Increasing amounts of recycled water are being used in urban wetlands; as such, monitoring the growth of wetland plants over large areas is of great significance to assessing the restoration and reconstruction of wetlands created by recycled water. At present, remote-sensing technology is considered an important method for monitoring the growth of plants on a large scale. In this study, typical wetland plants (Phragmites australis and Typha angustifolia) growing in the South Park Wetland of Olympic Park were selected as research subjects. Spectral reflectance was determined at a domain ranging from 400 to 760 nm to avoid the influence of leaf water on the established model. Chlorophyll content was obtained from data sources. Statistical analysis, including correlation and stepwise regression analysis, was conducted to establish chlorophyll content inversion models with different derivative transformation spectrums at the leaf level for:(1) band depth (BD), (2) continuum-removed derivative reflectance (CRDR), (3) band depth ratio (BDR), and (4) normalized band depth index (NBDI). We found that 550 nm to 750 nm, particularly 700 nm to 750 nm (red edge range), was the key range to estimate biochemical parameters. Single removal cross-validation results indicated that optimal models of chlorophyll content inversion in reeds, cattails, and combined samples were BD, CRDR, and NBDI, respectively. Corresponding R² values were 0.87, 0.83, and 0.81, and the respective RMSE values were 0.16, 0.15, and 0.33, respectively. Kruskal-Wallis non-parametric tests and multi-way ANOVAs were performed to elucidate the influence of relevant factors individually and in combination with one another on the regression results of biochemical parameters of plant water. Results showed that vegetation type (reed, cattail) and data type (single or mixed species) greatly influenced the inversion model. In contrast, the spectral derivative transformation(BD, CRDR, BDR, and CRDR)and the interaction between spectral derivative transformation and data types did not significantly affect the inversion model. In this study, an estimation model of wetland plant biochemical parameters was established and functions of related factors in the estimation model were analyzed. Our results could be used as a scientific basis for non-destructive monitoring of growth in wetland plants. This study also provided a reference for the use of recycled water in restoration and management.