Abstract: The installation of groynes along the riverbanks is a widely adopted practice in stream corridor restoration projects, aiming to create backflow zones（also known as dead-water zones） that can effectively enhance the river geomorphological diversity.The presence of lowvelocity circulation pattern in dead-water zones can promote sediment deposition and nutrient accumulation, thus creating a conductive environment for the growth of aquatic plants. Simultaneously, it can also influence material transport and diffusion processes within rivers, which holds immense importance to river ecosystems.The mean residence time relationship for the dead-water zone with emergent vegetation is investigated here by using a combination of dimensional analysis and genetic algorithm. For vegetated dead-water zones, the factors influencing the mean residence time can be classified into three categories: the hydraulic characteristics of the mixing layer, the morphology features of side-cavities, and the drag effect caused by vegetation. Firstly, the parameter 1+C_Dad_c, which represents the obstructive impact of vegetation, is introduced via π theorem with reference to previous work. It should be noted that in the absence of vegetation, i.e., 1+C_Dad_c=1, the material exchange activities are not affected by the canopy factor 1+C_Dad_c. However, in the presence of vegetation, the equation 1+C_Dad_c＞1suggests an influence on exchange processes. Secondly, other dominant factors, including the mainstream Froude number Fr which reflects the inlet flow intensity, as well as the three-dimensional shape factor（Wd_c）^0.5/L and the width-to-length ratio W/L,which reflect the morphological features of cavities, are identified through a comprehensive analysis and comparison. Then, the aforementioned four factors are used as independent variables to construct a general predictive model for the mean residence time in the vegetated cavity, i.e., a product model of power functions incorporating these four factors. Finally, based on 85 groups of data gathered from previous studies, the genetic program Eureqa is employed to train this general model, and subsequently, a mean residence time relationship is developed for vegetated dead-water zones. The evaluation on the coefficient of determination R~2 and the mean absolute error MAE demonstrates that the present formula possesses good predictive ability, and the analysis of the value ranges of each factor reveals that this formula exhibits a broad range of applicability. In addition, based on a comparative analysis of the impact of the four factors on the model results, the cavity aspect ratio W/L is considered as a critical parameter that significantly influences water residence characteristics in dead-water zones and should be duly taken into account when relevant engineering designs are conducted.