme precipitation events. We assess the potential implications of changes in extreme precipitation and changing land cover in urban and urbanizing watersheds at the regional scale using a combination of hydrology and water quality models. Specifically, we describe the integration of a spatially distributed hydrological model - the Distributed Hydrology Soil Vegetation Model (DHSVM), the urban water quality model in EPA's Storm Water Management Model (SWMM), the semi-Lagrangian stream temperature model RBM10, and dynamical and statistical downscaling methods applied to global climate predictions. Key output water quality parameters include total suspended solids (TSS), toal nitrogen, total phosphorous, fecal coliform bacteria and stream temperature. We have evaluated the performance of the modeling system in the highly urbanized Mercer Creek watershed in the rapidly growing Bellevue urban area in WA, USA. The results suggest that the model is able to (1) produce reasonable streamflow predictions at fine temporal and spatial scales; (2) provide spatially distributed water temperature predictions that mostly agree with observations throughout a complex stream network, and characterize impacts of climate, landscape, near-stream vegetation change on stream temperature at local and regional scales; and (3) capture plausibly the response of water quality constituents to varying magnitude of precipitation events in urban environments. Next we will extend the scope of the study from the Mercer Creek watershed to include the entire Puget Sound Basin, WA, USA.

  13. Water Quality Control, Curriculum Guide.

    Science.gov (United States)

    Washington City Board of Education, NC.

    Activities which study how water is used, contaminated, and treated or purified are presented in this curriculum guide, culminating in the investigation of a local water quality problem. Designed as a 12 week mini-course for students in grades eight and nine, the guide first presents a review of the content, objectives, major concepts, and sources…

  14. 5 Water Quality.cdr

    African Journals Online (AJOL)

    Administrator

    degraded forested area from the developing world where agricultural-derived revenue ... The water quality assessment conducted in the Densu, Birim and Ayensu Basins of Ghana in the Okyeman area between August 2005 and June 2006 .... Akwadun (Bridge-down) and. Kukurantumi. • Birim River Stations: Bunso Cocoa.

  15. 3D Printing-Based Integrated Water Quality Sensing System.

    Science.gov (United States)

    Banna, Muinul; Bera, Kaustav; Sochol, Ryan; Lin, Liwei; Najjaran, Homayoun; Sadiq, Rehan; Hoorfar, Mina

    2017-06-08

    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.

  16. 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.

  17. 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...

  18. General equilibrium modelling of the direct and indirect economic impacts of water quality improvements in the Netherlands at national and river basin scale

    NARCIS (Netherlands)

    Brouwer, R.; Hofkes, M.W.; Linderhof, V.G.M.

    2008-01-01

    The main objective of the study presented in this paper is to estimate the direct and indirect economic impacts of water quality policy scenarios in the Netherlands focusing on the reduction of emission levels of nutrients and a number of eco-toxicological substances. For this purpose, an Applied

  19. Landscape-scale modeling of water quality in Lake Superior and Lake Michigan watersheds: How useful are forest-based indicators? Journal of Great Lakes Research

    Science.gov (United States)

    Titus S. Seilheimer; Patrick L. Zimmerman; Kirk M. Stueve; Charles H. Perry

    2013-01-01

    The Great Lakes watersheds have an important influence on the water quality of the nearshore environment, therefore, watershed characteristics can be used to predict what will be observed in the streams. We used novel landscape information describing the forest cover change, along with forest census data and established land cover data to predict total phosphorus and...

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

    Directory of Open Access Journals (Sweden)

    Hong Yao

    Full Text Available 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.

  1. 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

  2. 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

  3. 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

  4. Modeling Network Interdiction Tasks

    Science.gov (United States)

    2015-09-17

    allow professionals and families to stay in touch through voice or video calls. Power grids provide electricity to homes , offices, and recreational...instances using IBMr ILOGr CPLEXr Optimization Studio V12.6. For each instance, two solutions are deter- mined. First, the MNDP-a model is solved with no...three values: 0.25, 0.50, or 0.75. The DMP-a model is solved for the various random network instances using IBMr ILOGr CPLEXr Optimization Studio V12.6

  5. Water quality monitoring using remote sensing technique

    Science.gov (United States)

    Adsavakulchai, Suwannee; Panichayapichet, Paweena

    2003-03-01

    There has been a rapid growth of shrimp farm around Kung Krabaen Bay in the past decade. This has caused enormous rise in generation of domestic and industrial wastes. Most of these wastes are disposed in the Kung Krabaen Bay. There is a serious need to retain this glory by better water quality management of this river. Conventional methods of monitoring of water quality have limitations in collecting information about water quality parameters for a large region in detailed manner due to high cost and time. Satellite based technologies have offered an alternate approach for many environmental monitoring needs. In this study, the high-resolution satellite data (LANDSAT TM) was utilized to develop mathematical models for monitoring of chlorophyll-a. Comparison between empirical relationship of spectral reflectance with chl-a and band ratio between the near infrared (NIR) and red was suggested to detect chlorophyll in water. This concept has been successfully employed for marine zones and big lakes but not for narrow rivers due to constraints of spatial resolution of satellite data. This information will be very useful in locating point and non-point sources of pollution and will help in designing and implementing controlling structures.

  6. Fuzzy Logic Water Quality Index and Importance of Water Quality Parameters

    Directory of Open Access Journals (Sweden)

    Raman Bai. V

    2009-01-01

    Full Text Available Determination of status of water quality of a river or any other water sources is highly indeterminate. It is necessary to have a competent model to predict the status of water quality and to advice for type of water treatment for meeting different demands. One such model (UNIQ2007 is developed as an application software in water quality engineering. The unit operates in a fuzzy logic mode including a fuzzification engine receiving a plurality of input variables on its input and being adapted to compute membership function parameters. A processor engine connected downstream of the fuzzification unit will produce fuzzy set, based on fuzzy variable viz. DO, BOD, COD, AN, SS and pH. It has a defuzzification unit operative to translate the inference results into a discrete crisp value of WQI. The UNIQ2007 contains a first memory device connected to the fuzzification unit and containing the set of membership functions, a secondary memory device connected to the defuzzification unit and containing the set of crisp value which appear in the THEN part of the fuzzy rules and an additional memory device connected to the defuzzification unit. More advantageously, UINQ2007 is constructed with control elements having dynamic fuzzy logic properties wherein target non-linearity can be input to result in a perfect evaluation of water quality. The development of the fuzzy model with one river system is explained in this paper. Further the model has been evaluated with the data from few rivers in Malaysia, India and Thailand. This water quality assessor probe can provide better quality index or identify the status of river with 90% perfection. Presently, WQI in most of the countries is referring to physic-chemical parameters only due to great efforts needed to quantify the biological parameters. This study ensures a better method to include pathogens into WQI due to superior capabilities of fuzzy logic in dealing with non-linear, complex and uncertain systems.