- Developing data assimilation algorithms using observed streamflow data to improve initial hydrologic conditions for lumped hydrological models as well as Land Surface Models (LSM) in order to improve the streamflow forecasts.- Developing and analyzing probabilistic statistical downscaling methods that utilize the climate models ensemble of forecasts to develop streamflow forecasts- Decomposition of various sources of errors in streamflow forecasting- Evaluation of different spatio-temporal downscaling methods on large-scale climate forecasts-Collaborative Research with NC State Climate Office: Developing an automatic streamflow forecasting tool on the NC State Climate Office Water Portal

Courses: Hydrology Engineering, Hydraulics Lab, Water Resources Engineering

Research Applications Laboratory (RAL), Data Assimilation studies

As part of the Global Change Fellows Program, I participated in the following: (a) a one-week workshop on Structured Decision Making (SDM) on August 3-7, 2015, (b) two seminar courses in NCSU, and (c) two workshops, dealing with science communication and science video-making. This ensured productive interdisciplinary engagement and inquiry with the other Fellows throughout the year.

Incorporating the gridded forecasts of streamflow and soil moisture into the "Frecasts" section of NC state Water Portal