Wild waterfowl (family Anatidae) are reported as secondary transmitters of HPAIV and primary reservoirs for low-pathogenic avian influenza viruses, yet spatial inputs for disease risk modeling for this group have been lacking. Using geographic information software and Monte Carlo simulations, we developed geospatial indices of waterfowl abundance at 1 km resolutions for the breeding and wintering seasons for China, the epicenter of H5N1. Two types of spatial layers were developed: cumulative waterfowl abundance (WAB), a measure of predicted abundance by species, and cumulative abundance weighted by H5N1 prevalence (WPR), whereby abundance for each species was adjusted based on species specific prevalence values. Spatial patterns of the model output differed between seasons, with higher WAB and WPR in the northern and western regions of China for the breeding season and in the southeast for the wintering season. Uncertainty measures indicated highest error in southeastern China for both WAB and WPR.