Journal of Hydrology最新文献

{"title":"The hydrological effects of dispersed stormwater management at the catchment scale","authors":"Congying Li,Matthew J. Burns,Christopher J. Walsh,Moss J. Imberger,Peter J. Poelsma,Robert James,Darren G. Bos,Tim D. Fletcher","doi":"10.1016/j.jhydrol.2026.136546","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136546","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"37 1","pages":"136546"},"PeriodicalIF":6.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149089738","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":"Beyond better predictions: reflections on the growth, rigor, and impact of AI/ML in hydrology","authors":"Dan Lu","doi":"10.1016/j.jhydrol.2026.136211","DOIUrl":"10.1016/j.jhydrol.2026.136211","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"679 ","pages":"Article 136211"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148716455","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":"Coupling water balance and vegetation carbon dynamics in a parsimonious global hydrologic model","authors":"Guta Wakbulcho Abeshu, Hong-Yi Li, L.Ruby Leung","doi":"10.1016/j.jhydrol.2026.136520","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136520","url":null,"abstract":"Understanding ecohydrological responses to environmental change requires parsimonious models that can represent interactions between water balance and vegetation carbon uptake. Simple conceptual hydrologic models efficiently simulate runoff and evapotranspiration, but they usually lack dynamic vegetation representation. We extend the <ce:italic>abcd</ce:italic> monthly water-balance model to simulate coupled water–carbon dynamics by integrating the Horton Index framework with a two-parameter Gross Primary Productivity–Evapotranspiration (GPP–ET) functional relationship. The resulting eight-parameter framework is calibrated using observation-constrained runoff and GPP, while ET is withheld from the calibration objective and evaluated independently. Using GSWP3-W5E5 forcing, FLUXCOM-X BASE GPP and ET, and GRUN-ensemble runoff over 235 global basins, we calibrate the model for 2001–2014 and evaluate it independently for 2015–2019. During validation, the model reproduces GPP robustly, with a median Kling–Gupta Efficiency (KGE) of 0.758 and positive KGE in 97.9% of basins. ET performance is also broadly positive despite not being directly calibrated, with a median validation KGE of 0.673 and positive KGE in 87.7% of basins. Runoff skill is moderate and more heterogeneous, with a median validation KGE of 0.435 and positive KGE in 81.7% of basins. Seasonal-cycle and anomaly analyses show that the model strongly captures the climatological timing of GPP and ET while retaining meaningful anomaly skill after removing the mean annual cycle. The calibrated coupling parameters <mml:math altimg=\"si11.svg\"><mml:mi>λ</mml:mi></mml:math>, <mml:math altimg=\"si12.svg\"><mml:mi>β</mml:mi></mml:math>, and <mml:math altimg=\"si13.svg\"><mml:mi>α</mml:mi></mml:math> exhibit geographically organized patterns consistent with their physically interpretable roles in evaporative partitioning and water–carbon coupling, while <mml:math altimg=\"si12.svg\"><mml:mi>β</mml:mi></mml:math> and <mml:math altimg=\"si13.svg\"><mml:mi>α</mml:mi></mml:math> remain effective model-scale rather than intrinsic physiological coefficients. These results show that a parsimonious monthly hydrologic model can be extended to diagnose first-order coupled water–carbon dynamics while retaining interpretable structure and computational efficiency.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"24 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149087437","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 “Global mapping of potential hydropolitical system archetypes in international transboundary basins: a shift in perspective from geopolitical temperature into structural process” [J. Hydrol. (2026) 135881]","authors":"Mohammadreza Shahbazbegian, Mohammadreza Shirinzadeh","doi":"10.1016/j.jhydrol.2026.136361","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136361","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"1 1","pages":"136361"},"PeriodicalIF":6.4,"publicationDate":"2026-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149087559","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":"Drone–based camera discharge derived from the entropy–based probability concept and image velocimetry algorithms","authors":"Duncan B. Morel, Christopher A. Kirk, John W. Fulton, Frank L. Engel, Carl J. Legleiter, Brandon T. Forbes, Noah Eno, Matthew J. Nicotra, Matthew C. Gyves, Robert R. Lotspeich, Heather R. Best","doi":"10.1016/j.jhydrol.2026.136428","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136428","url":null,"abstract":"In June and August 2023, the U.S. Geological Survey (USGS) conducted small Uncrewed Aircraft System (sUAS or drone) flights at five streamgages in the Upper Colorado River Basin, Colorado, USA. The objectives of this research were (1) compare maximum surface velocities and discharges derived from Space-time Image Velocimetry (STIV) and Particle Image Velocimetry (PIV) and (2) evaluate drone-based camera algorithms that rely on the entropy-based probability concept and mid-section method relative to standard discharge measurements.