Newswise —

In the last 25 years, the Northeast has seen the highest surge in intense precipitation across the country. Previous studies indicate that the volume of extreme precipitation, defined as rain or snow accumulating one to two inches of water in a day, has risen by nearly 50% compared to the period between 1901 and 1995.

A recent study from Dartmouth sheds light on the impact of global warming on streamflow and flooding in the Northeast by examining shifts in precipitation and temperature. The research results are now available in the Journal of the American Water Resources Association.

The scientists conducted a comprehensive analysis of various precipitation factors, including snowfall, winter rain on snow occurrences, springtime snowmelt, and soil conditions, to assess their impact on streamflow. Their study centered on four watersheds in the Northeast region: the Mattawamkeag River in northeastern Maine, the Dead Diamond River in northern New Hampshire, the White River in eastern Vermont, and the Shenandoah River in West Virginia.

The study revealed that snowmelt has a significant impact on streamflow in the three northern watersheds, while rainfall plays a more prominent role in the Shenandoah River watershed. The researchers specifically chose these four watersheds as they are unregulated rivers, meaning their streamflow is not influenced by dams, and they represent a diverse range of latitudes in the Northeast region.

In the initial phase of the research, the team developed a machine learning model by analyzing the historical correlations between streamflow and various factors. These factors encompassed temperature, precipitation (differentiating between rainfall and snow), the antecedent precipitation index (a measure of soil moisture prior to a storm), the standardized precipitation index (used to characterize wet and dry periods), and streamflow data.

The researchers utilized an extensive dataset, encompassing over 95 years of historical climate data spanning from 1915 to 2011. They also incorporated streamflow data obtained from the U.S. Geological Survey, as well as snow depth observations sourced from the Northeast Regional Climate Center. This comprehensive data allowed for a robust analysis of the relationship between the various factors and streamflow patterns in the Northeast.

According to Charlotte Cockburn, the lead author of the study and a former master's student in earth sciences at Dartmouth, "Both the antecedent precipitation index and the standardized precipitation index serve as indicators of the moisture content of the land surface, which directly impacts runoff and streamflow." These measures help in understanding the wetness of the land surface prior to storms and provide valuable insights into how it influences streamflow dynamics in the Northeast.

“If you have a really big rainstorm on a relatively dry surface, a lot of that water can be absorbed by the soil, but if you have multiple rainstorms leading up to the really big rainstorm, there’s no room in the soil for the water, which creates higher streamflow.”

Charlotte Cockburn further highlighted that such factors had significant implications during specific events, such as Hurricane Irene in August 2011. Hurricane Irene, referred to as Tropical Storm Irene in many parts of New England, resulted in catastrophic flooding, loss of life, and extensive financial damages. The impacts of extreme weather events like Hurricane Irene underscore the importance of understanding the relationships between precipitation, streamflow, and flooding in the Northeast region.

To forecast streamflow during the colder months of November to May, the researchers incorporated average temperature, three-day and 30-day rainfall, and three-day and 30-day snowfall as variables in their model. Additionally, they developed a sub-model specifically designed to simulate snowmelt. Using this comprehensive model, the team could input specific dates, such as April 1, 2009, and generate streamflow predictions based on the variables incorporated in the model. This allowed them to forecast streamflow dynamics based on the interplay between temperature, precipitation, and snowmelt in the Northeast region.

Jonathan Winter, the senior author of the study and an associate professor of geography at Dartmouth, explains that streamflow in Northeast watersheds typically reaches its peak during spring, which is around the current time. This peak is driven by various factors, including snowmelt, increased rainfall compared to winter, minimal vegetation to absorb water from the soil, and soil conditions that are either saturated or frozen. Understanding these contextual factors is crucial in comprehending the dynamics of streamflow in the Northeast region and their implications for water resource management and flood prediction.

The researchers acknowledge in the study that one of the challenges with their model is that it relies on historical data and snowpack as a significant driver for predicting streamflow during the colder months. This presents a conundrum as the changing climate can alter snowpack dynamics, which may impact streamflow patterns in the future. As climate change continues to affect precipitation patterns and temperature regimes, it is crucial to continuously refine and update the model to account for potential shifts in snowpack dynamics and their implications for streamflow projections in the Northeast region.

As the researchers explain, when the model encounters future dates with reduced snowpack due to global warming, it predicts a decrease in streamflow. However, as Charlotte Cockburn, the first author of the study, points out, the models may not fully capture the dynamics of winter streamflow changes because they are trained on historical data, which may not fully account for the impact of climate change. In a warmer world due to climate change, rain is expected to play a more significant role in driving winter streamflow, which may not be adequately accounted for in the current model. This highlights the need for ongoing research and model refinement to better understand and predict the potential impacts of climate change on streamflow dynamics in the Northeast region.

For the second part of the study, the team forced the machine learning model with a projection of climate from 2070 to 2099, to see what happens to streamflow in a future climate.

The key findings are:

  • Across watersheds and seasons, three-day precipitation and initial soil moisture are the most important variables that determine streamflow in the Northeast.
     
  • Thirty-day snowmelt and 30-day rainfall are important to Mattawamkeag River streamflow because the watershed is both the largest and most northern, making it less sensitive to short extreme precipitation events and more sensitive to snow.
     
  • Future cold season streamflow depends on how New England watersheds respond to the change from more snowfall dominated winters to more rainfall dominated winters.
     
  • Future warm season streamflow depends almost exclusively on changes in rainfall.

Winter explains that if the Northeast region experiences wetter soils and more frequent heavy rainfall events, as predicted by climate models, it is likely to result in increased streamflow and higher flood risk. As the changing climate influences precipitation patterns and soil moisture conditions, it can have significant implications for streamflow dynamics and flood risk in the Northeast. This underscores the importance of proactive measures such as improved flood preparedness, infrastructure resilience, and land-use planning to mitigate potential impacts of increased streamflow and flooding in the region as climate change continues to unfold.

This past winter the Northeast had below normal snowpack due to temperatures that were more than 4 degrees Fahrenheit warmer than average.

Winter highlights that the recent winter weather patterns may provide a glimpse into the future, as climate change continues to impact the Northeast. He emphasizes that their analysis has revealed that, contrary to common belief, snowpack plays a relatively minor role compared to precipitation in driving streamflow dynamics in the region. The study suggests that streamflow in the Northeast is highly sensitive to precipitation, including rainfall, and that projected changes in precipitation patterns due to climate change could have significant impacts on streamflow dynamics and flood risk in the region. This underscores the need for continued research and planning to better understand and prepare for potential future changes in streamflow and precipitation patterns in the Northeast.

Winter stresses the importance of comprehending potential changes in streamflow patterns in the context of a warmer and wetter climate due to climate change. He highlights that such understanding is crucial as it has implications for various aspects, including flooding risks, ecosystems, water resources, and hydropower generation. The findings of the study provide valuable insights into how precipitation patterns, including rainfall and snow, can impact streamflow dynamics in the Northeast, and how these dynamics may evolve in the face of ongoing climate change. This knowledge can inform decision-making and planning for resilient water management strategies in the future.

Erich Osterberg, an earth sciences associate professor, and Frank Magilligan, the Frank J. Reagan '09 Chair of Policy Studies and a geography professor at Dartmouth, were also co-authors of the study.
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Journal Link: Journal of the American Water Resources Association (JAWRA)