Understanding vegetation resilience, defined as the recovery speed of vegetation following external perturbations, is essential for predicting ecosystem stability under climate change, yet the role of lithosphere in mountain systems remains poorly understood. Here, we assess how lithology and tectonics modulate vegetation resilience across global mountains using integrated climate, soil, topography, human footprint, lithology, land-cover, and vegetation datasets. Vegetation type and temperature dominate global patterns, with resilience highest in trees, followed by herbs and shrubs, together explaining 86% of the spatial variability. After accounting for climatic and anthropogenic effects, resilience across vegetation types is strongly mediated by lithospheric pathways. Tree resilience peaks in steep, actively incising terrains underlain by erosion-resistant plutonic and metamorphic rocks, as well as dissolution-prone carbonate rocks. Herb resilience is strongly linked to soil organic carbon enriched on mafic and metamorphic rocks. Shrub resilience is primarily temperature-dependent (93%) but shows reduced warming sensitivity on nutrient-poor substrates. Moreover, resilience peaks at intermediate channel steepness (ksn ≈ 500), suggesting that moderate tectonic uplift promotes vegetation resilience. These findings identify the lithosphere as a fundamental modulator of mountain vegetation resilience and highlight geological constraints on ecosystem stability across heterogeneous landscapes.

Flash drought (FD) is a type of extreme events characterized by rapid intensification of drought/dryness conditions, severely affecting vegetation growth and agricultural production. However, how the spatiotemporal dynamic risk of FD will change under future climate warming remains unclear owing to the limitations in the identification methods of FD dynamic characteristics and large uncertainty in global climate model projections. Here, we propose a comprehensive framework for projecting spatiotemporal dynamic characteristics of FD under future climate change by coupling the CMIP6 multi-GCM ensembles, the Variable Infiltration Capacity model, and an extended three-dimensional (3D) FD identification method. Based on this framework, we assess the projected changes in 3D dynamic characteristics of FD in China under SSP126, SSP245 and SSP585 scenarios. Model projections indicate a significant influence of climate change on FD characteristics, but the effects on different FD characteristics vary significantly. Climate change is expected to exacerbate FD severity and intensity for almost 75.3% of the national total area in China under three SSP scenarios, and prolong FD duration by 4.2%similar to 9.7%, especially under the higher SSP scenarios. Moreover, the migration distance of long-duration (>2-month) FD events tends to extend over time under all SSP scenarios, leading to an expansion of FD impact area in China under SSP245 and SSP585 (<36.4%). However, climate change will not alter the overall migration direction of FD, mostly from the humid South China to the arid and semi-arid North China regions. Our results emphasize the great importance of understanding the climate warming impacts on FD from a multi-attribute perspective.

The historical and future spatiotemporal responses of terrestrial water storage (TWS), a crucial water cycle component, to climate warming are poorly understood due to the lack of globally observational TWS data and the high uncertainty of climate projection studies, especially in China with diverse climate types. This study develops a new framework for comprehensive TWS projection attribution by integrating the data from CMIP6 Global Climate Models (GCMs), Variable Infiltration Capability (VIC) hydrological model, machine learning algorithms, and hierarchical sensitivity analysis, based on which the spatiotemporal TWS changes in response to climate change in China are analyzed under the SSP1-2.6, SSP2-4.5, SSP5-8.5 scenarios. Climate warming is expected to intensify the water cycle in China, leading to an increase of 5.59 21.09 mm/10a in precipitation and 2.48 11.61 mm/10a in evapotranspiration during 2030–2099, respectively. The greater water cycle intensification rate is projected in some parts of western China, with precipitation and evapotranspiration respectively increasing by 50

