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Monday, August 10, 2020 | History

2 edition of Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams found in the catalog.

Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams

Harvey E. Jobson

Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams

by Harvey E. Jobson

  • 376 Want to read
  • 23 Currently reading

Published by Diane Pub Co .
Written in English

    Subjects:
  • Science/Mathematics

  • The Physical Object
    FormatPaperback
    ID Numbers
    Open LibraryOL10856433M
    ISBN 100756708583
    ISBN 109780756708580

    A Genetic Algorithm-Artificial Neural Network Method for the Prediction of Longitudinal Dispersion Coefficient in Rivers: /ch In this chapter a novel method, the Genetic Neural Mathematical Method (GNMM), for the prediction of longitudinal dispersion coefficient is presented. ThisCited by: 2. This fascinating work is divided into two main sections. Part I reviews the basic principles of water movement in channels and the mass balance approach common to most models. It also covers the practical usefulness, model peer review, and guidance on model selection and calibration. Part II discusses flow simulation and prediction of time of travel, dye tracing and mixing, heat .

    COVID Resources. Reliable information about the coronavirus (COVID) is available from the World Health Organization (current situation, international travel).Numerous and frequently-updated resource results are available from this ’s WebJunction has pulled together information and resources to assist library staff as they consider how to handle . Downloadable (with restrictions)! Abstract Accurate prediction of longitudinal dispersion coefficient (K) is a key element in studying of pollutant transport in rivers when the full cross sectional mixing has occurred. In this regard, several research studies have been carried out and different equations have been proposed. The predicted values of K obtained by different Cited by:

    pollutants transport to longitudinal dispersion coefficient. Owing to the importance of longitudinal dispersion coefficient in water quality related issues, many studies have been developed to predict longitudinal dispersion coefficient in rivers File Size: KB. Accurate estimation of longitudinal dispersion coefficient is required in several applied hydraulic problems such as: river engineering, environmental engineering, intake designs, estuaries problems and risk assessment of injection of hazardous pollutant and contaminants into river flows (Sedighnezhad et al., ; Seo & Bake, ).Investigation of quality condition of natural rivers Cited by: 2.


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Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams by Harvey E. Jobson Download PDF EPUB FB2

Supply is a constant concern to those diverting and using water from streams and rivers. A method of rapidly estimating traveltime or dispersion is needed for pollution control or warning systems on streams where data are limited.

As greater demands are placed on streams, the evaluation of significant forces ofCited by: Buy Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams on FREE SHIPPING on qualified orders Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams: Harvey E.

Jobson: : Books. The possibility of a contaminant being accidentally or intentionally spilled upstream from a water supply is a constant concern to those diverting and using water from streams and rivers.

Although many excellent models are available to estimate traveltime and dispersion, none can be used with confidence before calibration and verification to the particular river reach in.

The most significant other variable in the correlation was the ratio of the river discharge to mean annual discharge. The prediction of the traveltime is more difficult than the prediction of unit-peak concentration; but the logarithm of stream velocity can be assumed to be linearly correlated with the logarithm of by: BibTeX @MISC{_predictionof, author = {}, title = {Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams}, year = {}}.

Prediction of Traveltime and Longitudinal Dispersion in Rivers and Streams by Harvey E. Jobson. USGS, Water Resources Division National Center Reston, VA Internet: [email protected] Phone: () FAX: () To implement this study, a total of 69 measured longitudinal dispersion coefficient data obtained from 29 natural streams were used.

These data sets were obtained from the study by Deng et al. The data include discharge, shear velocity, normalized relative width (W/H) and normalized velocity (U/U*).Cited by: 5. Download PDF: Sorry, we are unable to provide the full text but you may find it at the following location(s): (external link) http.

An analytical method is developed to determine the longitudinal dispersion coefficient in Fischer's triple integral expression for natural rivers.

The method is based on the hydraulic geometry relationship for stable rivers and on the assumption that the uniform-flow formula is valid for local depth-averaged variables.

A new expression for the prediction of longitudinal dispersion coefficient in natural rivers, using genetic algorithms, is proposed. The expression uses hydraulic and geometric characteristics of. Introduction.

The longitudinal dispersion coefficient (D) is an important parameter that describes the transport of solutes in streams and te estimation of the dispersion coefficient is important from human health and public safety perspectives as the parameter is needed to predict contaminant concentrations near drinking water intakes and receiving water Cited by:   Using a new channel shape equation for straight channels and a more versatile channel shape or local flow depth equation for natural streams a method is developed for prediction of the longitudinal dispersion coefficient in single-channel natural streams, including straight and meandering ones.

The longitudinal dispersion coefficient is a key element in determining the distribution and transmission of pollution, especially when cross-sectional mixing is completed.

However, the existing predictive techniques for this purpose exhibit great amounts of Cited by: usage of a river or estuarine system can bypass the need for a reliable means of predicting the dispersion characteristics of the water body (Sooky ).

There have been many studies on longitudinal dispersion ofpollutants in rivers and natural streams. The best-knownstudy, usually quoted in texts on the subject, is the Fickian Size: 4MB. The possibility of a contaminant being accidentally or intentionally spilled in a river is a constant concern to those using the water.

Methods are developed to estimate: (1) the velocity of a contaminant in a river; (2) the rate of attenuation of the peak concentration of a conservative contaminant; and (3) the time required for a contaminant plume to pass a point. Sahay R.R. Prediction of longitudinal dispersion coefficients in natural rivers using artificial neural network.

Environ. Fluid Mechanics 11 Sahay R.R. Dutta S. Prediction of longitudinal dispersion coefficients in natural rivers using genetic algorithm. Hydrology Research 40(6) Sayre W.W. Cited by:   The water quality problems of rivers and streams are controlled by the natural behaviour of the water body, which is interpreted by means of proper terms and expressions of free surface hydraulics.

Pollution transport is due primarily to advection, but there are many situations in which dispersion plays an important role and cannot be : Marcello Benedini, George Tsakiris.

A fully hydrodynamic 2-D, depth averaged advection-dispersion solute transport numerical simulation study on hypothetical stream with pool reveals that a pool can sharply enhance longitudinal spreading, cause a lag in the plume travel-time and radically increase solute residence time in the by: 5.

The dispersion coefficients obtained by the routing procedure are used to test a theory for predicting dispersion coefficients, proposed by the writer in a separate paper.

The predicted and observed coefficients agree within 30% in half of the tests, and in the remainder (including some highly nonuniform streams) within a factor of by: longitudinal dispersion coefficients for the River Waters were not constant, but varies between m2/s, from point to point along the River Water surface depending on the hydraulic parameters.

Uchenna and Nwaogazie [10] observed that the value of its tracer measurement for the longitudinal dispersion coefficient. This paper presents the results of an experimental work conducted in the framework of a research project that deals with the effect of dead zones (groyne fields, harbours) on the longitudinal dispersion in rivers.

The objective is an improved prediction of travel time, maximum concentration and skewness of a tracer cloud than is possible with existing alarm models.Get this from a library! Contaminants in rivers and streams: prediction of travel time and logitudinal dispersion.

[Harvey E Jobson].Distribution of Water-Resources Investigations Report"Prediction of traveltime and longitudinal dispersion in rivers and streams," by Harvey E.

Jobson In Reply Refer To: Ap Mail Stop OFFICE OF SURFACE WATER TECHNICAL MEMORANDUM NO. Subject: Distribution of Water-Resources Investigations Report"Prediction of traveltime and longitudinal dispersion .