Development of Water Quality Modeling in the United States

EPA Science Inventory

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

DTIC Science & Technology

2016-07-01

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

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

USGS Publications Warehouse

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 in water-quality conditions through time, characterizing potentially harmful cyanobacterial events, and indicating changes in water-quality conditions that may affect drinking-water treatment processes.

Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model

PubMed Central

Xu, Shiguo; Wang, Tianxiang; Hu, Suduan

2015-01-01

Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results. PMID:25689998

Dynamic assessment of water quality based on a variable fuzzy pattern recognition model.

PubMed

Xu, Shiguo; Wang, Tianxiang; Hu, Suduan

2015-02-16

Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results.

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

NASA Astrophysics Data System (ADS)

SHI, J.

2014-12-01

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

Modeling the Water - Quality Effects of Changes to the Klamath River Upstream of Keno Dam, Oregon

USGS Publications Warehouse

Sullivan, Annett B.; Sogutlugil, I. Ertugrul; Rounds, Stewart A.; Deas, Michael L.

2013-01-01

The Link River to Keno Dam (Link-Keno) reach of the Klamath River, Oregon, generally has periods of water-quality impairment during summer, including low dissolved oxygen, elevated concentrations of ammonia and algae, and high pH. Efforts are underway to improve water quality in this reach through a Total Maximum Daily Load (TMDL) program and other management and operational actions. To assist in planning, a hydrodynamic and water-quality model was used in this study to provide insight about how various actions could affect water quality in the reach. These model scenarios used a previously developed and calibrated CE-QUAL-W2 model of the Link-Keno reach developed by the U.S. Geological Survey (USGS), Watercourse Engineering Inc., and the Bureau of Reclamation for calendar years 2006-09 (referred to as the "USGS model" in this report). Another model of the same river reach was previously developed by Tetra Tech, Inc. and the Oregon Department of Environmental Quality for years 2000 and 2002 and was used in the TMDL process; that model is referred to as the "TMDL model" in this report. This report includes scenarios that (1) assess the effect of TMDL allocations on water quality, (2) provide insight on certain aspects of the TMDL model, (3) assess various methods to improve water quality in this reach, and (4) examine possible water-quality effects of a future warmer climate. Results presented in this report for the first 5 scenarios supersede or augment those that were previously published (scenarios 1 and 2 in Sullivan and others [2011], 3 through 5 in Sullivan and others [2012]); those previous results are still valid, but the results for those scenarios in this report are more current.

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

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

2018-04-22

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

Water quality modelling of Jadro spring.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Boon, J.; Smits, J. G.

2006-12-01

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

An Integrated Decision Support System for Water Quality Management of Songhua River Basin

NASA Astrophysics Data System (ADS)

Zhang, Haiping; Yin, Qiuxiao; Chen, Ling

2010-11-01

In the Songhua River Basin of China, many water resource and water environment conflicts interact. A Decision Support System (DSS) for the water quality management has been established for the Basin. The System is featured by the incorporation of a numerical water quality model system into a conventional water quality management system which usually consists of geographic information system (GIS), WebGIS technology, database system and network technology. The model system is built based on DHI MIKE software comprising of a basin rainfall-runoff module, a basin pollution load evaluation module, a river hydrodynamic module and a river water quality module. The DSS provides a friendly graphical user interface that enables the rapid and transparent calculation of various water quality management scenarios, and also enables the convenient access and interpretation of the modeling results to assist the decision-making.

Implications of Modeling Uncertainty for Water Quality Decision Making

NASA Astrophysics Data System (ADS)

Shabman, L.

2002-05-01

The report, National Academy of Sciences report, "Assessing the TMDL Approach to Water Quality Management" endorsed the "watershed" and "ambient water quality focused" approach" to water quality management called for in the TMDL program. The committee felt that available data and models were adequate to move such a program forward, if the EPA and all stakeholders better understood the nature of the scientific enterprise and its application to the TMDL program. Specifically, the report called for a greater acknowledgement of model prediction uncertinaity in making and implementing TMDL plans. To assure that such uncertinaity was addressed in water quality decision making the committee called for a commitment to "adaptive implementation" of water quality management plans. The committee found that the number and complexity of the interactions of multiple stressors, combined with model prediction uncertinaity means that we need to avoid the temptation to make assurances that specific actions will result in attainment of particular water quality standards. Until the work on solving a water quality problem begins, analysts and decision makers cannot be sure what the correct solutions are, or even what water quality goals a community should be seeking. In complex systems we need to act in order to learn; adaptive implementation is a concurrent process of action and learning. Learning requires (1) continued monitoring of the waterbody to determine how it responds to the actions taken and (2) carefully designed experiments in the watershed. If we do not design learning into what we attempt we are not doing adaptive implementation. Therefore, there needs to be an increased commitment to monitoring and experiments in watersheds that will lead to learning. This presentation will 1) explain the logic for adaptive implementation; 2) discuss the ways that water quality modelers could characterize and explain model uncertinaity to decision makers; 3) speculate on the implications of the adaptive implementation for setting of water quality standards, for design of watershed monitoring programs and for the regulatory rules governing the TMDL program implementation.

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

PubMed

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

2015-05-01

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

Long-term behaviour and cross-correlation water quality analysis of the River Elbe, Germany.

PubMed

Lehmann, A; Rode, M

2001-06-01

This study analyses weekly data samples from the river Elbe at Magdeburg between 1984 and 1996 to investigate the changes in metabolism and water quality in the river Elbe since the German reunification in 1990. Modelling water quality variables by autoregressive component models and ARIMA models reveals the improvement of water quality due to the reduction of waste water emissions since 1990. The models are used to determine the long-term and seasonal behaviour of important water quality variables. Organic and heavy metal pollution parameters showed a significant decrease since 1990, however, no significant change of chlorophyll-a as a measure for primary production could be found. A new procedure for testing the significance of a sample correlation coefficient is discussed, which is able to detect spurious sample correlation coefficients without making use of time-consuming prewhitening. The cross-correlation analysis is applied to hydrophysical, biological, and chemical water quality variables of the river Elbe since 1984. Special emphasis is laid on the detection of spurious sample correlation coefficients.

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

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Relations of water-quality constituent concentrations to surrogate measurements in the lower Platte River corridor, Nebraska, 2007 through 2011

USGS Publications Warehouse

Schaepe, Nathaniel J.; Soenksen, Philip J.; Rus, David L.

2014-01-01

The lower Platte River, Nebraska, provides drinking water, irrigation water, and in-stream flows for recreation, wildlife habitat, and vital habitats for several threatened and endangered species. The U.S. Geological Survey (USGS), in cooperation with the Lower Platte River Corridor Alliance (LPRCA) developed site-specific regression models for water-quality constituents at four sites (Shell Creek near Columbus, Nebraska [USGS site 06795500]; Elkhorn River at Waterloo, Nebr. [USGS site 06800500]; Salt Creek near Ashland, Nebr. [USGS site 06805000]; and Platte River at Louisville, Nebr. [USGS site 06805500]) in the lower Platte River corridor. The models were developed by relating continuously monitored water-quality properties (surrogate measurements) to discrete water-quality samples. These models enable existing web-based software to provide near-real-time estimates of stream-specific constituent concentrations to support natural resources management decisions. Since 2007, USGS, in cooperation with the LPRCA, has continuously monitored four water-quality properties seasonally within the lower Platte River corridor: specific conductance, water temperature, dissolved oxygen, and turbidity. During 2007 through 2011, the USGS and the Nebraska Department of Environmental Quality collected and analyzed discrete water-quality samples for nutrients, major ions, pesticides, suspended sediment, and bacteria. These datasets were used to develop the regression models. This report documents the collection of these various water-quality datasets and the development of the site-specific regression models. Regression models were developed for all four monitored sites. Constituent models for Shell Creek included nitrate plus nitrite, total phosphorus, orthophosphate, atrazine, acetochlor, suspended sediment, and Escherichia coli (E. coli) bacteria. Regression models that were developed for the Elkhorn River included nitrate plus nitrite, total Kjeldahl nitrogen, total phosphorus, orthophosphate, chloride, atrazine, acetochlor, suspended sediment, and E. coli. Models developed for Salt Creek included nitrate plus nitrite, total Kjeldahl nitrogen, suspended sediment, and E. coli. Lastly, models developed for the Platte River site included total Kjeldahl nitrogen, total phosphorus, sodium, metolachlor, atrazine, acetochlor, suspended sediment, and E. coli.

A three-dimensional conceptual model of the water quality distribution in the Albuquerque Basin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romero, D.

1995-12-31

It is possible to construct a conceptual model of the Albuquerque Basin`s geochemical characteristics and water quality distribution based on (1) the Hawley and Haase hydrogeological model, (2) water analyses from City of Albuquerque water wells, and (3) sound geological and chemical principles. Previous studies have characterized the water quality and geochemistry of the Albuquerque Basin from a two-dimensional perspective; however, to date, there has been no examination of the variation of water quality with depth within the Albuquerque Basin. The primary focus of this paper is to describe a first attempt at developing a conceptual understanding of the three-dimensionalmore » water quality distribution of the Albuquerque Basin based on the above three building blocks.« less

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

PubMed

Lu, Yan; He, Tian

2014-09-15

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

Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Kong, Shish-Jeng; Chang, Chih-Hua

2018-03-01

The turbidity (TB) of a water body varies with time and space. Water quality is traditionally estimated via linear regression based on satellite images. However, estimating and mapping water quality require a spatio-temporal nonstationary model, while TB mapping necessitates the use of geographically and temporally weighted regression (GTWR) and geographically weighted regression (GWR) models, both of which are more precise than linear regression. Given the temporal nonstationary models for mapping water quality, GTWR offers the best option for estimating regional water quality. Compared with GWR, GTWR provides highly reliable information for water quality mapping, boasts a relatively high goodness of fit, improves the explanation of variance from 44% to 87%, and shows a sufficient space-time explanatory power. The seasonal patterns of TB and the main spatial patterns of TB variability can be identified using the estimated TB maps from GTWR and by conducting an empirical orthogonal function (EOF) analysis.

Research on the Relationship between Water Diversion and Water Quality of Xuanwu Lake, China.

PubMed

Song, Weiwei; Xu, Qing; Fu, Xingqian; Zhang, Peng; Pang, Yong; Song, Dahao

2018-06-14

Water diversion is often used to improve water quality to reach the standard of China in the short term. However, this large amount of water diversion can not only improve the water quality, but also lead to a decline in the water quality (total phosphorus, total nitrogen) of Xuanwu Lake. Through theoretical analysis, the relationship between water quality and water diversion is established. We also found that the multiplication of the pollutant degradation coefficient ( K ) and the water residence time ( T ) is a constant ( N ), K⋅T=N. The water quality changed better at first, with the increase of inflow discharge, and then became worse, and the optimal water quality inflow discharge is 180,000 m³/day. By constructing two-dimensional hydrodynamic and water quality models, the optimal diversion water plan is calculated. Through model calculations, it can be seen that reducing the inflow discharge makes the water residence time longer (15.3 days changed to 23.8 days). Thereby, increasing the degradation of pollutants, and thus improving water quality. Compared with other wind directions, the southwest wind makes the water quality of Xuanwu Lake the most uniform. The concentration of water quality first became smaller and then became larger, as the wind speed increased, and eventually became constant. Implementing these results for water quality improvement in small and medium lakes will significantly reduce the cost of water diversion.

Simulation of effects of wastewater discharges on Sand Creek and lower Caddo Creek near Ardmore, Oklahoma

USGS Publications Warehouse

Wesolowski, Edwin A.

1999-01-01

A streamflow and water-quality model was developed for reaches of Sand and Caddo Creeks in south-central Oklahoma to simulate the effects of wastewater discharge from a refinery and a municipal treatment plant.The purpose of the model was to simulate conditions during low streamflow when the conditions controlling dissolved-oxygen concentrations are most severe. Data collected to calibrate and verify the streamflow and water-quality model include continuously monitored streamflow and water-quality data at two gaging stations and three temporary monitoring stations; wastewater discharge from two wastewater plants; two sets each of five water-quality samples at nine sites during a 24-hour period; dye and propane samples; periphyton samples; and sediment oxygen demand measurements. The water-quality sampling, at a 6-hour frequency, was based on a Lagrangian reference frame in which the same volume of water was sampled at each site. To represent the unsteady streamflows and the dynamic water-quality conditions, a transport modeling system was used that included both a model to route streamflow and a model to transport dissolved conservative constituents with linkage to reaction kinetics similar to the U.S. Environmental Protection Agency QUAL2E model to simulate nonconservative constituents. These model codes are the Diffusion Analogy Streamflow Routing Model (DAFLOW) and the branched Lagrangian transport model (BLTM) and BLTM/QUAL2E that, collectively, as calibrated models, are referred to as the Ardmore Water-Quality Model.The Ardmore DAFLOW model was calibrated with three sets of streamflows that collectively ranged from 16 to 3,456 cubic feet per second. The model uses only one set of calibrated coefficients and exponents to simulate streamflow over this range. The Ardmore BLTM was calibrated for transport by simulating dye concentrations collected during a tracer study when streamflows ranged from 16 to 23 cubic feet per second. Therefore, the model is expected to be most useful for low streamflow simulations. The Ardmore BLTM/QUAL2E model was calibrated and verified with water-quality data from nine sites where two sets of five samples were collected. The streamflow during the water-quality sampling in Caddo Creek at site 7 ranged from 8.4 to 20 cubic feet per second, of which about 5.0 to 9.7 cubic feet per second was contributed by Sand Creek. The model simulates the fate and transport of 10 water-quality constituents. The model was verified by running it using data that were not used in calibration; only phytoplankton were not verified.Measured and simulated concentrations of dissolved oxygen exhibited a marked daily pattern that was attributable to waste loading and algal activity. Dissolved-oxygen measurements during this study and simulated dissolved-oxygen concentrations using the Ardmore Water-Quality Model, for the conditions of this study, illustrate that the dissolved-oxygen sag curve caused by the upstream wastewater discharges is confined to Sand Creek.

AMERICAN-SOVIET SYMPOSIUM ON USE OF MATHEMATICAL MODELS TO OPTIMIZE WATER QUALITY MANAGEMENT HELD AT KHARKOV AND ROSTOV-ON-DON, USSR ON DECEMBER 9-16, 1975

EPA Science Inventory

The American-Soviet Symposium on Use of Mathematical Models to Optimize Water Quality Management examines methodological questions related to simulation and optimization modeling of processes that determine water quality of river basins. Discussants describe the general state of ...

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

PubMed

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.

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

PubMed

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.

ENHANCED STREAM WATER QUALITY MODEL (QUAL2EU)

EPA Science Inventory

The enhanced stream water quality model QUAL2E and QUAL2E-UNCAS (37) permits simulation of several water quality constituents in a branching stream system using a finite difference solution to the one-dimensional advective-dispersive mass transport and reaction equation. The con...

Land use impact on water quality: valuing forest services in terms of the water supply sector.

PubMed

Fiquepron, Julien; Garcia, Serge; Stenger, Anne

2013-09-15

The aim of this paper is to quantify the impact of the forest on raw water quality within the framework of other land uses. On the basis of measurements of quality parameters that were identified as being the most problematic (i.e., pesticides and nitrates), we modeled how water quality is influenced by land uses. In order to assess the benefits provided by the forest in terms of improved water quality, we used variations of drinking water prices that were determined by the operating costs of water supply services (WSS). Given the variability of links between forests and water quality, we chose to cover all of France using data observed in each administrative department (France is divided into 95 départements), including a description of WSS and information on land uses. We designed a model that describes the impact of land uses on water quality, as well as the operation of WSS and prices. This bioeconomic model was estimated by the generalized method of moments (GMM) to account for endogeneity and heteroscedasticity issues. We showed that the forest has a positive effect on raw water quality compared to other land uses, with an indirect impact on water prices, making them lower for consumers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Hydrogeology, ground-water quality, and source of ground water causing water-quality changes in the Davis well field at Memphis, Tennessee

USGS Publications Warehouse

Parks, William S.; Mirecki, June E.; Kingsbury, James A.

1995-01-01

NETPATH geochemical model code was used to mix waters from the alluvial aquifer with water from the Memphis aquifer using chloride as a conservative tracer. The resulting models indicated that a mixture containing 3 percent alluvial aquifer water mixed with 97 percent unaffected Memphis aquifer water would produce the chloride concentration measured in water from the Memphis aquifer well most affected by water-quality changes. NETPATH also was used to calculate mixing percentages of alluvial and Memphis aquifer Abstract waters based on changes in the concentrations of selected dissolved major inorganic and trace element constituents that define the dominant reactions that occur during mixing. These models indicated that a mixture containing 18 percent alluvial aquifer water and 82 percent unaffected Memphis aquifer water would produce the major constituent and trace element concentrations measured in water from the Memphis aquifer well most affected by water-quality changes. However, these model simulations predicted higher dissolved methane concentrations than were measured in water samples from the Memphis aquifer wells.

Assessing Cumulative Impacts of Coal Bed Methane Development on Surface Water Quality and its Suitability for Irrigation in the Powder River Basin

NASA Astrophysics Data System (ADS)

Dawson, H. E.

2003-12-01

This paper presents a mass balance approach to assessing the cumulative impacts of discharge from Coal Bed Methane (CBM) wells on surface water quality and its suitability for irrigation in the Powder River Basin. Key water quality parameters for predicting potential effects of CBM development on irrigated agriculture are sodicity, expressed as sodium adsorption ratio (SAR) and salinity, expressed as electrical conductivity (EC). The assessment was performed with the aid of a spreadsheet model, which was designed to estimate steady-state SAR and EC at gauged stream locations after mixing with CBM produced water. Model input included ambient stream water quality and flow, CBM produced water quality and discharge rates, conveyance loss (quantity of water loss that may occur between the discharge point and the receiving streams), beneficial uses, regulatory thresholds, and discharge allocation at state-line boundaries. Historical USGS data were used to establish ambient stream water quality and flow conditions. The resultant water quality predicted for each stream station included the cumulative discharge of CBM produced water in all reaches upstream of the station. Model output was presented in both tabular and graphical formats, and indicated the suitability of pre- and post-mixing water quality for irrigation. Advantages and disadvantages of the spreadsheet model are discussed. This approach was used by federal agencies to support the development of the January 2003 Environmental Impact Statements (EIS) for the Wyoming and Montana portions of the Powder River Basin.

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

USDA-ARS?s Scientific Manuscript database

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...

Water Operations Technical Support Program: Proceedings of the Seminar on Water Quality (9th) Held in San Antonio, Texas on 16-20 March 1992

DTIC Science & Technology

1992-10-01

System Model for Water Quality Control by Jackson K. Brown ...................................... 119 Management Technique for Long-Term Flow... Modeling Activities for the ARCS Program by David C. Cowgill ...................................... 141 Toxicity and Chemistry Testing of Great Lakes...225 Combined Hydrodynamic and Water Quality Modeling of Lower Green Bay by David J. Mark, Barry W. Bunch, and Norman W. Scheffner

Managing water quality under drought conditions in the Llobregat River Basin.

PubMed

Momblanch, Andrea; Paredes-Arquiola, Javier; Munné, Antoni; Manzano, Andreu; Arnau, Javier; Andreu, Joaquín

2015-01-15

The primary effects of droughts on river basins include both depleted quantity and quality of the available water resources, which can render water resources useless for human needs and simultaneously damage the environment. Isolated water quality analyses limit the action measures that can be proposed. Thus, an integrated evaluation of water management and quality is warranted. In this study, a methodology consisting of two coordinated models is used to combine aspects of water resource allocation and water quality assessment. Water management addresses water allocation issues by considering the storage, transport and consumption elements. Moreover, the water quality model generates time series of concentrations for several pollutants according to the water quality of the runoff and the demand discharges. These two modules are part of the AQUATOOL decision support system shell for water resource management. This tool facilitates the analysis of the effects of water management and quality alternatives and scenarios on the relevant variables in a river basin. This paper illustrates the development of an integrated model for the Llobregat River Basin. The analysis examines the drought from 2004 to 2008, which is an example of a period when the water system was quantitative and qualitatively stressed. The performed simulations encompass a wide variety of water management and water quality measures; the results provide data for making informed decisions. Moreover, the results demonstrated the importance of combining these measures depending on the evolution of a drought event and the state of the water resources system. Copyright © 2014 Elsevier B.V. All rights reserved.

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

EPA Science Inventory

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...

Use of ocean color scanner data in water quality mapping

NASA Technical Reports Server (NTRS)

Khorram, S.

1981-01-01

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

Performance of stochastic approaches for forecasting river water quality.

PubMed

Ahmad, S; Khan, I H; Parida, B P

2001-12-01

This study analysed water quality data collected from the river Ganges in India from 1981 to 1990 for forecasting using stochastic models. Initially the box and whisker plots and Kendall's tau test were used to identify the trends during the study period. For detecting the possible intervention in the data the time series plots and cusum charts were used. The three approaches of stochastic modelling which account for the effect of seasonality in different ways. i.e. multiplicative autoregressive integrated moving average (ARIMA) model. deseasonalised model and Thomas-Fiering model were used to model the observed pattern in water quality. The multiplicative ARIMA model having both nonseasonal and seasonal components were, in general, identified as appropriate models. In the deseasonalised modelling approach, the lower order ARIMA models were found appropriate for the stochastic component. The set of Thomas-Fiering models were formed for each month for all water quality parameters. These models were then used to forecast the future values. The error estimates of forecasts from the three approaches were compared to identify the most suitable approach for the reliable forecast. The deseasonalised modelling approach was recommended for forecasting of water quality parameters of a river.

Modelling the impacts of agricultural management practices on river water quality in Eastern England.

PubMed

Taylor, Sam D; He, Yi; Hiscock, Kevin M

2016-09-15

Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km(2). A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of unintended pollutant impacts when evaluating the effectiveness of mitigation options, and showed that high-frequency water quality datasets can be applied to robustly calibrate water quality models, creating DSTs that are more effective and reliable. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Watershed water environment pollution models and their applications: a review].

PubMed

Zhu, Yao; Liang, Zhi-Wei; Li, Wei; Yang, Yi; Yang, Mu-Yi; Mao, Wei; Xu, Han-Li; Wu, Wei-Xiang

2013-10-01

Watershed water environment pollution model is the important tool for studying watershed environmental problems. Through the quantitative description of the complicated pollution processes of whole watershed system and its parts, the model can identify the main sources and migration pathways of pollutants, estimate the pollutant loadings, and evaluate their impacts on water environment, providing a basis for watershed planning and management. This paper reviewed the watershed water environment models widely applied at home and abroad, with the focuses on the models of pollutants loading (GWLF and PLOAD), water quality of received water bodies (QUAL2E and WASP), and the watershed models integrated pollutant loadings and water quality (HSPF, SWAT, AGNPS, AnnAGNPS, and SWMM), and introduced the structures, principles, and main characteristics as well as the limitations in practical applications of these models. The other models of water quality (CE-QUAL-W2, EFDC, and AQUATOX) and watershed models (GLEAMS and MIKE SHE) were also briefly introduced. Through the case analysis on the applications of single model and integrated models, the development trend and application prospect of the watershed water environment pollution models were discussed.

Modelling the effect of wildfire on forested catchment water quality using the SWAT model

NASA Astrophysics Data System (ADS)

Yu, M.; Bishop, T.; van Ogtrop, F. F.; Bell, T.

2016-12-01

Wildfire removes the surface vegetation, releases ash, increase erosion and runoff, and therefore effects the hydrological cycle of a forested water catchment. It is important to understand chnage and how the catchment recovers. These processes are spatially sensitive and effected by interactions between fire severity and hillslope, soil type and surface vegetation conditions. Thus, a distributed hydrological modelling approach is required. In this study, the Soil and Water Analysis Tool (SWAT) is used to predict the effect of 2001/02 Sydney wild fire on catchment water quality. 10 years pre-fire data is used to create and calibrate the SWAT model. The calibrated model was then used to simulate the water quality for the 10 years post-fire period without fire effect. The simulated water quality data are compared with recorded water quality data provided by Sydney catchment authority. The mean change of flow, total suspended solid, total nitrate and total phosphate are compare on monthly, three month, six month and annual basis. Two control catchment and three burn catchment were analysed.

WATER QUALITY MODELING IN THE RIO CHONE ESTUARY

EPA Science Inventory

Water quality in the Rio Chone Estuary, a seasonally inverse, tropical estuary, in Ecuador was characterized by modeling the distribution of biochemical oxygen demand (BOD) and dissolved inorganic nitrogen (DIN) within the water column. These two variables are modeled using modif...

The risk assessment of sudden water pollution for river network system under multi-source random emission

NASA Astrophysics Data System (ADS)

Li, D.

2016-12-01

Sudden water pollution accidents are unavoidable risk events that we must learn to co-exist with. In China's Taihu River Basin, the river flow conditions are complicated with frequently artificial interference. Sudden water pollution accident occurs mainly in the form of a large number of abnormal discharge of wastewater, and has the characteristics with the sudden occurrence, the uncontrollable scope, the uncertainty object and the concentrated distribution of many risk sources. Effective prevention of pollution accidents that may occur is of great significance for the water quality safety management. Bayesian networks can be applied to represent the relationship between pollution sources and river water quality intuitively. Using the time sequential Monte Carlo algorithm, the pollution sources state switching model, water quality model for river network and Bayesian reasoning is integrated together, and the sudden water pollution risk assessment model for river network is developed to quantify the water quality risk under the collective influence of multiple pollution sources. Based on the isotope water transport mechanism, a dynamic tracing model of multiple pollution sources is established, which can describe the relationship between the excessive risk of the system and the multiple risk sources. Finally, the diagnostic reasoning algorithm based on Bayesian network is coupled with the multi-source tracing model, which can identify the contribution of each risk source to the system risk under the complex flow conditions. Taking Taihu Lake water system as the research object, the model is applied to obtain the reasonable results under the three typical years. Studies have shown that the water quality risk at critical sections are influenced by the pollution risk source, the boundary water quality, the hydrological conditions and self -purification capacity, and the multiple pollution sources have obvious effect on water quality risk of the receiving water body. The water quality risk assessment approach developed in this study offers a effective tool for systematically quantifying the random uncertainty in plain river network system, and it also provides the technical support for the decision-making of controlling the sudden water pollution through identification of critical pollution sources.

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

PubMed

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.

STORM WATER MANAGEMENT MODEL QUALITY ASSURANCE REPORT: DYNAMIC WAVE FLOW ROUTING

EPA Science Inventory

The Storm Water Management Model (SWMM) is a computer-based tool for simulating storm water runoff quantity and quality from primarily urban areas. In 2002 the U.S. Environmental Protection Agency’s Water Supply and Water Resources Division partnered with the consulting firm CDM ...

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

NASA Astrophysics Data System (ADS)

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 water quality. The developed system dynamics model is realized in the «PowerSim Studio» media. The data of natural measurements of water quality are applied for the model verification, and the correlated numerical results for the Russian Black Sea coast are presented. The main objective of the present paper is to present the actual examples, and to generalise the problems and to discuss the possible approaches of their solution.

[Water environmental capacity calculation model for the rivers in drinking water source conservation area].

PubMed

Chen, Ding-jiang; Lü, Jun; Shen, Ye-na; Jin, Shu-quan; Shi, Yi-ming

2008-09-01

Based on the one-dimension model for water environmental capacity (WEC) in river, a new model for the WEC estimation in river-reservoir system was developed in drinking water source conservation area (DWSCA). In the new model, the concept was introduced that the water quality target of the rivers in DWSCA was determined by the water quality demand of reservoir for drinking water source. It implied that the WEC of the reservoir could be used as the water quality control target at the reach-end of the upstream rivers in DWSCA so that the problems for WEC estimation might be avoided that the differences of the standards for a water quality control target between in river and in reservoir, such as the criterions differences for total phosphorus (TP)/total nitrogen (TN) between in reservoir and in river according to the National Surface Water Quality Standard of China (GB 3838-2002), and the difference of designed hydrology conditions for WEC estimation between in reservoir and in river. The new model described the quantitative relationship between the WEC of drinking water source and of the river, and it factually expressed the continuity and interplay of these low water areas. As a case study, WEC for the rivers in DWSCA of Laohutan reservoir located in southeast China was estimated using the new model. Results indicated that the WEC for TN and TP was 65.05 t x a(-1) and 5.05 t x a(-1) in the rivers of the DWSCA, respectively. According to the WEC of Laohutan reservoir and current TN and TP quantity that entered into the rivers, about 33.86 t x a(-1) of current TN quantity should be reduced in the DWSCA, while there was 2.23 t x a(-1) of residual WEC of TP in the rivers. The modeling method was also widely applicable for the continuous water bodies with different water quality targets, especially for the situation of higher water quality control target in downstream water body than that in upstream.

Correction of stream quality trends for the effects of laboratory measurement bias

USGS Publications Warehouse

Alexander, Richard B.; Smith, Richard A.; Schwarz, Gregory E.

1993-01-01

We present a statistical model relating measurements of water quality to associated errors in laboratory methods. Estimation of the model allows us to correct trends in water quality for long-term and short-term variations in laboratory measurement errors. An illustration of the bias correction method for a large national set of stream water quality and quality assurance data shows that reductions in the bias of estimates of water quality trend slopes are achieved at the expense of increases in the variance of these estimates. Slight improvements occur in the precision of estimates of trend in bias by using correlative information on bias and water quality to estimate random variations in measurement bias. The results of this investigation stress the need for reliable, long-term quality assurance data and efficient statistical methods to assess the effects of measurement errors on the detection of water quality trends.

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

PubMed

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.

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

USGS Publications Warehouse

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.

Modeling Source Water Threshold Exceedances with Extreme Value Theory

NASA Astrophysics Data System (ADS)

Rajagopalan, B.; Samson, C.; Summers, R. S.

2016-12-01

Variability in surface water quality, influenced by seasonal and long-term climate changes, can impact drinking water quality and treatment. In particular, temperature and precipitation can impact surface water quality directly or through their influence on streamflow and dilution capacity. Furthermore, they also impact land surface factors, such as soil moisture and vegetation, which can in turn affect surface water quality, in particular, levels of organic matter in surface waters which are of concern. All of these will be exacerbated by anthropogenic climate change. While some source water quality parameters, particularly Total Organic Carbon (TOC) and bromide concentrations, are not directly regulated for drinking water, these parameters are precursors to the formation of disinfection byproducts (DBPs), which are regulated in drinking water distribution systems. These DBPs form when a disinfectant, added to the water to protect public health against microbial pathogens, most commonly chlorine, reacts with dissolved organic matter (DOM), measured as TOC or dissolved organic carbon (DOC), and inorganic precursor materials, such as bromide. Therefore, understanding and modeling the extremes of TOC and Bromide concentrations is of critical interest for drinking water utilities. In this study we develop nonstationary extreme value analysis models for threshold exceedances of source water quality parameters, specifically TOC and bromide concentrations. In this, the threshold exceedances are modeled as Generalized Pareto Distribution (GPD) whose parameters vary as a function of climate and land surface variables - thus, enabling to capture the temporal nonstationarity. We apply these to model threshold exceedance of source water TOC and bromide concentrations at two locations with different climate and find very good performance.

Water Quality Analysis Simulation Program (WASP)

EPA Pesticide Factsheets

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream.

PubMed

Hong, Eun-Mi; Shelton, Daniel; Pachepsky, Yakov A; Nam, Won-Ho; Coppock, Cary; Muirhead, Richard

2017-02-01

Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four years to adequately evaluate the quality of water intended for produce irrigation. The objective of this work was to evaluate the effect of interannual weather variability on surface water microbial quality. We used the Soil and Water Assessment Tool model to simulate E. coli concentrations in the Little Cove Creek; this is a perennial creek located in an agricultural watershed in south-eastern Pennsylvania. The model performance was evaluated using the US FDA regulatory microbial water quality metrics of geometric mean (GM) and the statistical threshold value (STV). Using the 90-year time series of weather observations, we simulated and randomly sampled the time series of E. coli concentrations. We found that weather conditions of a specific year may strongly affect the evaluation of microbial quality and that the long-term assessment of microbial water quality may be quite different from the evaluation based on short-term observations. The variations in microbial concentrations and water quality metrics were affected by location, wetness of the hydrological years, and seasonality, with 15.7-70.1% of samples exceeding the regulatory threshold. The results of this work demonstrate the value of using modeling to design and evaluate monitoring protocols to assess the microbial quality of water used for produce irrigation. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

USGS Publications Warehouse

Booth, N.L.; Everman, E.J.; Kuo, I.-L.; Sprague, L.; Murphy, L.

2011-01-01

The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water-quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water-quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow-weighted concentration, or load of constituents in water under various land-use condition, change, or resource management scenarios. A web-based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

Artificial neural network modeling of the water quality index using land use areas as predictors.

PubMed

Gazzaz, Nabeel M; Yusoff, Mohd Kamil; Ramli, Mohammad Firuz; Juahir, Hafizan; Aris, Ahmad Zaharin

2015-02-01

This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management.

Projection pursuit water quality evaluation model based on chicken swam algorithm

NASA Astrophysics Data System (ADS)

Hu, Zhe

2018-03-01

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

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

USDA-ARS?s Scientific Manuscript database

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...

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

NASA Astrophysics Data System (ADS)

Ahmad, S.

2007-05-01

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

Water quality, hydrology, and the effects of changes in phosphorus loading to Pike Lake, Washington County, Wisconsin, with special emphasis on inlet-to-outlet short-circuiting

USGS Publications Warehouse

Rose, William J.; Robertson, Dale M.; Mergener, Elizabeth A.

2004-01-01

Simulations using water-quality models within the Wisconsin Lake Model Suite (WiLMS) indicated Pike Lake's response to 13 different phosphorus-loading scenarios. These scenarios included a base 'normal' year (2000) for which lake water quality and loading were known, six different percentage increases or decreases in phosphorus loading from controllable sources, and six different loading scenarios corresponding to specific management actions. Model simulations indicate that a 50-percent reduction in controllable loading sources would be needed to achieve a mesotrophic classification with respect to phosphorus, chlorophyll a, and Secchi depth (an index of water clarity). Model simulations indicated that short-circuiting of phosphorus from the inlet to the outlet was the main reason the water quality of the lake is good relative to the amount of loading from the Rubicon River and that changes in the percentage of inlet-to-outlet short-circuiting have a significant influence on the water quality of the lake.

Relations between continuous real-time physical properties and discrete water-quality constituents in the Little Arkansas River, south-central Kansas, 1998-2014

USGS Publications Warehouse

Rasmussen, Patrick P.; Eslick, Patrick J.; Ziegler, Andrew C.

2016-08-11

Water from the Little Arkansas River is used as source water for artificial recharge of the Equus Beds aquifer, one of the primary water-supply sources for the city of Wichita, Kansas. The U.S. Geological Survey has operated two continuous real-time water-quality monitoring stations since 1995 on the Little Arkansas River in Kansas. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to compute concentrations of those constituents of interest. Site-specific regression models were originally published in 2000 for the near Halstead and near Sedgwick U.S. Geological Survey streamgaging stations and the site-specific regression models were then updated in 2003. This report updates those regression models using discrete and continuous data collected during May 1998 through August 2014. In addition to the constituents listed in the 2003 update, new regression models were developed for total organic carbon. The real-time computations of water-quality concentrations and loads are available at http://nrtwq.usgs.gov. The water-quality information in this report is important to the city of Wichita because water-quality information allows for real-time quantification and characterization of chemicals of concern (including chloride), in addition to nutrients, sediment, bacteria, and atrazine transported in the Little Arkansas River. The water-quality information in this report aids in the decision making for water treatment before artificial recharge.

PREDICTIVE UNCERTAINTY IN HYDROLOGIC AND WATER QUALITY MODELING: APPROACHES, APPLICATION TO ENVIRONMENTAL MANAGEMENT, AND FUTURE CHALLENGES (PRESENTATION)

EPA Science Inventory

Extant process-based hydrologic and water quality models are indispensable to water resources planning and environmental management. However, models are only approximations of real systems and often calibrated with incomplete and uncertain data. Reliable estimates, or perhaps f...

PREDICTIVE UNCERTAINTY IN HYDROLOGIC AND WATER QUALITY MODELING: APPROACHES, APPLICATION TO ENVIRONMENTAL MANAGEMENT, AND FUTURE CHALLENGES

EPA Science Inventory

Extant process-based hydrologic and water quality models are indispensable to water resources planning and environmental management. However, models are only approximations of real systems and often calibrated with incomplete and uncertain data. Reliable estimates, or perhaps f...

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

EPA Science Inventory

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...

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

PubMed

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

2014-01-01

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

A framework for modeling contaminant impacts on reservoir water quality

NASA Astrophysics Data System (ADS)

Jeznach, Lillian C.; Jones, Christina; Matthews, Thomas; Tobiason, John E.; Ahlfeld, David P.

2016-06-01

This study presents a framework for using hydrodynamic and water quality models to understand the fate and transport of potential contaminants in a reservoir and to develop appropriate emergency response and remedial actions. In the event of an emergency situation, prior detailed modeling efforts and scenario evaluations allow for an understanding of contaminant plume behavior, including maximum concentrations that could occur at the drinking water intake and contaminant travel time to the intake. A case study assessment of the Wachusett Reservoir, a major drinking water supply for metropolitan Boston, MA, provides an example of an application of the framework and how hydrodynamic and water quality models can be used to quantitatively and scientifically guide management in response to varieties of contaminant scenarios. The model CE-QUAL-W2 was used to investigate the water quality impacts of several hypothetical contaminant scenarios, including hypothetical fecal coliform input from a sewage overflow as well as an accidental railway spill of ammonium nitrate. Scenarios investigated the impacts of decay rates, season, and inter-reservoir transfers on contaminant arrival times and concentrations at the drinking water intake. The modeling study highlights the importance of a rapid operational response by managers to contain a contaminant spill in order to minimize the mass of contaminant that enters the water column, based on modeled reservoir hydrodynamics. The development and use of hydrodynamic and water quality models for surface drinking water sources subject to the potential for contaminant entry can provide valuable guidance for making decisions about emergency response and remediation actions.

Interacting coastal based ecosystem services: recreation and water quality in Puget Sound, WA

USGS Publications Warehouse

Kreitler, Jason; Papenfus, Michael; Byrd, Kristin; Labiosa, William

2013-01-01

Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments.

Interacting Coastal Based Ecosystem Services: Recreation and Water Quality in Puget Sound, WA

PubMed Central

Kreitler, Jason; Papenfus, Michael; Byrd, Kristin; Labiosa, William

2013-01-01

Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments. PMID:23451067

Assessing the impacts of land use on downstream water quality using a hydrologically sensitive area concept.

PubMed

Giri, Subhasis; Qiu, Zeyuan; Zhang, Zhen

2018-05-01

Understanding the relationship between land use and water quality is essential to improve water quality through carefully managing landscape change. This study applies a linear mixed model at both watershed and hydrologically sensitive areas (HSAs) scales to assess such a relationship in 28 northcentral New Jersey watersheds located in a rapidly urbanizing region in the United States. Two models differ in terms of the geographic scope used to derive land use matrices that quantify land use conditions. The land use matrices at the watershed and HSAs scales represent the land use conditions in these watersheds and their HSAs, respectively. HSAs are the hydrological "hotspots" in a watershed that are prone to runoff generation during storm events. HSAs are derived using a soil topographic index (STI) that predicts hydrological sensitivity of a landscape based on a variable source area hydrology concept. The water quality indicators in these models are total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) concentrations in streams observed at the watershed outlets. The modeling results suggest that presence of low density urban land, agricultural land and wetlands elevate while forest decreases TN, TP and/or TSS concentrations in streams. The watershed scale model tends to emphasize the role of agricultural lands in water quality degradation while the HSA scale model highlights the role of forest in water quality improvement. This study supports the hypothesis that even though HSAs are relatively smaller area compared to watershed, still the land uses within HSAs have similar impacts on downstream water quality as the land uses in entire watersheds, since both models have negligible differences in model evaluation parameters. Inclusion of HSAs brings an interesting perspective to understand the dynamic relationships between land use and water quality. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

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

USDA-ARS?s Scientific Manuscript database

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...

AHP-based spatial analysis of water quality impact assessment due to change in vehicular traffic caused by highway broadening in Sikkim Himalaya

NASA Astrophysics Data System (ADS)

Banerjee, Polash; Ghose, Mrinal Kanti; Pradhan, Ratika

2018-05-01

Spatial analysis of water quality impact assessment of highway projects in mountainous areas remains largely unexplored. A methodology is presented here for Spatial Water Quality Impact Assessment (SWQIA) due to highway-broadening-induced vehicular traffic change in the East district of Sikkim. Pollution load of the highway runoff was estimated using an Average Annual Daily Traffic-Based Empirical model in combination with mass balance model to predict pollution in the rivers within the study area. Spatial interpolation and overlay analysis were used for impact mapping. Analytic Hierarchy Process-Based Water Quality Status Index was used to prepare a composite impact map. Model validation criteria, cross-validation criteria, and spatial explicit sensitivity analysis show that the SWQIA model is robust. The study shows that vehicular traffic is a significant contributor to water pollution in the study area. The model is catering specifically to impact analysis of the concerned project. It can be an aid for decision support system for the project stakeholders. The applicability of SWQIA model needs to be explored and validated in the context of a larger set of water quality parameters and project scenarios at a greater spatial scale.

Integrated planning for regional development planning and water resources management under uncertainty: A case study of Xining, China

NASA Astrophysics Data System (ADS)

Fu, Z. H.; Zhao, H. J.; Wang, H.; Lu, W. T.; Wang, J.; Guo, H. C.

2017-11-01

Economic restructuring, water resources management, population planning and environmental protection are subjects to inner uncertainties of a compound system with objectives which are competitive alternatives. Optimization model and water quality model are usually used to solve problems in a certain aspect. To overcome the uncertainty and coupling in reginal planning management, an interval fuzzy program combined with water quality model for regional planning and management has been developed to obtain the absolutely ;optimal; solution in this study. The model is a hybrid methodology of interval parameter programming (IPP), fuzzy programing (FP), and a general one-dimensional water quality model. The method extends on the traditional interval parameter fuzzy programming method by integrating water quality model into the optimization framework. Meanwhile, as an abstract concept, water resources carrying capacity has been transformed into specific and calculable index. Besides, unlike many of the past studies about water resource management, population as a significant factor has been considered. The results suggested that the methodology was applicable for reflecting the complexities of the regional planning and management systems within the planning period. The government policy makers could establish effective industrial structure, water resources utilization patterns and population planning, and to better understand the tradeoffs among economic, water resources, population and environmental objectives.

Influence of the South-North Water Diversion Project and the mitigation projects on the water quality of Han River.

PubMed

Zhu, Y P; Zhang, H P; Chen, L; Zhao, J F

2008-11-15

Situated in the central part of China, the Han River Basin is undergoing rapid social and economic development with some human interventions to be made soon which will profoundly influence the water environment of the basin. The integrated MIKE 11 model system comprising of a rainfall-runoff model (NAM), a non-point load evaluation model (LOAD), a hydrodynamic model (MIKE 11 HD) and a water quality model (ECOLab) was applied to investigate the impact of the Middle Route of the South-North Water Diversion Project on the Han River and the effectiveness of the 2 proposed mitigation projects, the 22 wastewater treatment plants (WWTPs) and the Yangtze-Han Water Diversion Project. The study concludes that business as usual will lead to a continuing rapid deterioration of the water quality of the Han River. Implementation of the Middle Route of the South-North Water Diversion Project in 2010 will bring disastrous consequence in the form of the remarkably elevated pollution level and high risk of algae bloom in the middle and lower reaches. The proposed WWTPs will merely lower the pollution level in the reach by around 10%, while the Yangtze-Han Water Diversion Project can significantly improve the water quality in the downstream 200-km reach. The results reveal that serious water quality problem will emerge in the middle reach between Xiangfan and Qianjiang in the future. Implementation of the South-North Water Diversion Project (phase II) in 2030 will further exacerbate the problem. In order to effectively improve the water quality of the Han River, it is suggested that nutrient removal processes should be adopted in the proposed WWTPs, and the pollution load from the non-point sources, especially the load from the upstream Henan Province, should be effectively controlled.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Taiping; Yang, Zhaoqing

Increased eutrophication and degraded water quality in estuarine and coastal waters have been a worldwide environmental concern. While it is commonly accepted that anthropogenic impact plays a major role in many emerging water quality issues, natural conditions such as restricted water circulations controlled by geometry may also substantially contribute to unfavorable water quality in certain ecosystems. To elucidate the contributions from different factors, a hydrodynamic-water quality model that integrates both physical transport and pollutant loadings is particularly warranted. A preliminary modeling study using the Environmental Fluid Dynamic Code (EFDC) is conducted to investigate hydrodynamic circulation and low dissolved oxygen (DO)more » in Hood Canal, a representative fjord in the U.S. Pacific Northwest. Because the water quality modeling work is still ongoing, this paper focuses on the progress in hydrodynamic modeling component. The hydrodynamic model has been set up using the publicly available forcing data and was calibrated against field observations or NOAA predictions for tidal elevation, current, salinity and temperature. The calibrated model was also used to estimate physical transport timescales such as residence time in the estuary. The preliminary model results demonstrate that the EFDC Hood Canal model is capable of capturing the general circulation patterns in Hood Canal, including weak tidal current and strong vertical stratification. The long residence time (i.e., on the order of 100 days for the entire estuary) also indicates that restricted water circulation could contribute to low DO in the estuary and also makes the system especially susceptible to anthropogenic disturbance, such as excess nutrient input.« less

Real-time assessments of water quality: expanding nowcasting throughout the Great Lakes

USGS Publications Warehouse

,

2013-01-01

Nowcasts are systems that inform the public of current bacterial water-quality conditions at beaches on the basis of predictive models. During 2010–12, the U.S. Geological Survey (USGS) worked with 23 local and State agencies to improve existing operational beach nowcast systems at 4 beaches and expand the use of predictive models in nowcasts at an additional 45 beaches throughout the Great Lakes. The predictive models were specific to each beach, and the best model for each beach was based on a unique combination of environmental and water-quality explanatory variables. The variables used most often in models to predict Escherichia coli (E. coli) concentrations or the probability of exceeding a State recreational water-quality standard included turbidity, day of the year, wave height, wind direction and speed, antecedent rainfall for various time periods, and change in lake level over 24 hours. During validation of 42 beach models during 2012, the models performed better than the current method to assess recreational water quality (previous day's E. coli concentration). The USGS will continue to work with local agencies to improve nowcast predictions, enable technology transfer of predictive model development procedures, and implement more operational systems during 2013 and beyond.

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

NASA Astrophysics Data System (ADS)

Miralha, L.; Kim, D.

2017-12-01

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

Water-quality modeling of Klamath Straits Drain recirculation, a Klamath River wetland, and 2011 conditions for the Link River to Keno Dam reach of the Klamath River, Oregon

USGS Publications Warehouse

Sullivan, Annett B.; Sogutlugil, I. Ertugrul; Deas, Michael L.; Rounds, Stewart A.

2014-01-01

The upper Klamath River and adjacent Lost River are interconnected basins in south-central Oregon and northern California. Both basins have impaired water quality with Total Maximum Daily Loads (TMDLs) in progress or approved. In cooperation with the Bureau of Reclamation, the U.S. Geological Survey (USGS) and Watercourse Engineering, Inc., have conducted modeling and research to inform management of these basins for multiple purposes, including agriculture, endangered species protection, wildlife refuges, and adjacent and downstream water users. A water-quality and hydrodynamic model (CE-QUAL-W2) of the Link River to Keno Dam reach of the Klamath River for 2006–09 is one of the tools used in this work. The model can simulate stage, flow, water velocity, ice cover, water temperature, specific conductance, suspended sediment, nutrients, organic matter in bed sediment and the water column, three algal groups, three macrophyte groups, dissolved oxygen, and pH. This report documents two model scenarios and a test of the existing model applied to year 2011, which had exceptional water quality. The first scenario examined the water-quality effects of recirculating Klamath Straits Drain flows into the Ady Canal, to conserve water and to decrease flows from the Klamath Straits Drain to the Klamath River. The second scenario explicitly incorporated a 2.73×106 m2 (675 acre) off-channel connected wetland into the CE-QUAL-W2 framework, with the wetland operating from May 1 through October 31. The wetland represented a managed treatment feature to decrease organic matter loads and process nutrients. Finally, the summer of 2011 showed substantially higher dissolved-oxygen concentrations in the Link-Keno reach than in other recent years, so the Link-Keno model (originally developed for 2006–09) was run with 2011 data as a test of model parameters and rates and to develop insights regarding the reasons for the improved water-quality conditions.

HAWQS (Hydrologic and Water Quality System)

EPA Pesticide Factsheets

A water quantity and quality modeling system to evaluate the impacts of management alternatives, pollution control scenarios, and climate change scenarios on the quantity and quality of water at a national scale.

Water Quality Analysis Simulation

EPA Pesticide Factsheets

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.

Water quality analysis in rivers with non-parametric probability distributions and fuzzy inference systems: application to the Cauca River, Colombia.

PubMed

Ocampo-Duque, William; Osorio, Carolina; Piamba, Christian; Schuhmacher, Marta; Domingo, José L

2013-02-01

The integration of water quality monitoring variables is essential in environmental decision making. Nowadays, advanced techniques to manage subjectivity, imprecision, uncertainty, vagueness, and variability are required in such complex evaluation process. We here propose a probabilistic fuzzy hybrid model to assess river water quality. Fuzzy logic reasoning has been used to compute a water quality integrative index. By applying a Monte Carlo technique, based on non-parametric probability distributions, the randomness of model inputs was estimated. Annual histograms of nine water quality variables were built with monitoring data systematically collected in the Colombian Cauca River, and probability density estimations using the kernel smoothing method were applied to fit data. Several years were assessed, and river sectors upstream and downstream the city of Santiago de Cali, a big city with basic wastewater treatment and high industrial activity, were analyzed. The probabilistic fuzzy water quality index was able to explain the reduction in water quality, as the river receives a larger number of agriculture, domestic, and industrial effluents. The results of the hybrid model were compared to traditional water quality indexes. The main advantage of the proposed method is that it considers flexible boundaries between the linguistic qualifiers used to define the water status, being the belongingness of water quality to the diverse output fuzzy sets or classes provided with percentiles and histograms, which allows classify better the real water condition. The results of this study show that fuzzy inference systems integrated to stochastic non-parametric techniques may be used as complementary tools in water quality indexing methodologies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Simulation of in-stream water quality on global scale under changing climate and anthropogenic conditions

NASA Astrophysics Data System (ADS)

Voss, Anja; Bärlund, Ilona; Punzet, Manuel; Williams, Richard; Teichert, Ellen; Malve, Olli; Voß, Frank

2010-05-01

Although catchment scale modelling of water and solute transport and transformations is a widely used technique to study pollution pathways and effects of natural changes, policies and mitigation measures there are only a few examples of global water quality modelling. This work will provide a description of the new continental-scale model of water quality WorldQual and the analysis of model simulations under changed climate and anthropogenic conditions with respect to changes in diffuse and point loading as well as surface water quality. BOD is used as an indicator of the level of organic pollution and its oxygen-depleting potential, and for the overall health of aquatic ecosystems. The first application of this new water quality model is to river systems of Europe. The model itself is being developed as part of the EU-funded SCENES Project which has the principal goal of developing new scenarios of the future of freshwater resources in Europe. The aim of the model is to determine chemical fluxes in different pathways combining analysis of water quantity with water quality. Simple equations, consistent with the availability of data on the continental scale, are used to simulate the response of in-stream BOD concentrations to diffuse and anthropogenic point loadings as well as flow dilution. Point sources are divided into manufacturing, domestic and urban loadings, whereas diffuse loadings come from scattered settlements, agricultural input (for instance livestock farming), and also from natural background sources. The model is tested against measured longitudinal gradients and time series data at specific river locations with different loading characteristics like the Thames that is driven by domestic loading and Ebro with relative high share of diffuse loading. With scenario studies the influence of climate and anthropogenic changes on European water resources shall be investigated with the following questions: 1. What percentage of river systems will have degraded water quality due to different driving forces? 2. How will climate change and changes in wastewater discharges affect water quality? For the analysis these scenario aspects are included: 1. climate with changed runoff (affecting diffuse pollution and loading from sealed areas), river discharge (causing dilution or concentration of point source pollution) and water temperature (affecting BOD degradation). 2. Point sources with changed population (affecting domestic pollution), connectivity to treatment plants (influencing domestic and manufacturing pollution as well as input from sealed areas and scattered settlements).

Prediction of settled water turbidity and optimal coagulant dosage in drinking water treatment plant using a hybrid model of k-means clustering and adaptive neuro-fuzzy inference system

NASA Astrophysics Data System (ADS)

Kim, Chan Moon; Parnichkun, Manukid

2017-11-01

Coagulation is an important process in drinking water treatment to attain acceptable treated water quality. However, the determination of coagulant dosage is still a challenging task for operators, because coagulation is nonlinear and complicated process. Feedback control to achieve the desired treated water quality is difficult due to lengthy process time. In this research, a hybrid of k-means clustering and adaptive neuro-fuzzy inference system ( k-means-ANFIS) is proposed for the settled water turbidity prediction and the optimal coagulant dosage determination using full-scale historical data. To build a well-adaptive model to different process states from influent water, raw water quality data are classified into four clusters according to its properties by a k-means clustering technique. The sub-models are developed individually on the basis of each clustered data set. Results reveal that the sub-models constructed by a hybrid k-means-ANFIS perform better than not only a single ANFIS model, but also seasonal models by artificial neural network (ANN). The finally completed model consisting of sub-models shows more accurate and consistent prediction ability than a single model of ANFIS and a single model of ANN based on all five evaluation indices. Therefore, the hybrid model of k-means-ANFIS can be employed as a robust tool for managing both treated water quality and production costs simultaneously.

Assessment of the Impacts of Climate Change on Stream Discharge and Water Quality in an Arid, Urbanized Watershed

NASA Astrophysics Data System (ADS)

Ranatunga, T.; Tong, S.; Yang, J.

