Lakes and reservoirs are essential freshwater sources, yet global monitoring of surface water storage faces challenges due to sparse gauge observations and limitations in remote sensing techniques. The lack of detailed knowledge about spatiotemporal dynamics of inland surface water storage impairs accurate global weather forecasting, Earth system modeling, and water management planning. To address this, we present Water area Tracking from Satellite imagery (WaTSat), a Google Earth Engine-based tool that generates long-term water area time series for global lakes and reservoirs from satellite imagery. Requiring minimal user input, low storage demand, and efficient computational overhead, the tool automates multiple tasks to modify the lake shoreline search area, identify and remove cloud-contaminated images, delineate the lake extent, detect and remove the outliers, and generate the water area time series. The initial version of the WaTSat tool utilizes the MODIS MOD09Q1 product to generate water area time series from February 2000 until the present. Validation against altimetric water level time series for 40 global lakes of varying sizes and regions demonstrates an average correlation of 0.89, confirming WaTSat's capability to accurately estimate surface water area and capture long-term trends and annual fluctuations. The tool's outputs can make a significant contribution to both scientific studies and operational applications in water resource management, hydrological modeling, and climate studies.