This study systematically reviews the application of geospatial technology, particularly remote sensing (RS) and Geographic Information Systems (GIS), in agricultural water management in India. The review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, focusing on 60 recent research articles. The primary objectives are to identify specific challenges in agricultural water management, the datasets and tools used, and the progress and future scope of geospatial technology in this domain. Key findings include: 1. **Challenges and Applications**: The review highlights various challenges in agricultural water management, such as evapotranspiration estimation, irrigation water requirement, drought assessment, runoff estimation, water body mapping, and soil moisture estimation. 2. **Remote Sensing Datasets**: Landsat series data, particularly multispectral sensors, are widely used for agricultural water management. However, advanced technologies like Sentinel, Unmanned Aerial Vehicles (UAVs), and hyperspectral technology have not been fully explored. 3. **Future Scope**: The integration of advanced technologies such as cloud computing, IoT, artificial intelligence, 3D GIS, mobile GIS, augmented reality, hyperspectral drones, balloons, robotics, digital twins, and blockchain with GIS and remote sensing technologies is expected to revolutionize agricultural water management. 4. **Data Sources**: The review notes that while Landsat and MODIS are commonly used, the potential of newer sensors like Sentinel-1 and -2, which offer better revisit times and spatial resolution, has not been fully utilized. The study emphasizes the importance of timely, accurate, and objective data provided by RS technologies for effective agricultural water management. It also highlights the need for further research to develop advanced models and algorithms that can better address the challenges of water scarcity and climate change in India.This study systematically reviews the application of geospatial technology, particularly remote sensing (RS) and Geographic Information Systems (GIS), in agricultural water management in India. The review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, focusing on 60 recent research articles. The primary objectives are to identify specific challenges in agricultural water management, the datasets and tools used, and the progress and future scope of geospatial technology in this domain. Key findings include: 1. **Challenges and Applications**: The review highlights various challenges in agricultural water management, such as evapotranspiration estimation, irrigation water requirement, drought assessment, runoff estimation, water body mapping, and soil moisture estimation. 2. **Remote Sensing Datasets**: Landsat series data, particularly multispectral sensors, are widely used for agricultural water management. However, advanced technologies like Sentinel, Unmanned Aerial Vehicles (UAVs), and hyperspectral technology have not been fully explored. 3. **Future Scope**: The integration of advanced technologies such as cloud computing, IoT, artificial intelligence, 3D GIS, mobile GIS, augmented reality, hyperspectral drones, balloons, robotics, digital twins, and blockchain with GIS and remote sensing technologies is expected to revolutionize agricultural water management. 4. **Data Sources**: The review notes that while Landsat and MODIS are commonly used, the potential of newer sensors like Sentinel-1 and -2, which offer better revisit times and spatial resolution, has not been fully utilized. The study emphasizes the importance of timely, accurate, and objective data provided by RS technologies for effective agricultural water management. It also highlights the need for further research to develop advanced models and algorithms that can better address the challenges of water scarcity and climate change in India.