2021 journal article
DRAINMOD modeling framework for simulating controlled drainage effect on lateral seepage from artificially drained fields
AGRICULTURAL WATER MANAGEMENT, 254.
We demonstrated a DRAINMOD modeling framework to predict controlled drainage (CD) effect on the fate of water in artificially drained agricultural fields, which is key for determining the water quality benefits of the practice. To demonstrate this modeling framework, DRAINMOD simulated the hydrology of a subsurface drained grass field in Eastern North Carolina, U.S. under both free drainage (FD) and CD. Three scenarios were simulated for each water management: no lateral seepage (LS) and LS with constant and dynamic hydraulic head (Hr). For each scenario, predicted water table depth (WTD) and subsurface drainage were compared to observed values using Mean Absolute Error, Nash-Sutcliffe Efficiency, and Normalized Percent Error. Predicted water balance components for different scenarios were also investigated. Results clearly showed that LS was a significant component of the water balance for CD. Model predictions showed that 96% of the reduction in subsurface drainage due to CD could be attributed to LS (33.5 cm yr−1). The large values of LS predicted by the model were attributed to the presence of a permeable sandy layer in the soil profile, the shallow management depth of the drain outlet, and the small size of the experimental field plots. Agreement between predicted and observed WTD and subsurface drainage ranged from acceptable to excellent for FD with and without considering LS. In contrast, DRAINMOD simulations for CD yielded acceptable predictions only for the scenario considering LS with dynamic Hr. This study demonstrated the power of process-based simulation models, such as DRAINMOD, for interpreting and explaining data of experimental studies and underscored the importance of using a proper model calibration strategy for yielding reliable predictions. This study highlights the need for well-coordinated experimental and modeling research to further investigate how seepage affect CD performance for reducing drainage flow and nitrogen losses from artificially drained agricultural fields.