ROOT ZONE WATER QUALITY MODEL SENSITIVITY ANALYSIS USING MONTE CARLO SIMULATION

Abstract

Performing a sensitivity analysis for a mathematical simulation model is helpful in identifying key modelparameters 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 agriculturalmanagement systems and their representative input parameters are lacking. This study presents results of RZWQM outputresponse sensitivity to selected model input parameters. Baseline values for the parameters were measured for anexperiment on a manured corn field in eastern Colorado. Four groups of model input parameters (saturated hydraulicconductivity, organic matter/nitrogen cycling, plant growth, and irrigation water/manure application rates) were selectedand three model output responses (plant nitrogen uptake, silage yield, and nitrate leaching) were used to quantifyRZWQM sensitivity to selected model input parameters. A modified Monte Carlo sampling method (Latin HypercubeSampling) was used to obtain parameter sets for model realizations. The model parameter sets were then analyzedseparately using linear regression analysis. In general, RZWQM output responses were most sensitive to plant growthinput parameters and manure application rates. The plant nitrogen uptake and silage yield model output responses wereless 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 resultsshowed that model output responses were more sensitive to the average saturated hydraulic conductivity of the entire soilprofile than to the saturated hydraulic conductivity of individual soil layers.