Hydroclimatic Extremes in a Changing Environment (HExChangE)

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Dr. Arpita Mondal works as an Associate Professor in Civil Engineering, and the Center for Climate Studies at IIT Bombay, Mumbai, India. Arpita has been a researcher, educator and communicator in climate change with more than fifteen years of experience. Arpita's research focuses on hydroclimatic extremes such as heat waves, floods and droughts - how they can be characterized, what causes them, and how they are likely to evolve with climate change. She serves as an Associate Editor of Earth’s Future, Journal of Hydrology and Hydrological Sciences Journal. She has been featured in the book ‘She Is: 75 Indian Women in STEAM’ by the Office of the Principal Scientific Advisor to the Government of India and the Red Dot Foundation. Arpita received the Asian Universities’ Alliance (AUA) Scholars’ Award in 2020, DST’s INSPIRE Faculty Award in 2020, SERB’S Early Career Research Award in 2020, and the SERB’s POWER Research Grant in 2023. Arpita completed her PhD in Civil Engineering at the Indian Institute of Science (IISc), Bangalore, when she had received the Endeavour Research Fellowship of the Government of Australia, the Fulbright-Nehru Research Fellowship of the United-States India Education Forum, and the Berkner Travel Grant of the American Geophysical Union (AGU). Apart from publishing in peer-reviewed scientific literature, Arpita strongly engages in public media outreach and has been a regular author in print (Hindustan Times, Indian Express, The Statesman, etc), and contributor to international tv (BBC, UK; CVO, Canada; Sky News, UK), radio (All India Radio Kolkata, Radio Mirchi) or international digital media (Al Jazeera, The Washington Post, CNBC, ABC News, etc.), as well as vernacular outlets in Indian languages. 

Research Interests: Hydroclimatic Extremes such as Heat Waves, Heavy Rain, Floods,  Droughts, Climate Change, Detection and Attribution, Statistical Spatio-Temporal Modeling of Extremes, Uncertainty Analysis, Statistical Downscaling, Regionalization and Prediction in Ungauged Basins, Risk Assessment under Non-stationarity.

Teaching Interests: Hydraulic Engineering, Open Channel Flows, Statistical/Machine Learning Applications in Water Science - Hydroinformatics, Applications of Probability and Statistics, Extreme Value Analysis, Hydroclimatology, Fluid Mechanics.