Climate change and human activities directly or indirectly affect the global and regional hydrologic cycle, which is the main factor leading to the temporal and spatial distribution of water resources. Based on the long-short-term-memory (LSTM) model, this paper attributes the contribution of climate change and human activities on runoff variation in the Lake Poyang Basin. Results show that the runoff process was simulated well by LSTM framework with a window size of 10 days for both accuracy and computational efficiency. The overall performance of the model was good with Nash-Sutcliffe Efficiency varied from 0.94 to 0.95 in the training period and 0.90 to 0.98 in the test period, respectively. Based on the simulation results, the contribution of human activities and climate change on runoff change in Lake Poyang Basin was then quantified. Results show that the runoff increased by 139.47 m³/s due to human activities in spring, accounting for 77.26% of runoff change. Whereas climate change was the dominant factor in changing runoff in the other seasons, which led the runoff to decrease by 34.37 m³/s, accounting for about 75.84% of runoff changes. The results can provide scientific basis and theoretical guidance for water resources management in Lake Poyang Basin.