Terrestrial water storage change (Delta S) is an important indicator of climate change that can monitor and predict hydrological changes. However, the interactions between Delta S and climate, vegetation, and soil factors add complexity in temporal variability of Delta S, particularly at seasonal scale. Here, we conduct a systematic assessment in the roles that seasonal variabilities of climate and vegetation modulate seasonal variability of Delta S in 769 basins covering a wide range of climate regimes and vegetation types globally. The variance decomposition method of Delta S based on the Budyko framework is used to estimate the contributions of climate factors (precipitation P and potential evapotranspiration PET) and runoff (R) to Delta S variability for different vegetation types. Results indicate that the increased climatic (P, PET) and R seasonal variabilities enhances Delta S seasonal variability under both in-phase (IP) and out-of-phase (OP) seasonal relations between P and PET, with a larger contribution from P than PET and R. However, the P-PET covariance tends to reduce (enhance) Delta S seasonal variability under the IP (OP) relation, while the P-R covariance tends to reduce Delta S variability for both IP and OP relations. Climate seasonality influencing Delta S is regulated through vegetation dynamics, mainly via extending plant roots to access deeper soil water under water stress or by seasonally adapting water use efficiency and primary production. The growth of seasonal vegetation under the IP P-PET relation can cope with limited soil water, while the growth of evergreen vegetation under OP P-PET relation depends on soil water availability throughout the year.

In the context of climate warming, compound dry-hot (CDH), dry-cold (CDC), wet-hot (CWH), and wet-cold (CWC) events have become increasingly frequent and widespread in recent decades, causing severe but disproportionate impacts on terrestrial vegetation. However, the understanding of how vegetation vulnerability responds to these compound climate events (CCEs) is still limited. Here, we developed a multivariate copula conditional probabilistic model integrating the Standardized Precipitation Index (SPI), Standardized Temperature Index (STI), and Normalized Difference Vegetation Index (NDVI) together to quantify the vegetation response to each of CDH, CDC, CWH and CWC events under diverse climates in mainland China. Results show that CDC has a greater likelihood of causing vegetation loss relative to other CCEs, with the probability of NDVI ≤ 40th being 4.8–13.0

This study advances the dynamic assessment of flash drought (FD) by extending the voxel-based three-dimensional FD (V3DFD) framework developed previously to improve tracking the FD trajectory and measuring the migration distance. We apply the extended V3DFD to evaluate the spatiotemporal evolutions of FD during 1980-2020 in three river basins in China: a semi-arid to semi-humid Yellow River Source basin (YRSB), a semi-humid to humid Huai River basin (HRB), and a humid Xijiang River basin (XRB). Our results indicate that the extended V3DFD method can effectively capture the entire lifecycle and migration patterns of FD. The humid XRB is prone to severe FD events, characterized by long migration distances and durations, large spatial coverage, and mainly starting in August and October and ending in November. In contrast, FD events in arid basins have shorter duration and migration distance, lower severity, smaller affected area, but higher frequency, with most events occurring in the first half of the year. Precipitation deficit is responsible for early FD development in all basins. The FD development in YRSB is typically accompanied with large evaporation caused by strong wind, while that in HRB mainly attributed to high temperature. Low relative humidity has a more significant impact on FD in wetter basins, leading to higher evaporative demand dominating FD development in XRB. It is also found that shallow soils in XRB accelerate SM depletion, while prolonged snowmelt in YRSB increases FD sensitivity to runoff partitioning parameters, highlighting the role of climate-hydrology interactions in modulating FD dynamics.

