Journal of Hydrology最新文献

{"title":"Hydrodynamic reconstruction of tidal river networks based on sensitivity analysis of responses to sluice–pump scheduling: a case study of episodic pollution control","authors":"Ming Huang,Hongwu Tang,Xianglong Wei,Xiangju Cheng,Saiyu Yuan,Qihua Ran,Fuxin Zhang,Wei He","doi":"10.1016/j.jhydrol.2026.136344","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136344","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"175 1","pages":"136344"},"PeriodicalIF":6.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148895161","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":"Rainfall selectivity in large dry heatwave events across the contiguous United States","authors":"Yajie Shi,Wei Dai,Xiangrui Xu,Yuyou Zhi,Xi Zhang,Yinglong Chen,Weijun Fu","doi":"10.1016/j.jhydrol.2026.136320","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136320","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"7 1","pages":"136320"},"PeriodicalIF":6.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148896023","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":"Climate change impacts on alpine springs in Austria: shifts in discharge seasonality and water availability","authors":"Martin Masten,Magdalena Seelig,Simon Seelig,Matevž Vremec,Thomas Wagner,Maria Obwegs,Matthias Hausleber,Jutta Eybl,Gerfried Winkler","doi":"10.1016/j.jhydrol.2026.136337","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136337","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"156 1","pages":"136337"},"PeriodicalIF":6.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148895162","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":"Groundwater discharge dominates CO2 emission with low CH4 efflux in a glacier-fed stream on the Qinghai-Tibet Plateau","authors":"Chuan Wang,Xin Dai,Sen Xu,Yueqing Xie,Yanxia Shen,Chunhui Lu,Wei Zhi","doi":"10.1016/j.jhydrol.2026.136333","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136333","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"38 1","pages":"136333"},"PeriodicalIF":6.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148895160","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":"Mapping new pre-consolidation head, safe pumping buffer, and safe pumping volume for groundwater management in post-subsidence cities: a case study from Houston, Texas","authors":"Guoquan Wang","doi":"10.1016/j.jhydrol.2026.136345","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136345","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"35 1","pages":"136345"},"PeriodicalIF":6.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148895158","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":"Organic phosphorus fractions drive microbial diversity and assembly in the largest freshwater lake in northeast Asia","authors":"Xinghong Liu,Zijian Xie,Bo Bo,Weiwei Wei,Chunhua Li,Chun Ye","doi":"10.1016/j.jhydrol.2026.136325","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136325","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"170 1","pages":"136325"},"PeriodicalIF":6.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148895159","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":"Corrigendum to “Simulation of pollutant transport and identification of longitudinal dispersion coefficient in vegetated channels based on a vegetation-constrained physics-informed neural network” [J. Hydrol. 677(Part B) (2026) 135849]","authors":"Jiao Zhang,Suyuan Zhong,Wen Wang,Zhanbin Li,Peng Li,Jieyu Liu,Mengjing Guo,Lu Jia,Mingjiang Deng","doi":"10.1016/j.jhydrol.2026.136190","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136190","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"38 1","pages":"136190"},"PeriodicalIF":6.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148895155","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":"Spatially distributed modeling of biofilm-induced hydrodynamic evolution in porous media","authors":"Hongcheng Zhang, Chaomeng Dai, Jixiang Li, Jiajun Hu, Wang Kai Tong, Jia Jie Zou, Min-tian Gao, Zhi Li, Xihua Wang, Yalei Zhang, Kah Hon Leong, Swee Pin Yeap, Araceli Martín Candilejo","doi":"10.1016/j.jhydrol.2026.136323","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136323","url":null,"abstract":"Biofilm growth in porous media significantly alters flow and transport properties in groundwater remediation, filtration and bioreactor operation, and membrane-related processes. However, most models treat biofilm zones as hydraulically uniform, neglecting internal heterogeneity and potentially compromising flow-field predictions. Here, we establish a spatially distributed framework for modeling the evolving hydrodynamics of biofilm growth in porous media by translating time-lapse biofilm images into distributed porosity and permeability fields, and evaluate it against the conventional uniform strategy. The results show that geometric heterogeneity promotes preferential colonization in narrow throats and the formation of larger pore-spanning clusters. Under the uniform strategy, multiple porosity–permeability combinations can reproduce the same bulk pressure drop and collapse onto a narrow compensation ridge (slope −11.15), revealing strong equifinality in hydraulic calibration and limited transferability of the calibrated parameters across growth stages. By contrast, the spatially distributed strategy reproduces the pressure drop evolution across growth stages. Although bulk pressure-drop calibration alone does not uniquely identify the absolute local values of <mml:math altimg=\"si7.svg\"><mml:mi>n</mml:mi></mml:math> and <mml:math altimg=\"si8.svg\"><mml:mi>k</mml:mi></mml:math>, the hydraulically admissible mappings yield effective hydraulic-property fields with broadly consistent spatial organization. Under the examined conditions, the resulting permeability distributions exhibit high-permeability tails that can be described by a Pareto-II distribution. Although both the uniform and spatially distributed strategies reproduce similar bulk pressure drops, the uniform treatment predicts more pronounced fast–slow segregation and velocity extremes. These findings establish a new framework for translating biofilm structure into hydraulically meaningful parameter fields, advancing predictive modeling of biofilm-driven hydrodynamics in porous media.