Journal of Hydrology-Regional Studies最新文献

{"title":"Optimizing snow property forecasts over the tibetan plateau through hybrid assimilation of satellite precipitation and water vapor radiances using WRF model configured with Noah-MP","authors":"Jing Ren ,&nbsp;Chunlin Huang ,&nbsp;Jinliang Hou ,&nbsp;Ying Zhang ,&nbsp;Ling Yang","doi":"10.1016/j.ejrh.2025.102334","DOIUrl":"10.1016/j.ejrh.2025.102334","url":null,"abstract":"<div><h3>Study region</h3><div>The Eastern region of the Qinghai-Tibet Plateau (EQTP)</div></div><div><h3>Study focus</h3><div>A regional numerical weather prediction and data assimilation system is constructed to investigate the impact of assimilating Global Precipitation Measurement (GPM) precipitation and Himawari-8/Advanced Himawari Imager (AHI) water vapor radiance using Weather Research and forecast (WRF) model and Four-dimensional variational assimilation (4Dvar) method on snow properties predictions. The predictions were compared with some reference datasets, including MODIS、VIIRS、GLDAS and ERA5-land.</div></div><div><h3>New hydrological insights for the region</h3><div>DA_G&amp;A showed a significant increase in deep snow area (SD &gt;15 cm), and a decrease in shallow snow area (SD&lt;5 cm). Comparing with some reference datasets, the predictions exhibit good physical consistency between snow parameters and fine temporal-spatial resolution. The forecasts are found to be reliable and reasonable. However, Noah-MP coupled in WRF tends to overestimate SCF and SAL, which is largely attributed to the limitations of the associated parameterization schemes. These findings highlight the assimilation of atmospheric data can improve the forecasting of snow properties. However, in Noah-MP, there remains significant uncertainty in the snow-related parameterization schemes and initial conditions.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102334"},"PeriodicalIF":4.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704566","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":"Assessment of future water availability and seasonal patterns of dry seasons under climate change in Cidanau Watershed Banten Province, Indonesia","authors":"Septian Fauzi Dwi Saputra ,&nbsp;Budi Indra Setiawan ,&nbsp;Chusnul Arif ,&nbsp;Satyanto Krido Saptomo ,&nbsp;Atiqotun Fitriyah ,&nbsp;Tasuku Kato","doi":"10.1016/j.ejrh.2025.102344","DOIUrl":"10.1016/j.ejrh.2025.102344","url":null,"abstract":"<div><h3>Study region</h3><div>Cidanau Watershed, Banten Province, Indonesia, features a natural wetland (caldera) surrounded by mountains.</div></div><div><h3>Study focus</h3><div>The SWAT was employed to assess future hydrological changes in water availability and seasonal patterns of dry seasons in Cidanau watershed. The dry season was determined when the rate of cumulative evapotranspiration was higher than the rate of cumulative rainfall. Using 2002 – 2021 data as a baseline, future projections were evaluated for 2030 s, 2050 s, 2070 s, 2090 s. The SWAT model has been edited with wetland input parameters and calibrated with river channel and watershed parameters.</div></div><div><h3>New hydrological insights</h3><div>1) The SWAT model performance marginally improved after incorporating wetland input and river channel parameters in parameterization process; 2) Projected increase in mean Tmin &amp; Tmax range from 0.5°C to 2.9°C, while mean annual rainfall is expected to decrease by −7 %– –10.3 % compare to the baseline periods; 3) As the result, the annual water yield is projected to decline by –11 % – –26 %, with the rainy season experiencing the most significant reduction; 4) The length of dry seasons is projected to increase, further impacting water availability; 5) Additionally, the frequency of extended dry seasons is expected to increase under future climate scenarios. This study highlights the anticipated decline in water availability and shifting dry season pattern, supporting decision-maker in developing adaptive and mitigation strategies for future climate challenges.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102344"},"PeriodicalIF":4.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714630","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":"Impact of vegetation restoration on preferential flow and soil infiltration capacity in the hilly region of the Loess Plateau","authors":"Shuyu Zhang ,&nbsp;Yuanhao Liu ,&nbsp;Mingyue Yang ,&nbsp;Peng Tian ,&nbsp;Xingmin Mu ,&nbsp;Guangju Zhao","doi":"10.1016/j.ejrh.2025.102333","DOIUrl":"10.1016/j.ejrh.2025.102333","url":null,"abstract":"<div><h3>Study region</h3><div>The Zhifanggou Watershed, a typical watershed in the hilly region of Loess Plateau in China.