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• The model of the LSTM was used to simulate transboundary streamflow temperature using an Open-Source database. • Operation of the cascade reservoirs was the dominant driver of the slight change in annual river temperature in the LMRB. • Cascade reservoir operation resulted in seasonal warming and cooling of the LMR, linearizing river temperature processes. The Lancang-Mekong River Basin (LMRB) is an important transboundary river basin containing large-scale cascade hydropower dams. There has been increasing interest in the cross-border impacts of cascade reservoirs and climate change on the water temperature of the LMRB. However, there remain limited related basin-scale quantitative studies. This study applied a deep learning method (Long short-term memory neural network, LSTM) to reconstruct the natural water temperature of the Lower Mekong River (LMR), which was compared with observation data influenced by dam operation. The aim of this study was to assess the impacts of the dams and climate change on the dynamics of water temperature in the basin. The results showed that: (1) Climate change had a relatively minor effect on the water temperature of the LMRB, with the warming effect of climate change gradually increasing from upstream to downstream. (2) The operation of the cascade reservoirs has resulted in seasonal warming and cooling of water temperature, although the average annual water temperature of the LMRB has increased by 0.27–0.59 °C. (3) The slight increase in annual average water temperature due to reservoir operation gradually weakened from upstream to downstream. (4) The increase in annual river temperature became more pronounced from 2008 to 2016 with the completion of Xiaowan, Nuozadu, and other power stations. This study characterized the responses of streamflow temperature to climate change and cascade reservoirs and can act as a reference for water resources management and hydropower development in the LMRB. [ABSTRACT FROM AUTHOR]