Modeling streamflow sensitivity to climate change in New York City water supply streams using a stochastic weather generator

Abstract Study region The New York City water supply watersheds Study focus This study is a modeling analysis on climate change impact on streamflow using a stochastic weather generator (SWG), a hydrologic model, and downscaled future climate scenarios. Streamflow generated using synthetic time series of precipitation and air temperature from a SWG were compared to those simulated from observed historical and projected future weather. New hydrologic insights for the region Synthetic weather was able to mimic the observed annual streamflow cycle for the six watersheds studied, including the seasonal pattern as well as magnitude and occurrence of extreme hydrologic events. Streamflow simulations using projected climate from 20 global climate models (GCM) for one of the New York City water supply watersheds indicate the potential for changes in the hydrologic regime in this region. The models indicate a shift in the timing of spring melt runoff from a distinct peak in late March and April under historical (1950–2009) conditions towards earlier in the year for mid-century (2041–2060) period. Results indicate that the region may experience an overall increase in mean streamflow in the future due to the combined effect of decreasing spring runoff peak and increasing streamflow during other seasons. More importantly, the magnitude and frequency of extreme hydrological events are projected to increase under future scenarios. These results have implications for future operation and management of the water supply.