Extreme glacier melt events accelerate mass loss, increase glacier instability, and temporarily increase downstream runoff, potentially alleviating drought conditions. Yet the glacier energy–mass balance in the Geladandong region – a headwater region of the Yangtze River (China's longest river) and one of the source regions feeding Siling Co (Tibet's largest lake) – and its connection to the unprecedented 2022 summer melt remain insufficiently quantified. To address this gap, we integrated in-situ mass balance observations and glacio-meteorological data from a 5700 m monitoring site with an energy-mass balance model and applied a novel dual-threshold framework (based on mean and standard deviation) to identify extreme mass loss/melt events in short-term glacier mass balance records. Our novel methodology identified 2021/22 as a period of extreme mass loss and melt intensity, with melt during the 2022 summer heatwave reaching unprecedented extremes. These heatwaves caused an increase in melt amount of 317.8 mm w.e., amounting to 1.66 and 1.69 times the values recorded for the same period in 2019/20 and 2020/21, respectively. This extreme melt was driven by energy balance anomalies over the glacier surface. In terms of net contributions to the +28.2 W m−2 melt energy anomaly during the three identified heatwave windows, enhanced sensible heat flux was the largest term (+17.0 W m−2; 60.3 %), followed by increased net longwave radiation (+14.0 W m−2; 49.7 %) and increased net shortwave radiation (+5.1 W m−2; 18.1 %) associated with reduced albedo, with negative contributions from latent heat flux and subsurface heat flux. Such anomalies were driven by large-scale atmospheric circulation patterns, specifically the eastward extension and northward displacement of the South Asian High (SAH), together with near-neutral mid-latitude westerlies. This study advances the understanding of glacier mass balance responses to extreme weather and climate events on the central Tibetan Plateau.
Multiyear droughts (MYDs) are severe drought events with profound impacts on human activities and ecosystems. However, the timing that maximizes drought attenuation efficiency under additional precipitation (toptimal) remains insufficiently quantified. With that in mind, we conducted a retrospective grid-based analysis of historical MYDs in China using the Palmer Drought Severity Index (PDSI) over 1961–2020, with a calibration period of 1961–1990, and performed numerical experiments with hypothetical precipitation gradient increases during 1991–2020. We defined k to quantify the sensitivity of drought alleviation to precipitation input. Actual k values derived from the numerical experiments showed strong consistency with theoretical k derived from a drought attenuation quantitative model (DAQM). Theoretical k was further used to quantify MYD attenuation efficiency, with toptimal identified as the timing of maximum theoretical k (kmax). Overall, drought severity (DS) exhibits a nonlinear response to hypothetical precipitation increases. Both numerical experiment-based and DAQM-derived results identify an early-stage response window within the first three months (t1∼t3), and multiple robustness analyses confirm its stability. kmax occurs most frequently at t1, in 58.79 % of all grids, while t2 and t3 were also non-negligible (22.11 % and 11.06 %). This suggests that missing t1 within this window does not necessarily imply a substantial reduction in k. Compared with humid river basins in southern China, arid and semi-arid northern basins show a higher probability that k at t2 or t3 exceed k at t1. Drought duration (DD) is a key factor, as longer DD is associated with a greater likelihood of t2 or t3 being the toptimal (R2=0.526 and 0.578). We noticed that k is jointly influenced by the cumulative temporal advantage of earlier precipitation input and the higher sensitivity of standardized drought indices under severe drought conditions. This study identifies an early-stage response window during MYD evolution and provides conceptual guidance for understanding how precipitation input timing influences drought alleviation across regions.
Sand mining, dam construction, and climate change have profoundly altered the hydrological dynamics of the Mekong River-Tonle Sap Lake floodplain system, one of the world's most ecologically productive river-lake complexes. This study provides an integrated, multi-scale assessment of flow regime alteration across the Mekong mainstream and its coupling with the Tonle Sap Lake across three periods: pre-dam (1976–1991), transition (1992–2009), and post-dam (2010–2024). Using daily and sub-daily data from eight mainstream stations, we quantify shifts in long-term flow memory, short-term variability, and flow amplitude. We use a hydrodynamic response-time model to link upstream regime change to the Mekong–Tonle Sap flow exchange. During the post-dam period, flow memory increased in the upper mainstream but decreased slightly downstream, indicating growing upstream–downstream divergence in flow-regime characteristics and increasing hydrological fragmentation. Upstream stations, particularly Chiang Saen, exhibit a 33.3 % increase in minimum flows and a 40 % decrease in maximum flows during the post-dam period compared to the pre-dam period, alongside higher flow memory (+0.11), reflecting flow smoothing by reservoir operations. At the most downstream station at Kratie, a key control point for Tonle Sap inflow, maximum flows decreased by 9.4 %, while minimum flows increased by 117 % relative to the pre-dam baseline; the seasonal timing of peak discharge was also delayed by approximately two to three weeks. Critically, the combined effects of the altered mainstream flow regime and sand-mining-driven riverbed lowering have shifted the conditions under which Tonle Sap flow reversal initiates. Using the lag-adjusted Kratie discharge at onset as a proxy for the Mekong-Tonle Sap confluence stage/head condition, we find that the median onset discharge increased from ∼ 3200 m3 s−1 (pre-dam) to ∼ 4300 m3 s−1 under the post-dam fixed-bed scenario (2010–2024 hydrology with reference morphology), and to ∼ 7200 m3 s−1 once sand-mining-driven channel incision is added. This indicates that post-2010 hydrological alteration reduced the probability of exceeding the discharge threshold for initiating reverse flow, while sand-mining-driven riverbed lowering substantially amplified this shift by modifying local stage–discharge relationships. Together, these interacting drivers shorten the reverse-flow season by approximately 28 d relative to the pre-dam baseline. Sustaining the Mekong–Tonle Sap flood pulse will therefore require basin-wide monitoring and transboundary governance that address flow timing and variability, not volume alone.