2011-12-01

Hydrologic and water quality models can provide a general framework to conceptualize and investigate the relationships between climate and water resources. Under a hot and dry climate, highly urbanized watersheds are more vulnerable to changes in climate, such as excess heat and drought. In this study, a comprehensive watershed model, Hydrological Simulation Program FORTRAN (HSPF), is used to assess the impacts of future climate change on the stream discharge and water quality in Las Vegas Wash in Nevada, the only surface water body that drains from the Las Vegas Valley (an area with rapid population growth and urbanization) to Lake Mead. In this presentation, the process of model building, calibration and validation, the generation of climate change scenarios, and the assessment of future climate change effects on stream hydrology and quality are demonstrated. The hydrologic and water quality model is developed based on the data from current national databases and existing major land use categories of the watershed. The model is calibrated for stream discharge, nutrients (nitrogen and phosphorus) and sediment yield. The climate change scenarios are derived from the outputs of the Global Climate Models (GCM) and Regional Climate Models (RCM) simulations, and from the recent assessment reports from the Intergovernmental Panel on Climate Change (IPCC). The Climate Assessment Tool from US EPA's BASINS is used to assess the effects of likely future climate scenarios on the water quantity and quality in Las Vegas Wash. Also the presentation discusses the consequences of these hydrologic changes, including the deficit supplies of clean water during peak seasons of water demand, increased eutrophication potentials, wetland deterioration, and impacts on wild life habitats.

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

PubMed

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.

Monitoring and modeling of microbial and biological water quality

USDA-ARS?s Scientific Manuscript database

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...

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

NASA Astrophysics Data System (ADS)

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.

Tracking and forecasting the Nation’s water quality - Priorities and strategies for 2013-2023

USGS Publications Warehouse

Rowe, Gary L.; Gilliom, Robert J.; Woodside, Michael D.

2013-01-01

Water-quality issues facing the Nation are growing in number and complexity, and solutions are becoming more challenging and costly. Key factors that affect the quality of our drinking water supplies and ecosystem health include contaminants of human and natural origin in streams and groundwater; excess nutrients and sediment; alteration of natural streamflow; eutrophication of lakes, reservoirs, and coastal estuaries; and changes in surface and groundwater quality associated with changes in climate, land and water use, and management practices. Tracking and forecasting the Nation's water quality in the face of these and other pressing water-quality issues are important goals for 2013-2023, the third decade of the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program. In consultation with stakeholders and the National Research Council, a new strategic Science Plan has been developed that describes a strategy for building upon and enhancing assessment of the Nation's freshwater quality and aquatic ecosystems. The plan continues strategies that have been central to the NAWQA program's long-term success, but it also makes adjustments to the monitoring and modeling approaches NAWQA will use to address critical data and science information needs identified by stakeholders. This fact sheet describes surface-water and groundwater monitoring and modeling activities that will start in fiscal year 2013. It also provides examples of the types of data and information products planned for the next decade, including (1) restored monitoring for reliable and timely status and trend assessments, (2) maps and models that show the distribution of selected contaminants (such as atrazine, nitrate, and arsenic) in streams and aquifers, and (3) Web-based modeling tools that allow managers to evaluate how water quality may change in response to different scenarios of population growth, climate change, or land-use management.

Stochastic modeling for river pollution of Sungai Perlis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yunus, Nurul Izzaty Mohd.; Rahman, Haliza Abd.; Bahar, Arifah

2015-02-03

River pollution has been recognized as a contributor to a wide range of health problems and disorders in human. It can pose health dangers to humans who come into contact with it, either directly or indirectly. Therefore, it is most important to measure the concentration of Biochemical Oxygen Demand (BOD) as a water quality parameter since the parameter has long been the basic means for determining the degree of water pollution in rivers. In this study, BOD is used as a parameter to estimate the water quality at Sungai Perlis. It has been observed that Sungai Perlis is polluted duemore » to lack of management and improper use of resources. Therefore, it is of importance to model the Sungai Perlis water quality in order to describe and predict the water quality systems. The BOD concentration secondary data set is used which was extracted from the Drainage and Irrigation Department Perlis State website. The first order differential equation from Streeter – Phelps model was utilized as a deterministic model. Then, the model was developed into a stochastic model. Results from this study shows that the stochastic model is more adequate to describe and predict the BOD concentration and the water quality systems in Sungai Perlis by having smaller value of mean squared error (MSE)« less

WASP TRANSPORT MODELING AND WASP ECOLOGICAL MODELING

EPA Science Inventory

A combination of lectures, demonstrations, and hands-on excercises will be used to introduce pollutant transport modeling with the U.S. EPA's general water quality model, WASP (Water Quality Analysis Simulation Program). WASP features include a user-friendly Windows-based interfa...

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

PubMed

Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

2015-09-15

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

Evaluating confidence in the impact of regulatory nutrient reduction and assessing the competing impact of climate change

NASA Astrophysics Data System (ADS)

Irby, I.; Friedrichs, M. A. M.

2017-12-01

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 the Bay's water quality. As a result, in 2010, a Total Maximum Daily Load (TMDL) was established for the Chesapeake Bay that limited nutrient and sediment input in an effort to increase dissolved oxygen. This research utilizes a multiple model approach to evaluate confidence in the estuarine water quality modeling portion of the TMDL. One of the models is then used to assess the potential impact climate change may have on the success of currently mandated nutrient reduction levels in 2050. Results demonstrate that although the models examined differ structurally and in biogeochemical complexity, they project a similar attainment of regulatory water quality standards after nutrient reduction, while also establishing that meeting water quality standards is relatively independent of hydrologic conditions. By developing a Confidence Index, this research identifies the locations and causes of greatest uncertainty in modeled projections of water quality. Although there are specific locations and times where the models disagree, this research lends an increased degree of confidence in the appropriateness of the TMDL levels and in the general impact nutrient reductions will have on Chesapeake Bay water quality under current environmental conditions. However, when examining the potential impacts of climate change, this research shows that the combined impacts of increasing temperature, sea level, and river flow negatively affect dissolved oxygen throughout the Chesapeake Bay and impact progress towards meeting the water quality standards associated with the TMDL with increased temperature as the primary culprit. These results, having been continually shared with the regulatory TMDL modelers, will aid in the decision making for the 2017 TMDL Mid-Point Assessment.

Identification of watershed priority management areas under water quality constraints: A simulation-optimization approach with ideal load reduction

NASA Astrophysics Data System (ADS)

Dong, Feifei; Liu, Yong; Wu, Zhen; Chen, Yihui; Guo, Huaicheng

2018-07-01

Targeting nonpoint source (NPS) pollution hot spots is of vital importance for placement of best management practices (BMPs). Although physically-based watershed models have been widely used to estimate nutrient emissions, connections between nutrient abatement and compliance of water quality standards have been rarely considered in NPS hotspot ranking, which may lead to ineffective decision-making. It's critical to develop a strategy to identify priority management areas (PMAs) based on water quality response to nutrient load mitigation. A water quality constrained PMA identification framework was thereby proposed in this study, based on the simulation-optimization approach with ideal load reduction (ILR-SO). It integrates the physically-based Soil and Water Assessment Tool (SWAT) model and an optimization model under constraints of site-specific water quality standards. To our knowledge, it was the first effort to identify PMAs with simulation-based optimization. The SWAT model was established to simulate temporal and spatial nutrient loading and evaluate effectiveness of pollution mitigation. A metamodel was trained to establish a quantitative relationship between sources and water quality. Ranking of priority areas is based on required nutrient load reduction in each sub-watershed targeting to satisfy water quality standards in waterbodies, which was calculated with genetic algorithm (GA). The proposed approach was used for identification of PMAs on the basis of diffuse total phosphorus (TP) in Lake Dianchi Watershed, one of the three most eutrophic large lakes in China. The modeling results demonstrated that 85% of diffuse TP came from 30% of the watershed area. Compared with the two conventional targeting strategies based on overland nutrient loss and instream nutrient loading, the ILR-SO model identified distinct PMAs and narrowed down the coverage of management areas. This study addressed the urgent need to incorporate water quality response into PMA identification and showed that the ILR-SO approach is effective to guide watershed management for aquatic ecosystem restoration.

DISCRETE VOLUME-ELEMENT METHOD FOR NETWORK WATER- QUALITY MODELS

EPA Science Inventory

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...

Quantification of Water Quality Parameters for the Wabash River Using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Tan, J.; Cherkauer, K. A.; Chaubey, I.

2011-12-01

Increasingly impaired water bodies in the agriculturally dominated Midwestern United States pose a risk to water supplies, aquatic ecology and contribute to the eutrophication of the Gulf of Mexico. Improving regional water quality calls for new techniques for monitoring and managing water quality over large river systems. Optical indicators of water quality enable a timely and cost-effective method for observing and quantifying water quality conditions by remote sensing. Compared to broad spectral sensors such as Landsat, which observe reflectance over limited spectral bands, hyperspectral sensors should have significant advantages in their ability to estimate water quality parameters because they are designed to split the spectral signature into hundreds of very narrow spectral bands increasing their ability to resolve optically sensitive water quality indicators. Two airborne hyperspectral images were acquired over the Wabash River using a ProSpecTIR-VS2 sensor system on May 15th, 2010. These images were analyzed together with concurrent in-stream water quality data collected to assess our ability to extract optically sensitive constituents. Utilizing the correlation between in-stream data and reflectance from the hyperspectral images, models were developed to estimate the concentrations of chlorophyll a, dissolved organic carbon and total suspended solids. Models were developed using the full array of hyperspectral bands, as well as Landsat bands synthesized by averaging hyperspectral bands within the Landsat spectral range. Higher R2 and lower RMSE values were found for the models taking full advantage of the hyperspectral sensor, supporting the conclusion that the hyperspectral sensor was better at predicting the in-stream concentrations of chlorophyll a, dissolved organic carbon and total suspended solids in the Wabash River. Results also suggest that predictive models may not be the same for the Wabash River as for its tributaries.

Fact sheets and slides summarizing Soil and Water Assessment Tool (SWAT) and Integrated Farm Systems Model (IFSM)

USDA-ARS?s Scientific Manuscript database

Water quality models address nonpoint source pollution from agricultural land at a range of scales and complexities and involve a variety of input parameters. It is often difficult for conservationists and stakeholders to understand and reconcile water quality results from different models. However,...

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

USDA-ARS?s Scientific Manuscript database

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...

Remote measurements of water pollution with a lidar polarimeter

NASA Technical Reports Server (NTRS)

Sheives, T. C.; Rouse, J. W., Jr.; Mayo, W. T., Jr.

1974-01-01

This paper examines a dual polarization laser backscatter system as a method for remote measurements of certain water quality parameters. Analytical models for describing the backscatter from turbid water and oil on turbid water are presented and compared with experimental data. Laser backscatter field measurements from natural waterways are presented and compared with simultaneous ground observations of the water quality parameters: turbidity, suspended solids, and transmittance. The results of this study show that the analytical models appear valid and that the sensor investigated is applicable to remote measurements of these water quality parameters and oil spills on water.-

Adapting water treatment design and operations to the impacts of global climate change

NASA Astrophysics Data System (ADS)

Clark, Robert M.; Li, Zhiwei; Buchberger, Steven G.

2011-12-01

It is anticipated that global climate change will adversely impact source water quality in many areas of the United States and will therefore, potentially, impact the design and operation of current and future water treatment systems. The USEPA has initiated an effort called the Water Resources Adaptation Program (WRAP) which is intended to develop tools and techniques that can assess the impact of global climate change on urban drinking water and wastewater infrastructure. A three step approach for assessing climate change impacts on water treatment operation and design is being persude in this effort. The first step is the stochastic characterization of source water quality, the second step is the application of the USEPA Water Treatment Plant model and the third step is the application of cost algorithms to provide a metric that can be used to assess the coat impact of climate change. A model has been validated using data collected from Cincinnati's Richard Miller Water Treatment Plant for the USEPA Information Collection Rule (ICR) database. An analysis of the water treatment processes in response to assumed perturbations in raw water quality identified TOC, pH, and bromide as the three most important parameters affecting performance of the Miller WTP. The Miller Plant was simulated using the EPA WTP model to examine the impact of these parameters on selected regulated water quality parameters. Uncertainty in influent water quality was analyzed to estimate the risk of violating drinking water maximum contaminant levels (MCLs).Water quality changes in the Ohio River were projected for 2050 using Monte Carlo simulation and the WTP model was used to evaluate the effects of water quality changes on design and operation. Results indicate that the existing Miller WTP might not meet Safe Drinking Water Act MCL requirements for certain extreme future conditions. However, it was found that the risk of MCL violations under future conditions could be controlled by enhancing existing WTP design and operation or by process retrofitting and modification.

Watershed modeling and monitoring for assessing nutrient ...

EPA Pesticide Factsheets

Presentation for the American Water Works Association Water Sustainability Conference. The presentation highlights latest results from water quality trading research conducted by ORD using the East Fork Watershed in Southwestern Ohio as a case study. The watershed has a nutrient enrichment problem that is creating harmful algal blooms in a reservoir used for drinking water and recreation. Innovative modeling and monitoring is combined to understand how to best manage this water quality problem and costs associated with this endeavor. The presentation will provide an overview of the water quality trading feasibility research. The research includes the development and evaluation of innovative modeling and monitoring approaches to manage watersheds for nutrient pollution using a whole systems approach.

Putting people into water quality modelling.

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Application of Hyperspectral Remote Sensing Techniques to Evaluate Water Quality in Turbid Coastal Waters of South Carolina.

NASA Astrophysics Data System (ADS)

Ali, K. A.; Ryan, K.

2014-12-01

Coastal and inland waters represent a diverse set of resources that support natural habitat and provide valuable ecosystem services to the human population. Conventional techniques to monitor water quality using in situ sensors and laboratory analysis of water samples can be very time- and cost-intensive. Alternatively, remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic and unique water quality parameters. Existing remote sensing ocean color products, such as the water quality proxy chlorophyll-a, are based on ocean derived bio-optical models that are primarily calibrated in Case 1 type waters. These traditional models fail to work when applied in turbid (Case 2 type), coastal waters due to spectral interference from other associated color producing agents such as colored dissolved organic matter and suspended sediments. In this work, we introduce a novel technique for the predictive modeling of chlorophyll-a using a multivariate-based approach applied to in situ hyperspectral radiometric data collected from the coastal waters of Long Bay, South Carolina. This method uses a partial least-squares regression model to identify prominent wavelengths that are more sensitive to chlorophyll-a relative to other associated color-producing agents. The new model was able to explain 80% of the observed chlorophyll-a variability in Long Bay with RMSE = 2.03 μg/L. This approach capitalizes on the spectral advantage gained from current and future hyperspectral sensors, thus providing a more robust predicting model. This enhanced mode of water quality monitoring in marine environments will provide insight to point-sources and problem areas that may contribute to a decline in water quality. The utility of this tool is in its versatility to a diverse set of coastal waters and its use by coastal and fisheries managers with regard to recreation, regulation, economic and public health purposes.

Analysis of trends in water-quality data for water conservation area 3A, the Everglades, Florida

USGS Publications Warehouse

Mattraw, H.C.; Scheidt, D.J.; Federico, A.C.

1987-01-01

Rainfall and water quality data bases from the South Florida Water Management District were used to evaluate water quality trends at 10 locations near or in Water Conservation Area 3A in The Everglades. The Seasonal Kendall test was applied to specific conductance, orthophosphate-phosphorus, nitrate-nitrogen, total Kjeldahl nitrogen, and total nitrogen regression residuals for the period 1978-82. Residuals of orthophosphate and nitrate quadratic models, based on antecedent 7-day rainfall at inflow gate S-11B, were the only two constituent-structure pairs that showed apparent significant (p < 0.05) increases in constituent concentrations. Elimination of regression models with distinct residual patterns and data outlines resulted in 17 statistically significant station water quality combinations for trend analysis. No water quality trends were observed. The 1979 Memorandum of Agreement outlining the water quality monitoring program between the Everglades National Park and the U.S. Army Corps of Engineers stressed collection four times a year at three stations, and extensive coverage of water quality properties. Trend analysis and other rigorous statistical evaluation programs are better suited to data monitoring programs that include more frequent sampling and that are organized in a water quality data management system. Pronounced areal differences in water quality suggest that a water quality monitoring system for Shark River Slough in Everglades National Park include collection locations near the source of inflow to Water Conservation Area 3A. (Author 's abstract)

A random optimization approach for inherent optic properties of nearshore waters

NASA Astrophysics Data System (ADS)

Zhou, Aijun; Hao, Yongshuai; Xu, Kuo; Zhou, Heng

2016-10-01

Traditional method of water quality sampling is time-consuming and highly cost. It can not meet the needs of social development. Hyperspectral remote sensing technology has well time resolution, spatial coverage and more general segment information on spectrum. It has a good potential in water quality supervision. Via the method of semi-analytical, remote sensing information can be related with the water quality. The inherent optical properties are used to quantify the water quality, and an optical model inside the water is established to analysis the features of water. By stochastic optimization algorithm Threshold Acceptance, a global optimization of the unknown model parameters can be determined to obtain the distribution of chlorophyll, organic solution and suspended particles in water. Via the improvement of the optimization algorithm in the search step, the processing time will be obviously reduced, and it will create more opportunity for the increasing the number of parameter. For the innovation definition of the optimization steps and standard, the whole inversion process become more targeted, thus improving the accuracy of inversion. According to the application result for simulated data given by IOCCG and field date provided by NASA, the approach model get continuous improvement and enhancement. Finally, a low-cost, effective retrieval model of water quality from hyper-spectral remote sensing can be achieved.

Verification and Evaluation of Aquatic Contaminant Simulation Module (CSM)

DTIC Science & Technology

2016-08-01

RECOVERY model (Boyer et al. 1994, Ruiz et al. 2000) and Water- quality Analysis Simulation Program (WASP) model (Wool et al. 2006). This technical note (TN...bacteria, and detritus). Natural waters can contain a mixture of solid particles ranging from gravel (2 mm to 20 mm) or sand (0.07 mm to 2 mm) down to... quality perspective, cohesive sediments are usually of greater importance in water quality modeling. The chemical species in the active sediment

Storm Water Management Model Reference Manual Volume II ...

EPA Pesticide Factsheets

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 generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps. The reference manual for this edition of SWMM is comprised of three volumes. Volume I describes SWMM’s hydrologic models, Volume II its hydraulic models, and Volume III its water quality and low impact development models. This document provides the underlying mathematics for the hydraulic calculations of the Storm Water Management Model (SWMM)

Meeting in Turkey: WASP Transport Modeling and WASP Ecological Modeling

EPA Science Inventory

A combination of lectures, demonstrations, and hands-on excercises will be used to introduce pollutant transport modeling with the U.S. EPA's general water quality model, WASP (Water Quality Analysis Simulation Program). WASP features include a user-friendly Windows-based interfa...

Meeting in Korea: WASP Transport Modeling and WASP Ecological Modeling

EPA Science Inventory

A combination of lectures, demonstrations, and hands-on excercises will be used to introduce pollutant transport modeling with the U.S. EPA's general water quality model, WASP (Water Quality Analysis Simulation Program). WASP features include a user-friendly Windows-based interfa...

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

USGS Publications Warehouse

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.

Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data

USGS Publications Warehouse

Krizanich, Gary; Finn, Michael P.

2009-01-01

Water quality of Table Rock Lake in southwestern Missouri is assessed using Landsat Thematic Mapper satellite data. A pilot study uses multidate satellite image scenes in conjunction with physical measurements of secchi disk transparency collected by the Lakes of Missouri Volunteer Program to construct a regression model used to estimate water clarity. The natural log of secchi disk transparency is the dependent variable in the regression and the independent variables are Thematic Mapper band 1 (blue) reflectance and a ratio of the band 1 and band 3 (red) reflectance. The regression model can be used to reliably predict water clarity anywhere within the lake. A pixel-level lake map of predicted water clarity or computed trophic state can be produced from the model output. Information derived from this model can be used by water-resource managers to assess water quality and evaluate effects of changes in the watershed on water quality.

Receiving water quality assessment: comparison between simplified and detailed integrated urban modelling approaches.

PubMed

Mannina, Giorgio; Viviani, Gaspare

2010-01-01

Urban water quality management often requires use of numerical models allowing the evaluation of the cause-effect relationship between the input(s) (i.e. rainfall, pollutant concentrations on catchment surface and in sewer system) and the resulting water quality response. The conventional approach to the system (i.e. sewer system, wastewater treatment plant and receiving water body), considering each component separately, does not enable optimisation of the whole system. However, recent gains in understanding and modelling make it possible to represent the system as a whole and optimise its overall performance. Indeed, integrated urban drainage modelling is of growing interest for tools to cope with Water Framework Directive requirements. Two different approaches can be employed for modelling the whole urban drainage system: detailed and simplified. Each has its advantages and disadvantages. Specifically, detailed approaches can offer a higher level of reliability in the model results, but can be very time consuming from the computational point of view. Simplified approaches are faster but may lead to greater model uncertainty due to an over-simplification. To gain insight into the above problem, two different modelling approaches have been compared with respect to their uncertainty. The first urban drainage integrated model approach uses the Saint-Venant equations and the 1D advection-dispersion equations, for the quantity and for the quality aspects, respectively. The second model approach consists of the simplified reservoir model. The analysis used a parsimonious bespoke model developed in previous studies. For the uncertainty analysis, the Generalised Likelihood Uncertainty Estimation (GLUE) procedure was used. Model reliability was evaluated on the basis of capacity of globally limiting the uncertainty. Both models have a good capability to fit the experimental data, suggesting that all adopted approaches are equivalent both for quantity and quality. The detailed model approach is more robust and presents less uncertainty in terms of uncertainty bands. On the other hand, the simplified river water quality model approach shows higher uncertainty and may be unsuitable for receiving water body quality assessment.

Identification and Assessment of Potential Water Quality Impact Factors for Drinking-Water Reservoirs

PubMed Central

Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang

2014-01-01

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources. PMID:24919129

Identification and assessment of potential water quality impact factors for drinking-water reservoirs.

PubMed

Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang

2014-06-10

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources.

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

NASA Astrophysics Data System (ADS)

Kim, C.

2016-12-01

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

Real-time control of combined surface water quantity and quality: polder flushing.

PubMed

Xu, M; van Overloop, P J; van de Giesen, N C; Stelling, G S

2010-01-01

In open water systems, keeping both water depths and water quality at specified values is critical for maintaining a 'healthy' water system. Many systems still require manual operation, at least for water quality management. When applying real-time control, both quantity and quality standards need to be met. In this paper, an artificial polder flushing case is studied. Model Predictive Control (MPC) is developed to control the system. In addition to MPC, a 'forward estimation' procedure is used to acquire water quality predictions for the simplified model used in MPC optimization. In order to illustrate the advantages of MPC, classical control [Proportional-Integral control (PI)] has been developed for comparison in the test case. The results show that both algorithms are able to control the polder flushing process, but MPC is more efficient in functionality and control flexibility.

A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices.

PubMed

Vadiati, M; Asghari-Moghaddam, A; Nakhaei, M; Adamowski, J; Akbarzadeh, A H

2016-12-15

Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain and complex hydrogeological systems. In the present study, a Mamdani fuzzy-logic-based decision-making approach was developed to assess groundwater quality based on relevant indices. In an effort to develop a set of new hybrid fuzzy indices for groundwater quality assessment, a Mamdani fuzzy inference model was developed with widely-accepted groundwater quality indices: the Groundwater Quality Index (GQI), the Water Quality Index (WQI), and the Ground Water Quality Index (GWQI). In an effort to present generalized hybrid fuzzy indices a significant effort was made to employ well-known groundwater quality index acceptability ranges as fuzzy model output ranges rather than employing expert knowledge in the fuzzification of output parameters. The proposed approach was evaluated for its ability to assess the drinking water quality of 49 samples collected seasonally from groundwater resources in Iran's Sarab Plain during 2013-2014. Input membership functions were defined as "desirable", "acceptable" and "unacceptable" based on expert knowledge and the standard and permissible limits prescribed by the World Health Organization. Output data were categorized into multiple categories based on the GQI (5 categories), WQI (5 categories), and GWQI (3 categories). Given the potential of fuzzy models to minimize uncertainties, hybrid fuzzy-based indices produce significantly more accurate assessments of groundwater quality than traditional indices. The developed models' accuracy was assessed and a comparison of the performance indices demonstrated the Fuzzy Groundwater Quality Index model to be more accurate than both the Fuzzy Water Quality Index and Fuzzy Ground Water Quality Index models. This suggests that the new hybrid fuzzy indices developed in this research are reliable and flexible when used in groundwater quality assessment for drinking purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Impact assessments of water allocation on water environment of river network: Method and application

NASA Astrophysics Data System (ADS)

Wang, Qinggai; Wang, Yaping; Lu, Xuchuan; Jia, Peng; Zhang, Beibei; Li, Chen; Li, Sa; Li, Shibei

2018-02-01

Two types of water allocation scenarios were proposed for reasonably utilizing water resources and improving water quality in a two-river network in Tongzhou District. Water circulation and quality were selected as two important indexes to evaluate the two scenario. Meanwhile, one-dimensional water amount and quality model was set up on the basis of the MIKE11 model to compare the two scenarios in terms of improving water environment. The results showed that both scenarios changed the hydrodynamic conditions, and consequently the river flow reached 0.05 m/s or higher in the central part of river stream. In addition, we also found that the two plans have similar effects on water quality, with first scenario producing larger area of water class III and IV than the second scenario.

Assessing potential effects of highway runoff on receiving-water quality at selected sites in Oregon with the Stochastic Empirical Loading and Dilution Model (SELDM)

USGS Publications Warehouse

Risley, John C.; Granato, Gregory E.

2014-01-01

6. An analysis of the use of grab sampling and nonstochastic upstream modeling methods was done to evaluate the potential effects on modeling outcomes. Additional analyses using surrogate water-quality datasets for the upstream basin and highway catchment were provided for six Oregon study sites to illustrate the risk-based information that SELDM will produce. These analyses show that the potential effects of highway runoff on receiving-water quality downstream of the outfall depends on the ratio of drainage areas (dilution), the quality of the receiving water upstream of the highway, and the concentration of the criteria of the constituent of interest. These analyses also show that the probability of exceeding a water-quality criterion may depend on the input statistics used, thus careful selection of representative values is important.

The contingent behavior of charter fishing participants on the Chesapeake Bay: Welfare estimates associated with water quality improvements

USGS Publications Warehouse

Poor, P.J.; Breece, M.

2006-01-01

Water quality in the Chesapeake Bay has deteriorated over recent years. Historically, fishing has contributed to the region's local economy in terms of commercial and recreational harvests. A contingent behavior model is used to estimate welfare measures for charter fishing participants with regard to a hypothetical improvement in water quality. Using a truncated Poisson count model corrected for endogenous stratification, it was found that charter fishers not only contribute to the local market economy, but they also place positive non-market value on preserving the Bay's water quality. Using two estimates for travels costs it is estimated that the individual consumer surplus is $200 and $117 per trip, and the average individual consumer surplus values for an improvement in water quality is $75 and $44 for two models estimated. ?? 2006 University of Newcastle upon Tyne.

DEVELOPMENT OF GUIDELINES FOR CALIBRATING, VALIDATING, AND EVALUATING HYDROLOGIC AND WATER QUALITY MODELS: ASABE ENGINEERING PRACTICE 621

USDA-ARS?s Scientific Manuscript database

Information to support application of hydrologic and water quality (H/WQ) models abounds, yet modelers commonly use arbitrary, ad hoc methods to conduct, document, and report model calibration, validation, and evaluation. Consistent methods are needed to improve model calibration, validation, and e...

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

EPA Science Inventory

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

Klang River water quality modelling using music

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2017-07-01

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

An integrated fuzzy-based advanced eutrophication simulation model to develop the best management scenarios for a river basin.

PubMed

Srinivas, Rallapalli; Singh, Ajit Pratap

2018-03-01

Assessment of water quality status of a river with respect to its discharge has become prerequisite to sustainable river basin management. The present paper develops an integrated model for simulating and evaluating strategies for water quality management in a river basin management by controlling point source pollutant loadings and operations of multi-purpose projects. Water Quality Analysis and Simulation Program (WASP version 8.0) has been used for modeling the transport of pollutant loadings and their impact on water quality in the river. The study presents a novel approach of integrating fuzzy set theory with an "advanced eutrophication" model to simulate the transmission and distribution of several interrelated water quality variables and their bio-physiochemical processes in an effective manner in the Ganges river basin, India. After calibration, simulated values are compared with the observed values to validate the model's robustness. Fuzzy technique of order preference by similarity to ideal solution (F-TOPSIS) has been used to incorporate the uncertainty associated with the water quality simulation results. The model also simulates five different scenarios for pollution reduction, to determine the maximum pollutant loadings during monsoon and dry periods. The final results clearly indicate how modeled reduction in the rate of wastewater discharge has reduced impacts of pollutants in the downstream. Scenarios suggesting a river discharge rate of 1500 m 3 /s during the lean period, in addition to 25 and 50% reduction in the load rate, are found to be the most effective option to restore quality of river Ganges. Thus, the model serves as an important hydrologic tool to the policy makers by suggesting appropriate remediation action plans.

Season-ahead water quality forecasts for the Schuylkill River, Pennsylvania

NASA Astrophysics Data System (ADS)

Block, P. J.; Leung, K.

2013-12-01

Anticipating and preparing for elevated water quality parameter levels in critical water sources, using weather forecasts, is not uncommon. In this study, we explore the feasibility of extending this prediction scale to a season-ahead for the Schuylkill River in Philadelphia, utilizing both statistical and dynamical prediction models, to characterize the season. This advance information has relevance for recreational activities, ecosystem health, and water treatment, as the Schuylkill provides 40% of Philadelphia's water supply. The statistical model associates large-scale climate drivers with streamflow and water quality parameter levels; numerous variables from NOAA's CFSv2 model are evaluated for the dynamical approach. A multi-model combination is also assessed. Results indicate moderately skillful prediction of average summertime total coliform and wintertime turbidity, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic Ocean. Models predicting the number of elevated turbidity events across the wintertime season are also explored.

Dissolved oxygen, stream temperature, and fish habitat response to environmental water purchases.

PubMed

Null, Sarah E; Mouzon, Nathaniel R; Elmore, Logan R

2017-07-15

Environmental water purchases are increasingly used for ecological protection. In Nevada's Walker Basin (western USA), environmental water purchases augment streamflow in the Walker River and increase lake elevation of terminal Walker Lake. However, water quality impairments like elevated stream temperatures and low dissolved oxygen concentrations also limit ecosystems and species, including federally-threatened Lahontan cutthroat trout. In this paper, we prioritize water volumes and locations that most enhance water quality for riverine habitat from potential environmental water rights purchases. We monitored and modeled streamflows, stream temperatures, and dissolved oxygen concentrations using River Modeling System, an hourly, physically-based hydrodynamic and water quality model. Modeled environmental water purchases ranged from average daily increases of 0.11-1.41 cubic meters per second (m 3 /s) during 2014 and 2015, two critically dry years. Results suggest that water purchases consistently cooled maximum daily stream temperatures and warmed nightly minimum temperatures. This prevented extremely low dissolved oxygen concentrations below 5.0 mg/L, but increased the duration of moderate conditions between 5.5 and 6.0 mg/L. Small water purchases less than approximately 0.71 m 3 /s per day had little benefit for Walker River habitat. Dissolved oxygen concentrations were affected by upstream environmental conditions, where suitable upstream water quality improved downstream conditions and vice versa. Overall, this study showed that critically dry water years degrade environmental water quality and habitat, but environmental water purchases of at least 0.71 m 3 /s were promising for river restoration. Published by Elsevier Ltd.

Water quality management using statistical analysis and time-series prediction model

NASA Astrophysics Data System (ADS)

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2014-12-01

This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

Identification of Important Parameter from Leachate Solid Waste Landfill on Water Quality, Case Study of Pesanggrahan River

NASA Astrophysics Data System (ADS)

Yanidar, R.; Hartono, D. M.; Moersidik, S. S.

2018-03-01

Cipayung Landfill takes waste generation from Depok City approximately ± 750 tons/day of solid waste. The south and west boundaries of the landfill is Pesanggarahan River which 200m faraway. The objectives of this study are to indicate an important parameter which greatly affects the water quality of Pesanggrahan River and purpose the dynamic model for improving our understanding of the dynamic behavior that captures the interactions and feedbacks important parameter in river in order to identify and assess the effects of the treated leachate from final solid waste disposal activity as it responds to changes over time in the river. The high concentrations of BOD and COD are not the only cause significantly affect the quality of the pesanggrahan water, it also because the river has been contaminated in the upstream area. It need the water quality model to support the effectiveness calculation of activities for preventing a selected the pollutant sources the model should be developed for simulating and predicting the trend of water quality performance in Pesanggrahan River which can potentially be used by policy makers in strategic management to sustain river water quality as raw drinking water.

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

PubMed Central

2012-01-01

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. PMID:23369363

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

NASA Astrophysics Data System (ADS)

Gidey, Amanuel

2018-06-01

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

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

USGS Publications Warehouse

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.

Forecasting models for flow and total dissolved solids in Karoun river-Iran

NASA Astrophysics Data System (ADS)

Salmani, Mohammad Hassan; Salmani Jajaei, Efat

2016-04-01

Water quality is one of the most important factors contributing to a healthy life. From the water quality management point of view, TDS (total dissolved solids) is the most important factor and many water developing plans have been implemented in recognition of this factor. However, these plans have not been perfect and very successful in overcoming the poor water quality problem, so there are a good volume of related studies in the literature. We study TDS and the water flow of the Karoun river in southwest Iran. We collected the necessary time series data from the Harmaleh station located in the river. We present two Univariate Seasonal Autoregressive Integrated Movement Average (ARIMA) models to forecast TDS and water flow in this river. Then, we build up a Transfer Function (TF) model to formulate the TDS as a function of water flow volume. A performance comparison between the Seasonal ARIMA and the TF models are presented.

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

PubMed

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

2015-03-15

Contrasting seasonal variations occur in river flow and water quality as a result of short duration, severe intensity storms and typhoons in Taiwan. Sudden changes in river flow caused by impending extreme events may impose serious degradation on river water quality and fateful impacts on ecosystems. Water quality is measured in a monthly/quarterly scale, and therefore an estimation of water quality in a daily scale would be of good help for timely river pollution management. This study proposes a systematic analysis scheme (SAS) to assess the spatio-temporal interrelation of water quality in an urban river and construct water quality estimation models using two static and one dynamic artificial neural networks (ANNs) coupled with the Gamma test (GT) based on water quality, hydrological and economic data. The Dahan River basin in Taiwan is the study area. Ammonia nitrogen (NH3-N) is considered as the representative parameter, a correlative indicator in judging the contamination level over the study. Key factors the most closely related to the representative parameter (NH3-N) are extracted by the Gamma test for modeling NH3-N concentration, and as a result, four hydrological factors (discharge, days w/o discharge, water temperature and rainfall) are identified as model inputs. The modeling results demonstrate that the nonlinear autoregressive with exogenous input (NARX) network furnished with recurrent connections can accurately estimate NH3-N concentration with a very high coefficient of efficiency value (0.926) and a low RMSE value (0.386 mg/l). Besides, the NARX network can suitably catch peak values that mainly occur in dry periods (September-April in the study area), which is particularly important to water pollution treatment. The proposed SAS suggests a promising approach to reliably modeling the spatio-temporal NH3-N concentration based solely on hydrological data, without using water quality sampling data. It is worth noticing that such estimation can be made in a much shorter time interval of interest (span from a monthly scale to a daily scale) because hydrological data are long-term collected in a daily scale. The proposed SAS favorably makes NH3-N concentration estimation much easier (with only hydrological field sampling) and more efficient (in shorter time intervals), which can substantially help river managers interpret and estimate water quality responses to natural and/or manmade pollution in a more effective and timely way for river pollution management. Copyright © 2014 Elsevier Ltd. All rights reserved.

A dynamic water-quality modeling framework for the Neuse River estuary, North Carolina

USGS Publications Warehouse

Bales, Jerad D.; Robbins, Jeanne C.

1999-01-01

As a result of fish kills in the Neuse River estuary in 1995, nutrient reduction strategies were developed for point and nonpoint sources in the basin. However, because of the interannual variability in the natural system and the resulting complex hydrologic-nutrient inter- actions, it is difficult to detect through a short-term observational program the effects of management activities on Neuse River estuary water quality and aquatic health. A properly constructed water-quality model can be used to evaluate some of the potential effects of manage- ment actions on estuarine water quality. Such a model can be used to predict estuarine response to present and proposed nutrient strategies under the same set of meteorological and hydrologic conditions, thus removing the vagaries of weather and streamflow from the analysis. A two-dimensional, laterally averaged hydrodynamic and water-quality modeling framework was developed for the Neuse River estuary by using previously collected data. Development of the modeling framework consisted of (1) computational grid development, (2) assembly of data for model boundary conditions and model testing, (3) selection of initial values of model parameters, and (4) limited model testing. The model domain extends from Streets Ferry to Oriental, N.C., includes seven lateral embayments that have continual exchange with the main- stem of the estuary, three point-source discharges, and three tributary streams. Thirty-five computational segments represent the mainstem of the estuary, and the entire framework contains a total of 60 computa- tional segments. Each computational cell is 0.5 meter thick; segment lengths range from 500 meters to 7,125 meters. Data that were used to develop the modeling framework were collected during March through October 1991 and represent the most comprehensive data set available prior to 1997. Most of the data were collected by the North Carolina Division of Water Quality, the University of North Carolina Institute of Marine Sciences, and the U.S. Geological Survey. Limitations in the modeling framework were clearly identified. These limitations formed the basis for a set of suggestions to refine the Neuse River estuary water-quality model.

The use of GIS and multi-criteria evaluation (MCE) to identify agricultural land management practices which cause surface water pollution in drinking water supply catchments.

PubMed

Grayson, Richard; Kay, Paul; Foulger, Miles

2008-01-01

Diffuse pollution poses a threat to water quality and results in the need for treatment for potable water supplies which can prove costly. Within the Yorkshire region, UK, nitrates, pesticides and water colour present particular treatment problems. Catchment management techniques offer an alternative to 'end of pipe' solutions and allow resources to be targeted to the most polluting areas. This project has attempted to identify such areas using GIS based modelling approaches in catchments where water quality data were available. As no model exists to predict water colour a model was created using an MCE method which is capable of predicting colour concentrations at the catchment scale. CatchIS was used to predict pesticide and nitrate N concentrations and was found to be generally capable of reliably predicting nitrate N loads at the catchment scale. The pesticides results did not match the historic data possibly due to problems with the historic pesticide data and temporal and spatially variability in pesticide usage. The use of these models can be extended to predict water quality problems in catchments where water quality data are unavailable and highlight areas of concern. IWA Publishing 2008.

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

NASA Astrophysics Data System (ADS)

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.

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

DOE PAGES

Shaw, Amelia R.; Sawyer, Heather Smith; LeBoeuf, Eugene J.; ...

2017-10-24

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-W2more » 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. Here, 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.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shaw, Amelia R.; Sawyer, Heather Smith; LeBoeuf, Eugene J.

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-W2more » 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. Here, 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.« less

Relationship between Hydrodynamic Conditions and Water Quality in Landscape Water Body

NASA Astrophysics Data System (ADS)

Kang, Mengxin; Tian, Yimei; Zhang, Haiya; Wang, Dehong

2018-01-01

The urban landscape water usually lacks necessary water cycle and water speed is closed to zero, which easily lead to eutrophication in water system and deterioration of water quality. Therefore, understanding the impact of water circulation on the water quality is of great significance. With that significance, this research has been done to investigate the relationship between hydrodynamic conditions and water quality of urban landscape water based on adopted water quality indexes such as chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP) and nitrogen-ammonia (NH3-N). Moreover, MIKE 21 model is used to simulate the hydrodynamics and water quality under different cases in an urban landscape lake. The results of simulation show that water circulation system could effectively improve current speeds, reduce the proportion of stagnation area, and solve the problem of water quality deterioration caused by reclaimed water in the lake.

A simulation-based approach for estimating premining water quality: Red Mountain Creek, Colorado

USGS Publications Warehouse

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

2007-01-01

Regulatory agencies are often charged with the task of setting site-specific numeric water quality standards for impaired streams. This task is particularly difficult for streams draining highly mineralized watersheds with past mining activity. Baseline water quality data obtained prior to mining are often non-existent and application of generic water quality standards developed for unmineralized watersheds is suspect given the geology of most watersheds affected by mining. Various approaches have been used to estimate premining conditions, but none of the existing approaches rigorously consider the physical and geochemical processes that ultimately determine instream water quality. An approach based on simulation modeling is therefore proposed herein. The approach utilizes synoptic data that provide spatially-detailed profiles of concentration, streamflow, and constituent load along the study reach. This field data set is used to calibrate a reactive stream transport model that considers the suite of physical and geochemical processes that affect constituent concentrations during instream transport. A key input to the model is the quality and quantity of waters entering the study reach. This input is based on chemical analyses available from synoptic sampling and observed increases in streamflow along the study reach. Given the calibrated model, additional simulations are conducted to estimate premining conditions. In these simulations, the chemistry of mining-affected sources is replaced with the chemistry of waters that are thought to be unaffected by mining (proximal, premining analogues). The resultant simulations provide estimates of premining water quality that reflect both the reduced loads that were present prior to mining and the processes that affect these loads as they are transported downstream. This simulation-based approach is demonstrated using data from Red Mountain Creek, Colorado, a small stream draining a heavily-mined watershed. Model application to the premining problem for Red Mountain Creek is based on limited field reconnaissance and chemical analyses; additional field work and analyses may be needed to develop definitive, quantitative estimates of premining water quality.

ERD WATERSHED AND WATER QUALITY MODEL DEVELOPMENT AND TECHNICAL SUPPORT PROGRAM

EPA Science Inventory

The ERD has a long history in providing model research and development and technical support to Regions, States and the Office of Water for watersheds/water quality ecosystem research. The ERD efforts are described in major subtasks comprising the Program. Briefly, these are:

The Assessment of Instruments for Detecting Surface Water Spills Associated with Oil and Gas Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, Aubrey E.; Hopkinson, Leslie; Soeder, Daniel

Surface water and groundwater risks associated with unconventional oil and gas development result from potential spills of the large volumes of chemicals stored on-site during drilling and hydraulic fracturing operations, and the return to the surface of significant quantities of saline water produced during oil or gas well production. To better identify and mitigate risks, watershed models and tools are needed to evaluate the dispersion of pollutants in possible spill scenarios. This information may be used to determine the placement of in-stream water-quality monitoring instruments and to develop early-warning systems and emergency plans. A chemical dispersion model has been usedmore » to estimate the contaminant signal for in-stream measurements. Spills associated with oil and gas operations were identified within the Susquehanna River Basin Commission’s Remote Water Quality Monitoring Network. The volume of some contaminants was found to be sufficient to affect the water quality of certain drainage areas. The most commonly spilled compounds and expected peak concentrations at monitoring stations were used in laboratory experiments to determine if a signal could be detected and positively identified using standard water-quality monitoring equipment. The results were compared to historical data and baseline observations of water quality parameters, and showed that the chemicals tested do commonly affect water quality parameters. This work is an effort to demonstrate that hydrologic and water quality models may be applied to improve the placement of in-stream water quality monitoring devices. This information may increase the capability of early-warning systems to alert community health and environmental agencies of surface water spills associated with unconventional oil and gas operations.« less

Linking land cover and water quality in New York City's water supply watersheds.

PubMed

Mehaffey, M H; Nash, M S; Wade, T G; Ebert, D W; Jones, K B; Rager, A

2005-08-01

The Catskill/Delaware reservoirs supply 90% of New York City's drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.

Regional-scale comparison of the effects of lakes and reservoirs versus streams on water quality

NASA Astrophysics Data System (ADS)

Schmadel, N. M.; Harvey, J. W.; Alexander, R. B.; Schwarz, G. E.; Moore, R. B.; Gomez-Velez, J. D.; Scott, D.; Boyer, E. W.

2017-12-01

Recent physically-based modeling at regional scales has revealed that the potential for biogeochemical transformations of nitrogen—such as denitrification—along a fluvial network may be dominated by hyporheic exchange. However, fluvial networks are comprised of a mosaic of water body types from headwaters to coasts, each potentially playing a different role in water quality. For example, depending on conditions, streams or ponded waters (lakes, reservoirs) may disproportionately act as biogeochemical hotspots. Because downstream water quality reflects an accumulation or blending of processes, it is not clear how ponded waters that vary in number and location across a network influence downstream water quality. Here, we quantified the effects of ponded waters along fluvial networks on the fate of nitrogen in the Northeastern and Mid-Atlantic regions of the United States. We used a spatially referenced model calibrated to land use and water quality data and considered both the number and location of ponded waters across the regions. We experimentally modeled the replacement of nearly 30,000 ponded waters with streams using corresponding estimates of hydraulic geometry and nitrogen removal, thereby providing a direct comparison of the role of ponded waters versus the role of streams with regard to nitrogen removal. We found that pond size, density (total pond area to drainage area), and position within a network were all important factors. These findings complement field measurements and reach-scale modeling by upscaling to reveal cumulative effects. This regional-scale modeling of ponded waters is useful toward developing better strategies for prioritizing creation of new reservoirs or removal of dams, or informing stream restoration at ecologically-relevant scales. This research is a product of the John Wesley Powell Center River Corridor Working Group. powellcenter.usgs.gov/view-project

Modeling hydrodynamics, temperature and water quality in Henry Hagg Lake, Oregon, 2000-2003

USGS Publications Warehouse

Sullivan, Annette B.; Rounds, Stewart A.

2004-01-01

The two-dimensional model CE-QUAL-W2 was used to simulate hydrodynamics, temperature, and water quality in Henry Hagg Lake, Oregon, for the years 2000 through 2003. Input data included lake bathymetry, meteorologic conditions, tributary inflows, tributary temperature and water quality, and lake outflows. Calibrated constituents included lake hydrodynamics, water temperature, orthophosphate, total phosphorus, ammonia, algae, chlorophyll a, zooplankton, and dissolved oxygen. Other simulated constituents included nitrate, dissolved and particulate organic matter, dissolved solids, and suspended sediment. Two algal groups (blue-green algae, and all other algae) were included in the model to simulate the lakes algal communities. Measured lake stage data were used to calibrate the lakes water balance; calibration of water temperature and water quality relied upon vertical profile data taken in the deepest part of the lake near the dam. The model initially was calibrated with data from 200001 and tested with data from 200203. Sensitivity tests were performed to examine the response of the model to specific parameters and coefficients, including the light-extinction coefficient, wind speed, tributary inflows of phosphorus, nitrogen and organic matter, sediment oxygen demand, algal growth rates, and zooplankton feeding preference factors.

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

PubMed

Heddam, Salim; Kisi, Ozgur

2017-07-01

In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme learning machine (OS-ELM), and optimally pruned extreme learning machine (OP-ELM), are newly applied for predicting dissolved oxygen concentration with and without water quality variables as predictors. Firstly, using data from eight United States Geological Survey (USGS) stations located in different rivers basins, USA, the S-ELM, R-ELM, OS-ELM, and OP-ELM were compared against the measured dissolved oxygen (DO) using four water quality variables, water temperature, specific conductance, turbidity, and pH, as predictors. For each station, we used data measured at an hourly time step for a period of 4 years. The dataset was divided into a training set (70%) and a validation set (30%). We selected several combinations of the water quality variables as inputs for each ELM model and six different scenarios were compared. Secondly, an attempt was made to predict DO concentration without water quality variables. To achieve this goal, we used the year numbers, 2008, 2009, etc., month numbers from (1) to (12), day numbers from (1) to (31) and hour numbers from (00:00) to (24:00) as predictors. Thirdly, the best ELM models were trained using validation dataset and tested with the training dataset. The performances of the four ELM models were evaluated using four statistical indices: the coefficient of correlation (R), the Nash-Sutcliffe efficiency (NSE), the root mean squared error (RMSE), and the mean absolute error (MAE). Results obtained from the eight stations indicated that: (i) the best results were obtained by the S-ELM, R-ELM, OS-ELM, and OP-ELM models having four water quality variables as predictors; (ii) out of eight stations, the OP-ELM performed better than the other three ELM models at seven stations while the R-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.

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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 regions, and across sectors demand for an integrated approach to assess main causes of water quality degradation.

Geostatistical Prediction of Microbial Water Quality Throughout a Stream Network Using Meteorology, Land Cover, and Spatiotemporal Autocorrelation.

PubMed

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

2018-06-25

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

Modeling the Effects of Conservation Tillage on Water Quality at the Field Scale

USDA-ARS?s Scientific Manuscript database

The development and application of predictive tools to quantitatively assess the effects of tillage and related management activities should be carefully tested against high quality field data. This study reports on: 1) the calibration and validation of the Root Zone Water Quality Model (RZWQM) to a...

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

USDA-ARS?s Scientific Manuscript database

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...

BASINS Tutorials and Training

EPA Pesticide Factsheets

A series of lectures and exercises on how to use BASINS for water quality modeling and watershed assessment. The lectures follow sequentially. Companion exercises are provided for users to practice different BASINS water quality modeling techniques.

Modeling discharge, temperature, and water quality in the Tualatin River, Oregon

USGS Publications Warehouse

Rounds, Stewart A.; Wood, Tamara M.; Lynch, Dennis D.

1999-01-01

The discharge, water temperature, and water quality of the Tualatin River in northwestern Oregon was simulated with CE-QUAL-W2, a two-dimensional, laterally averaged model developed by the U.S. Army Corps of Engineers. The model was calibrated for May through October periods of 1991, 1992, and 1993. Nine hypothetical scenarios were tested with the model to provide insight for river managers and regulators.

Bayesian Framework for Water Quality Model Uncertainty Estimation and Risk Management

EPA Science Inventory

A formal Bayesian methodology is presented for integrated model calibration and risk-based water quality management using Bayesian Monte Carlo simulation and maximum likelihood estimation (BMCML). The primary focus is on lucid integration of model calibration with risk-based wat...

Great Lakes Water Quality Agreement (GLWQA)

EPA Pesticide Factsheets

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.

Assessment of Gas Potential in the Niobrara Formation, Rosebud Reservation, South Dakota

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, Aubrey E.; Hopkinson, Leslie; Soeder, Daniel

2016-01-23

Surface water and groundwater risks associated with unconventional oil and gas development result from potential spills of the large volumes of chemicals stored on-site during drilling and hydraulic fracturing operations, and the return to the surface of significant quantities of saline water produced during oil or gas well production. To better identify and mitigate risks, watershed models and tools are needed to evaluate the dispersion of pollutants in possible spill scenarios. This information may be used to determine the placement of in-stream water-quality monitoring instruments and to develop early-warning systems and emergency plans. A chemical dispersion model has been usedmore » to estimate the contaminant signal for in-stream measurements. Spills associated with oil and gas operations were identified within the Susquehanna River Basin Commission’s Remote Water Quality Monitoring Network. The volume of some contaminants was found to be sufficient to affect the water quality of certain drainage areas. The most commonly spilled compounds and expected peak concentrations at monitoring stations were used in laboratory experiments to determine if a signal could be detected and positively identified using standard water-quality monitoring equipment. The results were compared to historical data and baseline observations of water quality parameters, and showed that the chemicals tested do commonly affect water quality parameters. This work is an effort to demonstrate that hydrologic and water quality models may be applied to improve the placement of in-stream water quality monitoring devices. This information may increase the capability of early-warning systems to alert community health and environmental agencies of surface water spills associated with unconventional oil and gas operations.« less

Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

PubMed

Pratt, Bethany; Chang, Heejun

2012-03-30

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants. Copyright © 2012 Elsevier B.V. All rights reserved.

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

USGS Publications Warehouse

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 because of limitations in sensor technology and fiscal constraints. Regression models for 28 water-quality constituents were developed and documented. The water-quality information in this report is important to Johnson County Wastewater because it allows the concentrations of many potential pollutants of interest, including nutrients and sediment, to be estimated in real time and characterized during conditions and time scales that would not be possible otherwise.

A Flexible Modeling Framework For Hydraulic and Water Quality Performance Assessment of Stormwater Green Infrastructure

EPA Science Inventory

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...

UNCERTAINTY ANALYSIS IN WATER QUALITY MODELING USING QUAL2E

EPA Science Inventory

A strategy for incorporating uncertainty analysis techniques (sensitivity analysis, first order error analysis, and Monte Carlo simulation) into the mathematical water quality model QUAL2E is described. The model, named QUAL2E-UNCAS, automatically selects the input variables or p...

Predicting effects of environmental change on river inflows to ...

EPA Pesticide Factsheets

Estuarine river watersheds provide valued ecosystem services to their surrounding communities including drinking water, fish habitat, and regulation of estuarine water quality. However, the provisioning of these services can be affected by changes in the quantity and quality of river water, such as those caused by altered landscapes or shifting temperatures or precipitation. We used the ecohydrology model, VELMA, in the Trask River watershed to simulate the effects of environmental change scenarios on estuarine river inputs to Tillamook Bay (OR) estuary. The Trask River watershed is 453 km2 and contains extensive agriculture, silviculture, urban, and wetland areas. VELMA was parameterized using existing spatial datasets of elevation, soil type, land use, air temperature, precipitation, river flow, and water quality. Simulated land use change scenarios included alterations in the distribution of the nitrogen-fixing tree species Alnus rubra, and comparisons of varying timber harvest plans. Scenarios involving spatial and temporal shifts in air temperature and precipitation trends were also simulated. Our research demonstrates the utility of ecohydrology models such as VELMA to aid in watershed management decision-making. Model outputs of river water flow, temperature, and nutrient concentrations can be used to predict effects on drinking water quality, salmonid populations, and estuarine water quality. This modeling effort is part of a larger framework of

Trophic state and toxic cyanobacteria density in optimization modeling of multi-reservoir water resource systems.

