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Drainage reorganization generally occurs on geological time scales under unstable river network conditions. A few local‐scale studies indicate that recent climatic changes might accelerate the drainage reorganization process. However, large‐scale drainage reorganization during the modern era is rarely documented. This study examines ongoing drainage reorganization on the endorheic Tibetan Plateau (TP) as a primary result of drastic lake expansion. A total of 11 drainage system reorganization events comprising 24 different lake basins and covering a total area of 61,115 km2 occurred between 2000 and 2018. Assuming the continued growth rate of TP lakes, we project another 20 basins will be reorganized before 2030. These drainage basin reorganizations not only alter hydrological processes in the endorheic TP but may also cause the endorheic‐exorheic transition, leading to the upstream sprawl of the Yangtze River Basin and posing outburst flooding risks on China's key infrastructure such as the Qinghai‐Tibet Railway. Plain Language Summary: Recent climatic changes have intensified the global hydrologic cycle, and have likely accelerated drainage system evolution. We have provided a holistic picture of ongoing drainage reorganization driven by drastic lake expansions on the Tibetan Plateau (TP). Our results indicate that 24 different lake drainage systems have undergone reorganization between 2000 and 2018, and the number of basins is expected to increase to 44 by the year 2030. One notable drainage reorganization is between the endorheic Lake Yanhu and the exorheic Chumaer river, resulting in the upstream expansion of the Yangtze River Basin. These findings provide an increased understanding of ongoing drainage reorganization events driven by climatic changes. Further, this work advances our understanding of the connections between ongoing hydrologic changes and their effect on related geological disasters (e.g., outburst floods) within the TP. Key Points: Rapid lake growths drive large‐scale drainage reorganizations on the Tibetan Plateau24 lake drainage systems have undergone reorganization from 2000 to 2018 and this number is expected to increase to 44 by the year 2030The northern portion of the upstream Yangtze basin has expanded by around 8,400 km2 due to an endorheic‐exorheic transition [ABSTRACT FROM AUTHOR]

Lake Hulun is the fifth‐largest lake in China, playing a substantial role in maintaining the balance of the grassland ecosystem of the Mongolia Plateau, which is a crucial ecological barrier in North China. To better understand the changing characteristics of Lake Hulun and the driving mechanisms, it is necessary to investigate the water storage changes of Lake Hulun on extended timescales. The main objective of this study is to reconstruct the water storage time series of Lake Hulun over the past century. We employed a machine learning approach termed the extreme gradient boosting tree (XGBoost) to reconstruct the water storage changes over a one‐century timescale based on the generated bathymetry and satellite altimetry data and investigated the relationships with hydrological and climatic variables in long term. Results show that the water storage changes from 1961 to 2019 were featured by four fluctuation phases, with the highest water storage observed in 1991 (14.02 Gt) and the lowest point in 2012 (5.18 Gt). The century‐scale reconstruction result reveals that the water storage of Lake Hulun reached the highest point in the 1960s within the period of 1910–2019. The lowest stage occurred in the sub‐period of the 1930s–1940s, which was even lower than the alerted shrinkage stage in 2012. The predictive model results indicate the effective performance of the XGBoost model in reconstructing century‐scale water storage variations, with the mean absolute error of 0.68, normalized root mean square error of 0.11, Nash–Sutcliffe efficiency of 0.97, and correlation coefficient of 0.94. The annual fluctuations of water storage were mostly affected by precipitation, followed by vapor pressure, temperature, potential evapotranspiration, and wet day frequency. The dominating characteristics of different variables vary evidently with different sub‐periods. The atmospheric circulations of the Arctic Oscillation, El Nino Southern Oscillation, Pacific Decadal Oscillation, and North Atlantic Oscillation have tight associations with the water storage variations of Lake Hulun, which change with different study periods. Plain Language Sumamry: To better understand the changing characteristics of Lake Hulun and the driving mechanisms, it is necessary to investigate the water storage changes of Lake Hulun on extended timescales (e.g., century timescale). The main objective of this study is to reconstruct the water storage time series of Lake Hulun over the past one century. We employed a machine learning approach termed the extreme gradient boosting tree (XGBoost) to reconstruct the one‐century water storage changes and investigated the relationships with hydrological and climatic variables in long term. The century‐scale reconstruction result reveals that the water storage reached the highest point in the 1960s within the period 1910‐2019. The lowest stage occurred in the 1930s‐1940s, which was even lower than the alarted shrinkage stage in 2012. The annual fluctuations of water storage were mostly affected by precipitation, followed by vapor pressure, wet day frequency, potential evapotranspiration, and temperature. However, the dominating characteristics of different variables vary evidently with different sub‐periods. This study is expected to provide an efficient technical solution of reconstructing long‐term lake water storage records and to advance our scientific understanding of the characteristics of lake water balances in response to climate change and variability in the Mongolia Plateau. Key Points: The complete bathymetry map of Lake Hulun was constructed based multi‐source remote sensing dataA machine learning approach was employed to reconstruct the century‐scale water storage of Lake HulunThe potential links of one‐century variations of lake water storage with climatic variables and atmospheric circulations [ABSTRACT FROM AUTHOR]

