Sudarshana’s primary research area is statistical hydrology with an emphasis on stochastic hydrological modeling that aims at efficiently using climate information in water resources management. She is interested in river-basin scale multi-reservoir modeling for understanding water-energy nexus using probabilistic hydroclimatological forecasts and identifying the drivers of hydroclimatic variability across different spatial and temporal scale.
Current Projects
- National Science Foundation (Cybersees-Type II)
- A Global Synthesis of land-surface fluxes under natural and human-altered watersheds using the Budyko framework
Current Research Topics:
- Understanding seasonality and effect of spatio-temporal scales on weather regimes.
- Improving reservoir management using sub-seasonal to seasonal stream flow forecast.
- Understanding teleconnection between watershed responses and climate indices.
- Cumulative effects of dams on flow regime alteration and its impact on biodiversity.
Publications:
Presentations:
- AGU Fall Meeting (2017) presentation . Presentation title: ‘Sub-seasonal-to-seasonal Reservoir Inflow Forecast using Bayesian Hierarchical Hidden Markov Model ‘ [presented on Dec 14, 2017]
- ASCE World Environmental and Water Resources Congress (EWRI) (2017) Oral presentation. Presentation title : ‘Equivalent Reservoir Modelling for Multipurpose and Multi-Reservoir Systems over the Southern United States’. [presented on May 24, 2017]
Sudarshana Mukhopadhyay 