Updating the U.S. Nationwide Urban runoff quality data base

1999 ◽  
Vol 39 (12) ◽  
pp. 9-16 ◽  
Author(s):  
James T. Smullen ◽  
Amy L. Shallcross ◽  
Kelly A. Cave
Keyword(s):  
Water Quality ◽  
Data Base ◽  
Oxygen Demand ◽  
Urban Runoff ◽  
The United States ◽  
Geographic Region ◽  
Storm Water ◽  
Quality Data ◽  
Water Quality Data ◽  
Urban Stormwater Quality

Urban stormwater quality data collected over the past 20 years for several large government-sponsored sampling programs in the United States were assembled and analyzed to develop new nationwide estimators and statistics for urban storm water quality. We believe that this is the first attempt to assemble and analyze these major storm water quality data sets for this purpose. In this paper, the first public report of our work to-date, we present the results of the data acquisition, data base assembly, quality assurance, computation of new stormwater event mean concentrations and associated statistics, and comparisons with the original U.S. Environmental Protection Agency's Nationwide Urban Runoff Program (NURP) results. The differences between the pooled means and those estimated from our analysis of the NURP data range from a 79% lower estimate for Copper to a 36% higher estimate for Biochemical Oxygen Demand. It is concluded that the variations between the NURP results and those developed here from the pooling of the three national data bases are important and that future work may provide a basis for differentiating Event Mean Concentrations among urban land uses, geographic region and seasons.

scholarly journals URBAN GROWTH AND WATER QUALITY IN THIMPHU, BHUTAN

2013 ◽  
pp. 82-95 ◽  
Author(s):  
Nandu Giri ◽  
O. P. Singh
Keyword(s):  
Water Quality ◽  
Urban Area ◽  
Water Samples ◽  
Urban Areas ◽  
Forest Cover ◽  
Rapid Development ◽  
Oxygen Demand ◽  
Capital City ◽  
Quality Data ◽  
Water Quality Data

Detailed study was undertaken in 2008 and 2009 on assessment of water quality of River Wang Chhu which flows through Thimphu urban area, the capital city of Bhutan. The water samples were examined at upstream of urban area, within the urban area and its downstream. The water samples were analyzed by studying the physico-chemical, biological and benthic macro-invertebrates. The water quality data obtained during present study are discussed in relation to land use/land cover changes(LULC) and various ongoing human activities at upstream, within the each activity areas and it’s downstream. Analyses of satellite imagery of 1990 and 2008 using GIS revealed that over a period of eighteen years the forest, scrub and agricultural areas have decreased whereas urban area and road network have increased considerably. The forest cover, agriculture area and scrub decreased from 43.3% to 42.57%, 6.88% to 5.33% and 42.55% to 29.42%, respectively. The LULC changes effect water quality in many ways. The water temperature, pH, conductivity, total dissolved solids, turbidity, nitrate, phosphate, chloride, total coliform, and biological oxygen demand were lower at upstream and higher in urban area. On the other hand dissolved oxygen was found higher at upstream and lower in urban area. The pollution sensitive benthic macro-invertebrates population were dominant at upstream sampling sites whereas pollution tolerant benthic macro-invertebrates were found abundant in urban area and its immediate downstream. The rapid development of urban infrastructure in Thimphu city may be posing serious threats to water regime in terms of its quality. Though the deterioration of water quality is restricted to a few localized areas, the trend is serious and needs proper attention of policy planners and decision makers. Proper treatment of effluents from urban areas is urgently needed to reduce water pollution in such affected areas to check further deterioration of water quality. This present study which is based on upstream, within urban area and downstream of Thimphu city can be considered as an eye opener.

scholarly journals Time series modeling of biochemical oxygen demand at the upstream catchment of Feitsui Reservoir, Taiwan

2016 ◽  
Vol 47 (5) ◽  
pp. 1069-1085 ◽  
Author(s):  
Yung-Chia Chiu ◽  
Chih-Wei Chiang ◽  
Tsung-Yu Lee
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Biochemical Oxygen Demand ◽  
Oxygen Demand ◽  
Quality Data ◽  
Series Data ◽  
Water Quality Data ◽  
Inference System ◽  
Feitsui Reservoir ◽  
Upstream Catchment

