IIT Delhi, New Delhi
Dhanya C T is an Assistant Professor in the Department of Civil Engineering, IIT Delhi. She holds PhD in hydro-climatology from IISc, Bengaluru. She attempts to generate a fundamental scientific understanding of hydrological extremes along with improvising hydrological modeling, to provide early-warning methods and adaptation policies for sustainable water resources management. She is the recipient of numerous awards including the NASI Young Scientist Platinum Jubilee Award (2017), the Young Researcher Award – Ministry of Earth Sciences (2017), and the DAAD Faculty Exchange Scholarship to serve as a visiting faculty in Forschungszentrum Jlich, Germany. She was selected as an Associate of the Indian Academy of Sciences in 2016.
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Hydrological extremes and hazard modeling – Exploring the intricacies and predictability of the regional hydrologic system
Hydrological extremes, though rare, have always existed, adversely affecting the economy, in the form of floods and droughts. The rarity and intensity of such events often jeopardize the management policies undertaken. Recently, India has witnessed an increase in the occurrence of hydrologic extremes, i.e., floods, droughts, and heat waves, the impacts of which proved to be much detrimental to the Indian society and economy, especially due to the lack of any systematic early warning systems and subsequent strategic planning. These extremes increase the stress undertaken by the water sector owing to the compounding effects of climate change, growing population, and globalization, with implications for food and energy security, ecology and environment, critical infrastructures and emergency preparedness, as well as human lives, health, and economy. The talk will elaborate the research attempted to gain fundamental insights into such hydrological extremes and towards improving hydrological modeling to aid the development of early-warning methods and policies for sustainable water resources and hazard management. The two-fold approach undertaken: (i) Statistical learning from time series of observations, and (ii) Theoretical modeling hydrological and holistic models to simulate the regional hydrological cycle behavior, will be covered. Major research outputs and accomplishments, so far, will be comprehended.