@article{haan_skaggs_2003, title={Effect of parameter uncertainty on DRAINMOD predictions: I. Hydrology and yield}, volume={46}, DOI={10.13031/2013.13968}, abstractNote={The computer–based hydrologic model DRAINMOD can be used to predict the effect of drainage design on the 
rate of subsurface drainage and on crop yield. An uncertainty analysis was conducted to quantitatively assess the variability 
in model outputs caused by parameter uncertainty. The analysis was based on an experimental field at the Tidewater Research 
Station in Plymouth, North Carolina. As a first step in the uncertainty analysis, a sensitivity test was conducted to determine 
which parameters in the model have the most influence on the model objective functions. First–order approximation and 
Monte Carlo simulation were used to determine the effect of the uncertainty in the most sensitive parameters on the 
uncertainty in the model objective functions. Objective functions evaluated were: average annual subsurface drainage 
volume; SEW30 (a measure of stress caused by excessive soil water in the top 30 cm) during the growing season; and relative 
yield for both conventional and controlled drainage. Nine parameters found to significantly affect model output were used 
in the uncertainty analysis. The first–order approximation showed that in the case of conventional drainage, lateral saturated 
hydraulic conductivity accounted for 81% of the uncertainty in terms of variance for predicted annual subsurface drainage 
volume, 81% for growing season SEW30, and 71% for relative yield. For controlled drainage, lateral saturated hydraulic 
conductivity contributed 62% of the uncertainty in terms of the variance in predicted annual subsurface drainage volume, 
69% in growing season SEW30, and 62% in relative yield. The Monte Carlo simulation showed similar results. Improving the 
knowledge of these most influential parameters will help to reduce the uncertainty in DRAINMOD predictions for these 
objective functions.}, number={4}, journal={Transactions of the ASAE}, author={Haan, P. K. and Skaggs, R. W.}, year={2003}, pages={1061–1067} }
 @article{haan_skaggs_2003, title={Effect of parameter uncertainty on DRAINMOD predictions: II. Nitrogen loss}, volume={46}, DOI={10.13031/2013.13969}, abstractNote={Reducing nitrate levels in sensitive coastal waters has become a national priority. Agriculture has been targeted 
as a significant contributor to this problem. Controlled drainage is recognized as one way to reduce nitrate losses from 
agricultural fields requiring subsurface drainage. The computer–based hydrology model DRAINMOD can be used to predict 
the effect of drainage design on the rate of subsurface drainage and the water quality related to nitrates in these waters. An 
uncertainty analysis of the model was conducted to quantitatively assess the variability in the model predictions for average 
annual nitrate loss through subsurface drainage, surface runoff, and denitrification caused by parameter uncertainty. 
First–order approximation and Monte Carlo simulation were used to estimate the effect of the uncertainty in the most sensitive 
parameters (dispersivity, bulk density, % nitrogen uptake by corn, mineralization rate constant, and denitrification rate 
constant) on the uncertainty in the model objective functions. The denitrification rate constant accounted for greater than 
70% of the uncertainty in terms of the variance for all objective functions under both conventional and controlled drainage. 
Reducing the uncertainty in influential parameters can reduce the uncertainty in DRAINMOD predictions for nitrate loss.}, number={4}, journal={Transactions of the ASAE}, author={Haan, P. K. and Skaggs, R. W.}, year={2003}, pages={1069–1075} }