Journal of Hydrology-Regional Studies最新文献

{"title":"How have the drawdown zones of large reservoirs changed over the past two decades in China?","authors":"Jiamin Qin ,&nbsp;Shengjun Wu ,&nbsp;Zhaofei Wen","doi":"10.1016/j.ejrh.2025.102260","DOIUrl":"10.1016/j.ejrh.2025.102260","url":null,"abstract":"<div><h3>Study region</h3><div>This study focuses on the Reservoir Drawdown Zones (RDZs) of 727 large reservoirs in China.</div></div><div><h3>Study focus</h3><div>The research investigates the spatiotemporal dynamics of RDZs from 2000 to 2021, utilizing remote sensing data from the Global Surface Water Dataset (GSWD). It examines trends in RDZ area changes, their spatial distribution across major river basins, and the key drivers, including reservoir operations, climate variability, and human activity.</div></div><div><h3>New hydrological insights for the region</h3><div>According to the findings, RDZ zones constitute around 35 % of a major reservoir's maximum water surface area. Although there are significant fluctuations over time, the total area of RDZs shows an increasing trend on a temporal scale. Prior to 2015, there were some variations in the growth of RDZ areas, which were likely caused by external factors such as operating plans, early reservoir commissioning, and climate change. The capacity of reservoir operations to adjust to climate change was enhanced after 2015 due to the construction and operation of additional large reservoirs, as well as improvements in scheduling and management. As a result, RDZ regions continued to expand at a rate significantly faster than before 2015. Geographically, RDZs are primarily distributed in eastern, central, and southern China, particularly in the Songhua and Liaohe River Basins, the Yangtze River Basin, and the Pearl River Basin. From a spatial perspective, local population density, economic growth, and water resource management techniques, in addition to geographic and climatic factors, may influence the distribution patterns of RDZs across reservoirs of varying sizes. In RDZ regions, more than one-fourth of the reservoirs exhibit notable interannual changes, where climate or human activity may be the primary driving factor. This challenges the conventional wisdom that RDZ regions typically exhibit consistent interannual patterns.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102260"},"PeriodicalIF":4.7,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-reservoirs joint flood control scheduling using a two-layer hedging robust optimization method under uncertain inflows","authors":"Xinting Yu,&nbsp;Yue-Ping Xu,&nbsp;Yuxue Guo,&nbsp;Li Liu","doi":"10.1016/j.ejrh.2025.102244","DOIUrl":"10.1016/j.ejrh.2025.102244","url":null,"abstract":"<div><div>Study region: The Shifeng Creek, situated within the Jiao River basin in East China. Study focus: To address complicated contradictory relationships in multi-reservoir scheduling system, this study develops a new two-layer hedging robust optimization model (TL-HRO) for multi-reservoir scheduling by combining the hedging strategy with robust optimization. The first hedging layer of the TL-HRO model integrates critical hedging relationship that exists between flood control and power generation benefits. The flood control benefits can be subdivided into upstream and downstream benefits, which also have a hedging relationship. The second layer mainly focuses on the interaction of the scheduling for the current period with the future period. Furthermore, considering the impact of uncertain inflows on scheduling, this study employed the vine copula function to extract the multivariate spatial-temporal relationships and perform stochastic simulations. For comparison, a multi-objective robust optimization model (MORO) is constructed where multiple objectives are optimized in parallel. New hydrological insights for the region: The TL-HRO model, through iterative optimization, yielded an optimal scheduling solution that improved total benefits by roughly 58.26 %, covering both flood control and power generation. The results further demonstrated that the TL-HRO model is closer to the optimal solution than the MORO model, particularly during flood seasons, under uncertain inflow conditions. This study serves as a valuable reference for decision-makers in formulating efficient scheduling schemes during flood seasons.