Exploring Machine Learning and Deep Learning Techniques for Univariate and Multivariate Time Series Forecasting in the Area of Barisal in Bangladesh

Bangladesh, a densely populated country in South Asia, faces substantial challenges in water resources management due to its geographic location, hydrological features, and socio-economic aspects. Groundwater plays a dynamic role in meeting the water needs of both rural and urban population, accounting for approximately 85% of the total drinking water supply and a significant portion of irrigation water. With rapid population growing, urbanization, and industrialization, the demand for groundwater is constantly growing, increasing pressure on existing water resources and necessitating effective managing approaches. The consequence of this study lies in its potential to improve the correctness and trustworthiness of groundwater level forecasts, thereby supporting more conversant decision-making in water resources management, urban planning, and structure development. By using advanced machine learning and deep learning performances, this research challenges to fill the gaps that exist in traditional predicting methods and contribute to the justifiable use of groundwater resources in Bangladesh.