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Elevated turbidity (Tn) and suspended sediment concentrations (SSC) during and following flood events can degrade water supply quality and aquatic ecosystem integrity. Streams draining glacially conditioned mountainous terrain, such as those in the Catskill Mountains of New York State, are particularly susceptible to high levels of Tn and SSC sourced from erosional contact with glacial‐related sediment. This study forwards a novel approach to evaluate the effectiveness of stream restoration best management practices (BMPs) meant to reduce stream Tn and SSC, and demonstrates the approach within the Stony Clove sub‐basin of the Catskills, a water supply source for New York City. The proposed approach is designed to isolate BMP effects from natural trends in Tn and SSC caused by trends in discharge and shifts in average Tn or SSC per unit discharge (Q) following large flood events. We develop Dynamic Linear Models (DLMs) to quantify how Tn‐Q and SSC‐Q relationships change over time at monitoring stations upstream and downstream of BMPs within the Stony Clove and in three other sub‐basins without BMPs, providing observational evidence of BMP effectiveness. A process‐based model, the River Erosion Model, is then developed to simulate natural, hydrology‐driven SSC‐Q dynamics in the Stony Clove sub‐basin (absent of BMP effects). We use DLMs to compare the modelled and observed SSC‐Q dynamics and isolate the influence of the BMPs. Results suggest that observed reductions in SSC and Tn in the Stony Clove sub‐basin have been driven by a combination of declining streamflow and the installed BMPs, confirming the utility of the BMPs for the monitored hydrologic conditions. [ABSTRACT FROM AUTHOR]

This study focuses on the impact of changes in winter streamflow on in-stream turbidity in the Esopus Creek watershed, one of the New York City water supply watersheds. Projected changes in daily precipitation and air temperature from a suite of five global climate models and three emission scenarios for future periods 2046-2065 and 2081-2100 were downscaled for the study region. The simulated climate scenarios were used to project future streamflows using the Generalized Watershed Loading Functions - Variable Source Area watershed model. Seasonal turbidity rating curves based on measured historical streamflow and stream turbidity were used in combination with the simulated streamflow for generating future stream turbidity scenarios. Results indicate an increase in future ambient stream turbidity from November to March and a decrease during April. These results are the effects of increased winter rainfall, reduced snowfall, and a shift to early timing of spring snowmelt runoff, causing an increase in streamflow during early winter. It also suggests a reduction in the traditional peak streamflow around April that is expected to occur in this region. As a result, our models simulate a consistent increase in the low to medium percentile range of turbidity values associated with low to medium range of streamflows and no apparent change in high-percentile turbidity values associated with high streamflows. Our results may be applicable in regions where snowmelt runoff is an important process and turbidity caused by the suspension of fine clay particles is a water quality concern. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]