Journal of Hydrology最新文献

{"title":"Efficient Markov chain Monte Carlo sampling for Bayesian inverse problems with covariance matrix adaptation","authors":"Kun Zhang ,&nbsp;Hui Wu ,&nbsp;Jiangjiang Zhang ,&nbsp;Songjun Wu","doi":"10.1016/j.jhydrol.2025.134235","DOIUrl":"10.1016/j.jhydrol.2025.134235","url":null,"abstract":"<div><div>Bayesian inference provides a principled framework for solving inverse problems, yet efficient sampling of high-dimensional non-Gaussian posterior distributions remains challenging for conventional Markov chain Monte Carlo (MCMC) methods. This study introduces the covariance matrix adaptation Metropolis (CMAM) algorithm, an efficient MCMC approach that synergistically integrates the population-based covariance matrix adaptation evolution strategy (CMA-ES) optimization algorithm with Metropolis sampling. The proposed CMAM employs multiple parallel chains to enhance exploration in Bayesian inversion and leverages the adaptive mechanisms of CMA-ES to dynamically adapt both the direction and scale of proposal distributions. A decoupled Metropolis acceptance mechanism ensures proper Markov chain construction throughout the adaptation process. The method further incorporates augmentation and dual adaptation strategies, utilizing information from rejected samples and dual CMA-ES optimizations, to improve robustness in multimodal and high-dimensional scenarios. Theoretical analysis confirms ergodicity of the proposed method. Numerical benchmarks demonstrate that CMAM is capable of sampling with sub-dimensional chains, while still achieving comparable performance in inversion accuracy and convergence efficiency to state-of-the-art multi-chain adaptive MCMC methods. Hydrogeological case studies further show that CMAM accurately reconstructs spatially heterogeneous conductivity fields and simultaneously identifies contaminant source locations and release histories. These results highlight CMAM as a practical tool for Bayesian inference in real-world hydrological and environmental applications.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134235"},"PeriodicalIF":6.3,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecohydrological adaptation: A research and management framework for ecosystems in Australia’s drying and warming climate","authors":"Sally E. Thompson ,&nbsp;Caitlin E. Moore ,&nbsp;Qiaoyun Xie ,&nbsp;Jaume Ruscadella-Alvarez ,&nbsp;Gavan McGrath ,&nbsp;Katinka X. Ruthrof","doi":"10.1016/j.jhydrol.2025.134210","DOIUrl":"10.1016/j.jhydrol.2025.134210","url":null,"abstract":"<div><div>Australia – the driest inhabited continent and the continent with the most exceptionally variable rainfall globally – is also home to a diverse range of unique and often endemic ecosystems. While globally the productivity and distribution of many ecosystems is strongly controlled by temperature, water availability is the primary driver of productivity and the distribution of most Australian ecosystems. Despite its high rainfall variability, Australia’s ecosystems display great resilience to changes in water availability. The limits of this resilience in the context of climate change are of increasing concern, as multiple extreme events in quick succession reduce opportunities for recovery. In this review, we introduce Australian ecosystems and their water use, outline drivers of changing water availability to Australian ecosystems, their likely consequences, and a hierarchy of potential management options available to slow the pace and decrease the magnitude of water-driven ecosystem and ecohydrological change. We present case studies where previous implementation of such management solutions have been applied. We conclude by identifying the ecohydrological knowledge gaps needed to equip Australia, and other nations worldwide, to implement these strategies responsibly, considering the costs and uncertainties associated with potential management measures.