Floodplain methane (CH4) emissions represent a significant component of the global CH4 budget. However, their response to escalating extreme drought events remains poorly understood, mainly due to high temporal variability under alternating wet-dry conditions. To address this gap, we conducted two years of in-situ CH4 flux measurements using the chamber technique across alternating hydrological cycles (2022-2023) in the Poyang Lake floodplain, during which the region experienced a prolonged drought. Our results showed that CH4 emissions during non-flooding periods (1.82 f 1.36 mg CH4 m-2 h-1) (mean f standard deviation) were significantly higher than those during flooding periods (1.26 f 0.96 mg CH4 m-2 h-1). Notably, CH4 fluxes in the autumn growing period (2.04 f 1.43 mg CH4 m-2 h-1) were 35 % higher than in the spring (1.51 f 1.21 mg CH4 m-2 h-1) under drought conditions. Further analysis revealed that, apart from air temperature, CH4 fluxes were primarily regulated by vegetation during non-flooding periods and by fluctuating water levels and flooding duration that influence biogeochemical processes during flooding periods. The enhanced temperature sensitivity of CH4 emissions emerged as a key factor for the higher autumn emissions compared to spring, which is directly linked to the shortened flooding period in the Poyang Lake floodplain. These findings underscore the critical role of extreme drought in reshaping hydrological conditions and CH4 emissions in floodplain wetlands, with important implications for predicting wetland responses under future climate change scenarios.

The Qilian Mountains are a crucial ecological security barrier in arid northwestern China, yet the coupled response of ecosystem services (ESs) to compound extreme climate events remains poorly quantified. Four ESs (habitat quality, water yield, soil retention, and water conservation) were quantified using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and coupled with pixel-scale extreme climate indices from 2000 to 2023. Regionally, ESs remained stable but varied locally. Habitat quality remained relatively stable, while water yield and water conservation declined after 2008. By 2023, water yield, water conservation, and soil retention decreased to 511.81 mm, 315.35 mm, and 1521.81 t/ha, respectively. The Trend-Free Pre-Whitening Mann-Kendall (TFPW-MK) test and the spatial Gini coefficient showed that extreme precipitation exhibited stronger intensification and spatial clustering than extreme temperature. Optimal geodetector and ridge regression multimodel framework indicated that ES changes were primarily driven by precipitation frequency and intensity. A framework combining Peaks Over Threshold, the Generalized Pareto Distribution, and a trivariate vine copula identified three joint risk types: high water yield with low soil retention, high water yield with low water conservation, and low water conservation with low soil retention. Under compound triggers of annual maximum 1 day precipitation (Rx1day) > 30.31 mm and days with precipitation >= 20 mm (R20) > 2.47 d, high-risk areas constituted 0.7%, 0.6%, and 3.1%, respectively. Medium-risk zones were significantly enriched in shrublands and forests (enrichment indices: 1.96 and 1.36). Hazard-Exposure-Vulnerability (H-E-V) zoning delineated eight priority areas and a high-risk corridor across Minle, Shandan, Qilian, and Sunan, encompassing over 40% of all high-risk zones. These findings provide a transferable framework for linking climate triggers to ecosystem service risk zoning and support risk-informed, zoning-based management in cold arid mountain ecosystems.

Abstract The carbon budget of floodplain lakes is regulated by natural hydrological processes, yet the role of human interventions, including cascade river‐lake hydraulic projects, remains unclear. We evaluated the combined effects of the Three Gorges Dam (TGD) located on the Yangtze River and the proposed lake‐specific hydraulic projects (LHPs) on the carbon budgets of the respective Dongting and Poyang Lakes downstream of the TGD. As a result of TGD's operation, Dongting Lake saw a weakened carbon sink, with carbon dioxide (CO2) uptake reduced by 6% and methane (CH4) emissions increasing by 4%. The opposite is true for the downstream Poyang Lake, with CO2 uptake increasing by 8% and CH4 emissions decreasing by 1%. This divergence stems from the lake‐specific vegetation composition and TGD's regulation strategy. The Phragmites in Dongting Lake is sensitive to hydrological regulation during the pre‐flooding seasons, while the Carex in Poyang Lake is sensitive to hydrological regulation during the post‐flooding seasons. In contrast, the operation of LHPs will uniformly reduce the carbon sink due to elevated lake water levels, leading to a sharp decline in CO2 uptake in Poyang Lake (36.98 gC m−2 yr−1) and Dongting Lake (11.87 gC m−2 yr−1). A cascade operation of these projects will increase the global warming potential (GWP) by 0.88 Tg CO2eq yr−1. Our findings underscore the necessity of integrating ecological consequences into water resources management to reconcile water security with climate stability goals.

