Water management technologies−including center pivot irrigation, subsurface drip irrigation, tile drainage, and open ditch drainage−require substantial upfront capital investments, yet their economic viability in the humid southeastern United States remains poorly understood. Previous research has largely evaluated irrigation and drainage technologies independently; this study jointly assesses both strategies for corn production in North Carolina’s northern coastal region, the Blacklands. This study develops and applies a farm-scale profitability framework in which corn yield responses to eighteen water management strategies are simulated using DRAINMOD (Skaggs, 2013), calibrated against field trial data, and integrated with empirical cost estimates through a novel grid search-based numerical optimization approach spanning 20 years of historical data (2005-2024). We find that drainage is the primary driver of profitability in the poorly drained Blacklands. Open ditch drainage with no land leveling or irrigation yields the shortest payback period (0.91 years), the highest net present value ($235,096.81), and the highest internal rate of return (32.52%), while subsurface drip irrigation combined with tile drainage and no land leveling generates the highest mean annual per-acre profit ($337.85). An important economic finding is that the profit-maximizing level of water management is generally less intensive than the agronomic optimum, highlighting the need to account for investment and operating costs in technology adoption decisions. These results are consistent with stakeholder sentiment and indicate that excess water is the primary limiting hydrological factor in the Blacklands. The framework in this study is designed to be transferable across North Carolina’s diverse agronomic regions as additional calibration data become available, and it has the potential to generate spatially differentiated profitability estimates that can help producers, policymakers, and stakeholders make more informed investment decisions.