PubMed

Sulis, Andrea; Buscarinu, Paola; Soru, Oriana; Sechi, Giovanni M

2014-04-22

The definition of a synthetic index for classifying the quality of water bodies is a key aspect in integrated planning and management of water resource systems. In previous works [1,2], a water system optimization modeling approach that requires a single quality index for stored water in reservoirs has been applied to a complex multi-reservoir system. Considering the same modeling field, this paper presents an improved quality index estimated both on the basis of the overall trophic state of the water body and on the basis of the density values of the most potentially toxic Cyanobacteria. The implementation of the index into the optimization model makes it possible to reproduce the conditions limiting water use due to excessive nutrient enrichment in the water body and to the health hazard linked to toxic blooms. The analysis of an extended limnological database (1996-2012) in four reservoirs of the Flumendosa-Campidano system (Sardinia, Italy) provides useful insights into the strengths and limitations of the proposed synthetic index.

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

PubMed

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.

Using land-cover change as dynamic variables in surface-water and water-quality models

USGS Publications Warehouse

Karstensen, Krista A.; Warner, Kelly L.; Kuhn, Anne

2010-01-01

Land-cover data are typically used in hydrologic modeling to establish or describe land surface dynamics. This project is designed to demonstrate the use of land-cover change data in surface-water and water-quality models by incorporating land-cover as a variable condition. The project incorporates three different scenarios that vary hydrologically and geographically: 1) Agriculture in the Plains, 2) Loon habitat in New England, and 3) Forestry in the Ozarks.

SPARROW MODELING - Enhancing Understanding of the Nation's Water Quality

USGS Publications Warehouse

Preston, Stephen D.; Alexander, Richard B.; Woodside, Michael D.; Hamilton, Pixie A.

2009-01-01

The information provided here is intended to assist water-resources managers with interpretation of the U.S. Geological Survey (USGS) SPARROW model and its products. SPARROW models can be used to explain spatial patterns in monitored stream-water quality in relation to human activities and natural processes as defined by detailed geospatial information. Previous SPARROW applications have identified the sources and transport of nutrients in the Mississippi River basin, Chesapeake Bay watershed, and other major drainages of the United States. New SPARROW models with improved accuracy and interpretability are now being developed by the USGS National Water Quality Assessment (NAWQA) Program for six major regions of the conterminous United States. These new SPARROW models are based on updated geospatial data and stream-monitoring records from local, State, and other federal agencies.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Enhancing water quality in hydropower system operations

NASA Astrophysics Data System (ADS)

Hayes, Donald F.; Labadie, John W.; Sanders, Thomas G.; Brown, Jackson K.

1998-03-01

The quality of impounded waters often degrades over time because of thermal stratification, sediment oxygen demands, and accumulation of pollutants. Consequently, reservoir releases impact water quality in tailwaters, channels, and other downstream water bodies. Low dissolved oxygen (DO) concentrations in the Cumberland River below Old Hickory dam result from stratification of upstream reservoirs and seasonally low release rates. Operational changes in upstream hydropower reservoirs may be one method to increase DO levels without substantially impacting existing project purposes. A water quality model of the upper Cumberland basin is integrated into an optimal control algorithm to evaluate water quality improvement opportunities through operational modifications. The integrated water quantity/quality model maximizes hydropower revenues, subject to various flow and headwater operational restrictions for satisfying multiple project purposes, as well as maintenance of water quality targets. Optimal daily reservoir release policies are determined for the summer drawdown period which increase DO concentrations under stratification conditions with minimal impact on hydropower production and other project purposes. Appendixes A-D available with entire article on microfiche. Order by mail from AGU, 2000 Florida Ave., N.W., Washington, DC 20009 or by phone at 800-966-2481; $2.50. Document W97-003. Payment must accompany order.

Use of soft data for multi-criteria calibration and validation of APEX: Impact on model simulations

USDA-ARS?s Scientific Manuscript database

It is widely known that the use of soft data and multiple model performance criteria in model calibration and validation is critical to ensuring the model capture major hydrologic and water quality processes. The Agricultural Policy/Environmental eXtender (APEX) is a hydrologic and water quality mod...

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

USDA-ARS?s Scientific Manuscript database

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

Relevance of Regional Hydro-Climatic Projection Data for Hydrodynamics and Water Quality Modelling of the Baltic Sea

NASA Astrophysics Data System (ADS)

Goldenberg, R.; Vigouroux, G.; Chen, Y.; Bring, A.; Kalantari, Z.; Prieto, C.; Destouni, G.

2017-12-01

The Baltic Sea, located in Northern Europe, is one of the world's largest body of brackish water, enclosed and surrounded by nine different countries. The magnitude of climate change may be particularly large in northern regions, and identifying its impacts on vulnerable inland waters and their runoff and nutrient loading to the Baltic Sea is an important and complex task. Exploration of such hydro-climatic impacts is needed to understand potential future changes in physical, ecological and water quality conditions in the regional coastal and marine waters. In this study, we investigate hydro-climatic changes and impacts on the Baltic Sea by synthesizing multi-model climate projection data from the CORDEX regional downscaling initiative (EURO- and Arctic- CORDEX domains, http://www.cordex.org/). We identify key hydro-climatic variable outputs of these models and assess model performance with regard to their projected temporal and spatial change behavior and impacts on different scales and coastal-marine parts, up to the whole Baltic Sea. Model spreading, robustness and impact implications for the Baltic Sea system are investigated for and through further use in simulations of coastal-marine hydrodynamics and water quality based on these key output variables and their change projections. Climate model robustness in this context is assessed by inter-model spreading analysis and observation data comparisons, while projected change implications are assessed by forcing of linked hydrodynamic and water quality modeling of the Baltic Sea based on relevant hydro-climatic outputs for inland water runoff and waterborne nutrient loading to the Baltic sea, as well as for conditions in the sea itself. This focused synthesis and analysis of hydro-climatically relevant output data of regional climate models facilitates assessment of reliability and uncertainty in projections of driver-impact changes of key importance for Baltic Sea physical, water quality and ecological conditions and their future evolution.

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Python tools for rapid development, calibration, and analysis of generalized groundwater-flow models

NASA Astrophysics Data System (ADS)

Starn, J. J.; Belitz, K.

2014-12-01

National-scale water-quality data sets for the United States have been available for several decades; however, groundwater models to interpret these data are available for only a small percentage of the country. Generalized models may be adequate to explain and project groundwater-quality trends at the national scale by using regional scale models (defined as watersheds at or between the HUC-6 and HUC-8 levels). Coast-to-coast data such as the National Hydrologic Dataset Plus (NHD+) make it possible to extract the basic building blocks for a model anywhere in the country. IPython notebooks have been developed to automate the creation of generalized groundwater-flow models from the NHD+. The notebook format allows rapid testing of methods for model creation, calibration, and analysis. Capabilities within the Python ecosystem greatly speed up the development and testing of algorithms. GeoPandas is used for very efficient geospatial processing. Raster processing includes the Geospatial Data Abstraction Library and image processing tools. Model creation is made possible through Flopy, a versatile input and output writer for several MODFLOW-based flow and transport model codes. Interpolation, integration, and map plotting included in the standard Python tool stack also are used, making the notebook a comprehensive platform within on to build and evaluate general models. Models with alternative boundary conditions, number of layers, and cell spacing can be tested against one another and evaluated by using water-quality data. Novel calibration criteria were developed by comparing modeled heads to land-surface and surface-water elevations. Information, such as predicted age distributions, can be extracted from general models and tested for its ability to explain water-quality trends. Groundwater ages then can be correlated with horizontal and vertical hydrologic position, a relation that can be used for statistical assessment of likely groundwater-quality conditions. Convolution with age distributions can be used to quickly ascertain likely future water-quality conditions. Although these models are admittedly very general and are still being tested, the hope is that they will be useful for answering questions related to water quality at the regional scale.

PROJECT SUMMARY: DEVELOPMENT OF THE VIRTUAL BEACH MODEL, PHASE I: AN EMPIRICAL MODEL

EPA Science Inventory

Mathematical models based on water-quality and other environmental surrogates may help to provide water quality assessment within a few hours and potentially provide one to three day forecasts, providing beach managers and public-health officials a tool for developing beach-speci...

Performance measures and criteria for hydrologic and water quality models

USDA-ARS?s Scientific Manuscript database

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...

Hydrologic and water quality terminology as applied to modeling

USDA-ARS?s Scientific Manuscript database

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...

COMPUTER PROGRAM DOCUMENTATION FOR THE ENHANCED STREAM WATER QUALITY MODEL QUAL2E

EPA Science Inventory

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 growt...

Water Quality Assessment Simulation Program (WASP8): Upgrades to the Advanced Toxicant Module for Simulating Dissolved Chemicals, Nanomaterials, and Solids

EPA Science Inventory

The Water Quality Analysis Simulation Program (WASP) is a dynamic, spatially-resolved, differential mass balance fate and transport modeling framework. WASP is used to develop models to simulate concentrations of environmental contaminants in surface waters and sediments. As a mo...

A statistical model for water quality predictions from a river discharge using coastal observations

NASA Astrophysics Data System (ADS)

Kim, S.; Terrill, E. J.

2007-12-01

Understanding and predicting coastal ocean water quality has benefits for reducing human health risks, protecting the environment, and improving local economies which depend on clean beaches. Continuous observations of coastal physical oceanography increase the understanding of the processes which control the fate and transport of a riverine plume which potentially contains high levels of contaminants from the upstream watershed. A data-driven model of the fate and transport of river plume water from the Tijuana River has been developed using surface current observations provided by a network of HF radar operated as part of a local coastal observatory that has been in place since 2002. The model outputs are compared with water quality sampling of shoreline indicator bacteria, and the skill of an alarm for low water quality is evaluated using the receiver operating characteristic (ROC) curve. In addition, statistical analysis of beach closures in comparison with environmental variables is also discussed.

Water Quality Variable Estimation using Partial Least Squares Regression and Multi-Scale Remote Sensing.

NASA Astrophysics Data System (ADS)

Peterson, K. T.; Wulamu, A.

2017-12-01

Water, essential to all living organisms, is one of the Earth's most precious resources. Remote sensing offers an ideal approach to monitor water quality over traditional in-situ techniques that are highly time and resource consuming. Utilizing a multi-scale approach, incorporating data from handheld spectroscopy, UAS based hyperspectal, and satellite multispectral images were collected in coordination with in-situ water quality samples for the two midwestern watersheds. The remote sensing data was modeled and correlated to the in-situ water quality variables including chlorophyll content (Chl), turbidity, and total dissolved solids (TDS) using Normalized Difference Spectral Indices (NDSI) and Partial Least Squares Regression (PLSR). The results of the study supported the original hypothesis that correlating water quality variables with remotely sensed data benefits greatly from the use of more complex modeling and regression techniques such as PLSR. The final results generated from the PLSR analysis resulted in much higher R2 values for all variables when compared to NDSI. The combination of NDSI and PLSR analysis also identified key wavelengths for identification that aligned with previous study's findings. This research displays the advantages and future for complex modeling and machine learning techniques to improve water quality variable estimation from spectral data.

Application of digital profile modeling techniques to ground-water solute transport at Barstow, California

USGS Publications Warehouse

Robson, Stanley G.

1978-01-01

This study investigated the use of a two-dimensional profile-oriented water-quality model for the simulation of head and water-quality changes through the saturated thickness of an aquifer. The profile model is able to simulate confined or unconfined aquifers with nonhomogeneous anisotropic hydraulic conductivity, nonhomogeneous specific storage and porosity, and nonuniform saturated thickness. An aquifer may be simulated under either steady or nonsteady flow conditions provided that the ground-water flow path along which the longitudinal axis of the model is oriented does not move in the aquifer during the simulation time period. The profile model parameters are more difficult to quantify than are the corresponding parameters for an areal-oriented water-fluality model. However, the sensitivity of the profile model to the parameters may be such that the normal error of parameter estimation will not preclude obtaining acceptable model results. Although the profile model has the advantage of being able to simulate vertical flow and water-quality changes in a single- or multiple-aquifer system, the types of problems to which it can be applied is limited by the requirements that (1) the ground-water flow path remain oriented along the longitudinal axis of the model and (2) any subsequent hydrologic factors to be evaluated using the model must be located along the land-surface trace of the model. Simulation of hypothetical ground-water management practices indicates that the profile model is applicable to problem-oriented studies and can provide quantitative results applicable to a variety of management practices. In particular, simulations of the movement and dissolved-solids concentration of a zone of degraded ground-water quality near Barstow, Calif., indicate that halting subsurface disposal of treated sewage effluent in conjunction with pumping a line of fully penetrating wells would be an effective means of controlling the movement of degraded ground water.

Modeling water quality effects of structural and operational changes to Scoggins Dam and Henry Hagg Lake, Oregon

USGS Publications Warehouse

Sullivan, Annett B.; Rounds, Stewart A.

2006-01-01

To meet water quality targets and the municipal and industrial water needs of a growing population in the Tualatin River Basin in northwestern Oregon, an expansion of Henry Hagg Lake is under consideration. Hagg Lake is the basin's primary storage reservoir and provides water during western Oregon's typically dry summers. Potential modifications include raising the dam height by 6.1 meters (20 feet), 7.6 meters (25 feet), or 12.2 meters (40 feet); installing additional outlets (possibly including a selective withdrawal tower); and adding additional inflows to provide greater reliability of filling the enlarged reservoir. One method of providing additional inflows is to route water from the upper Tualatin River through a tunnel and into Sain Creek, a tributary to the lake. Another option is to pump water from the Tualatin River (downstream of the lake) uphill and into the reservoir during the winter--the 'pump-back' option. A calibrated CE-QUAL-W2 model of Henry Hagg Lake's hydrodynamics, temperature, and water quality was used to examine the effect of these proposed changes on water quality in the lake and downstream. Most model scenarios were run with the calibrated model for 2002, a typical water year; a few scenarios were run for 2001, a drought year. More...

The challenge of documenting water quality benefits of conservation practices: a review of USDA-ARS's conservation effects assessment project watershed studies.

PubMed

Tomer, M D; Locke, M A

2011-01-01

The Conservation Effects Assessment Project was established to quantify water quality benefits of conservation practices supported by the U.S. Department of Agriculture (USDA). In 2004, watershed assessment studies were begun in fourteen agricultural watersheds with varying cropping systems, landscapes, climate, and water quality concerns. This paper reviews USDA Agricultural Research Service 'Benchmark' watershed studies and the challenge of identifying water quality benefits in watersheds. Study goals included modeling and field research to assess practices, and evaluation of practice placement in watersheds. Not all goals were met within five years but important lessons were learned. While practices improved water quality, problems persisted in larger watersheds. This dissociation between practice-focused and watershed-scale assessments occurred because: (1) Conservation practices were not targeted at critical sources/pathways of contaminants; (2) Sediment in streams originated more from channel and bank erosion than from soil erosion; (3) Timing lags, historical legacies, and shifting climate combined to mask effects of practice implementation; and (4) Water quality management strategies addressed single contaminants with little regard for trade-offs among contaminants. These lessons could help improve conservation strategies and set water quality goals with realistic timelines. Continued research on agricultural water quality could better integrate modeling and monitoring capabilities, and address ecosystem services.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

Sensitivity of stream water age to climatic variability and land use change: implications for water quality

NASA Astrophysics Data System (ADS)

Soulsby, Chris; Birkel, Christian; Geris, Josie; Tetzlaff, Doerthe

2016-04-01

Advances in the use of hydrological tracers and their integration into rainfall runoff models is facilitating improved quantification of stream water age distributions. This is of fundamental importance to understanding water quality dynamics over both short- and long-time scales, particularly as water quality parameters are often associated with water sources of markedly different ages. For example, legacy nitrate pollution may reflect deeper waters that have resided in catchments for decades, whilst more dynamics parameters from anthropogenic sources (e.g. P, pathogens etc) are mobilised by very young (<1 day) near-surface water sources. It is increasingly recognised that water age distributions of stream water is non-stationary in both the short (i.e. event dynamics) and longer-term (i.e. in relation to hydroclimatic variability). This provides a crucial context for interpreting water quality time series. Here, we will use longer-term (>5 year), high resolution (daily) isotope time series in modelling studies for different catchments to show how variable stream water age distributions can be a result of hydroclimatic variability and the implications for understanding water quality. We will also use examples from catchments undergoing rapid urbanisation, how the resulting age distributions of stream water change in a predictable way as a result of modified flow paths. The implication for the management of water quality in urban catchments will be discussed.

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

EPA Science Inventory

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...

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

USDA-ARS?s Scientific Manuscript database

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...

McCook Reservoir Water Quality Model. Numerical Model Investigation

DTIC Science & Technology

1991-09-01

REPT TYPE AND DATES COVERED ad September Cana Final report . LEAND SUBTITLE S. FUNDING NUERS Spinfild VA2261 ThcCook Reservoir Water Quality Model...oxygen injected by the aeration system Manufacturers of diffusers supply OTE information specific to gas flow rate and depth. The depths at which most

Monitoring water quality in a hypereutrophic reservoir using Landsat ETM+ and OLI sensors: how transferable are the water quality algorithms?

PubMed

Deutsch, Eliza S; Alameddine, Ibrahim; El-Fadel, Mutasem

2018-02-15

The launch of the Landsat 8 in February 2013 extended the life of the Landsat program to over 40 years, increasing the value of using Landsat to monitor long-term changes in the water quality of small lakes and reservoirs, particularly in poorly monitored freshwater systems. Landsat-based water quality hindcasting often incorporate several Landsat sensors in an effort to increase the temporal range of observations; yet the transferability of water quality algorithms across sensors remains poorly examined. In this study, several empirical algorithms were developed to quantify chlorophyll-a, total suspended matter (TSM), and Secchi disk depth (SDD) from surface reflectance measured by Landsat 7 ETM+ and Landsat 8 OLI sensors. Sensor-specific multiple linear regression models were developed by correlating in situ water quality measurements collected from a semi-arid eutrophic reservoir with band ratios from Landsat ETM+ and OLI sensors, along with ancillary data (water temperature and seasonality) representing ecological patterns in algae growth. Overall, ETM+-based models outperformed (adjusted R 2 chlorophyll-a = 0.70, TSM = 0.81, SDD = 0.81) their OLI counterparts (adjusted R 2 chlorophyll-a = 0.50, TSM = 0.58, SDD = 0.63). Inter-sensor differences were most apparent for algorithms utilizing the Blue spectral band. The inclusion of water temperature and seasonality improved the power of TSM and SDD models.

Quality Assurance Project Plan - Modeling the Impact of Hydraulic Fracturing on Water Resources Based on Water Acquisition Scenarios

EPA Pesticide Factsheets

This planning document describes the quality assurance/quality control activities and technical requirements that will be used during the research study. The goal of this project is to evaluate the potential impacts of large volume water withdrawals.

MEASURING & MODELING VARIATIONS IN DISTRIBUTION WATER QUALITY

EPA Science Inventory

Until recently most interest in drinking water quality has been in the finished water as it leaves the treatment plant. he Safe Drinking Water requires that MCLs be met at the consumers tap. ecause finished water may undergo substantial changes while being transported through the...

Sedimentation and Its Impacts/Effects on River System and Reservoir Water Quality: case Study of Mazowe Catchment, Zimbabwe

NASA Astrophysics Data System (ADS)

Tundu, Colleta; Tumbare, Michael James; Kileshye Onema, Jean-Marie

2018-04-01

Sediment delivery into water sources and bodies results in the reduction of water quantity and quality, increasing costs of water purification whilst reducing the available water for various other uses. The paper gives an analysis of sedimentation in one of Zimbabwe's seven rivers, the Mazowe Catchment, and its impact on water quality. The Revised Universal Soil Loss Equation (RUSLE) model was used to compute soil lost from the catchment as a result of soil erosion. The model was used in conjunction with GIS remotely sensed data and limited ground observations. The estimated annual soil loss in the catchment indicates soil loss ranging from 0 to 65 t ha yr-1. Bathymetric survey at Chimhanda Dam showed that the capacity of the dam had reduced by 39 % as a result of sedimentation and the annual sediment deposition into Chimhanda Dam was estimated to be 330 t with a specific yield of 226 t km-2 yr-1. Relationship between selected water quality parameters, TSS, DO, NO3, pH, TDS, turbidity and sediment yield for selected water sampling points and Chimhanda Dam was analyzed. It was established that there is a strong positive relationship between the sediment yield and the water quality parameters. Sediment yield showed high positive correlation with turbidity (0.63) and TDS (0.64). Water quality data from Chimhanda treatment plant water works revealed that the quality of water is deteriorating as a result of increase in sediment accumulation in the dam. The study concluded that sedimentation can affect the water quality of water sources.

Data collection and development of a hydrodynamic and temperature model to evaluate causeway modifications at the mouth of the Yakima River

NASA Astrophysics Data System (ADS)

Martinez Baquero, G. F.; Furnans, J.; Hudson, C.; Magan, C.

2012-12-01

Management decisions on rivers and associated habitats require sound tools to identify major drivers for spatial and temporal variations of temperature and related water quality variables. 3D hydrodynamic and water quality models are key components to abstract flow dynamics in complex river systems as they allow extrapolating available observations to ungaged locations and alternative scenarios. The data collection and model development are intended to support the Mid-Columbia Fisheries Enhancement Group in conjunction with the Benton Conservation District in efforts to understand how seasonal flow patterns in the Yakima and Columbia rivers interact with the Yakima delta geometry to cause the relatively high water temperatures previously observed west of Bateman Island. These high temperatures are suspected of limiting salmonid success in the area, possibly contributing to adjustments in migration patterns and increased predation. The Environmental Fluid Dynamics Code (EFDC) and Water Quality Analysis Simulation Program (WASP) are used to model flow patterns and enable simulations of temperature distributions and water quality parameters at the confluence. Model development is supported by a bathymetric campaign in 2011 to evaluate delta geometry and to construct the EFDC domain, a sonar river survey in 2012 to measure velocity profiles and to enable model calibration, and a continuous collection of temperature and dissolved oxygen records from Level Scout probes at key locations during last year to drive water quality simulations. The current model is able to reproduce main flow features observed at the confluence and is being prepared to integrate previous and current temperature observations. The final model is expected to evaluate scenarios for the removal or alteration of the Bateman Island Causeway. Alterations to the causeway that permit water passage to the south of Bateman Island are likely to dramatically alter the water flow patterns through the Yakima and Columbia River confluence, which in turn will alter water temperature distributions, sediment transport pathways, and salmonid migration routes.

Modeling water quality, temperature, and flow in Link River, south-central Oregon

USGS Publications Warehouse

Sullivan, Annett B.; Rounds, Stewart A.

2016-09-09

The 2.1-km (1.3-mi) Link River connects Upper Klamath Lake to the Klamath River in south-central Oregon. A CE-QUAL-W2 flow and water-quality model of Link River was developed to provide a connection between an existing model of the upper Klamath River and any existing or future models of Upper Klamath Lake. Water-quality sampling at six locations in Link River was done during 2013–15 to support model development and to provide a better understanding of instream biogeochemical processes. The short reach and high velocities in Link River resulted in fast travel times and limited water-quality transformations, except for dissolved oxygen. Reaeration through the reach, especially at the falls in Link River, was particularly important in moderating dissolved oxygen concentrations that at times entered the reach at Link River Dam with marked supersaturation or subsaturation. This reaeration resulted in concentrations closer to saturation downstream at the mouth of Link River.

Compartment-based hydrodynamics and water quality modeling of a northern Everglades wetland, Florida, USA

USGS Publications Warehouse

Wang, Hongqing; Meselhe, Ehab A.; Waldon, Michael G.; Harwell, Matthew C.; Chen, Chunfang

2012-01-01

The last remaining large remnant of softwater wetlands in the US Florida Everglades lies within the Arthur R. Marshall Loxahatchee National Wildlife Refuge. However, Refuge water quality today is impacted by pumped stormwater inflows to the eutrophic and mineral-enriched 100-km canal, which circumscribes the wetland. Optimal management is a challenge and requires scientifically based predictive tools to assess and forecast the impacts of water management on Refuge water quality. In this research, we developed a compartment-based numerical model of hydrodynamics and water quality for the Refuge. Using the numerical model, we examined the dynamics in stage, water depth, discharge from hydraulic structures along the canal, and exchange flow among canal and marsh compartments. We also investigated the transport of chloride, sulfate and total phosphorus from the canal to the marsh interior driven by hydraulic gradients as well as biological removal of sulfate and total phosphorus. The model was calibrated and validated using long-term stage and water quality data (1995-2007). Statistical analysis indicates that the model is capable of capturing the spatial (from canal to interior marsh) gradients of constituents across the Refuge. Simulations demonstrate that flow from the eutrophic and mineral-enriched canal impacts chloride and sulfate in the interior marsh. In contrast, total phosphorus in the interior marsh shows low sensitivity to intrusion and dispersive transport. We conducted a rainfall-driven scenario test in which the pumped inflow concentrations of chloride, sulfate and total phosphorus were equal to rainfall concentrations (wet deposition). This test shows that pumped inflow is the dominant factor responsible for the substantially increased chloride and sulfate concentrations in the interior marsh. Therefore, the present day Refuge should not be classified as solely a rainfall-driven or ombrotrophic wetland. The model provides an effective screening tool for studying the impacts of various water management alternatives on water quality across the Refuge, and demonstrates the practicality of similarly modeling other wetland systems. As a general rule, modeling provides one component of a multi-faceted effort to provide technical support for ecosystem management decisions.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The derivation of water quality criteria of copper in Biliu River

NASA Astrophysics Data System (ADS)

Zheng, Hongbo; Jia, Xinru

2018-03-01

Excessive copper in water can be detrimental to the health of human and aquatic life. China has promulgated Environmental Quality Standards for Surface Water to control water pollution, but uniform standard values may cause under-protection or over-protection. Therefore, the basic research work on water quality criteria of water source or reservoir is urgently needed. This study deduces the acute and chronic Water Quality Criteria (WQC) of copper in Biliu River by Species Sensitivity Distribution method (SSD). The result shows that BiDoseResp is the most suitable model and the acute and chronic water quality benchmark of copper are 10.72 µg•L-1 and 5.86 µg•L-1. This study provides basis for the construction of water quality standard of Liaoning and the environmental management of Biliu River.

Comparative evaluation of urban storm water quality models

NASA Astrophysics Data System (ADS)

Vaze, J.; Chiew, Francis H. S.

2003-10-01

The estimation of urban storm water pollutant loads is required for the development of mitigation and management strategies to minimize impacts to receiving environments. Event pollutant loads are typically estimated using either regression equations or "process-based" water quality models. The relative merit of using regression models compared to process-based models is not clear. A modeling study is carried out here to evaluate the comparative ability of the regression equations and process-based water quality models to estimate event diffuse pollutant loads from impervious surfaces. The results indicate that, once calibrated, both the regression equations and the process-based model can estimate event pollutant loads satisfactorily. In fact, the loads estimated using the regression equation as a function of rainfall intensity and runoff rate are better than the loads estimated using the process-based model. Therefore, if only estimates of event loads are required, regression models should be used because they are simpler and require less data compared to process-based models.

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

USDA-ARS?s Scientific Manuscript database

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...

The Spatially-Distributed Agroecosystem-Watershed (Ages-W) Hydrologic/Water Quality (H/WQ) model for assessment of conservation effects

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality (H/WQ) simulation components under the Object Modeling System (OMS3) environmental modeling framework. AgES-W has recently been enhanced with the addition of nitrogen (N) a...

Water quality observations of ice-covered, stagnant, eutrophic water bodies and analysis of influence of ice-covered period on water quality

NASA Astrophysics Data System (ADS)

sugihara, K.; Nakatsugawa, M.

2013-12-01

The water quality characteristics of ice-covered, stagnant, eutrophic water bodies have not been clarified because of insufficient observations. It has been pointed out that climate change has been shortening the duration of ice-cover; however, the influence of climate change on water quality has not been clarified. This study clarifies the water quality characteristics of stagnant, eutrophic water bodies that freeze in winter, based on our surveys and simulations, and examines how climate change may influence those characteristics. We made fixed-point observation using self-registering equipment and vertical water sampling. Self-registering equipment measured water temperature and dissolved oxygen(DO).vertical water sampling analyzed biological oxygen demand(BOD), total nitrogen(T-N), nitrate nitrogen(NO3-N), nitrite nitrogen(NO2-N), ammonium nitrogen(NH4-N), total phosphorus(TP), orthophosphoric phosphorus(PO4-P) and chlorophyll-a(Chl-a). The survey found that climate-change-related increases in water temperature were suppressed by ice covering the water area, which also blocked oxygen supply. It was also clarified that the bottom sediment consumed oxygen and turned the water layers anaerobic beginning from the bottom layer, and that nutrient salts eluted from the bottom sediment. The eluted nutrient salts were stored in the water body until the ice melted. The ice-covered period of water bodies has been shortening, a finding based on the analysis of weather and water quality data from 1998 to 2008. Climate change was surveyed as having caused decreases in nutrient salts concentration because of the shortened ice-covered period. However, BOD in spring showed a tendency to increase because of the proliferation of phytoplankton that was promoted by the climate-change-related increase in water temperature. To forecast the water quality by using these findings, particularly the influence of climate change, we constructed a water quality simulation model that incorporates the freezing-over of water bodies. The constructed model shows good temporal and spatial reproducibility and enables water quality to be forecast throughout the year, including during the ice-covered period. The forecasts using the model agree well with the survey results of shortened ice period and climate-change-related increase in the BOD in spring. From the result of calculations and observations, it is suggested that water quality of spring has been deteriorate because of freezing period to be shortened due to temperature rising.

Combined risk assessment of nonstationary monthly water quality based on Markov chain and time-varying copula.

PubMed

Shi, Wei; Xia, Jun

2017-02-01

Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH 3 -N) and permanganate index (COD Mn ) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH 3 -N and COD Mn series at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class V w , Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH 3 -N and COD Mn simultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH 3 -N and COD Mn is inferior to class V and class IV water quality standards, respectively.

Support vector machine-an alternative to artificial neuron network for water quality forecasting in an agricultural nonpoint source polluted river?

PubMed

Liu, Mei; Lu, Jun

2014-09-01

Water quality forecasting in agricultural drainage river basins is difficult because of the complicated nonpoint source (NPS) pollution transport processes and river self-purification processes involved in highly nonlinear problems. Artificial neural network (ANN) and support vector model (SVM) were developed to predict total nitrogen (TN) and total phosphorus (TP) concentrations for any location of the river polluted by agricultural NPS pollution in eastern China. River flow, water temperature, flow travel time, rainfall, dissolved oxygen, and upstream TN or TP concentrations were selected as initial inputs of the two models. Monthly, bimonthly, and trimonthly datasets were selected to train the two models, respectively, and the same monthly dataset which had not been used for training was chosen to test the models in order to compare their generalization performance. Trial and error analysis and genetic algorisms (GA) were employed to optimize the parameters of ANN and SVM models, respectively. The results indicated that the proposed SVM models performed better generalization ability due to avoiding the occurrence of overtraining and optimizing fewer parameters based on structural risk minimization (SRM) principle. Furthermore, both TN and TP SVM models trained by trimonthly datasets achieved greater forecasting accuracy than corresponding ANN models. Thus, SVM models will be a powerful alternative method because it is an efficient and economic tool to accurately predict water quality with low risk. The sensitivity analyses of two models indicated that decreasing upstream input concentrations during the dry season and NPS emission along the reach during average or flood season should be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data and even trimonthly data are available, the SVM methodology developed here can easily be applied to other NPS-polluted rivers.

Water Quality Is a Poor Predictor of Recreational Hotspots in England

PubMed Central

Mullin, Karen; Boeuf, Blandine; Fincham, William; Taylor, Nigel; Villalobos-Jiménez, Giovanna; von Vittorelli, Laura; Wolf, Christine; Fritsch, Oliver; Strauch, Michael; Seppelt, Ralf; Volk, Martin; Beckmann, Michael

2016-01-01

Maintaining and improving water quality is key to the protection and restoration of aquatic ecosystems, which provide important benefits to society. In Europe, the Water Framework Directive (WFD) defines water quality based on a set of biological, hydro-morphological and chemical targets, and aims to reach good quality conditions in all river bodies by the year 2027. While recently it has been argued that achieving these goals will deliver and enhance ecosystem services, in particular recreational services, there is little empirical evidence demonstrating so. Here we test the hypothesis that good water quality is associated with increased utilization of recreational services, combining four surveys covering walking, boating, fishing and swimming visits, together with water quality data for all water bodies in eight River Basin Districts (RBDs) in England. We compared the percentage of visits in areas of good water quality to a set of null models accounting for population density, income, age distribution, travel distance, public access, and substitutability. We expect such association to be positive, at least for fishing (which relies on fish stocks) and swimming (with direct contact to water). We also test if these services have stronger association with water quality relative to boating and walking alongside rivers, canals or lakeshores. In only two of eight RBDs (Northumbria and Anglian) were both criteria met (positive association, strongest for fishing and swimming) when comparing to at least one of the null models. This conclusion is robust to variations in dataset size. Our study suggests that achieving the WFD water quality goals may not enhance recreational ecosystem services, and calls for further empirical research on the connection between water quality and ecosystem services. PMID:27875562

Methods for estimating monthly mean concentrations of selected water-quality constituents for stream sites in the Red River of the North basin, North Dakota and Minnesota

USGS Publications Warehouse

Guenthner, R.S.

1991-01-01

Future development of the Garrison Diversion Unit may divert water from the Missouri River into the Sheyenne River and the Red River of the North for municipal and industrial use. The U.S. Bureau of Reclamation's Canals, Rivers, and Reservoirs Salinity Accounting Procedures model can be used to predict the effect various operating plans could have on water quality in the Sheyenne River and the Red River of the North. The model uses, as Input, monthly means of streamflow and selected water-quality constituents for a 54-year period at 28 nodes on the Sheyenne River and the Red River of the North. This report provides methods for estimating monthly mean concentrations of selected water-quality constituents that can be used for input to and calibration of the salinity model.Mater-quality data for 32 gaging stations can be used to define selected water-quality characteristics at the 28 model nodes. Materquality data were retrieved from the U.S. Geological Survey's National Mater Data Storage and Retrieval System data base and statistical summaries were prepared. The frequency of water-quality data collection at the gaging stations is inadequate to define monthly mean concentrations of the individual water-quality constituents for all months for the 54-year period; therefore, methods for estimating monthly mean concentrations were developed. Relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and streamflow were developed as the primary method to estimate monthly mean concentrations. Relations between specific conductance and streamflow and relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and specific conductance were developed so that a cascaded-regression relation could be developed as a second method of estimating monthly mean concentrations and, thus, utilize a large specific-conductance data base. Information about the quantity and the quality of ground water discharging to the Sheyenne River is needed for model input for reaches of the river where ground water accounts for a substantial part of streamflow during periods of low flow. Ground-water discharge was identified for two reaches of the Sheyenne River. Ground-water discharge to the Sheyenne River in the vicinity of Warwick, N.Dak., was about 14.8 cubic feet per second and the estimated dissolved-solids concentration was about 441 milligrams per liter during October 15 and 16, 1986. Ground-water discharge to the Sheyenne River in a reach between Lisbon and Kindred, N.Dak., ranged from an average of 25.3 cubic feet per second during September 13 to November 19, 1963, to about 45.0 cubic feet per second during October 21 and 22, 1986. Dissolved-solids concentration was estimated at about 442 milligrams per liter during October 21 and 22, 1986.

Threshold and resilience management of coupled urbanization and water environmental system in the rapidly changing coastal region.

PubMed

Li, Yangfan; Li, Yi; Wu, Wei

2016-01-01

The concept of thresholds shows important implications for environmental and resource management. Here we derived potential landscape thresholds which indicated abrupt changes in water quality or the dividing points between exceeding and failing to meet national surface water quality standards for a rapidly urbanizing city on the Eastern Coast in China. The analysis of landscape thresholds was based on regression models linking each of the seven water quality variables to each of the six landscape metrics for this coupled land-water system. We found substantial and accelerating urban sprawl at the suburban areas between 2000 and 2008, and detected significant nonlinear relations between water quality and landscape pattern. This research demonstrated that a simple modeling technique could provide insights on environmental thresholds to support more-informed decision making in land use, water environmental and resilience management. Copyright © 2015 Elsevier Ltd. All rights reserved.

A spatial model to aggregate point-source and nonpoint-source water-quality data for large areas

USGS Publications Warehouse

White, D.A.; Smith, R.A.; Price, C.V.; Alexander, R.B.; Robinson, K.W.

1992-01-01

More objective and consistent methods are needed to assess water quality for large areas. A spatial model, one that capitalizes on the topologic relationships among spatial entities, to aggregate pollution sources from upstream drainage areas is described that can be implemented on land surfaces having heterogeneous water-pollution effects. An infrastructure of stream networks and drainage basins, derived from 1:250,000-scale digital-elevation models, define the hydrologic system in this spatial model. The spatial relationships between point- and nonpoint pollution sources and measurement locations are referenced to the hydrologic infrastructure with the aid of a geographic information system. A maximum-branching algorithm has been developed to simulate the effects of distance from a pollutant source to an arbitrary downstream location, a function traditionally employed in deterministic water quality models. ?? 1992.

Predicting non-stationary algal dynamics following changes in hydrometeorological conditions using data assimilation techniques

NASA Astrophysics Data System (ADS)

Kim, S.; Seo, D. J.

2017-12-01

When water temperature (TW) increases due to changes in hydrometeorological conditions, the overall ecological conditions change in the aquatic system. The changes can be harmful to human health and potentially fatal to fish habitat. Therefore, it is important to assess the impacts of thermal disturbances on in-stream processes of water quality variables and be able to predict effectiveness of possible actions that may be taken for water quality protection. For skillful prediction of in-stream water quality processes, it is necessary for the watershed water quality models to be able to reflect such changes. Most of the currently available models, however, assume static parameters for the biophysiochemical processes and hence are not able to capture nonstationaries seen in water quality observations. In this work, we assess the performance of the Hydrological Simulation Program-Fortran (HSPF) in predicting algal dynamics following TW increase. The study area is located in the Republic of Korea where waterway change due to weir construction and drought concurrently occurred around 2012. In this work we use data assimilation (DA) techniques to update model parameters as well as the initial condition of selected state variables for in-stream processes relevant to algal growth. For assessment of model performance and characterization of temporal variability, various goodness-of-fit measures and wavelet analysis are used.

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

EPA Science Inventory

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

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

EPA Science Inventory

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...

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

EPA Science Inventory

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...

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

NASA Astrophysics Data System (ADS)

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 intervention scenarios were explored (including changes to land use and pesticide usage) with the aim of providing a useful input to the debate between water companies, their regulators and pesticide users over the scale of catchment management required to support both DWD and WFD Article 7 compliance.

Modelling transport of storm-water pollutants using the distributed Multi-Hydro platform on an urban catchment near Paris

NASA Astrophysics Data System (ADS)

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

2015-04-01

Nowadays, the increasingly use of vehicles causes expanding contaminated storm-water runoff from roads and the associated quarters. Besides, the current utilization of city's separated sewer systems underlines the needs for evaluating precisely the growing impact of these polluted effluents on receiving water bodies. Nevertheless, traditional means of water quality modelling had shown its limits (Kanso, 2004), more accurate modelling schemes are hence required. In this paper, we found that the application of physically based and fully distributed model coupled with detailed high-resolution data is a promising approach to reproduce the various dynamics and interactions of water quantity/quality processes in urban or peri-urban environment. Over recent years, the physically based and spatially distributed numerical platform Multi-Hydro (MH) has been developed at Ecole des Ponts ParisTech (El-Tabach et al. , 2009 ; Gires et al., 2013 ; Giangola-Murzyn et al., 2014). This platform is particularly adapted for representing the hydrological processes for medium size watersheds, including the surface runoff, drainage water routing and the infiltrations on permeable zones. It is formed by the interactive coupling of several independent modules, which depend on generally used open-access models. In the framework of the ANR (French National Agency for Research) Trafipollu project, a new extension of MH, MH-quality, was set up for the water-quality modelling. MH-quality was used for the simulation of pollutant transport on a peri-urban and highly trafficked catchment located near Paris (Le Perreux-sur-Marne, 0.2 km2). The set-up of this model is based on the detailed description of urban land use features. For this purpose, 15 classes of urban land uses relevant to water quality modelling were defined in collaboration with the National Institute of Geography of France (IGN) using Digital Orthophoto Quadrangles (5cm). The delimitation of the urban catchment was then performed by operating a Digital Terrain Model which was generated by applying Lidar data (20cm), and by using GIS information of the drainage system. In addition to land use information, the implementation of different human activities allows a better evaluation of contamination. Experimental data such as rainfall intensities, particle size distribution and dry weather depositions are also used, in order to feed the model with realistic input data and parameters. The runoff and water quality are then simulated for a few rainfall events. Taking advantage of the available data of the continuous observations of precipitation, water discharges and turbidity at the outlet of the drainage systems, the sensitivity analysis is carried out in order to evaluate the performance of MH-quality and the most sensitive parameters. Using appropriate parameters, we are now able to follow the pollutant transport on our experimental urban catchment. The limitations and the perspectives of MH-quality are discussed as well.

An Integrated Risk Management Model for Source Water Protection Areas

PubMed Central

Chiueh, Pei-Te; Shang, Wei-Ting; Lo, Shang-Lien

2012-01-01

Watersheds are recognized as the most effective management unit for the protection of water resources. For surface water supplies that use water from upstream watersheds, evaluating threats to water quality and implementing a watershed management plan are crucial for the maintenance of drinking water safe for humans. The aim of this article is to establish a risk assessment model that provides basic information for identifying critical pollutants and areas at high risk for degraded water quality. In this study, a quantitative risk model that uses hazard quotients for each water quality parameter was combined with a qualitative risk model that uses the relative risk level of potential pollution events in order to characterize the current condition and potential risk of watersheds providing drinking water. In a case study of Taipei Source Water Area in northern Taiwan, total coliforms and total phosphorus were the top two pollutants of concern. Intensive tea-growing and recreational activities around the riparian zone may contribute the greatest pollution to the watershed. Our risk assessment tool may be enhanced by developing, recording, and updating information on pollution sources in the water supply watersheds. Moreover, management authorities could use the resultant information to create watershed risk management plans. PMID:23202770

Assessment of the hydrogeology and water quality in a near-shore well field, Sarasota, Florida

USGS Publications Warehouse

Broska, J.C.; Knochenmus, L.A.

1996-01-01

The city of Sarasota, Florida, operates a downtown well field that pumps mineralized water from ground water sources to supply a reverse osmosis plant. Because of the close proximity of the well field to Sarasota Bay and the high sulfate and chloride concentrations of ground-water supplies, a growing concern exists about the possibility of lateral movement of saltwater in a landward direction (intrusion) and vertical movement of relict sea water (upconing). In 1992, the U.S. Geological Survey began a 3-year study to evaluate the hydraulic characteristics and water quality of ground-water resources within the downtown well field and the surrounding 235-square-mile study area. Delineation of the hydrogeology of the study area was based on water- quality data, aquifer test data, and extensive borehole geophysical surveys (including gamma, caliper, temperature, electrical resistivity, and flow meter logs) from the six existing production wells and from a corehole drilled as part of the study, as well as from published and unpublished reports on file at the U.S. Geological Survey, the Southwest Florida Water Management District, and consultant's reports. Water-quality data were examined for spatial and temporal trends that might relate to the mechanism for observed water-quality changes. Water quality in the study area appears to be dependent upon several mechanisms, including upconing of higher salinity water from deeper zones within the aquifer system, interbore-hole flow between zones of varying water quality through improperly cased and corroded wells, migration of highly mineralized waters through structural deformities, and the presence of unflushed relict seawater. A numerical ground-water flow model was developed as an interpretative tool where field-derived hydrologic characteristics could be tested. The conceptual model consisted of seven layers to represent the multilayered aquifer systems underlying the study area. Particle tracking was utilized to delineate the travel path of water as it enters the model area under a set of given conditions. Within the model area, simulated flow in the intermediate aquifer system originates primarily from the northwestern boundary. Simulated flow in the Upper Floridan aquifer originates in lower model layers (deeper flow zones) and ultimately can be traced to the southeastern and northwestern boundaries. Volumetric budgets calculated from numerical simulation of a hypothetical well field indicate that the area of contribution to the well field changes seasonally. Although ground-water flow patterns change with wet and dry seasons, most water enters the well-field flow system through lower parts of the Upper Floridan aquifer from a southeastern direction. Moreover, particle tracking indicated that ground-water flow paths with strictly lateral pathlines in model layers correspond to the intermediate aquifer system, whereas particles traced through model layers corresponding to the Upper Floridan aquifer had components of vertical and lateral flow.

Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development?

NASA Astrophysics Data System (ADS)

Honti, Mark; Schuwirth, Nele; Rieckermann, Jörg; Stamm, Christian

2017-03-01

The design and evaluation of solutions for integrated surface water quality management requires an integrated modelling approach. Integrated models have to be comprehensive enough to cover the aspects relevant for management decisions, allowing for mapping of larger-scale processes such as climate change to the regional and local contexts. Besides this, models have to be sufficiently simple and fast to apply proper methods of uncertainty analysis, covering model structure deficits and error propagation through the chain of sub-models. Here, we present a new integrated catchment model satisfying both conditions. The conceptual iWaQa model was developed to support the integrated management of small streams. It can be used to predict traditional water quality parameters, such as nutrients and a wide set of organic micropollutants (plant and material protection products), by considering all major pollutant pathways in urban and agricultural environments. Due to its simplicity, the model allows for a full, propagative analysis of predictive uncertainty, including certain structural and input errors. The usefulness of the model is demonstrated by predicting future surface water quality in a small catchment with mixed land use in the Swiss Plateau. We consider climate change, population growth or decline, socio-economic development, and the implementation of management strategies to tackle urban and agricultural point and non-point sources of pollution. Our results indicate that input and model structure uncertainties are the most influential factors for certain water quality parameters. In these cases model uncertainty is already high for present conditions. Nevertheless, accounting for today's uncertainty makes management fairly robust to the foreseen range of potential changes in the next decades. The assessment of total predictive uncertainty allows for selecting management strategies that show small sensitivity to poorly known boundary conditions. The identification of important sources of uncertainty helps to guide future monitoring efforts and pinpoints key indicators, whose evolution should be closely followed to adapt management. The possible impact of climate change is clearly demonstrated by water quality substantially changing depending on single climate model chains. However, when all climate trajectories are combined, the human land use and management decisions have a larger influence on water quality against a time horizon of 2050 in the study.

Ground-water models for water resource planning

USGS Publications Warehouse

Moore, J.E.

1983-01-01

In the past decade hydrogeologists have emphasized the development of computer-based mathematical models to aid in the understanding of flow, the transport of solutes, transport of heat, and deformation in the ground-water system. These models have been used to provide information and predictions for water managers. Too frequently, ground-water was neglected in water resource planning because managers believed that it could not be adequately evaluated in terms of availability, quality, and effect of development on surface-water supplies. Now, however, with newly developed digital ground-water models, effects of development can be predicted. Such models have been used to predict hydrologic and quality changes under different stresses. These models have grown in complexity over the last ten years from simple one-layer models to three-dimensional simulations of ground-water flow, which may include solute transport, heat transport, effects of land subsidence, and encroachment of saltwater. Case histories illustrate how predictive ground-water models have provided the information needed for the sound planning and management of water resources in the USA. ?? 1983 D. Reidel Publishing Company.

Hydrologic and water quality sensitivity to climate and land ...

EPA Pesticide Factsheets

This page describes a current EPA ORD project. No project report or other download is available at this time. Please see the section Next Steps below for a timeline of anticipated products of this work. Background: Projected changes in climate during the next century could cause or contribute to increased flooding, drought, water quality degradation, and ecosystem impairment. The effects of climate change in different watersheds will vary due to regional differences in climate change, physiographic setting, and interaction with land-use, pollutant sources, and water management in different locations. EPA is conducting watershed modeling to develop hydrologic and water quality change scenarios for 20 relatively large U.S. watersheds. Watershed modeling will be conducted using the Hydrologic Simulation Program-FORTRAN (HSPF) and Soil Water Assessment Tool (SWAT) watershed models. Study areas range from about 10,000-15,000 square miles in size, and will cover nearly every ecoregion in the United States and a range of hydro-climatic conditions. A range of hydrologic and water quality endpoints will be determined for each watershed simulation. Endpoints will be selected to inform upon a range of stream flow, water quality, aquatic ecosystem, and EPA program management goals and targets. Model simulations will be conducted to evaluate a range of projected future (2040-2070) changes in climate and land-use. Simulations will include baseline conditions,

Beach boundary layer: a framework for addressing recreational water quality impairment at enclosed beaches.

PubMed

Grant, Stanley B; Sanders, Brett F

2010-12-01

Nearshore waters in bays, harbors, and estuaries are frequently contaminated with human pathogens and fecal indicator bacteria. Tracking down and mitigating this contamination is complicated by the many point and nonpoint sources of fecal pollution that can degrade water quality along the shore. From a survey of the published literature, we propose a conceptual and mathematical framework, the "beach boundary layer model", for understanding and quantifying the relative impact of beach-side and bay-side sources of fecal pollution on nearshore water quality. In the model, bacterial concentration in ankle depth water C(ankle) [bacteria L(-3)] depends on the flux m'' [bacteria L(-2) T(-1)] of fecal bacteria from beach-side sources (bather shedding, bird and dog feces, tidal washing of sediments, decaying vegetation, runoff from small drains, and shallow groundwater discharge), a cross-shore mass transfer velocity k [L T(-1)] that accounts for the physics of nearshore transport and mixing, and a background concentration C(bay) [bacteria L(-3)] attributable to bay-side sources of pollution that impact water quality over large regions (sewage outfalls, creeks and rivers): C(ankle) = m''/k + C(bay). We demonstrate the utility of the model for identifying risk factors and pollution sources likely to impact shoreline water quality, and evaluate the model's underlying assumptions using computational fluid dynamic simulations of flow, turbulence, and mass transport in a trapezoidal channel.

Modelling daily dissolved oxygen concentration using least square support vector machine, multivariate adaptive regression splines and M5 model tree

NASA Astrophysics Data System (ADS)

Heddam, Salim; Kisi, Ozgur

2018-04-01

In the present study, three types of artificial intelligence techniques, least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5T) are applied for modeling daily dissolved oxygen (DO) concentration using several water quality variables as inputs. The DO concentration and water quality variables data from three stations operated by the United States Geological Survey (USGS) were used for developing the three models. The water quality data selected consisted of daily measured of water temperature (TE, °C), pH (std. unit), specific conductance (SC, μS/cm) and discharge (DI cfs), are used as inputs to the LSSVM, MARS and M5T models. The three models were applied for each station separately and compared to each other. According to the results obtained, it was found that: (i) the DO concentration could be successfully estimated using the three models and (ii) the best model among all others differs from one station to another.

Dynamic extreme values modeling and monitoring by means of sea shores water quality biomarkers and valvometry.

PubMed

Durrieu, Gilles; Pham, Quang-Khoai; Foltête, Anne-Sophie; Maxime, Valérie; Grama, Ion; Tilly, Véronique Le; Duval, Hélène; Tricot, Jean-Marie; Naceur, Chiraz Ben; Sire, Olivier

2016-07-01

Water quality can be evaluated using biomarkers such as tissular enzymatic activities of endemic species. Measurement of molluscs bivalves activity at high frequency (e.g., valvometry) during a long time period is another way to record the animal behavior and to evaluate perturbations of the water quality in real time. As the pollution affects the activity of oysters, we consider the valves opening and closing velocities to monitor the water quality assessment. We propose to model the huge volume of velocity data collected in the framework of valvometry using a new nonparametric extreme values statistical model. The objective is to estimate the tail probabilities and the extreme quantiles of the distribution of valve closing velocity. The tail of the distribution function of valve closing velocity is modeled by a Pareto distribution with parameter t,τ , beyond a threshold τ according to the time t of the experiment. Our modeling approach reveals the dependence between the specific activity of two enzymatic biomarkers (Glutathione-S-transferase and acetylcholinesterase) and the continuous recording of oyster valve velocity, proving the suitability of this tool for water quality assessment. Thus, valvometry allows in real-time in situ analysis of the bivalves behavior and appears as an effective early warning tool in ecological risk assessment and marine environment monitoring.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Estimating the susceptibility of surface water in Texas to nonpoint-source contamination by use of logistic regression modeling

USGS Publications Warehouse

Battaglin, William A.; Ulery, Randy L.; Winterstein, Thomas; Welborn, Toby

2003-01-01

In the State of Texas, surface water (streams, canals, and reservoirs) and ground water are used as sources of public water supply. Surface-water sources of public water supply are susceptible to contamination from point and nonpoint sources. To help protect sources of drinking water and to aid water managers in designing protective yet cost-effective and risk-mitigated monitoring strategies, the Texas Commission on Environmental Quality and the U.S. Geological Survey developed procedures to assess the susceptibility of public water-supply source waters in Texas to the occurrence of 227 contaminants. One component of the assessments is the determination of susceptibility of surface-water sources to nonpoint-source contamination. To accomplish this, water-quality data at 323 monitoring sites were matched with geographic information system-derived watershed- characteristic data for the watersheds upstream from the sites. Logistic regression models then were developed to estimate the probability that a particular contaminant will exceed a threshold concentration specified by the Texas Commission on Environmental Quality. Logistic regression models were developed for 63 of the 227 contaminants. Of the remaining contaminants, 106 were not modeled because monitoring data were available at less than 10 percent of the monitoring sites; 29 were not modeled because there were less than 15 percent detections of the contaminant in the monitoring data; 27 were not modeled because of the lack of any monitoring data; and 2 were not modeled because threshold values were not specified.

Evaluation of the influence of economic groups on the efficiency and quality of service of water companies: an empirical approach for Chile.

PubMed

Molinos-Senante, María; Farías, Rodrigo

2018-06-04

The privatization of water and sewerage services (WSS) has led to the foundation of water economic groups, which integrate several water companies and have gained notable importance at the global level. In the framework of benchmarking studies, there are no prior studies exploring the impact that economic groups have on the efficiency and quality of service provided by water companies. This study investigates, for the first time, whether the membership of water companies in an economic group influences their performance. Quantity- and quality-adjusted efficiency scores were computed using data envelopment analysis models. An empirical application was developed for the Chilean water industry since most of their water companies are private and belong to an economic group. The results show that independent water companies provide WSS with better quality than do water companies that belong to an economic group. From a statistical point of view, it was evident that membership in an economic group impacts both the quantity- and quality-adjusted efficiency scores of water companies. The results of this study illustrate that applying the model-firm regulation to the Chilean water industry has significant drawbacks that should be addressed by the water regulator to promote the long-term sustainability of the water industry.