Climate warming is driving an increase in the frequency and intensity of heatwaves. However, such extreme events are mostly studied based on air temperature that does not fully capture thermal stress on Earth’s surface layer. Here we explored the evolution of global heatwaves from near-surface air, land surface, to subsurface soils worldwide during 1980–2024. Results show heatwaves have strengthened across all layers, with a pronounced acceleration since the early 21st century. Relative to air and land surface, soils generally exhibit a greater heatwave exposure and severity. The peak intensity weakens as depth increases, with inter-layer differences closely linked to soil moisture, clay, and organic carbon content. The northern high latitudes are more prone to events of greater severity, particularly during summer, while lower latitudes and the Southern Hemisphere are characterized by events of greater persistence. Forests tend to buffer heat extremes, whereas non-forest land covers readily amplify heat exposure. Our findings imply that reliance on air temperature alone might underestimate heatwave risks to soil ecosystems, and soil temperature should be incorporated into monitoring and early-warning systems.

Water Resource Carrying Capacity (WRCC) is a crucial measure for assessing the balance between regional water availability, socioeconomic development, and ecological needs, especially in arid and semi-arid regions. This study evaluates the spatiotemporal evolution of WRCC across 14 prefecture-level units in Gansu Province, China, from 2000 to 2023. A multi-dimensional evaluation system comprising 29 indicators across water resources, ecological environment, economy, society, and coordination subsystems was established. The Entropy Weight Method was applied to determine indicator weights and calculate a comprehensive index (CI) to quantify carrying pressure. A Random Forest model identified dominant influencing factors, and an autoregressive integrated moving average model projected trends from 2024 to 2028. The results show the provincial mean CI increased from 0.49 to 0.91, indicating intensifying pressure and a shift toward mild overload. Spatially, pressure exhibits a stable west-east gradient, with the highest levels persistently in western prefectures like Jiuquan, Jinchang, and Baiyin. In contrast, Gannan and Longnan in the south maintain lower pressure but show high interannual variability, indicating ecological sensitivity. The Random Forest model demonstrated strong performance, with training R2 values exceeding 0.88 across all regions and mean absolute error mostly below 0.10. Projections suggest continued high pressure from 2024 to 2028 in the west, while central and southern regions show stable or slightly decreasing trends. These findings provide a quantitative basis for establishing differentiated, zoned water resource management and sustainable demand-side regulation strategies in water-limited regions.

The sustainability of water resource systems in arid regions plays a pivotal role in regional ecological security and socio-economic development. A scientific elucidation of their state evolution provides a critical foundation for water resources management decision-making. To address the assessment bias inherent in traditional static fuzzy comprehensive evaluation, which arises from the difficulty of fixed weights in effectively characterizing interannual variations in indicators and the impacts of extreme climate events, this study proposes an innovative fuzzy comprehensive evaluation model based on threshold-directed dynamic reward-penalty weighting. Using the Shule River Basin in northwestern China (2005–2023) as a case study, a threshold-based indicator system comprising five subsystems and 30 indicators was established. Initial indicator weights were determined via the entropy weight method, and a dynamic reward-penalty weighting function was constructed to enable real-time weight adaptation to system states. This dynamically adjusted framework was integrated with the fuzzy comprehensive evaluation method for system scoring, followed by a comparative analysis against conventional static fuzzy comprehensive evaluation results. Key results demonstrate that: (1) The threshold-directed dynamic reward-penalty mechanism significantly enhanced weight adaptability. For instance, a sharp 71.1 percent decline in precipitation in 2020 triggered a 33.2 percent increase in the dynamic weight of this indicator compared to its entropy weight. Conversely, in the same year, the ecological-environmental water use ratio exceeding its threshold by 27 percent resulted in a 52.9 percent reduction in its dynamic weight, thereby precisely quantifying the temporal effects of drought impact and policy intervention. (2) Subsystem scores exhibited dynamic differentiation: The socioeconomic water use subsystem exhibited the highest mean score, while significant interannual fluctuations were observed in the agricultural water use and food security subsystem and the ecosystem health and sustainability subsystem, collectively revealing the stability of regional water use structure and the heightened sensitivity of ecological and agricultural systems to climate fluctuations. (3) The basin's comprehensive water resources system score evolved through three distinct phases: a slow ascent phase (2005–2008), a fluctuating rise phase (2009–2017), and a high-quality development phase (2018–2023). This trajectory confirms the presence of a compound regulatory mechanism within the Shule River Basin's water resources system, characterized by "ecological hysteresis, policy-driven interventions, and technical compensation". This study establishes a novel dynamic analytical framework for assessing arid region water resource systems, substantiated the methodological advantage of this dynamic weighting approach in the non-stationary environments typical of arid zones.

