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Abstract. -- The issue of a minimum flow threshold (also referred to as enable level) above which to trigger sampling plays an important role in water quality sampling projects; however, guidance on developing appropriate storm sampling strategies for small streams is limited. As a result, arbitrary strategies are used that may not accurately characterize pollutant flux. Therefore, the objectives of this study were to: (1) compare measured nutrient flux data to hypothetical results collected under several alternative minimum flow threshold or enable level scenarios and (2) publish initial guidance on setting minimum flow thresholds for automated storm sampling in small watersheds. 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 sampled. In order to manage the number of samples collected, enable levels should be raised only after careful consideration of the resulting consequences. 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 into one collection bottle, introduce substantially less error than does increasing minimum flow thresholds.
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Monitoring water quality during storm events is becoming increasingly important in characterization of pollutant loading to water bodies, especially as National Water Quality Inventories (USEPA 1995; USEPA 2000) continue to report that nonpoint source (NPS) pollution adversely impacts rivers, lakes and coastal waters. NPS pollution includes runoff from diffuse sources such as urban areas, farms, and silvicultural operations. Excessive anthropogenic NPS inputs of the macro-nutrients, nitrogen (N) and phosphorus (P) or "cultural eutrophication" can create accelerated algal growth which degrades aquatic ecosystem health, increases water treatment costs and diminishes recreational and aesthetic values (Kolbe & Luedke 1993).
The traditional monitoring focus on periodic grab sampling of low flows to characterize point source pollution (discharged from specific locations such as factories and waste water treatment plants) is now often coupled with automated storm flow monitoring to characterize NPS pollution. Most commercially available automated samplers contain similar components, including: programmable operation and memory, water level recorder, sample collection pump and sample bottles. Typical storm sampling operation involves setting a minimum flow threshold or enable level to start and finish sampling (either a flow depth or a rainfall depth per specified time) and setting a time or flow interval on which to collect samples after the sampler is triggered. This type of automated storm monitoring is often the cornerstone of small watersheds projects whose objectives are to compare water quality impacts of various land management activities, evaluate water quality improvement following implementation of best management practices and determine annual pollutant fluxes for Total Maximum Daily Load (TMDL) projects (Tate et al. 1999; Robertson & Roerish 1999).
On small watershed monitoring projects, however, sampling and funding considerations, along with NPS variability, often make it difficult to achieve project objectives (Tate et …