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Storm events play a crucial role in organic matter transport within watersheds and can increase the concentration and alter the composition of NOMs and DBP formation potential. To assess the impact that storm events can have on drinking water quality, samples were collected and analyzed across four storm events in the Neversink River, Catskill region, New York in 2019 and 2022. Source water natural organic matter (NOM) was characterized, and the change of NOM quality was evaluated due to storm impacts. During storm events, a high level of NOM mobilization is initiated by heavy precipitation causing overland flow and a rise in the water table. In this way, storms result in increased access to stored NOM pools that are generated during inter-storm periods. A significant correlation was observed between several organic water quality parameters such as UV absorbance (UV 254 ), dissolved organic carbon (DOC) and chlorine demand. Precursors for the total trihalomethanes (TTHM), dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA) exhibited comparable patterns with UV 254 , DOC, and chlorine demand for four storms. Despite the potential for increased dilution resulting from higher discharges, all organic water quality parameters, including yields of disinfection byproducts (i.e., DBP precursors), exhibited elevated concentrations during periods of higher flows. Three of the four storms showed hysteresis patterns with higher observed concentrations of organic constituents in the falling limb of the hydrographs. Precursors for the nitrogenous DBPs (N-DBPs) were proportional to the DOC for all four storms. The coefficient of determination (R 2 ) for TTHM, DCAA, TCAA with UV 254 is higher (R 2 0.92-0.98) than corresponding correlations with DOC (R 2 0.89-0.92). The R 2 for UV 254 showed the following hierarchy: DCAA≈TCAA>TTHM. Additionally, the R 2 for DOC and specific ultraviolet absorbance (SUVA) had the following hierarchy: DCAA>TCAA>TTHM and TCAA>DCAA>TTHM respectively. A significant correlation between UV 254 and DOC (R = 0.99) for all storms was observed. Chlorine demand also yielded a strong correlation (R = 0.91∼0.98) with UV 254 and DOC. This research indicates that a significant and disproportionate export of NOM to source waters occurs during storm events compared to baseflow conditions. Consequently, it is recommended for drinking water treatment facilities to reassess chlorine dosages during these events. Treatment plants can employ UV 254 as a tool to determine appropriate chlorine dosages, aiming to mitigate DBP formation in treated waters., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Mohammad (Kiron) Shakhawat reports financial support was provided by Bureau of Water Supply, NYC Department of Environmental Protection, Kingston, NY. Rakesh K Gelda, Karen E. Moore, Rajith Mukundan reports a relationship with Bureau of Water Supply, NYC Department of Environmental Protection, Kingston, NY that includes: employment. Sean McBeath, Christian D. Guzman, Dave Reckhow reports a relationship with Bureau of Water Supply, NYC Department of Environmental Protection, Kingston, NY that includes: funding grants. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Streamflow-based rating curves are widely used to estimate turbidity or suspended sediment concentrations in streams. However, such estimates are often inaccurate at the event scale due to inter- and intra-event variability in sediment-streamflow relationships. In this study, we use a quantile regression approach to derive a probabilistic distribution of turbidity predictions for Esopus Creek, a major stream in one of the watersheds that supply drinking water to New York City, using measured daily mean streamflow-turbidity data pairs for 2003 to 2016. Although a single regression curve can underpredict or overpredict the actual observation, quantile regression can estimate a range of possible turbidity values for a given value of streamflow. Regression relationships for various quantiles were applied to streamflows simulated by a watershed model to predict stream turbidity under: (i) the observed historical climate, and (ii) a future climate derived from 20 global climate model (GCM) scenarios. Future scenarios using quantile regression in combination with these GCMs and a stochastic weather generator indicated an increase in the frequency and magnitude of hydrological events that may generate high stream turbidity and cause potential water quality challenges to the water supply. The methods outlined in this study can be used for probabilistic estimation of stream turbidity for operational decisions and can be part of a vulnerability-based method to explore climate impacts on water resources., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

This work presents a retrospective analysis of long-term trends in loading of forms of nitrogen (N) from the Metropolitan Syracuse Wastewater Treatment Plant (Metro), N concentrations in the receiving urban lake (Onondaga Lake, New York), and related water quality status for the period from 1972 to 2007. The history of the evolution of treatment and discharge at Metro, as it affected N loading, is reviewed and forms the basis for identification of five regimes during which unifying conditions of loading and in-lake conditions prevailed. Changes in industrial waste inputs have complicated the effects of upgrades in treatment at Metro from primary (until 1978) to advanced (starting in 2004). Current N loading from Metro is approximately 35% lower than the peak levels observed in the late 1980s to late 1990s, but the areal rate to the lake remains extremely high (approximately 97 g/m(2).y), representing approximately 75% of the overall N load. Implementation of year-round nitrification treatment has resulted in transformation of the composition of the N load from Metro from ammonia (T-NH3) to nitrate (NO3(-)) dominance. High N concentrations have prevailed in the upper waters of the lake throughout the study period with averages of total N ranging from 2.6 to 4.3 mg/L for the five regimes. Total N levels and partitioning among the forms in the lake generally have tracked Metro loading conditions for the five regimes. The effects of Metro loading on seasonal in-lake patterns are demonstrated to be modified by both hydrologic inputs from tributaries and in-lake operation of biochemical processes. Resolution of these effects is supported by application of both empirical and dynamic mass balance models. Water quality problems related to high concentrations of forms of N are documented, including (1) augmentation of dissolved oxygen depletion during fall mixing from in-lake nitrification events, enabled by high T-NH3 levels; (2) violations of ammonia toxicity limits; and (3) violations of nitrite toxicity standards. These problems were either greatly ameliorated or eliminated by Metro's most recent treatment upgrades. Prevailing conditions are considered in a management context, including (1) likelihood of exceedances of toxicity limits in the future and (2) potential role of elevated nitrate levels in preventing mobilization of methyl mercury from the lake's sediments.

The recent history of loading of total ammonia (T-NH3) and organic nitrogen (N) from a pharmaceutical manufacturing facility to a municipal treatment plant (Metro) in Syracuse, New York, and the discharge of these constituents from Metro to N-polluted Onondaga Lake is documented. Further, the benefit of the implementation of pretreatment at the pharmaceutical plant, and the effect of an upset event at this treatment facility on loading to Metro and the lake and inlake concentrations are also documented. Models are used as analytical tools to couple loading and in-lake concentrations, to delineate the role that this pharmaceutical facility has played in the lake's ammonia pollution problem, and to evaluate the potential implications of future pretreatment upset events for the success of a rehabilitation program that is underway for the lake. The responsiveness of the lake to reductions in external loading is established by the lower T-NH3 concentration observed in the upper waters of the lake in the spring of 1999. Model analysis demonstrates this reduction was primarily (approximately 75%) because of the decrease in loading from the pharmaceutical facility achieved by pretreatment. An abrupt increase in loading in May 1999 associated with an upset event at the pretreatment facility caused a corresponding increase in the T-NH3 concentration of the lake of approximately 0.5 mg N/L. Model projections demonstrate that the load from the pharmaceutical plant before construction of the pretreatment facility exacerbated the lake's ammonia problems by increasing the occurrence and margin of violations of the toxicity standard. Continued upset events at the pretreatment plant could compromise the lake rehabilitation program.