Studying the temporal and spatial variations of potential evapotranspiration (ET0) in the Hexi Corridor region and its response to climatic factors is of great significance for improving the utilization efficiency of agricultural water resources. The temporal and spatial characteristics of ET0 and the six meteorological factors influencing the variation of ET0 in the FAO P-M formula during 1960-2019 have been revealed based on the statistical analysis method and the spatial interpolation method. Qualitative methods such as principal component analysis, cluster analysis, and grey relational grade were organically combined with quantitative methods such as sensitivity analysis and contribution rate calculation to comprehensively and objectively reveal the response relationship of ET0 to climate factors. The results showed that ET0 in the Hexi corridor showed a fluctuating increase during the period 1960-2019, and the change points were 1969 and 2002, respectively. ET0 increased from the southeast to the northwest, with a range from 812.3 to 1516.6 mm. Temperature factors such as Rn, Tmean, Tmax, and Tmin, change closely with ET0, followed by humidity and wind speed factors. The increase in ET0 is the most sensitive to the decrease in Rn, followed by the decrease in u2 and the increase in Tmean. Increasing Tmean was the main reason for increasing ET0, followed by u2 and Rn, and the combined contribution of the six meteorological factors was 72.39% during 1960-2019. This study has revealed the response of ET0 to climate factors, providing a scientific reference for more rational planning and efficient utilization of water resources in arid and semi-arid regions.

Landscape patterns of land use serve as critical mediators of air pollution source convergence and directly shape the spatiotemporal distribution of population-weighted air pollutant concentration (PWP). However, the differential effects of anthropogenic (impervious surfaces) and natural (barren land) source landscapes on population-weighted exposure to multiple pollutants remain insufficiently quantified. Here, we calculated population-weighted exposure to PM2.5, PM10 and O3 for 337 prefecture-level cities in China from 2008 to 2023 and used random forest (RF) models with SHAP analysis to explain how six landscape metrics of impervious surfaces and barren land affect exposure. PM2.5 and PM10 exposure declined significantly over the period, whereas O3 exposure increased steadily, indicating worsening complex pollution. Nationally, impervious landscape indicators contributed more than barren indicators to all exposure metrics, with class area (CA) and patch proportion (PLAND) being the strongest predictors, while aggregation index (AI) and division index (DIVISION) had the weakest effects. Regionally, impervious surfaces dominated exposure in central and eastern China, whereas barren land dominated in western China. Nonlinear analysis revealed that pollution-source landscapes with large total area, high aggregation, low connectivity, and regular shape significantly increase exposure risk, with clear thresholds. These findings suggest that mitigating air pollution exposure also requires strategic landscape planning. Our study provides quantitative, landscape-based guidelines for integrating air quality management into land use planning.

