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The extent and mechanisms by which precipitation extremes affect hydrological processes in the critical zone (CZ) of loess possessing a thick unsaturated zone remains poorly understood. To this end, we here employed a coupled liquid‒vapor‒heat‒airflow STEMMUS (simultaneous transfer of energy, mass, and momentum in unsaturated soil) model to investigate the impact of extreme precipitation, at both event and annual scales, on CZ hydrological processes within a semiarid loess site vegetated by apple trees on China's Loess Plateau. At the event scale, the vapor flux was two orders of magnitude lower than the liquid water flux. However, the thermal vapor flux penetrated to depths of 200 cm, whereas the isothermal liquid water flux only infiltrated to 100 cm during the study period, implying that thermal‐gradient‐driven vapor transfer is an important mechanism for deep‐layer recharge (DLR). At the annual scale, the DLR below 200 cm during extremely wet years was 6.5 times larger than that during extremely dry years. In contrast, extreme changes in climate had only limited impacts on evapotranspiration; the difference between extremely wet and extremely dry years averaged only 35 mm, much less than the difference in precipitation, which averaged 310 mm. However, the extremely dry years showed a higher ratio (0.58) between transpiration and evapotranspiration than did the extremely wet years (0.51). The findings reported here improve our understanding of CZ hydrological processes related to precipitation extremes in semiarid loess regions. Key Points: Thermal‐gradient‐driven vapor transfer is an important mechanism for deep‐layer recharge (DLR) in loessThe DLR below 200 cm during extremely wet years was 6.5 times larger than that during extremely dry yearsExtreme changes in precipitation had only limited impacts on evapotranspiration [ABSTRACT FROM AUTHOR]

Afforestation to control soil erosion has been implemented throughout China over the past few decades. The long‐term hydrological effects, such as total water yield and baseflow, of this large‐scale anthropogenic activity remain unclear. Using six decades of hydrologic observations and remote sensing data, we explore the hydrological responses to forest expansion in four basins with contrasting climates across China. No significant change in runoff was found for the period 1970–2012 for the cold and dry Hailar River Basin in northeastern China. However, both forest expansion and reduced precipitation contributed to the runoff reduction after afforestation since the late 1990s. Similarly, afforestation and drying climate since the mid‐1990s induced a significant decrease in runoff for the Weihe River Basin in semi‐arid northwestern China. In contrast, the two wet basins in the humid southern China, Ganjiang River Basin and Dongjiang River Basin, showed insignificant changes in total runoff during their study periods. However, the baseflow in the winter dry seasons in these two watersheds significantly increased since the 1950s. Our results highlight the long‐term variable effects of forest expansion and local climatic variability on basin hydrology in different climatic regions. This study suggests that landuse change in the humid study watersheds did not cause dramatic change in river flow and that region‐specific afforestation policy should be considered to deal with forestation‐water quantity trade‐off. Conclusions from this study can help improve decision‐making for ecological restoration policies and water resource management in China and other countries where intensive afforestation efforts are taking place. Key Points: Both precipitation and afforestation explained reduction in runoff for dry basinsForest recovery did not result in significant changes in total runoff for two wet basinsDry season baseflow in two wet basins had an upward trend [ABSTRACT FROM AUTHOR]

