Journal of Hydrology-Regional Studies最新文献

{"title":"South African soil, land cover and weather generator file databases for SWAT applications","authors":"Jay le Roux ,&nbsp;Ndifelani Mararakanye ,&nbsp;Michael van der Laan ,&nbsp;Leushantha Mudaly ,&nbsp;Harold Louw Weepener ,&nbsp;Johan van Tol","doi":"10.1016/j.ejrh.2025.102387","DOIUrl":"10.1016/j.ejrh.2025.102387","url":null,"abstract":"<div><h3>Study region</h3><div>South Africa.</div></div><div><h3>Study focus</h3><div>The focus of the study is to develop soil, land cover and weather generator file datasets for Soil and Water Assessment Tool (SWAT) applications in South Africa. The first objective was to format national datasets for use as baseline to run the SWAT model in South Africa. The second objective was to evaluate the performance of the baseline input data by applying the national datasets in four (previously simulated) research catchments.</div></div><div><h3>New hydrological insights for the region</h3><div>The input datasets comprise of geo-spatial datasets at a national scale to run ArcSWAT or QSWAT (graphical user interface for SWAT in ArcGIS and SWAT+ in QGIS, respectively) in South Africa including: SWAT catchment outline data (tertiary and quaternary); Land cover maps at 20–30 m resolution including South African National Land Cover (2014, 2018, 2020) linked to SWAT land cover codes; A soil map with SWAT attribute data derived from pedotransfer functions of the Land Type Database of South Africa useable at a scale of 1:250,000; Weather statistics (WGN) files for 12 weather stations obtained from the Agricultural Research Council in South Africa. The national baseline data is an important step forward in hydrological modelling by assisting modellers to set-up and run the SWAT model in South Africa.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102387"},"PeriodicalIF":4.7,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Water resource vulnerabilities from climate-induced tipping point behaviour in runoff volumes and seasonality in the region of the ‘Karakoram Anomaly’: A snow-glacier melt perspective","authors":"Jamal Hassan Ougahi ,&nbsp;John S. Rowan","doi":"10.1016/j.ejrh.2025.102386","DOIUrl":"10.1016/j.ejrh.2025.102386","url":null,"abstract":"<div><h3>Study region</h3><div>Hunza River Basin, Karakoram range, Pakistan</div></div><div><h3>Focus of study</h3><div>Assessing the future persistence of the 'Karakoram Anomaly,' under climate change scenarios, where glaciers in the region exhibit stable or slightly negative mass balances, contrary to global trends.</div></div><div><h3>New Hydrological insights for the region</h3><div>The study explores how long the anomalous behaviour in Karakoram glaciers will persist under future climate scenarios. The results indicate a significant temperature rise under Shared Socioeconomic Pathway 5 (SSP5), whereas SSP2 exhibits greater variability. Snow Water Equivalent (SWE) is projected to decline due to reduced snowfall and faster snowmelt across all seasons, particularly in summer and autumn. Our glacio-hydrological model projects substantial glacier retreat from 4270 km² in 2010 reducing to 3540 km² or 2730 km² by 2100 according to SSP2 and SSP5, respectively. Increased annual runoff peaks around 2050 (SSP2) and by 2070 (SSP5) before decline in total runoff by 2100. The study also highlights significant climate change impacts on seasonal hydrology, associated with declines in glacier and snowpack water storage in the next three decades. This stresses the need for adaptive water resource management (e.g. storage infrastructure or changing demand management) to address potential water shortages to human water users e.g. irrigation and hydropower and associated ecosystem disruptions including extreme flooding. These findings provide valuable insights for future hydro-climatic dynamics and policymaking in the region.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102386"},"PeriodicalIF":4.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What role does agriculture play in irrigation water footprint consumption? A perspective based on sectoral linkage and structural path","authors":"Xiaoling Li ,&nbsp;Yu Song","doi":"10.1016/j.ejrh.2025.102378","DOIUrl":"10.1016/j.ejrh.2025.102378","url":null,"abstract":"<div><h3>Study region</h3><div>China</div></div><div><h3>Study focus</h3><div>This study employs a novel three-module analytical framework to appraise the linkage effects and structural paths associated with the irrigation water footprint in the agricultural sector from 2002 to 2020.</div></div><div><h3>New hydrological insights for the regions</h3><div>The results showed that a) The agricultural sector exhibits a significant reliance on its own internal water resources, while simultaneously representing a critical source of water resources for other sectors, thus positioning agriculture as a net water resource provider. b) Different from the overall irrigation water footprint, which is upward and then downward, the irrigation water footprint in agriculture is characterized by a downward and then oscillating upward. In addition, the net input irrigation water footprint turned from negative to positive highlighting the significant role of imported water in reducing domestic water scarcity. c) An in-depth analysis of agriculture indicates that direct consumption constitutes the largest component of the irrigation water footprint, with outflow significantly exceeding inflow. From a production standpoint, agriculture and industry represent the primary intermediate consumers of the irrigation water footprint. From a consumption perspective, while the structural paths of the irrigation water footprint vary across different consumers, agriculture consistently functions as the initial sector in irrigation water footprint transmission. These findings provide valuable insights for developing nations to develop effective water management strategies in their respective agricultural sectors.