【Objective】River basins in arid regions are sensitive to climate change and human activities, with their water-sediment processes undergoing profound changes that would affect ecological security and water resource management. Using Budyko's water-heat coupling theory, this paper analyses the effects of climate change and human activities on water and sediment processes in an inland river basin.【Method】Taking the Shule River Basin as an example and based on runoff depth, sediment discharge, precipitation and potential evapotranspiration measured from 1972 to 2022 at three hydrological stations: Changma Fort, Panjiazhuang and Dangchengwan in the basin, we analysed the changes in water and sediment processes and their influencing factors. The Mann-Kendall trend test and Pettitt abrupt change test were used to analyse and identify the temporal variations and abrupt change in hydrological processes. The elasticity coefficient method and cumulative slope change rate method were used to evaluate the contribution of climate change and human activities to changes in runoff and sediment discharge.【Result】① From 1972 to 2022, the annual runoff depth at all three stations showed an ‘increase-decrease-increase’ trend, with significant abrupt changes identified in 2001 at Changma Fort, 2011 at Panjiazhuang, and 1986 at Dangchengwan; compared with the baseline period, the runoff depth at the three stations increased by 43.26 mm, 7.21 mm and 4.24 mm respectively. ② The annual sediment discharge at the three stations showed an ‘increase-decrease-increase- decrease’ trend, with abrupt changes identified in 1995 at Changma Fort, 1988 at Panjiazhuang and 2007 at Dangchengwan. Compared with the baseline period, the sediment discharge increased by 1.885 9 million tons and 0.329 7 million tons at Changma Fort and Panjiazhuang, and decreased by 0.168 1 million tons at Dangchengwan. ③ The contribution of climate change to runoff changes at Changma Fort, Panjiazhuang and Dangchengwan was 52.86%, 39.16% and -91.38%, respectively, with the remaining contributed by human activities. The contribution of climate change to sediment changes at Changma Fort and Panjiazhuang was 18.88% and 45.31%, respectively, with the remaining contributed by human activities. At Dangchengwan, the contribution of climate change and human activities to the sediment discharge was 31.17% and 68.83%, respectively. The runoff was most sensitive to the underlying surface characteristic, followed by precipitation, and least affected by potential evapotranspiration. Overall, human activities were the dominant factors influencing changes in water and sediment processes.【Conclusion】The runoff change in the upper reaches of the Shule River was mainly affected by climate change, while in the middle and lower reaches, human activities were the dominant factors. The contribution of human activities to sediment changes was significantly higher than that of climate change.

Plant transpiration (Tc) is a key element of the water cycle. The conductance-photosynthesis (Gs-A) model, which assumes a linear relationship between stomatal conductance (Gs) and photosynthetic rate (A) under specific environmental conditions, is widely used to estimate Gs for the remote sensing of Tc. Nevertheless, the key parameter of the Gs-A model, the slope parameter, is typically assigned a biome-specific constant value, despite significant spatial heterogeneity observed within individual biomes. Moreover, the Gs-A model may introduce uncertainties into Tc estimation due to the broad-scale GPP simulated by empirical or complex process models. In this study, Gs was estimated using a typical Gs-A model (i.e., Ball-Berry model) enhanced by integrating daily satellite-observed solar-induced chlorophyll fluorescence (SIF), with a corresponding slope parameter (termed msif) that varies spatially with the local leaf area index (LAI) and air temperature (TEMa). Subsequently, a daily global Tc product (named Tsif) at a 0.05 degrees spatial resolution (2001-2018) was generated, utilizing the PenmanMonteith equation combined with the improved Gs-A model. Observation data of 56 flux sites from the FLUXNET2015 were used to assess the performance and uncertainty of Tc across major vegetation types. Results demonstrated that daily-scale Tc estimation using the dynamic parameterization scheme of msif (DYN) outperformed the fixed scheme (FIX), reducing the root mean square error (RMSE) by an average of 10.89 % compared with flux observations. Furthermore, the spatiotemporal variations in Tc from our product showed good agreement with widely used Tc products, such as GLEAM, SiTHv2, and PML_v2. Notably, compared with flux observations, Tsif exhibited superior performance for Evergreen Broadleaf Forest, Deciduous Broadleaf Forest & Woody Savannas (DW), Savannas & Shrubland, and Grass, achieving the lowest RMSE values (0.88, 0.85, 0.55, and 0.74 mm day-1, respectively). The Tsif dataset provides a novel, independent product valuable for analyses of the water cycle and ecohydrology at large scales.

Coastal salt marshes (CSMs) are vital blue carbon (BC) reservoirs, yet accurately quantifying their gross primary productivity (GPP) remains challenging due to limitations in terrestrial biosphere models (TBMs), which often overlook coastal-specific processes. Here, we present SAL-GPP, a process-based model that incorporates coastal-specific modules to capture the effects of salinity and temperature stress on photosynthesis, as well as light-use efficiency across salinity gradients in diverse CSM plant species. Model validation showed strong agreement with observations, with R2 of 0.82 and model efficiencies of 0.82 and 0.74 for daily and seasonal GPP, respectively. Driven with global inputs, SAL-GPP produced high-resolution global simulations, yielding a mean annual GPP of 66.89 ± 11.68 TgC yr-1 (2011-2020), with 64% concentrated in key hotspots across the southeastern United States, western Europe, southeastern China, and Australia. From 2011 to 2016, global CSM GPP increased by 1.56 TgC yr-1, then declined, rebounded after 2018, and peaked at 71.45 ± 12.02 TgC yr-1 in 2020. Model evaluation showed that SAL-GPP outperformed existing remote sensing-based GPP products and TBMs at both site and grid levels. By explicitly incorporating coastal ecosystem dynamics, SAL-GPP supports global BC accounting and climate mitigation strategies aligned with nature-based solutions for carbon neutrality.