Compound Dry-Hot (CDH) events, the simultaneous occurrence of drought and high temperature events, have become more frequent under recent global warming, posing a serious threat to terrestrial vegetation. However, the role of anthropogenic climate change (ACC) signals in the characteristics of CDH events, and its consequence to vegetation vulnerability, are still poorly understood. Based on the meteorological data and simulated Leaf Area Index (LAI) data from four CMIP6 models under the "natural-only" (NAT) and "natural and anthropogenic" (ALL) experiments, this study investigates the ACC impacts on historical (1982-2014) occurrence of CDH (with different intensities and durations) and quantifies the anthropogenic signals in vegetation vulnerability by using the Fraction of Attributable Risk method. The results show that ACC not only increases the frequency and duration of CDH over most global regions, also simultaneously causes a globally widespread increase in vegetation resistance to CDH (particularly in the Southern Hemisphere), which reduces the probability of vegetation loss (defined as LAI <= 40th percentile) by 7.2 similar to 19.6 % on global average. Moreover, vegetation resistance generally increases with CDH intensity globally, mainly due to the expanded vegetation coverage and the alleviation of high-temperature inhibitory effects on vegetation growth. We also find that ACC increases the vulnerability of Tundra and Taiga to CDH only in northern high-latitudes due to the decreased vegetation coverage, but enhances the grassland resistance to CDH to a lesser extent than forests due to the greater physiological burden brought by CDH to grasslands than to forests. These findings suggest that climate adaptation strategies should prioritize vegetation protection in high-latitudes and promote drought- and heat-resilient vegetation types in grassland and semi-arid regions in order to enhance ecosystem stability under future CDH extremes.

Terrestrial evaporation (ET) estimates from the water balance framework and large-scale modeling have been widely used in the evaluation and prediction of hydrological regimes. However, each method has its inherent limitations, including the external bias introduced by forcing variables, simplified functional relationships, and unconsidered human modules. A systematic comparison between water balance ET and modeled ET remains unexplored. Here, we quantify and attribute the difference between water balance estimations of ET and modelsimulated ET (i.e., DET) on a global scale. We apply an unprecedentedly unique probabilistic ensemble of 84,042 DET estimates (2002-2021) based on all currently available datasets on water balance components. Satisfactory performance is found from the validation of the water balance-derived ET against several benchmarking ET products. We identify the regions with significantly positive DET in South and East Asia, Southern and Northern Africa, and southwestern parts of North America, with a global mean of 7 mm/a (5 % spread range: -2 to 16 mm/ a). The patterns are primarily contributed by human water use and reservoir construction. We also report negative DET in the majority of South America, which may be related to human-induced deforestation. In addition, the seasonality of DET reflects the significant role of irrigation in regional ET dynamics. Variance analysis indicates higher uncertainties of DET in humid zones, mainly contributed by precipitation and simulated ET. Our uncertainty-constrained DET estimates have potential implications for assessing global and regional water availability, benchmarking climate and hydrological models, and developing sustainable mitigation and adaptation strategies.

Groundwater storage anomaly (GWSA) can be estimated either at the large scale from the Gravity Recovery and Climate Experiment (GRACE) or at the local scale based on in situ observed groundwater level (GWL) and aquifer storage parameters. Yet, the accuracy of GRACE-based estimate is affected by leakage errors, while that of local GWL-based estimate requires the reliable specific yield (Sy) data that are usually not available. Here, we developed a novel approach, the coordinated forward modeling (CoFM), based on the iterative forward modeling to improve GWSA estimation at the sub-regional scale smaller than the typical GRACE footprint. It is achieved by solving Sy through iterative comparisons between GRACE-based and observation-based GWSA at 0.5 degrees grid scale, and then re-calculating GWSA using the updated Sy and observed GWL. The utility of CoFM is explored by using the hypothetical experiments and a real case study in the Piedmont Plain (PP, similar to 54,000 km2) and East-central Plain (ECP, similar to 86,000 km2) of North China Plain. Results show that CoFM can detect GWSA at 0.5 degrees grid scale in the hypothetical experiments given the large spatial variability of GWL. While in the real case study, the CoFM distinguishes between the divergent unconfined GWSA trends (2005-2016) in PP (-41.80 +/- 0.55 mm/yr) and ECP (-7.57 +/- 0.60 mm/yr) caused by the differences in hydrogeological conditions and groundwater use. The improvement made by CoFM can be attributed to the use of the distributed GWL information to constrain GRACE leakage errors. This study highlights a practical important solution for improving sub-regional GWSA estimation through the joint use of large-scale GRACE data and local-scale well observations. A coordinated forward modeling (CoFM) is developed to utilize in situ groundwater level to constrain Gravity Recovery and Climate Experiment leakage errors CoFM enables the estimation of sub-regional groundwater storage variations without requiring reliable specific yield data CoFM estimates groundwater depletion rate in the piedmont unconfined aquifers of North China Plain (NCP) is similar to 6 times of that in the east-central area of NCP