The adaptive neuro fuzzy inference system (ANFIS) has been proposed to model the time series of water quality data in this study. The biochemical oxygen demand data collected at the upstream catchment of Feitsui Reservoir in Taiwan for more than 20 years are selected as the target water quality variable. The classical statistical technique of the Box-Jenkins method is applied for the selection of appropriate input variables and data pre-processing of using differencing is implemented during the model development. The time series data obtained by ANFIS models are compared to those obtained by autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs). The results show that the ANFIS model identified at each sampling station is superior to the respective ARIMA and ANN models. The R values at all sampling stations of the training and testing datasets are 0.83–0.98 and 0.81–0.89, respectively, except at Huang-ju-pi-liao station. ANFIS models can provide accurate predictions for complex hydrological processes, and can be extended to other areas to improve the understanding of river pollution trends. The procedure of input selection and the pre-processing of input data proposed in this study can stimulate the usage of ANFIS in other related studies.

Empowering Community Water Data Stakeholders

2019 ◽  
Vol 31 (5) ◽  
pp. 492-506
Author(s):  
John Millar Carroll ◽  
Jordan Beck ◽  
Elizabeth W Boyer ◽  
Shipi Dhanorkar ◽  
Srishti Gupta
Keyword(s):  
Water Quality ◽  
Best Practices ◽  
The United States ◽  
Quality Data ◽  
Community Informatics ◽  
Water Quality Data ◽  
Quality Practices ◽  
Data Practices ◽  
Information Infrastructures ◽  
Local Water

Abstract Access to clean water is a critical challenge and opportunity for community-level collaboration. People rely on local water sources, but awareness of water quality and participation in water management is often limited. Lack of community engagement can increase risks of water catastrophes, such as those in Flint, Michigan, and Cape Town, South Africa. We investigated water quality practices in a watershed system serving c.100 000 people in the United States. We identified a range of entities including government and nonprofit citizen groups that gather water quality data. Many of these data are accessible in principle to citizens. However, the data are scattered and diverse; information infrastructures are primitive and not integrated. Water quality data and data practices are hidden in plain sight. Based on fieldwork, we consider sociotechnical courses of action, drawing on best practices in human–computer interaction and community informatics, data and environmental systems management.

scholarly journals A Multivariate and Spatiotemporal Analysis of Water Quality in Code River, Indonesia

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mochamad A. Pratama ◽  
Yan D. Immanuel ◽  
Dwinanti R. Marthanty
Keyword(s):  
Water Quality ◽  
Land Cover ◽  
Agricultural Land ◽  
Water Quality Management ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Water Quality Data

The efficacy of a water quality management strategy highly depends on the analysis of water quality data, which must be intensively analyzed from both spatial and temporal perspectives. This study aims to analyze spatial and temporal trends in water quality in Code River in Indonesia and correlate these with land use and land cover changes over a particular period. Water quality data consisting of 15 parameters and Landsat image data taken from 2011 to 2017 were collected and analyzed. We found that the concentrations of total dissolved solid, nitrite, nitrate, and zinc had increasing trends from upstream to downstream over time, whereas concentrations of parameter biological oxygen demand, cuprum, and fecal coliform consistently undermined water quality standards. This study also found that the proportion of natural vegetation land cover had a positive correlation with the quality of Code River’s water, whereas agricultural land and built-up areas were the most sensitive to water pollution in the river. Moreover, the principal component analysis of water quality data suggested that organic matter, metals, and domestic wastewater were the most important factors for explaining the total variability of water quality in Code River. This study demonstrates the application of a GIS-based multivariate analysis to the interpretation of water quality monitoring data, which could aid watershed stakeholders in developing data-driven intervention strategies for improving the water quality in rivers and streams.