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134210"},"PeriodicalIF":6.3,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dominating effect of extreme precipitation over potential groundwater recharge beneath shallow rooted vegetation","authors":"Han Li ,&nbsp;Guanpeng Dong ,&nbsp;Min Min ,&nbsp;Huijie Li ,&nbsp;Jingjing Jin ,&nbsp;Han Wang ,&nbsp;Bingcheng Si ,&nbsp;Changhong Miao ,&nbsp;Dong Wang","doi":"10.1016/j.jhydrol.2025.134293","DOIUrl":"10.1016/j.jhydrol.2025.134293","url":null,"abstract":"<div><div>Potential groundwater recharge (PGR) beneath shallow-rooted vegetation, a dominant ecosystem in temperate and arid regions, remains poorly understood. Current global syntheses are hindered by methodological inconsistencies and mixed temporal scales, particularly in relatively homogeneous soil environments like the Loess Plateau, where shallow-rooted crops/grasslands dominate but regional PGR controls are uncharacterized. This study uses the tritium peak method (35 profiles, tritium peak depth 3.6–26.4 m) and partial least squares structural equation modeling (PLS-SEM) to quantify PGR (8.8–93.0 mm yr⁻¹ over the past five decades, mean 43.0 ± 3.7 mm yr⁻¹) and drivers. Extreme precipitation (EP) is the sole significant driver, explaining 50.5 % of PGR variance (path coefficient = 0.667, p &lt; 0.001), with negligible empirical effects of soil texture (silt-dominated), shallow roots (95 % above 2.0 m), and soil hydraulic properties. The tritium method’s unified temporal scale (past five decades) and single-variable design eliminate parameter biases, confirming EP-driven pulse infiltration bypasses shallow roots and relatively homogeneous loess soils. This study reveals PGR in shallow-rooted, uniform soil systems is climate-dominated, offering an EP-centric framework for regional hydrological modeling and water management globally.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134293"},"PeriodicalIF":6.3,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145103975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrological water exchange and nitrogen transformation in the two consecutive meander-driven hyporheic zones","authors":"Yiwei Song ,&nbsp;Haizhu Hu ,&nbsp;Dongyuan Xue ,&nbsp;Jinning Zhang ,&nbsp;Jiawei Ren ,&nbsp;Xixi Lu","doi":"10.1016/j.jhydrol.2025.134291","DOIUrl":"10.1016/j.jhydrol.2025.134291","url":null,"abstract":"<div><div>Hyporheic zones play a critical role in water exchange and nitrogen (N) removal from river ecosystems. However, the hyporheic water exchange and N transformation driven by consecutive meanders have rarely been explored. To better understand how hydrological conditions control N transformation processes in two consecutive meander bends, high-resolution sampling campaigns were carried out in a meandering reach of the Xilin River during the rainy seasons of 2021 (wet year) and 2022 (normal year). Highly spatial and temporal variability of hyporheic water exchange and nitrogen concentrations were found in two consecutive meander bends. The higher hydrological connectivity between river water and shallow groundwater was observed in the inner bank of upstream sharp meander with a sinuosity of 2.01, compared to the consecutive downstream mild bend with a sinuosity of 1.47. Higher connectivity allows river water to provide more adequate nutrients as a reaction substrate, thereby promoting nitrate attenuation in the hyporheic zone of meander A. Although higher nitrate (NO₃^–) and ammonium (NH₄⁺) concentrations were observed in subsurface water during the wet year, NO₃^– removal efficiency in the hyporheic zone increased by 47.8 % relative to normal year, attributed to enhanced subsurface hydrological connectivity in the two consecutive meanders. Rainfall events of varying magnitude resulted in distinct alterations in hyporheic exchange and N distribution patterns. The sharp meander bend exhibited a shielding effect, sustaining the inner-bank lateral hyporheic flow even during storm events. The results suggest hydrogeomorphic characteristics, hyporheic exchange and nitrogen transformation are highly coupled in a consecutive meander system.