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.

Long-term continuous monitoring of precipitation isotopes has great potential to advance our understanding of hydrometeorological processes that determine stable isotope variability in the monsoon regions. This study presents 4-yr daily precipitation isotopes from Yungui Plateau in southwestern China that are influenced by Indian summer monsoon and East Asian monsoon. The local meteoric water line (LMWL; δ²H = 8.12δ¹⁸O + 11.2) was first established at the Tengchong (TC) site, which was close to the global meteoric water line (GMWL; δ²H = 8δ¹⁸O + 10), indicating little secondary subcloud evaporation in the falling rain. Precipitation δ¹⁸O values exhibited significant inverse relationships with precipitation amount (r = −0.42), air temperature (r = −0.43), and relative humidity (r = −0.41) with lower correlation coefficients throughout the entire period, which indicated that precipitation isotopic variability in TC could not be well explained by the local meteorological factors but influenced by other combined factors of regional precipitation amount and upstream rainout. Precipitation δ¹⁸O values showed a clear V-shaped trend throughout the observation period, characterized by higher δ¹⁸O values during the premonsoon period whereas lower values during the postmonsoon period. This seasonal variation of precipitation δ¹⁸O values was associated with the seasonal movement of the intertropical convergence zone and seasonal changes in moisture transport. Combined with backward trajectory analysis, precipitation δ¹⁸O values were estimated by a Rayleigh distillation model showing that upstream rainout processes from the Bay of Bengal (BoB) toward land (Myanmar) and recycling moisture over land were key factors affecting the isotopic compositions of the TC precipitation. These findings could enhance our understanding of atmospheric dynamics and moisture source in the monsoon regions and will potentially facilitate the interpretation of numerous isotopic proxy records from this region. SIGNIFICANCE STATEMENT: The variability of the summer monsoon and its onset, duration, and failure directly determine the strong rainfall and drought in a given region and have great impacts on regional societies and agriculture. To better understand this variability, this study presented a 4-yr daily dataset of precipitation isotopes on the Yungui Plateau of southwestern China to explore atmospheric processes and moisture sources that drive isotopic variability in this region. Precipitation δ¹⁸O exhibited remarkably seasonal variability, with higher values in premonsoon period and lower values in the postmonsoon period. During the Indian summer monsoon period, moisture sources primarily originated from the BoB toward the TC site, experiencing rainout processes and local moisture recycling over land using a Rayleigh fractionation model. These findings shed new light on the temporal variations of precipitation stable isotopes and facilitate our understanding of hydrological cycle in the monsoon regions.

Indirect nitrous oxide (N₂O) emissions from drainage ditches and headwater streams are poorly constrained. Few studies have monitored stream N₂O emissions and fewer modeling studies have been conducted to simulate stream N₂O emissions. In this study, we developed direct and indirect N₂O emission modules and a corresponding calibration module for use in the Soil and Water Assessment Tool (SWAT) model, and implemented the expanded SWAT model (termed SWAT‐N₂O) to a representative fourth‐stream‐order catchment (210 km²) and six first‐order stream catchments (0.22–1.83 km²) in southeastern Minnesota. We simulated the spatial and temporal fluctuations of the indirect emissions from streams, identified emission “hot spots” and “hot moments,” and diagnosed the correlations between direct and indirect emissions. We showed that zero‐order streams and first‐order streams could contribute 0.034–0.066 and 0.011 nmol N₂O m⁻² s⁻¹ (expressed on the basis of unit catchment area) to the total surface emissions, respectively. Emissions from zero‐order and first‐order streams equal 24–41% of direct emissions from soil, which may explain the emission gap between calculations using top‐down and bottom‐up methods. Clear spatial patterns were identified for both direct and indirect emissions and their spatial variations were negatively correlated. Our results suggest that the IPCC N₂O emission factor for streams in the Corn Belt should be increased by 3.2–5.7 times. Increasing precipitation and streamflow in the Corn Belt may potentially increase frequencies of soil anoxic conditions and nitrate leaching to streams, and subsequently increase N₂O emissions from both soils and streams.