A growing number of studies employ time-averaged experimental data to determine dynamic ensembles of biomolecules of biomalecules. While it is well-known. that different ensembles Can satisfy experimental data to Within error, the extent, and nature of these degeneracies, and their impact on the accuracy Of the ensemble, determination remains poorly understood. Here, we use simulations. and a recently introduced metric. for assessing ensemble similarity-to explore degeneracies in determining ensembles using NMR residual dipolar couplings (RDCs) with specific application to A-form helices in RNA. Various :target ensembles were constructed representing different domain domain orientational distributions that are confined to a topologically restricted (<10%) conformational space. Five independent sets of ensemble averaged RDCs were then computed for each target ensemble and a "sample and select" scheme used to identify degenerate ensembles that satisfy RDCs to within experimental uncertainty. We find that ensembles with different ensemble sizes and that can differ significantly from the target ensemble (by as much as Sigma Omega similar to 0.4 where Sigma Omega varies between 0 and 1 for maximum and minimum ensemble similarity, respectively) can satisfy the ensemble averaged RDCs. These deviations increase with the number of unique conformers and breadth of the target distribution, and result in significant uncertainty in determining conformational entropy (as large as 5 kcal/mol at T = 298 K). Nevertheless, the RDC-degenerate ensembles are biased toward populated regions of the target ensemble, and capture other essential features of the distribution, including the shape. Our results identify ensemble site as a major source of uncertainty in determining ensembles and suggest that NMR interactions such as RDCs and spin relaxation, on their own, do not carry the necessary information needed to determine conformational entropy at a useful level of precision, The framework introduced here provides a general approach for exploring degeneracies in ensemble determination for different types of experimental data.