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"457 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884679","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":"Predicting root-zone soil moisture using a small sample deep learning approach","authors":"Yalin Xie, Jing Tian, Yongqiang Zhang, Xuanze Zhang, Longhao Wang, Haoshan Wei, Xian Wang, Zixuan Tang","doi":"10.1016/j.jhydrol.2026.136348","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136348","url":null,"abstract":"Estimating root-zone soil moisture (RZSM) under sparse in-situ observations is closely related to the broader Prediction in Ungauged Basins (PUB) challenge. This study introduces a novel application of the Tabular Prior-data Fitted Network (TabPFN) for predicting RZSM using small sample sizes (fewer than 10,000) and evaluates its robustness under extreme data sparsity conditions. Using five-fold spatial cross-validation conducted at the grid-cell level, TabPFN was trained on sampled data, while the baseline models (RF, XGBoost, CatBoost and Tabular ResNet) were trained on both sampled and full datasets. All models were evaluated on full test sets to ensure a consistent benchmark. Our results indicate that under extremely sparse training conditions (one sample per grid), TabPFN achieves the highest prediction accuracy (R = 0.726 ± 0.002; RMSE = 0.069 ± 0.0004; MAE = 0.053 ± 0.0003), improving correlation by 2.5–9.2% and reducing prediction errors by 2.6–9.8% compared to benchmark models. In time-specific modeling, where separate models were constructed for each day, week, and month, its performance advantage was broadly maintained across changing hydro-climatic states and under consistent temporal aggregation. Its performance also remained relatively stable as training grid density decreased, including when fewer than 40% of the available training grids were used. These results demonstrate that TabPFN enables robust RZSM prediction using small samples and provides a practical tool for drought monitoring and water assessment in data-scarce or poorly monitored regions.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"19 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884676","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":"Anthropogenic dominance of water storage variability in the Yellow River Basin: A machine learning synthesis of multi-source data (1981–2031)","authors":"Yanping Cao, Zunyi Xie, Dandan Liu, Chaolin Mu, Jielun Wang, Yihao Chang, Yingjun Pang","doi":"10.1016/j.jhydrol.2026.136347","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136347","url":null,"abstract":"Water is critical to sustainable development in arid river basins such as the Yellow River Basin (YRB), where rapid population and economic growth have profoundly altered the hydrological regime. However, the historical evolution and future trajectories of water resources, together with the relative roles of natural and anthropogenic influences, remain incompletely understood, limiting effective water management and ecohydrological sustainability. Here, we integrated satellite observations, model simulations, and machine learning methods to reconstruct terrestrial water storage anomalies (TWSA) from 1981 to 2002 and forecast monthly TWSA through 2031. Our results identify a pivotal transition around 2000, when TWSA variability in the YRB shifted from being predominantly associated with climatic fluctuations to being increasingly associated with human activities. This transition was accompanied by concurrent changes in climatic and ecohydrological conditions and increasing anthropogenic pressures. Before 2000, TWSA variations were primarily associated with natural hydroclimatic fluctuations and showed only a modest decline. After 2000, socioeconomic development and large-scale ecological restoration became increasing associated with accelerated TWSA depletion. More recently, depletion moderation alongside water-conservation initiatives and increasing precipitation, although no statistically significant hydrological turning point was detected. Across three Shared Socioeconomic Pathways, residual non-climatic influences, which may include anthropogenic effects and processes not represented by the selected climatic predictors, accounted for approximately 84%–97% of the projected TWSA trends. This dominant residual contribution highlights the importance of non-climatic influences on future water storage trajectory in the basin. This study provides sustainable water management, policy, and adaptation in water-limited basins facing growing supply–demand imbalances.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"4 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884677","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}