Root zone water quality model sensitivity analysis using Monte Carlo simulation

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 of RZWQM output response sensitivity to selected model input parameters. Baseline values for the parameters were measured for an experiment on a manured corn field in eastern Colorado. Four groups of model input parameters (saturated hydraulic conductivity, organic matter/nitrogen cycling, plant growth, and irrigation water/manure application rates) were selected and three model output responses (plant nitrogen uptake, silage yield, and nitrate leaching) 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, RZWQM output responses were most sensitive to plant growth input parameters and manure application rates. The plant nitrogen uptake and silage yield model output responses were less sensitive to nitrogen cycling and irrigation rate input parameters than those observed in previous field experiments. This finding may warrant further study on the effects of water and nitrogen stresses on crop growth. Finally, the results showed that model output responses were more sensitive to the average saturated hydraulic conductivity of the entire soil profile than to the saturated hydraulic conductivity of individual soil layers.