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 con centrations in surface and subsurface drainage water which exceed water qua lity guidelines. Numerous studies have been conducted to examine the effect s 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 tabl e management are used in combination with conservation tillage and intercro pping treatments to determine if nitrate leaching can be effectively reduce d 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 co ntrolled 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 (modi fied chisel plow) with and without an annual ryegrass intercrop (SS, SS + I C), 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 mod el worked well when the difference between the predicted and measured value s approached zero. When the CDS system was modeled, the mean error differen ce values ranged from -1.67 to 0.33 mg N l(-1) for the I crop management tr eatments whereas the values were considerably greater when the FD system wa s modeled with values ranging between 7.48 and 12.7 mg N l(-1). Hence the L EACHM model predicted nitrate leaching better on plots under CDS system tha n on plots under FD, Both the Leaching Estimation and Chemistry Model (LEAC HM) predicted scenarios and field sampled data showed that CDS reduced nitr ate leaching substantially. Model calibration by using one full year of fie ld data was found to be acceptable, but for predictions based on shorter ca libration periods unsatisfactory results were obtained. (C) 2000 Elsevier S cience B.V. All rights reserved.