75 FR 2860 - Clean Water Act Section 303(d): Call for Data for the Illinois River Watershed in Oklahoma and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-19

... in Oklahoma and Arkansas to address nutrient water quality impairments. The results of this watershed... Watershed. EPA requests that the public provide any water quality related data and information that may be... loads that are needed to meet water quality standards in both States. This watershed model will serve as...

Trophic State and Toxic Cyanobacteria Density in Optimization Modeling of Multi-Reservoir Water Resource Systems

PubMed Central

Sulis, Andrea; Buscarinu, Paola; Soru, Oriana; Sechi, Giovanni M.

2014-01-01

The definition of a synthetic index for classifying the quality of water bodies is a key aspect in integrated planning and management of water resource systems. In previous works [1,2], a water system optimization modeling approach that requires a single quality index for stored water in reservoirs has been applied to a complex multi-reservoir system. Considering the same modeling field, this paper presents an improved quality index estimated both on the basis of the overall trophic state of the water body and on the basis of the density values of the most potentially toxic Cyanobacteria. The implementation of the index into the optimization model makes it possible to reproduce the conditions limiting water use due to excessive nutrient enrichment in the water body and to the health hazard linked to toxic blooms. The analysis of an extended limnological database (1996–2012) in four reservoirs of the Flumendosa-Campidano system (Sardinia, Italy) provides useful insights into the strengths and limitations of the proposed synthetic index. PMID:24759172

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Impact of length of calibration period on the apex model output simulation performance

USDA-ARS?s Scientific Manuscript database

Datasets from long-term monitoring sites that can be used for calibration and validation of hydrologic and water quality models are rare due to resource constraints. As a result, hydrologic and water quality models are calibrated and, when possible, validated using short-term measured data. A previo...

Impact of length of calibration period on the APEX model water quantity and quality simulation performance

USDA-ARS?s Scientific Manuscript database

Availability of continuous long-term measured data for model calibration and validation is limited due to time and resources constraints. As a result, hydrologic and water quality models are calibrated and, if possible, validated when measured data is available. Past work reported on the impact of t...

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

PubMed

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.

An approach to predict water quality in data-sparse catchments using hydrological catchment similarity

NASA Astrophysics Data System (ADS)

Pohle, Ina; Glendell, Miriam; Stutter, Marc I.; Helliwell, Rachel C.

2017-04-01

An understanding of catchment response to climate and land use change at a regional scale is necessary for the assessment of mitigation and adaptation options addressing diffuse nutrient pollution. It is well documented that the physicochemical properties of a river ecosystem respond to change in a non-linear fashion. This is particularly important when threshold water concentrations, relevant to national and EU legislation, are exceeded. Large scale (regional) model assessments required for regulatory purposes must represent the key processes and mechanisms that are more readily understood in catchments with water quantity and water quality data monitored at high spatial and temporal resolution. While daily discharge data are available for most catchments in Scotland, nitrate and phosphorus are mostly available on a monthly basis only, as typified by regulatory monitoring. However, high resolution (hourly to daily) water quantity and water quality data exist for a limited number of research catchments. To successfully implement adaptation measures across Scotland, an upscaling from data-rich to data-sparse catchments is required. In addition, the widespread availability of spatial datasets affecting hydrological and biogeochemical responses (e.g. soils, topography/geomorphology, land use, vegetation etc.) provide an opportunity to transfer predictions between data-rich and data-sparse areas by linking processes and responses to catchment attributes. Here, we develop a framework of catchment typologies as a prerequisite for transferring information from data-rich to data-sparse catchments by focusing on how hydrological catchment similarity can be used as an indicator of grouped behaviours in water quality response. As indicators of hydrological catchment similarity we use flow indices derived from observed discharge data across Scotland as well as hydrological model parameters. For the latter, we calibrated the lumped rainfall-runoff model TUWModel using multiple objective functions. The relationships between indicators of hydrological catchment similarity, physical catchment characteristics and nitrate and phosphorus concentrations in rivers are then investigated using multivariate statistics. This understanding of the relationship between catchment characteristics, hydrological processes and water quality will allow us to implement more efficient regulatory water quality monitoring strategies, to improve existing water quality models and to model mitigation and adaptation scenarios to global change in data-sparse catchments.

Assessment of impacts of agricultural and climate change scenarios on watershed water quantity and quality, and crop production

NASA Astrophysics Data System (ADS)

Teshager, Awoke D.; Gassman, Philip W.; Schoof, Justin T.; Secchi, Silvia

2016-08-01

Modeling impacts of agricultural scenarios and climate change on surface water quantity and quality provides useful information for planning effective water, environmental and land use policies. Despite the significant impacts of agriculture on water quantity and quality, limited literature exists that describes the combined impacts of agricultural land use change and climate change on future bioenergy crop yields and watershed hydrology. In this study, the soil and water assessment tool (SWAT) eco-hydrological model was used to model the combined impacts of five agricultural land use change scenarios and three downscaled climate pathways (representative concentration pathways, RCPs) that were created from an ensemble of eight atmosphere-ocean general circulation models (AOGCMs). These scenarios were implemented in a well-calibrated SWAT model for the intensively farmed and tiled Raccoon River watershed (RRW) located in western Iowa. The scenarios were executed for the historical baseline, early century, mid-century and late century periods. The results indicate that historical and more corn intensive agricultural scenarios with higher CO2 emissions consistently result in more water in the streams and greater water quality problems, especially late in the 21st century. Planting more switchgrass, on the other hand, results in less water in the streams and water quality improvements relative to the baseline. For all given agricultural landscapes simulated, all flow, sediment and nutrient outputs increase from early-to-late century periods for the RCP4.5 and RCP8.5 climate scenarios. We also find that corn and switchgrass yields are negatively impacted under RCP4.5 and RCP8.5 scenarios in the mid- and late 21st century.

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

PubMed

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 management of pollution and better protection of important riverine water quality. Copyright © 2016 Elsevier B.V. All rights reserved.

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

EPA Science Inventory

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...

Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China

USGS Publications Warehouse

Wu, Yiping; Chen, Ji

2013-01-01

Understanding the physical processes of point source (PS) and nonpoint source (NPS) pollution is critical to evaluate river water quality and identify major pollutant sources in a watershed. In this study, we used the physically-based hydrological/water quality model, Soil and Water Assessment Tool, to investigate the influence of PS and NPS pollution on the water quality of the East River (Dongjiang in Chinese) in southern China. Our results indicate that NPS pollution was the dominant contribution (>94%) to nutrient loads except for mineral phosphorus (50%). A comprehensive Water Quality Index (WQI) computed using eight key water quality variables demonstrates that water quality is better upstream than downstream despite the higher level of ammonium nitrogen found in upstream waters. Also, the temporal (seasonal) and spatial distributions of nutrient loads clearly indicate the critical time period (from late dry season to early wet season) and pollution source areas within the basin (middle and downstream agricultural lands), which resource managers can use to accomplish substantial reduction of NPS pollutant loadings. Overall, this study helps our understanding of the relationship between human activities and pollutant loads and further contributes to decision support for local watershed managers to protect water quality in this region. In particular, the methods presented such as integrating WQI with watershed modeling and identifying the critical time period and pollutions source areas can be valuable for other researchers worldwide.

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

PubMed

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.

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

EPA Science Inventory

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...

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

PubMed Central

An, Yan; Zou, Zhihong; Li, Ranran

2014-01-01

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. PMID:24675643

Surface-water quality in agricultural watersheds of the North Carolina Coastal Plain associated with concentrated animal feeding operations

USGS Publications Warehouse

Harden, Stephen L.

2015-01-01

A classification tree model was developed to examine relations of watershed environmental attributes among the study sites with and without CAFO manure effects. Model results indicated that variations in swine barn density, percentage of wetlands, and total acres available for applying swine-waste manures had an important influence on those watersheds where CAFO effects on water quality were either evident or mitigated. Measurable effects of CAFO waste manures on stream water quality were most evident in those SW and SP watersheds having lower percentages of wetlands combined with higher swine barn densities and (or) higher total acres available for applying waste manure at the swine CAFOs. Stream water quality was similar to background agricultural conditions in SW and SP watersheds with lower swine barn densities coupled with higher percentages of wetlands or lower acres available for swine manure applications. The model provides a useful tool for exploring and identifying similar, unmonitored watersheds in the North Carolina Coastal Plain with potential CAFO manure influences on water quality that might warrant further examination.

Improving Water Management Decision Support Tools Using NASA Satellite and Modeling Data

NASA Astrophysics Data System (ADS)

Toll, D. L.; Arsenault, K.; Nigro, J.; Pinheiro, A.; Engman, E. T.; Triggs, J.; Cosgrove, B.; Alonge, C.; Boyle, D.; Allen, R.; Townsend, P.; Ni-Meister, W.

2006-05-01

One of twelve Applications of National priority within NASA's Applied Science Program, the Water Management Program Element addresses concerns and decision making related to water availability, water forecast and water quality. The goal of the Water Management Program Element is to encourage water management organizations to use NASA Earth science data, models products, technology and other capabilities in their decision support tools for problem solving. The Water Management Program Element partners with Federal agencies, academia, private firms, and may include international organizations. This paper further describes the Water Management Program with the objective of informing the applications community of the potential opportunities for using NASA science products for problem solving. We will illustrate some ongoing and application Water Management projects evaluating and benchmarking NASA data with partnering federal agencies and their decision support tools: 1) Environmental Protection Agency for water quality; 2) Bureau of Reclamation for water supply, demand and forecast; and 3) NOAA National Weather Service for improved weather prediction. Examples of the types of NASA contributions to the these agency decision support tools include: 1) satellite observations within models assist to estimate water storage, i.e., snow water equivalent, soil moisture, aquifer volumes, or reservoir storages; 2) model derived products, i.e., evapotranspiration, precipitation, runoff, ground water recharge, and other 4-dimensional data assimilation products; 3) improve water quality, assessments by using improved inputs from NASA models (precipitation, evaporation) and satellite observations (e.g., temperature, turbidity, land cover) to nonpoint source models; and 4) water (i.e., precipitation) and temperature predictions from days to decades over local, regional and global scales.

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

USGS Publications Warehouse

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. However, a combination of funding growth and extensive collaboration with other USGS programs and other Federal, State, and local agencies, public interest groups, professional and trade associations, academia, and private industry will be needed to fully realize the monitoring and modeling goals laid out in this plan (USGS Fact Sheet 2013-3008).

Predicting Trihalomethanes (THMs) in the New York City Water Supply

NASA Astrophysics Data System (ADS)

Mukundan, R.; Van Dreason, R.

2013-12-01

Chlorine, a commonly used disinfectant in most water supply systems, can combine with organic carbon to form disinfectant byproducts including carcinogenic trihalomethanes (THMs). We used water quality data from 24 monitoring sites within the New York City (NYC) water supply distribution system, measured between January 2009 and April 2012, to develop site-specific empirical models for predicting total trihalomethane (TTHM) levels. Terms in the model included various combinations of the following water quality parameters: total organic carbon, pH, specific conductivity, and water temperature. Reasonable estimates of TTHM levels were achieved with overall R2 of about 0.87 and predicted values within 5 μg/L of measured values. The relative importance of factors affecting TTHM formation was estimated by ranking the model regression coefficients. Site-specific models showed improved model performance statistics compared to a single model for the entire system most likely because the single model did not consider locational differences in the water treatment process. Although never out of compliance in 2011, the TTHM levels in the water supply increased following tropical storms Irene and Lee with 45% of the samples exceeding the 80 μg/L Maximum Contaminant Level (MCL) in October and November. This increase was explained by changes in water quality parameters, particularly by the increase in total organic carbon concentration and pH during this period.

Environmental and Water Quality Operational Studies: Proceedings of the DeGray Lake Symposium Held in Arkadelphia, Arkansas.

DTIC Science & Technology

1987-03-01

statistics for storm water quality variables and fractions of phosphorus, solids, and carbon are presented in Tables 7 and 8, respectively. The correlation...matrix and factor analysis (same method as used for baseflow) of storm water quality variables suggested three groups: Group I - TMG, TCA, TNA, TSI...models to predict storm water quality . The 11 static and 3 dynamic storm variables were used as potential dependent variables. All independent and

A probabilistic model of gastroenteritis risks associated with consumption of street food salads in Kumasi, Ghana: evaluation of methods to estimate pathogen dose from water, produce or food quality.

PubMed

Barker, S Fiona; Amoah, Philip; Drechsel, Pay

2014-07-15

With a rapidly growing urban population in Kumasi, Ghana, the consumption of street food is increasing. Raw salads, which often accompany street food dishes, are typically composed of perishable vegetables that are grown in close proximity to the city using poor quality water for irrigation. This study assessed the risk of gastroenteritis illness (caused by rotavirus, norovirus and Ascaris lumbricoides) associated with the consumption of street food salads using Quantitative Microbial Risk Assessment (QMRA). Three different risk assessment models were constructed, based on availability of microbial concentrations: 1) Water - starting from irrigation water quality, 2) Produce - starting from the quality of produce at market, and 3) Street - using microbial quality of street food salad. In the absence of viral concentrations, published ratios between faecal coliforms and viruses were used to estimate the quality of water, produce and salad, and annual disease burdens were determined. Rotavirus dominated the estimates of annual disease burden (~10(-3)Disability Adjusted Life Years per person per year (DALYs pppy)), although norovirus also exceeded the 10(-4)DALY threshold for both Produce and Street models. The Water model ignored other on-farm and post-harvest sources of contamination and consistently produced lower estimates of risk; it likely underestimates disease burden and therefore is not recommended. Required log reductions of up to 5.3 (95th percentile) for rotavirus were estimated for the Street model, demonstrating that significant interventions are required to protect the health and safety of street food consumers in Kumasi. Estimates of virus concentrations were a significant source of model uncertainty and more data on pathogen concentrations is needed to refine QMRA estimates of disease burden. Copyright © 2014 Elsevier B.V. All rights reserved.

The role of headwater streams in downstream water quality

USGS Publications Warehouse

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

2007-01-01

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters. ?? 2007 American Water Resources Association.

Water quality, hydrology, and phosphorus loading to Little St. Germain Lake, Wisconsin, with special emphasis on the effects of winter aeration and ground-water inputs

USGS Publications Warehouse

Robertson, Dale M.; Rose, William J.; Saad, David A.

2005-01-01

Several empirical water-quality models were used to simulate how the East and Upper East Bays of the lake should respond to reductions in phosphorus loading from Muskellunge Creek. Simulation results indicated that reductions in tributary loading could improve the water quality of the East and Upper East Bays. Improving the water quality of these bays would also improve the water quality of the South and Second South Bays because of the flow of water through the lake. However, even with phosphorus loading from Muskellunge Creek completely eliminated, most of the lake would remain borderline mesotrophic/eutrophic because of the contributions of phosphorus from ground water.

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

PubMed

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

2018-03-01

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

Statistical Analysis of Regional Surface Water Quality in Southeastern Ontario.

ERIC Educational Resources Information Center

Bodo, Byron A.

1992-01-01

Historical records from Ontario's Provincial Water Quality Monitoring Network for rivers and streams were analyzed to assess the feasibility of mapping regional water quality patterns in southeastern Ontario, spanning the Precambrian Shield and the St. Lawrence Lowlands. The study served as a model for much of Ontario. (54 references) (Author/MDH)

Three-Dimensional Numerical Simulation of Water Quality and Sediment-Associated Processes with Application to a Mississippi Delta Lake

USDA-ARS?s Scientific Manuscript database

A three-dimensional water quality model was developed for simulating temporal and spatial variations of phytoplankton, nutrients, and dissolved oxygen in freshwater bodies. Effects of suspended and bed sediment on the water quality processes were simulated. A formula was generated from field measure...

Numerical methods for assessing water quality in lakes and reservoirs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mahamah, D.S.

1984-01-01

Water quality models are used as tools for predicting both short-term and long-term trends in water quality. They are generally classified into two groups based on the degree of empiricism. The two groups consists of the purely empirical types known as black-box models and the theoretical types called ecosystem models. This dissertation deals with both types of water quality models. The first part deals with empirical phosphorus models. The theory behind this class of models is discussed, leading to the development of an empirical phosphorus model using data from 79 western US lakes. A new approach to trophic state classificationmore » is introduced. The data used for the model was obtained from the Environmental Protection Agency National Eutrophication Study (EPA-NES) of western US lakes. The second portion of the dissertation discusses the development of an ecosystem model for culturally eutrophic Liberty Lake situated in eastern Washington State. The model is capable of simulating chlorophyll-a, phosphorus, and nitrogen levels in the lake on a weekly basis. For computing sediment release rates of phosphorus and nitrogen, equations based on laboratory bench-top studies using sediment samples from Liberty Lake are used. The model is used to simulate certain hypothetical nutrient control techniques such as phosphorus flushing, precipitation, and diversion.« less

Swimmer illness associated with marine water exposure and water quality indicators: impact of widely used assumptions

EPA Science Inventory

Studies of health risks associated with recreational water exposure require investigators to make choices about water quality indicator averaging techniques, exposure definitions, follow-up periods, and model specifications; but, investigators seldom describe the impact of these ...

The Role of Headwater Streams in Downstream Water Quality1

PubMed Central

Alexander, Richard B; Boyer, Elizabeth W; Smith, Richard A; Schwarz, Gregory E; Moore, Richard B

2007-01-01

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters. PMID:22457565

Source partitioning of anthropogenic groundwater nitrogen in a mixed-use landscape, Tutuila, American Samoa

NASA Astrophysics Data System (ADS)

Shuler, Christopher K.; El-Kadi, Aly I.; Dulai, Henrietta; Glenn, Craig R.; Fackrell, Joseph

2017-12-01

This study presents a modeling framework for quantifying human impacts and for partitioning the sources of contamination related to water quality in the mixed-use landscape of a small tropical volcanic island. On Tutuila, the main island of American Samoa, production wells in the most populated region (the Tafuna-Leone Plain) produce most of the island's drinking water. However, much of this water has been deemed unsafe to drink since 2009. Tutuila has three predominant anthropogenic non-point-groundwater-pollution sources of concern: on-site disposal systems (OSDS), agricultural chemicals, and pig manure. These sources are broadly distributed throughout the landscape and are located near many drinking-water wells. Water quality analyses show a link between elevated levels of total dissolved groundwater nitrogen (TN) and areas with high non-point-source pollution density, suggesting that TN can be used as a tracer of groundwater contamination from these sources. The modeling framework used in this study integrates land-use information, hydrological data, and water quality analyses with nitrogen loading and transport models. The approach utilizes a numerical groundwater flow model, a nitrogen-loading model, and a multi-species contaminant transport model. Nitrogen from each source is modeled as an independent component in order to trace the impact from individual land-use activities. Model results are calibrated and validated with dissolved groundwater TN concentrations and inorganic δ15N values, respectively. Results indicate that OSDS contribute significantly more TN to Tutuila's aquifers than other sources, and thus should be prioritized in future water-quality management efforts.

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

NASA Astrophysics Data System (ADS)

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-time for the reservoir model. This approach proved useful in probing a water supply's resilience to extreme events, and to inform management responses, particularly in a region such as the American Northeast where climate change is expected to bring such events with higher frequency and intensity than have occurred in the past.

High-Performance Integrated Control of water quality and quantity in urban water reservoirs

NASA Astrophysics Data System (ADS)

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

2015-11-01

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 3-D, high-fidelity simulation model to predict the main water quality dynamics and inform a real-time controller based on Model Predictive Control. The integration of the simulation model into the control scheme is performed by a model reduction process that identifies a low-order, dynamic emulator running 4 orders of magnitude faster. The model reduction, which relies on a semiautomatic procedural approach integrating time series clustering and variable selection algorithms, generates a compact and physically meaningful emulator that can be coupled with the controller. The framework is used to design the hourly operation of Marina Reservoir, a 3.2 Mm3 storm-water-fed reservoir located in the center 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 behavior is modeled with Delft3D-FLOW. Results show that our control framework reduces the minimum salinity levels by nearly 40% and cuts the average annual deficit of drinking water supply by about 2 times the active storage of the reservoir (about 4% of the total annual demand).

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

PubMed

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.

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

PubMed

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

2018-02-01

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

Total maximum allocated load calculation of nitrogen pollutants by linking a 3D biogeochemical-hydrodynamic model with a programming model in Bohai Sea

NASA Astrophysics Data System (ADS)

Dai, Aiquan; Li, Keqiang; Ding, Dongsheng; Li, Yan; Liang, Shengkang; Li, Yanbin; Su, Ying; Wang, Xiulin

2015-12-01

The equal percent removal (EPR) method, in which pollutant reduction ratio was set as the same in all administrative regions, failed to satisfy the requirement for water quality improvement in the Bohai Sea. Such requirement was imposed by the developed Coastal Pollution Total Load Control Management. The total maximum allocated load (TMAL) of nitrogen pollutants in the sea-sink source regions (SSRs) around the Bohai Rim, which is the maximum pollutant load of every outlet under the limitation of water quality criteria, was estimated by optimization-simulation method (OSM) combined with loop approximation calculation. In OSM, water quality is simulated using a water quality model and pollutant load is calculated with a programming model. The effect of changes in pollutant loads on TMAL was discussed. Results showed that the TMAL of nitrogen pollutants in 34 SSRs was 1.49×105 ton/year. The highest TMAL was observed in summer, whereas the lowest in winter. TMAL was also higher in the Bohai Strait and central Bohai Sea and lower in the inner area of the Liaodong Bay, Bohai Bay and Laizhou Bay. In loop approximation calculation, the TMAL obtained was considered satisfactory for water quality criteria as fluctuation of concentration response matrix with pollutant loads was eliminated. Results of numerical experiment further showed that water quality improved faster and were more evident under TMAL input than that when using the EPR method

Modeling the impacts of winter cover crops on water quality in two adjacent sub-watersheds within the Chesapeake Bay Watershed, Maryland, USA

USDA-ARS?s Scientific Manuscript database

The Choptank River on Maryland’s Eastern Shore has been designated by the USEPA as “impaired waters” under Section 303(d) of the Federal Clean Water Act of 1972, mainly because of significant nutrient loads that resulted in not meeting the EPA water quality standards. This water quality deteriorati...

MODELING CONSISTENCY, MODEL QUALITY, AND FOSTERING CONTINUED IMPROVEMENT

EPA Science Inventory

We believe that most contributors to and participants of the International Conference, Marine Waste Water Discharges 2000, "MWWD 2000," could agree that the overarching dream of the conference might be to chart a path the will lead to the best, long-term, applicable water quality...

STAND, A DYNAMIC MODEL FOR SEDIMENT TRANSPORT AND WATER QUALITY. (R825758)

EPA Science Inventory

We introduce a new model–STAND (Sediment-Transport-Associated Nutrient Dynamics)–for simulating stream flow, sediment transport, and the interactions of sediment with other attributes of water quality. In contrast to other models, STAND employs a fully dynamic ba...

Assessing the use of treated waste water for irrigation agricultural lands by using soil quality indices

NASA Astrophysics Data System (ADS)

Arcenegui, V.; Morugán, A.; García-Orenes, F.; Zornoza, R.; Mataix-Solera, J.; Navarro, M. A.; Guerrero, C.; Mataix-Beneyto, J.

2009-04-01

The use of treated wastewater for the irrigation of agricultural soils is an alternative to utilizing better-quality water, especially in semiarid regions where water shortage is a very serious problem. However, this practise can modify the soil equilibrium and affect its quality. In this work two soil quality indices (models) are used to evaluate the effects of long-term irrigation with treated wastewater in soil. The models were developed studying different soil properties in undisturbed forest soils in SE Spain, and the relationships between soil parameters were established using multiple linear regressions. Model 1, that explained 92% of the variance in soil organic carbon (SOC) showed that the SOC can be calculated by the linear combination of 6 physical, chemical and biochemical properties (acid phosphatase, water holding capacity (WHC), electrical conductivity (EC), available phosphorus (P), cation exchange capacity (CEC) and aggregate stability (AS)). Model 2 explains 89% of the SOC variance, which can be calculated by means of 7 chemical and biochemical properties (urease, phosphatase, and

Ground-water models for water resources planning

USGS Publications Warehouse

Moore, John E.

1980-01-01

In the past decade hydrologists have emphasized the development of computer-based mathematical models to aid in the understanding of flow, the transport of solutes, transport of heat, and deformation in the groundwater system. These models have been used to provide information and predictions for water managers. Too frequently, groundwater was neglected in water-resource planning because managers believed that it could not be adequately evaluated in terms of availability, quality, and effect of development on surface water supplies. Now, however, with newly developed digital groundwater models, effects of development can be predicted. Such models have been used to predict hydrologic and quality changes under different stresses. These models have grown in complexity over the last 10 years from simple one-layer flow models to three-dimensional simulations of groundwater flow which may include solute transport, heat transport, effects of land subsidence, and encroachment of salt water. This paper illustrates, through case histories, how predictive groundwater models have provided the information needed for the sound planning and management of water resources in the United States. (USGS)

Perceptions of drinking water quality and risk and its effect on behaviour: a cross-national study.

PubMed

Doria, Miguel de França; Pidgeon, Nick; Hunter, Paul R

2009-10-15

There is a growing effort to provide drinking water that has the trust of consumers, but the processes underlying the perception of drinking water quality and risks are still not fully understood. This paper intends to explore the factors involved in public perception of the quality and risks of drinking water. This purpose was addressed with a cross-national mixed-method approach, based on quantitative (survey) and qualitative (focus groups) data collected in the UK and Portugal. The data were analysed using several methods, including structural equation models and generalised linear models. Results suggest that perceptions of water quality and risk result from a complex interaction of diverse factors. The estimation of water quality is mostly influenced by satisfaction with organoleptic properties (especially flavour), risk perception, contextual cues, and perceptions of chemicals (lead, chlorine, and hardness). Risk perception is influenced by organoleptics, perceived water chemicals, external information, past health problems, and trust in water suppliers, among other factors. The use of tap and bottled water to drink was relatively well explained by regression analysis. Several cross-national differences were found and the implications are discussed. Suggestions for future research are provided.

Using water-quality profiles to characterize seasonal water quality and loading in the upper Animas River basin, southwestern Colorado

USGS Publications Warehouse

Leib, Kenneth J.; Mast, M. Alisa; Wright, Winfield G.

2003-01-01

One of the important types of information needed to characterize water quality in streams affected by historical mining is the seasonal pattern of toxic trace-metal concentrations and loads. Seasonal patterns in water quality are estimated in this report using a technique called water-quality profiling. Water-quality profiling allows land managers and scientists to assess priority areas to be targeted for characterization and(or) remediation by quantifying the timing and magnitude of contaminant occurrence. Streamflow and water-quality data collected at 15 sites in the upper Animas River Basin during water years 1991?99 were used to develop water-quality profiles. Data collected at each sampling site were used to develop ordinary least-squares regression models for streamflow and constituent concentrations. Streamflow was estimated by correlating instantaneous streamflow measured at ungaged sites with continuous streamflow records from streamflow-gaging stations in the subbasin. Water-quality regression models were developed to estimate hardness and dissolved cadmium, copper, and zinc concentrations based on streamflow and seasonal terms. Results from the regression models were used to calculate water-quality profiles for streamflow, constituent concentrations, and loads. Quantification of cadmium, copper, and zinc loads in a stream segment in Mineral Creek (sites M27 to M34) was presented as an example application of water-quality profiling. The application used a method of mass accounting to quantify the portion of metal loading in the segment derived from uncharacterized sources during different seasonal periods. During May, uncharacterized sources contributed nearly 95 percent of the cadmium load, 0 percent of the copper load (or uncharacterized sources also are attenuated), and about 85 percent of the zinc load at M34. During September, uncharacterized sources contributed about 86 percent of the cadmium load, 0 percent of the copper load (or uncharacterized sources also are attenuated), and about 52 percent of the zinc load at M34. Characterized sources accounted for more of the loading gains estimated in the example reach during September, possibly indicating the presence of diffuse inputs during snowmelt runoff. The results indicate that metal sources in the upper Animas River Basin may change substantially with season, regardless of the source.

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Treesearch

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...

STREAM WATER QUALITY MODEL

EPA Science Inventory

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). Q2K is similar to Q2E in the following respects:

• One dimensional. The channel is well-mixed vertically a...

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

  USGS Publications Warehouse

  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)

• Simulation of runoff and water quality for 1990 and 2008 land use conditions in the Reedy Creek watershed, East-Central Florida

  USGS Publications Warehouse

  Wicklein, Shaun M.; Schiffer, Donna M.

  2002-01-01

  Hydrologic and water-quality data have been collected within the 177-square-mile Reedy Creek, Florida, watershed, beginning as early as 1939, but the data have not been used to evaluate relations among land use, hydrology, and water quality. A model of the Reedy Creek watershed was developed and applied to the period January 1990 to December 1995 to provide a computational foundation for evaluating the effects of future land-use changes on hydrology and water quality in the watershed. The Hydrological Simulation Program-Fortran (HSPF) model was used to simulate hydrology and water quality of runoff for pervious land areas, impervious land areas, and stream reaches. Six land-use types were used to characterize the hydrology and water quality of pervious and impervious land areas in the Reedy Creek watershed: agriculture, rangeland, forest, wetlands, rapid infiltration basins, and urban areas. Hydrologic routing and water-quality reactions were simulated to characterize hydrologic and water-quality processes and the movement of runoff and its constituents through the main stream channels and their tributaries. Because of the complexity of the stream system within the Reedy Creek Improvement District (RCID) (hydraulic structures, retention ponds) and the anticipated difficulty of modeling the system, an approach of calibrating the model parameters for a subset of the gaged watersheds and confirming the usefulness of the parameters by simulating the remainder of the gaged sites was selected for this study. Two sub-watersheds (Whittenhorse Creek and Davenport Creek) were selected for calibration because both have similar land use to watersheds within the RCID (with the exception of urban areas). Given the lack of available rainfall data, the hydrologic calibration of the Whittenhorse Creek and Davenport Creek sub-watersheds was considered acceptable (for monthly data, correlation coefficients, 0.86 and 0.88, and coefficients of model-fit efficiency, 0.72 and 0.74, respectively). The hydrologic model was tested by applying the parameter sets developed for Whittenhorse Creek and Davenport Creek to other land areas within the Reedy Creek watershed, and by comparing the simulated results to observed data sets for Reedy Creek near Vineland, Bonnet Creek near Vineland, and Reedy Creek near Loughman. The hydrologic model confirmation for Reedy Creek near Vineland (correlation coefficient, 0.91, and coefficient of model fit efficiency, 0.78, for monthly flows) was acceptable. Flows for Bonnet Creek near Vineland were substantially under simulated. Consideration of the ground-water contribution to Bonnet Creek could improve the water balance simulation for Bonnet Creek near Vineland. On longer time scales (monthly or over the 72-month simulation period), simulated discharges for Reedy Creek near Loughman agreed well with observed data (correlation coefficient, 0.88). For monthly flows the coefficient of model-fit efficiency was 0.77. On a shorter time scale (less than a month), however, storm volumes were greatly over simulated and low flows (less than 8 cubic feet per second) were greatly under simulated. A primary reason for the poor results at low flows is the diversion of an unknown amount of water from the RCID at the Bonnet Creek near Kissimmee site. Selection of water-quality constituents for simulation was based primarily on the availability of water-quality data. Dissolved oxygen, nitrogen, and phosphorus species were simulated. Representation of nutrient cycling in HSPF also required simulation of biochemical oxygen demand and phytoplankton populations. The correlation coefficient for simulated and observed daily mean dissolved oxygen concentration values at Reedy Creek near Vineland was 0.633. Simulated time series of total phosphorus, phosphate, ammonia nitrogen, and nitrate nitrogen generally agreed well with periodically observed values for the Whittenhorse Creek and Davenport Creek sites. Simulated water-quality c

• Modeling Water Clarity and Light Quality in Oceans

  EPA Science Inventory

  Phytoplankton is a primary producer of organic compounds, and it forms the base of the food chain in ocean waters. The concentration of phytoplankton in the water column controls water clarity and the amount and quality of light that penetrates through it. The availability of ade...

• Modeling the impact of watershed management policies on marine ecosystem services with application to Hood Canal, WA, USA

  NASA Astrophysics Data System (ADS)

  Sutherland, D. A.; Kim, C.; Marsik, M.; Spiridonov, G.; Toft, J.; Ruckelshaus, M.; Guerry, A.; Plummer, M.

  2011-12-01

  Humans obtain numerous benefits from marine ecosystems, including fish to eat; mitigation of storm damage; nutrient and water cycling and primary production; and cultural, aesthetic and recreational values. However, managing these benefits, or ecosystem services, in the marine world relies on an integrated approach that accounts for both marine and watershed activities. Here we present the results of a set of simple, physically-based, and spatially-explicit models that quantify the effects of terrestrial activities on marine ecosystem services. Specifically, we model the circulation and water quality of Hood Canal, WA, USA, a fjord system in Puget Sound where multiple human uses of the nearshore ecosystem (e.g., shellfish aquaculture, recreational Dungeness crab and shellfish harvest) can be compromised when water quality is poor (e.g., hypoxia, excessive non-point source pollution). Linked to the estuarine water quality model is a terrestrial hydrology model that simulates streamflow and nutrient loading, so land cover and climate changes in watersheds can be reflected in the marine environment. In addition, a shellfish aquaculture model is linked to the water quality model to test the sensitivity of the ecosystem service and its value to both terrestrial and marine activities. The modeling framework is general and will be publicly available, allowing easy comparisons of watershed impacts on marine ecosystem services across multiple scales and regions.

• Predicting fire effects on water quality: a perspective and future needs

  NASA Astrophysics Data System (ADS)

  Smith, Hugh; Sheridan, Gary; Nyman, Petter; Langhans, Christoph; Noske, Philip; Lane, Patrick

  2017-04-01

  Forest environments are a globally significant source of drinking water. Fire presents a credible threat to the supply of high quality water in many forested regions. The post-fire risk to water supplies depends on storm event characteristics, vegetation cover and fire-related changes in soil infiltration and erodibility modulated by landscape position. The resulting magnitude of runoff generation, erosion and constituent flux to streams and reservoirs determines the severity of water quality impacts in combination with the physical and chemical composition of the entrained material. Research to date suggests that most post-fire water quality impacts are due to large increases in the supply of particulates (fine-grained sediment and ash) and particle-associated chemical constituents. The largest water quality impacts result from high magnitude erosion events, including debris flow processes, which typically occur in response to short duration, high intensity storm events during the recovery period. Most research to date focuses on impacts on water quality after fire. However, information on potential water quality impacts is required prior to fire events for risk planning. Moreover, changes in climate and forest management (e.g. prescribed burning) that affect fire regimes may alter water quality risks. Therefore, prediction requires spatial-temporal representation of fire and rainfall regimes coupled with information on fire-related changes to soil hydrologic parameters. Recent work has applied such an approach by combining a fire spread model with historic fire weather data in a Monte Carlo simulation to quantify probabilities associated with fire and storm events generating debris flows and fine sediment influx to a reservoir located in Victoria, Australia. Prediction of fire effects on water quality would benefit from further research in several areas. First, more work on regional-scale stochastic modelling of intersecting fire and storm events with landscape zones of erosion vulnerability is required to support quantitative evaluation of water quality risk and the effect of future changes in climate and land management. Second, we underscore previous calls for characterisation of landscape-scale domains to support regionalisation of parameter sets derived from empirical studies. Recent examples include work identifying aridity as a control of hydro-geomorphic response to fire and the use of spectral-based indices to predict spatial heterogeneity in ash loadings. Third, information on post-fire erosion from colluvial or alluvial stores is needed to determine their significance as both sediment-contaminant sinks and sources. Such sediment stores may require explicit spatial representation in risk models for some environments and sediment tracing can be used to determine their relative importance as secondary sources. Fourth, increased dating of sediment archives could provide regional datasets of fire-related erosion event frequency. Presently, the lack of such data hinders evaluation of risk models linking fire and storm events to erosion and water quality impacts.

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

  NASA Astrophysics Data System (ADS)

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

  2013-12-01

  The evaluation of water quality through 'indexes' is widely used in environmental sciences. There are a number of methods available for calculating water quality indexes (WQI), usually based on site-specific parameters. In Brazil, WQI were initially used in the 1970s and were adapted from the methodology developed in association with the National Science Foundation (Brown et al, 1970). Specifically, the WQI 'IQA/SCQA', developed by the Institute of Water Management of Minas Gerais (IGAM), is estimated based on nine parameters: Temperature Range, Biochemical Oxygen Demand, Fecal Coliforms, Nitrate, Phosphate, Turbidity, Dissolved Oxygen, pH and Electrical Conductivity. The goal of this study was to develop a model for calculating the IQA/SCQA, for the Piabanha River basin in the State of Rio de Janeiro (Brazil), using only the parameters measurable by a Multiparameter Water Quality Sonde (MWQS) available in the study area. These parameters are: Dissolved Oxygen, pH and Electrical Conductivity. The use of this model will allow to further the water quality monitoring network in the basin, without requiring significant increases of resources. The water quality measurement with MWQS is less expensive than the laboratory analysis required for the other parameters. The water quality data used in the study were obtained by the Geological Survey of Brazil in partnership with other public institutions (i.e. universities and environmental institutes) as part of the project "Integrated Studies in Experimental and Representative Watersheds". Two models were developed to correlate the values of the three measured parameters and the IQA/SCQA values calculated based on all nine parameters. The results were evaluated according to the following validation statistics: coefficient of determination (R2), Root Mean Square Error (RMSE), Akaike information criterion (AIC) and Final Prediction Error (FPE). The first model was a linear stepwise regression between three independent variables (input) and one dependent variable (output) to establish an equation relating input to output. This model produced the following statistics: R2 = 0.85, RMSE = 6.19, AIC =0.65 and FPE = 1.93. The second model was a Feedforward Neural Network with one tan-sigmoid hidden layer (4 neurons) and one linear output layer. The neural network was trained based on a backpropagation algorithm using the input as predictors and the output as target. The following statistics were found: R2 = 0.95, RMSE = 4.86, AIC= 0.33 and FPE = 1.39. The second model produced a better fit than the first one, having a greater R2 and smaller RMSE, AIC and FPE. The best performance of the second method can be attributed to the fact that the water quality parameters often exhibit nonlinear behaviors and neural networks are capable of representing nonlinear relationship efficiently, while the regression is limited to linear relationships. References: Brown, R.M., McLelland, N.I., Deininger, R.A., Tozer, R.G.1970. A Water Quality Index-Do we dare? Water & Sewage Works, October: 339-343.

• Development of water environment information management and water pollution accident response system

  NASA Astrophysics Data System (ADS)

  Zhang, J.; Ruan, H.

  2009-12-01

  In recent years, many water pollution accidents occurred with the rapid economical development. In this study, water environment information management and water pollution accident response system are developed based on geographic information system (GIS) techniques. The system integrated spatial database, attribute database, hydraulic model, and water quality model under a user-friendly interface in a GIS environment. System ran in both Client/Server (C/S) and Browser/Server (B/S) platform which focused on model and inquiry respectively. System provided spatial and attribute data inquiry, water quality evaluation, statics, water pollution accident response case management (opening reservoir etc) and 2D and 3D visualization function, and gave assistant information to make decision on water pollution accident response. Polluted plume in Huaihe River were selected to simulate the transport of pollutes.

• Evaluation of future base-flow water-quality conditions in the Hillsborough River, Florida

  USGS Publications Warehouse

  Fernandez, Mario; Goetz, C.L.; Miller, J.E.

  1984-01-01

  A one-dimensional, steady-state, water-quality model was developed for a 30.0 mile reach of the Hillsborough River to evaluate water-quality conditions to be expected from future development. The model was calibrated and verified using data collected under critical base-flow conditions in April and December 1978. Dissolved organic nitrogen, nitrate nitrogen, and total and fecal coliforms were modeled for most of the study reach. Model results were used to evaluate the impacts of two typical housing developments on water-quality conditions in Tampa Reservoir. One development is located in the Cypress Creek basin and the other near the upper end of the study reach. Model results show development in the Hillsborough River basin may cause increased total and fecal coliform conditions. Simulated total coliforms at the Tampa water treatment plant for 1-, 3-, and 5-square-mile developments located in the Cypress Creek basin were 3,000, 5,400, and 8,300 colonies per 100 milliliters. Similar developments, however, located near the upper end of the study reach were 2,000, 3,600, and 5,100 colonies per 100 milliliters. Simulated fecal coliforms were 360, 700, and 100 and 180, 350, and 510 colonies per 100 milliliters, respectively. Other constituents modeled showed only minor increases in concentrations. (USGS)

• Exploratory multivariate modeling and prediction of the physico-chemical properties of surface water and groundwater

  NASA Astrophysics Data System (ADS)

  Ayoko, Godwin A.; Singh, Kirpal; Balerea, Steven; Kokot, Serge

  2007-03-01

  SummaryPhysico-chemical properties of surface water and groundwater samples from some developing countries have been subjected to multivariate analyses by the non-parametric multi-criteria decision-making methods, PROMETHEE and GAIA. Complete ranking information necessary to select one source of water in preference to all others was obtained, and this enabled relationships between the physico-chemical properties and water quality to be assessed. Thus, the ranking of the quality of the water bodies was found to be strongly dependent on the total dissolved solid, phosphate, sulfate, ammonia-nitrogen, calcium, iron, chloride, magnesium, zinc, nitrate and fluoride contents of the waters. However, potassium, manganese and zinc composition showed the least influence in differentiating the water bodies. To model and predict the water quality influencing parameters, partial least squares analyses were carried out on a matrix made up of the results of water quality assessment studies carried out in Nigeria, Papua New Guinea, Egypt, Thailand and India/Pakistan. The results showed that the total dissolved solid, calcium, sulfate, sodium and chloride contents can be used to predict a wide range of physico-chemical characteristics of water. The potential implications of these observations on the financial and opportunity costs associated with elaborate water quality monitoring are discussed.

• Examining issues with water quality model configuration

  USDA-ARS?s Scientific Manuscript database

  Complex watershed–scale, water quality models require a considerable amount of data in order to be properly configured, especially in view of the scarcity of data in many regions due to temporal and economic constraints. In this study, we examined two different input issues incurred while building ...

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

  USDA-ARS?s Scientific Manuscript database

  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 ...

• USING COMPUTER MODELS TO DETERMINE THE EFFECT OF STORAGE ON WATER QUALITY

  EPA Science Inventory

  Studies have indicated that water quality is degraded as a result of long residence times in storage tanks, highlighting the importance of tank design, location, and operation. Computer models, developed to explain some of the mixing and distrribution issues associated with tank...

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

  EPA Science Inventory

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

APPLICATION OF A WATER QUALITY ASSESSMENT MODELING SYSTEM AT A SUPERFUND SITE

EPA Science Inventory

Water quality modeling and related exposure assessments at a Superfund site, Silver Bow Creek-Clark Fork River in Montana, demonstrate the capability to predict the fate of mining waste pollutants in the environment. inked assessment system--consisting of hydrology and erosion, r...

Storm Water Management Model Reference Manual Volume III – Water Quality

EPA Science Inventory

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...

Optimising The Available Scarce Water Resources At European Scale In A Modelling Environment: Results And Challenges

NASA Astrophysics Data System (ADS)

de Roo, Ad; Burek, Peter; Gentile, Alessandro; Udias, Angel; Bouraoui, Faycal

2013-04-01

As a next step to European drought monitoring and forecasting, which is covered in the European Drought Observatory (EDO) activity of JRC, a modeling environment has been developed to assess optimum measures to match water availability and water demand, while keeping ecological, water quality and flood risk aspects also into account. A multi-modelling environment has been developed to assess combinations of water retention measures, water savings measures, and nutrient reduction measures for continental Europe. These simulations have been carried out to assess the effects of those measures on several hydro-chemical indicators, such as the Water Exploitation Index, Environmental Flow indicators, low-flow frequency, N and P concentrations in rivers, the 50-year return period river discharge as an indicator for flooding, and economic losses due to water scarcity for the agricultural sector, the industrial sector, and the public sector. Also, potential flood damage of a 100-year return period flood has been used as an indicator. This modeling environment consists of linking the agricultural CAPRI model, the land use LUMP model, the water quantity LISFLOOD model, the water quality EPIC model, the combined water quantity/quality and hydro-economic LISQUAL model and a multi-criteria optimization routine. A python interface platform (IMO) has been built to link the different models. The work was carried out in the framework of a new European Commission policy document "Blueprint to Safeguard Europe's Water Resources", COM(2012)673), launched in November 2012. Simulations have been carried out to assess the effects of water retention measures, water savings measures, and nutrient reduction measures on several hydro-chemical indicators, such as the Water Exploitation Index, Environmental Flow indicators, N and P concentrations in rivers, the 50-year return period river discharge as an indicator for flooding, and economic losses due to water scarcity for the agricultural sector, the manufacturing-industry sector, the energy-production sector and the domestic sector. Also, potential flood damage of a 100-year return period flood has been used as an indicator. The study has shown that technically this modelling software environment can deliver optimum scenario combinations of packages of measures that improve various water quantity and water quality indicators, but that additional work is needed before final conclusions can be made using the tool. Further work is necessary, especially in the economic loss estimations, the water prices and price-elasticity, as well as the implementation and maintenance costs of individual scenarios. First results and challenges will be presented and discussed.

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

USGS Publications Warehouse

Lundgren, Robert F.; Nustad, Rochelle A.

2008-01-01

A time-of-travel and reaeration-rate study was conducted by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, the Minnesota Pollution Control Agency, and the cities of Fargo, North Dakota, and Moorhead, Minnesota, to provide information to calibrate a water-quality model for streamflows of less than 150 cubic feet per second. Data collected from September 24 through 27, 2003, were used to develop and calibrate the U.S. Environmental Protection Agency Water Quality Analysis Simulation Program model (hereinafter referred to as the Fargo WASP water-quality model) for a 19.2-mile reach of the Red River of the North. The Fargo WASP water-quality model was calibrated for the transport of dye by fitting simulated time-concentration dye curves to measured time-concentration dye curves. Simulated peak concentrations were within 10 percent of measured concentrations. Simulated traveltimes of the dye cloud centroid were within 7 percent of measured traveltimes. The variances of the simulated dye concentrations were similar to the variances of the measured dye concentrations, indicating dispersion was reproduced reasonably well. Average simulated dissolved-oxygen concentrations were within 6 percent of average measured concentrations. Average simulated ammonia concentrations were within the range of measured concentrations. Simulated dissolved-oxygen and ammonia concentrations were affected by the specification of a single nitrification rate in the Fargo WASP water-quality model. Data sets from August 1989 and August 1990 were used to test traveltime and simulation of dissolved oxygen and ammonia. For streamflows that ranged from 60 to 407 cubic feet per second, simulated traveltimes were within 7 percent of measured traveltimes. Measured dissolved-oxygen concentrations were underpredicted by less than 15 percent for both data sets. Results for ammonia were poor; measured ammonia concentrations were underpredicted by as much as 70 percent for both data sets. Overall, application of the Fargo WASP water-quality model to the 1989 and 1990 data sets resulted in poor agreement between measured and simulated concentrations. This likely is a result of changes in the waste-load composition for the Fargo and Moorhead wastewater-treatment plants as a result of improvements to the wastewater-treatment plants since 1990. The change in waste-load composition probably resulted in a change in decay rates and in dissolved oxygen no longer being substantially depressed downstream from the Moorhead and Fargo wastewater-treatment plants. The Fargo WASP water-quality model is valid for the current (2008) treatment processes at the wastewater-treatment plants.

Simulated effects of irrigation on salinity in the Arkansas River Valley in Colorado

USGS Publications Warehouse

Goff, K.; Lewis, M.E.; Person, M.A.; Konikow, Leonard F.

1998-01-01

Agricultural irrigation has a substantial impact on water quantity and quality in the lower Arkansas River valley of southeastern Colorado. A two-dimensional flow and solute transport model was used to evaluate the potential effects of changes in irrigation on the quantity and quality of water in the alluvial aquifer and in the Arkansas River along an 17.7 km reach of the fiver. The model was calibrated to aquifer water level and dissolved solids concentration data collected throughout the 24 year study period (197195). Two categories of irrigation management were simulated with the calibrated model: (1) a decrease in ground water withdrawals for irrigation; and (2) cessation of all irrigation from ground water and surface water sources. In the modeled category of decreased irrigation from ground water pumping, there was a resulting 6.9% decrease in the average monthly ground water salinity, a 0.6% decrease in average monthly river salinity, and an 11.1% increase in ground water return flows to the river. In the modeled category of the cessation of all irrigation, average monthly ground water salinity decreased by 25%; average monthly river salinity decreased by 4.4%; and ground water return flows to the river decreased by an average of 64%. In all scenarios, simulated ground water salinity decreased relative to historical conditions for about 12 years before reaching a new dynamic equilibrium condition. Aquifer water levels were not sensitive to any of the modeled scenarios. These potential changes in salinity could result in improved water quality for irrigation purposes downstream from the affected area.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

Maintaining water quality standards in highly urbanised hydrological catchments is a worldwide challenge. Water management authorities struggle to cope with changing climate and an increase in pollution pressures. Water quality modelling has been used as a decision support tool for investment and regulatory developments. This approach led to the development of integrated catchment models (ICM), which account for the link between the urban/rural hydrology and the in-river pollutant dynamics. In the modelled system, rainfall triggers the drainage systems of urban areas scattered along a river. When flow exceeds the sewer infrastructure capacity, untreated wastewater enters the natural system by combined sewer overflows. This results in a degradation of the river water quality, depending on the magnitude of the emission and river conditions. Thus, being capable of representing these dynamics in the modelling process is key for a correct assessment of the water quality. In many urbanised hydrological systems the distances between draining sewer infrastructures go beyond the de-correlation length of rainfall processes, especially, for convective summer storms. Hence, spatial and temporal scales of selected rainfall inputs are expected to affect water quality dynamics. The objective of this work is to evaluate how the use of rainfall data from different sources and with different space-time characteristics affects modelled output concentrations of dissolved oxygen in a simplified ICM. The study area is located at the Dommel, a relatively small and sensitive river flowing through the city of Eindhoven (The Netherlands). This river stretch receives the discharge of the 750,000 p.e. WWTP of Eindhoven and from over 200 combined sewer overflows scattered along its length. A pseudo-distributed water quality model has been developed in WEST (mikedhi.com); this is a lumped-physically based model that accounts for urban drainage processes, WWTP and river dynamics for several pollutant typologies. Different rainfall products are tested: 1) Block kriging of a single reliable rain gauge, 2) Block kriging product from a network of 13 rain gauges and, 3) Universal block kriging with 13 rain gauges and KNMI weather radar estimates as a covariate. Different temporal accumulation levels are compared ranging from 10min to 1h. A geostatistical approach is used to allocate the prediction of the rainfall input in each of the urban hydrological units composing the model. The change in model performance is then assessed by contrasting it with dissolved oxygen monitoring data in a series of events.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

NASA Astrophysics Data System (ADS)

Booth, N. L.; Everman, E.; Kuo, I.; Sprague, L.; Murphy, L.

2011-12-01

A new web-based decision support system has been developed as part of the U.S. Geological Survey (USGS) National Water Quality Assessment Program's (NAWQA) effort to provide ready access to Spatially Referenced Regressions On Watershed attributes (SPARROW) results of stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via an intuitive graphical user interface with a map-based display. The SPARROW Decision Support System (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions, distribution of nutrient sources, nutrient delivery to downstream waterbodies, and simulations of altered nutrient inputs including atmospheric and agricultural sources. The DSS offers other features for analysis including various background map layers, model output exports, and the ability to save and share prediction scenarios. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. The underlying modeling framework and server infrastructure illustrate innovations in the information technology and geosciences fields for delivering SPARROW model predictions over the web by performing intensive model computations and map visualizations of the predicted conditions within the stream network.

Linked Hydrologic-Hydrodynamic Model Framework to Forecast Impacts of Rivers on Beach Water Quality

NASA Astrophysics Data System (ADS)

Anderson, E. J.; Fry, L. M.; Kramer, E.; Ritzenthaler, A.

2014-12-01

The goal of NOAA's beach quality forecasting program is to use a multi-faceted approach to aid in detection and prediction of bacteria in recreational waters. In particular, our focus has been on the connection between tributary loads and bacteria concentrations at nearby beaches. While there is a clear link between stormwater runoff and beach water quality, quantifying the contribution of river loadings to nearshore bacterial concentrations is complicated due to multiple processes that drive bacterial concentrations in rivers as well as those processes affecting the fate and transport of bacteria upon exiting the rivers. In order to forecast potential impacts of rivers on beach water quality, we developed a linked hydrologic-hydrodynamic water quality framework that simulates accumulation and washoff of bacteria from the landscape, and then predicts the fate and transport of washed off bacteria from the watershed to the coastal zone. The framework includes a watershed model (IHACRES) to predict fecal indicator bacteria (FIB) loadings to the coastal environment (accumulation, wash-off, die-off) as a function of effective rainfall. These loadings are input into a coastal hydrodynamic model (FVCOM), including a bacteria transport model (Lagrangian particle), to simulate 3D bacteria transport within the coastal environment. This modeling system provides predictive tools to assist local managers in decision-making to reduce human health threats.

Impacts of changes in water quality on recreation behavior and benefits in Finland.

