Parameterization is the key factor affecting the implementation of mos
t infiltration models. For the successful application of the Green-Amp
t equation in the Water Erosion Prediction Project (WEPP) model, proce
dures for estimating the effective hydraulic conductivity (K-e) must b
e developed. The objective of this study was to identify the major var
iables which affect K-e under row-cropped conditions and to develop st
atistical equations to quantify these relationships for use in WEPP. A
total of 328 plot-years of data from natural runoff plots from eight
sites was used to develop equations for estimating temporal variabilit
y of K-e under row-cropped conditions. The average period of record fo
r each crop management system was approximately nine years, during whi
ch an average of 96 storm events was selected for each treatment. Crop
s included corn, cotton, oars, soybeans, and potatoes. Measured soil,
climate, slope, and crop management information was used to build all
of the WEPP input files. An optimization program was written to determ
ine K-e for every selected event for which measured and predicted runo
ff volumes matched. Correlation analyses showed that storm rainfall, t
otal effective surface cover, and their cross-product were strongly re
lated to the optimized K-e. An interactive term consisting of soil pro
perties, storm rainfall, and effective surface cover was developed and
used for K-e prediction for row-cropped conditions. The r(2) for mode
l predicted total runoff of the selected events versus the measured wa
s 0.94 and the slope of regression was 1.01. Model efficiencies for in
dividual storm runoff predictions averaged 0.66. The results also show
ed that seasonal variations of K-e and runoff were adequately represen
ted.