</div></div><div><h3>Study focus</h3><div>Assessing effects of various vegetation types on soil water infiltration facilitates understanding of soil hydrological processes and provides valuable references for reforestation in arid areas. Double-ring infiltrometers and dye tracing were employed across plots with various vegetation types and restoration durations to comprehensively investigate the impact of vegetation restoration on soil infiltration capacity, preferential flow, and their influencing factors.</div></div><div><h3>New hydrological insight for the region</h3><div>The results showed that the highest stable infiltration rate occurred in 30-year-old replanted monoculture forestland (0.57 cm min⁻¹), followed by 30-year-old replanted shrubland (0.42 cm min⁻¹). Monocultured forestland had slightly higher soil infiltration rates than mixed forestland, with macropore flow was dominant. Mixed forestlands exhibited the highest degree of preferential flow and the most preferential flow paths. Soil infiltration capacity and preferential flow paths increased with restoration years, and preferential flow was promoted in deeper soil layers. Soil macroporosity, clay content, and root length density predominantly influenced soil infiltration capacity and dye-stained characteristics parameters. Root characteristics were critical for the degree of preferential flow, with rock fragment and cracks also being not negligible factors. These findings could deepen our understanding of vegetation restoration in improving soil hydrological functions, and provide a reference for the management of vegetation restoration.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102333"},"PeriodicalIF":4.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697254","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":"Spatio-temporal dynamics of water quality and land use in the Lake Dianchi (China) system: A multi-source data-driven approach","authors":"Xinyu Wang ,&nbsp;Yawen Wu ,&nbsp;Samuel A. Cushman ,&nbsp;Cheng Tie ,&nbsp;Gillian Lawson ,&nbsp;László Kollányi ,&nbsp;Guifang Wang ,&nbsp;Jian Ma ,&nbsp;Jingli Zhang ,&nbsp;Tian Bai","doi":"10.1016/j.ejrh.2025.102341","DOIUrl":"10.1016/j.ejrh.2025.102341","url":null,"abstract":"<div><h3>Study region</h3><div>Lake Dianchi, China.</div></div><div><h3>Study focus</h3><div>Urbanization and land development increasingly challenge water quality, yet their interactions remain unclear. This study examines these interactions in Lake Dianchi by developing an empirical water quality inversion model. Multi-year water quality data from monitoring stations were integrated with Landsat 8 L2 data to analyze seven key Water Quality Parameters (WQPs): TP, Hg, Cd, As, Zn, S, and NH₃-N. Land use was assessed using a multi-dimensional framework incorporating weighted overlays of multi-source data. The relationships between land use and water quality were analyzed using Spearman correlation, redundancy analysis (RDA), and the Optimal Parameter Geodetector (OPGD).</div></div><div><h3>New hydrological insights for the region</h3><div>From 2014–2022, pollutant concentrations declined, yet TP pollution remains severe, keeping the lake classified as Class V. Pollution was more concentrated in Caohai than Waihai, highlighting point-source pollution. Land use changes were dominated by “urban expansion” and the “returning farmland to forest” program. RDA results indicated that construction (positive) and farmland (negative) were the primary drivers of WPI. OPGD analysis showed that FACI∩CACI was the strongest explanatory factor for WPI. Over time, land use influence on WPI weakened due to urban saturation, environmental policies, and delayed water quality responses. These findings quantify land use-water quality interactions and provide insights for managing urban plateau lakes amid rapid development.