PubMed

Vesterinen, J; Pouta, E; Huhtala, A; Neuvonen, M

2010-01-01

The implementation of the European Union Water Framework Directive (WFD) requires nationally generalizable estimates of the benefits of protecting inland and coastal waters. As an alternative to benefit transfers and meta-analyses, we utilize national recreation inventory data combined with water quality data to model recreation participation and estimate the benefits of water quality improvements. Using hurdle models, we analyze the association of water clarity in individuals' home municipalities with the three most common water recreation activities--swimming, fishing and boating. The results show no effect on boating, but improved water clarity would increase the frequency of close-to-home swimming and fishing, as well as the number of fishers. Furthermore, to value the potential benefits of the WFD, we estimate the consumer surplus of a water recreation day using a travel cost approach. A water policy scenario with a 1-m improvement in water clarity for both inland and coastal waters indicates that the consumer surplus would increase 6% for swimmers and 15% for fishers. In contrast to previously estimated abatement costs to improve water quality, net benefits could turn out to be positive. Our study is a promising example of applying existing national recreation inventory data to estimate the benefits of water quality improvements for the purposes of the WFD. Copyright 2009 Elsevier Ltd. All rights reserved.

Development and application of the microbial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

NASA Astrophysics Data System (ADS)

Hong, E.; Park, Y.; Muirhead, R.; Jeong, J.; Pachepsky, Y. A.

2017-12-01

Pathogenic microorganisms in recreational and irrigation waters remain the subject of concern. Water quality models are used to estimate microbial quality of water sources, to evaluate microbial contamination-related risks, to guide the microbial water quality monitoring, and to evaluate the effect of agricultural management on the microbial water quality. The Agricultural Policy/Environmental eXtender (APEX) is the watershed-scale water quality model that includes highly detailed representation of agricultural management. The APEX currently does not have microbial fate and transport simulation capabilities. The objective of this work was to develop the first APEX microbial fate and transport module that could use the APEX conceptual model of manure removal together with recently introduced conceptualizations of the in-stream microbial fate and transport. The module utilizes manure erosion rates found in the APEX. Bacteria survival in soil-manure mixing layer was simulated with the two-stage survival model. Individual survival patterns were simulated for each manure application date. Simulated in-stream microbial fate and transport processes included the reach-scale passive release of bacteria with resuspended bottom sediment during high flow events, the transport of bacteria from bottom sediment due to the hyporheic exchange during low flow periods, the deposition with settling sediment, and the two-stage survival. Default parameter values were available from recently published databases. The APEX model with the newly developed microbial fate and transport module was applied to simulate seven years of monitoring data for the Toenepi watershed in New Zealand. Based on calibration and testing results, the APEX with the microbe module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water under various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.

Modeling Study of the Marano and Grado Lagoon (Italy) to Support the Regional Water Protection Plan) TO SUPPORT THE REGIONAL WATER PROTECTION PLAN

NASA Astrophysics Data System (ADS)

Scroccaro, Isabella; Mattassi, Giorgio

2014-05-01

The Water Framework Directive 2000/60/EC (WFD) contemplates the classification of water bodies and establishes the quality objectives of water bodies to achieve a good status within 2015. Further, the Italian law which takes in the WFD with Decree n. 152/2006, allows to identify some water bodies as heavily modified (HMWB). The Regional Administration, involved in the setting up of the Water Protection Plan, according with the above mentioned decree and directive, has to establish specific programs to maintain or conform water quality to the requested quality objectives, also for heavily modified water bodies that have to reach the ecological potential. In the north-eastern part of Italy, in the Friuli Venezia Giulia Region, the Marano and Grado Lagoon is the most complex transitional ecosystem in which four water bodies have been temporarily classified as heavily modified. They are identified as FM1, FM2, FM3 and FM4. In particular, FM2 - "Paludo della Carogna" and FM3 - "Barbana" water bodies seem to be characterized by some confinement since they are delimited by a bridge, called "Ponte Belvedere". The preliminary evaluation of the quality status of FM2 and FM3 water bodies is conditioned by the value of one of the quality criteria: the macrophytes. In fact, macrophytes are represented by very few species in these two water bodies. In a preliminary way the overall judgement of FM2 and FM3 water bodies has been indicated by the experts as scarse. This means that a specific programme of measures has to be proposed to improve the quality status of these water bodies in order to reach the ecological potential. In this context modeling may be used as a scientific and technical tool to support the evaluation on FM2 and FM3 water bodies and the effectiveness of specific measures for the achievement of the quality objectives. Numerical simulations of the Marano and Grado lagoon were performed for hydrodynamic circulation, temperature and salinity behavior with the SHYFEM model, a shallow water finite element model developed at ISMAR-CNR in Venice (Ferrarin et al., 2010) and experimental data were used to calibrate the numerical model. In this study the effectiveness of some proposed measures is investigated with the SHYFEM model, trying to solve the problem of the scarse quality evaluation of FM2 and FM3 in the eastern part of the Marano and Grado lagoon. The proposals are: Modification of the bridge "Ponte Belvedere": the bridge, which divides FM2 and FM3 from the western part of the lagoon, has some openings which are not very large. The proposal is to enlarge these openings on the dam to assess if this action might improve the circulation and consequently the water quality. Excavation of a new channel on the bottom of the lagoon: besides the openings on the dam, it is also possible to hypothetically excavate one or more channels; these are preferential ways for the water to pass in and arrive to the areas in which the circulation has to be increased. This proposal seems to be efficient, with good effects on the inner circulation of the eastern lagoon.

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

NASA Astrophysics Data System (ADS)

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 pollution diet in light of future projections for air temperature, sea level, and precipitation was examined. While a changing climate will reduce the ability of the nutrient reduction to improve oxygen concentrations, that effect is trumped by the improvements in dissolved oxygen stemming from the pollution diet itself. However, climate change still has the potential to cause the current level of nutrient reduction to be inadequate. This is primarily due to the fact that low-oxygen conditions are predicted to start one week earlier, on average, in the future, with the primary changes resulting from the increase in temperature. Overall, this research lends an increased degree of confidence in the water quality modeling of the potential impact of the Chesapeake Bay pollution diet. This research also establishes the efficacy of utilizing a multiple model approach to examining projected changes in water quality while establishing that the pollution diet trumps the impact from climate change. This work will lead directly to advances in scientific understanding of the response of water quality, ecosystem health, and ecological resilience to the impacts of nutrient reduction and climate change.

Hydrology and water quality of a field and riparian buffer adjacent to a mangrove wetland in Jobos Bay Watershed, Puerto Rico

USDA-ARS?s Scientific Manuscript database

Models that estimate the effects of agricultural conservation practices on water quantity and quality have become increasingly important tools for short- and long-term assessments. In this study, we simulated the water quality and hydrology of a portion of the Jobos Bay watershed, Puerto Rico using...

The nematode Caenorhabditis elegans as an integrated toxicological tool to assess water quality and pollution.

PubMed

Clavijo, Araceli; Kronberg, María Florencia; Rossen, Ariana; Moya, Aldana; Calvo, Daniel; Salatino, Santa Esmeralda; Pagano, Eduardo Antonio; Morábito, José Antonio; Munarriz, Eliana Rosa

2016-11-01

Determination of water quality status in rivers is critical to establish a sustainable water management policy. For this reason, over the last decades it has been recommended to perform integrated water assessments that include water quantities and physicochemical, ecological and toxicological tests. However, sometimes resources are limited and it is not possible to perform large-scale chemical determinations of pollutants or conduct numerous ecotoxicological tests. To overcome this problem we use and measure the growth, as a response parameter, of the soil nematode Caenorhabditis elegans to assess water quality in rivers. The C. elegans is a ubiquitous organism that has emerged as an important model organism in aquatic and soil toxicology research. The Tunuyán River Basin (Province of Mendoza, Argentina) has been selected as a representative traditional water monitoring system to test the applicability of the C. elegans toxicological bioassay to generate an integrated water quality evaluation. Jointly with the C. elegans toxic assays, physicochemical and bacteriological parameters were determined for each monitoring site. C. elegans bioassays help to identify different water qualities in the river basin. Multivariate statistical analysis (PCA and linear regression models) has allowed us to confirm that traditional water quality studies do not predict potential toxic effects on living organisms. On the contrary, physicochemical and bacteriological analyzes explain <62% of the C. elegans growth response variability, showing that ecotoxicological bioassays are important to obtain a realistic scenario of water quality threats. Our results confirm that the C. elegans bioassay is a sensible and suitable tool to assess toxicity and should be implemented in routine water quality monitoring. Copyright © 2016 Elsevier B.V. All rights reserved.

A review of distributed parameter groundwater management modeling methods

USGS Publications Warehouse

Gorelick, Steven M.

1983-01-01

Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

A Review of Distributed Parameter Groundwater Management Modeling Methods

NASA Astrophysics Data System (ADS)

Gorelick, Steven M.

1983-04-01

Models which solve the governing groundwater flow or solute transport equations in conjunction with optimization techniques, such as linear and quadratic programing, are powerful aquifer management tools. Groundwater management models fall in two general categories: hydraulics or policy evaluation and water allocation. Groundwater hydraulic management models enable the determination of optimal locations and pumping rates of numerous wells under a variety of restrictions placed upon local drawdown, hydraulic gradients, and water production targets. Groundwater policy evaluation and allocation models can be used to study the influence upon regional groundwater use of institutional policies such as taxes and quotas. Furthermore, fairly complex groundwater-surface water allocation problems can be handled using system decomposition and multilevel optimization. Experience from the few real world applications of groundwater optimization-management techniques is summarized. Classified separately are methods for groundwater quality management aimed at optimal waste disposal in the subsurface. This classification is composed of steady state and transient management models that determine disposal patterns in such a way that water quality is protected at supply locations. Classes of research missing from the literature are groundwater quality management models involving nonlinear constraints, models which join groundwater hydraulic and quality simulations with political-economic management considerations, and management models that include parameter uncertainty.

Water quality and relation to taste-and-odor compounds in North Fork Ninnescah River and Cheney Reservoir, south-central Kansas, 1997-2003

USGS Publications Warehouse

Christensen, Victoria G.; Graham, Jennifer L.; Milligan, Chad R.; Pope, Larry M.; Ziegler, Andrew C.

2006-01-01

Regression models were developed between geosmin and the physical property measurements continuously recorded by water-quality monitors at each site. The geosmin regression model was applied to water-quality monitor measurements, providing a continuous estimate of geosmin for 2003. The city of Wichita will be able to use this type of analysis to determine the probability of when concentrations of geosmin are likely to be at or above the human detection level of 0.01 microgram per liter.

MODELING THE IMPACTS OF FIRE FLOWS ON DISTRIBUTION SYSTEM WATER QUALITY, DESIGN AND OPERATION

EPA Science Inventory

In most water distribution systems, a significant amount of the piping and storage capacity is used to provide adequate quantities of water during fire conditions. This increased capacity results in higher capital costs and potential negative impacts on water quality due to longe...

Climate Adaptation Capacity for Conventional Drinking Water Treatment Facilities

NASA Astrophysics Data System (ADS)

Levine, A.; Goodrich, J.; Yang, J.

2013-12-01

Water supplies are vulnerable to a host of climate- and weather-related stressors such as droughts, intense storms/flooding, snowpack depletion, sea level changes, and consequences from fires, landslides, and excessive heat or cold. Surface water resources (lakes, reservoirs, rivers, and streams) are especially susceptible to weather-induced changes in water availability and quality. The risks to groundwater systems may also be significant. Typically, water treatment facilities are designed with an underlying assumption that water quality from a given source is relatively predictable based on historical data. However, increasing evidence of the lack of stationarity is raising questions about the validity of traditional design assumptions, particularly since the service life of many facilities can exceed fifty years. Given that there are over 150,000 public water systems in the US that deliver drinking water to over 300 million people every day, it is important to evaluate the capacity for adapting to the impacts of a changing climate. Climate and weather can induce or amplify changes in physical, chemical, and biological water quality, reaction rates, the extent of water-sediment-air interactions, and also impact the performance of treatment technologies. The specific impacts depend on the watershed characteristics and local hydrological and land-use factors. Water quality responses can be transient, such as erosion-induced increases in sediment and runoff. Longer-term impacts include changes in the frequency and intensity of algal blooms, gradual changes in the nature and concentration of dissolved organic matter, dissolved solids, and modulation of the microbiological community structure, sources and survival of pathogens. In addition, waterborne contaminants associated with municipal, industrial, and agricultural activities can also impact water quality. This presentation evaluates relationships between climate and weather induced water quality variability and the capacity of treatment facilities and supporting water infrastructure to deliver safe drinking water consistently and reliably. Simulation models of water treatment facilities are used to evaluate the outcome of specific source water quality scenarios on treatment system performance and reliability. Modeling results are used to evaluate the process and operational capacity to respond to transient water quality changes and adapt to longer-term variability in water quality and availability. In some cases, changes in temperature and mineral content serve to improve the overall treatment performance. In addition, the integration of microbially enhanced treatment systems such as biological filtration can provide additional capacity. Conversely, changes in the nutrient and temperature dynamics can trigger algal and cyanobacterial blooms that can impair performance. Research needs are identified and the importance of developing more integrated modeling systems is highlighted.

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

USGS Publications Warehouse

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

2011-01-01

A hydrodynamic, water temperature, and water-quality model was constructed for a 20-mile reach of the Klamath River downstream of Upper Klamath Lake, from Link River to Keno Dam, for calendar years 2006-09. The two-dimensional, laterally averaged model CE-QUAL-W2 was used to simulate water velocity, ice cover, water temperature, specific conductance, dissolved and suspended solids, dissolved oxygen, total nitrogen, ammonia, nitrate, total phosphorus, orthophosphate, dissolved and particulate organic matter, and three algal groups. The Link-Keno model successfully simulated the most important spatial and temporal patterns in the measured data for this 4-year time period. The model calibration process provided critical insights into water-quality processes and the nature of those inputs and processes that drive water quality in this reach. The model was used not only to reproduce and better understand water-quality conditions that occurred in 2006-09, but also to test several load-reduction scenarios that have implications for future water-resources management in the river basin. The model construction and calibration process provided results concerning water quality and transport in the Link-Keno reach of the Klamath River, ranging from interesting circulation patterns in the Lake Ewauna area to the nature and importance of organic matter and algae. These insights and results include: * Modeled segment-average water velocities ranged from near 0.0 to 3.0 ft/s in 2006 through 2009. Travel time through the model reach was about 4 days at 2,000 ft3/s and 12 days at 700 ft3/s flow. Flow direction was aligned with the upstream-downstream channel axis for most of the Link-Keno reach, except for Lake Ewauna. Wind effects were pronounced at Lake Ewauna during low-flow conditions, often with circulation in the form of a gyre that rotated in a clockwise direction when winds were towards the southeast and in a counterclockwise direction when winds were towards the northwest. * Water temperatures ranged from near freezing in winter to near 30 degrees C at some locations and periods in summer; seasonal water temperature patterns were similar at the inflow and outflow. Although vertical temperature stratification was not present at most times and locations, weak stratification could persist for periods up to 1-2 weeks, especially in the downstream parts of the reach. Thermal stratification was important in controlling vertical variations in water quality. * The specific conductance, and thus density, of tributaries within the reach usually was higher than that of the river itself, so that inflows tended to sink below the river surface. This was especially notable for inflows from the Klamath Straits Drain, which tended to sink to the bottom of the Klamath River at its confluence and not mix vertically for several miles downstream. * The model was able to capture most of the seasonal changes in the algal population by modeling that population with three algal groups: blue-green algae, diatoms, and other algae. The blooms of blue-green algae, consisting mostly of Aphanizomenon flos aquae that entered from Upper Klamath Lake, were dominant, dwarfing the populations of the other two algae groups in summer. A large part of the blue-green algae population that entered this reach from upstream tended to settle out, die, and decompose, especially in the upper part of the Link-Keno reach. Diatoms reached a maximum in spring and other algae in midsummer. * Organic matter, occurring in both dissolved and particulate forms, was critical to the water quality of this reach of the Klamath River, and was strongly tied to nutrient and dissolved-oxygen dynamics. Dissolved and particulate organic matter were subdivided into labile (quickly decaying) and refractory (slowing decaying) groups for modeling purposes. The particulate matter in summer, consisting largely of dead blue-green algae, decayed quickly. Consequently, this particulate matt

The impact of water quality in Narragansett Bay on housing prices

NASA Astrophysics Data System (ADS)

Liu, Tingting; Opaluch, James J.; Uchida, Emi

2017-08-01

We examine the impact of water quality in Narragansett Bay on housing prices in coastal towns and cities using a hedonic housing-price model. Unlike other hedonic studies of water quality, we test whether housing market responds to average water quality or more to extreme events. We also test the spatial and temporal extent of effects of water quality on housing prices. We find that poor coastal water quality, measured in terms of the concentration of chlorophyll, has a negative impact on housing prices that diminishes with distance from the shoreline. Furthermore, our finding suggests that housing prices are most influenced by the extreme environmental conditions, which may be accompanied by unpleasant odors, discoloration, and even fish kills. We further predict potential increases in home values associated under water quality improvement scenarios and find an increase in the values of homes in coastal communities along Narragansett Bay of about 18 million up to 136 million.

Development of a regional ocean color algorithm using field- and satellite-derived datasets: Long Bay, South Carolina

NASA Astrophysics Data System (ADS)

Ryan, Kimberly Susan

Coastal and inland waters represent a diverse set of resources that support natural habitat and provide numerous ecosystem services to the human population. Conventional techniques to monitor water quality using in situ sensors and laboratory analysis of water samples can be very time- and cost-intensive. Alternatively, remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic and unique water quality parameters. However, bio and geo-optical models are required that relate the remotely sensed spectral data with color producing agents (CPAs) that define the water quality. These CPAs include chlorophyll-a, suspended sediments, and colored-dissolved organic matter. Developing these models may be challenging for coastal environments such as Long Bay, South Carolina, due to the presence of multiple optically interfering CPAs. In this work, a regionally tiered ocean color model was developed using band ratio techniques to specifically predict the variability of chlorophyll-a concentrations in the turbid Long Bay waters. This model produced higher accuracy results (r-squared = 0.62; RMSE = 0.87 micrograms per liter) compared to the existing models, which gave a highest r-squared value of 0.58 and RMSE = 0.99 micrograms per liter. To further enhance the retrievals of chlorophyll-a in these optically complex waters, a novel multivariate-based approach was developed using current generation hyperspectral data. This approach uses a partial least-squares regression model to identify wavelengths that are more sensitive to chlorophyll-a relative to other associated CPAs. This model was able to explain 80% of the observed chlorophyll-a variability in Long Bay with RMSE = 2.03 micrograms per liter. This approach capitalizes on the spectral advantage gained from hyperspectral sensors, thus providing a more robust predicting model. This enhanced mode of water quality monitoring in marine environments will provide insight to point-sources and problem areas that may contribute to a decline in water quality. Moreover, remote sensing applications such as this can be used as a tool for coastal and fisheries managers with regard to recreation, regulation, economic and public health purposes.

Assessing the Challenges Associated with Developing an Integrated Modeling Approach for Predicting and Managing Water Quality and Quantity from the Watershed through the Drinking Water Treatment System

EPA Science Inventory

Natural and Engineered water systems interact throughout watersheds (e.g., at water intakes, wastewater outfalls and water pipe breaks of all kinds), and while there is clearly a link between watershed activities and the quality of water entering the engineered environment, surfa...

Spatial and temporal variations in the relationship between lake water surface temperatures and water quality - A case study of Dianchi Lake.

PubMed

Yang, Kun; Yu, Zhenyu; Luo, Yi; Yang, Yang; Zhao, Lei; Zhou, Xiaolu

2018-05-15

Global warming and rapid urbanization in China have caused a series of ecological problems. One consequence has involved the degradation of lake water environments. Lake surface water temperatures (LSWTs) significantly shape water ecological environments and are highly correlated with the watershed ecosystem features and biodiversity levels. Analysing and predicting spatiotemporal changes in LSWT and exploring the corresponding impacts on water quality is essential for controlling and improving the ecological water environment of watersheds. In this study, Dianchi Lake was examined through an analysis of 54 water quality indicators from 10 water quality monitoring sites from 2005 to 2016. Support vector regression (SVR), Principal Component Analysis (PCA) and Back Propagation Artificial Neural Network (BPANN) methods were applied to form a hybrid forecasting model. A geospatial analysis was conducted to observe historical LSWTs and water quality changes for Dianchi Lake from 2005 to 2016. Based on the constructed model, LSWTs and changes in water quality were simulated for 2017 to 2020. The relationship between LSWTs and water quality thresholds was studied. The results show limited errors and highly generalized levels of predictive performance. In addition, a spatial visualization analysis shows that from 2005 to 2020, the chlorophyll-a (Chla), chemical oxygen demand (COD) and total nitrogen (TN) diffused from north to south and that ammonia nitrogen (NH 3 -N) and total phosphorus (TP) levels are increases in the northern part of Dianchi Lake, where the LSWT levels exceed 17°C. The LSWT threshold is 17.6-18.53°C, which falls within the threshold for nutritional water quality, but COD and TN levels fall below V class water quality standards. Transparency (Trans), COD, biochemical oxygen demand (BOD) and Chla levels present a close relationship with LSWT, and LSWTs are found to fundamentally affect lake cyanobacterial blooms. Copyright © 2017 Elsevier B.V. All rights reserved.

Variation of Water Quality Parameters with Siltation Depth for River Ichamati Along International Border with Bangladesh Using Multivariate Statistical Techniques

NASA Astrophysics Data System (ADS)

Roy, P. K.; Pal, S.; Banerjee, G.; Biswas Roy, M.; Ray, D.; Majumder, A.

2014-12-01

River is considered as one of the main sources of freshwater all over the world. Hence analysis and maintenance of this water resource is globally considered a matter of major concern. This paper deals with the assessment of surface water quality of the Ichamati river using multivariate statistical techniques. Eight distinct surface water quality observation stations were located and samples were collected. For the samples collected statistical techniques were applied to the physico-chemical parameters and depth of siltation. In this paper cluster analysis is done to determine the relations between surface water quality and siltation depth of river Ichamati. Multiple regressions and mathematical equation modeling have been done to characterize surface water quality of Ichamati river on the basis of physico-chemical parameters. It was found that surface water quality of the downstream river was different from the water quality of the upstream. The analysis of the water quality parameters of the Ichamati river clearly indicate high pollution load on the river water which can be accounted to agricultural discharge, tidal effect and soil erosion. The results further reveal that with the increase in depth of siltation, water quality degraded.

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

USDA-ARS?s Scientific Manuscript database

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...

Impact of Rainfall Data Source on Hydrologic and Water Quality Model Response of a Coastal Plain Watershed

USDA-ARS?s Scientific Manuscript database

Hydrologic and water quality models are very sensitive to input parameter values, especially precipitation input data. With several different sources of precipitation data now available, it is quite difficult to determine which source is most appropriate under various circumstances. We used several ...

LUMINATE: Linking agricultural land use, local water quality and Gulf of Mexico hypoxia

USDA-ARS?s Scientific Manuscript database

In this paper, we discuss the importance of developing integrated assessment models to support the design and implementation of policies to address water quality problems associated with agricultural pollution. We describe a new modelling system, LUMINATE, which links land use decisions made at the...

Simulation of Management Effect on Runoff and Sediment Transport in Riparian Forest Buffers by APEX Model

USDA-ARS?s Scientific Manuscript database

Hydrologic/water quality models are increasingly used to explore management and policy alternatives for managing water quality and quantity from intensive silvicultural practices with Best Management Practices (BMPs) in forested watersheds due to the limited number of studies and the cost of conduct...

EUTROPHICATION MODELING CAPABILITIES FOR WATER QUALITY AND INTEGRATION TOWARDS ECOLOGICAL ENDPOINTS

EPA Science Inventory

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...

Comparisons of Historical versus Synthetic Weather Inputs to Watershed Models and their Effect on Pollutant Loads

USDA-ARS?s Scientific Manuscript database

Synthetic weather generators are important for continuous-simulation of agricultural watersheds for risk analyses of downstream water quality. Many watersheds are sparsely or totally ungauged and daily weather must either be transposed or augmented. Since water quality models must recognize runoff...

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

USGS Publications Warehouse

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 model 6136 sensor at the Cheney Reservoir site. Because a high percentage of geosmin and microcystin data were below analytical detection thresholds (censored data), multiple logistic regression was used to develop models that best explained the probability of geosmin and microcystin concentrations exceeding relevant thresholds. The geosmin and microcystin models are particularly important because geosmin is a taste-and-odor compound and microcystin is a cyanotoxin.

Using a Data-Driven Approach to Understand the Interaction between Catchment Characteristics and Water Quality Responses

NASA Astrophysics Data System (ADS)

Western, A. W.; Lintern, A.; Liu, S.; Ryu, D.; Webb, J. A.; Leahy, P.; Wilson, P.; Waters, D.; Bende-Michl, U.; Watson, M.

2016-12-01

Many streams, lakes and estuaries are experiencing increasing concentrations and loads of nutrient and sediments. Models that can predict the spatial and temporal variability in water quality of aquatic systems are required to help guide the management and restoration of polluted aquatic systems. We propose that a Bayesian hierarchical modelling framework could be used to predict water quality responses over varying spatial and temporal scales. Stream water quality data and spatial data of catchment characteristics collected throughout Victoria and Queensland (in Australia) over two decades will be used to develop this Bayesian hierarchical model. In this paper, we present the preliminary exploratory data analysis required for the development of the Bayesian hierarchical model. Specifically, we present the results of exploratory data analysis of Total Nitrogen (TN) concentrations in rivers in Victoria (in South-East Australia) to illustrate the catchment characteristics that appear to be influencing spatial variability in (1) mean concentrations of TN; and (2) the relationship between discharge and TN throughout the state. These important catchment characteristics were identified using: (1) monthly TN concentrations measured at 28 water quality gauging stations and (2) climate, land use, topographic and geologic characteristics of the catchments of these 28 sites. Spatial variability in TN concentrations had a positive correlation to fertiliser use in the catchment and average temperature. There were negative correlations between TN concentrations and catchment forest cover, annual runoff, runoff perenniality, soil erosivity and catchment slope. The relationship between discharge and TN concentrations showed spatial variability, possibly resulting from climatic and topographic differences between the sites. The results of this study will feed into the hierarchical Bayesian model of river water quality.

Trend analysis of a tropical urban river water quality in Malaysia.

PubMed

Othman, Faridah; M E, Alaa Eldin; Mohamed, Ibrahim

2012-12-01

Rivers play a significant role in providing water resources for human and ecosystem survival and health. Hence, river water quality is an important parameter that must be preserved and monitored. As the state of Selangor and the city of Kuala Lumpur, Malaysia, are undergoing tremendous development, the river is subjected to pollution from point and non-point sources. The water quality of the Klang River basin, one of the most densely populated areas within the region, is significantly degraded due to human activities as well as urbanization. Evaluation of the overall river water quality status is normally represented by a water quality index (WQI), which consists of six parameters, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen and pH. The objectives of this study are to assess the water quality status for this tropical, urban river and to establish the WQI trend. Using monthly WQI data from 1997 to 2007, time series were plotted and trend analysis was performed by employing the first-order autocorrelated trend model on the moving average values for every station. The initial and final values of either the moving average or the trend model were used as the estimates of the initial and final WQI at the stations. It was found that Klang River water quality has shown some improvement between 1997 and 2007. Water quality remains good in the upper stream area, which provides vital water sources for water treatment plants in the Klang valley. Meanwhile, the water quality has also improved in other stations. Results of the current study suggest that the present policy on managing river quality in the Klang River has produced encouraging results; the policy should, however, be further improved alongside more vigorous monitoring of pollution discharge from various point sources such as industrial wastewater, municipal sewers, wet markets, sand mining and landfills, as well as non-point sources such as agricultural or urban runoff and commercial activity.

Simulation of Surface-Water Conditions in the Nontidal Passaic River Basin, New Jersey

USGS Publications Warehouse

Spitz, Frederick J.

2007-01-01

The Passaic River Basin, the third largest drainage basin in New Jersey, encompasses 950 mi2 (square miles) in the highly urbanized area outside New York City, with a population of 2 million. Water quality in the basin is affected by many natural and anthropogenic factors. Nutrient loading to the Wanaque Reservoir in the northern part of the basin is of particular concern and is caused partly by the diversion of water at two downstream intakes that is transferred back upstream to refill the reservoir. The larger of these diversions, Wanaque South intake, is on the lower Pompton River near Two Bridges, New Jersey. To support the development of a Total Maximum Daily Load (TMDL) for nutrients in the nontidal part of the basin (805 mi2), a water-quality transport model was needed. The U.S. Geological Survey, in cooperation with the New Jersey Department of Environmental Protection and New Jersey EcoComplex, developed a flow-routing model to provide the hydraulic inputs to the water-quality model. The Diffusion Analogy Flow model (DAFLOW) described herein was designed for integration with the Water Quality Analysis Simulation Program (WASP) watershed water-quality model. The flow routing model was used to simulate flow in 108 miles of the Passaic River and major tributaries. Flow data from U.S. Geological Survey streamflow-gaging stations represent most of the model's upstream boundaries. Other model inputs include estimated flows for ungaged tributaries and unchanneled drainage along the mainstem, and reported flows for major point-source discharges and diversions. The former flows were calibrated using the drainage-area ratio method. The simulation extended over a 4+ year period representing a range in flow conditions. Simulated channel cross-sectional geometry in the DAFLOW model was calibrated using several different approaches by adjusting area and top width parameters. The model also was calibrated to observed flows for water year 2001 (low flow) at five mainstem gaging stations and one station at which flow was estimated. The model's target range was medium to low flows--the range of typical intake operations. Simulated flow mass balance, hydrographs (flood-wave speed, attenuation, and spread), flow-duration curves, and velocity and depth values were compared to observed counterparts. Mass balance and hydrograph fit were evaluated quantitatively. Simulation results generally were within the accuracy of the flow data at the measurement stations. The model was validated to observed flows for water years 2000 (average flow), 2002 (extreme low flow), and 2003 (high flow). Results for 19 of 20 comparisons indicate average mass-balance and model-fit errors of 6.6 and 15.7 percent, respectively, indicating that the model reasonably represents the time variation of streamflow in the nontidal Passaic River Basin. An algorithm (subroutine) also was developed for DAFLOW to simulate the hydraulic mixing that occurs near the Wanaque South intake upstream from the confluence of the Pompton and Passaic Rivers. The intake draws water from multiple sources, including effluent from a nearby wastewater-treatment plant, all of which have different phosphorus loads. The algorithm determines the proportion of flow from each source and operates within a narrow flow range. The equations used in the algorithm are based on the theory of diffusion and lateral mixing in rivers. Parameters used in the equations were estimated from limited available local flow and water-quality data. As expected, simulation results for water years 2000, 2001, and 2003 indicate that most of the water drawn to the intake comes from the Pompton River; however, during many short periods of low flow and high diversion, particularly in water year 2002, entrainment of the other flow sources compensated for the insufficient flow in the Pompton River. As additional verification of the flow model used in the water-quality model, a Branched Lagrangian Transport Model (B

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

Treesearch

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...

Urban storm-runoff modelling; Madison, Wisconsin

USGS Publications Warehouse

Grant, R. Stephen; Goddard, Gerald

1979-01-01

A brief inconclusive evaluation of the water-quality subroutines of the model was made. Close agreement was noted between observed and simulated loads for nitrates, organic nitrogen, total phosphate, and total solids. Ammonia nitrogen and orthophosphate computed by the model ranged 7 to 11 times greater than the observed loads. Observed loads are doubtful because of the sparsity of water-quality data.

Simulation of water environmental capacity and pollution load reduction using QUAL2K for water environmental management.

PubMed

Zhang, Ruibin; Qian, Xin; Yuan, Xingcheng; Ye, Rui; Xia, Bisheng; Wang, Yulei

2012-12-07

In recent years, water quality degradation associated with rapid socio-economic development in the Taihu Lake Basin, China, has attracted increasing attention from both the public and the Chinese government. The primary sources of pollution in Taihu Lake are its inflow rivers and their tributaries. Effective water environmental management strategies need to be implemented in these rivers to improve the water quality of Taihu Lake, and to ensure sustainable development in the region. The aim of this study was to provide a basis for water environmental management decision-making. In this study, the QUAL2K model for river and stream water quality was applied to predict the water quality and environmental capacity of the Hongqi River, which is a polluted tributary in the Taihu Lake Basin. The model parameters were calibrated by trial and error until the simulated results agreed well with the observed data. The calibrated QUAL2K model was used to calculate the water environmental capacity of the Hongqi River, and the water environmental capacities of COD(Cr) NH(3)-N, TN, and TP were 17.51 t, 1.52 t, 2.74 t and 0.37 t, respectively. The results showed that the NH(3)-N, TN, and TP pollution loads of the studied river need to be reduced by 50.96%, 44.11%, and 22.92%, respectively to satisfy the water quality objectives. Thus, additional water pollution control measures are needed to control and reduce the pollution loads in the Hongqi River watershed. The method applied in this study should provide a basis for water environmental management decision-making.

Simulation of Water Environmental Capacity and Pollution Load Reduction Using QUAL2K for Water Environmental Management

PubMed Central

Zhang, Ruibin; Qian, Xin; Yuan, Xingcheng; Ye, Rui; Xia, Bisheng; Wang, Yulei

2012-01-01

In recent years, water quality degradation associated with rapid socio-economic development in the Taihu Lake Basin, China, has attracted increasing attention from both the public and the Chinese government. The primary sources of pollution in Taihu Lake are its inflow rivers and their tributaries. Effective water environmental management strategies need to be implemented in these rivers to improve the water quality of Taihu Lake, and to ensure sustainable development in the region. The aim of this study was to provide a basis for water environmental management decision-making. In this study, the QUAL2K model for river and stream water quality was applied to predict the water quality and environmental capacity of the Hongqi River, which is a polluted tributary in the Taihu Lake Basin. The model parameters were calibrated by trial and error until the simulated results agreed well with the observed data. The calibrated QUAL2K model was used to calculate the water environmental capacity of the Hongqi River, and the water environmental capacities of CODCr NH3-N, TN, and TP were 17.51 t, 1.52 t, 2.74 t and 0.37 t, respectively. The results showed that the NH3-N, TN, and TP pollution loads of the studied river need to be reduced by 50.96%, 44.11%, and 22.92%, respectively to satisfy the water quality objectives. Thus, additional water pollution control measures are needed to control and reduce the pollution loads in the Hongqi River watershed. The method applied in this study should provide a basis for water environmental management decision-making. PMID:23222206

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

PubMed

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

2018-04-01

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

Water quality and algal community dynamics of three deepwater lakes in Minnesota utilizing CE-QUAL-W2 models

USGS Publications Warehouse

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

2014-01-01

Water quality, habitat, and fish in Minnesota lakes will potentially be facing substantial levels of stress in the coming decades primarily because of two stressors: (1) land-use change (urban and agricultural) and (2) climate change. Several regional and statewide lake modeling studies have identified the potential linkages between land-use and climate change on reductions in the volume of suitable lake habitat for coldwater fish populations. In recent years, water-resource scientists have been making the case for focused assessments and monitoring of sentinel systems to address how these stress agents change lakes over the long term. Currently in Minnesota, a large-scale effort called “Sustaining Lakes in a Changing Environment” is underway that includes a focus on monitoring basic watershed, water quality, habitat, and fish indicators of 24 Minnesota sentinel lakes across a gradient of ecoregions, depths, and nutrient levels. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Department of Natural Resources, developed predictive water quality models to assess water quality and habitat dynamics of three select deepwater lakes in Minnesota. The three lakes (Lake Carlos in Douglas County, Elk Lake in Clearwater County, and Trout Lake in Cook County) were assessed under recent (2010–11) meteorological conditions. The three selected lakes contain deep, coldwater habitats that remain viable during the summer months for coldwater fish species. Hydrodynamics and water-quality characteristics for each of the three lakes were simulated using the CE-QUAL-W2 model, which is a carbon-based, laterally averaged, two-dimensional water-quality model. The CE-QUAL-W2 models address the interaction between nutrient cycling, primary production, and trophic dynamics to predict responses in the distribution of temperature and oxygen in lakes. The CE-QUAL-W2 models for all three lakes successfully predicted water temperature, on the basis of the two metrics of absolute mean error and root mean square error, using measured inputs of water temperature and nutrients. One of the main calibration tools for CE-QUAL-W2 model development was the vertical profile temperature data, available for all three lakes. For all three lakes, the absolute mean error and root mean square error were less than 1.0 degree Celsius and 1.2 degrees Celsius, respectively, for the different depth ranges used for vertical profile comparisons. In Lake Carlos, simulated water temperatures compared better to measured water temperatures in the epilimnion than in the hypolimnion. The reverse was true for the other two lakes, Elk Lake and Trout Lake, where the simulated results were slightly better for the hypolimnion than the epilimnion. The model also was used to approximate the location of the thermocline throughout the simulation periods, approximately April to November, in all three lake models. Deviations between the simulated and measured water temperatures in the vertical lake profile commonly were because of an offset in the timing of thermocline shifts rather than the simulated results missing thermocline shifts altogether.

An evaluation of the relative quality of dike pools for benthic macroinvertebrates in the Lower Missouri River, USA

USGS Publications Warehouse

Poulton, B.C.; Allert, A.L.

2012-01-01

A habitat-based aquatic macroinvertebrate study was initiated in the Lower Missouri River to evaluate relative quality and biological condition of dike pool habitats. Water-quality and sediment-quality parameters and macroinvertebrate assemblage structure were measured from depositional substrates at 18 sites. Sediment porewater was analysed for ammonia, sulphide, pH and oxidation-reduction potential. Whole sediments were analysed for particle-size distribution, organic carbon and contaminants. Field water-quality parameters were measured at subsurface and at the sediment-water interface. Pool area adjacent and downstream from each dike was estimated from aerial photography. Macroinvertebrate biotic condition scores were determined by integrating the following indicator response metrics: % of Ephemeroptera (mayflies), % of Oligochaeta worms, Shannon Diversity Index and total taxa richness. Regression models were developed for predicting macroinvertebrate scores based on individual water-quality and sediment-quality variables and a water/sediment-quality score that integrated all variables. Macroinvertebrate scores generated significant determination coefficients with dike pool area (R2=0.56), oxidation–reduction potential (R2=0.81) and water/sediment-quality score (R2=0.71). Dissolved oxygen saturation, oxidation-reduction potential and total ammonia in sediment porewater were most important in explaining variation in macroinvertebrate scores. The best two-variable regression models included dike pool size + the water/sediment-quality score (R2=0.84) and dike pool size + oxidation-reduction potential (R2=0.93). Results indicate that dike pool size and chemistry of sediments and overlying water can be used to evaluate dike pool quality and identify environmental conditions necessary for optimizing diversity and productivity of important aquatic macroinvertebrates. A combination of these variables could be utilized for measuring the success of habitat enhancement activities currently being implemented in this system.

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

USGS Publications Warehouse

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

2001-01-01

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

Numerical Simulation of Pollutants' Transport and Fate in AN Unsteady Flow in Lower Bear River, Box Elder County, Utah

NASA Astrophysics Data System (ADS)

Salha, A. A.; Stevens, D. K.

2013-12-01

This study presents numerical application and statistical development of Stream Water Quality Modeling (SWQM) as a tool to investigate, manage, and research the transport and fate of water pollutants in Lower Bear River, Box elder County, Utah. The concerned segment under study is the Bear River starting from Cutler Dam to its confluence with the Malad River (Subbasin HUC 16010204). Water quality problems arise primarily from high phosphorus and total suspended sediment concentrations that were caused by five permitted point source discharges and complex network of canals and ducts of varying sizes and carrying capacities that transport water (for farming and agriculture uses) from Bear River and then back to it. Utah Department of Environmental Quality (DEQ) has designated the entire reach of the Bear River between Cutler Reservoir and Great Salt Lake as impaired. Stream water quality modeling (SWQM) requires specification of an appropriate model structure and process formulation according to nature of study area and purpose of investigation. The current model is i) one dimensional (1D), ii) numerical, iii) unsteady, iv) mechanistic, v) dynamic, and vi) spatial (distributed). The basic principle during the study is using mass balance equations and numerical methods (Fickian advection-dispersion approach) for solving the related partial differential equations. Model error decreases and sensitivity increases as a model becomes more complex, as such: i) uncertainty (in parameters, data input and model structure), and ii) model complexity, will be under investigation. Watershed data (water quality parameters together with stream flow, seasonal variations, surrounding landscape, stream temperature, and points/nonpoint sources) were obtained majorly using the HydroDesktop which is a free and open source GIS enabled desktop application to find, download, visualize, and analyze time series of water and climate data registered with the CUAHSI Hydrologic Information System. Processing, assessment of validity, and distribution of time-series data was explored using the GNU R language (statistical computing and graphics environment). Physical, chemical, and biological processes equations were written in FORTRAN codes (High Performance Fortran) in order to compute and solve their hyperbolic and parabolic complexities. Post analysis of results conducted using GNU R language. High performance computing (HPC) will be introduced to expedite solving complex computational processes using parallel programming. It is expected that the model will assess nonpoint sources and specific point sources data to understand pollutants' causes, transfer, dispersion, and concentration in different locations of Bear River. Investigation the impact of reduction/removal in non-point nutrient loading to Bear River water quality management could be addressed. Keywords: computer modeling; numerical solutions; sensitivity analysis; uncertainty analysis; ecosystem processes; high Performance computing; water quality.

Linking land-use type and stream water quality using spatial data of fecal indicator bacteria and heavy metals in the Yeongsan river basin.

PubMed

Kang, Joo-Hyon; Lee, Seung Won; Cho, Kyung Hwa; Ki, Seo Jin; Cha, Sung Min; Kim, Joon Ha

2010-07-01

This study reveals land-use factors that explain stream water quality during wet and dry weather conditions in a large river basin using two different linear models-multiple linear regression (MLR) models and constrained least squares (CLS) models. Six land-use types and three topographical parameters (size, slope, and permeability) of the watershed were incorporated into the models as explanatory variables. The suggested models were then demonstrated using a digitized elevation map in conjunction with the land-use and the measured concentration data for Escherichia coli (EC), Enterococci bacteria (ENT), and six heavy metal species collected monthly during 2007-2008 at 50 monitoring sites in the Yeongsan Watershed, Korea. The results showed that the MLR models can be a powerful tool for predicting the average concentrations of pollutants in stream water (the Nash-Sutcliffe (NS) model efficiency coefficients ranged from 0.67 to 0.95). On the other hand, the CLS models, with moderately good prediction performance (the NS coefficients ranged 0.28-0.85), were more suitable for quantifying contributions of respective land-uses to the stream water quality. The CLS models suggested that industrial and urban land-uses are major contributors to the stream concentrations of EC and ENT, whereas agricultural, industrial, and mining areas were significant sources of many heavy metal species. In addition, the slope, size, and permeability of the watershed were found to be important factors determining the extent of the contribution from each land-use type to the stream water quality. The models proposed in this paper can be considered useful tools for developing land cover guidelines and for prioritizing locations for implementing management practices to maintain stream water quality standard in a large river basin. Copyright 2010 Elsevier Ltd. All rights reserved.

Impact of river basin management on coastal water quality and ecosystem services: A southern Baltic estuary

NASA Astrophysics Data System (ADS)

Schernewski, Gerald; Hürdler, Jens; Neumann, Thomas; Stybel, Nardine; Venohr, Markus

2010-05-01

Eutrophication management is still a major challenge in the Baltic Sea region. Estuaries or coastal waters linked to large rivers cannot be managed independently. Nutrient loads into these coastal ecosystems depend on processes, utilisation, structure and management in the river basin. In practise this means that we need a large scale approach and integrated models and tools to analyse, assess and evaluate the effects of nutrient loads on coastal water quality as well as the efficiency of river basin management measures on surface waters and especially lagoons and estuaries. The Odra river basin, the Szczecin Lagoon and its coastal waters cover an area of about 150,000 km² and are an eutrophication hot-spot in the Baltic region. To be able to carry out large scale, spatially integrative analyses, we linked the river basin nutrient flux model MONERIS to the coastal 3D-hydrodynamic and ecosystem model ERGOM. Objectives were a) to analyse the eutrophication history in the river basin and the resulting functional changes in the coastal waters between early 1960's and today and b) to analyse the effects of an optimal nitrogen and phosphorus management scenario in the Oder/Odra river basin on coastal water quality. The models show that an optimal river basin management with reduced nutrient loads (e.g. N-load reduction of 35 %) would have positive effects on coastal water quality and algae biomass. The availability of nutrients, N/P ratios and processes like denitrification and nitrogen-fixation would show spatial and temporal changes. It would have positive consequences for ecosystems functions, like the nutrient retention capacity, as well. However, this optimal scenario is by far not sufficient to ensure a good coastal water quality according to the European Water Framework Directive. A "good" water quality in the river will not be sufficient to ensure a "good" water quality in the coastal waters. Further, nitrogen load reductions bear the risk of increased potentially toxic, blue-green algae blooms. The presentation will summarize recent results (Behrendt et al. 2009, Schernewski et al. 2009, Schernewski et al. in press, Schernewski et al. submitted) and give an overview how Climate Change and socio-economic transformation processes in the river basin will effect coastal water quality during the next decades. The opportunities and threats of a changing lagoon ecosystem for tourism and fisheries, the major economic activities, will be shown.

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

NASA Technical Reports Server (NTRS)

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.

Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods

NASA Astrophysics Data System (ADS)

Vanrolleghem, Peter A.; Mannina, Giorgio; Cosenza, Alida; Neumann, Marc B.

2015-03-01

Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important (factor prioritisation) and non-influential (factor fixing) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality-quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiarities, applicability, and reliability of the three methods is presented. Moreover, a graphical Venn diagram based classification scheme and a precise terminology for better identifying important, interacting and non-influential factors for each method is proposed. In terms of convergence, it was shown that sensitivity indices related to factors of the quantity model achieve convergence faster. Results for the Morris screening method deviated considerably from the other methods. Factors related to the quality model require a much higher number of simulations than the number suggested in literature for achieving convergence with this method. In fact, the results have shown that the term "screening" is improperly used as the method may exclude important factors from further analysis. Moreover, for the presented application the convergence analysis shows more stable sensitivity coefficients for the Extended-FAST method compared to SRC and Morris screening. Substantial agreement in terms of factor fixing was found between the Morris screening and Extended FAST methods. In general, the water quality related factors exhibited more important interactions than factors related to water quantity. Furthermore, in contrast to water quantity model outputs, water quality model outputs were found to be characterised by high non-linearity.

How is the River Water Quality Response to Climate Change Impacts?

NASA Astrophysics Data System (ADS)

Nguyen, T. T.; Willems, P.

2015-12-01

Water quality and its response to climate change have been become one of the most important issues of our society, which catches the attention of many scientists, environmental activists and policy makers. Climate change influences the river water quality directly and indirectly via rainfall and air temperature. For example, low flow decreases the volume of water for dilution and increases the residence time of the pollutants. By contrast, high flow leads to increases in the amount of pollutants and sediment loads from catchments to rivers. The changes in hydraulic characteristics, i.e. water depth and velocity, affect the transportation and biochemical transformation of pollutants in the river water body. The high air temperature leads to increasing water temperature, shorter growing periods of different crops and water demands from domestic households and industries, which eventually effects the level of river pollution. This study demonstrates the quantification of the variation of the water temperature and pollutant concentrations along the Molse Neet river in the North East of Belgium as a result of the changes in the catchment rainfall-runoff, air temperature and nutrient loads. Firstly, four climate change scenarios were generated based on a large ensemble of available global and regional climate models and statistical downscaling based on a quantile perturbation method. Secondly, the climatic changes to rainfall and temperature were transformed to changes in the evapotranspiration and runoff flow through the conceptual hydrological model PDM. Thirdly, the adjustment in nutrient loads from agriculture due to rainfall and growing periods of crops were calculated by means of the semi-empirical SENTWA model. Water temperature was estimated from air temperature by a stochastic model separating the temperature into long-term annual and short-term residual components. Next, hydrodynamic and water quality models of the river, implemented in InfoWorks RS, were simulated for both historical (2000-2010) and projected future periods (2050-2060). The advection movement and physico-biochemical processes were considered for simulation of the following water quality variables: water temperature, dissolved oxygen, biological oxygen demand, ammonium, nitrate, nitrite and organic nitrogen.

Comparative assessment for future prediction of urban water environment using WEAP model: A case study of Kathmandu, Manila and Jakarta

NASA Astrophysics Data System (ADS)

Kumar, Pankaj; Yoshifumi, Masago; Ammar, Rafieiemam; Mishra, Binaya; Fukushi, Ken

2017-04-01

Uncontrolled release of pollutants, increasing extreme weather condition, rapid urbanization and poor governance posing a serious threat to sustainable water resource management in developing urban spaces. Considering half of the world's mega-cities are in the Asia and the Pacific with 1.7 billion people do not access to improved water and sanitation, water security through its proper management is both an increasing concern and an imperative critical need. This research work strives to give a brief glimpse about predicted future water environment in Bagmati, Pasig and Ciliwung rivers from three different cities viz. Manila, Kathmandu and Jakarta respectively. Hydrological model used here to foresee the collective impacts of rapid population growth because of urbanization as well as climate change on unmet demand and water quality in near future time by 2030. All three rivers are major source of water for different usage viz. domestic, industrial, agriculture and recreation but uncontrolled withdrawal and sewerage disposal causing deterioration of water environment in recent past. Water Evaluation and Planning (WEAP) model was used to model river water quality pollution future scenarios using four indicator species i.e. Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD) and Nitrate (NO3). Result for simulated water quality as well as unmet demand for year 2030 when compared with that of reference year clearly indicates that not only water quality deteriorates but also unmet demands is increasing in future course of time. This also suggests that current initiatives and policies for water resource management are not sufficient enough and hence immediate and inclusive action through transdisciplinary research.

Approach for environmental baseline water sampling

USGS Publications Warehouse

Smith, K.S.

2011-01-01

Samples collected during the exploration phase of mining represent baseline conditions at the site. As such, they can be very important in forecasting potential environmental impacts should mining proceed, and can become measurements against which future changes are compared. Constituents in stream water draining mined and mineralized areas tend to be geochemically, spatially, and temporally variable, which presents challenges in collecting both exploration and baseline water-quality samples. Because short-term (daily) variations can complicate long-term trends, it is important to consider recent findings concerning geochemical variability of stream-water constituents at short-term timescales in designing sampling plans. Also, adequate water-quality information is key to forecasting potential ecological impacts from mining. Therefore, it is useful to collect baseline water samples adequate tor geochemical and toxicological modeling. This requires complete chemical analyses of dissolved constituents that include major and minor chemical elements as well as physicochemical properties (including pH, specific conductance, dissolved oxygen) and dissolved organic carbon. Applying chemical-equilibrium and appropriate toxicological models to water-quality information leads to an understanding of the speciation, transport, sequestration, bioavailability, and aquatic toxicity of potential contaminants. Insights gained from geochemical and toxicological modeling of water-quality data can be used to design appropriate mitigation and for economic planning for future mining activities.

Regional characterization of freshwater Use in LCA: modeling direct impacts on human health.

PubMed

Boulay, Anne-Marie; Bulle, Cécile; Bayart, Jean-Baptiste; Deschênes, Louise; Margni, Manuele

2011-10-15

Life cycle assessment (LCA) is a methodology that quantifies potential environmental impacts for comparative purposes in a decision-making context. While potential environmental impacts from pollutant emissions into water are characterized in LCA, impacts from water unavailability are not yet fully quantified. Water use can make the resource unavailable to other users by displacement or quality degradation. A reduction in water availability to human users can potentially affect human health. If financial resources are available, there can be adaptations that may, in turn, shift the environmental burdens to other life cycle stages and impact categories. This paper proposes a model to evaluate these potential impacts in an LCA context. It considers the water that is withdrawn and released, its quality and scarcity in order to evaluate the loss of functionality associated with water uses. Regionalized results are presented for impacts on human health for two modeling approaches regarding affected users, including or not domestic uses, and expressed in disability-adjusted life years (DALY). A consumption and quality based scarcity indicator is also proposed as a midpoint. An illustrative example is presented for the production of corrugated board with different effluents, demonstrating the importance of considering quality, process effluents and the difference between the modeling approaches.

A one-dimensional, steady-state, dissolved-oxygen model and waste-load assimilation study for Silver Creek, Clark and Floyd counties, Indiana

USGS Publications Warehouse

Wilber, William G.; Crawford, Charles G.; Peters, James G.

1979-01-01

The Indiana State Board of Health is developing a State water-quality management plan that includes establishing limits for wastewater effluents discharged into Indiana streams. A digital model calibrated to conditions in Silver Creek was used to develop alternatives for future waste loadings that would be compatible with Indiana stream water-quality standards defined for two critical hydrologic conditions, summer and winter low flows. Effluents from the Sellersburg and Clarksville-North wastewater-treatment facilities are the only point-source waste loads that significantly affect the water quality in the modeled segment of Silver Creek. Model simulations indicate that nitrification is the most significant factor affecting the dissolved-oxygen concentration in Silver Creek during summer and winter low flows. Natural streamflow in Silver Creek during the summer and annual 7-day, 10-year low flow is zero, so no benefit from dilution is provided. Present ammonia-nitrogen and dissolved-oxygen concentrations of effluent from the Sellersburg and Clarksville-North wastewater-treatment facilities will violate current Indiana water-quality standards for ammonia toxicity and dissolved oxygen during summer and winter low flows. The current biochemical-oxygen demand limits for the Sellersburg and Clarksville-North wastewater-treatment facilities are not sufficient to maintain an average dissolved-oxygen concentration of at least 5 milligrams per liter, the State 's water-quality standard for streams. Calculations of the stream 's assimilative capacity indicate that Silver Creek cannot assimilate additional waste loadings and meet current Indiana water-quality standards. (Kosco-USGS)

The water-quality monitoring program for the Baltimore reservoir system, 1981-2007—Description, review and evaluation, and framework integration for enhanced monitoring

USGS Publications Warehouse

Koterba, Michael T.; Waldron, Marcus C.; Kraus, Tamara E.C.

