Ashish Sharma's research interests include:
Synthetic generation of seasonal streamflow; Single and multi-site generation of daily rainfall; Identification of long-term memory in hydrological time series.
Probabilistic forecasting and downscaling
Predictor identification strategies for formulating probabilistic forecasting models; Partial Mutual Information (PMI); Medium to long-term forecasting of seasonal rainfall using hydroclimatic forcing variables; Stochastic downscaling of rainfall and evapotranspiration through a Catchment Scale Climate Change Assesment Framework.
Uncertainty analysis in radar rainfall relationships; Probability based calibration techniques for estimation of radar rainfall.
Use of Bayesian techniques in rainfall-runoff modelling; Markov Chain Monte Carlo sampling for selection of hydrologic models.
Water Resources Management
Uncertainty and risk analysis of water resources systems; Optimal reservoir management using time series and probabilistic forecasting techniques.
Always interested in new developments in statistics and how they can be put to use to solve water problems.