Modeling movements of particulates in the atmosphere involves its own set of complexities as compared to modeling gaseous materials. Whether inert or biota, particulate deposition can be a minor or overwhelming loss mechanism. Dry deposition has been analyzed fairly extensively in the literature with a resistance scheme used in many transport-dispersion models. Wet deposition on the other hand, has not been as widely studied and is less accurately modeled. The physical interaction of particles and raindrops producing interception and impaction scavenging can be estimated if the raindrop and particle size distributions are known. The largest uncertainty in wet deposition, however, is determining the temporal and spatial distribution of precipitation. The most common source of rainfall data comes from standard surface weather observations. These data are sparse in both space and time. Prognostic models such as RAMS or MM5 can be used to predict non-convective and convective rainfall. The accuracy of these predictions may be questionable at times. This paper will compare wet deposition rates, within the SLAM-P trajectory dispersion model, estimated using rainfall rates from observed data and RAMS model output. With the increased availability of NEXRAD data, these data may produce the best estimates of precipitation fields. Comparison of wet deposition fields may be compared to precipitation estimates from local NEXRAD data.