2011-01-01

The City of Baltimore, Maryland, and parts of five surrounding counties obtain their water from Loch Raven and Liberty Reservoirs. A third reservoir, Prettyboy, is used to resupply Loch Raven Reservoir. Management of the watershed conditions for each reservoir is a shared responsibility by agreement among City, County, and State jurisdictions. The most recent (2005) Baltimore Reservoir Watershed Management Agreement (RWMA) called for continued and improved water-quality monitoring in the reservoirs and selected watershed tributaries. The U.S. Geological Survey (USGS) conducted a retrospective review of the effectiveness of monitoring data obtained and analyzed by the RWMA jurisdictions from 1981 through 2007 to help identify possible improvements in the monitoring program to address RWMA water-quality concerns. Long-term water-quality concerns include eutrophication and sedimentation in the reservoirs, and elevated concentrations of (a) nutrients (nitrogen and phosphorus) being transported from the major tributaries to the reservoirs, (b) iron and manganese released from reservoir bed sediments during periods of deep-water anoxia, (c) mercury in higher trophic order game fish in the reservoirs, and (d) bacteria in selected reservoir watershed tributaries. Emerging concerns include elevated concentrations of sodium, chloride, and disinfection by-products (DBPs) in the drinking water from both supply reservoirs. Climate change and variability also could be emerging concerns, affecting seasonal patterns, annual trends, and drought occurrence, which historically have led to declines in reservoir water quality. Monitoring data increasingly have been used to support the development of water-quality models. The most recent (2006) modeling helped establish an annual sediment Total Maximum Daily Load to Loch Raven Reservoir, and instantaneous and 30-day moving average water-quality endpoints for chlorophyll-a (chl-a) and dissolved oxygen (DO) in Loch Raven and Prettyboy Reservoirs. Modelers cited limitations in data, including too few years with sufficient stormflow data, and (or) a lack of (readily available) data, for selected tributary and reservoir hydrodynamic, water-quality, and biotic conditions. Reservoir monitoring also is too infrequent to adequately address the above water-quality endpoints. Monitoring data also have been effectively used to generally describe trophic states, changes in trophic state or conditions related to trophic state, and in selected cases, trends in water-quality or biotic parameters that reflect RWMA water-quality concerns. Limitations occur in the collection, aggregation, analyses, and (or) archival of monitoring data in relation to most RWMA water-quality concerns. Trophic, including eutrophic, conditions have been broadly described for each reservoir in terms of phytoplankton production, and variations in production related to typical seasonal patterns in the concentration of DO, and hypoxic to anoxic conditions, where the latter have led to elevated concentrations of iron and manganese in reservoir and supply waters. Trend analyses for the period 1981-2004 have shown apparent declines in production (algal counts and possibly chl-a). The low frequency of phytoplankton data collection (monthly or bimonthly, depending on the reservoir), however, limits the development of a model to quantitatively describe and relate temporal variations in phytoplankton production including seasonal succession to changes in trophic states or other reservoir water-quality or biotic conditions. Extensive monitoring for nutrients, which, in excessive amounts, cause eutrophic conditions, has been conducted in the watershed tributaries and reservoirs. Data analyses (1980-90s) have (a) identified seasonal patterns in concentrations, (b) characterized loads from (non)point sources, and (c) shown that different seasonal patterns and trends in nutrient concentrations occur between watershed tributaries and downstream reservoir

Concentrations and annual fluxes for selected water-quality constituents from the USGS National Stream Quality Accounting Network (NASQAN) 1996-2000

USGS Publications Warehouse

Kelly, Valerie J.; Hooper, Richard P.; Aulenbach, Brent T.; Janet, Mary

2001-01-01

This report contains concentrations and annual mass fluxes (loadings) for a broad range of water-quality constituents measured during 1996-2000 as part of the U.S. Geological Survey National Stream Quality Accounting Network (NASQAN). During this period, NASQAN operated a network of 40-42 stations in four of the largest river basins of the USA: the Colorado, the Columbia, the Mississippi (including the Missouri and Ohio), and the Rio Grande. The report contains surface-water quality data, streamflow data, field measurements (e.g. water temperature and pH), sediment-chemistry data, and quality-assurance data; interpretive products include annual and average loads, regression parameters for models used to estimate loads, sub-basin yield maps, maps depicting percent detections for censored constituents, and diagrams depicting flow-weighted average concentrations. Where possible, a regression model relating concentration to discharge and season was used for flux estimation. The interpretive context provided by annual loads includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean.

Water quality assessment of the Li Canal using a functional fuzzy synthetic evaluation model.

PubMed

Feng, Yan; Ling, Liu

2014-07-01

Through introducing functional data analysis (FDA) theory into the conventional fuzzy synthetic evaluation (FSE) method, the functional fuzzy synthetic evaluation (FFSE) model is established. FFSE keeps the property of the conventional FSE that the fuzziness in the water quality condition can be suitably measured. Furthermore, compared with FSE, FFSE has the following advantages: (1) FFSE requires fewer conditions for observation, for example, pollutants can be monitored at different times, and missing data is accepted; (2) the dynamic variation of the water quality condition can be represented more comprehensively and intuitively. The procedure of FFSE is discussed and the water quality of the Li Canal in 2012 is evaluated as an illustration. The synthetic classification of the Li Canal is "II" in January, February and July, and "I" in other months, which can satisfy the requirement of the Chinese South-to-North Water Diversion Project.

Cost-effective water quality assessment through the integration of monitoring data and modeling results

NASA Astrophysics Data System (ADS)

Lobuglio, Joseph N.; Characklis, Gregory W.; Serre, Marc L.

2007-03-01

Sparse monitoring data and error inherent in water quality models make the identification of waters not meeting regulatory standards uncertain. Additional monitoring can be implemented to reduce this uncertainty, but it is often expensive. These costs are currently a major concern, since developing total maximum daily loads, as mandated by the Clean Water Act, will require assessing tens of thousands of water bodies across the United States. This work uses the Bayesian maximum entropy (BME) method of modern geostatistics to integrate water quality monitoring data together with model predictions to provide improved estimates of water quality in a cost-effective manner. This information includes estimates of uncertainty and can be used to aid probabilistic-based decisions concerning the status of a water (i.e., impaired or not impaired) and the level of monitoring needed to characterize the water for regulatory purposes. This approach is applied to the Catawba River reservoir system in western North Carolina as a means of estimating seasonal chlorophyll a concentration. Mean concentration and confidence intervals for chlorophyll a are estimated for 66 reservoir segments over an 11-year period (726 values) based on 219 measured seasonal averages and 54 model predictions. Although the model predictions had a high degree of uncertainty, integration of modeling results via BME methods reduced the uncertainty associated with chlorophyll estimates compared with estimates made solely with information from monitoring efforts. Probabilistic predictions of future chlorophyll levels on one reservoir are used to illustrate the cost savings that can be achieved by less extensive and rigorous monitoring methods within the BME framework. While BME methods have been applied in several environmental contexts, employing these methods as a means of integrating monitoring and modeling results, as well as application of this approach to the assessment of surface water monitoring networks, represent unexplored areas of research.

Santa Margarita Estuary Water Quality Monitoring Data

DTIC Science & Technology

2018-02-01

ADMINISTRATIVE INFORMATION The work described in this report was performed for the Water Quality Section of the Environmental Security Marine Corps Base...water quality model calibration given interest and the necessary resources. The dataset should also inform the stakeholders and Regional Board on...period. Several additional ancillary datasets were collected during the monitoring timeframe that provide key information though they were not collected

Hydraulic optimization and modeling of hydro-cyclone-systems for treatment and purification of any kind of waters

NASA Astrophysics Data System (ADS)

Spangemacher, Lars; Fröhlich, Siegmund; Buse, Hauke

2017-11-01

Water is an indispensable resource for many purposes and good drinking water quality is essential for mankind. This article is supposed to show the need for mobile water treatment systems and therefore to give an overview of different mobile drinking water systems and the technologies available for obtaining good water quality. The aim is to develop a simple to operate water treatment system with few processing stages such as multi-cyclone-cartridge and reverse osmosis with energy recuperation, while the focus is set on modeling and optimizing of hydrocyclone systems as the first treatment stage.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khangaonkar, Tarang; Sackmann, Brandon S.; Long, Wen

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 themore » 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« less

Land cover impacts on stream nutrients and fecal coliform in the lower Piedmont of West Georgia

NASA Astrophysics Data System (ADS)

Schoonover, Jon E.; Lockaby, B. Graeme

2006-12-01

SummaryAs urbanization infiltrates into rural areas, stream water quality is expected to decline as a result from increased impervious surface and greater sources for pollutants. Consequently, West Georgia's water quality is threatened by extensive development as well as other land uses such as livestock grazing and silvicultural activity. Maintenance of stream water quality, as land development occurs, is critical for the protection of drinking water and biotic integrity. A 2-phase, watershed-scale study was established to develop relationships among land cover and water quality within western Georgia. During phase 1, nutrient and fecal coliform data were collected within 18 mixed land use watersheds, ranging in size from 500 to 2500 ha. Regression models were developed that related land cover to stream water nutrient and fecal coliform concentrations. Nutrient and fecal coliform concentrations within watersheds having >24% impervious surface (IS) were often higher than those in nonurban watersheds (i.e., <5% IS) during both base flow (N: 1.64 mg/L versus 0.61 mg/L, and FC: 430 versus 120 MPN/100 ml) and storm flow (N: 1.93 mg/L versus 0.36 mg/L, and FC: 1600 versus 167 MPN/100 ml). Fecal coliform bacteria in urbanized areas consistently exceeded the US EPA's review criterion for recreational waters during both base flow and to a greater extent storm flow. During phase 2, regression models were tested based on data from six newly chosen watersheds with similar land use/cover patterns. Lastly, theoretical watersheds, based on land use percentages, were created to illustrate trends in water quality impairment as land development occurs. The models developed from this research could be used to forecast water quality changes under various land use scenarios in the developing Piedmont region of the US.

Modeling Effects of Groundwater Basin Closure, and Reversal of Closure, on Groundwater Quality

NASA Astrophysics Data System (ADS)

Pauloo, R.; Guo, Z.; Fogg, G. E.

2017-12-01

Population growth, the expansion of agriculture, and climate uncertainties have accelerated groundwater pumping and overdraft in aquifers worldwide. In many agricultural basins, a water budget may be stable or not in overdraft, yet disconnected ground and surface water bodies can contribute to the formation of a "closed" basin, where water principally exits the basin as evapotranspiration. Although decreasing water quality associated with increases in Total Dissolved Solids (TDS) have been documented in aquifers across the United States in the past half century, connections between water quality declines and significant changes in hydrologic budgets leading to closed basin formation remain poorly understood. Preliminary results from an analysis with a regional-scale mixing model of the Tulare Lake Basin in California indicate that groundwater salinization resulting from open to closed basin conversion can operate on a decades-to-century long time scale. The only way to reverse groundwater salinization caused by basin closure is to refill the basin and change the hydrologic budget sufficiently for natural groundwater discharge to resume. 3D flow and transport modeling, including the effects of heterogeneity based on a hydrostratigraphic facies model, is used to explore rates and time scales of groundwater salinization and its reversal under different water and land management scenarios. The modeling is also used to ascertain the extent to which local and regional heterogeneity need to be included in order to appropriately upscale the advection-dispersion equation in a basin scale groundwater quality management model. Results imply that persistent managed aquifer recharge may slow groundwater salinization, and complete reversal may be possible at sufficiently high water tables.

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

EPA Science Inventory

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

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

EPA Science Inventory

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

ASSESSING THE WATER QUALITY IMPACTS OF GLOBAL CLIMATE CHANGE IN SOUTHWESTERN OHIO, U.S.A

EPA Science Inventory

This paper uses a watershed-scale hydrologic model (Soil and Water Assessment Tool) to simulate the water quality impacts of future climate change in the Little Miami River (LMR) watershed in southwestern Ohio. The LMR watershed, the principal source of drinking water for 1.6 mi...

Impacts of forest to urban land conversion and ENSO phase on water quality of a public water supply reservoir

USDA-ARS?s Scientific Manuscript database

We used coupled watershed and reservoir models to evaluate the impacts of deforestation and ENSO phase on drinking water quality. Source water total organic carbon (TOC) is especially important due to the potential for production of carcinogenic disinfection byproducts (DBPs). The Environmental Flui...

Urban Stormwater Management Model and Tools for Designing Stormwater Management of Green Infrastructure Practices

NASA Astrophysics Data System (ADS)

Haris, H.; Chow, M. F.; Usman, F.; Sidek, L. M.; Roseli, Z. A.; Norlida, M. D.

2016-03-01

Urbanization is growing rapidly in Malaysia. Rapid urbanization has known to have several negative impacts towards hydrological cycle due to decreasing of pervious area and deterioration of water quality in stormwater runoff. One of the negative impacts of urbanization is the congestion of the stormwater drainage system and this situation leading to flash flood problem and water quality degradation. There are many urban stormwater management softwares available in the market such as Storm Water Drainage System design and analysis program (DRAINS), Urban Drainage and Sewer Model (MOUSE), InfoWorks River Simulation (InfoWork RS), Hydrological Simulation Program-Fortran (HSPF), Distributed Routing Rainfall-Runoff Model (DR3M), Storm Water Management Model (SWMM), XP Storm Water Management Model (XPSWMM), MIKE-SWMM, Quality-Quantity Simulators (QQS), Storage, Treatment, Overflow, Runoff Model (STORM), and Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS). In this paper, we are going to discuss briefly about several softwares and their functionality, accessibility, characteristics and components in the quantity analysis of the hydrological design software and compare it with MSMA Design Aid and Database. Green Infrastructure (GI) is one of the main topics that has widely been discussed all over the world. Every development in the urban area is related to GI. GI can be defined as green area build in the develop area such as forest, park, wetland or floodway. The role of GI is to improve life standard such as water filtration or flood control. Among the twenty models that have been compared to MSMA SME, ten models were selected to conduct a comprehensive review for this study. These are known to be widely accepted by water resource researchers. These ten tools are further classified into three major categories as models that address the stormwater management ability of GI in terms of quantity and quality, models that have the capability of conducting the economic analysis of GI and models that can address both stormwater management and economic aspects together.

Assessing the Effects of Water Rights Purchases on Dissolved Oxygen, Stream Temperatures, and Fish Habitat

NASA Astrophysics Data System (ADS)

Mouzon, N. R.; Null, S. E.

2014-12-01

Human impacts from land and water development have degraded water quality and altered the physical, chemical, and biological integrity of Nevada's Walker River. Reduced instream flows and increased nutrient concentrations affect native fish populations through warm daily stream temperatures and low nightly dissolved oxygen concentrations. Water rights purchases are being considered to maintain instream flows, improve water quality, and enhance habitat for native fish species, such as Lahontan cutthroat trout. This study uses the River Modeling System (RMSv4), an hourly, physically-based hydrodynamic and water quality model, to estimate streamflows, temperatures, and dissolved oxygen concentrations in the Walker River. We simulate thermal and dissolved oxygen changes from increased streamflow to prioritize the time periods and locations that water purchases most enhance native trout habitat. Stream temperatures and dissolved oxygen concentrations are proxies for trout habitat. Monitoring results indicate stream temperature and dissolved oxygen limitations generally exist in the 115 kilometers upstream of Walker Lake (about 37% of the study area) from approximately May through September, and this reach currently acts as a water quality barrier for fish passage.

Improved algorithms in the CE-QUAL-W2 water-quality model for blending dam releases to meet downstream water-temperature targets

USGS Publications Warehouse

Rounds, Stewart A.; Buccola, Norman L.

2015-01-01

Water-quality models allow water resource professionals to examine conditions under an almost unlimited variety of potential future scenarios. The two-dimensional (longitudinal, vertical) water-quality model CE-QUAL-W2, version 3.7, was enhanced and augmented with new features to help dam operators and managers explore and optimize potential solutions for temperature management downstream of thermally stratified reservoirs. Such temperature management often is accomplished by blending releases from multiple dam outlets that access water of different temperatures at different depths. The modified blending algorithm in version 3.7 of CE-QUAL-W2 allows the user to specify a time-series of target release temperatures, designate from 2 to 10 floating or fixed-elevation outlets for blending, impose minimum and maximum head and flow constraints for any blended outlet, and set priority designations for each outlet that allow the model to choose which outlets to use and how to balance releases among them. The modified model was tested with a variety of examples and against a previously calibrated model of Detroit Lake on the North Santiam River in northwestern Oregon, and the results compared well. These updates to the blending algorithms will allow more complicated dam-operation scenarios to be evaluated somewhat automatically with the model, with decreased need for multiple model runs or preprocessing of model inputs to fully characterize the operational constraints.

Scale effects on spatially varying relationships between urban landscape patterns and water quality.

PubMed

Sun, Yanwei; Guo, Qinghai; Liu, Jian; Wang, Run

2014-08-01

Scientific interpretation of the relationships between urban landscape patterns and water quality is important for sustainable urban planning and watershed environmental protection. This study applied the ordinary least squares regression model and the geographically weighted regression model to examine the spatially varying relationships between 12 explanatory variables (including three topographical factors, four land use parameters, and five landscape metrics) and 15 water quality indicators in watersheds of Yundang Lake, Maluan Bay, and Xinglin Bay with varying levels of urbanization in Xiamen City, China. A local and global investigation was carried out at the watershed-level, with 50 and 200 m riparian buffer scales. This study found that topographical features and landscape metrics are the dominant factors of water quality, while land uses are too weak to be considered as a strong influential factor on water quality. Such statistical results may be related with the characteristics of land use compositions in our study area. Water quality variations in the 50 m buffer were dominated by topographical variables. The impact of landscape metrics on water quality gradually strengthen with expanding buffer zones. The strongest relationships are obtained in entire watersheds, rather than in 50 and 200 m buffer zones. Spatially varying relationships and effective buffer zones were verified in this study. Spatially varying relationships between explanatory variables and water quality parameters are more diversified and complex in less urbanized areas than in highly urbanized areas. This study hypothesizes that all these varying relationships may be attributed to the heterogeneity of landscape patterns in different urban regions. Adjustment of landscape patterns in an entire watershed should be the key measure to successfully improving urban lake water quality.

An evaluation of freshwater mussel toxicity data in the derivation of water quality guidance and standards for copper

USGS Publications Warehouse

March, F.A.; Dwyer, F.J.; Augspurger, T.; Ingersoll, C.G.; Wang, N.; Mebane, C.A.

2007-01-01

The state of Oklahoma has designated several areas as freshwater mussel sanctuaries in an attempt to provide freshwater mussel species a degree of protection and to facilitate their reproduction. We evaluated the protection afforded freshwater mussels by the U.S. Environmental Protection Agency (U.S. EPA) hardness-based 1996 ambient copper water quality criteria, the 2007 U.S. EPA water quality criteria based on the biotic ligand model and the 2005 state of Oklahoma copper water quality standards. Both the criterion maximum concentration and criterion continuous concentration were evaluated. Published acute and chronic copper toxicity data that met American Society for Testing and Materials guidance for test acceptability were obtained for exposures conducted with glochidia or juvenile freshwater mussels. We tabulated toxicity data for glochidia and juveniles to calculate 20 species mean acute values for freshwater mussels. Generally, freshwater mussel species mean acute values were similar to those of the more sensitive species included in the U.S. EPA water quality derivation database. When added to the database of genus mean acute values used in deriving 1996 copper water quality criteria, 14 freshwater mussel genus mean acute values included 10 of the lowest 15 genus mean acute values, with three mussel species having the lowest values. Chronic exposure and sublethal effects freshwater mussel data available for four species and acute to chronic ratios were used to evaluate the criterion continuous concentration. On the basis of the freshwater mussel toxicity data used in this assessment, the hardness-based 1996 U.S. EPA water quality criteria, the 2005 Oklahoma water quality standards, and the 2007 U.S. EPA water quality criteria based on the biotic ligand model might need to be revised to afford protection to freshwater mussels. ?? 2007 SETAC.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Determination of the optimal training principle and input variables in artificial neural network model for the biweekly chlorophyll-a prediction: a case study of the Yuqiao Reservoir, China.

PubMed

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang

2015-01-01

Predicting the levels of chlorophyll-a (Chl-a) is a vital component of water quality management, which ensures that urban drinking water is safe from harmful algal blooms. This study developed a model to predict Chl-a levels in the Yuqiao Reservoir (Tianjin, China) biweekly using water quality and meteorological data from 1999-2012. First, six artificial neural networks (ANNs) and two non-ANN methods (principal component analysis and the support vector regression model) were compared to determine the appropriate training principle. Subsequently, three predictors with different input variables were developed to examine the feasibility of incorporating meteorological factors into Chl-a prediction, which usually only uses water quality data. Finally, a sensitivity analysis was performed to examine how the Chl-a predictor reacts to changes in input variables. The results were as follows: first, ANN is a powerful predictive alternative to the traditional modeling techniques used for Chl-a prediction. The back program (BP) model yields slightly better results than all other ANNs, with the normalized mean square error (NMSE), the correlation coefficient (Corr), and the Nash-Sutcliffe coefficient of efficiency (NSE) at 0.003 mg/l, 0.880 and 0.754, respectively, in the testing period. Second, the incorporation of meteorological data greatly improved Chl-a prediction compared to models solely using water quality factors or meteorological data; the correlation coefficient increased from 0.574-0.686 to 0.880 when meteorological data were included. Finally, the Chl-a predictor is more sensitive to air pressure and pH compared to other water quality and meteorological variables.

Watershed-Scale Modeling of Land-Use and Altered Environment Impacts on Aquatic Weed Growth in the Delta

NASA Technical Reports Server (NTRS)

Bubenheim, David; Potter, Christopher; Zhang, Minghua

2016-01-01

The California Sacramento-San Joaquin River Delta is the hub for California's water supply, conveying water from Northern to Southern California agriculture and communities while supporting important ecosystem services, agriculture, and communities in the Delta. Changes in climate, long-term drought, and water quality have all been suspected as playing role in the dramatic expansion of invasive aquatic plants and their impact on ecosystems of the San Francisco Bay / California Delta complex. NASA Ames Research Center, USDA-Agricultural Research Service, the State of California, UC Davis, and local governments have partnered under a USDA sponsored project (DRAAWP) to develop science-based, adaptive-management strategies for invasive aquatic plants in Sacramento-San Joaquin Delta. Critical to developing management strategies is to understand how the Delta is affected by both the magnitude of fluctuations in land-use and climate / drought induced altered environments and how the plants respond to these altered environments. We utilize the Soil Water Assessment Tool (SWAT), a watershed-scale model developed to quantify the impact of land management practices in large and complex watersheds on water quality, as the backbone for a customized Delta model - Delta-SWAT. The model uses land-use, soils, elevation, and hydrologic routing to characterize pesticide and nutrient transport from the Sacramento and San Joaquin rivers watersheds and loading into the Delta. Land-use within the Delta, as well as water extraction to supply those functions, and the resulting return of water to Delta waterways are included in Delta-SWAT. Hydrologic transport within the Delta has required significant attention to address the lack of elevation driven transport processes. Delta-SWAT water quality trend estimates are compared with water quality monitoring conducted throughout the Delta. Aquatic plant response to water quality and other environmental factors is carried out using a customized model component. Plant response to the range of water quality factors, response times, and altered temperature and light regimes of the Delta have required gap-filling studies to provide model parameters. Delta-SWAT provides a tool for evaluating temporal and spatial effects of land-use and altered environments in the Delta and contributing watersheds on aquatic weed growth. Using Delta-SWAT for simulation modeling allows evaluation of historic and current conditions as well as consideration potential climate change and management practice outcomes. Delta-SWAT adds to the scientific understanding of dynamics in the Delta and enhances development of science-informed, management strategies and practices.

Multilayer perceptron neural network-based approach for modeling phycocyanin pigment concentrations: case study from lower Charles River buoy, USA.

PubMed

Heddam, Salim

2016-09-01

This paper proposes multilayer perceptron neural network (MLPNN) to predict phycocyanin (PC) pigment using water quality variables as predictor. In the proposed model, four water quality variables that are water temperature, dissolved oxygen, pH, and specific conductance were selected as the inputs for the MLPNN model, and the PC as the output. To demonstrate the capability and the usefulness of the MLPNN model, a total of 15,849 data measured at 15-min (15 min) intervals of time are used for the development of the model. The data are collected at the lower Charles River buoy, and available from the US Environmental Protection Agency (USEPA). For comparison purposes, a multiple linear regression (MLR) model that was frequently used for predicting water quality variables in previous studies is also built. The performances of the models are evaluated using a set of widely used statistical indices. The performance of the MLPNN and MLR models is compared with the measured data. The obtained results show that (i) the all proposed MLPNN models are more accurate than the MLR models and (ii) the results obtained are very promising and encouraging for the development of phycocyanin-predictive models.

Simulation of flow and water quality of the Arroyo Colorado, Texas, 1989-99

USGS Publications Warehouse

Raines, Timothy H.; Miranda, Roger M.

2002-01-01

A model parameter set for use with the Hydrological Simulation Program—FORTRAN watershed model was developed to simulate flow and water quality for selected properties and constituents for the Arroyo Colorado from the city of Mission to the Laguna Madre, Texas. The model simulates flow, selected water-quality properties, and constituent concentrations. The model can be used to estimate a total maximum daily load for selected properties and constituents in the Arroyo Colorado. The model was calibrated and tested for flow with data measured during 1989–99 at three streamflow-gaging stations. The errors for total flow volume ranged from -0.1 to 29.0 percent, and the errors for total storm volume ranged from -15.6 to 8.4 percent. The model was calibrated and tested for water quality for seven properties and constituents with 1989–99 data. The model was calibrated sequentially for suspended sediment, water temperature, biochemical oxygen demand, dissolved oxygen, nitrate nitrogen, ammonia nitrogen, and orthophosphate. The simulated concentrations of the selected properties and constituents generally matched the measured concentrations available for the calibration and testing periods. The model was used to simulate total point- and nonpoint-source loads for selected properties and constituents for 1989–99 for urban, natural, and agricultural land-use types. About one-third to one-half of the biochemical oxygen demand and nutrient loads are from urban point and nonpoint sources, although only 13 percent of the total land use in the basin is urban.

Integration of social perceptions, behaviors, and economic valuations of groundwater quality as an ecosystem service following exurban development

NASA Astrophysics Data System (ADS)

Godsey, S.; Larson, D. M.; Ohr, C. A.; Kobs-Nawotniak, S. E.; Lohse, K. A.; Lybecker, D.; Hale, R. L.; Stoutenborough, J.

2015-12-01

Millions of people rely on groundwater as a key, provisioning ecosystem service (ES). Our previous data suggested that drinking water nitrate concentrations and exurban development have significantly increased in the last three decades in Pocatello, Idaho, USA. Increased nitrate can lead to changes in ES and human values (such as water quality, people's knowledge, and housing values). We predicted people who tested their water quality would be aware of nitrate contamination and its potential to affect their housing prices, and they would choose to invest in home drinking water treatment systems. To test these hypotheses, we measured nitrate concentrations in hundreds of drinking water wells in years 1985, 1994, 2004, and 2015. We conducted a randomized public survey to determine the degrees to which: (1) people tested their private well water for nitrate and (2) were concerned about health issues related to contamination; (3) how important water quality is for determining local property values; and (4) if people treat their drinking water. We then developed a biophysical model to understand how exurban growth, local geology, and time influenced groundwater nitrate. Finally, we applied an economic, hedonic model to determine if groundwater nitrate concentrations negatively correlated to property values. Aquifer boundaries, slope, rock and soil type were significant predictors of nitrate (ordinary least squares, α <0.05). The hedonic model suggested that although nitrate and local housing values were spatially heterogeneous and increasing through time, exurban growth and nitrate alone were not strong predictors of water quality or property values. We also present an integrated biophysical, economic, and social model to better understand people's perceptions and behaviors of local nitrate pollution. Interdisciplinary ES and valuation may require multiple data types and integrated models to understand how ES and human values are influenced by exurban growth.

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

USDA-ARS?s Scientific Manuscript database

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-...

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

Treesearch

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...

The Heartland Region P-Index Conservation Innovation Grant: protecting water quality through improved phosphorus management

USDA-ARS?s Scientific Manuscript database

Reducing phosphorus loss from agricultural land is important for improvement and protection of surface water quality. Agricultural models can be used to determine management impacts on P loss and therefore serve as a guide for recommending best management practices. However, the models must be comp...

Lessons learned from a one-dimensional water quality model for the Gulf of Mexico

EPA Science Inventory

Hypoxia in the northern Gulf of Mexico has been a major concern for many years. Several water quality models have attempted to describe the link between high nutrient loads from the Mississippi River and hypoxia in the Gulf of Mexico with varied success. Here we describe the dev...

UTILIZATION OF LANDSCAPE INDICATORS TO MODEL WATER QUALITY

EPA Science Inventory

Many water-bodies within the United States are contaminated by, non-point source (NFS) pollution, which is defined as those materials posing a threat to water quality arising from a number of individual sources and diffused through hydrologic processes. One such NPS pollu...

Seasonal Phosphorus Sources and Loads to Upper Klamath Lake, Oregon, as Determined by a Dynamic SPARROW Model

NASA Astrophysics Data System (ADS)

Saleh, D.; Domagalski, J. L.; Smith, R. A.

2016-12-01

The SPARROW (SPAtially-Referenced Regression On Watershed Attributes) model, developed by the U.S. Geological Survey, has been used to identify and quantify the sources of nitrogen and phosphorus in watersheds and to predict their fluxes and concentration at specified locations downstream. Existing SPARROW models use a hybrid statistical approach to describe an annual average ("steady-state") relationship between sources and stream conditions based on long-term water quality monitoring data and spatially-referenced explanatory information. Although these annual models are useful for some management purposes, many water quality issues stem from intra- and inter-annual changes in constituent sources, hydrologic forcing, or other environmental conditions, which cause a lag between watershed inputs and stream water quality. We are developing a seasonal dynamic SPARROW model of sources, fluxes, and yields of phosphorus for the watershed (approximately 9,700 square kilometers) draining to Upper Klamath Lake, Oregon. The lake is hyper-eutrophic and various options are being considered for water quality improvement. The model was calibrated with 11 years of water quality data (2000 to 2010) and simulates seasonal loads and yields for a total of 44 seasons. Phosphorus sources to the watershed include animal manure, farm fertilizer, discharges of treated wastewater, and natural sources (soil and streambed sediment). The model predicts that phosphorus delivery to the lake is strongly affected by intra- and inter-annual changes in precipitation and by temporary seasonal storage of phosphorus in the watershed. The model can be used to predict how different management actions for mitigating phosphorus sources might affect phosphorus loading to the lake as well as the time required for any changes in loading to occur following implementation of the action.

Evaluative methodology for comprehensive water quality management planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dyer, H. L.

Computer-based evaluative methodologies have been developed to provide for the analysis of coupled phenomena associated with natural resource comprehensive planning requirements. Provisions for planner/computer interaction have been included. Each of the simulation models developed is described in terms of its coded procedures. An application of the models for water quality management planning is presented; and the data requirements for each of the models are noted.

A Systems Approach to Manage Drinking Water Quality ...

EPA Pesticide Factsheets

Drinking water supplies can be vulnerable to impacts from short-term weather events, long-term changes in land-use and climate, and water quality controls in treatment and distribution. Disinfection by-product (DBP) formation in drinking water is a prominent example to illustrate the water supply vulnerability and examine technological options in adaptation. Total organic carbon (TOC) in surface water can vary significantly due to changes or a combination of changes in watershed land use, climate variability, and extreme meteorological events (e.g., hurricanes). On the other hand, water demand is known to vary temporarily and spatially leading to changes in water ages and hence DBP formation potential. Typically a drinking water facility is designed to operate within a projected range of influent water quality and water demand. When the variations exceed the design range, water supply becomes vulnerable in the compliance to Safe Drinking Water Act (SDWA) Stage-II disinfection by-product (DBP) rules. This paper describes a framework of systems-level modeling, monitoring and control in adaptive planning and system operation. The framework, built upon the integration of model projections, adaptive monitoring and systems control, has three primary functions. Its advantages and limitations will be discussed with the application examples in Cincinnati (Ohio, USA) and Las Vegas (Nevada, USA). At a conceptual level, an integrated land use and hydrological model

Use of a macroinvertebrate based biotic index to estimate critical metal concentrations for good ecological water quality.

PubMed

Van Ael, Evy; De Cooman, Ward; Blust, Ronny; Bervoets, Lieven

2015-01-01

Large datasets from total and dissolved metal concentrations in Flemish (Belgium) fresh water systems and the associated macroinvertebrate-based biotic index MMIF (Multimetric Macroinvertebrate Index Flanders) were used to estimate critical metal concentrations for good ecological water quality, as imposed by the European Water Framework Directive (2000). The contribution of different stressors (metals and water characteristics) to the MMIF were studied by constructing generalized linear mixed effect models. Comparison between estimated critical concentrations and the European and Flemish EQS, shows that the EQS for As, Cd, Cu and Zn seem to be sufficient to reach a good ecological quality status as expressed by the invertebrate-based biotic index. In contrast, the EQS for Cr, Hg and Pb are higher than the estimated critical concentrations, which suggests that when environmental concentrations are at the same level as the EQS a good quality status might not be reached. The construction of mixed models that included metal concentrations in their structure did not lead to a significant outcome. However, mixed models showed the primary importance of water characteristics (oxygen level, temperature, ammonium concentration and conductivity) for the MMIF. Copyright © 2014 Elsevier Ltd. All rights reserved.

Should we trust build-up/wash-off water quality models at the scale of urban catchments?

PubMed

Bonhomme, Céline; Petrucci, Guido

2017-01-01

Models of runoff water quality at the scale of an urban catchment usually rely on build-up/wash-off formulations obtained through small-scale experiments. Often, the physical interpretation of the model parameters, valid at the small-scale, is transposed to large-scale applications. Testing different levels of spatial variability, the parameter distributions of a water quality model are obtained in this paper through a Monte Carlo Markov Chain algorithm and analyzed. The simulated variable is the total suspended solid concentration at the outlet of a periurban catchment in the Paris region (2.3 km 2 ), for which high-frequency turbidity measurements are available. This application suggests that build-up/wash-off models applied at the catchment-scale do not maintain their physical meaning, but should be considered as "black-box" models. Copyright © 2016 Elsevier Ltd. All rights reserved.

Water quality modeling using geographic information system (GIS) data

NASA Technical Reports Server (NTRS)

Engel, Bernard A

1992-01-01

Protection of the environment and natural resources at the Kennedy Space Center (KSC) is of great concern. The potential for surface and ground water quality problems resulting from non-point sources of pollution was examined using models. Since spatial variation of parameters required was important, geographic information systems (GIS) and their data were used. The potential for groundwater contamination was examined using the SEEPAGE (System for Early Evaluation of the Pollution Potential of Agricultural Groundwater Environments) model. A watershed near the VAB was selected to examine potential for surface water pollution and erosion using the AGNPS (Agricultural Non-Point Source Pollution) model.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Large scale hydro-economic modelling for policy support

NASA Astrophysics Data System (ADS)

de Roo, Ad; Burek, Peter; Bouraoui, Faycal; Reynaud, Arnaud; Udias, Angel; Pistocchi, Alberto; Lanzanova, Denis; Trichakis, Ioannis; Beck, Hylke; Bernhard, Jeroen

2014-05-01

To support European Union water policy making and policy monitoring, a hydro-economic modelling environment has been developed to assess optimum combinations of water retention measures, water savings measures, and nutrient reduction measures for continental Europe. This modelling environment consists of linking the agricultural CAPRI model, the LUMP land use model, the LISFLOOD water quantity model, the EPIC water quality model, the LISQUAL combined water quantity, quality and hydro-economic model, and a multi-criteria optimisation routine. With this modelling environment, river basin scale simulations are carried out to assess the effects of water-retention measures, water-saving measures, and nutrient-reduction measures on several hydro-chemical indicators, such as the Water Exploitation Index (WEI), Nitrate and Phosphate concentrations in rivers, the 50-year return period river discharge as an indicator for flooding, and economic losses due to water scarcity for the agricultural sector, the manufacturing-industry sector, the energy-production sector and the domestic sector, as well as the economic loss due to flood damage. Recently, this model environment is being extended with a groundwater model to evaluate the effects of measures on the average groundwater table and available resources. Also, water allocation rules are addressed, while having environmental flow included as a minimum requirement for the environment. Economic functions are currently being updated as well. Recent development and examples will be shown and discussed, as well as open challenges.

Simulated water-level and water-quality changes in the bolson-fill aquifer, Post Headquarters area, White Sands Missile Range, New Mexico

USGS Publications Warehouse

Risser, D.W.

1988-01-01

The quantity of freshwater available in the Post Headquarters well field, White Sand Missile Range, New Mexico, is limited and its quality is threatened by saltwater enroachment. A three-dimensional, finite-difference, groundwater flow model and a cross-sectional, density-dependent solute-transport model were constructed to simulate possible future water level declines and water quality changes in the Post Headquarters well field. A six-layer flow model was constructed using hydraulic-conductivity values in the upper 600 ft of saturated aquifer ranging from 0.1 to 10 ft/day, specific yield of 0.15, and average recharge of about 1,590 acre-ft/yr. Water levels simulated by the model closely matched measured water levels for 1948-82. Possible future water level changes for 1983-2017 were simulated using rates of groundwater withdrawal of 1,033 and 2 ,066 acre-ft/year and wastewater return flow of 0 or 30% of the groundwater withdrawal rate. The cross-sectional solute-transport model indicated that the freshwater zone is about 1,500 to 2,000 ft thick beneath the well field. Transient simulations show that solutes probably will move laterally toward the well field rather than from beneath the well field. (USGS)

The Role of Reliability, Vulnerability and Resilience in the Management of Water Quality Systems

NASA Astrophysics Data System (ADS)

Lence, B. J.; Maier, H. R.

2001-05-01

The risk based performance indicators reliability, vulnerability and resilience provide measures of the frequency, magnitude and duration of the failure of water resources systems, respectively. They have been applied primarily to water supply problems, including the assessment of the performance of reservoirs and water distribution systems. Applications to water quality case studies have been limited, although the need to consider the length and magnitude of violations of a particular water quality standard has been recognized for some time. In this research, the role of reliability, vulnerability and resilience in water quality management applications is investigated by examining their significance as performance measures for water quality systems and assessing their potential for assisting in decision making processes. The importance of each performance indicator is discussed and a framework for classifying such systems, based on the relative significance of each of these indicators, is introduced and illustrated qualitatively with various case studies. Quantitative examples drawn from both lake and river water quality modeling exercises are then provided.

Data visualization, time-series analysis, and mass-balance modeling of hydrologic and water-quality data for the McTier Creek watershed, South Carolina, 2007-2009

USGS Publications Warehouse

Benedict, Stephen T.; Conrads, Paul; Feaster, Toby D.; Journey, Celeste A.; Golden, Heather E.; Knightes, Christopher D.; Davis, Gary M.; Bradley, Paul M.

2012-01-01

The McTier Creek watershed is located in the headwaters of the Edisto River Basin, which is in the Coastal Plain region of South Carolina. The Edisto ecosystem has some of the highest recorded fish-tissue mercury concentrations in the United States. In an effort to advance the understanding of the fate and transport of mercury in stream ecosystems, the U.S. Geological Survey, as part of its National Water-Quality Assessment Program, initiated a field investigation of mercury in the McTier Creek watershed in 2006. The initial efforts of the investigation included the collection of extensive hydrologic and water-quality field data, along with the development of several hydrologic and water-quality models. This series of measured and modeled data forms the primary source of information for this investigation to assess the fate and transport of mercury within the McTier Creek watershed.

Impacts of climate change and socio-economic scenarios on flow and water quality of the Ganges, Brahmaputra and Meghna (GBM) river systems: low flow and flood statistics.

PubMed

Whitehead, P G; Barbour, E; Futter, M N; Sarkar, S; Rodda, H; Caesar, J; Butterfield, D; Jin, L; Sinha, R; Nicholls, R; Salehin, M

2015-06-01

The potential impacts of climate change and socio-economic change on flow and water quality in rivers worldwide is a key area of interest. The Ganges-Brahmaputra-Meghna (GBM) is one of the largest river basins in the world serving a population of over 650 million, and is of vital concern to India and Bangladesh as it provides fresh water for people, agriculture, industry, conservation and for the delta system downstream. This paper seeks to assess future changes in flow and water quality utilising a modelling approach as a means of assessment in a very complex system. The INCA-N model has been applied to the Ganges, Brahmaputra and Meghna river systems to simulate flow and water quality along the rivers under a range of future climate conditions. Three model realisations of the Met Office Hadley Centre global and regional climate models were selected from 17 perturbed model runs to evaluate a range of potential futures in climate. In addition, the models have also been evaluated using socio-economic scenarios, comprising (1) a business as usual future, (2) a more sustainable future, and (3) a less sustainable future. Model results for the 2050s and the 2090s indicate a significant increase in monsoon flows under the future climates, with enhanced flood potential. Low flows are predicted to fall with extended drought periods, which could have impacts on water and sediment supply, irrigated agriculture and saline intrusion. In contrast, the socio-economic changes had relatively little impact on flows, except under the low flow regimes where increased irrigation could further reduce water availability. However, should large scale water transfers upstream of Bangladesh be constructed, these have the potential to reduce flows and divert water away from the delta region depending on the volume and timing of the transfers. This could have significant implications for the delta in terms of saline intrusion, water supply, agriculture and maintaining crucial ecosystems such as the mangrove forests, with serious implications for people's livelihoods in the area. The socio-economic scenarios have a significant impact on water quality, altering nutrient fluxes being transported into the delta region.

Characterization of water quality and simulation of temperature, nutrients, biochemical oxygen demand, and dissolved oxygen in the Wateree River, South Carolina, 1996-98

USGS Publications Warehouse

Feaster, Toby D.; Conrads, Paul

2000-01-01

In May 1996, the U.S. Geological Survey entered into a cooperative agreement with the Kershaw County Water and Sewer Authority to characterize and simulate the water quality in the Wateree River, South Carolina. Longitudinal profiling of dissolved-oxygen concentrations during the spring and summer of 1996 revealed dissolved-oxygen minimums occurring upstream from the point-source discharges. The mean dissolved-oxygen decrease upstream from the effluent discharges was 2.0 milligrams per liter, and the decrease downstream from the effluent discharges was 0.2 milligram per liter. Several theories were investigated to obtain an improved understanding of the dissolved-oxygen dynamics in the upper Wateree River. Data suggest that the dissolved-oxygen concentration decrease is associated with elevated levels of oxygen-consuming nutrients and metals that are flowing into the Wateree River from Lake Wateree. Analysis of long-term streamflow and water-quality data collected at two U.S. Geological Survey gaging stations suggests that no strong correlation exists between streamflow and dissolved-oxygen concentrations in the Wateree River. However, a strong negative correlation does exist between dissolved-oxygen concentrations and water temperature. Analysis of data from six South Carolina Department of Health and Environmental Control monitoring stations for 1980.95 revealed decreasing trends in ammonia nitrogen at all stations where data were available and decreasing trends in 5-day biochemical oxygen demand at three river stations. The influence of various hydrologic and point-source loading conditions on dissolved-oxygen concentrations in the Wateree River were determined by using results from water-quality simulations by the Branched Lagrangian Transport Model. The effects of five tributaries and four point-source discharges were included in the model. Data collected during two synoptic water-quality samplings on June 23.25 and August 11.13, 1997, were used to calibrate and validate the Branched Lagrangian Transport Model. The data include dye-tracer concentrations collected at six locations, stream-reaeration data collected at four locations, and water-quality and water-temperature data collected at nine locations. Hydraulic data for the Branched Lagrangian Transport Model were simulated by using the U.S. Geological Survey BRANCH one-dimensional, unsteady-flow model. Data that were used to calibrate and validate the BRANCH model included time-series of water-level and streamflow data at three locations. The domain of the hydraulic model and the transport model was a 57.3- and 43.5-mile reach of the river, respectively. A sensitivity analysis of the simulated dissolved-oxygen concentrations to model coefficients and data inputs indicated that the simulated dissolved-oxygen concentrations were most sensitive to changes in the boundary concentration inputs of water temperature and dissolved oxygen followed by sensitivity to the change in streamflow. A 35-percent increase in streamflow resulted in a negative normalized sensitivity index, indicating a decrease in dissolved-oxygen concentrations. The simulated dissolved-oxygen concentrations showed no significant sensitivity to changes in model input rate kinetics. To demonstrate the utility of the Branched Lagrangian Transport Model of the Wateree River, the model was used to simulate several hydrologic and water-quality scenarios to evaluate the effects on simulated dissolved-oxygen concentrations. The first scenario compared the 24-hour mean dissolved-oxygen concentrations for August 13, 1997, as simulated during the model validation, with simulations using two different streamflow patterns. The mean streamflow for August 13, 1997, was 2,000 cubic feet per second. Simulations were run using mean streamflows of 1,000 and 1,400 cubic feet per second while keeping the water-quality boundary conditions the same as were used during the validation simulations. When compared t

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

NASA Astrophysics Data System (ADS)

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.

Modelling impacts of climate change and socio-economic change on the Ganga, Brahmaputra, Meghna, Hooghly and Mahanadi river systems in India and Bangladesh.

PubMed

Whitehead, Paul G; Jin, Li; Macadam, Ian; Janes, Tamara; Sarkar, Sananda; Rodda, Harvey J E; Sinha, Rajiv; Nicholls, Robert J

2018-09-15

The Ganga-Brahmaputra-Meghna (GBM) River System, the associated Hooghly River and the Mahanadi River System represent the largest river basins in the world serving a population of over 780 million. The rivers are of vital concern to India and Bangladesh as they provide fresh water for people, agriculture, industry, conservation and support the Delta System in the Bay of Bengal. Future changes in both climate and socio-economics have been investigated to assess whether these will alter river flows and water quality. Climate datasets downscaled from three different Global Climate Models have been used to drive a daily process based flow and water quality model. The results suggest that due to climate change the flows will increase in the monsoon period and also be enhanced in the dry season. However, once socio-economic changes are also considered, increased population, irrigation, water use and industrial development reduce water availability in drought conditions, threatening water supplies and posing a threat to river and coastal ecosystems. This study, as part of the DECCMA (Deltas, vulnerability and Climate Change: Migration and Adaptation) project, also addresses water quality issues, particularly nutrients (N and P) and their transport along the rivers and discharge into the Delta System. Climate will alter flows, increasing flood flows and changing pollution dilution factors in the rivers, as well as other key processes controlling water quality. Socio-economic change will affect water quality, as water diversion strategies, increased population and industrial development alter the water balance and enhance fluxes of nutrients from agriculture, urban centers and atmospheric deposition. Copyright © 2018 Elsevier B.V. All rights reserved.

Modelling of the Water Exchange between Shallow Groundwater and River during bank filtration and changing conditions

NASA Astrophysics Data System (ADS)

Wang, Weishi; Munz, Matthias; Oswald, Sascha E.

2015-04-01

The interaction of river water and groundwater is of importance for the hydrological cycle and water quality in rivers. Moreover, drinking water is often obtained by pumping groundwater in the direct vicinity of rivers, called bank filtration. Typically this implies a considerable dynamics, because changes in river water level and pumping activities will cause varying conditions, and in its effects modified by the local hydrogeology. Numerical modelling can be a tool to study spatial patterns and temporal changes. Often this is limited by model performance, uncertainty of geological structure and lack of sufficient observation values beyond water heads, for example water quality or temperature data. The aim of this research is to model the hydraulic conditions for transient conditions, including a period of substantial re-construction works in the river. Later this will then be used to include the temperature and other water quality data to improve the model performance. As shown from the geological information analysis, the majority of the water volume pumped is from the first and second aquifers, where a strong exchange between the river and groundwater can happen. The implementation of the geological structure is based on 7 main geological profiles and several scattered drilling wells of difference depths. A first model has been built in FEFLOW 6.2 as a steady fluid flow model, while the pilot-points auto-calibration method is used for estimating the hydraulic conductivity of different sediment types, based on water head information of 19 observation wells. Then a transient model during the year 2011-2013 is further calibrated based on estimated hydraulic conductivity. Furthermore, the observation wells are used to make a statistic analysis with the hydrograph of the river to clarify the correlation of changes in river to changes in groundwater.

Environmetric data interpretation to assess the water quality of Maritsa River catchment.

PubMed

Papazova, Petia; Simeonova, Pavlina

2013-01-01

Maritsa River is one of the largest rivers flowing on Bulgarian territory. The quality of its waters is of substantial importance for irrigation, industrial, recreation and domestic use. Besides, part of the river is flowing on Turkish territory and the control and management of the Maritsa catchment is of mutual interst for the neighboring countires. Thus, performing interpretation and modeling of the river water quality is a major environmetric problem. Two multivariate statstical methods (Cluster analysis/CA/and Principal components analysis/PCA/) were applied for model assessment of the water quality of Maritsa River on Bulgarian territory. The study used long-term monitoring data from 21 sampling sites characterized by 8 surface water quality indicators. The application of CA to the indicators results in 3 significant clusters showing the impact of biological, anthropogenic and eutrophication sources. For further assessment of the monitoring data, PCA was implemented, which identified, again,three latent factors confirming, in principle, the clustering output. The latent factors were conditionally named "biologic", "anthropogenic" and "eutrophication" source. Their identification coinside correctly to the location of real pollution sources along the Maritsa River catchment. The linkage of the sampling sites along the river flow by CA identified four special patterns separated by specific tracers levels: biological and anthropogenic major impact for pattern 1, euthrophication major impact for pattern 2, background levels for pattern 3 and eutrophication and agricultural major impact for pattern 4. The apportionment models of the pollution determined the contribution of each one of identified pollution factors to the total concentration of each one of the water quality parameters. Thus, a better risk management of the surface water quality is achieved both on local and national level.

Development of Load Duration Curve System in Data Scarce Watersheds Based on a Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

WANG, J.

2017-12-01

In stream water quality control, the total maximum daily load (TMDL) program is very effective. However, the load duration curves (LDC) of TMDL are difficult to be established because no sufficient observed flow and pollutant data can be provided in data-scarce watersheds in which no hydrological stations or consecutively long-term hydrological data are available. Although the point sources or a non-point sources of pollutants can be clarified easily with the aid of LDC, where does the pollutant come from and to where it will be transported in the watershed cannot be traced by LDC. To seek out the best management practices (BMPs) of pollutants in a watershed, and to overcome the limitation of LDC, we proposed to develop LDC based on a distributed hydrological model of SWAT for the water quality management in data scarce river basins. In this study, firstly, the distributed hydrological model of SWAT was established with the scarce-hydrological data. Then, the long-term daily flows were generated with the established SWAT model and rainfall data from the adjacent weather station. Flow duration curves (FDC) was then developed with the aid of generated daily flows by SWAT model. Considering the goal of water quality management, LDC curves of different pollutants can be obtained based on the FDC. With the monitored water quality data and the LDC curves, the water quality problems caused by the point or non-point source pollutants in different seasons can be ascertained. Finally, the distributed hydrological model of SWAT was employed again to tracing the spatial distribution and the origination of the pollutants of coming from what kind of agricultural practices and/or other human activities. A case study was conducted in the Jian-jiang river, a tributary of Yangtze river, of Duyun city, Guizhou province. Results indicate that this kind of method can realize the water quality management based on TMDL and find out the suitable BMPs for reducing pollutant in a watershed.

Application of a water quality model in the White Cart water catchment, Glasgow, UK.

PubMed

Liu, S; Tucker, P; Mansell, M; Hursthouse, A

2003-03-01

Water quality models of urban systems have previously focused on point source (sewerage system) inputs. Little attention has been given to diffuse inputs and research into diffuse pollution has been largely confined to agriculture sources. This paper reports on new research that is aimed at integrating diffuse inputs into an urban water quality model. An integrated model is introduced that is made up of four modules: hydrology, contaminant point sources, nutrient cycling and leaching. The hydrology module, T&T consists of a TOPMODEL (a TOPography-based hydrological MODEL), which simulates runoff from pervious areas and a two-tank model, which simulates runoff from impervious urban areas. Linked into the two-tank model, the contaminant point source module simulates the overflow from the sewerage system in heavy rain. The widely known SOILN (SOIL Nitrate model) is the basis of nitrogen cycle module. Finally, the leaching module consists of two functions: the production function and the transfer function. The production function is based on SLIM (Solute Leaching Intermediate Model) while the transfer function is based on the 'flushing hypothesis' which postulates a relationship between contaminant concentrations in the receiving water course and the extent to which the catchment is saturated. This paper outlines the modelling methodology and the model structures that have been developed. An application of this model in the White Cart catchment (Glasgow) is also included.

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

NASA Astrophysics Data System (ADS)

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 quantifiable water-related ecosystem services such as water provision (river flows, groundwater recharge and vegetation transpiration), flood regulation or nutrient and sediment retention. This combination of models will be used to carry out scenario analyses on IPCC climate change scenarios as well as various land use scenarios. Results will be presented for a test catchment in the Republic of Ireland.

Modeling hydrodynamics, water quality, and benthic processes to predict ecological effects in Narragansett Bay

EPA Science Inventory

The environmental fluid dynamics code (EFDC) was used to study the three dimensional (3D) circulation, water quality, and ecology in Narragansett Bay, RI. Predictions of the Bay hydrodynamics included the behavior of the water surface elevation, currents, salinity, and temperatur...

CHARACTERIZING PIPE WALL DEMAND: IMPLICATIONS FOR WATER QUALITY MODELING

EPA Science Inventory

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

MEASURING AND MODELING VARIATIONS IN DISTRIBUTION SYSTEM WATER QUALITY

EPA Science Inventory

The authors describe a field study that examined the effects of hydraulic mixing on water quality variations in a distribution system. Conducted at the North Penn Water Authority (average production of 5 mgd and 225 mi of distribution pipe), the study incorporated a field samplin...

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

EPA Science Inventory

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...

Disentangling the Effects of Water Stress on Carbon Acquisition, Vegetative Growth, and Fruit Quality of Peach Trees by Means of the QualiTree Model.

