Controlled drainage is a management strategy designed to mitigate water quality issues caused by subsurface drainage but it may increase surface ponding and runoff. To improve controlled drainage system management, a long-term and broader study is needed that goes beyond the experimental studies. Therefore, the goal of this study was to parametrize the DRAINMOD field-scale, hydrologic model for the Davis Purdue Agricultural Center located in Eastern Indiana and to predict the subsurface drain flow and surface runoff and ponding at this research site. The Green-Ampt equation was used to characterize the infiltration, and digital elevation models (DEMs) were used to estimate the maximum depressional storage as the surface ponding parameter inputs to DRAINMOD. Hydraulic conductivity was estimated using the Hooghoudt equation and the measured drain flow and water table depths. Other model inputs were either estimated or taken from the measurements. The DRAINMOD model was calibrated and validated by comparing model predictions of subsurface drainage and water table depths with field observations from 2012 to 2016. Simulations based on the DRAINMOD model can increase understanding of the environmental and hydrological effects over a broader temporal and spatial scale than is possible using field-scale data and this is useful for developing management recommendations for water resources at field and watershed scales.