Land and Water Resources Management Using Machine Learning and Geospatial Techniques addresses critical knowledge gaps in hydrology, remote sensing, and soil and water conservation. The book explores various methodologies for estimating soil loss, encompassing modeling techniques, geospatial methodologies, and machine learning approaches in an effort to empower researchers in their pursuit of sustainable solutions for effective land and water management. Furthermore, it explore the fusion of geospatial tools with ML-based models, fostering an innovative approach to resource management.