The potential impact of climate change on water eutrophication and ecosystems is of great international and domestic concern. This study aims to analyze the impact of climate change on algal bloom problems in large river systems by utilizing a parametric river eutrophication model that is established using indicators of climate change, hydrological regimes, water quality and nutrient loads. Specifically, the developed parametric modeling method is based on statistical and simulation methods including: Multiple Linear Regressions (MLR), Multiple Non-linear Regressions (MNR), Artificial Neural Network (ANN) based on Back-propagation (BP) algorithms, as well as an integrated river eutrophication model. The developed model was applied to Han River, which is one of the major sources of fresh water in Wuhan City, China. The impacts of climate change and human activities on the occurrence mechanisms of algal blooms in the Han River were identified by scenarios analysis. The individual assessment result indicates that the waste nutrient P load has the most significant impact (14.82%), followed by the flow rate (5.56%) and then by temperature (3.7%). For the integrated climate change assessment, it has been found that there is a significant impact (20.37%) when waste load increases and flow rate decreases at the same time. This is followed by increase of both waste load and temperature (15.82%). If temperature increases but flow rate decreases, the impact is predicted to be 11.11%. The final results point to human activities as a significant influence on water quality and the Han River ecosystem, temperature is also one of the main factors which directly contribute to algal blooms in Han River. The results in present study are expected to give theoretical supports for further relevant research on water eutrophication.