| Popis: |
The Three Gorges Reservoir (TGR) operation has profoundly altered the hydrological regimes and ecosystem in the middle and lower Yangtze River basin. Its impacts on the river flow regime, sedimentation, lake level decline, and biodiversity have been extensively studied. However, the quantitative influence of the TGR on the downstream water exchange between the Yangtze River and Poyang Lake is lacking attention. In this study, we developed a machine learning model to investigate the river–lake water exchange variations under the TGR operation in typical hydrological years, compared with the natural scenario (i.e., no TGR). The results show that the machine learning model could provide a fast and accurate approach to identify the long-distance impact of reservoirs. The operation of the TGR has significant effects on the water exchange between the Yangtze River and Poyang Lake in the impounding period, with a 10,000 m³/s decrease in reservoir discharge approximately causing a 4,000 m³/s decrease in river–lake water exchange in the dry year and a decrease of 6,000 m³/s and 8,000 m³/s in reservoir discharge causing an increase of 4,000 m³/s and 6,000 m³/s in the normal year and the wet year, respectively. The TGR effect varies with different hydrological conditions of the river and lake, showing longer time range (from May to October) and greater degree (1.5 times the change rate in other years) in the wet year. The TGR operation is beneficial to the water maintenance of the lake in the dry year and flood control in the lake area in the wet year. This study provides a constructive approach and valuable information for decision making in water resource management and ecosystem protection in large river–lake systems. |