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102341"},"PeriodicalIF":4.7,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704565","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":"Examining the complexity of discharge-suspended sediment behaviour of a tropical monsoon-dominated river, India","authors":"Balai Chandra Das ,&nbsp;Aznarul Islam ,&nbsp;Sadik Mahammad ,&nbsp;Edris Alam ,&nbsp;Abu Reza Md Towfiqul Islam ,&nbsp;Biplab Sarkar ,&nbsp;Suman Deb Barman ,&nbsp;Subodh Chandra Pal ,&nbsp;Md Kamrul Islam","doi":"10.1016/j.ejrh.2025.102335","DOIUrl":"10.1016/j.ejrh.2025.102335","url":null,"abstract":"<div><h3>Study region</h3><div>Multiple gauging stations of the Brahmani River Basin, India.</div></div><div><h3>Study focus</h3><div>This study provides an understanding of sediment transport complexities in monsoon-type rivers and supports informed decision-making for effective river management and environmental conservation. It also underscores the impact of surface landscape, the management of reservoirs and the role of anthropogenic impacts on sediment transport dynamics.</div></div><div><h3>New hydrological insights for the region</h3><div>River discharge and sediment concentration are measured at four gauging stations of Brahmani River: Tilga, Panposh, Gomlai, and Jenapur. The first three are located in the upper reaches above the Rengali Dam, while Jenapur is in the plain area below the dam. The analysis reveals diverse correlations for fine sediment (&lt;0.075 mm), ranging from linear at Tilga to logarithmic at Panposh and power-law at Gomlai. Medium sediment (0.075–0.2 mm) exhibits linear and logarithmic correlations at Tilga and Panposh while coarse sediment (&gt;0.2 mm) displays logarithmic correlations at Panposh and Gomlai. Total sediment concentrations showcase both linear and logarithmic relationships at Tilga and Panposh, indicating the complexity of sediment-transport dynamics. The study unveils compelling relationships between river discharge and total sediment load (MT/day), with notable power-lla correlations at Gomlai, emphasising the influence of river discharge variations on sediment transport quantity. It underscores the impact of surface geology, the location of reservoirs and the role of anthropogenic interventions on sediment dynamics.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102335"},"PeriodicalIF":4.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681584","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":"Enhancing the accuracy and generalizability of reference evapotranspiration forecasting in California using deep global learning","authors":"Arman Ahmadi ,&nbsp;Andre Daccache ,&nbsp;Minxue He ,&nbsp;Peyman Namadi ,&nbsp;Alireza Ghaderi Bafti ,&nbsp;Prabhjot Sandhu ,&nbsp;Zhaojun Bai ,&nbsp;Richard L. Snyder ,&nbsp;Tariq Kadir","doi":"10.1016/j.ejrh.2025.102339","DOIUrl":"10.1016/j.ejrh.2025.102339","url":null,"abstract":"<div><h3>Study region</h3><div>This research focuses on the Central Valley of California, a climatically homogeneous region known for its significant agricultural productivity and reliance on extensive irrigation. Our study utilizes monthly reference evapotranspiration (ET_O) time series data from 55 standardized weather stations as part of the California Irrigation Management Information System (CIMIS).</div></div><div><h3>Study focus</h3><div>ET_O is a critical component of regional water cycles, indicating atmospheric water demand. This study evaluates the potential of deep learning (DL) models for ET_O forecasting, particularly emphasizing the efficacy of a global learning scheme compared to traditional local learning. Global learning involves training forecasting models on pooled data from multiple time series, tested over new instances. We compared the performance of statistical models and advanced DL models, demonstrating significant accuracy enhancements in global learning schemes. We also explored automatic hyperparameter optimization for these models to achieve state-of-the-art forecasting accuracy, yielding RMSE values below 10 mm/month for one-year-ahead forecasts on new, unseen stations.</div></div><div><h3>New hydrological insight for the region</h3><div>Applying global learning methodologies to DL models markedly improved forecasting performance, showcasing an ability to generalize findings to ungauged regions and even newly established weather stations. This suggests a promising avenue for enhancing water resource management efficiency in data-scarce areas. Our findings argue that such data-centric methodological shifts could play a critical role in better managing the irrigation demands of the Central Valley, thereby supporting sustainable water usage and agricultural productivity in the region.