Dr Prateek Gantayat is a modeller by training, specialising in the development of mathematical models to simulate naturally occurring physical processes in high mountain environments.

He completed his BTech in Electronics and Communications Engineering from Amrita Vishwavidyapeetham, Coimbatore, in 2011. In 2013, he joined the Centre for Atmospheric and Oceanic Sciences at the Indian Institute of Science (IISc), Bengaluru, for an MTech programme. His master’s dissertation focused on techniques for estimating the volume of high mountain ice reserves.

Following his master’s degree, he pursued a PhD in Climate Science at the same institution from 2013 to 2018, with a focus on the dynamics of Himalayan glaciers. During his doctoral research, he developed a new model for estimating glacier volumes across the Himalaya using freely available satellite data. He also developed numerical models to simulate the past, present, and future evolution of glaciers with complex geometries in the Himalayan region.

From 2019 to mid-2026, he undertook postdoctoral research at the Indian Institute of Technology Bombay, Lancaster University (UK), the University of Dayton (Ohio, USA), and the Institute of Science and Technology Austria. During this period, he developed numerical models to simulate the evolution of surface hydrology on the Greenland Ice Sheet, as well as the formation and evolution of high mountain lakes and their implications for mountain hazards and future glacier evolution.

Research 

During my PhD, I focussed on modelling the evolution of glacier volume under a changing climate. During my postdoctoral fellowship at IIT Bombay, I went a step further and developed a numerical model to forecast proglacial lake expansion due to glacier evolution. At Lancaster University in the UK, I developed a new numerical supraglacial hydrological model for the Greenland ice sheet. I used satellite products to evaluate crop stress and yield during my brief stint as a Data Scientist for Earth Now Private Limited. As a postdoctoral scholar at the University of Dayton in the US, I developed a Bayesian statistics-based numerical model to estimate proglacial lake volume in High Mountain Asia (HMA) and a numerical ice flow model to project the evolution of hazard exposure of the largest proglacial lake in Nepal Himalaya, under different climate scenarios. Currently, as a postdoctoral researcher at the Institute of Science and Technology Austria, I am working on modelling the impact of the evolution of supraglacial debris cover on the evolution of mountain hydrology in a changing climate. 

With an academic background in Atmospheric-Oceanic sciences and a research background in modelling climate-cryosphere interactions, I will bring in unique set of skills and expertise that is currently lacking at SIAS in Krea university. 

Keeping the above things in mind in the coming five years, I plan to work on the following topics: 

1. Future impact of regional/global weather phenomena on high mountain hydrology in the Himalaya: The Himalayan water resources are an important source of livelihood for a significant population living in the Indian sub-continent. The major components of high mountain hydrology are glacier-runoff, proglacial lakes, rain, snow-runoff, permafrost. Till date no study has comprehensively quantified the impact of regional and global weather circulation phenomena (e.g., Western Disturbances, East Asian Monsoon, Indian Summer Monsoon, El Nino, La Nina) on the evolution of the above-mentioned components of high mountain hydrology. There is also a paucity of knowledge about how the future evolution of the regional/global weather phenomena will impact the evolution of the above-mentioned components of high mountain hydrology. To address this issue, I aim to use a combination of data from climate models, high-resolution satellite imagery and process-based modelling. With the availability of a wealth of high-resolution optical and microwave satellite imagery, I aim to develop new and robust parameterizations of the processes that quantify runoff from mountain catchments (e.g., debris supply rate, snow runoff and permafrost cover), for the present climate setting. Next, I aim to analyse the impact of the past and future evolution of the regional/global weather phenomena on the corresponding fluctuations in mountain hydrology. This will help quantify the sensitivity of the different high mountain watersheds in the Himalaya to a changing climate. This would help identify the hydrological catchments whose water reserves are vulnerable to future warming. In addition to that, this project will give an important insight to the future impact that weakening of certain weather phenomena would have on the high mountain water reserve in the Himalaya. The results would be of great value to policy makers to draft laws to secure the water security of people living in the downstream areas of these vulnerable high mountain watersheds. Results of this work will be of high impact and can be published in journals such as PNAS.
2. Development of a new hazard index for proglacial lakes in High Mountain Asia (HMA): When glacier meltwater pools in glacier-bed overdeepenings exposed owing to glacier retreat, proglacial lakes are formed. They are found in highly remote, inhospitable areas and have been linked to Glacier Lake Outburst Floods (GLOFs). Hazard indices are estimated to assess the susceptibility of high mountain lakes to natural hazards. With the number of proglacial lakes expected to grow in the future due to a warming climate, the likelihood of lake outburst cascades increases. However, till date no hazard index has been able quantify the corresponding hazard susceptibilities of the lakes. Therefore, I propose to work on developing the most comprehensive hazard index till date where, I plan to include satellite and field-based estimates of morphological and climate triggers. This work will ultimately lead to the identification of high mountain basins that are vulnerable to natural hazards including lake outburst cascades. Results of this work will be of high impact and can be published in journals such as Nature. 
3. Quantification of the effect of supraglacial meltwater on ice-sheet mass loss and subsequent mean sea level rise: No study till date has ever assessed the effect of surface meltwater on ice flow and mass loss. To address this, I intend to couple the supraglacial hydrological model (that I developed as part of my postdoc) with a state of-the-art ice-flow model, such as Elmer/ Ice. The coupled model will be calibrated using proglacial river discharge data and satellite-derived ice-sheet surface velocity maps from Greenland. Upon calibration, the coupled ice-flow-cum-hydrology model will be forced with CMIP6 future climate scenarios and run over the Greenland Ice Sheet until AD 2124. This will allow us to provide revised forecasts of ice-sheet mass loss and mean sea level rise. Results of this work will be of high impact and can be published in journals such as Science or Nature. 

