Research Projects

The proposed research will be a novel study towards identifying, developing and integrating in-situ lab technologies in a data-driven architecture for tackling the water and food security challenges in the river water-groundwater interaction zones in Damodar basin. The intricate nexus between food crops, groundwater, sediments and living biota is currently facing both anthropogenic as well as geogenic disturbances. The pedosphere of the region indicates a developing catastrophe for the region, aided by accelerated growth of heavy industries, mining activities and extremely high population density. The severity of the situation is supported by the fact that presently no study exists that could explain the evolving threat in the interaction zones of the region, especially with regards to geogenic contaminants like arsenic and fluoride. Revealing the active geochemical cycle of the contaminants along with establishing its causal dependencies with inorganic or biotic ligand formation tendencies, requires a multi-level assessment approach. The current project aims to specifically target the prospect of using artificial intelligence, machine learning and geospatial techniques towards predicting the risk quotient for the region through possibly assimilating every feature of physics-based modelling, in-situ data collection, socio-economic drivers, contaminant pathways, aquifer characteristics and sediment signatures. Research with regards to tracing the rock groundwater-crop-contaminant interaction have been limited with even lesser focus on developing in situ remediation techniques that are suited to the hydrogeology and geomorphology of the region. The motivation of the study will be towards setting up critical zones in the region, in order to evaluate the existing hydro-chemical realities and to develop appropriate remediation methods that can serve as the basis for possible implementation in future planning of cities. The project at its completion will be the first of its kind study that will lead to formation of a high-resolution digital database through which the future task of population risk monitoring can be undertaken in the interaction zones.