Quantitative assessment of the relative impacts of climate change and human activity on flood susceptibility based on a cloud model

Abstract Floods are generally considered to be the most common natural disaster worldwide. Climate change and human activity are two key driving factors of flood formation, and it is difficult to determine how to quantitatively detect their relative impacts on flood susceptibility. As an important non-engineering measure of preventing floods and reducing losses, flood susceptibility assessment is a synthetic task that involves many factors. In this study, the flood susceptibility in Guangdong Province, China, was assessed based on a cloud model. The relative impacts of climate change and human activity on flood susceptibility were also quantitatively investigated from the spatial perspective. The results prove that the cloud model is a feasible, reasonable, and effective method for flood susceptibility assessment. Approximately 40% of the studied areas have changed their flood susceptibility level since 1985 due to the comprehensive impacts of climate change and human activity, of which about 56.3% converted from a low to high level, and 43.7% from a high to low level. About 35.7% of the areas changed their susceptibility level due to climate change, of which 55.8% converted from a low to high level and 44.2% from a high to low level. In contrast, only 9.8% of the areas changed the susceptibility level due to human activity, of which 57.2% converted from a low to high level and 42.8% from a high to low level. Generally, from the spatial perspective, climate change has a larger impact on flood susceptibility than human activity. This study aims to provide a novel idea to quantitatively detect the relative impacts of climate change and human activity on flood susceptibility from spatial perspective; the findings of this study are also expected to enhance the understanding on distribution rule of flood susceptibility in Guangdong Province and are conducive to taking targeted measures to reduce the flood risk.