Understanding Hydrological Changes at Chiang Saen in the Lancang–Mekong River by Integrating Satellite-Based Meteorological Observations into a Deep Learning Model

Understanding the temporal variation in streamflow in the Lancang–Mekong River and its driving mechanism is essential for water resource management of this important international river. In this study, streamflow at the Chiang Saen gauging station was simulated using a long short-term memory (LSTM) model driven by satellite-based Multi-Source Weighted-Ensemble Precipitation (MSWEP) and Multi-Source Weather (MSWX) datasets, with the aim of quantifying the contributions of climate change and human activities to streamflow variations. A key contribution of this work lies in the use of LSTM to reproduce naturalized streamflow conditions—using only climate inputs—thereby providing a data-driven alternative to conventional process-based modeling approaches in this data-scarce basin. The monthly precipitation and temperature data of Chiang Saen station from 1979 to 1991 are used for model training and validation. The natural streamflow of Chiang Saen station from 1992 to 2021 is reconstructed based on the trained model. The results show that the annual average precipitation of the basin from 1979 to 2021 only exhibits a statistically insignificant decreasing trend, while the annual average temperature shows a statistically significant upward trend, and the inter-annual variation in the annual average streamflow shows a non-significant downward trend. Periodic analysis shows that the main periodicity of precipitation, temperature, and streamflow data is 12 months, following annual periodicity in climate. LSTM simulations demonstrate high accuracy in predicting the streamflow in T month based on the MSWEP precipitation and MSWX temperature data in T-2, T-1, and T months. On an annual scale, the streamflow in the changing period (1992–2021) decreases by only 4.6% compared with the reference period (1979–1991). In spring, the streamflow in the changing period is 30.6% higher than that of the reference period, and climate change and human activities contribute 40.8% and 59.2%, respectively. Increases in streamflow (3.4%) are also detected in the winter, with human activity as the dominant contributing factor. For the summer, the streamflow in the changing period is −8.2% lower than that in the reference period, with a greater contribution from human activities (68.7%) than climate change (31.3%). The streamflow in autumn of the changing period is −12.1% lower than that in the reference period, with a greater contribution from human activities (90.2%) than climate change (9.8%). In general, the findings of this study indicate that the driving mechanisms behind streamflow changes at Chiang Saen are complex at different temporal scales, and they provide valuable insights for improving our understanding of hydrological changes within the Lancang–Mekong River Basin.