The Huaihe River basin (HRB) of China located in the climate transition zone between warm temperate and subtropical areas is highly sensitive to climatic change. However, the changes in future climate extreme events under anthropogenic warming and the population exposure to these climate extremes in HRB remain unexplored. Here, using the eight commonly used extreme climate indices and based on the bias-corrections of 16 global climate models (GCMs) in CMIP6, we present a projection and uncertainty analysis of extreme events and investigate the corresponding population exposure risk in HRB under three shared socioeconomic pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5). The 16-GCM ensemble mean projects an evident warming trend under all three scenarios with a total increase of 25.6-68.0 days in summer days (>25 degrees C) by the end of the century in HRB. Larger increases (decreases) in maximum and minimum temperatures (frost days) are projected in the western HRB. Very heavy rain days (R20mm), maximum 5-day precipitation (RX5day) and simple daily intensity index (SDII) will experience intensification across most of HRB (especially in southern and western HRB). The consecutive dry days is projected to decrease in northwestern HRB and increase in southern HRB. However, there is a large spatial variability in GCM uncertainty with a higher SSP scenario generally having higher uncertainty. Increases in summer days and R20mm exacerbate population exposure in HRB in near future (2030-2059), but in far future (2070-2099) although summer days (R20mm) continues to rise, population exposure is expected to decrease due to the rapid decline in population density.

Water availability needs to be accurately assessed to understand and effectively manage hydrologic environments. However, the estimation of evapotranspiration ( ET ) is prone to errors due to the complex interactions that occur between the atmosphere, the Earth ' s surface, and vegetation cover. This paper proposes a novel approach for analyzing the sources of inaccuracy in estimating the annual ET using the Budyko framework (BF), particularly temporal variability in precipitation ( P ), potential evapotranspiration ( E P ), runoff ( R ), and the change in soil storage ( & Aring; S ). Error decomposition is employed to determine the individual contributions of P , R , E P , and & Aring; S to the ET error variance at 12 locations in the state of Illinois using a dataset covering a 22 -year period. To the best of our knowledge, this study represents the first BF-based investigation that considers R in the error decomposition of the predicted ET variance. The ET error variance increases with the variance in the P and R in Illinois and decreases with the covariance between these two variables. In addition, when accounting for & Aring; S in the BF, the scenario in which & Aring; S affects the total available water (i.e., P ) is reliable, with a low prediction error and a 13.87 % lower root mean square error compared with the scenario in which the effect of & Aring; S is negligible. We thus recommend the inclusion of & Aring; S and R as key variables in the BF to improve water budget estimations.

The Budyko models (BM) have been extended in previous studies by incorporating water storage change (Delta S) (subtracting Delta S from precipitation) to estimate evapotranspiration (ET) under non-steady state conditions at scales finer than the climatological mean scale. However, a systematic assessment of the interannual ET predictability of the extended BM is still lacking, hence its validity and controlling factors of improvement (over the original BM) under globally diverse climates is not yet well understood. Based on a long-term (1984-2008) gridded water budget data set, we present a comparative analysis of annual ET predictability between the original BM (ET1) and the extended BM considering Delta S (ET2) in 32 global river basins to explore the sensitivity of climate factors and catchment hydrologic responses in determining ET predictability. Results show that the difference between ET1 and ET2 increases linearly with Delta S, with ET2 < ET1 (ET2 > ET1) when Delta S > 0 (Delta S < 0). When both ET1 and ET2 overestimate (underestimate) observed ET, the error in ET2 is smaller than ET1 when Delta S > 0 (Delta S < 0) for all 32 basins considered. When the error signs of ET2 and ET1 differ, however, the difference in the absolute magnitude of ET2 and ET1 errors (REdiff) under extremely humid climates is determined by the difference between potential ET and ET, leading to comparable accuracy between ET2 and ET1. In contrast, under extremely arid climates, REdiff is controlled by the combined influences of Delta S and R, resulting in more accurate ET2 than ET1 under the condition of the in-phase, positive-correlated relationship between Delta S and R.