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102378"},"PeriodicalIF":4.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Weakening greenhouse gas sink of intermittent river under human activities for the Inner Mongolia grassland region in China","authors":"Xinyu Liu ,&nbsp;Huifang He ,&nbsp;Weijie Han ,&nbsp;Wentao Liang ,&nbsp;Zhenqi Yang ,&nbsp;Jianying Guo","doi":"10.1016/j.ejrh.2025.102395","DOIUrl":"10.1016/j.ejrh.2025.102395","url":null,"abstract":"<div><h3>Study region</h3><div>This study was conducted in the Tabu River Basin, located within the Yinshanbeilu Grassland in central Inner Mongolia Autonomous Region, China.</div></div><div><h3>Study focus</h3><div>The Tabu River's runoff is significantly affected by human activities. This study investigated the spatiotemporal dynamics of the CO₂ flux under varying runoff conditions, identified the key drivers of CO₂ emissions, and assessed the influence of human activities on these emissions within the watershed.</div></div><div><h3>New hydrological insights for the region</h3><div>Our findings revealed a significant decline in runoff in the Tabu River Basin since 2010, primarily driven by human activities. Following river drying, riverbed ecosystem respiration (<em>ER</em>) increased, whereas riparian wetlands exhibited a marked decrease in <em>ER</em>. Furthermore, net ecosystem exchange (<em>NEE</em>) results indicated a shift from a carbon sink to a carbon source in the riparian wetlands during periods of river drying. Soil moisture content (SMC), above-ground biomass (Bios), and soil bulk density (ρb) emerged as critical factors regulating CO₂ emissions. These findings highlight the necessity for continuous, long-term monitoring of intermittent rivers and in-situ greenhouse gas flux measurements under diverse hydrological conditions. To enhance the resilience of riverine ecosystems and sustain their carbon sequestration potential, future management of the Tabu River Basin should focus on optimizing irrigation strategies and adapting reservoir management practices. Such interventions will enable efficient allocation and sustainable utilization of water resources.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102395"},"PeriodicalIF":4.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Customizing large-scale hydrological models: Harnessing the open data realm for impactful local applications","authors":"Ilias G. Pechlivanidis,&nbsp;Jude Lubega Musuuza","doi":"10.1016/j.ejrh.2025.102390","DOIUrl":"10.1016/j.ejrh.2025.102390","url":null,"abstract":"<div><h3>Study region</h3><div>Lake Hume in Australia and Harsha Lake in USA.</div></div><div><h3>Study focus</h3><div>Large-scale hydrological models (LSHMs), though important for both scientific and societal reasons, require the representation of many unknown features that influence river system response. However, current model identification practices in catchment modelling cannot lead to robust LSHMs for local decision-making. To address this, it is necessary to customise the models by integrating local data and knowledge from various sources (e.g. in-situ and earth observations) and fluxes. We present a framework to customize LSHMs for impactful local applications and showcase this using the global WWH hydrological model as the reference LSHM.</div></div><div><h3>New hydrological insights</h3><div>We present significant improvements in modelling streamflow and actual and potential evapotranspiration, following WWH refinements to include local lakes and reservoir management. Local streamflow measurements and earth observations from NASA MODIS evapotranspiration products were used to re-calibrate the locally adapted model, leading to spatial consistency in performance. Combining multiple variables and metrics during model identification improved streamflow performance and robustness, with combination sets reducing variability and enhancing representation of diverse hydrological processes, highlighting the need for tailored metric and variable selection. This underpins the importance of including informative data in customized multi-objective modelling chains. Finally, incorporating reservoir management improved simulation of a regulated system, with local insights informing reservoir parameterization in LSHMs and bridging the gap to global-scale applications.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102390"},"PeriodicalIF":4.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decomposition and attribution analysis of the coupled evolution characteristics of groundwater and land subsidence in the Beijing-Tianjin-Hebei Plain","authors":"Yongkang Wang ,&nbsp;Huili Gong ,&nbsp;Chaofan Zhou ,&nbsp;Qin Wang ,&nbsp;Haotong Wang ,&nbsp;Jincai Zhang","doi":"10.1016/j.ejrh.2025.102393","DOIUrl":"10.1016/j.ejrh.2025.102393","url":null,"abstract":"<div><h3>Study region</h3><div>This study investigated the relationship between groundwater storage and land subsidence and analyzed the potential causes of these variations in the Beijing-Tianjin-Hebei Plain from 2018 to 2022.