Thomas G. Sanders

Enhancing water quality in hydropower system operations

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;

Oxygen sag equation for second-order BOD decay

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Chapter 13 Water Quality Monitoring Networks

Abstract A dissolved oxygen (DO) equation for a stream is developed in which the biochemical oxygen demand (BOD) deoxygenation rate is described as a second-order reaction. Rate constants for a second-order BOD equation may be evaluated by graphical or numerical methods. The DO sag equation incorporates exponential integral functions. These functions are available in tabular form or they may be calculated by exact or approximate series. The time at which the minimum DO concentration occurs is calculated numerically. The DO sag equation using a second-order BOD model fills a gap in the literature, as a number of investigators had explored describing BOD decay as a second-order reaction but the corresponding DO sag equation was not available to predict the impact of such wastes on a river.

Uncertainty in Water Quality Data

Publisher Summary This chapter discusses the water quality monitoring networks. Environmental legislation and general water quality awareness have been responsible for recent increased monitoring and sampling of water in streams. Such monitoring and testing can be expensive and a scientific approach to minimizing costs whilst maximizing benefits is desirable. The assumption that a water quality monitoring network can detect trends in water quality, check compliance with stream standards, and measure ambient water quality, etc., is incorporated into legislation for water quality management. Monitoring performed by government agencies is, in many cases, conducted over large geographic areas covering many kilometers of streams. By using most resources to physically collect water samples, little resources are left to consider the representativeness of the sample in time and space, data analysis or data use.

Urban Water Demand

Abstract Water quality data are collected to provide information to assist in the understanding and managing of water resources. The usefulness of water quality data collected is inversely related to the amount of uncertainty in the data. Data uncertainty may be defined as a state of doubt in how representative observed values are of the true population characteristics. Data uncertainty may be estimated as a function of both sampling and nonsampling errors. Sampling errors result from the sampling network design (location and frequency of sample collection) which samples only a subset of the total population. Nonsampling errors result from the process of measuring the amount of water quality material present. The measurement process may be divided into sample collection and laboratory analysis. Sample collection includes the physical procedure for obtaining, storing, and transporting a water sample for later analysis. Laboratory analysis consists of some method of estimating the amount (concentration) of a given material in the water sample. Presented here is a general discussion of the sources of water quality data uncertainty, a method to estimate data uncertainty in water quality variables, and the implications of uncertainty in water quality data.

Unpaved Road Dust Control in the Piceance Creek Basin in Rio Blanco County, Colorado

Water demand generally referred to as future water requirements will be a function of the demanding entity. The demand characteristics such as trending, jumps, periodicity and stochasticity are different for an urban demand, irrigation and agriculture demand, industrial and hydropower demands. The variation in demand can be large as well. For example, urban water demand will vary hourly, daily, weekly, seasonally and annually. Whereas, irrigation demand in the Western United States, where appropriative water rights exists (first in time, first in right), although quite seasonal is much more predictable as most water rights specify a specific amount of water delivered during a specified period of time. If the demand exceeds the supply, the water rights having the highest priority will be supplied first and those rights having a lower priority may not receive any water at all.

Water Quality Model Incorporates Unconventional Bod Reduction

AbstractRoad dust from unpaved roads (dirt roads) is a major source of airborne particulates; the loss of those fines accelerates the deterioration of roads. As a result, road dust emissions are a major concern of the users and managers of dirt roads. Exxon Mobil has been concerned with the dust emissions and rapid road deterioration of the access roads in its natural gas production facility in the Piceance Creek Basin north of Rifle, Colorado. As part of the access road management plan for Exxon Mobil Piceance Creek, a research project was initiated to investigate the effectiveness of several chemical dust suppressants in reducing dust emissions, thus prolonging the intervals between periodic maintenance. Rio Blanco County and the Bureau of Land Management participated in this project. Using the Colorado State University Dustometer and its associated dust measurement protocol, it was found that all chemical suppressants decrease dust emissions and that magnesium chloride (MgCl2) was the most effective du...