To compensate for the intrinsic coarse spatial resolution of groundwater storage (GWS) anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) satellites and make better use of current dense in situ groundwater-level data in some regions, a new statistical downscaling method was proposed to derive high-resolution GRACE GWS changes. A ground-based scaling factor (SFGB) method was proposed to downscale GRACE GWS changes that were corrected using gridded scaling factors estimated from ground-based GWS changes through forward modeling. The proposed method was applied in the North China Plain (NCP), where many observation wells and consistently measured specific yield are available. Importantly, the sensitivity of the proposed method was explored considering the uncertainties of in situ GWS changes due to variable specific yield and/or number of observation wells. Independent validation shows that SFGB can effectively recover GRACE GWSA at the 0.5º grid scale (r = 0.81, root mean square error = 40.51 mm/yr). The SFGB-corrected GWSA in the NCP was -32.60{plus minus}0.99 mm/yr (-4.6{plus minus}0.14 km3/yr) during 2004-2015, showing contrasting GWS trends in the piedmont west (loss) and the coastal east (gains). Uncertainties in SFGB-corrected GWSA arising from specific yield, groundwater-level, and both can be reduced by 90%, 65%, and 84%, respectively relative to ground-based GWSA. This study highlights the potential value of jointly using GRACE and in situ observation data to improve the accuracy of GRACE-derived GWSA at smaller scales. The new downscaling method and the improved groundwater storage change estimates would facilitate better groundwater management.

High arsenic (As) groundwater is a global problem primarily originating from As-enriched sediments. The provenance (source) and release mechanisms (sinks) of high As sediment have been identified, but the source-sink transfer is poorly understood, especially the influence of geological and surface processes. In this study, we explore the roles of tectonic movement and Yellow River evolution in provenance formation processes and evaluate the combined effects of provenance and sediment age on the As content of aquifer sediments in the northern Hetao Basin of Inner Mongolia. Based on optically stimulated luminescence (OSL) and 14C dating and detrital zircon U-Pb, As content, and lithological analyses of a 400 m core, we reconstructed As changes over the last 160 ka. Our results show clay deposited in a paleo-lake during the Gonghe movement period in the late Pleistocene (∼100 ka B.P.) is enriched in As (31.8 μg/g) due to significant provenance contributions of the As-bearing Langshan Group under tectonic uplift and mountain erosion. In contrast, clay deposited in the middle Pleistocene (∼160 ka B.P.) has lower As content (7.3 μg/g) due to the Yellow River as the primary provenance. Accordingly, the provenance of basin As forced by tectonic uplift and Yellow River evolution determines the background As of aquifer sediments. After deposition, sediment As content decays over time, with higher decay rates in coarse-grained sands than fine-grained. Overall, both provenance formation and sediment age, representing initial and dynamic states of solid phase As, jointly determine the As content of aquifer sediments. More solid phase As provided by younger sediments from the proximal orogenic provenance and reducing conditions due to frequent river–lake transitions, jointly lead to higher As concentrations in shallow groundwater. The study highlights the potential for using a combined analysis of the tectonic movement-surface processes-environment system to improve understanding of geogenic high As groundwater over global large sedimentary basins in the proximity of young orogenic belts.

