Modeling and testing of the effect of tillage, cropping and water management practices on nitrate leaching in clay loam soil

Intensive agricultural management practices have contributed to nitrate concentrations in surface and subsurface drainage water which exceed water quality guidelines. Numerous studies have been conducted to examine the effects of soil and crop management practices on nitrate leaching, however, there are few studies which examine new technologies to reduce nitrate leaching from agricultural land. In this study, technological advances in water table management are used in combination with conservation tillage and intercropping treatments to determine if nitrate leaching can be effectively reduced in a clay loam soil. There were two water table management treatments and four crop management treatments arranged in a 2 by 4 factorial arrangement with two replicates. The water table management treatments consisted of controlled drainage/subirrigation system (CDS) and a free drainage system (FD). The crop management treatments consisted of moldboard plow tillage with and without an annual ryegrass intercrop (MP, MP + IC) and soil saver (modified chisel plow) with and without an annual ryegrass intercrop (SS, SS + IC), The data was modeled using LEACHM and a mean error difference procedure was used to determine how well the model predicted the field data. The model worked well when the difference between the predicted and measured values approached zero. When the CDS system was modeled, the mean error difference values ranged from -1.67 to 0.33 mg N l(-1) for the I crop management treatments whereas the values were considerably greater when the FD system was modeled with values ranging between 7.48 and 12.7 mg N l(-1). Hence the LEACHM model predicted nitrate leaching better on plots under CDS system than on plots under FD, Both the Leaching Estimation and Chemistry Model (LEACHM) predicted scenarios and field sampled data showed that CDS reduced nitrate leaching substantially. Model calibration by using one full year of field data was found to be acceptable, but for predictions based on shorter calibration periods unsatisfactory results were obtained. (C) 2000 Elsevier Science B.V. All rights reserved.