Hydrological prediction and attribution in mountain to plain transition basins remain challenging because topographic zonation, groundwater surface water connectivity, and human regulation can induce structural bias and weaken closure consistency. This study develops an integrated framework that combines an enhanced partitioned, connectivity weighted, and closure consistent Budyko scheme with interpretable deep learning. Annual connectivity weights are derived from the baseflow index and embedded in the partitioned closure accounting. Climate and human contributions are cross validated using an elasticity method and Shapley decomposition under scenario designs. Key predictors are screened with the optimal Geodetector. Runoff prediction is performed using an ensemble of a Convolutional Neural Network, a Bidirectional Long Short-Term Memory network, and Adaptive Boosting (CNN-BiLSTM-AdaBoost), and SHAP is applied to the prediction model to quantify driver contributions and diagnose threshold type responses. Results show that the annual runoff change point occurs in 1993. Both attribution approaches identify climate change as the dominant driver, with contributions of 82.4% and 85.5%, while human activities contribute 17.6% and 14.5%. SPEI_M, SPEI_P, SnSPI_P and Rx5day are identified as the primary meteorological drivers. The ensemble model achieves NSE values of 0.822 for training and 0.908 for testing. SHAP indicates relative contributions of 29.07% and 21.98% for SPEI_M and SPEI_P, respectively, and event scale precipitation shows a notable compensating effect around Rx5day of 49.2 mm. Spatially, mountainous zones are more sensitive to precipitation, enhanced evapotranspiration in the plains reduces outflow, and the integrated connectivity weights during the target period favor mountainous pathways. Overall, the framework unifies closure consistent attribution and interpretable prediction, providing a robust basis for diagnosing asymmetric hydrological responses and supporting management assessment in transition basins.

Abstract Climate change is intensifying the global water cycle, amplifying heavy precipitation and associated flood risks. However, the spatial extent of heavy precipitation—a critical factor for assessing total societal impact—has been largely overlooked. Here, we develop a method to identify the spatial extent of heavy precipitation that incorporates both intensity and anisotropy. Using multisource observations (ERA5, GPM, TRMM) and 23 CMIP6 model projections, we then quantify future changes in heavy precipitation extent and examine how these changes interact with population redistribution under different Shared Socioeconomic Pathways (SSPs). The results reveal that global daily heavy precipitation (≥50 mm/day) expands 2.86 times faster under the SSP5‐8.5 scenarios than the SSP2‐4.5 scenarios. Hotspots intensify in populous eastern North America, South Asia, central Africa, and northern Oceania. Conversely, population exposure surges 4.0 times faster under SSP2‐4.5 versus SSP5‐8.5. Meanwhile, regional disparities intensify. Exposure declines in Asia and South America, despite expanding precipitation, while North America, Africa, Europe, and Oceania face escalating risk. The exposure changes are primarily attributable to population redistribution under SSPs, not heavy precipitation expansion. This spatial mismatch between hazard development and demographic trends challenges hazard‐centric risk paradigms and redefines climate adaptation priorities. Our findings offer a new perspective for the global response to climate change. Spatial coupling between precipitation systems and human settlements—not just temporal hazard intensity—determines future disasters.