The successive runoff-heat extreme (SRHE) events, defined as the occurrence of an extreme runoff event followed by a heatwave event, have become more frequent under recent global warming. However, the impact of anthropogenic climate change (ACC) on global changes in SRHE characteristics during the past decades remains unclear. Here, we evaluate the impact of ACC on SRHE frequency and characteristics during 1950-2014, based on the daily maximum and minimum temperature and total runoff data simulated by five global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under the "anthropogenic and natural both (ALL)" and "natural only (NAT)" experiments. Attribution of SRHE changes with different durations and intervals between extreme runoff and heatwave (IRHs) is achieved by using the fraction attributable risk (FAR) method. Results indicate that ACC exacerbates SRHE occurrence for most global regions, especially in the Southern Hemisphere (> 60 % increase in probability), but the spatial variability of this impact decreases over time. The globally-average probability of SRHE occurrence due to ACC has increased significantly by 40 % during 1971-2014 (similar to 10 %/decade), and the probability of SRHE with the short IRHs and long duration tends to be larger than other types of SRHE. ACC also prolongs the duration of SRHE in most global regions, with an increase of 1-4.5 folds in northern South America, central Africa, and southeastern Asia during 1950-2014. Partial correlation analysis indicates that the intensification of heatwave due to ACC contributes more than that of extreme runoff to SRHE occurrence in nearly all global regions, particularly in the Southern Hemisphere.

Identifying dominant water stress on vegetation growth over the arid basins is essential to better understand ecosystems and water interactions, which are fundamental in managing regional water resources. The Kongqi River basin is an ecologically sensitive area with limited water resources in the northern part of Tarim Basin in northwest China. How is the spatial distribution of vegetation controlled by natural conditions and anthropogenic regulation of water resources is a concern for ecology system protection. This study explores the spatio-temporal variations in the remote-sensing vegetation index across the basin and identifies water stress forces with the Mann-Kendall trend test and linear regression analysis. Results show that the controls of vegetation change are different among geomorphological units over the past 20 years. In the northern mountains, the increasing vegetation trend mainly responds to climate change, particularly to increased precipitation. In contrast, in the plain area, the vegetation change is controlled by changes in hydrologic and anthropogenic water stresses. A significant rise in surface water and groundwater utilization counteracts the negative effect of the increasing hydrologic water stress in the upstream oasis. However, the increasing anthropogenic water stress contributed to more than 50% of vegetation decay in the downstream area during 2004-2015. The ecological water conveyance beginning in 2016 has promoted vegetation restoration, but the effect decreased with distance to the upstream area and showed a delay in response. This study provides evidence for ecological consequence of anthropogenic water stress that is beneficial to improve water resources management and ecosystem restoration.

A new approach combining groundwater storage change (GWSC) derived from Gravity Recovery and Climate Experiment (GRACE) satellite data and baseflow was proposed to estimate groundwater recharge at large spatial scales but a short (monthly) time scale. This method was applied in two typical karst basins of southwest China, the Wujiang River basin (WRB, ∼87,900 km 2 , ∼70% karstification) and Xijiang River Basin (XRB, ∼360,000 km 2 , ∼44% karstification). The 2006–2012 monthly baseflow was first separated from in situ streamflow through multivariate regression analysis. Groundwater recharge was estimated using separated baseflow and GWSC estimated from GRACE data and observation‐based groundwater‐level data. The comparison between GRACE‐ and observation‐based recharge in the larger XRB shows better consistency, while that in the smaller WRB shows larger discrepancies. Considering the associated uncertainty (60–93 mm/yr), the 2006–2012 mean recharge in two basins, ranging 199–225 mm/yr (17%–19% of precipitation) is comparable to bulletin‐reported estimates (∼145 mm/yr). Both the degree of karstification and aquifer water table depth influence recharge and discharge processes in karst areas of southwest China. The more karstic WRB exhibits more rapid infiltration (due to more developed permeable epikarst zone) and higher discharge capability (due to more developed underground drainage systems), particularly during dry periods (2009, 2011, and winter). Baseflow exhibits a shorter time lag to recharge and GWSC in the XRB than WRB owing to more quick flow, lower storage with more rapid infiltration, and shorter mean groundwater residence time. Observation‐based monthly recharge reflects different rainfall‐infiltration‐runoff processes under different rainfall intensities, particularly in the WRB.

