Sudhir Kumar Singh

GIS–AHP-based assessment of urban waterlogging susceptibility in Delhi using multi-source geospatial data

This study explores challenge of urban waterlogging in Delhi by utilizing a comprehensive methodology that merges geospatial analysis with the Analytic Hierarchy Process (AHP). A Digital Elevation Model (DEM), Landsat imagery and rainfall data were used as input datasets for asse...

Enhancing copper and cobalt hydrometallurgical leaching through deep learning-based process optimisation

This study presents a comprehensive machine learning framework for the optimisation of metallurgical parameters for the grinding, leaching and solid/liquid separation in a Congolese Copperbelt hydrometallurgical plant. Three deep learning architectures namely Deep Neural Network...

Hydrological responses to climate change in a central Himalayan basin: insights from snow and glacier runoff modelling

Assessment of the impacts of climate change on central Himalayan hydrology is vital for the sustainable management of downstream water resources under recent CMIP6 climate projections. We focused on the hydrological processes and water components of the Ghaghara River basin (GRB)...

Interpretable machine learning reveals contrasting drivers of streamflow droughts in regulated and natural river systems

This study investigates the spatial, temporal, and process-based dynamics of streamflow droughts across the Godavari River basin using daily discharge records from multiple gauging stations. A multivariate framework integrating drought duration, intensity, and deficit was employe...