Overview of Federal Law and USEPA Regulations for Urban Runoff

1994 ◽  
Vol 29 (1-2) ◽  
pp. 445-454 ◽  
Author(s):  
Larry A. Roesner ◽  
Paul Traina
Keyword(s):  
Water Quality ◽  
Environmental Protection Agency ◽  
Urban Areas ◽  
Water Quality Management ◽  
Urban Runoff ◽  
The United States ◽  
Storm Water ◽  
Water Quality Control ◽  
Drainage Systems ◽  
Wet Weather

Within the last three years, the United States Environmental Protection Agency (USEPA) has taken two significant steps with respect to regulating the quality of storm water discharges from urban areas. The first of these is the development of Final Rules and Regulations for Storm Water Discharges from urban areas with separated waste water and storm drainage systems. Published in late 1990, the rule requires all municipalities with populations over 100,000 to apply for a permit to discharge storm water under the USEPA's National Pollutant Discharge Elimination System (NPDES). The permit application must include, among other things, a plan to reduce the pollutants in urban runoff to the “Maximum Extent Practicable”. The second step is the publication in January, 1993, of a draft policy regulating discharges from combined sewer systems. These two initiatives for water quality control of wet weather discharges from urban drainage systems are significant steps forward in a national program to reduce pollution contributions to receiving waters in urban areas. This paper provides an overview of the requirements of these two wet weather water quality management programs.

Estimation of Storm Water Quality Characteristics and Overflow Loads from Treatment Plant Influent Data

1990 ◽  
Vol 22 (10-11) ◽  
pp. 77-85
Author(s):  
Roelof H. Aalderink
Keyword(s):  
Water Quality ◽  
Treatment Plant ◽  
Storm Water ◽  
Quality Data ◽  
Combined Sewer Overflows ◽  
Water Quality Data ◽  
Frequency Distributions ◽  
Simulation Techniques ◽  
Combined Sewer ◽  
In Series

A simple model, based on tanks in series, for the estimation of mean annual loads and frequency distributions of loads from combined sewer systems is presented. The input data, dry weather flow, dry weather quality, and storm water quality are estimated from treatment plant influent data. Two similar methods for the estimation of flow-average storm water quality were tested by using treatment plant influent data generated by the model in comparison with the model input. Both methods are based on daily mass balances, but differ slightly with respect to the averaging procedures used. The performance of both methods is about the same. They show a small bias, but the variability introduced is small when compared with the variation occurring in real storm water quality data. Application of one of the methods on field data revealed no distinct relationships between the flow-averaged storm water quality concentration and the dry weather period or the total daily rain depth. By combination of continuous and Monte Carlo simulation techniques the model can be used to estimate mean annual loads and frequency distribution of loads from combined sewer overflows. For the extreme events a large 90 % confidence interval was found due to the large variations in storm water quality.

Effect of Forest Cover on Water Treatment Costs

2017 ◽  
Vol 03 (04) ◽  
pp. 1750006 ◽  
Author(s):  
Travis Warziniack ◽  
Chi Ho Sham ◽  
Robert Morgan ◽  
Yasha Feferholtz
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Water Treatment ◽  
Forest Cover ◽  
The United States ◽  
Economic Benefits ◽  
Treatment Costs ◽  
Quality Data ◽  
Water Quality Data ◽  
The Impact

This paper studies the relationship between forest cover and drinking water chemical treatment costs using land use data and a survey by the American Water Works Association (AWWA). The survey gathers cost and water quality data from 37 treatment plants in forested ecoregions of the United States. We model the effect of forest conversion on the cost of water treatment using a two-step process. First, we examine the effect of changes in land use on water quality through an ecological production function. Second, we examine the effect of changes in water quality on cost of treatment through an economic benefits function. We find a negative relationship between forest cover and turbidity, but no relationship between forest cover and total organic carbon (TOC). Increasing forest cover in a watershed by 1% reduces turbidity by 3%, and increasing development by 1% in a watershed increases turbidity by 3%. The impact of development is more consistent across models than the impact of forest cover. We also find a large impact on turbidity from grazing in the watershed. Our economic benefits function shows a 1% increase in turbidity increases water treatment costs by 0.19%, and 1% increase in TOC increases water treatment costs by 0.46%. TOC has a clearer impact on costs than turbidity, which becomes insignificant when we omit one of our observations with high turbidity.

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