PubMed

Rahmati, Mitra; Mirás-Avalos, José M; Valsesia, Pierre; Lescourret, Françoise; Génard, Michel; Davarynejad, Gholam H; Bannayan, Mohammad; Azizi, Majid; Vercambre, Gilles

2018-01-01

Climate change projections predict warmer and drier conditions. In general, moderate to severe water stress reduce plant vegetative growth and leaf photosynthesis. However, vegetative and reproductive growths show different sensitivities to water deficit. In fruit trees, water restrictions may have serious implications not only on tree growth and yield, but also on fruit quality, which might be improved. Therefore, it is of paramount importance to understand the complex interrelations among the physiological processes involved in within-tree carbon acquisition and allocation, water uptake and transpiration, organ growth, and fruit composition when affected by water stress. This can be studied using process-based models of plant functioning, which allow assessing the sensitivity of various physiological processes to water deficit and their relative impact on vegetative growth and fruit quality. In the current study, an existing fruit-tree model (QualiTree) was adapted for describing the water stress effects on peach ( Prunus persica L. Batsch) vegetative growth, fruit size and composition. First, an energy balance calculation at the fruit-bearing shoot level and a water transfer formalization within the plant were integrated into the model. Next, a reduction function of vegetative growth according to tree water status was added to QualiTree. Then, the model was parameterized and calibrated for a late-maturing peach cultivar ("Elberta") under semi-arid conditions, and for three different irrigation practices. Simulated vegetative and fruit growth variability over time was consistent with observed data. Sugar concentrations in fruit flesh were well simulated. Finally, QualiTree allowed for determining the relative importance of photosynthesis and vegetative growth reduction on carbon acquisition, plant growth and fruit quality under water constrains. According to simulations, water deficit impacted vegetative growth first through a direct effect on its sink strength, and; secondly, through an indirect reducing effect on photosynthesis. Fruit composition was moderately affected by water stress. The enhancements performed in the model broadened its predictive capabilities and proved that QualiTree allows for a better understanding of the water stress effects on fruit-tree functioning and might be useful for designing innovative horticultural practices in a changing climate scenario.

Mapping Ecosystem Services in the Jordan Valley, Jordan

NASA Astrophysics Data System (ADS)

Luz, Ana; Marques, Ana; Ribeiro, Inês; Alho, Maria; Catarina Afonso, Ana; Almeida, Erika; Branquinho, Cristina; Talozi, Samer; Pinho, Pedro

2016-04-01

In the last decade researchers started using ecosystem services as a new framework to understand the relationships between environment and society. Habitat quality and water quality are related with ecosystem services regulation and maintenance, or even provision. According to the Common International Classification of Ecosystem Services (CICES) both habitat quality and water quality are associated with lifecycle maintenance, habitat and gene pool protection, and water conditions, among others. As there is increased pressure on habitats and rivers especially for agricultural development, mapping and evaluating habitat and water quality has important implications for resource management and conservation, as well as for rural development. Here, we model and map habitat and water quality in the Jordan Valley, Jordan. In this study, we aim to identify and analyse ecosystem services both through 1) habitat quality and 2) water quality modelling using InVest, an integrated valuation of ecosystem services and tradeoffs. The data used in this study mainly includes the LULC, Jordan River watershed and main threats and pollutants in the study area, such as agriculture, industry, fish farms and urbanization. Results suggest a higher pressure on natural habitats in the Northern region of the Jordan Valley, where industry is dominant. Agriculture is present along the Jordan Valley and limits the few natural forested areas. Further, water pollution is mainly concentrated in disposal sites due to the low flow of the Jordan River. Our results can help to identify areas where natural resources and water resource management is most needed in the Jordan Valley. Acknowledgements: Transbasin FP7 project

Drinking Water Quality Governance: A Comparative Case Study of Brazil, Ecuador, and Malawi.

PubMed

Kayser, Georgia L; Amjad, Urooj; Dalcanale, Fernanda; Bartram, Jamie; Bentley, Margaret E

2015-04-01

Human health is greatly affected by inadequate access to sufficient and safe drinking water, especially in low and middle-income countries. Drinking water governance improvements may be one way to better drinking water quality. Over the past decade, many projects and international organizations have been dedicated to water governance; however, water governance in the drinking water sector is understudied and how to improve water governance remains unclear. We analyze drinking water governance challenges in three countries-Brazil, Ecuador, and Malawi-as perceived by government, service providers, and civil society organizations. A mixed methods approach was used: a clustering model was used for country selection and qualitative semi-structured interviews were used with direct observation in data collection. The clustering model integrated political, economic, social and environmental variables that impact water sector performance, to group countries. Brazil, Ecuador and Malawi were selected with the model so as to enhance the generalizability of the results. This comparative case study is important because similar challenges are identified in the drinking water sectors of each country; while, the countries represent diverse socio-economic and political contexts, and the selection process provides generalizability to our results. We find that access to safe water could be improved if certain water governance challenges were addressed: coordination and data sharing between ministries that deal with drinking water services; monitoring and enforcement of water quality laws; and sufficient technical capacity to improve administrative and technical management of water services at the local level. From an analysis of our field research, we also developed a conceptual framework that identifies policy levers that could be used to influence governance of drinking water quality on national and sub-national levels, and the relationships between these levers.

Drinking Water Quality Governance: A Comparative Case Study of Brazil, Ecuador, and Malawi

PubMed Central

Kayser, Georgia L.; Amjad, Urooj; Dalcanale, Fernanda; Bartram, Jamie; Bentley, Margaret E.

2015-01-01

Human health is greatly affected by inadequate access to sufficient and safe drinking water, especially in low and middle-income countries. Drinking water governance improvements may be one way to better drinking water quality. Over the past decade, many projects and international organizations have been dedicated to water governance; however, water governance in the drinking water sector is understudied and how to improve water governance remains unclear. We analyze drinking water governance challenges in three countries—Brazil, Ecuador, and Malawi—as perceived by government, service providers, and civil society organizations. A mixed methods approach was used: a clustering model was used for country selection and qualitative semi-structured interviews were used with direct observation in data collection. The clustering model integrated political, economic, social and environmental variables that impact water sector performance, to group countries. Brazil, Ecuador and Malawi were selected with the model so as to enhance the generalizability of the results. This comparative case study is important because similar challenges are identified in the drinking water sectors of each country; while, the countries represent diverse socio-economic and political contexts, and the selection process provides generalizability to our results. We find that access to safe water could be improved if certain water governance challenges were addressed: coordination and data sharing between ministries that deal with drinking water services; monitoring and enforcement of water quality laws; and sufficient technical capacity to improve administrative and technical management of water services at the local level. From an analysis of our field research, we also developed a conceptual framework that identifies policy levers that could be used to influence governance of drinking water quality on national and sub-national levels, and the relationships between these levers. PMID:25798068

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

PubMed

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.

Consequences of land use cover change and precipitation regimes on water quality in a tropical landscape: the case of São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Ribeiro Piffer, P.; Reverberi Tambosi, L.; Uriarte, M.

2017-12-01

One of the most pressing challenges faced by modern societies is ensuring a sufficient supply of water considering the ever-growing conflict between environmental conservation and expansion of agricultural and urban frontiers worldwide. Land use cover change have marked effects on natural landscapes, putting key watershed ecosystem services in jeopardy. We investigated the consequences of land use cover change and precipitation regimes on water quality in the state of São Paulo, Brazil, a landscape that underwent major changes in past century. Water quality data collected bi-monthly between 2000 and 2014 from 229 water monitoring stations was analyzed together with 2011 land use cover maps. We focused on six water quality metrics (dissolved oxygen, total nitrogen, total phosphorus, turbidity, total dissolved solids and fecal coliforms) and used generalized linear mixed models to analyze the data. Models were built at two scales, the entire watershed and a 60 meters riparian buffer along the river network. Models accounted for 46-67% of the variance in water quality metrics and, apart from dissolved oxygen, which reflected land cover composition in riparian buffers, all metrics responded to land use at the watershed scale. Highly urbanized areas had low dissolved oxygen and high fecal coliforms, dissolved solids, phosphorus and nitrogen levels in streams. Pasture was associated with increases in turbidity, while sugarcane plantations significantly increased nitrogen concentrations. Watersheds with high forest cover had greater dissolved oxygen and lower turbidity. Silviculture plantations had little impact on water quality. Precipitation decreased dissolved oxygen and was associated with higher levels of turbidity, fecal coliforms and phosphorus. Results indicate that conversion of forest cover to other land uses had negative impacts on water quality in the study area, highlighting the need for landscape restoration to improve watersheds ecosystem services.

Management of groundwater supply and water quality in the Los Angeles Basin, California

USGS Publications Warehouse

Reichard, E.G.; Crawford, S.M.; Land, M.T.; Paybins, K.S.

1999-01-01

Water use and water needs in the coastal Los Angeles Basin in California have been very closely tied to the development of the region during the last 150 years. The first water wells were drilled in the mid-1800s. Currently about 40% of the water supply (9.4 m3 s-1) in the region is provided by groundwater. Other sources of water supply include reclaimed water and surface water imported from Owens Valley, the Colorado River, and northern California. Increasing groundwater use in the basin led to over-abstraction and seawater instrusion. Because of this, an important component of water management in the area has been the artificial recharge of local, imported, and reclaimed water which is spread in ponds and injected in wells to recharge the aquifer system and control seawater intrusion. The US Geological Survey (USGS) is working co-operatively with the Water Replenishment District of Southern California to evaluate the hydraulic and water-quality effects of these recharge operations and to assess the potential impacts of alternative water-management strategies, including changes in pumping and increases in the use of reclaimed water. As part of this work, the USGS has developed a geographic information system (GIS), collected water-quality and geohydrological data from new and existing wells, and developed a multi-aquifer regional groundwater flow model. Chemical and isotopic data were used to identify the age and source of recharge to groundwater throughout the study area. This information is key to understanding the fate of artificially recharged water and helps define the three-dimensional groundwater flow system. The geohydrological data, especially the geophysical and geological data collected from 11 newly installed multi-completion monitoring wells, were used to redefine the regional hydrostratigraphy. The groundwater flow model is being used to enhance the understanding of the geohydrological system and to quantitatively evaluate new water-management strategies.As part of the work aimed at evaluating the hydraulic and water-quality effects of recharge operations and to assess the potential impacts of alternative water-management strategies, the US Geological Survey (USGS), has developed a geographic information system (GIS), collected water-quality and geohydrological data from new and existing wells, and developed a multi-aquifer regional groundwater flow model. At present, the developed model is being used to enhance the understanding of the geohydrological system and to quantitatively evaluate new water-management strategies.

New steady-state models for water-limited cropping systems using saline irrigation waters: Analytical solutions and applications

USDA-ARS?s Scientific Manuscript database

Due to the diminishing availability of good quality water for irrigation, it is increasingly important that irrigation and salinity management tools be able to target submaximal crop yields and support the use of marginal quality waters. In this work, we present a steady-state irrigated systems mod...

New steady-state models for water-limited cropping systems using saline irrigation waters: Analytical solutions and applications

USDA-ARS?s Scientific Manuscript database

Due to the diminishing availability of good quality water for irrigation, it is increasingly important that irrigation and salinity management tools be able to target submaximal crop yields and support the use of marginal quality waters. In this work, we present a steady-state irrigated systems mode...

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvanian stream

USDA-ARS?s Scientific Manuscript database

Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four ye...

A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region.

PubMed

Hu, X H; Li, Y P; Huang, G H; Zhuang, X W; Ding, X W

2016-05-01

In this study, a Bayesian-based two-stage inexact optimization (BTIO) method is developed for supporting water quality management through coupling Bayesian analysis with interval two-stage stochastic programming (ITSP). The BTIO method is capable of addressing uncertainties caused by insufficient inputs in water quality model as well as uncertainties expressed as probabilistic distributions and interval numbers. The BTIO method is applied to a real case of water quality management for the Xiangxi River basin in the Three Gorges Reservoir region to seek optimal water quality management schemes under various uncertainties. Interval solutions for production patterns under a range of probabilistic water quality constraints have been generated. Results obtained demonstrate compromises between the system benefit and the system failure risk due to inherent uncertainties that exist in various system components. Moreover, information about pollutant emission is accomplished, which would help managers to adjust production patterns of regional industry and local policies considering interactions of water quality requirement, economic benefit, and industry structure.

Assessment and modeling of groundwater quality using WQI and GIS in Upper Egypt area.

PubMed

Rabeiy, Ragab ElSayed

2017-04-04

The continuous growth and development of population need more fresh water for drinking, irrigation, and domestic in arid countries like Egypt. Evaluation the quality of groundwater is an essential study to ensure its suitability for different purposes. In this study, 812 groundwater samples were taken within the middle area of Upper Egypt (Sohag Governorate) to assess the quality of groundwater for drinking and irrigation purposes. Eleven water parameters were analyzed at each groundwater sample (Na + , K + , Ca 2+ , Mg 2+ , HCO 3 - SO 4 2- , Fe 2+ , Mn 2+ , Cl - , electrical conductivity, and pH) to exploit them in water quality evaluation. A classical statistics were applied for the raw data to examine the distribution of physicochemical parameters in the investigated area. The relationship between groundwater parameters was tested using the correlation coefficient where a strong relationship was found between several water parameters such as Ca 2+ and Cl - . Water quality index (WQI) is a mathematical model used to transform many water parameters into a single indicator value which represents the water quality level. Results of WQI showed that 20% of groundwater samples are excellent, 75% are good for drinking, and 7% are very poor water while only 1% of samples are unsuitable for drinking. To test the suitability of groundwater for irrigation, three indices are used; they are sodium adsorption ration (SAR), sodium percentage (Na%), and permeability index (PI). For irrigation suitability, the study proved that most sampling sites are suitable while less than 3% are unsuitable for irrigation. The spatial distribution of the estimated values of WQI, SAR, Na%, PI, and each groundwater parameter was spatially modeled using GIS.

Simplifying and upscaling water resources systems models that combine natural and engineered components

NASA Astrophysics Data System (ADS)

McIntyre, N.; Keir, G.

2014-12-01

Water supply systems typically encompass components of both natural systems (e.g. catchment runoff, aquifer interception) and engineered systems (e.g. process equipment, water storages and transfers). Many physical processes of varying spatial and temporal scales are contained within these hybrid systems models. The need to aggregate and simplify system components has been recognised for reasons of parsimony and comprehensibility; and the use of probabilistic methods for modelling water-related risks also prompts the need to seek computationally efficient up-scaled conceptualisations. How to manage the up-scaling errors in such hybrid systems models has not been well-explored, compared to research in the hydrological process domain. Particular challenges include the non-linearity introduced by decision thresholds and non-linear relations between water use, water quality, and discharge strategies. Using a case study of a mining region, we explore the nature of up-scaling errors in water use, water quality and discharge, and we illustrate an approach to identification of a scale-adjusted model including an error model. Ways forward for efficient modelling of such complex, hybrid systems are discussed, including interactions with human, energy and carbon systems models.

Water quality in the Schuylkill River, Pennsylvania: the potential for long-lead forecasts

NASA Astrophysics Data System (ADS)

Block, P. J.; Peralez, J.

2012-12-01

Prior analysis of pathogen levels in the Schuylkill River has led to a categorical daily forecast of water quality (denoted as red, yellow, or green flag days.) The forecast, available to the public online through the Philadelphia Water Department, is predominantly based on the local precipitation forecast. In this study, we explore the feasibility of extending the forecast to the seasonal scale by associating large-scale climate drivers with local precipitation and water quality parameter levels. This advance information is relevant for recreational activities, ecosystem health, and water treatment (energy, chemicals), as the Schuylkill provides 40% of Philadelphia's water supply. Preliminary results indicate skillful prediction of average summertime water quality parameters and characteristics, including chloride, coliform, turbidity, alkalinity, and others, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic. Water quality parameter trends, including historic land use changes along the river, association with climatic variables, and prediction models will be presented.

Results of a modeling workshop concerning economic and environmental trends and concomitant resource management issues in the Mobile Bay area

USGS Publications Warehouse

Hamilton, David B.; Andrews, Austin K.; Auble, Gregor T.; Ellison, Richard A.; Johnson, Richard A.; Roelle, James E.; Staley, Michael J.

1982-01-01

During the past decade, the southern regions of the U.S. have experienced rapid change which is expected to continue into the foreseeable future. Growth in population, industry, and resource development has been attributed to a variety of advantages such as an abundant and inexpensive labor force, a mild climate, and the availability of energy, water, land, and other natural resources. While this growth has many benefits for the region, it also creates the potential for increased air, water, and solid waste pollution, and modification of natural habitats. A workshop was convened to consider the Mobile Bay area as a site-specific case of growth and its environmental consequences in the southern region. The objectives of the modeling workshop were to: (1) identify major factors of economic development as they relate to growth in the area over the immediate and longer term; (2) identify major environmental and resource management issues associated with this expected growth; and (3) identify and characterize the complex interrelationships among economic and environmental factors. This report summarizes the activities and results of a modeling workshop concerning economic growth and concomitant resource management issues in the Mobile Bay area. The workshop was organized around construction of a simulation model representing the relationships between a series of actions and indicators identified by participants. The workshop model had five major components. An Industry Submodel generated scenarios of growth in several industrial and transportation sectors. A Human Population/Economy Submodel calculated human population and economic variables in response to employment opportunities. A Land Use/Air Quality Submodel tabulated changes in land use, shoreline use, and air quality. A Water Submodel calculated indicators of water quality and quantity for fresh surface water, ground water, and Mobile Bay based on discharge information provided by the Industry and Human Population/Economy Submodels. Finally, a Fish Submodel calculated indicators of habitat quality for finfish and shellfish, utilizing information on water quality and wetlands acreage. The workshop was successful in identifying many of the critical interrelations between components of the Mobile area system. Not all of those interactions, such as the feedback of air quality as a limitation on development, could be incorporated into the workshop model because of the model's broad spatial scale and because of uncertainties or data gaps. Thus, the value of the modeling workshop was in the areas outlines below, rather than in the predictive power of the initial model developed at the workshop. First, participants developed a holistic perspective on the interactions which will determine future economic and environmental trends within the Mobile Bay area. Potential environmental consequences and limitations to grown identified at the workshop included: shoreline and water access; water quality of Mobile Bay; finfish and shellfish habitat quality with respect to dissolved oxygen and coliforms; air quality; and acreage of critical wetland habitat. Second, the model's requirements for specific, quantitative information stimulated supporting analyses, such as economic input-output calculations, which provide additional insight into the Mobile Bay area system. Third, the perspective of the Mobile area as an interacting system was developed in an open, cooperative forum which my provide a foundation for conflict resolution based on common understanding. Finally, the identification of model limitations and uncertainties should be useful in guiding the efficient allocation of future research effort.

Geochemical characterisation of seepage and drainage water quality from two sulphide mine tailings impoundments: Acid mine drainage versus neutral mine drainage

USGS Publications Warehouse

Heikkinen, P.M.; Raisanen, M.L.; Johnson, R.H.

2009-01-01

Seepage water and drainage water geochemistry (pH, EC, O2, redox, alkalinity, dissolved cations and trace metals, major anions, total element concentrations) were studied at two active sulphide mine tailings impoundments in Finland (the Hitura Ni mine and Luikonlahti Cu mine/talc processing plant). The data were used to assess the factors influencing tailings seepage quality and to identify constraints for water treatment. Changes in seepage water quality after equilibration with atmospheric conditions were evaluated based on geochemical modelling. At Luikonlahti, annual and seasonal changes were also studied. Seepage quality was largely influenced by the tailings mineralogy, and the serpentine-rich, low sulphide Hitura tailings produced neutral mine drainage with high Ni. In contrast, drainage from the high sulphide, multi-metal tailings of Luikonlahti represented typical acid mine drainage with elevated contents of Zn, Ni, Cu, and Co. Other factors affecting the seepage quality included weathering of the tailings along the seepage flow path, process water input, local hydrological settings, and structural changes in the tailings impoundment. Geochemical modelling showed that pH increased and some heavy metals were adsorbed to Fe precipitates after net alkaline waters equilibrated with the atmosphere. In the net acidic waters, pH decreased and no adsorption occurred. A combination of aerobic and anaerobic treatments is proposed for Hitura seepages to decrease the sulphate and metal loading. For Luikonlahti, prolonged monitoring of the seepage quality is suggested instead of treatment, since the water quality is still adjusting to recent modifications to the tailings impoundment.

Gulf of Mexico dissolved oxygen model (GoMDOM) research and quality assurance project plan

EPA Science Inventory

An integrated high resolution mathematical modeling framework is being developed that will link hydrodynamic, atmospheric, and water quality models for the northern Gulf of Mexico. This Research and Quality Assurance Project Plan primarily focuses on the deterministic Gulf of Me...

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

USGS Publications Warehouse

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 proportion of good-growth habitat and a sustained period of optimal growth habitat in the summer, without any periods of lethal oxythermal habitat. For Madison and Pearl Lakes, examples of important cool-water fish, particularly game fish, include northern pike (Esox lucius), walleye (Sander vitreus), and black crappie (Pomoxis nigromaculatus); examples of important warm-water fish include bluegill (Lepomis macrochirus), largemouth bass (Micropterus salmoides), and smallmouth bass (Micropterus dolomieu). Sensitivity analyses were completed to understand lake response effects through the use of controlled departures on certain calibrated model parameters and input nutrient loads. These sensitivity analyses also operated as land-use change scenarios because alterations in agricultural practices, for example, could potentially increase or decrease nutrient loads.

The effects of ground-water development on the water supply in the Post Headquarters area, White Sands Missile Range, New Mexico

USGS Publications Warehouse

Kelly, T.E.; Hearne, Glenn A.

1976-01-01

Water-level declines in the Post Headquarters area, White Sands Missile Range, N. Mex., have been accompanied by slight but progressive increases in the concentration of dissolved solids in water withdrawn from the aquifer. Projected water-level declines through 1996 are estimated from a digital simulation model to not exceed 200 feet (61 metres). A conceptual model of water quality provides three potential sources for water that is relatively high in dissolved solids: brine from the Tularosa Basin to the east, slightly saline water beneath the subjacent aquatard, and very slightly saline water from the less permeable units within the aquifer itself. Management of the well field to minimize drawdown and spread the cone of depression would minimize the rate of water-quality deterioration. A well designed monitoring network may provide advance warning of severe or rapid water-quality deterioration.. The Soledad Canyon area 10 miles (16.1 kilometres) south of the Post Headquarters offers the greatest potential for development of additional water supplies.

Evaluating water management strategies with the Systems Impact Assessment Model: SIAM version 4

USGS Publications Warehouse

Bartholow, John M.; Heasley, John; Hanna, Blair; Sandelin, Jeff; Flug, Marshall; Campbell, Sharon; Henriksen, Jim; Douglas, Aaron

2005-01-01

The apparent disparity between restoration benefits and costs for the Klamath River may suggest to some that water resources on the Klamath be reallocated to environmentally friendly nonmarket uses. The economic analysis rests in part on the information made available to the survey designers by the biological, hydrologic, and water quality data incorporated in The System Impact Assessment Model (SIAM). It is our hope that SIAM can be used to improve the river's water quality and fishery, and strengthen the important regional economy.

Enhancements to the EPANET-RTX (Real-Time Analytics) ...

EPA Pesticide Factsheets

Technical brief and software The U.S. Environmental Protection Agency (EPA) developed EPANET-RTX as a collection of object-oriented software libraries comprising the core data access, data transformation, and data synthesis (real-time analytics) components of a real-time hydraulic and water quality modeling system. While EPANET-RTX uses the hydraulic and water quality solvers of EPANET, the object libraries are a self-contained set of building blocks for software developers. “Real-time EPANET” promises to change the way water utilities, commercial vendors, engineers, and the water community think about modeling.

Social Perception of Public Water Supply Network and Groundwater Quality in an Urban Setting Facing Saltwater Intrusion and Water Shortages

NASA Astrophysics Data System (ADS)

Alameddine, Ibrahim; Jawhari, Gheeda; El-Fadel, Mutasem

2017-04-01

Perceptions developed by consumers regarding the quality of water reaching their household can affect the ultimate use of the water. This study identified key factors influencing consumers' perception of water quality in a highly urbanized coastal city, experiencing chronic water shortages, overexploitation of groundwater, and accelerated saltwater intrusion. Household surveys were administered to residents to capture views and perceptions of consumed water. Concomitantly, groundwater and tap water samples were collected and analyzed at each residence for comparison with perceptions. People's rating of groundwater quality was found to correlate to the measured water quality both in the dry and wet seasons. In contrast, perceptions regarding the water quality of the public water supply network did not show any correlation with the measured tap water quality indicators. Logistic regression models developed to predict perception based on salient variables indicated that age, apartment ownership, and levels of total dissolved solids play a significant role in shaping perceptions regarding groundwater quality. Perceptions concerning the water quality of the public water supply network appeared to be independent of the measured total dissolved solids levels at the tap but correlated to those measured in the wells. The study highlights misconceptions that can arise as a result of uncontrolled cross-connections of groundwater to the public supply network water and the development of misaligned perceptions based on prior consumption patterns, water shortages, and a rapidly salinizing groundwater aquifer.

Social Perception of Public Water Supply Network and Groundwater Quality in an Urban Setting Facing Saltwater Intrusion and Water Shortages.

PubMed

Alameddine, Ibrahim; Jawhari, Gheeda; El-Fadel, Mutasem

2017-04-01

Perceptions developed by consumers regarding the quality of water reaching their household can affect the ultimate use of the water. This study identified key factors influencing consumers' perception of water quality in a highly urbanized coastal city, experiencing chronic water shortages, overexploitation of groundwater, and accelerated saltwater intrusion. Household surveys were administered to residents to capture views and perceptions of consumed water. Concomitantly, groundwater and tap water samples were collected and analyzed at each residence for comparison with perceptions. People's rating of groundwater quality was found to correlate to the measured water quality both in the dry and wet seasons. In contrast, perceptions regarding the water quality of the public water supply network did not show any correlation with the measured tap water quality indicators. Logistic regression models developed to predict perception based on salient variables indicated that age, apartment ownership, and levels of total dissolved solids play a significant role in shaping perceptions regarding groundwater quality. Perceptions concerning the water quality of the public water supply network appeared to be independent of the measured total dissolved solids levels at the tap but correlated to those measured in the wells. The study highlights misconceptions that can arise as a result of uncontrolled cross-connections of groundwater to the public supply network water and the development of misaligned perceptions based on prior consumption patterns, water shortages, and a rapidly salinizing groundwater aquifer.

Triangle area water supply monitoring project, October 1988 through September 2001, North Carolina -- description of the water-quality network, sampling and analysis methods, and quality-assurance practices

USGS Publications Warehouse

Oblinger, Carolyn J.

2004-01-01

The Triangle Area Water Supply Monitoring Project was initiated in October 1988 to provide long-term water-quality data for six area water-supply reservoirs and their tributaries. In addition, the project provides data that can be used to determine the effectiveness of large-scale changes in water-resource management practices, document differences in water quality among water-supply types (large multiuse reservoir, small reservoir, run-of-river), and tributary-loading and in-lake data for water-quality modeling of Falls and Jordan Lakes. By September 2001, the project had progressed in four phases and included as many as 34 sites (in 1991). Most sites were sampled and analyzed by the U.S. Geological Survey. Some sites were already a part of the North Carolina Division of Water Quality statewide ambient water-quality monitoring network and were sampled by the Division of Water Quality. The network has provided data on streamflow, physical properties, and concentrations of nutrients, major ions, metals, trace elements, chlorophyll, total organic carbon, suspended sediment, and selected synthetic organic compounds. Project quality-assurance activities include written procedures for sample collection, record management and archive, collection of field quality-control samples (blank samples and replicate samples), and monitoring the quality of field supplies. In addition to project quality-assurance activities, the quality of laboratory analyses was assessed through laboratory quality-assurance practices and an independent laboratory quality-control assessment provided by the U.S. Geological Survey Branch of Quality Systems through the Blind Inorganic Sample Project and the Organic Blind Sample Project.

Integrating Hydrologic and Water Quality Models as a Decision Support Tool for Implementation of Low Impact Development in a Coastal Urban Watershed under Climate Variability and Sea Level Rise

NASA Astrophysics Data System (ADS)

Chang, N. B.

2016-12-01

Many countries concern about development and redevelopment efforts in urban regions to reduce the flood risk by considering hazards such as high-tide events, storm surge, flash floods, stormwater runoff, and impacts of sea level rise. Combining these present and future hazards with vulnerable characteristics found throughout coastal communities such as majority low-lying areas and increasing urban development, create scenarios for increasing exposure of flood hazard. As such, the most vulnerable areas require adaptation strategies and mitigation actions for flood hazard management. In addition, in the U.S., Numeric Nutrient Criteria (NNC) are a critical tool for protecting and restoring the designated uses of a waterbody with regard to nitrogen and phosphorus pollution. Strategies such as low impact development (LID) have been promoted in recent years as an alternative to traditional stormwater management and drainage to control both flooding and water quality impact. LID utilizes decentralized multifunctional site designs and incorporates on-site storm water management practices rather than conventional storm water management approaches that divert flow toward centralized facilities. How to integrate hydrologic and water quality models to achieve the decision support becomes a challenge. The Cross Bayou Watershed of Pinellas County in Tampa Bay, a highly urbanized coastal watershed, is utilized as a case study due to its sensitivity to flood hazards and water quality management within the watershed. This study will aid the County, as a decision maker, to implement its stormwater management policy and honor recent NNC state policy via demonstration of an integrated hydrologic and water quality model, including the Interconnected Channel and Pond Routing Model v.4 (ICPR4) and the BMPTRAIN model as a decision support tool. The ICPR4 can be further coupled with the ADCIRC/SWAN model to reflect the storm surge and seal level rise in coastal regions.

Literature Review of Marine Wetland and Estuarine Water Quality and Ecosystem Models.

DTIC Science & Technology

1980-07-01

for water quality models be- cause it limits light penetration and thus photosynthesis . Also, many pollutants attach readily to sediment particles... photosynthesis and respiration or decomposition of bottom muds, and sink terms for BOD due to sedimentation and/or adsorbtion. These early models did...Forcings include temperature, light (for photosynthesis ), wind (for reaeration), waste loading (for BOD), as well as the time-dependent tidal and nontidal

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Hydrology and water quality of Shell Lake, Washburn County, Wisconsin, with special emphasis on the effects of diversion and changes in water level on the water quality of a shallow terminal lake

USGS Publications Warehouse

Juckem, Paul F.; Robertson, Dale M.

2013-01-01

Shell Lake is a relatively shallow terminal lake (tributaries but no outlets) in northwestern Wisconsin that has experienced approximately 10 feet (ft) of water-level fluctuation over more than 70 years of record and extensive flooding of nearshore areas starting in the early 2000s. The City of Shell Lake (City) received a permit from the Wisconsin Department of Natural Resources in 2002 to divert water from the lake to a nearby river in order to lower water levels and reduce flooding. Previous studies suggested that water-level fluctuations were driven by long-term cycles in precipitation, evaporation, and runoff, although questions about the lake’s connection with the groundwater system remained. The permit required that the City evaluate assumptions about lake/groundwater interactions made in previous studies and evaluate the effects of the water diversion on water levels in Shell Lake and other nearby lakes. Therefore, a cooperative study between the City and U.S. Geological Survey (USGS) was initiated to improve the understanding of the hydrogeology of the area and evaluate potential effects of the diversion on water levels in Shell Lake, the surrounding groundwater system, and nearby lakes. Concerns over deteriorating water quality in the lake, possibly associated with changes in water level, prompted an additional cooperative project between the City and the USGS to evaluate efeffects of changes in nutrient loading associated with changes in water levels on the water quality of Shell Lake. Numerical models were used to evaluate how the hydrology and water quality responded to diversion of water from the lake and historical changes in the watershed. The groundwater-flow model MODFLOW was used to simulate groundwater movement in the area around Shell Lake, including groundwater/surface-water interactions. Simulated results from the MODFLOW model indicate that groundwater flows generally northward in the area around Shell Lake, with flow locally converging toward the lake. Total groundwater inflow to Shell Lake is small (approximately 5 percent of the water budget) compared with water entering the lake from precipitation (83 percent) and surface-water runoff (13 percent). The MODFLOW model also was used to simulate average annual hydrologic conditions from 1949 to 2009, including effects of the removal of 3 billion gallons of water during 2003–5. The maximum decline in simulated average annual water levels for Shell Lake due to the diversion alone was 3.3 ft at the end of the diversion process in 2005. Model simulations also indicate that although water level continued to decline through 2009 in response to local weather patterns (local drought), the effects of the diversion decreased after the diversion ceased; that is, after 4 years of recovery (2006–9), drawdown attributable to the diversion alone decreased by about 0.6 ft because of increased groundwater inflow and decreased lake-water outflow to groundwater caused by the artificially lower lake level. A delayed response in drawdown of less than 0.5 ft was transmitted through the groundwater-flow system to upgradient lakes. This relatively small effect on upgradient lakes is attributed in part to extensive layers of shallow clay that limit lake/groundwater interaction in the area. Data collected in the lake indicated that Shell Lake is polymictic (characterized by frequent deep mixing) and that its productivity is limited by the amount of phosphorus in the lake. The lake was typically classified as oligotrophic-mesotrophic in June, mesotrophic in July, and mesotrophic-eutrophic in August. In polymictic lakes like Shell Lake, phosphorus released from the sediments is not trapped near the bottom of the lake but is intermittently released to the shallow water, resulting in deteriorating water quality as summer progresses. Because the productivity of Shell Lake is limited by phosphorus, the sources of phosphorus to the lake were quantified, and the response in water quality to changes in phosphorus inputs were evaluated by means of eutrophication models. During 2009, the total input of phosphorus to Shell Lake was 1,730 pounds (lb), of which 1,320 lb came from external sources (76 percent) and 414 lb came from internal loading from sediments in the lake (24 percent). The largest external source was from surface-water runoff, which delivered about 52 percent of the total phosphorus load compared with about 13 percent of the water input. The second largest source was from precipitation (wetfall and dryfall), which delivered 19 percent of the load compared to about 83 percent of the water input. Contributions from septic systems and groundwater accounted for about 3 and 2 percent, respectively. Increased runoff raises water levels in the lake but does not necessarily increase phosphorus loading because phosphorus concentrations in the tributaries decline during increased flow, possibly because of shorter retention times in upstream wetlands. Phosphorus loading to the lake in 2009 represented what occurred after a series of dry years; therefore, this information was combined with data from 2011, a wet year, to estimate phosphorus loading during a range of hydrologic conditions by estimating loading from each component of the phosphorus budget for each year from 1949 to 2011. Comparisons of historical water-quality records with historical water levels and applications of a hydrodynamic model (Dynamic Lake Model, DLM) and empirical eutrophication models were used to understand how changes in water level and the coinciding changes in phosphorus loading affect the water quality of Shell Lake. DLM simulations indicate that large changes in water level (approximately 10 ft) affect the persistence of stratification in the lake. During periods with low water levels, the lake is a well-mixed, polymictic system, with water quality degrading slightly as summer progresses. During periods with high water levels, the lake is more stratified, and phosphorus from internal loading is trapped in the hypolimnion and released later in summer, which results in more extreme seasonality in water quality and better clarity in early summer. Results of eutrophication model simulations using a range in external phosphorus inputs illustrate how water quality in Shell Lake (phosphorus and chlorophyll a concentrations and Secchi depths) responds to changes in external phosphorus loading. Results indicate that a 50-percent reduction in external loading from that measured in 2009 would be required to change phosphorus concentrations from 0.018 milligram per liter (mg/L) (measured in 2009) to 0.012 mg/L (estimated for the mid-1800s from analysis of diatoms in sediment cores). Such reductions in phosphorus loading cannot be accomplished by targeting septic systems or internal loading alone because septic systems contribute only about 3 percent of the phosphorus input to the lake, and internal loading from the sediments of Shell Lake contributes only about 25 percent of phosphorus input. Complete elimination of phosphorus from septic systems and internal loading would decrease the phosphorus concentrations in the lake by 0.003–0.004 mg/L. Therefore, reducing phosphorus concentration in the lake more than by 0.004 mg/L requires decreasing phosphorus loading from surface-water contributions, primarily runoff to the lake. Reconstructed changes in water quality from 1860 to 2010, based on changes in the diatom communities archived in the sediments and eutrophication model simulations, suggest that anthropogenic changes in the watershed (sawmill construction in 1881; the establishment of the village of Shell Lake; and land-use changes in the 1920s, including increased agriculture) had a much larger effect on water quality than the natural changes associated with fluctuations in water level. Although the effects of natural changes in water level on water quality appear to be small, changes in water level do have a modest effect on water quality, primarily manifested as small improvements during higher water levels. Fluctuations in water level, however, have a larger effect on the seasonality of water-quality patterns, with better water quality, especially increased Secchi depths, in early summer during years with high water levels.

Mass imbalances in EPANET water-quality simulations

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Effects of tillage and application rate on atrazine transport to subsurface drainage: Evaluation of RZWQM using a six-year field study

USDA-ARS?s Scientific Manuscript database

Well-tested agricultural system models can improve our understanding of the water quality effects of management practices under different conditions. The Root Zone Water Quality Model (RZWQM) has been tested under a variety of conditions. However, the current model’s ability to simulate pesticide tr...

Sustainability of High Intensity Forest Management with Respect to Water QuaIity and Site Nutrient Reserves

Treesearch

Virginia R. Tolbert; Carl C. Trettin; Dale W. Johnson; John W. Parsons; Allan E. Houston; David A. Mays

2001-01-01

Ensuring sustainability of intensively managed woody crops requires determining soil and water quality effects using a combination of field data and modeling projections. Plot- and catchrnent-scale research, models, and meta-analyses are addressing nutrient availability, site quality, and measures to increase short-rotation woody crop (SRWC) productivity and site...

ENHANCED STREAM WATER QUALITY MODELS QUAL2E AND QUAL2E-UNCAS: DOCUMENTATION AND USER MANUAL

EPA Science Inventory

The manual is a major revision of the original QUAL2E program documentation released in 1985. It includes a description of the recent modifications and improvements to the widely used water quality models QUAL-II and QUAL2E. The enhancements include an extensive capability for un...

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

ERIC Educational Resources Information Center

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…

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

ERIC Educational Resources Information Center

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,…

Water-quality data of soil water from three watersheds, Shenandoah National Park, Virginia, 1999-2000

USGS Publications Warehouse

Rice, Karen C.; Maben, Suzanne W.; Webb, James R.

2001-01-01

Data on the chemical composition of soil-water samples were collected quarterly from three watersheds in Shenandoah National Park, Virginia, from September 1999 through July 2000. The soil-water samples were analyzed for specific conductance and concentrations of sodium, potassium, calcium, magnesium, ammonium, chloride, nitrate, sulfate, acid-neutralizing capacity, silica, and total monomeric aluminum. The soil-water data presented in this report can be used to support water-quality modeling of the response of streams to episodic acidification. Laboratory analytical data as well as laboratory quality-assurance information also are presented.

Water Quality and Hydrology of Silver Lake, Barron County, Wisconsin, With Special Emphasis on Responses of a Terminal Lake to Changes in Phosphorus Loading and Water Level

USGS Publications Warehouse

Robertson, Dale M.; Rose, William J.; Fitzpatrick, Faith A.

2009-01-01

Silver Lake is typically an oligotrophic-to-mesotrophic, soft-water, terminal lake in northwestern Wisconsin. A terminal lake is a closed-basin lake with surface-water inflows but no surface-water outflows to other water bodies. After several years with above-normal precipitation, very high water levels caused flooding of several buildings near the lake and erosion of soil around much of the shoreline, which has been associated with a degradation in water quality (increased phosphorus and chlorophyll a concentrations and decreased water clarity). To gain a better understanding of what caused the very high water levels and degradation in water quality and collect information to better understand the lake and protect it from future degradation, the U.S. Geological Survey did a detailed study from 2004 to 2008. This report describes results of the study; specifically, lake-water quality, historical changes in water level, water and phosphorus budgets for the two years monitored in the study, results of model simulations that demonstrate how changes in phosphorus inputs affect lake-water quality, and the relative importance of changes in hydrology and changes in the watershed to the water quality of the lake. From 1987 to about 1996, water quality in Silver Lake was relatively stable. Since 1996, however, summer average total phosphorus concentrations increased from about 0.008 milligrams per liter (mg/L) to 0.018 mg/L in 2003, before decreasing to 0.011 mg/L in 2008. From 1996 to 2003, Secchi depths decreased from about 14 to 7.4 feet, before increasing to about 19 feet in 2008. Therefore, Silver Lake is typically classified as oligotrophic to mesotrophic; however, during 2002-4, the lake was classified as mesotrophic to eutrophic. Because productivity in Silver Lake is limited by phosphorus, phosphorus budgets for the lake were constructed for monitoring years 2005 and 2006. The average annual input of phosphorus was 216 pounds: 78 percent from tributary and nearshore runoff and 22 percent from atmospheric deposition. Because Silver Lake is hydraulically mounded above the local groundwater system, little or no input of phosphorus to the lake is from groundwater and septic systems. Silver Lake had previously been incorrectly described as a groundwater flowthrough lake. Phosphorus budgets were constructed for a series of dry years (low water levels) and a series of wet years (high water levels). About 6 times more phosphorus was input to the lake during wet years with high water levels than during the dry years. Phosphorus from erosion represented 13-20 percent of the phosphorus input during years with very high water levels. Results from the Canfield and Bachman eutrophication model and Carlson trophic state index equations demonstrated that water quality in Silver Lake directly responds to changes in external phosphorus input, with the percent change in chlorophyll a being about 80 percent of the percent change in total phosphorus input and the change in Secchi depth and total phosphorus concentrations being about 40 and 50 percent of the percent change in input, respectively. Therefore, changes in phosphorus input should impact water quality. Specific scenarios were simulated with the models to describe the effects of natural (climate-driven) and anthropogenic (human-induced) changes. Results of these scenarios demonstrated that several years of above-normal precipitation cause sustained high water levels and a degradation in water quality, part of which is due to erosion of the shoreline. Results also demonstrated that 1) changes in tributary and nearshore runoff have a dramatic effect on lake-water quality, 2) diverting water into the lake to increase the water level is expected to degrade the water quality, and 3) removal of water to decrease the water level of the lake is expected to have little effect on water quality. Fluctuations in water levels since 1967, when records began for the lake, are representative

Effects of flood control and other reservoir operations on the water quality of the lower Roanoke River, North Carolina

USGS Publications Warehouse

Garcia, Ana Maria

2012-01-01

The Roanoke River is an important natural resource for North Carolina, Virginia, and the Nation. Flood plains of the lower Roanoke River, which extend from Roanoke Rapids Dam to Batchelor Bay near Albemarle Sound, support a large and diverse population of nesting birds, waterfowl, freshwater and anadromous fish, and other wildlife, including threatened and endangered species. The flow regime of the lower Roanoke River is affected by a number of factors, including flood-management operations at the upstream John H. Kerr Dam and Reservoir. A three-dimensional, numerical water-quality model was developed to explore links between upstream flows and downstream water quality, specifically in-stream dissolved-oxygen dynamics. Calibration of the hydrodynamics and dissolved-oxygen concentrations emphasized the effect that flood-plain drainage has on water and oxygen levels, especially at locations more than 40 kilometers away from the Roanoke Rapids Dam. Model hydrodynamics were calibrated at three locations on the lower Roanoke River, yielding coefficients of determination between 0.5 and 0.9. Dissolved-oxygen concentrations were calibrated at the same sites, and coefficients of determination ranged between 0.6 and 0.8. The model has been used to quantify relations among river flow, flood-plain water level, and in-stream dissolved-oxygen concentrations in support of management of operations of the John H. Kerr Dam, which affects overall flows in the lower Roanoke River. Scenarios have been developed to mitigate the negative effects that timing, duration, and extent of flood-plain inundation may have on vegetation, wildlife, and fisheries in the lower Roanoke River corridor. Under specific scenarios, the model predicted that mean dissolved-oxygen concentrations could be increased by 15 percent by flow-release schedules that minimize the drainage of anoxic flood-plain waters. The model provides a tool for water-quality managers that can help identify options that improve water quality and protect the aquatic habitat of the Roanoke River.

USING BAYESIAN SPATIAL MODELS TO FACILITATE WATER QUALITY MONITORING

EPA Science Inventory

The Clean Water Act of 1972 requires states to monitor the quality of their surface water. The number of sites sampled on streams and rivers varies widely by state. A few states are now using probability survey designs to select sites, while most continue to rely on other proce...

Spatial Optimization of Cropping Pattern in an Agricultural Watershed for Food and Biofuel Production with Minimum Downstream Pollution

NASA Astrophysics Data System (ADS)

Pv, F.; Sudheer, K.; Chaubey, I.; RAJ, C.; Her, Y.

2013-05-01

Biofuel is considered to be a viable alternative to meet the increasing fuel demand, and therefore many countries are promoting agricultural activities that help increase production of raw material for biofuel production. Mostly, the biofuel is produced from grain based crops such as Corn, and it apparently create a shortage in food grains. Consequently, there have been regulations to limit the ethanol production from grains, and to use cellulosic crops as raw material for biofuel production. However, cultivation of such cellulosic crops may have different effects on water quality in the watershed. Corn stover, one of the potential cellulosic materials, when removed from the agricultural field for biofuel production, causes a decrease in the organic nutrients in the field. This results in increased use of pesticides and fertilizers which in turn affect the downstream water quality due to leaching of the chemicals. On the contrary, planting less fertilizer-intensive cellulosic crops, like Switch Grass and Miscanthus, is expected to reduce the pollutant loadings from the watershed. Therefore, an ecologically viable land use scenario would be a mixed cropping of grain crops and cellulosic crops, that meet the demand for food and biofuel without compromising on the downstream water quality. Such cropping pattern can be arrived through a simulation-optimization framework. Mathematical models can be employed to evaluate various management scenarios related to crop production and to assess its impact on water quality. Soil and Water Assessment Tool (SWAT) model is one of the most widely used models in this context. SWAT can simulate the water and nutrient cycles, and also quantify the long-term impacts of land management practices, in a watershed. This model can therefore help take decisions regarding the type of cropping and management practices to be adopted in the watershed such that the water quality in the rivers is maintained at acceptable level. In this study, it is proposed to link SWAT model with an optimization algorithm, whose objective is to identify the optimal cropping pattern that results in maximum biomass production for biofuel generation as well as a minimum guaranteed amount of grain production. The optimal allocation ensures that the downstream water quality in the river is within a desirable limit. The study employed probabilistic information in order to address the uncertainty in model simulations. The residual variance of the model is used to transform the deterministic simulations in to probabilistic information. The proposed framework is illustrated using data pertaining to an agricultural watershed in the USA. The preliminary results of the study are encouraging and suggest that an appropriate combination of Corn, Soyabean, Miscanthus, Switch Grass and Pasture land can be arrived at through the developed framework. The placement of Miscanthus and Switch Grass in the watershed help improve the downstream water quality, while Corn and Soyabean makes it deteriorated. The spatial allocation of these crops therefore certainly plays a major role in the downstream water quality.

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

PubMed

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.

Modeling and evaluation of compliance to water quality regulations in bathing areas on the Daoulas catchment and estuary (France).

PubMed

Bougeard, M; Le Saux, J C; Jouan, M; Durand, G; Pommepuy, M

2010-01-01

The microbiological quality of waters in estuaries determines their acceptability for recreational uses. Microbiological contamination often results from urban wastewater discharges or non-point source pollution (manure spreading), and can cause bathing zones to be closed. European regulations (EC/7/2006) have proposed standards (500 E. coli/100 ml) for the acceptability areas for bathing. In this study, two models were associated to simulate contamination: SWAT on a catchment and MARS 2D in the downstream estuary. After river flow calibration and validation, two scenarios were simulated in SWAT, and E. coli fluxes obtained at the main outlet of the catchment were then introduced into MARS 2D to follow E. coli concentrations in the estuary. An annual evaluation of compliance to bathing area water quality standards was then calculated, linked with daily rainfall classes. Water quality in the estuary was below the standard on 13 days, including 5 days with rainfall superior to 10 mm, due to faecal contamination from soil leaching by rain, and 5 days with rainfall ranging from 0.1 to 5 mm/day, due to the high frequency of this level of rainfall. To conclude, this study allowed us to demonstrate the efficiency of models to gain a better understanding on water quality degradation factors.

Monitoring-well network and sampling design for ground-water quality, Wind River Indian Reservation, Wyoming

USGS Publications Warehouse

Mason, Jon P.; Sebree, Sonja K.; Quinn, Thomas L.

2005-01-01

The Wind River Indian Reservation, located in parts of Fremont and Hot Springs Counties, Wyoming, has a total land area of more than 3,500 square miles. Ground water on the Wind River Indian Reservation is a valuable resource for Shoshone and Northern Arapahoe tribal members and others who live on the Reservation. There are many types of land uses on the Reservation that have the potential to affect the quality of ground-water resources. Urban areas, rural housing developments, agricultural lands, landfills, oil and natural gas fields, mining, and pipeline utility corridors all have the potential to affect ground-water quality. A cooperative study was developed between the U.S. Geological Survey and the Wind River Environmental Quality Commission to identify areas of the Reservation that have the highest potential for ground-water contamination and develop a comprehensive plan to monitor these areas. An arithmetic overlay model for the Wind River Indian Reservation was created using seven geographic information system data layers representing factors with varying potential to affect ground-water quality. The data layers used were: the National Land Cover Dataset, water well density, aquifer sensitivity, oil and natural gas fields and petroleum pipelines, sites with potential contaminant sources, sites that are known to have ground-water contamination, and National Pollutant Discharge Elimination System sites. A prioritization map for monitoring ground-water quality on the Reservation was created using the model. The prioritization map ranks the priority for monitoring ground-water quality in different areas of the Reservation as low, medium, or high. To help minimize bias in selecting sites for a monitoring well network, an automated stratified random site-selection approach was used to select 30 sites for ground-water quality monitoring within the high priority areas. In addition, the study also provided a sampling design for constituents to be monitored, sampling frequency, and a simple water-table level observation well network.

The economics of water reuse and implications for joint water quality-quantity management

NASA Astrophysics Data System (ADS)

Kuwayama, Y.

2015-12-01

Traditionally, economists have treated the management of water quality and water quantity as separate problems. However, there are some water management issues for which economic analysis requires the simultaneous consideration of water quality and quantity policies and outcomes. Water reuse, which has expanded significantly over the last several decades, is one of these issues. Analyzing the cost effectiveness and social welfare outcomes of adopting water reuse requires a joint water quality-quantity optimization framework because, at its most basic level, water reuse requires decision makers to consider (a) its potential for alleviating water scarcity, (b) the quality to which the water should be treated prior to reuse, and (c) the benefits of discharging less wastewater into the environment. In this project, we develop a theoretical model of water reuse management to illustrate how the availability of water reuse technologies and practices can lead to a departure from established rules in the water resource economics literature for the optimal allocation of freshwater and water pollution abatement. We also conduct an econometric analysis of a unique dataset of county-level water reuse from the state of Florida over the seventeen-year period between 1996 and 2012 in order to determine whether water quality or scarcity concerns drive greater adoption of water reuse practices.

Simulation of streamflow and water quality in the White Clay Creek subbasin of the Christina River Basin, Pennsylvania and Delaware, 1994-98

USGS Publications Warehouse

Senior, Lisa A.; Koerkle, Edward H.

2003-01-01

The Christina River Basin drains 565 square miles (mi2) in Pennsylvania, Maryland, and Delaware. Water from the basin is used for recreation, drinking water supply, and to support aquatic life. The Christina River Basin includes the major subbasins of Brandywine Creek, White Clay Creek, and Red Clay Creek. The White Clay Creek is the second largest of the subbasins and drains an area of 108 mi2. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the streams. A multi-agency water-quality management strategy included a modeling component to evaluate the effects of point and nonpoint-source contributions of nutrients and suspended sediment on stream water quality. To assist in non point-source evaluation, four independent models, one for each of the three major subbasins and for the Christina River, were developed and calibrated using the model code Hydrological Simulation Program—Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in smaller subbasins predominantly covered by one land use following a nonpoint-source monitoring plan. Under this plan, stormflow and base- flow samples were collected during 1998 at two sites in the White Clay Creek subbasin and at nine sites in the other subbasins.The HSPF model for the White Clay Creek Basin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into 17 reaches draining areas that ranged from 1.37 to 13 mi2. Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the White Clay Creek Basin are agricultural, forested, residential, and urban.The hydrologic component of the model was run at an hourly time step and primarily calibrated using streamflow data from two U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Additional calibration was done using data from two other USGS streamflow-measurement stations with periods of record shorter than the calibration period. Daily precipitation data from two National Oceanic and Atmospheric Administration (NOAA) gages and hourly precipitation and other meteorological data for one NOAA gage were used for model input. The difference between simulated and observed streamflow volume ranged from -0.9 to 1.8 percent for the 4-year period at the two calibration sites with 4-year records. Annual differences between observed and simulated streamflow generally were greater than the overall error. For example, at a site near the bottom of the basin (drainage area of 89.1 mi2), annual differences between observed and simulated streamflow ranged from -5.8 to 14.4 percent and the overall error for the 4-year period was -0.9 percent. Calibration errors for 36 storm periods at the two calibration sites for total volume, low-flowrecession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were within the recommended criteria of 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the hourly rainfall data.The water-quality component of the model was calibrated using data collected by the USGS and state agencies at three USGS streamflow-measurement stations with variable water-quality monitoring periods ending October 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspended-sediment concentrations, although suspended solids may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulation. Comparison of observed to simulated loads for up to five storms in 1998 at each of the two nonpoint-source monitoring sites in the White Clay Creek Basin indicate that simulation error is commonly as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved nutrients than for particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria, with much larger errors possible for individual events. The accuracy of the water-quality calibration under stormflow conditions is limited by the relatively small amount of water-quality data available for the White Clay Creek Basin.Users of the White Clay Creek HSPF model should be aware of model limitations and consider the following if the model is used for predictive purposes: streamflow and water quality for individual storm events may not be well simulated, but the model performance is reasonable when evaluated over longer periods of time; the observed flow-duration curve for the simulation period is similar to the long-term flow-duration curve at White Clay Creek near Newark, Del., indicating that the calibration period is representative of all but highest 0.1 percent and lowest 0.1 percent of flows at that site; relative errors in streamflow and water-quality simulations are greater for smaller drainage areas than for larger areas; and calibration for water-quality was based on sparse data.

Predicting Bacteria Removal by Enhanced Stormwater Control Measures (SCMs) at the Watershed Scale

NASA Astrophysics Data System (ADS)

Wolfand, J.; Bell, C. D.; Boehm, A. B.; Hogue, T. S.; Luthy, R. G.

