Abstract

The potential impact of climate change on river eutrophication and ecosystems are emerging problems that are of great concern to international and domestic societies. Scientific research and developing methods to address these problems are challenging. 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 involving indicators of climate changes, 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 modeling method has been applied to the Wuhan section of Han River, which is one of major freshwater sources in China. The predicted probability of algal bloom occurrence for the next 40 years by the method is used to identify the impacts of climate change and human activities on the formation mechanisms of river algal blooms under three scenarios. The principles of possible adaptation options are discussed in this thesis.

The modeling results indicate the temperature is one of the direct factors contributing to river eutrophication and the change of river water quality. It has also been recognized that the climate change, which can alter water temperature and hydrological regimes, in conjunction with human activities can significantly influence water quality and the river ecosystem. The present study is expected to give theoretical supports and directions for further relevant research.