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ARS Home » Research » Publications at this Location » Publication #124599
Title: ROOT ZONE WATER QUALITY MODEL SENSITIVITY ANALYSIS USING MONTE CARLO SIMULATION

Author
item Ma, Liwang
item Ascough Ii, James
item Ahuja, Lajpat
item Weltz, Mark
item Rojas, Kenneth
item Hanson, Jonathan

Submitted to: Transactions of the ASAE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/28/1999
Publication Date: N/A
Citation: N/A

Interpretive Summary: Performing a sensitivity analysis for a mathematical simulation model is helpful in identifying key model parameters and simulation errors resulting from parameter uncertainty. The Root Zone Water Quality Model (RZWQM) has been evaluated for many years, however, detailed sensitivity analyses of the model to various agricultural management systems and their representative input parameters are lacking. This study presents results o RZWQM output response sensitivity to selected model input parameters. Baseline values for the parameters were measured for an experiment on a manured cornfield in eastern Colorado. Four groups of model input parameters were selected and three model output responses were used to quantify RZWQM sensitivity to selected model input parameters. A modified Monte Carlo sampling method (Latin Hypercube Sampling) was used to obtain parameter sets for model realizations. The model parameter sets were then analyzed separately using linear regression analysis. In general, RZQWM output responses were most sensitive to plant growth input parameters and manure application rates.

Technical Abstract: Performing a sensitivity analysis for a mathematical simulation model is helpful in identifying key model parameters and simulation errors resulting from parameter uncertainty. The Root Zone Water Quality Model (RZWQM) has been evaluated for many years, however, detailed sensitivity analyses of the model to various agricultural management systems and their representative input parameters are lacking. This study presents results o RZWQM output response sensitivity to selected model input parameters. Baseline values for the parameters were measured for an experiment on a manured cornfield in eastern Colorado. Four groups of model input parameters were selected and three model output responses were used to quantify RZWQM sensitivity to selected model input parameters. A modified Monte Carlo sampling method (Latin Hypercube Sampling) was used to obtain parameter sets for model realizations. The model parameter sets were then analyzed separately using linear regression analysis. In general, RZQWM output responses were most sensitive to plant growth input parameters and manure application rates.