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134291"},"PeriodicalIF":6.3,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of soil moisture profiles in ungauged stations by hybridizing sequential data assimilation and machine learning","authors":"Yakun Wang ,&nbsp;Qiuru Zhang ,&nbsp;Shikun Sun ,&nbsp;Yifei Yao ,&nbsp;Xiaotao Hu ,&nbsp;Shibiao Cai ,&nbsp;Hanbo Wang","doi":"10.1016/j.jhydrol.2025.134292","DOIUrl":"10.1016/j.jhydrol.2025.134292","url":null,"abstract":"<div><div>Although soil moisture content (SMC) is crucial for understanding land–atmosphere interface interactions, there is still a paucity of regional-scale long-term high resolution SMC datasets. How to deduce regional continuous SMC with discrete point-scale observations remains a prevalent and challenging issue. Existing physical models often struggle with parameter acquisition and high computational costs, whereas purely data-driven machine learning (ML) models may perform poorly outside its calibration range due to the lack of physical constraints. This study proposed a sequential hybrid method (mRestart-EnKF-ML) that combined the modified restart ensemble Kalman filter (mRestart-EnKF) with ML to estimate SMC in ungauged stations using historical information from adjacent available stations. With the aid of a series of real-world cases, we demonstrated the ability, and the challenge as well, of retrieving SMC in ungauged stations sequentially. The results showed that Kalman update improved the reliability of ML modeling by updating soil hydraulic parameters in real-time, thereby enhancing the overall estimation accuracy of SMC, especially for the surface-layer SMC. In contrast to purely data-driven models, the proposed mRestart-EnKF-ML significantly reduced the RMSE of SMC retrievals by means of both expanding the training dataset and introducing physical constraints into ML models. The impacts of input features on mRestart-EnKF-ML for SMC estimation exhibited significant spatial heterogeneity and align with physical processes based on the SHAP analysis. Training data with denser vertical spatial resolution can implicitly offer more accurate physical knowledge like mass conservation, thus ensuring the proposed method’s robustness in various application scenarios. The performance of the mRestart-EnKF-ML was significantly influenced by observation error settings, station-specific characteristics, and depth-dependent responses, with optimal error configurations varying by station type and depth playing key roles in shaping error-accuracy relationships.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134292"},"PeriodicalIF":6.3,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land use and economic development influenced the hotspots of groundwater storage gains and losses in mainland China in the past 20 years","authors":"Qian Zhang ,&nbsp;Shengwei Lv ,&nbsp;Shengwei Zhang ,&nbsp;Ying Zhou ,&nbsp;Xi Lin ,&nbsp;Lin Yang ,&nbsp;Shuai Wang ,&nbsp;Ruishen Li","doi":"10.1016/j.jhydrol.2025.134280","DOIUrl":"10.1016/j.jhydrol.2025.134280","url":null,"abstract":"<div><div>Groundwater is the world’s largest freshwater resource after ice caps and glaciers, and its over-exploitation can disrupt regional hydrological cycles, leading to issues such as land subsidence and salinization. Identifying hotspots and drivers of groundwater storage changes is essential for sustainable water management and climate change mitigation. This study uses GRACE/GRACE-FO satellite data to identify groundwater storage change hotspots in mainland China over the past two decades, employing Pettitt-test and temporal stability analyses. To ensure reliability, we cross-validated the GRACE/GRACE-FO-derived groundwater storage against Watergap Global Hydrological Model and available well records, the correlation coefficient distribution is 0.76–0.88. The hotspots are categorized into loss (I, II, III) and gain (IV, V) categories. The severity of both gain and loss conditions increases with the level. Additionally, the study quantifies the contributions of natural and anthropogenic factors by integrating climatic and socio-economic variables. The results indicate that loss hotspots dominate in North China, Loess Plateau, Northwest China, Northeast China, and Qinghai-Tibet Plateau. In the Qinghai-Tibet Plateau region, the combined proportion of Level I, II, and III loss hotspots exceeds 60%, whereas in other regions, the combined proportion of these loss hotspots is over 75%. In contrast, surplus hotspots are prevalent in South China, Ch-Yu region, Middle-Lower Yangtze River, and Yun-Gui Plateau, where level IV and V gain hotspots exceed 60%. Groundwater changes in the Qinghai-Tibet Plateau and Loess Plateau are primarily influenced by land use, whereas economic factors play a more significant role in other regions. This study offers valuable insights into regional groundwater changes across