Abstract

The collection and analysis of samples from storm events constitutes a large portion of the effort associated with water quality research. Estimating concentrations or loads from these events is often difficult. The equipment necessary to analyze the samples and the required laboratory resources are typically significant expenses incurred by the researcher. One potential method to reduce these costs is through the development of generic relationships between concentrations and easily measured variables such as dimensionless flow rate or time. The benefits recognized from such an effort include a reduction in the number of required samples, resulting in a reduction in cost. Using data collected from an Arkansas stream near Fayetteville, relationships between the generic variables (time and flow) and several constituents (nitrate–N, orthophosphate, total phosphorus, ammonia–N, total Kjeldahl nitrogen, chemical oxygen demand, total suspended solids, fecal coliforms, and fecal streptococci) were examined. Results of the analyses indicated that a form of the gamma function could be used to estimate the flow–weighted mean concentrations and loads of the constituents at a significant cost savings to the user, assuming that single–peak hydrograph data were readily available. By using a single sample collected at the peak of the storm along with information pertaining to the time of sample collection, time of the peak of the storm hydrograph, and the constituent concentration of the sample, the flow–weighted mean concentration or load could be determined. Results of the analysis indicate that the method performed reasonably well. Since the analysis of only one sample is required to determine the flow–weighted mean concentration or load, instead of several samples, this method is quite appealing to users on a limited budget.

Document Type

Article

Publication Date

3-2003

Notes/Citation Information

Published in Transactions of the ASAE, v. 46, issue 2, p. 245-256.

© 2003 American Society of Agricultural Engineers

The copyright holder has granted the permission for posting the article here.

Digital Object Identifier (DOI)

https://doi.org/10.13031/2013.12975

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