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Why is Quantifying Suspend Solids Important? The concentration of total suspended solids (TSS) is important to both river and lake ecosystems for ecolog and water quality reasons. Inorganic suspended solids attenuate light, primarily through the proces scattering. High concentrations of suspended solids degrade optical water quality by reducing water clarity decreasing light available to support photosynthesis. Suspended solids have been shown to alter pred prey relationships (for example turbid water might make it difficult for fish to see their prey (e.g., insec Suspended solids also influence metabolic activity and provide surface area for the sorption and transport o array of constituents. Deposited solids alter streambed properties and aquatic h abitat for fish, macrophy and benthic organisms. Deposited sediment may be available for resuspension and subsequent trans during periods of increased stream discharge Suspended solids in most freshwater systems originate f watershed sources, pollutant point sources, and sediment resuspension. More rarely other sources, suc hydrogeologic structures can be important. High stream total suspended solids can impact water quality deposition in downstream lakes and reservoirs. How Can Suspended Solids Be Measured Remotely? Suspended solids concentrations are highly variable in most streams. Characterization and quantification of variability is critical to accurately assess TSS impacts on aquatic systems, including the development of m loading estimates. Large increases in TSS and TSS loading (TSS L ) are widely observed in streams du runoff events. This often results in a large portion of the total TSS L being delivered during relatively interval s of high flow. Frequent measurements of flo w are widely availab le from USGS (United St Department of the Interior U.S. Geological Survey) gauging stations, but practical limitations in sampling h generally limited the frequency of TSS data. System-specific empirical relationships between TSS and flow have been widely developed and utilize estimate TSS L as a function of flow. However, a number of authors have discussed the accuracy limitations of TSS-flow relationships in predicting TSS L . The success of T SS-flow relationshi ps in predic TSS L depends strongly on the scatter around the best-fit regression line. Increased frequency of sampling, with an emphasis on coverage of runoff events, has been shown to result in stronger SS- relationship s and thereby increase the precision of TSSL estimates. However, manual event based samp and the associated laboratory analyses are tedious and costly. Even with the aid of automated samp equipment, laboratory demands continue to limit such a monitoring program. An alternative approach to estimate stream TSS L is based on frequent monitoring of turbidity that is hi correlated to TSS. This may have distinct advantages if the associated temporal coverage benefits ( deployed instrumentation for in situ measurements) more than compensate for the uncertainty in relationship between TSS and turbidity (Tn). Relationships between TSS and Tn are expected to be impe and system-specific because of variations in composition and particle size distributions that influence m concentration and light scattering differ ently. Yet the TSS-Tn relationship is stronger than the TSS- relationship in most cases. The approach of turbidity measurements as a surrogate of T SS has at least advantages:
