Climate Change Impacts on Watershed Hydrology: Trends, Models, and Adaptation Strategies

This review paper presents a consolidated examination of climate change impacts on watershed hydrology through the lens of eleven influential studies from diverse geographical regions. The review identifies prevailing hydrological trends, modeling tools, and adaptation strategies, while recognizing crucial gaps in data integration, real-time modeling, sociohydrological coupling, and resilience metrics. To address these shortcomings, the paper proposes a novel Watershed Resilience Indexing and Forecasting Engine (WRIFE) that fuses deep learning, participatory sensing, and dynamic scenario adaptation. This model aims to enhance the predictability, responsiveness, and inclusivity of future watershed management under changing climatic regimes.