We evaluate the response of a passive microwave soil moisture retrieval algorithm to errors in the estimation of input variables and parameters. The model is run varying one parameter at a time within a specified range to quantify the effects individual parameters have on soil moisture retrieval. Although errors in the estimation of most parameters yield total variations in soil moisture of less than about 4% volumetric water content (vwc), variations in the estimates of vegetation water content, vegetation b parameter, percent clay, and surface roughness yield the greatest total variations in calculated soil moisture. The effects of these parameter variations on calculated soil moisture are greater for wetter soils (above 25% vwc) and can result in total variations in soil moisture retrieval up to 24% vwc. These same parameters have a compound effect on calculated soil moisture when they vary collectively; variations in soil moisture retrieval with errors in vegetation water content and surface roughness may be as high as 38% vwc (-12%, +26%). Even over more common conditions between 10% and 25% vwc, errors in vegetation water content, percent clay, and surface roughness result in total soil moisture variations of 9% to 15% (plus or minus 4.5% to plus or minus 7.5%), which are unacceptably high for many applications. When random errors are imposed on these three parameters of the Southern Great Plains 1997 (SGP97) Hydrology Experiment data set, the macrostructure of the soil moisture distribution remains intact compared to the original calculations, but the moisture field is significantly more heterogeneous. It is demonstrated that the distribution (plus or minus 2(sigma) ) of soil moisture for given values of brightness temperature ranges between plus or minus 5% vwc from random errors imposed on the same three parameters. Improvements in parameter estimation in SGP97 contributed to a decrease in the soil moisture uncertainty ((alpha) equals 0.05) by about 67% to plus or minus 3% vwc.