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102339"},"PeriodicalIF":4.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696929","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":"Enhancing runoff simulation by combining superflex with deep learning methods in China's Qinghai Lake Basin, Northeast Tibetan Plateau","authors":"Kaixun Liu ,&nbsp;Na Li ,&nbsp;Sihai Liang","doi":"10.1016/j.ejrh.2025.102331","DOIUrl":"10.1016/j.ejrh.2025.102331","url":null,"abstract":"<div><h3>Study region</h3><div>The Qinghai Lake Basin on the Northeast Tibetan Plateau.</div></div><div><h3>Study focus</h3><div>Coupling physical models with deep learning methods offers potential advantages for runoff simulation, optimizing their interaction remains a crucial challenge. This study investigates hybrid models combining the Superflex hydrological model with Gated Recurrent Unit (GRU) for runoff modeling and simulation in the Qinghai Lake Basin. Our approach leverages Superflex as a pre-training step for the neural networks and incorporates key process variables from the physical model as inputs to the network, creating a physically-driven deep learning framework. We systematically explore various input-output combinations and selections of deep learning models, and comprehensively evaluated the most effective configuration for this specific basin. Furthermore, we use the SHAP method to reveal how meteorological factors influence runoff and their complex relationships, making the results interpretable.</div></div><div><h3>New hydrological insights for the region</h3><div>Compared to hydrological model, hybrid models significantly improve performance by incorporating internal hydrological variables and meteorological data as input features, reducing the error by over 50 % in Buha River Basin. We further observed that although different deep learning architectures exhibit varying performance outcomes, the GRU-based models consistently demonstrated significantly superior predictive capabilities. In addition, we use SHAP to understand the internal operation of the model, revealing how meteorological factors affect runoff and their complex relationships, successfully unveiling the \"black box\" nature of deep learning models.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102331"},"PeriodicalIF":4.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696928","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":"Method for identifying non-stationary hydrological drought in regions with intense human activities","authors":"Minhua Ling ,&nbsp;Jiawei Yao ,&nbsp;Cuimei Lv ,&nbsp;Erwei Zheng ,&nbsp;Xingyu Chu","doi":"10.1016/j.ejrh.2025.102330","DOIUrl":"10.1016/j.ejrh.2025.102330","url":null,"abstract":"<div><h3>Study region</h3><div>the middle reaches of the Yellow River Basin (MYRB).</div></div><div><h3>Study focus</h3><div>In regions with intense human activities, the stationarity of runoff sequences was disrupted due to the dual impacts of climate changing and human activities. Therefore, establishment of non-stationary hydrological drought identification methods is urgently required. Previous research infrequently addressed the influence of indirect human activities on the non-stationary hydrological drought. This study comprehensively considered the impacts of climate change, direct human activities, and indirect human activities (underlying surface alterations) on runoff. Consequently, a non-stationary standardized runoff index (NSRI) was constructed based on the Generalized Additive Models for Location, Scale, and Shape, establishing a method for identifying non-stationary hydrological droughts in regions with intense human activities.</div></div><div><h3>New hydrological insights for the region</h3><div>This study uncovered the variability in hydrological drought characteristics in the major sub-basins of the MYRB, where human activities are intense, from 1960–2019.The results demonstrate that the non-stationary hydrological drought identification method constructed in this paper is feasible. The NSRI exhibits superior performance in identifying hydrological drought events across multiple timescales compared with the Standardized Runoff Index. In many sub-basins, the frequency of severe and extreme droughts across various time scales increased, with upward trends measured in both drought severity and intensity. The severity of hydrological drought in the MYRB may further intensify in the future.