Sponsored research projects 

1. Low-cost Disaster & Emergency Services for Communities At Risk (LODESTAR), Cooperation India (DST) - the Netherlands (NWO Merian Fund) (2024-2027)

LODESTAR (guiding polestar for ships, resonating with the project’s vision) aims to co-create a low-cost, multi-hazard early warning system (MH-EWS) in collaboration with citizens, academics, disaster professionals, industry, and (national and local) policy actors.

The overall research objectives of LODESTAR are:

RO1: To develop socio-technical disaster and emergency (early warning) services (MH-EWS dashboards) to address the challenges of extreme compound disaster events emerging in India and the Netherlands.

RO2: To improve flood and drought modelling and user interface using high-resolution remote sensing data (spatially as well as temporally) by focusing on innovative technologies, to arrive at an integrated MH-EWS for floods and/or droughts.

RO3: To develop socio-cultural and management innovations via living labs, necessary for implementing new technologies and accelerating uptake, while ensuring long-term sustainability.

2. A web-based Tool for Statistical Downscaling of Hydroclimatic Variables-Application of Machine Learning Algorithms (MoES)

Objectives and Scope:

a) Develop a new framework for SD using ML algorithms

b) Assess the uncertainty in the GCM model outputs

c) Development of an interactive web-based desktop tool for the implementation of the SD of hydroclimatic variables using ML algorithms

d) Dissemination of the tool by providing necessary training

3. Modelling Forest Phenological Parameters from Time Series Remote Sensing Data (2021-2024 )

4. Interactive Desktop Tool for Nonstationary Intensity- Duration Frequency Curves under Climate Change (2019-2021 )

5. Streamflow monitoring and modeling for the development of micro-watershed - Vellore District (20197-2018)

6. Spatio-Temporal Groundwater Analysis: A case study in Kutrumali and Sijimali hilltops, Odisha (2016)