Submitted to: Agronomy Society of America, Crop Science Society of America, Soil Science Society of America Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 6/4/2009
Publication Date: 8/3/2009
Citation: Jabro J.D. 2009. Calibration and Sensitivity Analyses of LEACHM Simulation Model. . Agronomy Abstracts. In: Agronomy abstracts. ASA-CSSA-SSSA, November 1-5, 2009, Pittsburgh, PA. Cd-Rom.
Technical Abstract: Calibration and sensitivity analyses are essential processes in evaluation and application of computer simulation models. Calibration is a process of adjusting model inputs within expected values to minimize the differences between simulated and measured data. The objective of this study was to calibrate and determine sensitivity analyses of LEACHM model for its ability to predict annual water drainage flux and NO3-N leaching losses. Drainage water and NO3-N losses data were a collected using zero-tension pan lysimeters placed 1.2 m below the soil surface under continuous corn cropping system. LEACHM calibration was performed in terms of the simulative ability of the model to approximate the measured field data collected from control, fertilized and manure treatments. The model was calibrated to the field site conditions using 1989-1990 data from a long term leaching experiment conducted on a Hagerstown silt loam soil. The initial stage of calibration focused on small changes to soil water flow parameters in the model. Calibration then focused on input parameters controlling soil N transformation processes and rate constants in the model. Sensitivity analyses were carried out on the calibrated LEACHM model by changing the values of input parameters within acceptable range. Results of sensitivity analyses indicated that LEACHM response was sensitive to slight changes in initial water content, water release curve Campbell’s equation fitted coefficients, saturated hydraulic conductivity in terms of water drainage flux simulations. Furthermore, NO3-N leaching losses simulated by LEACHM were sensitive to nitrification, denitrification and minerlization rate constants in the model.