Wastewater Reuse — a Worldwide Issue

Biochemical Oxygen Demand (BOD) reduction through the joint action of BOD decay expressed as an unconventional second order reaction and sedimentation is incorporated into a dissolved oxygen (DO) sag model for a river. A term named the Phelps-Thomas index, which is a function of the reaeration and sedimentation rate constants, is introduced and presented as a composite measure of river and wastewater rejuvenation characteristics. Calculations using ranges of reaeration and sedimentation rates show the Phelps-Thomas index has values between –2 and 10 or larger, with large values associated with rapid recovery of DO. The time at which the minimum DO occurs is calculated numerically. Examples apply the DO sag model to logging debris in a stream. INTRODUCTION For decades, the pioneering work of Streeter and Phelps served as a basis for water quality modeling in a river [1]. Their classic dissolved oxygen sag model *Financial support was provided by the Louisiana Transportation Research Center, Louisiana Water Resources Institute, and a sabbatical leave for Adrian. 303 2006, Baywood Publishing Co., Inc. related stabilization of an organic waste measured by the biochemical oxygen demand (BOD) and the dissolved oxygen (DO) resources of the river. Thomas accounted for settleable BOD in the DO sag equation [2]. The effect of dispersion on BOD and DO in small rivers has been found to be negligible [3]. The BOD reaction model is an empirical expression chosen on the basis of convenience to describe the complex transformations that take place as BOD stabilizes in a water body. A first order BOD decay equation has been widely applied to describe the deoxygenation rate of most municipal wastewaters, although an unconventional second order rather than a first order model was introduced by Thomas [4] prior to being applied by many investigators [5-11]. Conventional practice treats the BOD reaction as being first order; however, in this investigation the term unconventional reaction order designates a BOD reaction that is other than first order. Streams are subject to many sources of BOD loadings in addition to municipal wastewaters; this study draws upon the BOD characteristics of logging debris as measured by Ponce [12]. Rigorous statistical bases for deciding whether a first order or an unconventional second order BOD model provided a better fit to data are available [7, 13]. An analytical DO sag equation that incorporated second order reaction kinetics to describe BOD decay was not available until one was developed in 1998 [10], simplified in 2003 [11], and generalized in 2004 [14]. A notable deficiency of these BOD and DO models was that they did not include loss of BOD by sedimentation. As a result, an analytical DO sag model is not currently available that incorporates BOD decay as a second order reaction while also including loss of BOD by sedimentation. The primary objective of this study was to develop a methodology for including BOD loss through sedimentation in a DO sag model which included BOD decay expressed as a second order reaction. In addition, an expression was to be developed with which to calculate the time to reach the minimum dissolved oxygen concentration. A secondary objective was to show through examples how to determine the BOD rate constant and the ultimate BOD from logging debris data. Additional examples were to demonstrate the effect of sedimentation rates on the DO behavior of streams in which BOD decays by a second order reaction. SECOND ORDER BOD MODEL The second order BOD decay model applied to a moving plug flow reactor or a moving Lagrangian control volume as proposed in [4] is L t L k L t ( ) 0 2 0 1 (1) in which L(t) = BOD remaining at time t, g/m, L0 = BOD at time zero, t = elapsed time or flow time, day, and k2 = BOD deoxygenation reaction rate 304 / ROIDER ET AL.

Environmental Pollution in Colorado by Nuclear Processing

Water resource shortages are a problem that are plaguing the world. Wastewater recycling and reuse may be the solution to this worldwide problem. Recycled and properly treated wastewater is a safe alternative source for irrigation, industry, groundwater recharge, and miscellaneous subpotable uses. The biggest problem with wastewater recycling and reuse is the concern for potential health risks. Currently, there are wastewater recycling and reuse projects in Singapore, Israel, Colorado, California, Florida as well as others. While California leads the way in developing regulations for wastewater recycling and reuse and the US EPA has developed a manual on water reuse criteria, much debate exists regarding regulations, uses and appropriate levels.

Environmental Pollution by Mining in Colorado

Many sources of pollution are just beginning to be identified in Colorado, especially since the emphasis on controlling point source pollution for the past twenty years in the USA has not cleaned up the environment. One source, mining, is important due to its volume of waste and its worldwide impact, and the other is important not so much for the volume of nuclear wastes but for its toxicity. The production and effects of nuclear wastes has historically suffered from a lack of knowledge due to secrecy. Because of this, the amount and distribution of nuclear wastes are just beginning to be understood. This text reports on the extent of pollutant releases and initial cleanup procedures being conducted at the Rocky Flats Nuclear Processing Plant near Denver, Colorado, USA.