China and provides a scientific foundation for effective water resource management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134280"},"PeriodicalIF":6.3,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Propagation dynamics of meteorological, agricultural, and vegetation droughts in China","authors":"Xianglei Yang ,&nbsp;Wenxiang Zhang ,&nbsp;Aifeng Lv ,&nbsp;Taohui Li ,&nbsp;Pengfei Yin","doi":"10.1016/j.jhydrol.2025.134284","DOIUrl":"10.1016/j.jhydrol.2025.134284","url":null,"abstract":"<div><div>Meteorological drought (MetD) serves as the primary driver of other drought types by altering the hydrological cycle and initiating subsequent droughts. However, the mechanisms of propagation from MetD to agricultural drought (AgrD) and vegetation drought (VegD) remain poorly quantified across China’s diverse climatic gradients. Elucidating this complete propagation pathway is critical for enhancing drought monitoring and early warning systems across various ecosystems. This study employed the Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSMI), and Vegetation Condition Index (VCI) to quantify MetD, AgrD, and VegD, respectively. The results revealed significant disparities in both the average duration and frequency of MetD, AgrD, and VegD across China. MetD exhibited the highest mean frequency (1.43 times/year), exceeding AgrD (0.54 times/year) and VegD (1.17 times/year). All drought types demonstrated alleviation trends, as evidenced by significant increases in SPI (57.11 %), SSMI (86.63 %), and VCI (65.00 %). MetD exerted the strongest influence on AgrD, while AgrD had a more substantial effect on VegD than MetD. The average propagation time from MetD to AgrD was 7.38 months, significantly shorter than from MetD to VegD (12.94 months) and from AgrD to VegD (12.79 months). Propagation processes were shorter in summer and autumn compared to spring and winter, influenced by climate and vegetation types. These findings provide a scientific foundation for drought risk assessment, ecological restoration, and vegetation recovery initiatives in China, contributing to the development of a more comprehensive drought monitoring system.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134284"},"PeriodicalIF":6.3,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of irrigation on hot extreme in the Yangtze River Basin using observed analysis and model simulation","authors":"Yafei Wang ,&nbsp;Pan Liu ,&nbsp;Qian Xia ,&nbsp;Zhaode Yun ,&nbsp;Weibo Liu","doi":"10.1016/j.jhydrol.2025.134271","DOIUrl":"10.1016/j.jhydrol.2025.134271","url":null,"abstract":"<div><div>Irrigation is one of the land management types with significant biophysical impact on local climate. Former studies have shown that irrigation has cooling effect on temperature, especially hot extremes. However, most of the studies are based on simulations from regional or global climate models, and the simulated irrigation-induced cooling remains largely unvalidated. In this study, two individual methods, observational analysis and the WRF model with irrigation module are used to assess the impacts of irrigation on hot extremes in the Yangtze River Basin (YRB) of China, a typical humid/semi-humid region with intensive irrigation. The average extreme high temperature in the YRB decreased by 0.3 °C with the highest decrease of 1.4 °C due to irrigation. We find a threshold for the cooling benefits of irrigation expansion in the YRB. Namely, the cooling intensity increases with the expansion of the irrigated area fraction, but diminishes once the irrigated area fraction exceeds the threshold value of 0.3. This can be explained by using model simulation, where irrigation primarily achieves the cooling effect on extreme high temperatures by increasing humidity and latent heat fluxes while reducing sensible heat fluxes. The study highlights the urgent need to understand the cooling effect of irrigation in such regions for efficient land management and emphasizes the necessity of considering the differences in irrigation impacts in future climate predictions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134271"},"PeriodicalIF":6.3,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating rainfall estimates derived from soil moisture using soil hydraulic properties over the Korean Peninsula","authors":"Doyoung