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102244"},"PeriodicalIF":4.7,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mass loss of Bayi Glacier in the Heihe River Basin revealed by ground-penetration radar measurements from 2006 to 2023","authors":"Xiaoguang Pang ,&nbsp;Liming Jiang ,&nbsp;Yuquan Liu ,&nbsp;Jie Pan ,&nbsp;Jinbiao Zhu ,&nbsp;Yi Liu ,&nbsp;Bo Yang ,&nbsp;Xiaoen Li ,&nbsp;Donghai Zheng ,&nbsp;Xin Li","doi":"10.1016/j.ejrh.2025.102255","DOIUrl":"10.1016/j.ejrh.2025.102255","url":null,"abstract":"<div><h3>Study region</h3><div>Bayi Glacier in the Heihe River Basin, northeast Tibetan Plateau.</div></div><div><h3>Study focus</h3><div>Glacier volume and mass balance are crucial to water supplies and human life within the basin in arid areas. This study employs aerial remote sensing and ground-penetrating radar (GPR) to conduct a comprehensive surveying on Bayi Glacier, mapping its surface and subglacial topography. Furthermore, multi-source remote sensing datasets are used to quantify the changes in glacier area and thickness from 2006 to 2023. The study aims to map the ice thickness distribution, surface and subglacial topography of Bayi Glacier, investigate the changes in glacier mass, volume, and area over the past 17 years, and analyze the influence of climate factors on the spatiotemporal changes of the glacier.</div></div><div><h3>New hydrological insights for the region</h3><div>Bayi Glacier is a low-altitude glacier, small in area but high sensitivity to climate change, with a volume of 0.1065 km³ and an area of 2.3569 km². From 2006–2023, the glacier area underwent sustained retreat, decreasing by 0.3266 km² (12.17 %). The GPR measurements collected in 2006 and 2023 revealed that the glacier thickness and volume decreased by an average of 9.04 m (16.68 %) and 0.0465 km³ (30.39 %), respectively. Rising summer temperatures led to a decrease in solid precipitation and an increase in evapotranspiration, which accelerated the ablation of Bayi Glacier. Additionally, the gentle slope of Bayi Glacier increases its exposure to solar radiation, resulting in a more negative glacier mass balance of −0.532 ± 0.0094 m/year, compared to that of the Qilian Mountains’ glaciers ( −0.366 ± 0.3417 m/year).</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102255"},"PeriodicalIF":4.7,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of long-term meteorological trends on streamflow in the Northern Murray-Darling Basin (MDB), Australia 1981–2020","authors":"Long Chu,&nbsp;John Williams,&nbsp;Ana Manero,&nbsp;R. Quentin Grafton","doi":"10.1016/j.ejrh.2025.102232","DOIUrl":"10.1016/j.ejrh.2025.102232","url":null,"abstract":"<div><h3>Study region</h3><div>The Northern Murray-Darling Basin, Australia.</div></div><div><h3>Study focus</h3><div>We estimated the impacts of meteorological trends on streamflow over a 40-year period for seven catchments in the Northern Murray-Darling Basin (NMDB), Australia.</div></div><div><h3>New hydrological insights for the region</h3><div>We found that meteorological trends over the 1981–2020 period explain all the streamflow decline in catchments with little or no irrigation withdrawals, whereas in catchments with substantial irrigation water withdrawals meteorological trends explained only about half the observed decline in streamflow. If the increase in water withdrawals for irrigation over the 2006–2020 period relative to 1981–2000 had, instead, been reallocated to mitigate declines in streamflow over the 1981–2000 period, the average annual gross value of irrigated agriculture (GVIA) in the NMDB would have been reduced by 9–14 %. If a water reallocation over the 2006–2020 period had been undertaken to maintain the same mean ratio of irrigation water withdrawals to streamflow over the 1980–2000 period, GVIA would have declined by 19–29 %. Our results highlight the importance of quantifying and partitioning the effects of long-term meteorological trends on streamflow in semi-arid and arid environments to improve water planning and allocation.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102232"},"PeriodicalIF":4.