Investigating impact of land-use and land cover changes on hydro-ecological balance using GIS: insights from IIT Bombay, India

Predicting the future land use and land cover changes for Saroor Nagar Watershed, Telangana, India, using open-source GIS

The dynamics of land use and land cover are profoundly affected by the growth, mobility, and demand of people. Thematic maps of land use and land cover (LULC) help planners account for conservation, concurrent uses, and land-use compressions by providing a reference for analysis, resource management, and prediction. The purpose of this research is to identify the transition of land-use changes in the Saroor Nagar Watershed between 2008 and 2014 using the Modules for Land Use Change Evaluation (MOLUSCE) plugin (MLP-ANN) model and to forecast and establish potential land-use changes for the years 2020 and 2026. To predict how these factors affected LULC from 2008 to 2014, MLP-ANN was trained with maps of DEM, slope, distance from the road, and distance to a waterbody. The projected and accurate LULC maps for 2020 have a Kappa value of 0.70 and a correctness percentage of 81.8%, indicating a high degree of accuracy. Changes in LULC are then predicted for the year 2026 using MLP-ANN, which shows a 17.4% increase in built-up area at the expense of vegetation and barren land. The results contribute to the development of sustainable plans for land use and resource management.

Assessing the impact of precipitation on hardrock aquifer system using standard precipitation index and groundwater resilience index: a case study of Purulia, West Bengal, India

Groundwater stored in the aquifers provides water security during natural hazards, e.g. clean water access during floods and droughts. Groundwater drought, a phenomenon closely linked with rainfall (climate) variability, is less researched, especially in India. This study aims to detect precipitation and groundwater droughts and comprehend the groundwater response to long-term precipitation trends (25 years). As a case study, the drought-affected and groundwater-depleted Purulia district in West Bengal, India, which is a part of the Chotanagpur plateau, was selected. Precipitation and groundwater droughts (in aquifer types of shallow, moderate and deep) are detected using the Standard Precipitation Index (SPI) and Groundwater Resilience Index (GRI). During the 25 year study period (1996-2020), Purulia had 13 (52%) rainfall deficiency years, with an annual average rainfall of 1382 mm. SPI detected four severe droughts and the most severe occurring in 2010-2011 (1.50). GRI found that aquifermedium had a 71% [Formula: see text] conditions and are the most resilient and aquiferdeep experienced maximum extreme drought events and is the most stressed. The cross-correlation coefficients (CCCs) between rainfall and groundwater is moderate in deep, shallow, and medium aquifers, with CCCs - 0.43, - 0.59, and - 0.49, respectively. Positive CCCs are found for seasonal lags of - 3, - 4, and - 7. The study found that during the monsoon, average depth to groundwater level is 1 - 4 m and it drops to 8 - 10 m during the lean period, more than 85% of wells are vulnerable to extreme droughts (SPI > 1.5), aquifer's response to rainfall is aquifershallow > aquifermoderate > aquiferdeep, and aquifer's may be arranged as aquifermoderate > aquifershallow > aquiferdeep depending on their drought resistance. This study, with the use of statistical tools and long term data, will aid in the management of groundwater at varying depths by creating basis for understanding the groundwater response to rainfall events.