CHANGING STREAMFLOW REGIMES IN NEW YORK STATE: TRENDS, PATTERNS, AND ATTRIBUTION

New York (NY) is among the first states in the US to sign a law, the Community Risk and Resiliency Act, aimed at requiring state agencies to consider climate change-associated risks and extreme weather events in regulatory decision-making. Hydrologic risks, including increased flooding, storm surges, and sea level rise, must be considered when designing infrastructure, such as bridges, highways, and culverts. An in-depth evaluation of hydrologic trends in NY can assist planning efforts associated with implementation of this law. Spatial and temporal patterns in streamflow magnitude, flood frequency, and timing were examined for 100 USGS stream gages in NY and adjacent areas from 1961 to 2015. Stream gages were clustered hierarchically based on similarities in inter-annual trends in mean seasonal streamflow. Clusters and spatial correlations vary seasonally, with the fewest spatial clusters occurring during spring and winter. Trend and change point analyses were performed on a suite of flow statistics including low, median, and high flow regime magnitudes, monthly mean discharge, peak flow frequency, and spring snowmelt timing. Increasing step changes in most variables occurred in the early 1970s, coincident with the end of a millennial drought. After 1975, low and median flow regimes show increasing trends in magnitude throughout the state, while the highest annual flow magnitudes remain relatively unchanged. Throughout NY and surrounding areas, flow magnitudes are increasing significantly in the month of January, consistent with increasing rain-on-snow events. For all spatial clusters, the timing of floods are transitioning away from spring and towards a more even distribution throughout the rest of the year. This could be due to a diminished influence of spring snowmelt on the annual hydrologic regime, along with increased precipitation events during other seasons. The trends in magnitude, timing, and frequency of high flows in NY are weakly correlated with increasing precipitation and temperature, and future analyses will explore the connections of flow patterns with large-scale climatic oscillations and land use changes. These results will improve our understanding of statewide hydrologic temporal and spatial patterns, and inform policy and decision-making related to vulnerable infrastructure.