Unraveling the Importance of the Yangtze River and Local Catchment on Water Level Variations of Poyang Lake (China) After the Three Gorges Dam Operation: Insights From Random Forest Modeling - Li, Bing; Yang, Guishan; Wan, Rongrong; Wang, Yanan; Xu, Chen; Wang, Dianchang; Mi, Chuang (Frontiers in Earth Science, 2022)
Investigating the contributions of the factors influencing lake water level and their related changes with regard to hydraulic facilities is vital for understanding the driving mechanism of water level variations under the manifold pressures from anthropogenic activities and climate change. In this study, a random forest (RF) model was used to investigate the changes of the relationship between water level and discharge of the Yangtze River and local tributaries in Poyang Lake, China, based on daily hydrological data from 1980 to 2018. The results indicated that RF exhibited robust capability for water level prediction in Poyang Lake, with average R2 of 0.95, 0.88, 0.92, and 0.94 for the dry, rising, wet, and recession seasons, respectively. Predictor importance analysis showed that the discharge of the Yangtze River had greater influence on the water level than the discharge of local tributaries except for the dry season in Poyang Lake, where the influence on the water level was evident with discharge less than 5,000 m3/s. The influence of the Yangtze River also showed a clear attenuation pattern as the distance from the outlet of the lake increased, where the water level was constantly regulated by the Yangtze River. In addition, the partial dependence plots also indicated that the Yangtze River discharge changes after the TGD operation have resulted in remarkable water level decreases in the wet and recession seasons, especially for the recession period. Meanwhile, a slight increase in water level was predicted under identical discharge of local catchment in the dry season, which was only concentrated in the outlet of the lake. This study indicated the RF model as a robust technique for water level predictions and attribution analysis under multiple temporal and spatial scales. Moreover, this study confirmed the uneven influences of the Yangtze River and local tributaries on water level across different seasons, gauging stations, and phases.