</div></div><div><h3>Study focus</h3><div>Independent Component Analysis (ICA) was applied to separate signals from Interferometric Synthetic Aperture Radar (InSAR) surface deformation data and Gravity Recovery and Climate Experiment (GRACE) and GRACE-Follow On (GRACE-FO) groundwater storage anomalies. A spatiotemporal feature coupling analysis was then conducted on the periodic and trend components. The CNN-LSTM-attention neural network further quantified the drivers of groundwater changes in the trending subsidence area.</div></div><div><h3>New hydrological insights for the region</h3><div>(1) periodic components showed a strong positive correlation (cross-correlation coefficient = 0.73, with land subsidence lagging behind groundwater storage changes by 1 month) and a 5–6 month delayed response to precipitation, with high-score areas clustered in the precipitation-rich eastern and southern BTHP. (2) The trend components revealed synchronized declines (2018–2021), followed by rebounds, with groundwater recovery outpacing subsidence mitigation. High-score zones were aligned with regions of intense groundwater extraction (e.g., the southern BTHP). (3) In the trending subsidence area, CNN-LSTM-attention model achieved higher accuracy (test set R²: 0.54 vs −0.99, RMSE: 13.11 mm vs 43.12 mm) using reconstructed groundwater signals, confirming precipitation and anthropogenic extraction as significant contributing factors. This study provides a reference for exploring the relationship between changes in groundwater reserves and land subsidence.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102393"},"PeriodicalIF":4.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying differences in evapotranspiration and ecosystem water use efficiency between different types of urban green spaces: A case study of the main urban area of Beijing","authors":"Rui Shao ,&nbsp;Jiaqi Li ,&nbsp;Weiwei Shao ,&nbsp;Yicheng Wang","doi":"10.1016/j.ejrh.2025.102374","DOIUrl":"10.1016/j.ejrh.2025.102374","url":null,"abstract":"<div><h3>Study region</h3><div>The main urban area of Beijing, China.</div></div><div><h3>Study focus</h3><div>Refined modeling is crucial for estimating carbon sequestration and water consumption in urban green spaces. This study used Sentinel-2 data, PT-JPLim, and analytical WUE models to estimate monthly ET and WUE in the main urban area of Beijing (2016–2021) at a 10 × 10 m resolution. Machine learning quantified the effects of environmental factors on ET and WUE across various green space types. Simulations assessed the impacts of different vegetation scenarios on ET and WUE, while urban ET and WUE were predicted for 2022–2100 under different climate scenarios using CMIP6.</div></div><div><h3>New hydrological insights for the region</h3><div>This study shows that vegetation, especially LAI, is the primary driver of spatiotemporal variations in ET and WUE across urban green spaces in Beijing, contributing 64.7 % and 62.5 % to these changes, respectively. Simulations of a 25 % vegetation increase revealed that residential green spaces are most sensitive, with ET and WUE rising by 6.2 % and 30 %, respectively. The study also estimated water requirements, with net irrigation needs of 95.18 million m³ in normal years and 125 million m³ in dry years. Projections under the SSP126 scenario indicate a near-equilibrium state for carbon sequestration and CO₂ concentrations, achieving greater carbon sinks and water conservation with minimal increases in water consumption. These insights are valuable for optimizing water resource management and ecological planning in urban green spaces.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102374"},"PeriodicalIF":4.7,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding flood dynamics in the Indus River Basin: Lessons from the 2022 Pakistan deluge","authors":"Aashutosh Aryal,&nbsp;Kyung Y. Kim,&nbsp;Venkataraman Lakshmi","doi":"10.1016/j.ejrh.2025.102362","DOIUrl":"10.1016/j.ejrh.2025.102362","url":null,"abstract":"<div><h3>Study region</h3><div>The study focuses on the Indus River Basin and southern Pakistan, severely affected by flooding in 2022.</div></div><div><h3>Study focus</h3><div>This study assessed how land surface temperature, snow cover, soil moisture, and precipitation contributed to the deluge of 2022. This study mainly investigated MODIS-AIRS land surface temperature, MODIS snow cover (NDSI), SMAP soil moisture, and GPM IMERG precipitation accumulation. Furthermore, different flood visualization and mapping techniques were applied to delineate the flood extent map using Landsat 8–9, Sentinel-2 MSI, and Sentinel-1 SAR data.