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal evolution of droughts and floods in the Yellow River Basin: A novel approach combining CMADS-L evaluation, hydroclimatic zonation and CNN-LSTM prediction","authors":"Xianyong Meng ,&nbsp;Chen Lin ,&nbsp;Jianli Ding ,&nbsp;Guoqing Wang ,&nbsp;Jianyun Zhang ,&nbsp;Hao Wang ,&nbsp;Chengbin Chu","doi":"10.1016/j.ejrh.2025.102250","DOIUrl":"10.1016/j.ejrh.2025.102250","url":null,"abstract":"<div><h3>Study Region</h3><div>Yellow River Basin, China, a region of critical ecological and economic significance.</div></div><div><h3>Study Focus</h3><div>This research presents a novel integrated framework for regional drought-flood analysis and precipitation forecasting by evaluating CMADS-L and ERA5 reanalysis datasets against ground-based observations in the Yellow River Basin. We implement K-means clustering on Standardized Precipitation Evapotranspiration Index (SPEI) sequences to identify drought-flood regions and validate a CNN-LSTM hybrid model for regional precipitation forecasting, uniquely bridging traditional climate analysis with modern deep learning techniques for enhanced prediction accuracy.</div></div><div><h3>New Hydrological Insights for the Region: Our Analysis Reveals</h3><div>(1) CMADS demonstrates superior performance over ERA5 in precipitation representation (r = 0.93 vs 0.92; MAE: 9.6 mm vs 17.5 mm; RMSE: 15.8 mm vs 25.9 mm), providing the first comprehensive evaluation of these datasets in complex terrain; (2) We identify three distinct hydroclimatic zones: Northeast (31.6 % area, \"wet-dry-wet\" sequences, quasi-4.5-year oscillations), Southeast (42.5 %, post-2000 drying trends, quasi-2.3-year cycles), and Western (25.9 %, post-2008 drying, quasi-12-year periodicities); (3) Our novel CNN-LSTM hybrid model achieves unprecedented prediction performance (R²: 0.70–0.85), with highest accuracy in the Western zone due to stable precipitation patterns. This integrated approach significantly advances regional hydroclimate understanding and provides a robust, transferable framework for water resource management under changing climate conditions, offering valuable methodological insights for similar river basins globally.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102250"},"PeriodicalIF":4.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiobjective risk-based optimization for real-time interbasin water diversion under decomposed chance-constrained total water use","authors":"Ran Mo ,&nbsp;Bin Xu ,&nbsp;Jianyun Zhang ,&nbsp;Guoqing Wang ,&nbsp;Ping-an Zhong ,&nbsp;Huili Wang ,&nbsp;Lingwei Zhu ,&nbsp;Jiaying Tan","doi":"10.1016/j.ejrh.2025.102252","DOIUrl":"10.1016/j.ejrh.2025.102252","url":null,"abstract":"<div><h3>Study Region</h3><div>The eastern route of the South-to-North Water Diversion Project in Jiangsu Province, China, a critical national interbasin water diversion system for alleviating water shortages.</div></div><div><h3>Study Focus</h3><div>This study proposed a risk-based multiobjective optimization model for interbasin water diversion, with chance constraint on total water use. Probabilistic forecasting of local streamflow and water demand was adopted to identify operation risks. Multiobjective stochastic optimization was then introduced to minimize the risks of water shortages and spillages. Furthermore, a decomposition method was proposed to investigate the regime of water use under different hydrological conditions, and the decomposed chance constraint was incorporated into the optimization model. Finally, two indices were designed to assess the value of forecasts and water utilization efficiency.</div></div><div><h3>New Hydrological Insights for the Region</h3><div>Developing a robust and efficient water diversion strategy based on forecast information is crucial. The proposed method with case study provides the following new hydrological insights: (1) conflict occurs between water diversion, spillage, and shortage, with water shortage and diversion representing major contradictions. (2) high-skilled forecasting helps reduce water diversion (22.3 %), spillage (over 60 %), and shortage (approximately 10 %), indicating considerable value for promoting the benefits of water diversion operations. (3) water use constraint focuses restricting excessive water diversion (30.8 %), exploiting the potential of local water supply, increasing in local water utilization efficiency from 92.8 % to 93.4 %.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102252"},"PeriodicalIF":4.