Reaeration equations derived from US geological survey database

Citation
Cs. Melching et He. Flores, Reaeration equations derived from US geological survey database, J ENV ENG, 125(5), 1999, pp. 407-414
Citations number
26
Categorie Soggetti
Environment/Ecology,"Environmental Engineering & Energy
Journal title
JOURNAL OF ENVIRONMENTAL ENGINEERING-ASCE
ISSN journal
07339372 → ACNP
Volume
125
Issue
5
Year of publication
1999
Pages
407 - 414
Database
ISI
SICI code
0733-9372(199905)125:5<407:REDFUG>2.0.ZU;2-R
Abstract
(A)ccurate estimation of the reaeration-rate coefficient (K-2) is extremely important for waste-load allocation. Currently, available K-2 estimation e quations generally yield poor estimates when applied to stream conditions d ifferent from those for which the equations were derived because they were derived from small databases composed of potentially highly inaccurate meas urements. A large data set of K-2 measurements made with tracer-gas methods was compiled from U.S. Geological Survey studies. This compilation include d 493 reaches on 166 streams in 23 states. Careful screening to detect and eliminate erroneous measurements reduced the data set to 371 measurements. These measurements were divided into four subgroups on the basis of flow re gime (channel control or pool and riffle) and stream scale (discharge great er than or less than 0.556 m(3)/s). Multiple linear regression in logarithm s was applied to relate K-2 to 12 stream hydraulic and water-quality charac teristics. The resulting best-estimation equations had the form of semiempi rical equations that included the rate of energy dissipation and discharge or depth and width as variables. For equation verification, a data set of K -2 measurements made with tracer-gas procedures by other agencies was compi led from the literature. This compilation included 127 reaches on at least 24 streams in at least seven states. The standard error of estimate obtaine d when applying the developed equations to the U.S. Geological Survey data set ranged from 44 to 61%, whereas the standard error of estimate was 78& w hen applied to the verification data set.