Groundwater underpins drinking water supply, food security and ecosystem resilience worldwide, yet many aquifers are threatened by over-abstraction, pollution and climate variability. This chapter reviews how advanced geospatial technologies such as remote sensing (RS), geographic information systems (GIS) and the Global Positioning System (GPS) can be integrated with conventional hydrogeological methods to improve assessment, monitoring and management of groundwater systems. We outline the current limitations of traditional field approaches, highlight the added value of geospatial data and analytics, and discuss emerging contributions from artificial intelligence and machine learning (AI/ML). Comparative analysis illustrates trade-offs in accuracy, efficiency and cost, and synthesis of case studies demonstrates the benefits of combined approaches for groundwater potential mapping, contamination risk assessment and climate resilience planning. The chapter concludes with research priorities and actionable recommendations for science, policy and practice.