China has experienced significant vegetation greening over recent decades. Vegetation greening may regulate the effective vegetation available water capacity (EVAWC), which determines the root zone water availability for evapotranspiration. EVAWC is one of the most important factors controlling vegetation growth and ecosystem resilience. Despite its importance, quantifying EVAWC at large scale is challenging due to limited observations of soil properties and insufficient understanding of underlying physical processes. Thus, to what extent changes in EVAWC are driven by vegetation and climate change is still unclear. Here, we establish a physics‐based, data‐driven stochastic approach to examine the spatiotemporal variability of the EVAWC and its potential drivers over China, with the consideration of vegetation and climate dynamics. The major strength of our approach is that it does not require observations related to soil properties as inputs, but only needs a few simple hydrometeorological and remotely sensed vegetation parameters that can be easily obtained. On average, we find that vegetation changes tend to increase EVAWC over 71.0 ± 3.9% of the total land area in China, while climate variabilities tend to reduce EVAWC over 73.7 ± 9.5% of the land area. More importantly, the potential increase in EVAWC resulting from vegetation changes is offset by climate variability. As a result, the changes in EVAWC over recent decades are generally dominated by climate variabilities (relative contribution of 82.7 ± 9.6%) rather than vegetation changes, especially in humid and semihumid areas. Our results suggest that vegetation greening in China has subordinate impacts on EVAWC, and ecosystem resilience is mainly dominated by the local climate. Key Points: A stochastic approach is developed to examine changes in effective vegetation available water capacity (EVAWC) over ChinaThis approach does not require observations related to soil properties as inputs, which are difficult to be obtained and have uncertaintiesChanges in EVAWC are dominated by climate variabilities (relative contribution 82.7 ± 9.6%) rather than vegetation changes [ABSTRACT FROM AUTHOR]

Climate elasticity of runoff is an important indicator for evaluating the effects of climate change on runoff. Consequently, this paper proposes an analytical derivation of climate elasticity. Based on the mean annual water-energy balance equation, two dimensionless numbers (the elasticities of runoff to precipitation and potential evaporation) were derived. Combining the first-order differential of the Penman equation, the elasticities of runoff to precipitation, net radiation, air temperature, wind speed, and relative humidity were derived to separate the contributions of different climatic variables. The case study was carried out in the Futuo River catchment in the Hai River basin, as well as in 89 catchments of the Hai River and the Yellow River basins of China. Based on the mean annual of climatic variables, the climate elasticity in the Futuo River basin was estimated as follows: precipitation elasticity ϵP} = 2.4$, net radiation elasticity ϵRn = - 0.8, air temperature elasticity ϵT} = -0.05°C-1 wind speed elasticity ϵU} = -0.3, and relative humidity elasticity ϵRH0.8. In this catchment, precipitation decrease was mainly responsible for runoff decline, and wind speed decline had the second greatest effect on runoff. In the 89 catchments of the Hai River and the Yellow River basins of China, climate elasticity was estimated as follows: ϵPranging from 1.6 to 3.9, ϵRn ranging from -1.9 to -0.3, ϵET ranging from -0.11 to -0.02°C-1, ϵU ranging from -0.8 to -0.1, and ϵRH ranging from 0.2 to 1.9. Additional analysis shows that climate elasticity was sensitive to catchment characteristics. [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]

Understanding whether a positive or negative correlation between actual ( E) and potential ( Ep) evaporation is of great importance in detecting changes of E from Ep. In this study, such correlation was evaluated via the linear regression slope ( k) between E and Ep derived from a nonlinear complementary relationship model. k varies with the relative degree of variability in the radiation term ( Erad) and aerodynamic term ( Eaero) of Ep, and is further affected by water availability. The sign of k is always positive under conditions with high Erad variability but at the same time with low Eaero variability (commonly true on an hourly basis). Under conditions with high Eaero variability but at the same time with low Erad variability, the sign of k tends to change from negative to positive with more readily water availability. On a daily or annual basis, the sign of k would be related with water availability. Under water-limited conditions, the Eaero variability is more significant than the Erad variability, and negative k is expected. Under energy-limited conditions, the Erad variability is compared to or even much obvious than the Eaero variability, and positive k is expected. This implies a negative correlation between E and Ep under water-limited conditions but a positive correlation under energy-limited conditions on the daily or annual basis. The above analysis is confirmed in a grassland site in Northeast China at daily and half-hourly time scales. The correlation between annual E and Ep over China was evaluated using data of 690 meteorological stations from 1956 to 2005. The k values change from negative in arid regions to positive in humid regions. According to k and the decreasing trends in annual Ep, it is deduced that E increased for most stations in arid regions but decreased for most stations in humid regions. [ABSTRACT FROM AUTHOR]