The Hulanhe Wetland is located in northeastern of China, and plays an important role in maintaining the biodiversity and regulating the microclimate in Harbin city. Although phytoplankton functional group studies on wetlands in northern China have increased recently, studies of the phytoplankton functional group in the Hulanhe Wetland are limited. To better understand processes of phytoplankton community succession in relation to environmental parameters, the functional mechanisms of biological communities may be better understood if species are pooled into groups with similar characteristics. Therefore, a detailed survey of three phytoplankton functional groups in spring, summer, and autumn are necessary. In this study, three different phytoplankton functional group methods were used to study phytoplankton community structure. Phytoplankton was qualitatively and quantitatively collected from 11 sampling sites in four typical habitats. The samples were collected in spring (April, May), summer (June, July, August), and autumn (September, October). A total of eleven sample sites were selected. We explored the succession characteristics of FG (Functional Group), MFG (Morpho-Functional Group) and MBFG (Morphology-Based Functional Group) functional groups by applying ASNOSIM and SIMPER analysis. A total of 243 phytoplankton species were identified, belonging to 7 phyla, 9 classes, 18 orders, 32 families and 75 genera. The phytoplankton species composition was dominated by and Chlorophyta (46.09%), followed by Euglenophyta (19.34%), Bacillariophyta (18.52%) and Cyanophyta (11.11%). During the study, the results showed that the average abundance of phytoplankton in the Hulanhe Wetland was significantly different (P<0.05). According to the abundance of phytoplankton, B (Cyclotella Kützing), J (Scenedesmus Meyen, Tetrastrum Chodat), D (Nitzschia Hassall), S1 (Pseudanabaena limnetica (Lemmermann) Komárek), Y (Cryptomonas erosa Hering, Cryptomonas ovata Hering) and W1 (Euglena Ehrenberg, Phacus Dujardin) were dominant in the functional groups. 25 functional groups, 20 Morpho-Functional Groups and 6 Morphology-based Functional Groups were identified during the study. The ANOSIM analysis showed significant differences in FG and MFG functional group structures between seasons. The SIMPER analysis indicated that the primary contributing phytoplankton functional groups were S1/Lo (Merismopedia Meyen)/W1/P (Melosira granulata (Ehrenberg) Ralfs)/J/Y, 9b (small unicells-Chlorococcales)/5a (thin fifilaments Oscillatoriales)/11b (Chlorococcales-Gelatinous colonies)/6a (large Centrics)/2c (small Euglenophytes)/2d (Cryptophytes)/1c (large Euglenophytes) and Ⅲ (large fifilaments)/Ⅰ (small organisms with high S/V). Redundancy Analysis (RDA) based on FG, MFG and MBFG and eleven environmental variables revealed that COD_Mn was the key factor driving the phytoplankton functional group succession, and Turbidity (Tur.), BOD₅ and pH were closely related to phytoplankton functional group patterns. We found that MBFG approach was not as sensitive as FG and MFG approach in describing the variability of phytoplankton groups in the environment. We suggested that MBFG approach was not suitable for indicating the temperate wetland water environment condition.