Climate change has altered precipitation events over past decades which impacted groundwater recharge in Michigan due to erratic rainfall, sandy soils, runoff fluctuations, seasonal and frozen ground in winter. Deep percolation (DP), critical factor for groundwater balance and hydrological processes, plays a significant role in groundwater sustainability and agricultural water management. Estimation of DP is challenging task and relies on different methods including soil moisture sensors that provides real-time soil water content measurements and weighing lysimeters which offers precise estimation under laboratory conditions. Soil moisture sensors were utilized for DP estimation in common Michigan soils, including Oakville Fine sand, Spinks Sandy loam, Riddles-Hillsdale loamy sand, and Kilmanagh loam soils. The CS655 soil sensors were installed at 15, 30, and 45 cm depths to estimate DP under different irrigation depths (mm) through change in soil moisture contents with time. A multilinear regression analysis was used to model the relationship between irrigation depths (mm), changes in soil water contents (cm