</div></div><div><h3>New hydrological insights for the region</h3><div>The region experienced some of the most anomalous climatic events in 2022, such as prolonged heatwaves as observed with higher-than-average land surface temperatures and subsequent rapid decline in snow cover extent during the spring, increased soil moisture followed by an abnormal amount of extreme monsoon precipitation in the summer. The upper subbasins experienced more than 8℃ in positive temperature anomaly, indicating a warmer climate in spring. Subsequently, the snow cover declined by more than 25 % in the upper subbasins. Further, higher surface soil moisture values (&gt; 0.3 m³/m³) were observed in the basin during the spring due to the rapid snow and ice melt. Furthermore, the basin received more than 200 mm of rainfall compared to the long-term average rainfall of about 98 mm, translating to about 300 % more rainfall than usual in July and August. The analysis helps understand the spatial and temporal variability within the basin and facilitates the understanding of factors and their intricate connections contributing to flooding.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102362"},"PeriodicalIF":4.7,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patterns of blue and green water in the Yellow River Basin from 1998 to 2020: Influence of climate change and human activity","authors":"Dongxue Yu ,&nbsp;Qiuan Zhu ,&nbsp;Jiang Zhang ,&nbsp;Le Wang ,&nbsp;Xiaoli Wu ,&nbsp;Shanhu Jiang ,&nbsp;Xiuqin Fang ,&nbsp;Jiaxin Jin ,&nbsp;Yanfen Wang ,&nbsp;Liliang Ren","doi":"10.1016/j.ejrh.2025.102367","DOIUrl":"10.1016/j.ejrh.2025.102367","url":null,"abstract":"<div><h3>Study region</h3><div>The Yellow River Basin in China.</div></div><div><h3>Study focus</h3><div>The hydrological cycle in the Yellow River Basin is undergoing significant changes due to the combined effects of climate change and human activities. Based the simulations of a processed model and observational data collected from official bulletins, this study focused on investigating the spatiotemporal variations of blue and green water in Yellow River basin from 1998 to 2020. Furthermore, the Partial Least Squares Structural Equation Modeling (PLS-SEM) method is used to quantify the respective contributions of climate change and human activities to these observed patterns.</div></div><div><h3>New hydrological insights for the region</h3><div>During the study period, both blue water volume and green water flow increased overall across the Basin where blue water volume and green water flow were higher in the west than in the east. Water withdrawal (including water consumption and water return flow) showed an increasing trend that mainly concentrated in the Toudaoguai (TDG) area, mainly due to increases in domestic and ecological water consumption, since water return flow showed a decreasing trend (due to decreases in agricultural and industrial water return flow). Climate change affected blue water volume and green water flows mainly through changes of precipitation (the path coefficient β &gt; 0.59). Changes in land cover were able to explain 87 % of the observed variation in water return flow and 95 % of the observed variation in water consumption and subsequently affected green water directly through water consumption (β = 0.515). Changes in land cover indirectly explained 20.9 % and 27.3 % of the variations in blue water volume and green water flow, respectively. Climate change showed greater influences on blue water volume and green water than human activities. These findings highlight the need for efficient water management in the Yellow River Basin.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102367"},"PeriodicalIF":4.7,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the dynamic changes and the effect of buoyancy of lake-terminating Yanong Glacier in the southeastern Tibetan Plateau with UAV surveys","authors":"Kunpeng Wu ,&nbsp;Tobias Bolch ,&nbsp;Pingping Cheng ,&nbsp;Francesca Baldacchino ,&nbsp;Yunpeng Duan ,&nbsp;Danyu Ma ,&nbsp;Shiyin Liu","doi":"10.1016/j.ejrh.2025.102385","DOIUrl":"10.1016/j.ejrh.2025.102385","url":null,"abstract":"<div><h3>Study region</h3><div>Yanong Glacier, a lake-terminating glacier, in the southeastern Tibetan Plateau.</div></div><div><h3>Study focus</h3><div>Previous researches had indicated higher mass loss of lake-terminating glaciers than land-terminating glaciers over the past few decades. However, the annual variability of lake-terminating glaciers, and the interaction between glaciers and lakes is still unclear. Here, we conducted two Uncrewed Aerial Vehicle (UAV) surveys to estimate the height changes and surface velocity of the tongue of lake-terminating Yanong Glacier, and try to find out the effect of proglcial lake on glacier dynamic changes.</div></div><div><h3>New hydrological insights for the region</h3><div>Results showed that the vertical uplift from buoyancy in glacier tongue causes an underestimation of mass loss of about 8 % over the entire Yanong Glacier, compared to the simulated mass balance. In addition to the vertical uplift, the buoyancy decreases the effective pressure of glacier terminus and causes more ice calving. Furthermore, the proglacial lake increases the subglacial hydrostatic pressure, resulting in a strong increase in glacier surface velocity. We estimate that the effect of the proglacial lake on glacier dynamic changes will last for more than 70 years, assuming that the proglacial lake expands at a rate of 0.1 km² a⁻¹ in the future. Overall, our study shows the importance to consider the effect of pro-glacial lakes and glacier dynamic changes in modelling and projecting glacier dynamics.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102385"},"PeriodicalIF":4.7,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143821439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}