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A Decision Support System for Estimating Changes in Extreme Floods and Droughts in the Northeast U.S.

New Hampshire
Rhode Island
+3 more
In Progress


Floods and droughts are forecasted to occur with greater frequency and to be more extreme because of climate change. These changes will increase stresses on both cities and natural systems. Increased flooding can harm infrastructure designed to support human needs and natural systems that support fish and wildlife. Increased drought can have direct impacts on fish and wildlife by increasing river and lake temperatures and stranding species in water-short systems.  

This project will develop a decision support system that helps resource managers in New England estimate the recurrence of future extreme floods and droughts while directly incorporating the impacts of future climate change. The decision support system expands upon previous regional and state studies performed by the Northeast CASC and tools created by the U.S. Geological Survey (USGS). The researchers will convene a working group composed of state and federal resource managers who are responsible for mitigating the impacts of climate change and extreme hydrologic events on fish and wildlife. Informed by this working group, the researchers will develop the decision support system that integrates recent USGS techniques for estimating daily streamflow in unregulated, unmonitored streams with Northeast CASC research on future changes in climate-impacted extreme flows.  

The decision support system will guide resource managers in estimating the recurrence intervals of future floods and droughts for user specified locations, including unmonitored stream locations. This research integrates three components to estimate expected climate impacts on flood and droughts: 1) forecasts from climate models, 2) physical basin characteristics, 3) and hydrologic models. The results of this research will be displayed in a simple to implement user-interface that illustrates climate change impacts for the scale most appropriate for decision making, whether it be for individual sites, larger watersheds, states, or entire river basins. 


Delsanto, Andrew, Palmer, Richard, Andreadis, Konstantinos. Applications of Machine Learning and Physical, Hydrologic Modeling for Estimating 7-Day 10-Year Low Flows for Climate Altered Futures in the Northeast and Mid-Atlantic United States. AGU Fall Meeting. December 15, 2022.