Ridwan Siddique, PhD
Senior Research Fellow

Dr. Ridwan Siddique is a Scientist in the Energy Systems and Climate Analysis Group at the Electric Power Research Institute (EPRI). His main research areas are regional and global scale hydroclimatic modeling, analysis and prediction of extreme events, uncertainty quantification and climate risk assessment.  Dr. Siddique's current research activities examine weather and climate impacts on renewable energy and electric power sector to facilitate climate resiliency and adaptation planning.

Before joining EPRI, he worked for the U.S. National Center for Atmospheric Research (NCAR) and United State Geological Survey (USGS) Northeast Climate Adaptation Science Center (NECASC). His dissertation was focused on improving short- to medium-range weather and flood forecasts and quantifying their associated uncertainties. He also has experiences working with different federal, state and private organizations like NOAA, NASA, Massachusetts State Office of Energy and Environment, Massachusetts Department of Transportation, and Idaho Power on climate analysis and research collaborations.

Dr. Siddique received his PhD from the Pennsylvania State University in Civil Engineering with a major in Hydrology and Water Resources and minor in Computational Science. He earned his MS from University of Texas at Arlington and BS from Bangladesh University of Engineering and Technology.


  1. Siddique, R., A. Mejia, N. Mizukami & R. Palmer, 2021. Impacts of global warming of 1.50C, 2.00C and 3.00C on hydrologic regimes in the northeastern U.S. Climate 2021, 9(1), 9; https://doi.org/10.3390/cli9010009
  2.  Siddique, R. & R. Palmer, 2021. Climate change impacts on local flood risks in the U.S. northeast: A Case Study on the Connecticut and Merrimack River Basins." Journal of the American Water Resources Association 1–21. https://doi.org/10.1111/1752-1688.12886.
  3. Siddique, R., A. Karmalkar, F. Sun & R. Palmer, 2020. Hydrological extremes across the Commonwealth of Massachusetts in a changing climate. Journal of Hydrology: Regional Studies, 32, 100733
  4. Sharma, S., R. Siddique, S. Reed, P. Ahnert & A. Mejia, 2019. Hydrological model diversity enhances streamflow forecast skill at short to mediumrange timescales. Water Resources Research, 55, 1510– 1530. https://doi.org/10.1029/2018WR023197