Deployment of entropy information theory in the Indian Sundarban region using hydrogeochemical parameters and GIS for assessment of irrigation suitability.

The evaluation of irrigation suitability plays a crucial role for the socio-economic development of the society, especially in the region of Sundarban. For sustainable agricultural practices, groundwater quality must be suitable for irrigation; otherwise, it can degrade soil and diminish crop yield. The entropy information theory, several irrigational indices, multivariate statistics, GIS, and geostatistics are used in this work to evaluate the geographical distribution and quality of groundwater in the Indian Sundarban region.

Suitability of the Lower Ganga basin groundwater for irrigation, using hydrogeochemical parameters and land-use dynamics.

The northern Ganga basin is one of the most densely populated basins in the world. Most agricultural and industrial contaminants drained in the river length are likely to be accumulated in the lower part of the Ganga basin. In this study, we have used ten parameters obtained from 495 sampling locations, besides using long-term climate data (GLDAS_NOAH025_M) to understand the irrigation suitability using the TOPSIS model.

Integrated approach for spatial flood susceptibility assessment in Bhagirathi sub-basin, India using entropy information theory and geospatial technology.

Globally, floods as dynamic hydraulic hazard have caused widespread damages to both socioeconomic conditions and environment at various scales. Managing flood and management of water resource is a global challenge under the changing climatic condition. This study assessed flood susceptibility in the Bhagirathi sub-basin, India using entropy information theory and geospatial technology.