The Global Gravity-based Groundwater Product (G3P) provides global groundwater storage (GWS) variations derived from GRACE/GRACE-FO terrestrial water storage (TWS) change by subtracting root-zone soil moisture, glacier mass change, surface water storage, and snow water equivalent. G3P thus provides the first globally consistent, publicly available groundwater dataset from satellite gravimetry for continental-scale water resources assessment. Here, we use G3P to assess global GWS trends over the extended GRACE/GRACE-FO record, jointly with TWS and the subtracted storage components. A central challenge is that apparent long-term trends in GRACE/GRACE-FO water storage records can reflect persistent storage change, natural climate variability, hydrological memory, and observational errors, complicating trend detection and continental-scale storage-change budgets. We address this using a calibrated trend-analysis framework that jointly accounts for trend, seasonal, and stochastic variations in each grid-cell time series. Statistically significant trends are then aggregated to quantify volumetric GWS and TWS gains, losses, and net changes at continental and global scales. Applying this framework to 21.5 years of data (April 2002–September 2023), we find that groundwater depletion is a major contributor to freshwater decline at continental scales, most prominently in Asia (−55 km3 yr−1), while cryospheric mass loss dominates the strongest TWS declines in high-latitude and glacierized regions. Pronounced regional contrasts include increasing groundwater storage across large parts of Africa (+37 km3 yr−1), negative trends in drought-affected regions, and widespread negative or near-threshold GWS tendencies across the Northern Hemisphere. Globally, significance-filtered net GWS and TWS changes are approximately −27 and −183 km3 yr−1, respectively. The corresponding gross negative GWS change of approximately 103 km3 yr−1 is of the same order as model-based estimates of global groundwater depletion. Sensitivity tests indicate robust results: at 95 %, detected area increases by 30 % for TWS and 36 % for GWS, while net-loss magnitudes rise by only 9 % and 18 %. Across much of the seasonal-to-interannual spectral range, GWS is the dominant individual storage-component signal within TWS, which highlights the importance of groundwater for continental freshwater availability.
Indian River basins experience frequent flooding during the Indian summer monsoon and pose several challenges for the region's large population, yet the hydrometeorological and catchment-scale drivers that control flood processes remain poorly explored across India. To effectively manage flood risk in the densely populated Indian region, it is essential to understand how the temporal properties of precipitation and runoff generate floods across different aridity regimes within a large catchment, and which specific areas of a large, climatically heterogeneous basin generate the runoff that drives downstream flood peaks. In this study, we address these gaps and examine the role of hydrometeorological variables (such as precipitation and surface runoff) and catchment area in the flood occurrence in the Godavari River basin (one of the largest river basins in the Indian Subcontinent) using observed and VIC-simulated datasets. Based on the temporal analysis of precipitation, runoff, and streamflow, we show that the majority of floods in the semi-humid sub-basins (Tekra, Pathagudam, Perur, and Polavaram) are predominantly associated with 10 to 11 d of accumulated precipitation, having multiple high-intensity precipitation events prior to flood. In contrast, the floods in the semi-arid region of Godavari (Mancherial sub-basin) are triggered by a single high-intensity precipitation day and are associated with short-duration (2 d) accumulated precipitation. In addition to temporal analysis, we performed Empirical Orthogonal Function (EOF) analysis using precipitation, runoff, and streamflow data to identify the specific sub-regions that disproportionately generate flood-causing runoff (flood-dominant catchment areas). Our results demonstrate that central and downstream areas of the basin contribute dominantly to flood occurrence, generating substantially higher runoff in the Tekra sub-basin. Overall, this study moves beyond basin-averaged flood attribution and advances understanding of flood-generating mechanisms over the Godavari River basin, which can be helpful for duration-informed forecasting and catchment-scale flood management during the monsoonal climate of the Indian Subcontinent.