2017-12-01

Urban stormwater is a major cause of water quality impairment, resulting in surface waters that fail to meet water quality standards and support their designated uses. Fecal indicator bacteria are present in high concentrations in stormwater and are strictly regulated in receiving waters; yet, their fate and transport in urban stormwater is poorly understood. Stormwater control measures (SCMs) are often used to treat, infiltrate, and release urban runoff, but field measurements show that the removal of bacteria by these structural solutions is limited (median log removal = 0.24, n = 370). Researchers have therefore looked to improve bacterial removal by enhancing SCMs through alterations in flow regimes or adding geomedia such as biochar. The present research seeks to develop a model to predict removal of fecal indicator bacteria by enhanced SCMs at the watershed scale in a semi-arid climate. Using the highly developed Ballona Creek watershed (290 km2) located in Los Angeles County as a case study, a hydrologic model is coupled with a stochastic water quality model to predict E. coli concentration near the outfall of the Ballona Creek, Santa Monica Bay. A hydrologic model was developed using EPA SWMM, calibrated for flow from water year 1998-2006 (NSE = 0.94; R2 = 0.94), and validated from water year 2007-2015 (NSE = 0.90; R2 = 0.93). This bacterial loading model was then linked to EPA SUSTAIN and a SCM bacterial removal script to simulate log removal of bacteria by various SCMs and predict bacterial concentrations in Ballona Creek. Preliminary results suggest small enhancements to SCMs that improve bacterial removal (<0.5 log removal) may offer large benefits to surface water quality and enable communities such as Los Angeles to meet their regulatory requirements.

Guidelines for Calibration and Application of Storm.

DTIC Science & Technology

1977-12-01

combination method uses the SCS method on pervious areas and the coefficient method on impervious areas of the watershed. Storm water quality is computed...stations, it should be accomplished according to procedures outlined In Reference 7. Adequate storm water quality data are the most difficult and costly...mass discharge of pollutants is negligible. The state-of-the-art in urban storm water quality modeling precludes highly accurate simulation of

Evaluating water quality ecosystem services of wetlands under historic and future climate

NASA Astrophysics Data System (ADS)

Records, R.; Arabi, M.; Fassnacht, S. R.; Duffy, W.; Ahmadi, M.; Hegewisch, K.

2013-12-01

Potential hydrologic effects of climate change have been assessed extensively; however, possible impacts of changing climate on in-stream water quality at the watershed scale have received little study. We assessed potential impacts of climate change on water quantity and quality in the mountainous Sprague River watershed, Oregon, USA, where high total phosphorus (TP) and sediment loads are associated with lake eutrophication and mortality of endangered fish species. Additionally, we analyzed water quality impacts of wetland and riparian zone loss and gain under present-day climate and future climate scenarios. We utilized the hydrologic model Soil and Water Assessment Tool (SWAT) forced with six distinct climate scenarios derived from Coupled Model Intercomparison Project 5 (CMIP5) General Circulation Models to assess magnitude and direction of trends in streamflow, sediment and TP fluxes in the mid-21st century (2030-2059). Model results showed little significant trend in average annual streamflow under most climate scenarios, but trends in annual and monthly streamflow, sediment, and TP fluxes were more pronounced and were generally increasing. Results also suggest that future loss of present-day wetlands and riparian zones under land use or climatic change could result in substantial increases in sediment and TP loads at the Sprague River outlet.

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

PubMed

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.

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

EPA Science Inventory

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

Developing a framework to assess the water quality and quantity impacts of climate change, shifting land use, and urbanization in a Midwestern agricultural landscape

NASA Astrophysics Data System (ADS)

Loheide, S. P.; Booth, E. G.; Kucharik, C. J.; Carpenter, S. R.; Gries, C.; Katt-Reinders, E.; Rissman, A. R.; Turner, M. G.

2011-12-01

Dynamic hydrological processes play a critical role in the structure and functioning of agricultural watersheds undergoing urbanization. Developing a predictive understanding of the complex interaction between agricultural productivity, ecosystem health, water quality, urban development, and public policy requires an interdisciplinary effort that investigates the important biophysical and social processes of the system. Our research group has initiated such a framework that includes a coordinated program of integrated scenarios, model experiments to assess the effects of changing drivers on a broad set of ecosystem services, evaluations of governance and leverage points, outreach and public engagement, and information management. Our geographic focus is the Yahara River watershed in south-central Wisconsin, which is an exemplar of water-related issues in the Upper Midwest. This research addresses three specific questions. 1) How do different patterns of land use, land cover, land management, and water resources engineering practices affect the resilience and sensitivity of ecosystem services under a changing climate? 2) How can regional governance systems for water and land use be made more resilient and adaptive to meet diverse human needs? 3) In what ways are regional human-environment systems resilient and in what ways are they vulnerable to potential changes in climate and water resources? A comprehensive program of model experiments and biophysical measurements will be utilized to evaluate changes in five freshwater ecosystem services (flood regulation, groundwater recharge, surface water quality, groundwater quality, and lake recreation) and five related ecosystem services (food crop yields, bioenergy crop yields, carbon storage in soil, albedo, and terrestrial recreation). Novel additions to existing biophysical models will allow us to simulate all components of the hydrological cycle as well as agricultural productivity, nitrogen and phosphorus transport, and lake water quality. The integrated model will be validated using a comprehensive observational database that includes soil moisture, evapotranspiration, stomatal conductance, streamflow, stream and lake water quality, and crop yields and productivity. Integrated scenarios will be developed to synthesize decision-maker perspectives, alternative approaches to resource governance, plausible trends in demographic and economic drivers, and model projections under alternate climate and land use regimes to understand future conditions of the watershed and its ecosystem services. The quantitative data and integrated scenarios will then be linked to evaluate governance of water and land use.

Agricultural land use and N losses to water: the case study of a fluvial park in northern Italy.

PubMed

Morari, F; Lugato, E; Borin, M

2003-01-01

An integrated water resource management programme has been under way since 1999 to reduce agricultural water pollution in the River Mincio fluvial park. The experimental part of the programme consisted of: a) a monitoring phase to evaluate the impact of conventional and environmentally sound techniques (Best Management Practices, BMPs) on water quality; this was done on four representative landscape units, where twelve fields were instrumented to monitor the soil, surface and subsurface water quality; b) a modelling phase to extend the results obtained at field scale to the whole territory of the Mincio watershed. For this purpose a GIS developed in the Arc/Info environment was integrated into the CropSyst model. The model had previously been calibrated to test its ability to describe the complexity of the agricultural systems. The first results showed a variable efficiency of the BMPs depending on the interaction between management and pedo-climatic conditions. In general though, the BMPs had positive effects in improving the surface and subsurface water quality. The CropSyst model was able to describe the agricultural systems monitored and its linking with the GIS represented a valuable tool for identifying the vulnerable areas within the watershed.

A web tool for STORET/WQX water quality data retrieval and Best Management Practice scenario suggestion.

PubMed

Park, Youn Shik; Engel, Bernie A; Kim, Jonggun; Theller, Larry; Chaubey, Indrajeet; Merwade, Venkatesh; Lim, Kyoung Jae

2015-03-01

Total Maximum Daily Load is a water quality standard to regulate water quality of streams, rivers and lakes. A wide range of approaches are used currently to develop TMDLs for impaired streams and rivers. Flow and load duration curves (FDC and LDC) have been used in many states to evaluate the relationship between flow and pollutant loading along with other models and approaches. A web-based LDC Tool was developed to facilitate development of FDC and LDC as well as to support other hydrologic analyses. In this study, the FDC and LDC tool was enhanced to allow collection of water quality data via the web and to assist in establishing cost-effective Best Management Practice (BMP) implementations. The enhanced web-based tool provides use of water quality data not only from the US Geological Survey but also from the Water Quality Portal for the U.S. via web access. Moreover, the web-based tool identifies required pollutant reductions to meet standard loads and suggests a BMP scenario based on ability of BMPs to reduce pollutant loads, BMP establishment and maintenance costs. In the study, flow and water quality data were collected via web access to develop LDC and to identify the required reduction. The suggested BMP scenario from the web-based tool was evaluated using the EPA Spreadsheet Tool for the Estimation of Pollutant Load model to attain the required pollutant reduction at least cost. Copyright © 2014 Elsevier Ltd. All rights reserved.

Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10

USGS Publications Warehouse

Littin, Gregory R.

2012-01-01

The Cedar River alluvial aquifer is the primary source of municipal water in the Cedar Rapids, Iowa area. Municipal wells are completed in the alluvial aquifer approximately 40 to 80 feet below land surface. The City of Cedar Rapids and the U.S. Geological Survey have been conducting a cooperative study of the groundwater-flow system and water quality of the aquifer since 1992. Cooperative reports between the City of Cedar Rapids and the U.S. Geological Survey have documented hydrologic and water-quality data, geochemistry, and groundwater models. Water-quality samples were collected for studies involving well field monitoring, trends, source-water protection, groundwater geochemistry, surface-water-groundwater interaction, and pesticides in groundwater and surface water. Water-quality analyses were conducted for major ions (boron, bromide, calcium, chloride, fluoride, iron, magnesium, manganese, potassium, silica, sodium, and sulfate), nutrients (ammonia as nitrogen, nitrite as nitrogen, nitrite plus nitrate as nitrogen, and orthophosphate as phosphorus), dissolved organic carbon, and selected pesticides including two degradates of the herbicide atrazine. Physical characteristics (alkalinity, dissolved oxygen, pH, specific conductance and water temperature) were measured in the field and recorded for each water sample collected. This report presents the results of routine water-quality data-collection activities from January 2006 through December 2010. Methods of data collection, quality-assurance, and water-quality analyses are presented. Data include the results of water-quality analyses from quarterly sampling from monitoring wells, municipal wells, and the Cedar River.

Spatial multiobjective optimization of agricultural conservation practices using a SWAT model and an evolutionary algorithm.

PubMed

Rabotyagov, Sergey; Campbell, Todd; Valcu, Adriana; Gassman, Philip; Jha, Manoj; Schilling, Keith; Wolter, Calvin; Kling, Catherine

2012-12-09

Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,(5,12,20)) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization. Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods(3,4,9,10,13-15,17-19,22,23,25). In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model(7) with a multiobjective evolutionary algorithm SPEA2(26), and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.

A Survey of Precipitation Data for Environmental Modeling

EPA Science Inventory

This report explores the types of precipitation data available for environmental modeling. Precipitation is the main driver in the hydrological cycle and modelers use this information to understand water quality and water availability. Models use observed precipitation informatio...

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Use of tolerance values to diagnose water-quality stressors to aquatic biota in New England streams

USGS Publications Warehouse

Meador, M.R.; Carlisle, D.M.; Coles, J.F.

2008-01-01

Identification of stressors related to biological impairment is critical to biological assessments. We applied nationally derived tolerance indicator values for four water-quality variables to fish and benthic macroinvertebrate assemblages at 29 sites along an urban gradient in New England. Tolerance indicator values (TIVs), as biologically based predictors of water-quality variables, were determined for dissolved oxygen, nitrite plus nitrate (nitrate), total phosphorus, and water temperature for each site based on observed biological assemblages (TIVO), and for expected assemblages (TIVE). The quotient method, based on a ratio of the TIVs for observed and expected assemblages (tolerance units), was used to diagnose potential water-quality stressors. In addition, the ratio of measured water-quality values to water-quality criteria (water-quality units) was calculated for each water-quality variable to assess measured water-quality stressors. Results from a RIVPACS predictive model for benthic macroinvertebrates and Bray-Curtis dissimilarity for fish were used to classify sites into categories of good or impaired ecological condition. Significant differences were detected between good and impaired sites for all biological tolerance units (fish and benthic macroinvertebrate assemblages averaged) except for nitrate (P = 0.480), and for all water-quality units except for nitrate (P = 0.183). Diagnosis of water-quality stressors at selected sites was, in general, consistent with State-reported causes of impairment. Tolerance units for benthic macroinvertebrate and fish assemblages were significantly correlated for water temperature (P = 0.001, r = 0.63), dissolved oxygen (P = 0.001, r = 0.61), and total phosphorus (P = 0.001, r = 0.61), but not for nitrate (P = 0.059, r = -0.35). Differences between the two assemblages in site-specific diagnosis of water-quality stressors may be the result of differences in nitrate tolerance.

Optimizing basin-scale coupled water quantity and water quality man-agement with stochastic dynamic programming

NASA Astrophysics Data System (ADS)

Davidsen, Claus; Liu, Suxia; Mo, Xingguo; Engelund Holm, Peter; Trapp, Stefan; Rosbjerg, Dan; Bauer-Gottwein, Peter

2015-04-01

Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen concentrations. Inelastic water demands, fixed water allocation curtailment costs and fixed wastewater treatment costs (before and after use) are estimated for the water users (agriculture, industry and domestic). If the BOD concentration exceeds a given user pollution thresh-old, the user will need to pay for pre-treatment of the water before use. Similarly, treatment of the return flow can reduce the BOD load to the river. A traditional SDP approach is used to solve one-step-ahead sub-problems for all combinations of discrete reservoir storage, Markov Chain inflow clas-ses and monthly time steps. Pollution concentration nodes are introduced for each user group and untreated return flow from the users contribute to increased BOD concentrations in the river. The pollutant concentrations in each node depend on multiple decision variables (allocation and wastewater treatment) rendering the objective function non-linear. Therefore, the pollution concen-tration decisions are outsourced to a genetic algorithm, which calls a linear program to determine the remainder of the decision variables. This hybrid formulation keeps the optimization problem computationally feasible and represents a flexible and customizable method. The method has been applied to the Ziya River basin, an economic hotspot located on the North China Plain in Northern China. The basin is subject to severe water scarcity, and the rivers are heavily polluted with wastewater and nutrients from diffuse sources. The coupled hydro-economic optimiza-tion model can be used to assess costs of meeting additional constraints such as minimum water qual-ity or to economically prioritize investments in waste water treatment facilities based on economic criteria.

Water Quality in the Delmarva Peninsula, Delaware, Maryland, and Virginia, 1999-2001

USGS Publications Warehouse

Denver, Judith M.; Ator, Scott W.; Debrewer, Linda M.; Ferrari, Matthew J.; Barbaro, Jeffrey R.; Hancock, Tracy C.; Brayton, Michael J.; Nardi, Mark R.

2004-01-01

This report contains the major findings of a 1999-2001 assessment of water quality in the Delmarva Peninsula. It is one of a series of reports by the National Water-Quality Assessment (NAWQA) Program that present major findings in 51 major river basins and aquifer systems across the Nation. In these reports, water quality is assessed at many scales?from local ground-water flow paths to regional ground-water networks and in surface water?and is discussed in terms of local, State, and regional issues. Conditions in the Delmarva Peninsula are compared to conditions found elsewhere and to selected national benchmarks, such as those for drinking-water quality and the protection of aquatic organisms. This report is intended for individuals working with water-resource issues in Federal, State, or local agencies; universities; public interest groups; or in the private sector. The information will be useful in addressing a number of current issues, such as the effects of agricultural and urban land use on water quality, human health, drinking water, source-water protection, hypoxia and excessive growth of algae and plants, pesticide registration, and monitoring and sampling strategies. This report is also for individuals who wish to know more about the quality of streams and ground water in areas near where they live, and how that water quality compares to the quality of water in other areas across the Nation. Other products describing water-quality conditions in the Delmarva Peninsula are available. Detailed technical information, data and analyses, methodology, models, graphs, and maps that support the findings presented in this report can be accessed from http://md.water.usgs.gov/delmarva. Other reports in this series and data collected from other basins can be accessed from the national NAWQA Web site (http://water.usgs.gov/nawqa).

Water pollution risk simulation and prediction in the main canal of the South-to-North Water Transfer Project

NASA Astrophysics Data System (ADS)

Tang, Caihong; Yi, Yujun; Yang, Zhifeng; Cheng, Xi

2014-11-01

The middle route of the South-to-North Water Transfer Project (MRP) will divert water to Beijing Tuancheng Lake from Taocha in the Danjiangkou reservoir located in the Hubei province of China. The MRP is composed of a long canal and complex hydraulic structures and will transfer water in open channel areas to provide drinking water for Beijing, Shijiazhuang and other cities under extremely strict water quality requirements. A large number of vehicular accidents, occurred on the many highway bridges across the main canal would cause significant water pollution in the main canal. To ensure that water quality is maintained during the diversion process, the effects of pollutants on water quality due to sudden pollution accidents were simulated and analyzed in this paper. The MIKE11 HD module was used to calculate the hydraulic characteristics of the 42-km Xishi-to-Beijuma River channel of the MRP. Six types of hydraulic structures, including inverted siphons, gates, highway bridges, culverts and tunnels, were included in this model. Based on the hydrodynamic model, the MIKE11 AD module, which is one-dimensional advection dispersion model, was built for TP, NH3-N, CODMn and F. The validated results showed that the computed values agreed well with the measured values. In accordance with transportation data across the Dianbei Highway Bridge, the effects of traffic accidents on the bridge on water quality were analyzed. Based on simulated scenarios with three discharge rates (ranged from 12 m3/s to 17 m3/s, 40 m3/s, and 60 m3/s) and three pollution loading concentration levels (5 t, 10 t and 20 t) when trucks spill their contents (i.e., phosphate fertilizer, cyanide, oil and chromium solution) into the channel, emergency measures were proposed. Reasonable solutions to ensure the water quality with regard to the various types of pollutants were proposed, including treating polluted water, maintaining materials, and personnel reserves.

Groundwater studies: principal aquifer surveys

USGS Publications Warehouse

Burow, Karen R.; Belitz, Kenneth

2014-01-01

In 1991, the U.S. Congress established the National Water-Quality Assessment (NAWQA) program within the U.S. Geological Survey (USGS) to develop nationally consistent long-term datasets and provide information about the quality of the Nation’s streams and groundwater. The USGS uses objective and reliable data, water-quality models, and systematic scientific studies to assess current water-quality conditions, to identify changes in water quality over time, and to determine how natural factors and human activities affect the quality of streams and groundwater. NAWQA is the only non-regulatory Federal program to perform these types of studies; participation is voluntary. In the third decade (Cycle 3) of the NAWQA program (2013–2023), the USGS will evaluate the quality and availability of groundwater for drinking supply, improve our understanding of where and why water quality is degraded, and assess how groundwater quality could respond to changes in climate and land use. These goals will be addressed through the implementation of a new monitoring component in Cycle 3: Principal Aquifer Surveys.

Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14

USGS Publications Warehouse

Francy, Donna S.; Graham, Jennifer L.; Stelzer, Erin A.; Ecker, Christopher D.; Brady, Amie M. G.; Pam Struffolino,; Loftin, Keith A.

2015-11-06

The results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.

Dynamic modeling of the Ganga river system: impacts of future climate and socio-economic change on flows and nitrogen fluxes in India and Bangladesh.

PubMed

Whitehead, P G; Sarkar, S; Jin, L; Futter, M N; Caesar, J; Barbour, E; Butterfield, D; Sinha, R; Nicholls, R; Hutton, C; Leckie, H D

2015-06-01

This study investigates the potential impacts of future climate and socio-economic change on the flow and nitrogen fluxes of the Ganga river system. This is the first basin scale water quality study for the Ganga considering climate change at 25 km resolution together with socio-economic scenarios. The revised dynamic, process-based INCA model was used to simulate hydrology and water quality within the complex multi-branched river basins. All climate realizations utilized in the study predict increases in temperature and rainfall by the 2050s with significant increase by the 2090s. These changes generate associated increases in monsoon flows and increased availability of water for groundwater recharge and irrigation, but also more frequent flooding. Decreased concentrations of nitrate and ammonia are expected due to increased dilution. Different future socio-economic scenarios were found to have a significant impact on water quality at the downstream end of the Ganga. A less sustainable future resulted in a deterioration of water quality due to the pressures from higher population growth, land use change, increased sewage treatment discharges, enhanced atmospheric nitrogen deposition, and water abstraction. However, water quality was found to improve under a more sustainable strategy as envisaged in the Ganga clean-up plan.

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

USDA-ARS?s Scientific Manuscript database

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...

Seasonal Dynamics of River Corridor Exchange Across the Continental United States

NASA Astrophysics Data System (ADS)

Gomez-Velez, J. D.; Harvey, J. W.; Scott, D.; Boyer, E. W.; Schmadel, N. M.

2017-12-01

River corridors store and convey mass and energy from landscapes to the ocean, altering water quality and ecosystem functioning at the local, reach, and watershed scales. As water moves through river corridors from headwaters streams to coastal estuaries, dynamic exchange between the river channel and its adjacent riparian, floodplain, and hyporheic zones, combined with ponded waters such as lakes and reservoirs, results in the emergence of hot spots and moments for biogeochemical transformations. In this work, we used the model Networks with EXchange and Subsurface Storage (NEXSS) to estimate seasonal variations in river corridor exchange fluxes and residence times along the continental United States. Using a simple routing scheme, we translate these estimates into a cumulative measure of river corridor connectivity at the watershed scale, differentiating the contributions of hyporheic zones, floodplains, and ponded waters. We find that the relative role of these exchange subsystems changes seasonally, driven by the intra-seasonal variability of discharge. In addition, we find that seasonal variations in discharge and the biogeochemical potential of hyporheic zones are out of phase. This behavior results in a significant reduction in hyporheic water quality functions during high flows and emphasizes the potential importance of reconnecting floodplains for managing water quality during seasonal high flows. Physical parameterizations of river corridor processes are critical to model and predict water quality and to sustainably manage water resources under present and future socio-economic and climatic conditions. Parsimonious models like NEXSS can play a key role in the design, implementation, and evaluation of sustainable management practices that target both water quantity and quality at the scale of the nation. This research is a product of the John Wesley Powell Center River Corridor Working Group.

Linking the physical and the socio-economic compartments of an integrated water and land use management model on a river basin scale using an object-oriented water supply model

NASA Astrophysics Data System (ADS)

Barthel, Roland; Nickel, Darla; Meleg, Alejandro; Trifkovic, Aleksandar; Braun, Juergen

Within the framework of the research project ‘GLOWA-Danube’, a model of the water supply sector has been developed. GLOWA-Danube investigates long-term changes in the water cycle of the Upper Danube river basin in light of global change. For this purpose, the decision support system DANUBIA, comprising 15 fully coupled models, has been developed. Within DANUBIA the water supply model (‘WaterSupply’) forms the link between various physical models determining water quality and availability and several socio-economic models determining water consumption and demand. Having a central focus on public drinking water supply, its purpose is to correctly simulate the present day system of water extraction and distribution and the related costs, but also to allow meaningful response to possible future changes of boundary conditions, first and foremost changes in water demand or water availability and quality. Response mechanisms are also envisioned for changes in political and economic boundary conditions, and advances in technology. The model will be used locate critical regions which could experience water stress in the future, but does not aim to find the appropriate solutions or to predict the optimal organisation of water supply in the Danube Basin under such changing conditions. In the object-oriented model structure, both water supply companies (WSC) and communities are represented by main classes. Both classes have a limited view and knowledge of their environment. A community knows where and how much water is consumed and from which WSC it is served. A WSC possesses information regarding extraction sites and water rights, raw water quality and potential collaborating WSC. The WSC can perform actions that are different from ‘business as usual’. These deviations from their usual behaviour can be interpreted by decision makers but should not be regarded as a replacement for the decision-making process itself. The model is conceptualised using object-oriented concepts of the Unified Modelling Language (UML) and is implemented in JAVA. This short overview is meant to answer key questions such as why and how WaterSupply was implemented, what is unique and new about the model and what are the general lessons learned and the added value with regard to integrated modelling on a river basin scale. It is obvious that in the attempt to answer these questions it is not possible to satisfy experts from all the relevant related fields, which include computer sciences, economy, behavioural science and not least water supply engineering and hydrology.

Characterisation of sources and pathways of microbiological pollutants to protect remote private water supplies

NASA Astrophysics Data System (ADS)

Neill, Aaron; Tetzlaff, Doerthe; Strachan, Norval; Hough, Rupert; Soulsby, Chris

2016-04-01

In order to comply with legislation such as the Water Framework Directive and to safeguard public health, there is a critical need to maintain the quality of water sources that are used to supply drinking water. Private water supplies (PWS) are still common in many rural areas in the UK, and are especially vulnerable to poor water quality, owing to the limited treatment they often receive and variable raw water quality in groundwater and surface water sources. A significant issue affecting PWS quality is contamination by faecal pathogens derived from grazing animals or agricultural practices. In Scotland, approximately 20,000 PWS serve around 200,000 people, with a number of these PWS consistently failing to meet water quality targets relating to coliform bacteria and E. coli, both of which can be indicative of faecal contamination (faecal indicator organisms - FIOs). The purpose of our study was to employ integrated empirical and modelling approaches from hydrology and microbiology to elucidate the nature of the still poorly-understood interplay between hydrological flow pathways which connect sources of pathogens to PWS sources, antecedent conditions, seasonality and pathogen transfer risk, for two catchments with contrasting land uses in Scotland: an agricultural catchment (Tarland Burn) and a montane catchment (Bruntland Burn). In the Tarland Burn, 15 years of spatially-distributed samples collected at the catchment-scale of FIO counts were analysed alongside hydrometric data to identify "hot spots" of faecal pathogen transfer risk and possible spatial and temporal controls. We also used a combination of tracer-based and numerical modelling approaches to identify the relationship between hydrological connectivity, flow pathways, and the mobilisation of faecal pathogens from different sources. In the Bruntland Burn, we coupled a pathogen storage, mobilisation and transport scheme to a previously developed tracer-informed hydrological model for the catchment to investigate temporal patterns and controls of pathogen transfer risk from different hydrological source areas identified from extensive past tracer and numerical modelling work: groundwater, hillslopes and the dynamic riparian zone.

Simulation of streamflow and water quality in the Christina River subbasin and overview of simulations in other subbasins of the Christina River Basin, Pennsylvania, Maryland, and Delaware, 1994-98

USGS Publications Warehouse

Senior, Lisa A.; Koerkle, Edward H.

2003-01-01

The Christina River Basin drains 565 square miles (mi2) in Pennsylvania and Delaware and includes the major subbasins of Brandywine Creek, Red Clay Creek, White Clay Creek, and Christina River. The Christina River subbasin (exclusive of the Brandywine, Red Clay, and White Clay Creek subbasins) drains an area of 76 mi2. Streams in the Christina River Basin are used for recreation, drinking water supply, and support of aquatic life. Water quality in some parts of the Christina River Basin is impaired and does not support designated uses of the stream. A multi-agency water-quality management strategy included a modeling component to evaluate the effects of point- and nonpoint-source contributions of nutrients and suspended sediment on stream water quality. To assist in nonpoint-source evaluation, four independent models, one for each of the four main subbasins of the Christina River Basin, were developed and calibrated using the model code Hydrological Simulation Program–Fortran (HSPF). Water-quality data for model calibration were collected in each of the four main subbasins and in small subbasins predominantly covered by one land use following a nonpoint- source monitoring plan. Under this plan, stormflow and base-flow samples were collected during 1998 at two sites in the Christina River subbasin and nine sites elsewhere in the Christina River Basin.The HSPF model for the Christina River subbasin simulates streamflow, suspended sediment, and the nutrients, nitrogen and phosphorus. In addition, the model simulates water temperature, dissolved oxygen, biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment and nutrient simulations. For the model, the basin was subdivided into nine reaches draining areas that ranged from 3.8 to 21.9 mi2. Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use areas were determined from 1995 land-use data. The predominant land uses in the Christina River subbasin are residential, urban, forested, agricultural, and open.The hydrologic component of the model was run at an hourly time step and calibrated using streamflow data from two U.S. Geological Survey (USGS) streamflow-measurement stations for the period of October 1, 1994, through October 29, 1998. Daily precipitation data from one National Oceanic and Atmospheric Administration (NOAA) meteorologic station and hourly data from one NOAA meteorologic station were used for model input. The difference between observed and simulated streamflow volume ranged from -2.3 to 5.3 percent for a 10-month portion of the calibration period at the two calibration sites. Annual differences between observed and simulated streamflow generally were greater than the overall error for the 4-year period. For example, at Christina River at Coochs Bridge, near the bottom of the free-flowing part of the subbasin (drainage area of 21 mi2), annual differences between observed and simulated streamflow ranged from -6.9 to 6.5 percent and the overall error for the 4-year period was -1.1 percent. Calibration errors for 36 storm periods at the three calibration sites for total volume, low-flow recession rate, 50-percent lowest flows, 10-percent highest flows, and storm peaks were within the recommended criteria of 20 percent or less. Much of the error in simulating storm events on an hourly time step can be attributed to uncertainty in the rainfall data.The water-quality component of the model was calibrated using nonpoint-source monitoring data collected at two USGS streamflow-measurement stations and other water-quality monitoring data. The period of record for water-quality monitoring was variable at the stations, with a start date ranging from October 1994 to January 1998 and an end date of October 1998. Because of availability, monitoring data for suspended-solids concentrations were used as surrogates for suspended-sediment concentrations, although suspended-solids data may underestimate suspended sediment and affect apparent accuracy of the suspended-sediment simulaion. Comparison of observed to simulated loads for up to six storms in 1998 at the two nonpoint-source monitoring sites (Little Mill Creek near Newport and Christina River at Coochs Bridge, Del.) indicate that simulation error is commonly as large as an order of magnitude for suspended sediment and nutrients. The simulation error tends to be smaller for dissolved nutrients than for particulate nutrients. Errors of 40 percent or less for monthly or annual values indicate a fair to good water-quality calibration according to recommended criteria; much larger errors are possible for individual events. Assessment of the water-quality calibration under stormflow conditions is limited by the relatively small amount of available water-quality data in the subbasin.Users of the Christina River subbasin HSPF model and HSPF models for other subbasins in the Christina River Basin should be aware of model limitations and consider the following if the model is used for predictive purposes: streamflow-duration curves suggest the model simulates streamflow reasonably well when measured over a broad range of conditions and time although streamflow and the corresponding water quality for individual storm events may not be well simulated; streamflow-duration curves for the simulation period compare well with duration curves for the 8-year period ending in 2001 at Christina River at Coochs Bridge, Del., and include all but the extreme high-flow and low-flow events; and calibration for water quality was based on limited data, with the result of increasing uncertainty in the water-quality simulation.

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

USGS Publications Warehouse

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.

River water quality management considering agricultural return flows: application of a nonlinear two-stage stochastic fuzzy programming.

PubMed

Tavakoli, Ali; Nikoo, Mohammad Reza; Kerachian, Reza; Soltani, Maryam

2015-04-01

In this paper, a new fuzzy methodology is developed to optimize water and waste load allocation (WWLA) in rivers under uncertainty. An interactive two-stage stochastic fuzzy programming (ITSFP) method is utilized to handle parameter uncertainties, which are expressed as fuzzy boundary intervals. An iterative linear programming (ILP) is also used for solving the nonlinear optimization model. To accurately consider the impacts of the water and waste load allocation strategies on the river water quality, a calibrated QUAL2Kw model is linked with the WWLA optimization model. The soil, water, atmosphere, and plant (SWAP) simulation model is utilized to determine the quantity and quality of each agricultural return flow. To control pollution loads of agricultural networks, it is assumed that a part of each agricultural return flow can be diverted to an evaporation pond and also another part of it can be stored in a detention pond. In detention ponds, contaminated water is exposed to solar radiation for disinfecting pathogens. Results of applying the proposed methodology to the Dez River system in the southwestern region of Iran illustrate its effectiveness and applicability for water and waste load allocation in rivers. In the planning phase, this methodology can be used for estimating the capacities of return flow diversion system and evaporation and detention ponds.

Application of Data Assimilation with the Root Zone Water Quality Model for Soil Moisture Profile Estimation

USDA-ARS?s Scientific Manuscript database

The Ensemble Kalman Filter (EnKF), a popular data assimilation technique for non-linear systems was applied to the Root Zone Water Quality Model. Measured soil moisture data at four different depths (5cm, 20cm, 40cm and 60cm) from two agricultural fields (AS1 and AS2) in northeastern Indiana were us...

Water-quality trends in the nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results

USGS Publications Warehouse

Oelsner, Gretchen P.; Sprague, Lori A.; Murphy, Jennifer C.; Zuellig, Robert E.; Johnson, Henry M.; Ryberg, Karen R.; Falcone, James A.; Stets, Edward G.; Vecchia, Aldo V.; Riskin, Melissa L.; De Cicco, Laura A.; Mills, Taylor J.; Farmer, William H.

2017-04-04

Since passage of the Clean Water Act in 1972, Federal, State, and local governments have invested billions of dollars to reduce pollution entering rivers and streams. To understand the return on these investments and to effectively manage and protect the Nation’s water resources in the future, we need to know how and why water quality has been changing over time. As part of the National Water-Quality Assessment Project, of the U.S. Geological Survey’s National Water-Quality Program, data from the U.S. Geological Survey, along with multiple other Federal, State, Tribal, regional, and local agencies, have been used to support the most comprehensive assessment conducted to date of surface-water-quality trends in the United States. This report documents the methods used to determine trends in water quality and ecology because these methods are vital to ensuring the quality of the results. Specific objectives are to document (1) the data compilation and processing steps used to identify river and stream sites throughout the Nation suitable for water-quality, pesticide, and ecology trend analysis, (2) the statistical methods used to determine trends in target parameters, (3) considerations for water-quality, pesticide, and ecology data and streamflow data when modeling trends, (4) sensitivity analyses for selecting data and interpreting trend results with the Weighted Regressions on Time, Discharge, and Season method, and (5) the final trend results at each site. The scope of this study includes trends in water-quality concentrations and loads (nutrient, sediment, major ion, salinity, and carbon), pesticide concentrations and loads, and metrics for aquatic ecology (fish, invertebrates, and algae) for four time periods: (1) 1972–2012, (2) 1982–2012, (3) 1992–2012, and (4) 2002–12. In total, nearly 12,000 trends in concentration, load, and ecology metrics were evaluated in this study; there were 11,893 combinations of sites, parameters, and trend periods. The final trend results are presented with examples of how to interpret the results from each trend model. Interpretation of the trend results, such as causal analysis, is not included.

Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.

USGS Publications Warehouse

Mahan, Carolyn G.; Young, John A.; Miller, Bruce; Saunders, Michael C.

2014-01-01

We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)—national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks’ conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a −1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape—we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.

Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the mid-Atlantic region, USA.

PubMed

Mahan, Carolyn G; Young, John A; Miller, Bruce J; Saunders, Michael C

2015-02-01

We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)-national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks' conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a -1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape-we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.

Using Ecological Indicators and a Decision Support System for Integrated Ecological Assessment at Two National Park Units in the Mid-Atlantic Region, USA

NASA Astrophysics Data System (ADS)

Mahan, Carolyn G.; Young, John A.; Miller, Bruce J.; Saunders, Michael C.

2015-02-01

We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)—national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks' conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a -1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape—we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.

Analysis of the ecological water diversion project in Wenzhou City

NASA Astrophysics Data System (ADS)

Xu, Haibo; Fu, Lei; Lin, Tong

2018-02-01

As a developed city in China, Wenzhou City has been suffered from bad water quality for years. In order to improve the river network water quality, an ecological water diversion project was designed and executed by the regional government. In this study, an investigation and analysis of the regional ecological water diversion project is made for the purpose of examining the water quality improvements. A numerical model is also established, different water diversion flow rates and sewer interception levels are considered during the simulation. Simulation results reveal that higher flow rate and sewer interception level will greatly improve the river network water quality in Wenzhou City. The importance of the flow rate and interception level has been proved and future work will be focused on increasing the flow rate and upgrading the sewer interception level.

Calibration of the Root Zone Water Quality Model and Application of Data Assimilation Techniques to Estimate Profile Soil Moisture

USDA-ARS?s Scientific Manuscript database

Estimation of soil moisture has received considerable attention in the areas of hydrology, agriculture, meteorology and environmental studies because of its role in the partitioning water and energy at the land surface. In this study, the USDA, Agricultural Research Service, Root Zone Water Quality ...

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

EPA Science Inventory

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...

Impacts of agricultural land use on biological integrity: A causal analysis

USGS Publications Warehouse

Riseng, C.M.; Wiley, M.J.; Black, R.W.; Munn, M.D.

2011-01-01

Agricultural land use has often been linked to nutrient enrichment, habitat degradation, hydrologic alteration, and loss of biotic integrity in streams. The U.S. Geological Survey's National Water Quality Assessment Program sampled 226 stream sites located in eight agriculture-dominated study units across the United States to investigate the geographic variability and causes of agricultural impacts on stream biotic integrity. In this analysis we used structural equation modeling (SEM) to develop a national and set of regional causal models linking agricultural land use to measured instream conditions. We then examined the direct, indirect, and total effects of agriculture on biotic integrity as it acted through multiple water quality and habitat pathways. In our nation-wide model, cropland affected benthic communities by both altering structural habitats and by imposing water quality-related stresses. Regionspecific modeling demonstrated that geographic context altered the relative importance of causal pathways through which agricultural activities affected stream biotic integrity. Cropland had strong negative total effects on the invertebrate community in the national, Midwest, and Western models, but a very weak effect in the Eastern Coastal Plain model. In theWestern Arid and Eastern Coastal Plain study regions, cropland impacts were transmitted primarily through dissolved water quality contaminants, but in the Midwestern region, they were transmitted primarily through particulate components of water quality. Habitat effects were important in the Western Arid model, but negligible in the Midwest and Eastern Coastal Plain models. The relative effects of riparian forested wetlands also varied regionally, having positive effects on biotic integrity in the Eastern Coastal Plain andWestern Arid region models, but no statistically significant effect in the Midwest. These differences in response to cropland and riparian cover suggest that best management practices and planning for the mitigation of agricultural land use impacts on stream ecosystems should be regionally focused. ?? 2011 by the Ecological Society of America.

A new and integrated hydro-economic accounting and analytical framework for water resources: a case study for North China.

PubMed

Guan, Dabo; Hubacek, Klaus

2008-09-01

Water is a critical issue in China for a variety of reasons. China is poor of water resources with 2,300 m(3) of per capita availability, which is less than 13 of the world average. This is exacerbated by regional differences; e.g. North China's water availability is only about 271 m(3) of per capita value, which is only 125 of the world's average. Furthermore, pollution contributes to water scarcity and is a major source for diseases, particularly for the poor. The Ministry of Hydrology [1997. China's Regional Water Bullets. Water Resource and Hydro-power Publishing House, Beijing, China] reports that about 65-80% of rivers in North China no longer support any economic activities. Previous studies have emphasized the amount of water withdrawn but rarely take water quality into consideration. The quality of the return flows usually changes; the water quality being lower than the water flows that entered the production process initially. It is especially important to measure the impacts of wastewater to the hydro-ecosystem. Thus, water consumption should not only account for the amount of water inputs but also the amount of water contaminated in the hydro-ecosystem by the discharged wastewater. In this paper we present a new accounting and analytical approach based on economic input-output modelling combined with a mass balanced hydrological model that links interactions in the economic system with interactions in the hydrological system. We thus follow the tradition of integrated economic-ecologic input-output modelling. Our hydro-economic accounting framework and analysis tool allows tracking water consumption on the input side, water pollution leaving the economic system and water flows passing through the hydrological system thus enabling us to deal with water resources of different qualities. Following this method, the results illustrate that North China requires 96% of its annual available water, including both water inputs for the economy and contaminated water that is ineligible for any uses.

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

NASA Astrophysics Data System (ADS)

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 management decisions. Our research results indicate that the (often large) observed differences between MPN and CFU values for the same water body are well within the ranges predicted by our probabilistic model. Our research also indicates that the probability of violating current water quality guidelines at specified true fecal coliform concentrations depends on the laboratory procedure used. As a result, quality-based management decisions, such as opening or closing a shellfishing area, may also depend on the laboratory procedure used.

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

PubMed

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.

Use of the Hydrological Simulation Program-FORTRAN and bacterial source tracking for development of the fecal coliform total maximum daily load (TMDL) for Blacks Run, Rockingham County, Virginia

USGS Publications Warehouse

Moyer, Douglas; Hyer, Kenneth

2003-01-01

Impairment of surface waters by fecal coliform bacteria is a water-quality issue of national scope and importance. Section 303(d) of the Clean Water Act requires that each State identify surface waters that do not meet applicable water-quality standards. In Virginia, more than 175 stream segments are on the 1998 Section 303(d) list of impaired waters because of violations of the water-quality standard for fecal coliform bacteria. A total maximum daily load (TMDL) will need to be developed by 2006 for each of these impaired streams and rivers by the Virginia Departments of Environmental Quality and Conservation and Recreation. A TMDL is a quantitative representation of the maximum load of a given water-quality constituent, from all point and nonpoint sources, that a stream can assimilate without violating the designated water-quality standard. Blacks Run, in Rockingham County, Virginia, is one of the stream segments listed by the State of Virginia as impaired by fecal coliform bacteria. Watershed modeling and bacterial source tracking were used to develop the technical components of the fecal coliform bacteria TMDL for Accotink Creek. The Hydrological Simulation Program?FORTRAN (HSPF) was used to simulate streamflow, fecal coliform concentrations, and source-specific fecal coliform loading in Blacks Run. Ribotyping, a bacterial source tracking technique, was used to identify the dominant sources of fecal coliform bacteria in the Blacks Run watershed. Ribotyping also was used to determine the relative contributions of specific sources to the observed fecal coliform load in Blacks Run. Data from the ribotyping analysis were incorporated into the calibration of the fecal coliform model. Study results provide information regarding the calibration of the streamflow and fecal coliform bacteria models and also identify the reductions in fecal coliform loads required to meet the TMDL for Blacks Run. The calibrated streamflow model simulated observed streamflow characteristics with respect to total annual runoff, seasonal runoff, average daily streamflow, and hourly stormflow. The calibrated fecal coliform model simulated the patterns and range of observed fecal coliform bacteria concentrations. Observed fecal coliform bacteria concentrations during low-flow periods ranged from 40 to 7,000 colonies per 100 milliliters, and peak concentrations during storm-flow periods ranged from 33,000 to 260,000 colonies per 100 milliliters. Simulated source-specific contributions of fecal coliform bacteria to instream load were matched to the observed contributions from the dominant sources, which were cats, cattle, deer, dogs, ducks, geese, horses, humans, muskrats, poultry, raccoons, and sheep. According to model results, a 95-percent reduction in the current fecal coliform load delivered from the watershed to Blacks Run would result in compliance with the designated water-quality goals and associated TMDL.

Use of the Hydrological Simulation Program-FORTRAN and Bacterial Source Tracking for Development of the fecal coliform Total Maximum Daily Load (TMDL) for Accotink Creek, Fairfax County, Virginia

USGS Publications Warehouse

Moyer, Douglas; Hyer, Kenneth

2003-01-01

Impairment of surface waters by fecal coliform bacteria is a water-quality issue of national scope and importance. Section 303(d) of the Clean Water Act requires that each State identify surface waters that do not meet applicable water-quality standards. In Virginia, more than 175 stream segments are on the 1998 Section 303(d) list of impaired waters because of violations of the water-quality standard for fecal coliform bacteria. A total maximum daily load (TMDL) will need to be developed by 2006 for each of these impaired streams and rivers by the Virginia Departments of Environmental Quality and Conservation and Recreation. A TMDL is a quantitative representation of the maximum load of a given water-quality constituent, from all point and nonpoint sources, that a stream can assimilate without violating the designated water-quality standard. Accotink Creek, in Fairfax County, Virginia, is one of the stream segments listed by the State of Virginia as impaired by fecal coliform bacteria. Watershed modeling and bacterial source tracking were used to develop the technical components of the fecal coliform bacteria TMDL for Accotink Creek. The Hydrological Simulation Program?FORTRAN (HSPF) was used to simulate streamflow, fecal coliform concentrations, and source-specific fecal coliform loading in Accotink Creek. Ribotyping, a bacterial source tracking technique, was used to identify the dominant sources of fecal coliform bacteria in the Accotink Creek watershed. Ribotyping also was used to determine the relative contributions of specific sources to the observed fecal coliform load in Accotink Creek. Data from the ribotyping analysis were incorporated into the calibration of the fecal coliform model. Study results provide information regarding the calibration of the streamflow and fecal coliform bacteria models and also identify the reductions in fecal coliform loads required to meet the TMDL for Accotink Creek. The calibrated streamflow model simulated observed streamflow characteristics with respect to total annual runoff, seasonal runoff, average daily streamflow, and hourly stormflow. The calibrated fecal coliform model simulated the patterns and range of observed fecal coliform bacteria concentrations. Observed fecal coliform bacteria concentrations during low-flow periods ranged from 25 to 800 colonies per 100 milliliters, and peak concentrations during storm-flow periods ranged from 19,000 to 340,000 colonies per 100 milliliters. Simulated source-specific contributions of fecal coliform bacteria to instream load were matched to the observed contributions from the dominant sources, which were cats, deer, dogs, ducks, geese, humans, muskrats, and raccoons. According to model results, an 89-percent reduction in the current fecal coliform load delivered from the watershed to Accotink Creek would result in compliance with the designated water-quality goals and associated TMDL.

Integrated Water and Sanitation Risk Assessment and Modeling in the Upper Sonora River basin (Northwest, Mexico)

NASA Astrophysics Data System (ADS)

Mayer, A. S.; Robles-Morua, A.; Halvorsen, K. E.; Vivoni, E. R.; Auer, M. T.

2011-12-01

Studies that integrate human dimensions and the biophysical characteristics of watersheds are necessary to meet the challenge of sustainable water resources development. In this project, we integrated perspectives from sociology, hydrology, and environmental engineering to examine and suggest solutions for managing waterborne disease risks associated with wastewater contamination in the Sonora River basin (SRB), a semiarid rural basin in northwest Mexico. This research consisted of four sub-projects. First, we assessed the perceptions of risks associated with wastewater contamination of water resources in rural communities in the SRB through a series of semi-structured interviews Results from this study indicate that there are major differences in risk perceptions among health professionals, government officials, and lay citizens. Government officials and lay citizens tend to underestimate the severity of the problems related to water related risks. Second, a fully distributed hydrologic model was used to make streamflow predictions in the un-gauged SRB. Synthetic flows generated from the hydrologic model were used to evaluate pollutant transport processes associated with wastewater loadings to the Sonora River. The hydrologic model revealed that the high degree of spatio-temporal variability of runoff in the SRB is associated with links between runoff generation mechanisms and land-atmosphere interactions. Third, a surface water quality model was used to assess the impact of wastewater discharges and develop pathogen contamination indicators in two sites along the Sonora River. To parameterize the water quality model, pathogenic indicator loadings and removal rates were estimated, along with their uncertainty. Results from the water quality modeling show regions in the watershed that may be exceeding pathogenic standards, but also that uncertainty in model parameters requires a probabilistic approach for estimating risks. Finally, a workshop was conducted to explore the use of participatory modeling frameworks in less developed regions. Results indicate that respondents agreed strongly with the hydrologic and water quality modeling methodologies presented and considered the modeling results useful. Our results also show that participatory modeling approaches can have short term impacts as seen in the changes in water-related risk perceptions. In total, these projects revealed that water resources management solutions need to take into account variations across the human landscape (i.e. risk perceptions) and variations in the biophysical response of watersheds to natural phenomena (i.e. streamflow generation) and to anthropogenic activities (i.e. contaminant fate and transport). In addition, this work underscores the notion that sustainable water resources solutions need to contend with uncertainty in our understanding and predictions of human perceptions and biophysical systems.

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

USGS Publications Warehouse

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 that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

Proposal and work plan to calibrate and verify a water-quality model to simulate effects of wastewater discharges to the Red River of the North at drought streamflow near Fargo, North Dakota, and Moorhead, Minnesota

USGS Publications Warehouse

Wesolowski, Edwin A.

2000-01-01

This report presents a proposal for conducting a water-quality modeling study at drought streamflow, a detailed comprehensive plan for collecting the data, and an annual drought-formation monitoring plan. 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 streamflow from the Sheyenne River. The water-quality modeling study will evaluate the effects of continuous treated-wastewater discharges to the study reach at drought streamflow. The study will define hydraulic characteristics and reaeration and selected reaction coefficients and will calibrate and verity a model.The study includes collecting synoptic water-quality samples for various types of analyses at a number of sites in the study reach. Dye and gas samples will be collected for traveltime and reaeration measurements. Using the Lagrangian reference frame, synoptic water-quality samples will be collected for analysis of nutrients, chlorophyll a, alkalinity, and carbonaceous biochemical oxygen demand. Field measurements will be made of specific conductance, pH, air and water temperature, dissolved oxygen, and sediment oxygen demand. Two sets of water-quality data will be collected. One data set will be used to calibrate the model, and the other data set will be used to verity the model.The DAFLOW/BLTM models will be used to evaluate the effects of the treated wastewater on the water quality of the river. The model will simulate specific conductance, temperature, dissolved oxygen, carbonaceous biochemical oxygen demand, total nitrogen (organic, ammonia, nitrite, nitrate), total orthophosphorus, total phosphorus, and phytoplankton as chlorophyll a.The work plan identifies and discusses the work elements needed for accomplishing the data collection for the study. The work elements specify who will provide personnel, vehicles, instruments, and supplies needed during data collection. The work plan contains instructions for data collection; inventory lists of needed personnel, vehicles, instruments, and supplies; and examples of computations for determining quantities of tracer to be injected into the stream. The work plan also contains an annual drought-formation monitoring plan that includes a 9-month time line that specifies when essential planning actions must occur before actual project start up. Drought streamflows are rare. The annual drought-formation monitoring plan is presented to assist project planning by providing early warning that conditions are favorable to produce drought streamflow. The plan to monitor drought-forming conditions discusses the drought indices to be monitored. To establish a baseline, historic values for some of the drought indices for selected years were reviewed. An annual review of the drought indices is recommended.

Research on Coupling Method of Watershed Initial Water Rights Allocation in Daling River

NASA Astrophysics Data System (ADS)

Liu, J.; Fengping, W.

2016-12-01

Water scarcity is now a common occurrence in many countries. The situation of watershed initial water rights allocation has caused many benefit conflicts among regions and regional water sectors of domestic and ecology environment and industries in China. This study aims to investigate the method of watershed initial water rights allocation in the perspective of coupling in Daling River Watershed taking provincial initial water rights and watershed-level governmental reserved water as objects. First of all, regarding the allocation subsystem of initial water rights among provinces, this research calculates initial water rights of different provinces by establishing the coupling model of water quantity and quality on the principle of "rewarding efficiency and penalizing inefficiency" based on the two control objectives of water quantity and quality. Secondly, regarding the allocation subsystem of watershed-level governmental reserved water rights, the study forecasts the demand of watershed-level governmental reserved water rights by the combination of case-based reasoning and water supply quotas. Then, the bilaterally coupled allocation model on water supply and demand is designed after supply analysis to get watershed-level governmental reserved water rights. The results of research method applied to Daling River Watershed reveal the recommended scheme of watershed initial water rights allocation based on coordinated degree criterion. It's found that the feasibility of the iteration coupling model and put forward related policies and suggestions. This study owns the advantages of complying with watershed initial water rights allocation mechanism and meeting the control requirements of water quantity, water quality and water utilization efficiency, which help to achieve the effective allocation of water resources.

Modelling Parameters Characterizing Selected Water Supply Systems in Lower Silesia Province

NASA Astrophysics Data System (ADS)

Nowogoński, Ireneusz; Ogiołda, Ewa

2017-12-01

The work presents issues of modelling water supply systems in the context of basic parameters characterizing their operation. In addition to typical parameters, such as water pressure and flow rate, assessing the age of the water is important, as a parameter of assessing the quality of the distributed medium. The analysis was based on two facilities, including one with a diverse spectrum of consumers, including residential housing and industry. The carried out simulations indicate the possibility of the occurrence of water quality degradation as a result of excessively long periods of storage in the water supply network. Also important is the influence of the irregularity of water use, especially in the case of supplying various kinds of consumers (in the analysed case - mining companies).

Cumulative uncertainty in measured streamflow and water quality data for small watersheds

USGS Publications Warehouse

Harmel, R.D.; Cooper, R.J.; Slade, R.M.; Haney, R.L.; Arnold, J.G.

2006-01-01

The scientific community has not established an adequate understanding of the uncertainty inherent in measured water quality data, which is introduced by four procedural categories: streamflow measurement, sample collection, sample preservation/storage, and laboratory analysis. Although previous research has produced valuable information on relative differences in procedures within these categories, little information is available that compares the procedural categories or presents the cumulative uncertainty in resulting water quality data. As a result, quality control emphasis is often misdirected, and data uncertainty is typically either ignored or accounted for with an arbitrary margin of safety. Faced with the need for scientifically defensible estimates of data uncertainty to support water resource management, the objectives of this research were to: (1) compile selected published information on uncertainty related to measured streamflow and water quality data for small watersheds, (2) use a root mean square error propagation method to compare the uncertainty introduced by each procedural category, and (3) use the error propagation method to determine the cumulative probable uncertainty in measured streamflow, sediment, and nutrient data. Best case, typical, and worst case "data quality" scenarios were examined. Averaged across all constituents, the calculated cumulative probable uncertainty (??%) contributed under typical scenarios ranged from 6% to 19% for streamflow measurement, from 4% to 48% for sample collection, from 2% to 16% for sample preservation/storage, and from 5% to 21% for laboratory analysis. Under typical conditions, errors in storm loads ranged from 8% to 104% for dissolved nutrients, from 8% to 110% for total N and P, and from 7% to 53% for TSS. Results indicated that uncertainty can increase substantially under poor measurement conditions and limited quality control effort. This research provides introductory scientific estimates of uncertainty in measured water quality data. The results and procedures presented should also assist modelers in quantifying the "quality"of calibration and evaluation data sets, determining model accuracy goals, and evaluating model performance.

Numerical modeling of chemical spills and assessment of their environmental impacts

USDA-ARS?s Scientific Manuscript database

Chemical spills in surface water bodies often occur in modern societies, which cause significant impacts on water quality, eco-environment and drinking water safety. In this paper, chemical spill contamination in water resources was studied using a depth-integrated computational model, CCHE2D, for p...