洞庭湖流域极端降水变化特征分析

随着极端降水事件变率增强,洞庭湖流域频繁的极端洪旱事件严重威胁了地区人水和谐。基于洞庭湖流域28个国家气象站1961-2015年的逐日降水资料,采用RClim Dex模型定义阈值来识别极端降水事件,利用线性倾向估计法和集合经验模态分解(EEMD)组合的方法进一步分析了洞庭湖流域极端降水变化特征,由EEMD方法分解得到的各类极端降水指数的3个固有模态函数分量分别表现出3~6a、8~15a和21~27a的准周期。结果表明:洞庭湖流域极端降水频次峰值出现在6月,4-10月份极端降水频次之和占全年的82.7%,南岳和安化为极端降水高发带。洞庭湖流域除持续湿润日数CWD略有减小外,各项极端降水指数均表现出小幅上升趋势。在空间分布上,该流域东南部受山区地形地貌的影响,极端降水呈明显上升趋势。洞庭湖流域极端降水时空格局变化特征分析对流域水资源开发利用和水安全预警具有重要参考价值。

Spatiotemporal characteristics analysis of extreme precipitation variations in Dongting Lake Basin

With the increasing of the variability of extreme precipitation events, the extreme flood and drought events in the Dongting Lake Basin have already seriously threatened the harmony relationship of human and water. Based on the daily precipitation records of 28 national meteorological stations in the Dongting Lake Basin from 1961-2015, a threshold defined by the RClimDex model was used to identify extreme precipitation events. The methods of linear regression and ensemble empirical mode decomposition (EEMD) were employed to quantitatively analyze the temporal variability and spatial distribution of extreme precipitation indices. The intrinsic mode function (IMF) components of six extreme precipitation indices by EEMD in the Dongting Lake Basin reflect quasi-periodic periods of 3-6a, 8-15a and 21-27a. The results show that: the peak of extremely heavy precipitation occurred in June, and the extreme precipitation occurrenced during April to October, accounted for 82.7% of the total annual rainfall. Nanyue and Anhua with a high incidence of extreme precipitation and all extreme precipitation indices showed a slight upward trend in the Dongting Lake Basin except for the number of consecutive wet days (CWD). The spatial distribution in the southeast of the basin showed a significant upward trend of extreme precipitation, which is affected by the mountainous topography. The study on the variation characteristics of extreme precipitation events in the Dongting Lake Basin will be of important reference value to the water resources utilization and water security early-warning.