Underwater images from different scenes often exhibit complex and non-uniform degradation due to factors such as light absorption by water and the scattering effects of suspended particles. Even within the same image， the degradation degree varies across regions due to differences in scene depth. The most existing underwater image enhancement methods fail to specifically address the non-uniform degradation， leading to poor enhancement results. To solve this issue， this paper proposes an iterative underwater image enhancement network （IUIENet） based on degration distribution perception. IUIENet consists of three modules： a pre-enhancement module， a degradation distribution estimation module and an image refinement module. The pre-enhancement module initially estimates the enhancement result， while the degradation distribution estimation module and the image refinement module optimize the enhancement results using iterative cooperation. Experimental results demonstrate that IUIENet outperforms the compared methods in both visual quality and quantitative metrics on the UIEB， EUVP， and LSUI benchmark datasets.