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102330"},"PeriodicalIF":4.7,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681531","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":"Estimating the groundwater table threshold for mitigating soil salinization in the Songnen Plain of China","authors":"Yiding Ding ,&nbsp;Haishen Lü ,&nbsp;Ligang Xu ,&nbsp;Robert Horton ,&nbsp;Mingliang Jiang ,&nbsp;Yonghua Zhu ,&nbsp;Junxiang Cheng ,&nbsp;Hongxiang Fan ,&nbsp;Jianbin Su","doi":"10.1016/j.ejrh.2025.102326","DOIUrl":"10.1016/j.ejrh.2025.102326","url":null,"abstract":"<div><h3>Study region</h3><div>The Songnen Plain is a key part of China’s largest plain, situated in northeastern China.</div></div><div><h3>Study focus</h3><div>Soil salinization has become one of the largest ecological issues in the Songnen Plain, and regulating groundwater levels is a crucial strategy for mitigating it. To address this, a comprehensive framework is developed to estimate the groundwater table threshold for soil salinization by integrating field sampling, remote sensing big data, and machine learning models.</div></div><div><h3>New hydrological insights for the region</h3><div>The soil salinity inversion model, which utilizes a random forest algorithm, achieves the highest accuracy (R² = 0.75, d = 0.94, RPD = 2.05), outperforming SVM, LightGBM, and XGBoost algorithms. From 2020–2023, areas with mild salinization accounted for 9.3 % of the total area, while moderate salinization accounted for 3.2 %, severe salinization accounted for 4.0 %, and saline soil areas accounted for 0.6 %. A probabilistic model further identifies groundwater depth thresholds for salinization: 2.3 m for sandy soil, 3.1 m for loamy soil, and 1.1 m for silty soil. Based on current groundwater depths, it is anticipated that 15.5 % of the Songnen Plain area will continue to be affected by soil salinization or remain at risk of potential salinization.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102326"},"PeriodicalIF":4.7,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681530","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":"Earlier vegetation green-up is intensifying hydrological drought in the Tianshan Mountain basins","authors":"Lilin Zheng ,&nbsp;Ruishan Chen ,&nbsp;Jianhua Xu ,&nbsp;Yinshuai Li ,&nbsp;Nan Jia ,&nbsp;Xiaona Guo","doi":"10.1016/j.ejrh.2025.102321","DOIUrl":"10.1016/j.ejrh.2025.102321","url":null,"abstract":"<div><h3>Study region</h3><div>Two inland basins in the Tianshan Mountains: the Huangshui Basin (HSB) and the Kashi Basin (KSB).</div></div><div><h3>Study focus</h3><div>Earlier green-up driven by climate warming can profoundly alter hydrological processes. However, the isolated impact of phenological changes on hydrological dynamics, independent of climatic factors, remains largely unexplored. To address this gap, we quantified the contributions of earlier green-up to evapotranspiration (ET) and basin streamflow by developing a framework that integrates an NDPI-based phenology model with the RHESSys eco-hydrological model.</div></div><div><h3>New hydrological insights for the region</h3><div>Between 2001 and 2020, the start of the growing season (SOS) advanced at rates of 1.02 days/year in HSB and 0.97 days/year in KSB, while changes in the end of the growing season were minimal (0.17 and − 0.12 days/year, respectively). In HSB, each one-day advancement in green-up increased ET by 2.22 mm and reduced streamflow discharge by 2.35 million m³. In contrast, in KSB, a one-day advancement in green-up resulted in a more significant increase in ET (11.22 mm) and a more substantial reduction in streamflow discharge (58.24 million m³). KSB's westward-facing topography facilitates the inflow of warm, humid Atlantic air, contributing to a more humid climate, higher vegetation cover, and an earlier SOS compared to HSB. These findings highlight the importance of incorporating phenological dynamics into eco-hydrological assessments to develop effective climate adaptation strategies for inland mountain basins.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"59 ","pages":"Article 102321"},"PeriodicalIF":4.7,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143681471","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}