In India, where agriculture is a vital source of livelihood for two-thirds of the population, accurate estimation and analysis of soil moisture are essential for effective hydrological modeling, weather forecasting, and irrigation management. Soil moisture is a critical parameter for assessing crop stress, potential yield losses, and scheduling irrigation water applications. The Google Earth Engine (GEE) provides a powerful platform for analyzing satellite data to determine soil moisture levels in a cloud environment. The present study utilizes GEE to determine soil moisture levels in the agricultural watershed, Tadepalligudem India, covering an area of 5375 hectares, dominated by agriculture. The analysis utilizes NASA USDA SMAP satellite data and applies an algorithm to measure the microwave emissions from the earth's surface via passive microwave radiometry and active wave sensing. The SMAP satellite measures the amount of water in the top 5 cm of the soil layer with a temporal resolution of 3 days. The results of the soil moisture analysis using GEE and SMAP data provide valuable insights into the levels of soil moisture in the agricultural watershed, facilitating better irrigation management without incurring any crop yield losses. This study demonstrates the effective potential of GEE for soil moisture analysis, contributing to better agricultural practices and sustainable water resource management.