Submitted to: Texas Journal of Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 1, 2002
Publication Date: May 20, 2002
Citation: Harmel, R.D., King, K.W., Wolfe, J.E., Torbert, H.A. Minimum flow considerations for automated storm sampling on small watersheds. Texas Journal of Science. 2002. v. 54(2). p. 177-188.
Interpretive Summary: As human population grows and water resources increase in value from a drinking water, industrial use, and environmental standpoint, accurate measurement of water quality will become more important. In order to correctly measure water quality, the traditional method of monitoring low flows with periodic grab samples to characterize pollution from factories and waste water treatment plants must be coupled with storm flow monitoring to measure pollution in runoff from urban areas, farms, and forestry operations. Even though storm monitoring is important, no guidance is available on developing storm sampling strategies for small streams. This guidance is needed to assist in developing sampling strategies to accurately measure pollutant movement. With this in mind, we compared several methods to manage the number samples taken by automated sampling equipment. Based on this study, we determined that it is better to increase the time between samples than to raise the level at which sampling begins. This result should assist monitoring project managers to develop monitoring programs that adequately measure pollutant movement in storm flow while not exceeding budget or personnel limitations.
In order to adequately quantify water quality constituent fluxes, the traditional methodology of monitoring low flows with periodic grab samples to characterize point sources must be coupled with storm flow monitoring to characterize nonpoint sources. However, since guidance on developing storm sampling strategies for small streams is limited and in light of budget and personnel constraints in most monitoring projects, appropriate guidance is needed to develop sampling strategies that accurately characterize pollutant flux within project resources. With this need in mind, the objectives of this study were to: 1) compare measured nutrient flux data to data collected under various minimum flow threshold or enable level scenarios and 2) publish initial guidance on setting minimum flow thresholds for automated storm sampling. Comparison of measured nutrient fluxes for various enable level scenarios illustrated that substantial error is introduced even with relatively small enable level increases. Based on these results, minimum flow thresholds for automated sampling equipment should be set such that even small storms with small increases in flow depth are captured. In order to manage the number of samples collected, enable levels should not be raised. Alternatives for decreasing the number of samples in nutrient flux measurements, such as increasing the time or flow volume between samples, or compositing several samples, introduce substantially less error than do increases in minimum flow thresholds.