Further, I plan to work on the following contemporary problem: 

1. Modelling climate-cryosphere-vegetation interactions in the Himalaya: The Himalaya are home to a large population of endangered species of flora and fauna. With a gradually warming climate, the evolution of high mountain water resources and associated vegetation cover directly impacts their survival. In this project, I plan to model and assess the likely future evolution of carbon and water cycle in various high mountain hydrological basins in the Himalaya. This work would result in the preparation of a pan-Himalaya maps of areas where the corresponding flora and fauna species are vulnerable to future climate change. The results would be of great value to policy makers to draft environment conservation measures.

Publications 

Journal papers: 

• Gantayat P, Sattar A, Haritashya UK, RAAJ Ramsankaran and Kargel JS: Evolution of the  Lower Barun lake and its exposure to potential mass movement slopes in the Nepal Himalaya, Science of Total Environment, 949, 2024. doi: https://doi.org/10.1016/j.scitotenv.2024.175028, Impact factor: 8.2, Quartile information: Q1. 
• Gantayat P, Sattar A, Haritashya UK, Watson CS, and Kargel JS: Bayesian approach to  estimate proglacial lake volume (BE‐GLAV). Earth and Space Science, 11, e2024EA003542,  2024. doi: https://doi.org/10.1029/2024EA003542, Impact factor: 3.1, Quartile information: Q1. 
• Gantayat P, Banwell A, Leeson A, Lea J, Petersen D, Gourmelen D and Fettweis X: A new  model for supraglacial hydrology evolution and drainage for the Greenland ice sheet (SHED  v1.0), Geoscientific Model Development, 16, 5803–5823, 2023. doi: https://doi.org/10.5194/gmd-16-5803-2023, Impact factor: 4.0, Quartile information:Q1. 
• Gantayat P and RAAJ Ramsankaran: Modelling the evolution of large, glacier-fed lake in  the Western Indian Himalaya, Nature Scientific Reports, 13, 1840, 1-13, 2023. doi: https://doi.org/10.1038/s41598-023-28144-8, Impact factor: 3.8, Quartile information: Q1. 
• Farinotti D, Brinkerhoff DJ, Frust JJ, Gantayat P, Gillet-Chaulet F, Huss M, Leclercq P,  Maurer H, Morlighem M, Pandit A, Rabatel A, Ramsankaran, R, Reerink TJ, Robo E, Rouges E, Tamre E, van Pelt WJJ, Werder MA, Azam MF, Li H and Andreassen LM: Results from  the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2). Frontiers in Earth  Science, 8, 484, 1-21, 2021. doi: 10.3389/feart.2020.571923, Impact factor: 2.0, Quartile information: Q1. 
• Gantayat P, Kulkarni A V, Srinivasan J and Schmeits MJ: Numerical modelling of past  retreat and future evolution of Chhota Shigri glacier in Western Indian Himalaya. Annals of  Glaciology, 58(75pt2), 136-144, 2017. doi: 10.1017/aog.2017.21, 2017. Impact factor: 2.86, Quartile information: Q1. 
• Bhushan S, Syed H T, Kulkarni A V, Gantayat P and Agarwal V: Quantifying changes in the Gangotri glacier of Central Himalaya. IEEE Journal of Selected Topics in Applied Earth  Observations and Remote Sensing, 10(12), 5295-5306, 2017. doi: 10.1109/JSTARS.2017.2771215, Impact factor: 4.7, Quartile information: Q1. 
• Farinotti D, Brinkerhoff DJ, Clarke GKC, Furst JJ, Gantayat P, Gillet-Chaulet F, Girard C,  Huss M, Leclercq P, Linsbauer A, Machguth H, Martin C, Maussion F, Morlighem M,  Mosbeux C, Pandit A, Portmann A, Rabatel A, Ramsankaran R, Reerink TJ, Sanchez O,  Stentoft, PA, Singh SK, van Pelt WJJ, Anderson B, Benham T, Binder D, Dowdeswell JA,  Fischer A, Helfricht K, Kutusov S, Lavrentiev I, McNabb R, Gudmundsson GH, Li H,  Andreassen LM: How accurate are estimates of glacier ice thickness? Results from ITMIX,  the ice thickness models intercomparison eXperiment. The Cryosphere, 11, 949–970, 2017. doi: 10.5194/tc-11-949-2017, Impact factor: 4.4, Quartile information: Q1.
• Gantayat P, Kulkarni AV and Srinivasan J: Estimation of ice thickness using surface  velocities and slope: case study at Gangotri glacier, India. Journal of Glaciology, 60(220),  277–282, 2014. doi: 10.3189/2014JoG13J078, 2014. Impact factor: 2.8, Quartile information: Q1. 

Book Chapters: 

• Gantayat P: Supraglacial Lake Filling Models: Examples From Greenland in the book titled,  Advances in Remote Sensing Technology and the Three Poles, Wiley online library, ISBN:9781119787754, doi:10.1002/9781119787754, 2022.