Compound flood-heat extreme (CFHE) is a successive flood and heatwave event that threatens human health, agriculture, economy, and building environment security that has attracted extensive research attention recently. However, the characteristics of global CFHE occurrence under climate warming remain unclear given the large uncertainties in climate change projections. This study presents a global-scale evaluation of the projected changes and model spreads in CFHE characteristics within the ISIMIP 2b framework based on the multi-model ensemble of 20 members (5 global water models forced by 4 global climate models) under RCP2.6 and RCP6.0. The results reveal that CFHE frequency is projected to increase nearly globally especially in tropical (e.g., north South America, central Africa, and southeast Asia) and some temperate (e.g., eastern Asia) regions. The higher projected CFHE frequency is generally accompanied by larger model uncertainty. Over most global land areas, the interval between flood and heatwave in CFHE tends to decrease (by up to 3 days) under both RCPs, implying more intermittent CFHE occurrence under future warming. The sensitivity of CFHE land exposure to climate warming is higher than that of floods and heatwaves, particularly under RCP6.0. Relative to the 1970-1999 baseline period, the CFHE land exposure is expected to increase by 10% (20%) by the end of this century under RCP2.6 (RCP6.0). Partial correlation analysis suggests that the increased flood frequency contributes more to the increased CFHE frequency than the increased heatwave frequency. Moreover, the relative contribution of flood frequency to CFHE frequency increases with the decrease of latitude in the northern hemisphere.

Exploration of paleo-lake evolution is crucial for the understanding of climatic and tectonic roles in earth surface. Previous studies mainly focused on the climatic effect on river-lake transitions and lake evolutions through lacustrine deposits, but with limited consideration of tectonic drivers, especially for the tectonic rift lakes in the Hetao area. Based on the analyses of lacustrine and fluvial piedmont terraces and a 400-m core from the northern Hetao Basin, along with the optically stimulated luminescence and detrital zircon U-Pb dating, we adopted an integrated "tectonics-climate-surface processes" approach to explore the climatic and tectonic effects on the lake evolution of the Hetao rift basin. Results show that lacustrine deposition on the piedmont terrace T1 (60-47 ka), underlying the T3 fluvial (80-60 ka), has an erosion contact with pluvial deposits at 55 ka, implying the paleolake formation at - 80-60 ka and shrinkage at - 55-47 ka. Lake formation was forced by basin depression under the tensile stress of tectonic movement, and was recharged by the Yellow River due to obstruction of the outlet at Tuoketuo caused by uplift. Lake shrinkage was due to the combined effect of basin lifting and warm-wet climate conditions that promoted outflow. A substantial decrease in the erosion base level and rapid water drainage induced by river cutting caused erosion of lacustrine deposits in the basin. The limited sedimentary space of the lake basin in early MIS 2 should be considered a factor in lake disappearance in addition to the dry climate. This study highlights that tectonic effects may be more important than climatic effects in the evolution of rift lakes near the young fold mountain belts.

Study Region: Yangtze River basin Study Focus: To improve the potential of the Gravity Recovery and Climate Experiment (GRACE) mission for estimating terrestrial water storage variations (ATWS) in smaller basins than its typical footprints (150,000 - 200,000 km2), an improved method named the Multi-Lagrange multiplier method (MLMM) is proposed to decrease leakage errors and restore signals from an independent hydrologic model. The MLMM is applied to estimate ATWS in the Yangtze River basin (YRB) and eleven of its sub-basins, and is assessed from different GRACE solutions and ground-based precipitation (P), evapotranspiration (ET), and runoff (R). Results indicate that MLMM estimates the leakage correction satisfactorily for small sub-basins. In the Tai Lake basin, the leakage ratio is improved by 16%. Excluding the Han River basin, ATWS from MLMM over the YRB are the best among different tested methods with a Nash-Sutcliffe Efficiency larger than 0.80, and the best root means square error (1.34 cm). New Hydrological Insights for the Region: The main contributor to ATWS over the YRB is P with 60%. The contribution of ET to ATWS is more extensive than that of R over the middle of YRB. The ATWS and the total groundwater and surface water were all increasing over the YRB and eleven of its sub-basins. This paper concludes that the proposed MLMM is helpful for ATWS estimation in the small ungauged basins.