Evaluation of DRAINMOD in Predicting Water Table Fluctuations and Yield of Canola in Paddy Fields (Case Study: Rasht, Iran)

Abstract

A hydrological simulation model, DRAINMOD, was used to predict the performance of surface drainage and yield of canola as post-rice cultivation during wet growing season of 2004-2005 in Rasht-Iran. The DRAINMOD model was evaluated on performance of surface drainage with 2 m spacings and 15 cm drain depth as compared with 4×10 m 2 plots having no drainage. The results showed that DRAINMOD model was well able to predict water table fluctuations. Evaluation of predicted daily water table depths as compared with measured values shows that the root mean square error (RMSE) was about 8 cm for both treatments. Predicted water table depth was, on average about 4% less than the measured water table depths for the surface drainage treatment and 17% less for the no drainage treatment. Accurate measurement of deep seepage is required to improve performance of the model. Results also showed DRAINMOD was capable of predicting relative yield of canola for both treatments. Poor aeration as a result of excess soil moisture could be related as the main reason for yield reduction.