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of drainage efficiency via street inlets under the influence of terrain slope in the course of pluvial urban flood event","authors":"Yun Xing ,&nbsp;Dong Shao ,&nbsp;Yifan Yang ,&nbsp;Qigen Lin ,&nbsp;Zhonghou Xu","doi":"10.1016/j.ejrh.2025.102243","DOIUrl":"10.1016/j.ejrh.2025.102243","url":null,"abstract":"<div><div><em>Study region:</em> This study is conducted in the northern urbanized region of Fuzhou City, China.</div><div><em>Study focus:</em> This study aims to conduct an investigation into the evolution of drainage efficiency via street inlets over the course of flood events in urbanized areas. Specific emphasis is placed on elucidating the influences imparted by variance in terrain slope, together with the revelation of the underlying mechanisms by which urban terrain slopes influence the dynamics of floodwater in the vicinity of street inlets.</div><div><em>New hydrological insights for region:</em> This study views the drainage efficiency in urbanized area as dynamic variable rather than static parameter and quantify the impacts of terrain slope during different stages of rainfall event. Through hydrodynamic modeling, the responses of drainage effects via street inlets to terrain slope changes in urbanized area are examined. Delayed peak responses in drainage efficiency under steeper terrain slope conditions are revealed, attributable to increased flood flow velocities bypassing street inlets. Localized flow fields demonstrate discernible terrain slope influence upon drainage functionality, with gravity-dominated directional flows disrupting inlet drainage above certain slope threshold. Data-driven regression captures distinct correlation of drainage efficiency with terrain slope and rainfall timing, enabling accurate event-scale predictions for specific urbanized area. The analysis provides novel insights into how terrain slope alters the floodwater flow on urban surface, leading to significant influence on functioning of street inlets.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102243"},"PeriodicalIF":4.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Significant differences in terrestrial water storage estimated by four common methods","authors":"Anqi Niu ,&nbsp;Long Sun ,&nbsp;Ranhao Sun ,&nbsp;Liding Chen","doi":"10.1016/j.ejrh.2025.102238","DOIUrl":"10.1016/j.ejrh.2025.102238","url":null,"abstract":"<div><h3>Study region</h3><div>The Yellow River headwaters, located in the northeastern part of the Tibetan Plateau.</div></div><div><h3>Study focus</h3><div>Terrestrial water storage can be estimated by multiple approaches. However, the limited quantification of these methods regarding terrestrial water storage stocks limits the assessment of their applicability. Here, we quantified and compared water storage and its spatial patterns by four common methods: SWAT, InVEST, WB (based on water balance theory), and RSI (remotely sensed inversion).</div></div><div><h3>New hydrological insights for the region</h3><div>The results showed that SWAT, InVEST, and WB captured remarkable spatial heterogeneity of water storage, with CV (coefficient of variation) being 57.8 %, 41.2 %, and 85.2 %, respectively, whereas the CV of RSI was only 12.5 %, with WB exhibited the most spatial heterogeneity. RSI showed a pronounced distinct spatial pattern compared to the other three methods. Precipitation and NDVI (p &lt; 0.01) are the common main drivers for all methods except RSI. The discrepancies in water storage can be attributed to the differences in models or methods response to influencing factors, e.g., the effects of topography and land use on water storage are considered to varying degrees. The biases or errors in the average water storage caused by different methods across various years range from 90.3 mm to 136.3 mm. Consequently, it is critical to consider the applicability of the methodology, especially considering different climatic, land use, soil, and topographic environments.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102238"},"PeriodicalIF":4.7,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rainfall-runoff generation patterns and key influencing factors in the plain of the Taihu Lake Basin, China","authors":"Pingnan Zhang ,&nbsp;Gang Chen ,&nbsp;Chuanhai Wang ,&nbsp;Pengxuan Zhao ,&nbsp;Lanlan Li ,&nbsp;Jingyi Cao ,&nbsp;Youlin Li","doi":"10.1016/j.ejrh.2025.102247","DOIUrl":"10.1016/j.ejrh.2025.102247","url":null,"abstract":"<div><h3>Study Region</h3><div>The two field runoff experimental sites, Baitaqiao and Wangmuguan, are located in the plains of the Taihu Basin, China.