Over the decade, rapid climatic changes threaten agroecosystem stability and food security. The rapid transition from natural vegetation to agricultural land results to alteration of surface energy balance. Numerous interactions occur within the agroecosystem among its diverse components. Properly understanding these interactions helps mitigate environmental impact through modern climate-smart technologies and sustainable crop water management based on unique needs. Smart water management paves the pathway, particularly in water crises phase through the use of numerous contemporary artificial intelligences, machine learning tools, agrometeorological models and Internet of Things based modern watering devices aid in the efficient use of resources both on and off farm to improve agricultural output and quality. The study's objective is reviewing core technologies including advanced sensors, internet of things, remote sensing and agrometeorological models. The highlights of this study to investigate SWM systems. A comparative analysis of existing technologies identifies challenges such as high cost, data privacy concerns and policy gap. To address these gaps, this study proposes an integrated approach that combines artificial intelligence, remote sensing and IoT framework as most effective approach, enabling real time monitoring, precise irrigation scheduling and adaptive response to climate variability. Advancing these technologies with suitable, cost effective solutions, and policy interventions is crucial for ensuring climate resilient, increasing the efficiency of the smart management system and sustainable agricultural water management.