Kim ,&nbsp;Seulchan Lee ,&nbsp;Seongkeun Cho ,&nbsp;Daeha Kim ,&nbsp;Minha Choi","doi":"10.1016/j.jhydrol.2025.134267","DOIUrl":"10.1016/j.jhydrol.2025.134267","url":null,"abstract":"<div><div>Rainfall is an essential element within hydrological systems, serving as the primary source of moisture on the land surface. Recent climate change-induced extreme weather events have increased the spatiotemporal variability of rainfall, highlighting the demand for diverse rainfall monitoring methods. This study used the SM2RAIN algorithm with soil physical properties (infiltration rate and soil moisture nonlinearity coefficient) to generate a rainfall dataset for the Korean Peninsula. By incorporating soil physical properties into SM2RAIN, the SM2RAIN-Soil Moisture Active and Passive (SM2RAIN-SMAP) dataset was created from SMAP L4 soil moisture. The accuracy of SM2RAIN-SMAP was compared with the Global Precipitation Mission Integrated Multi-satellitE Retrievals (GPM-IMERG) and SM2RAIN-Advanced SCATterometer (SM2RAIN-ASCAT). Rainfall estimated using soil physical property parameters showed good agreement with point-scale rainfall observations with a Spearman rank correlation (Rs) of 0.7. A comparison between SM2RAIN-SMAP and SM2RAIN-ASCAT revealed that the highest correlation occurred in spring (0.77), with an average correlation of 0.65 across all seasons. An analysis of rainfall estimation performance by the land cover type revealed that SM2RAIN-SMAP performed better in croplands, whereas SM2RAIN-ASCAT showed superior performance in forests. The performance difference was attributable to the influence of vegetation interception effects and systematic errors in soil moisture products, which vary depending on sensors. The proposed approach used relatively simple calculations to improve the accuracy of rainfall monitoring and has the potential to provide diverse and reliable rainfall data for hydrometeorological research and disaster management in monsoon regions. This physics-based approach offers an alternative to the traditional empirical calibration methods used in SM2RAIN.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134267"},"PeriodicalIF":6.3,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145103974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying glacier accumulation in the western Tianshan Mountains considering snow redistribution","authors":"Gonghuan Fang ,&nbsp;Zhi Li ,&nbsp;Jing Yang ,&nbsp;Yaning Chen ,&nbsp;Weili Duan ,&nbsp;Qifei Zhang ,&nbsp;Wenting Liang","doi":"10.1016/j.jhydrol.2025.134266","DOIUrl":"10.1016/j.jhydrol.2025.134266","url":null,"abstract":"<div><div>Snow redistribution in alpine catchments plays an important role in hydrological modeling. However, snow redistribution has rarely been incorporated into semi-distributed hydrological models. This omission has introduced considerable uncertainty and potential bias in glacier mass balance simulations. This study addressed this challenge by developing an empirical snow redistribution module (SRD) within the SWAT–Glacier model (SWAT–Glacier–SRD). The snow redistribution amount was a function of slope and snow density under a certain threshold. This model was applied to the Kumarik catchment, the largest tributary in the Tarim River Basin. To constrain the hydrological components, the model was calibrated using multiple observations, including runoff, glacier area, mass balance, and snow balance indices. Compared to SWAT–Glacier, SWAT–Glacier–SRD was able to more effectively simulate spring streamflow. Kling–Gupta Efficiency (KGE) was 0.82 in the calibration period and ranged from 0.57 to 0.91 in the validation period. The model also achieved improved performance in reproducing glacier- and snow-related indices. From 1975 to 2019, the mean rates of glacier accumulation and ablation were estimated at 0.573 m w.e. and 0.850 m w.e., respectively, resulting in a glacier mass balance of −0.277 m w.e. Glacier accumulation increased substantially from 0.460 m w.e. during 1975–1998 to 0.697 m w.e. during 1999–2019. The rate of glacier mass loss slowed, with glacier mass balance increasing from −0.359 m w.e. (1975–1998) to −0.187 m w.e. (1999–2019).</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134266"},"PeriodicalIF":6.3,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}