Monitoring water resources globally is crucial for forecasting future geo-hydro disasters across the Earth. In the present study, an attempt was made to assess the functional dimensionality of multi-satellite precipitation products, retrieved from CHIRPS, NASA POWER, ERA-5, and PERSIANN-CDR with respect to the gridded India Meteorological Department (IMD) precipitation dataset over a period of 30+ years (1990–2021) on monthly and yearly time scales at regional, sub regional, and pixel levels. The study findings showed that the performance of the PERSIANN-CDR dataset was significantly better in Central India, Northeast India, and Northwest India, whereas the NASA-POWER precipitation product performed better in Central India and South Peninsular of India. The other two precipitation products (CHIRPS and ERA-5) showed the intermediate performance over various sub regions of India. The CHIRPS and NASA POWER precipitation products underperformed from the mean value (3.05 mm/day) of the IMD gridded precipitation product, while the other two products ERA-5 and PERSIANN-CDR are over performed across all India. In addition, PERSIANN-CDR performed better in Central India, Northeast India, Northwest India, and the South Peninsula, when the yearly mean rainfall was between 0 and 7 mm/day, while ERA-5 performed better in Central India and the South Peninsula region for a yearly mean rainfall above 0–7 mm/day. Moreover, a peculiar observation was made from the investigation that the respective datasets were able to characterize the precipitation amount during the monsoon in Western Ghats. However, those products needed a regular calibration with the gauge-based datasets in order to improve the future applications and predictions of upcoming hydro-disasters for longer time periods with the very dense rain gauge data. The present study findings are expected to offer a valuable contribution toward assisting in the selection of an appropriate and significant datasets for various studies at regional and zonal scales.

This study presents a comprehensive analysis of extreme events, especially drought and wet events, spanning over the past years, evaluating their trends over time. An investigation of future projections under various scenarios such as SSP-126, SS-245, and SSP-585 for the near (2023–2048), mid (2049–2074), and far future (2075–2100) using the bias-corrected Coupled Model Intercomparisons Project 6 (CMIP6) multi-model ensemble method was also performed. The Standard Precipitation Index (SPI), a simple yet incredibly sensitive tool for measuring changes in drought, is utilized in this study, providing a valuable assessment of drought conditions across multiple timescales. The historical analysis shows that there is a significant increase in drought frequency in subdivisions such as East MP, Chhattisgarh, East UP, East Rajasthan, Tamil Nadu, and Rayalaseema over the past decades. Our findings from a meticulous examination of historical rainfall trends spanning from 1951 to 2022 show a noticeable decline in rainfall across various regions such as Uttar Pradesh, Chhattisgarh, Marathwada, and north-eastern states, with a concurrent increase in rainfall over areas such as Gujarat, adjoining regions of West MP and East Rajasthan, and South Interior Karnataka. The future projection portrays an unpredictable pattern of extreme events, including droughts and wet events, with indications that wet frequency is set to increase under extreme SSP scenarios, particularly over time, while highlighting the susceptibility of the northwest and south peninsula regions to a higher incidence of drought events in the near future. Analyzing the causes of the increase in drought frequency is crucial to mitigate its worst impacts, and recent experiences of drought consequences can help in effective planning and decision-making, requiring appropriate mitigation strategies in the vulnerable subdivisions.

Methane is produced by various natural processes that directly or indirectly contribute to the entire Earth’s methane budget. If the Earth’s overall methane budget becomes imbalanced, CH₄ has an impact on climate change. Wetlands, rice fields, animals, factories, and fossil fuels are major sources of methane emissions. Among all the resources, wetlands and rice fields are more prominent factors in methane emission, dependent on the water table, temperature, and vegetation. Our study employed the GIS remote sensing technique to analyze methane emissions from 2003 to 2021 in the northern part of India, East Uttar Pradesh and Bihar, and the northeast region of India that is Assam. We also predicted the water table, temperature, and vegetation as raw materials for methane creation. Water table, temperature, and vegetation are essential for wetland ecosystem life, particularly for methanogenic organisms; however, the water table and temperature are critical for rice plant growth and development. With the help of GIS remote sensing, India’s monthly rainfall pattern and the water table, vegetation, and temperature pattern over 41 years were analyzed. Our key findings highlight the importance of GIS remote-sensing-based monitoring of methane gas emissions from wetlands and rice fields for their management.