</div></div><div><h3>Study Focus</h3><div>This study investigates the hydrological cycle mechanisms in the Taihu Basin plains, aiming to support the development of next-generation, physically-based, refined hydrological models. Two experimental sites were established to comprehensively monitor hydrometeorological variables, including rainfall, evaporation, groundwater depth, soil water content, outlet flow, and other hydrological and meteorological factors. The study analyzes runoff processes and patterns under varying rainfall amounts and intensities, and examines the impacts of rainfall, groundwater depth, and micro-topography on runoff generation. Additionally, existing Taihu Basin models were used to simulate the rainfall-runoff process, with a focus on model errors and the significant role of rainfall-runoff patterns and micro-topography in the hydrological cycle.</div></div><div><h3>New Hydrological Insights for the Region</h3><div>This study provides a comprehensive clarification of the parameters for the saturation-excess runoff model in humid agricultural plains, offering valuable references for the calibration of hydrological models in similar regions. While the saturation-excess runoff model predominates in the Taihu Basin, the research also identifies the occurrence of infiltration-excess and mixed runoff mechanisms under specific conditions, thus highlighting the limitations of relying solely on the saturation-excess runoff model. Furthermore, the study demonstrates the significant impacts of rainfall amount, rainfall intensity, groundwater depth, and microtopography on rainfall-runoff processes. Through a mechanistic analysis of these factors, the findings provide a theoretical foundation for the refinement of physically based, fine-scale hydrological cycle models, advancing the understanding of hydrological processes and supporting future model development in plain areas.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102247"},"PeriodicalIF":4.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving trans-regional hydrological modelling by combining LSTM with big hydrological data","authors":"Senlin Tang ,&nbsp;Fubao Sun ,&nbsp;Qiang Zhang ,&nbsp;Vijay P. Singh ,&nbsp;Yao Feng","doi":"10.1016/j.ejrh.2025.102257","DOIUrl":"10.1016/j.ejrh.2025.102257","url":null,"abstract":"<div><h3>Study region</h3><div>Lancang-Mekong River Basin (LMRB), Brazil.</div></div><div><h3>Study focus</h3><div>Streamflow prediction in ungauged basins is a significant challenge in hydrology. This study investigates the transferability of deep learning models for hydrological simulations in ungauged basins, focusing on how constraints like catchment attributes, meteorological forcing, and Global Hydrological Models (GHMs) improve model performance when transferring knowledge from gauged to ungauged basins. We applied the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS-BR) dataset alongside GHMs and deep learning techniques to simulate hydrological processes in the LMRB.</div></div><div><h3>New hydrological insights for the region</h3><div>The results demonstrate that a post-processing scheme combining deep learning, meteorological data, and GHMs significantly improves model accuracy, achieving a median Nash-Sutcliffe Efficiency (NSE) of 0.64, compared to 0.50 for the baseline Long Short-Term Memory (LSTM) model without GHMs. Key factors influencing model performance include catchment attributes, climate variations, and the length of the modelling series. A notable finding is the importance of catchment attributes in defining hydrological similarity, which enhances model migration between regions with differing data availability. Cross-regional migration was particularly successful when hydrological similarities between the Amazon Basin and LMRB were evaluated, achieving an NSE of 0.86 at the Pakse hydrological station. These insights provide a novel modelling framework for hydrological simulations in data-scarce regions, emphasizing the role of physical mechanisms and hydrological similarities in improving model transferability.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"58 ","pages":"Article 102257"},"PeriodicalIF":4.7,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}