<p>Ignoring seasonal rainfall trends in India poses significant risks for urban water management and agriculture due to the increasing variability in precipitation patterns influenced by climate change. This study examines nine zones of Bihar’s rainfall patterns from 1984 to 2021, revealing shifts in winter rainfall, pre-monsoon, monsoon, and post-monsoon rains, with notable shifts in monsoon intensity. Such variability disrupts agricultural productivity, impacting food security and economic stability, especially in agriculture-dependent regions. The current study focuses on analyzing rainfall trends across nine zones of Bihar using approximately 37 years of remote sensing data (EC JRC/Google dataset); this research highlights significant temporal and spatial variations in surface water distribution across nine districts, with northern areas like Darbhanga and Kosi experiencing severe flooding and southern regions such as Magadh and Bhagalpur showing less water accumulation. The study also reveals regional disparities in rainfall, with Tirhut, Munger, and Patna receiving the highest rainfall, necessitating tailored water management strategies. Multiple seasonal decompositions and advanced statistical methods, including lagged scatterplots and autocorrelation function (ACF) analysis, were employed to identify distinct rainfall patterns and trends across different zones. Findings suggest the need for adaptive forecasting models that account for short-term and long-term variations, particularly in regions with high variability like Purnia and more stable regions such as Bhagalpur. This comprehensive analysis underscores the importance of developing region-specific strategies for effective water management and agricultural planning in the face of climate variability.</p> Graphical Abstract <p></p> <p>The study address the surface water changes in the eastern state of India, Bihar which has been divided into 9 zones. Bihar has been constantly facing water related issues where frequent floods, shifting rainfall patterns, decreasing groundwater levels and geographical position has been threating the life and livelihood of the residents. To better understand and manage the changes in the region, it is essential to apply PESTEL (Political, Economic, Social, Technological, Environmental, Legal) framework. To do so, the current study has tried to assess the changing precipitation Patterns and Trend Analysis using 37 years of remote sensing data with the help of machine learning tools. The Temporal changes in the distribution of surface water assessment, Rainfall Variability and Seasonality and pattern evaluation was done using Autocorrelation Function (ACF) and Partial autocorrelations (PACF) method and Multiple Seasonal-Trend Decomposition and Seasonal methods (Technological/Environmental). The study reveals significant temporal and spatial variations in rainfall, with notable shifts in monsoon intensity and seasonal distribution, impacting agriculture and water resources across the region (Economic/Social stability). The analysis highlights regional disparities, with northern zones like Darbhanga and Kosi experiencing higher rainfall, while southern regions like Magadh and Bhagalpur show more stable water accumulation. The result assessment reveals clear climate change signals across Bihar, reflected in shifting rainfall patterns and monsoon variability. It recommends adaptive forecasting models, region-specific water management strategies and the necessary legislative adaptations for transboundary water sharing (Legal/Political). The results offer a blueprint for region-specific water management, enhancing climate resilience through adaptive policy formulation.</p>