EVALUATION OF LEACHM .2. SIMULATION OF NITRATE LEACHING FROM NITROGEN-FERTILIZED AND MANURED CORN

Citation
Jm. Jemison et al., EVALUATION OF LEACHM .2. SIMULATION OF NITRATE LEACHING FROM NITROGEN-FERTILIZED AND MANURED CORN, Agronomy journal, 86(5), 1994, pp. 852-859
Citations number
30
Categorie Soggetti
Agriculture
Journal title
ISSN journal
00021962
Volume
86
Issue
5
Year of publication
1994
Pages
852 - 859
Database
ISI
SICI code
0002-1962(1994)86:5<852:EOL.SO>2.0.ZU;2-A
Abstract
High NO3-N concentrations in groundwater resulting from agricultural p roduction have increased the need for mathematical models to predict t he concentration and mass of NO3-N leached from agricultural soils. St udy objectives included evaluating the N version of LEACHM (LEACHMN) t o predict mass of NO-3-N leached from nonmanured and manured corn (Zea mays L.), and to test two methods of model validation. Four treatment s (no manure with 0 and 200 kg N ha-1 and a manure treatment with 0 an d 100 kg N ha-1) from a NO3 leaching experiment were modeled for 1988, 1989, and 1990. Model calibration involved adjusting nitrification, d enitrification, and volatilization rate constants to minimize differen ces between predicted and observed data. When calibrated for each year , LEACHMN produced reasonably accurate predictions of NO3-N mass leach ed; however, LEACHMN tended to overestimate summer and underestimate s pring leaching losses. The lack of a provision in LEACHM to allow solu te diffusion out of water flow channels, and underpredicted corn N upt ake early in the season probably created conditions conducive for high leaching losses early; following harvest, insufficient NO3-N in the s oil profile resulted in the model underestimating leaching in the spri ng. Validating LEACHMN using 1988 rate constants for the 1989 and 1990 years was unsuccessful. When 3-yr average rate constants were used, s imulation accuracy improved somewhat; most accurate simulations were f ound if 3-yr average values were close to the calibrated rate constant for that year. The model's predictive capability would probably impro ve if it contained a more complex corn N uptake routine and a dual-por e water flow component.