[Display omitted] • Centenary change of Bosten Lake water storage was reconstructed by machine learning. • The lake water storage underwent six dramatical fluctuations over the past century. • The annual salinity changes were affected mainly by vapor pressure and precipitation. • Lake salinities showed substantial spatial and intra-annual variability. In the context of accelerating climate changes and economic boom in the past decades, lakes have undergone drastic changes worldwide. Particularly in arid and semi-arid regions, those lakes were severely impacted and threatened due to their hydrologic sensitivity and ecological vulnerability. As the largest lake in Northwest China with arid climate, Bosten Lake provides precious water resources and ecosystem services to local communities. Although a large quantity of earlier efforts have been paid on Bosten Lake, there is still absence of tracking its changing trajectory at a long timescale (e.g., one century), which restricts the holistic understanding of the decadal periodic lake desiccations and their driving forces. This study employs a machine learning method to reconstruct the centenary covariations of water storage and salinity of Bosten Lake by integrating multi-source data. The results showed that, compared with the high stage of 6.76 × 109 m3 in 1961, the lake water storage substantially dropped twice to 3.96 × 109 m3 in 1987 and 4.67 × 109 m3 in 2013. In recent years, the lake level rose rapidly and recovered back to the comparable stage of the 1960 s by 2020. Four metrics of accuracy evaluation employed in this study indicate the reliability of the XGBoost model, with the mean absolute error of 0.31 m, mean squared error of 0.37 m, r-square of 0.85, and adjusted r-square of 0.84. The centenary reconstruction results reveal that the lake salinity underwent six-phase fluctuations with the water level and storage changes during 1920–2020, with the highest value of 1.87 g/L in 1987 and the lowest value of 1.19 g/L in 2002. During the past century, the water salinity and storage of Bosten Lake were influenced chiefly by vapor pressure and precipitation, followed by wet day frequency, daily mean temperature, and potential evapotranspiration. Moreover, the uncertainty of the machine learning model was also explored and discussed. It could be mainly associated with the data accuracy of input climate variables and the ignorance of environmental impacts from the intense agricultural activities after the 1960 s. This study is expected to advance the scientific understanding of long-term change characteristics of Bosten Lake and to provide a technical reference of reconstructing centenary hydrologic and environmental trajectory for dryland lakes. [ABSTRACT FROM AUTHOR]

• The rapid recovery of QHL water level is largely contributed in five anomalous years. • The abnormal water-level increases of QHL were closely related to precipitation. • The possible reason of anomalous precipitation over the QHL basin was explored. Qinghai Lake (QHL), the largest saline lake in China, is located in the Tibetan Plateau. The lake plays an important role in regional water and nutrient cycles and the sustenance of semi-arid ecosystem functions. Over the past half century, the lake experienced substantial changes in its water level in a seesaw pattern. In the first 35 years, the lake level presented a dramatic continual decrease of 2.63 m, then a reversed upward tendency appears beginning the early 21st century. The water level in the recent years has recovered to the stage from 50 years ago (around 1970). However, the driving factor causing the seesaw pattern changes remains to be unclearly understood. The goal of this study is to investigate the abnormal changes in the water level of the QHL from 1970 to 2018 and explore the primary contributor of the reversed shifts by taking the climate-driving view. Then, we discuss the possible atmospheric circulations that are tightly associated with the climate variables over the QHL catchment and its surroundings. Results show that the rapid water-level recovery of the QHL in recent years is attributable to the substantial increases in water levels in several key abnormal wet years of 2005, 2012, 2015, and 2017/2018. The lake level variations coincide with annual precipitation rather than temperature and evaporation. Besides, this study reveals that the atmospheric water vapor flux in the QHL basin is mainly transported from the west and southwest to the east. For the anomalous high-precipitation (wet) years, the total water vapor of the QHL basin increases significantly. The ENSO and other atmospheric circulation factors may be related to the precipitation variations that drive the water vapor transport of the QHL basin. [ABSTRACT FROM AUTHOR]