Floodplains are important methane (CH4) sources, yet it remains a challenge to capture diel CH4 fluxes dynamics due to strong hydrological seasonalities as well as recently frequent droughts. Based on intensive diel observations (2022-2023) in the Poyang Lake, China's largest floodplain lake, we revealed the importance of hydrological seasonality to drive CH4 dynamics in wet and dry seasons, including an extreme drought event. During the wet season, the floodplain functioned as a net CH4 source with minor diel differences (daytime 1.40 and nighttime 1.38 mg CH4 m- 2 h- 1). While the dry season showed a significant diel asymmetry, with daytime emission (1.38 mg CH4 m- 2 h- 1) exceeding nighttime emission (0.38 mg CH4 m- 2 h- 1), due to large nocturnal CH4 uptake. The pattern was shaped by the combined effects of temperature, soil wetness, and net ecosystem CO2 exchange. However, the contrasts in CH4 emissions tend to diminish during extreme droughts, which weakened the nocturnal CH4 sink. If the seasonal influences on diel CH4 variability are not considered, the CH4 emission can be overestimated by up to 65% during dry season. Our results will inform researchers to include the new and overlooked mechanism into ecosystem models.

Water scarcity and ecological fragility have become prominent constraints on sustainable development in arid inland river basins. Evaluating and forecasting the water resources carrying capacity (WRCC) is critical for achieving a balance between socioeconomic development and ecological conservation. This study constructs a comprehensive early warning framework for WRCC in the Shule River Basin, Northwest China, integrating water resources, ecology, economy, and society into a multidimensional indicator system. A combined weighting method based on entropy weight and CRITIC was employed to objectively determine indicator weights. The TOPSIS model was used to assess WRCC levels from 2000 to 2022. To provide dynamic predictions, a system dynamics (SD) model was developed in Vensim, simulating WRCC evolution under four scenarios: status quo, economic priority, environmental protection, and integrated coordination. Control charts were used to establish early warning thresholds and classify WRCC levels. The results indicate that WRCC showed a U-shaped trend from 2000 to 2022, only decreasing in 2009 and then returning to a high load state by 2022. Obstacle factor analysis identified key constraints in sewage treatment capacity, ecological water use, and economic water-use efficiency. Forecasts show that the integrated and coordinated scenario produces the most favorable outcome, with WRCC reaching 0.627 b y 2035, demonstrating a balance between economic growth and ecological protection. The proposed early warning and simulation framework offers a practical and adaptable approach for WRCC assessment and management in arid regions. The results provide a scientific basis for regional water resource planning and policy formulation under the pressures of climate change and rapid development.

Climate warming induces temporally varying atmospheric water vapor (WV), yet the spatial distribution of opposing trends across global land remains elusive. Here, we use the monthly European Centre for Medium-range Weather Forecasts Reanalysis v5 dataset to discern the responses of WV changes to the rising air temperature from 1982 to 2020. Simultaneous increases in both the WV and air temperature are observed over approximately three-quarters of global land, with a median of 0.21 mmK-1, particularly evident in the tropics. Strong positive responses are primarily influenced by increasing trends in evapotranspiration (ET) and low-elevation areas. About one-fifth of global land shows a decline in WV with a median of -0.62 mmK-1, predominantly in southeastern South America and southwestern North America. Negative responses are also driven by ET trends, where strong ET enhances these effects that are less pronounced in high-altitude regions. The prevalence of a positive response is highest during September-October-November (81%), while a negative response was observed most in December-January-February (35%). The spatial distribution of negative responses generally aligns with soil desiccation patterns; soil desiccation exacerbates negative responses in humid regions due to evaporative cooling but mitigates them in arid regions due to intensified warming. This study enhances our comprehension regarding the divergent responses of atmospheric WV toward global warming.

Carbon dynamics in floodplain lakes are critical to gaining a full understanding of the global carbon budget. Here, we constructed a spatially explicit carbon dioxide (CO2) flux data set covering 2003-2022 for China's largest floodplain lake (R2 = 0.86, RMSE = 0.49 gC m-2 d-1). The annual fluxes varied from 52.57 ± 4.71 gC m-2 in 2010 to -186.36 ± 7.27 gC m-2 in 2011. Temporal variations in CO2 flux were primarily driven by changes in the hydrological regime and wetland vegetation conditions. Specifically, water rise onset and recession onset emerged as the two most influential factors. A 10-day delay in lake water rise enhanced CO2 uptake by 19.20 gC m-2, whereas a 10-day advance in lake water recession increased uptake by 11.63 gC m-2. However, the enhancement of the CO2 sink can be impaired in the case of excessively early or rapid lake water level decline. For example, the extreme drought in 2022 reduced CO2 uptake by over 20% compared to moderate drought years due to plant water stress and increased ecosystem respiration. The findings offer insights into fully evaluating the ecological consequences of lake and water resource management from the perspective of carbon neutrality.