With the fast-growing human population and attendant human activities, eutrophication has become a severe problem in fresh as well as coastal waters in many regions of the world. Evaluation of eutrophication can provide critical information for the governance and management of water resources. However, two basic and significant uncertainties, i.e. randomness and fuzziness, are ubiquitous in water quality evaluation. The cloud model method has been proposed to address the two uncertainties based on the principle of maximum entropy (POME) and engineering fuzzy set theory (EFST). Poyang Lake is the largest fresh water lake in China with one of the most important wetlands in the world, recognized by the International Union for the Conservation of Nature (IUCN). Poyang Lake has been severely disturbed by human activities, such as sewage discharge and sand mining, which has caused a severe degradation of water quality. Previous evaluations of eutrophication have mainly focused on the central areas of Poyang Lake, whereas the surrounding wetland has much been neglected. In this study, we aimed to develop a cloud model to assess eutrophication in Poyang Lake wetland. We also employed the widely used comprehensive trophic level index (TLI) and tested whether the two methods generated different results. We conducted field surveys to obtain the data on water quality at 30 sample sites in Poyang Lake wetland during September 25 and October 31, 2016. Five key physico-chemical parameters, i.e., chlorophyll-a (Chl-a), Secchi disk depth (SD), chemical oxygen demand using manganese (COD_Mn), total nitrogen (TN), and total phosphorus (TP) were analyzed in the laboratory and used as the input data for the cloud model and TLI. The clouds of each water quality parameter at five eutrophication levels (i.e., oligotrophic, mesotrophic, light eutrophic, middle eutrophic, and hyper eutrophic) were generated in Matlab based on the criteria for eutrophication level classification proposed by the Ministry of Environmental Protection of the People's Republic of China. The eutrophication level at each sample site was then determined by the maximum degree of certainty. Both of the two methods indicated that Poyang Lake wetland was overall in a light eutrophic state. The cloud model showed that seven sample sites were classified as mesotrophic, seventeen as light eutrophic, five as middle eutrophic, and one as hyper eutrophic, whereas the TLI indicated that twelve sample sites were classified as mesotrophic, fifteen as light eutrophic, and three as middle eutrophic. The reason for the difference between the two sets of results was that water physico-chemical parameters were weighted differently in the two methods. Highest weights were given to TN and TP in the cloud model, whereas Chl-a concentration was the most important variable in the TLI. Nitrogen and phosphorus were the main pollutants in Poyang Lake, whereas Chl-a concentration was not high, because the fast flow of water, as well as the high concentration of suspended sediment, limited the growth of phytoplankton. We thus considered that the cloud model method was more appropriate for eutrophication evaluation in Poyang Lake wetland.