Development and application of DRAINMOD model for simulating crop yield and water conservation benefits of drainage water recycling

Drainage water recycling (DWR) is an emerging practice that has the potential to increase crop yield and improve water quality. DWR involves capturing and storing subsurface drainage water and surface runoff in ponds or reservoirs, and using this water for supplemental irrigation during dry periods of the growing season. The main objective of this study was to enhance DRAINMOD model to simulate the hydrology and crop yield of DWR systems. The expanded model; named DRAINMOD-DWR, has a new module that conducts a water balance of the storage reservoir and simulates the interaction between the reservoir and the field, irrigated from and/or draining into the reservoir. The model predicts the long-term performance of DWR as affected by weather conditions, soil type, crop rotation, reservoir size, and irrigation and drainage management. Three performance metrics were defined based on model predictions to quantify irrigation, crop yield, and water capture benefits of DWR. To demonstrate the new features of the model, uncalibrated DRAINMOD-DWR was applied to a hypothetical DWR system with continuous corn using a 50-yr (1970–2019) weather record in Eastern North Carolina, U.S. Different reservoir sizes were simulated to demonstrate how the model can predict the effect of storage capacity on the system’s performance. The model predicted that a 3.0-m deep reservoir with a surface area of 4% of the field area would optimize corn yield for the simulated conditions. The model application clearly demonstrated the DRAINMOD-DWR model’s capability of optimizing the DWR system design to avoid under-sizing or over-sizing the storage reservoir, which reduces system’s performance and increases implementation cost. Research is needed to test DRAINMOD-DWR using field measured data, and to develop routines for simulating the fate and transport of nutrients and sediment in the storage reservoir, which would enable the model to predict the water quality benefits of DWR.