Nonpoint source nitrogen pollution is difficult to effectively model in groundwater systems. This study aims to elucidate anthropogenic nonpoint source pollution discharging into Potowomut Pond and ultimately Narragansett Bay. Hydrologic modeling with Soil and Water Assessment Tool (SWAT) and SWAT Calibration and Uncertainty Program (SWAT-CUP) was used to simulate streamflow and nitrogen levels in the Hunt River with and without onsite wastewater treatment systems (OWTS). The objective of this study was to determine how input of OWTS data impacts nitrogen loading into the Hunt River Watershed in Rhode Island, USA. The model was simulated from 2006 to 2014, calibrated from 2007 to 2011 and validated from 2012 to 2014. Observed streamflow data was sourced from a US Geological Survey gauge and nitrogen loading data from University of Rhode Island Watershed Watch (URIWW). From the results, adding OWTS data to the SWAT simulation produced a better calibration and validation fit for total fit (Nash–Sutcliffe Efficiency (NSE) = 0.50 calibration, 0.78 validation) when compared with SWAT simulation without OWTS data (NSE = −1.3 calibration, −6.95) validation.
Extreme flood events present a significant challenge for operators and managers of large drinking water reservoirs. Detailed flood response analysis can predict the hydrology response of a reservoir to changing climate conditions and can aid in managing the reservoir in anticipation of extreme events. Herein, the Soil and Water Assessment Tool (SWAT), a watershed model, was used in conjunction with a reservoir management model, the Operational Analysis and Simulation of Integrated Systems (OASIS) model, to evaluate extreme flood events across a set of initial reservoir storage capacities across various CMIP6 climate scenarios. The SWAT model was calibrated and validated with PRISM climate data in conjunction with land and soil cover data and multi-site gauged stream discharges. The validated model demonstrated satisfactory performance (NSE = 0.55 and R2 = 0.56) for total reservoir inflow. The resulting inflow values from SWAT were utilized to set up a calibrated/validated OASIS model (NSE = 0.55 and R2 = 0.68). OASIS was then used to assess alternative operating rules for the reservoir under varying climate scenarios (RCP4.5 and RCP8.5) and extreme events (synthetic hurricanes). Focusing on a major reservoir in the Northeastern United States, the analysis of the reservoir response was based on (1) reservoir volume–elevation curve, (2) daily reservoir inflow, (3) daily precipitation, (4) spillway flow, and (5) reservoir evaporation. Projected future scenarios indicate a >20% increase in precipitation in April compared to historical records, coupled with likely reduced runoff from November to March. With extreme conditions most likely in the month of April, RCP4.5 and RCP8.5 projections suggest that most scenarios result in a 10–15% increase in the mean of 3D30Y runoff volumes, and a 150% increase under the most extreme conditions. For 7D30Y runoff volumes in April, the RCP4.5 and RCP8.5 analyses reveal an increased likelihood of the reservoir elevation reaching overspill flow levels during the latter half of the simulation period (2020 to 2080). Our findings indicate that simulations with SWAT coupled with OASIS can assist reservoir managers in regulating water levels in anticipation of extreme precipitation events.