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"290 1","pages":"136428"},"PeriodicalIF":6.4,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149084783","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":"An automated adaptative framework for weather data interpolation","authors":"Cédric Magain, Guillaume Renard, Philippe Orban, Aurore Degré, Jeroen Meersmans, Caroline De Clerck, Serge Brouyère, Joost Wellens","doi":"10.1016/j.jhydrol.2026.136419","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136419","url":null,"abstract":"Spatially continuous estimates of reference evapotranspiration and rainfall are crucial for environmental management applications. However, their estimation often relies on weather station measurements characterized by incomplete temporal records. Spatial interpolation methods (SIMs) address this issue but are variable and data-specific, making their selection challenging due to dynamic, unharmonized networks and missing data. Advances in computing capabilities enable automation of selection routines, allowing development of automatic SIMs selection process. Several authors proposed employing combined metrics to optimize model selection. Accordingly, this paper developed a new composite metric (CM), based on random and systematic error, integrated into an automated process, called JW<ce:italic>grid</ce:italic> (Judicious Widget for Geospatial Robust Interpolation Design or JW), to identify optimal interpolation methods across various contexts. Using Leave-One-Out Cross-Validation (LOOCV), the SIM with the lowest CM value is selected from popular interpolation techniques. The methodology was assessed on weather station networks in Luxembourg, evaluating rainfall and reference evapotranspiration related variables. Results showed low error values with SIM selection frequencies being variable dependent. The methodology’s robustness was assessed by (1) reducing data to 25, 50, and 75% of the original network size, by (2) using synthetic datasets with varying data variability, network configurations, and presence or absence of an external drift and (3) applying to a mountainous study area. Network density minimally affected overall accuracy, though SIM selection frequencies varied with no universally preferable method. In synthetic tests and the mountainous area, the JW methodology performed at least equally to the best single method by selecting the most appropriate method at every timestep. Those results highlight the proposed methodology’s advantages, producing reliable gridded datasets across diverse climatic conditions. The approach enables users with limited SIMs experience to easily generate gridded data, providing an effective solution for spatial interpolation challenges in environmental applications.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"1191 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148984872","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":"Locally relevant streamflow reanalysis using ensemble data assimilation and a gauge-based adaptive localization scheme","authors":"Ved Prakash,&nbsp;Manabendra Saharia","doi":"10.1016/j.jhydrol.2026.136277","DOIUrl":"10.1016/j.jhydrol.2026.136277","url":null,"abstract":"<div><div>Accurate, high-resolution streamflow estimates are crucial for effective water management, flood risk assessment, and mitigation planning. However, predicting streamflow using integrated hydrologic-hydrodynamic models remains challenging due to model errors and uncertainties in initial conditions. This study presents a novel streamflow Data Assimilation (DA) framework that combines Ensemble Kalman Filter (EnKF) with two key innovations: a gauge-based covariance localization derived from historical tuning aligned with a dense river network and targeted covariance inflation at gauge stations. The DA framework is implemented within a modeling chain comprising the Noah-MP land surface model and a vector-based streamflow routing model, MizuRoute, covering 553,312 river reaches across the Indian subcontinent. Results show that the assimilation framework significantly improves streamflow simulations, increasing the median Kling-Gupta Efficiency (KGE) by 0.22 and the median KGE skill score by 0.15 across both gauged and ungauged stations at the daily scale. The DA also enhances key hydrological signatures and exhibits strong performance during peak flow conditions. Notably, during peak flow events, the median probability of detection (POD) increases from 0.22 to 0.39 at gauged and from 0.16 to 0.29 at ungauged stations. The model demonstrates greater improvement in smaller catchments, which are more susceptible to flash floods. Furthermore, the mean peak flow and timing error for correctly predicted (“hit”) events are reduced by over 9% and over 1.5 days, respectively. This first-of-its-kind study in the Indian subcontinent on streamflow DA using a large-scale hydrologic-hydrodynamic model at a daily time scale offers a robust foundation for enhancing flood forecasting systems and informing sustainable water resource management under changing climate scenarios.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"679 ","pages":"Article 136277"},"PeriodicalIF":7.3,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148772878","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":"Evaporation, energy balance, and paleohydrology of the lakes along the Dead Sea rift","authors":"G. Tau,&nbsp;Y. Enzel,&nbsp;I. Sirota,&nbsp;N.G. Lensky","doi":"10.1016/j.jhydrol.2026.136226","DOIUrl":"10.1016/j.jhydrol.2026.136226","url":null,"abstract":"<div><div>Lake evaporation is a dominant yet poorly constrained component of water and energy budgets. This uncertainty critically undermines necessary paleoclimate reconstructions, particularly for terminal lakes, whose levels are considered the best direct indicators of the precise balance between catchment precipitation and evaporative losses. We address this by applying a physically grounded framework for lake evaporation based on a hybrid approach of direct measurements and theoretical analysis of lake energy-balance and its thermal-equilibrium solution, combined with calibrated bulk formulae. High-resolution data from long-term eddy-covariance measurements at three adjacent Dead Sea Rift lakes—spanning wide gradients in salinity (freshwater to hypersaline), climate (Mediterranean to hyper-arid), and thermal structure—were used to calibrate bulk formulae relating environmental forcing to heat fluxes. We show that the thermal equilibrium approach depends on the lake’s thermal response time; shallow lakes reach equilibrium at intra-annual timescales, whereas deeper stratified lakes require annual forcing. These observations, combined with accurate bulk formulae that relates to the environmental conditions, provides tools for modeling global lake evaporation using only standard environmental data and for reconstructing paleo-evaporation. Applying this framework to the Last Glacial Maximum (LGM) highstand of Lake Lisan (the Levant), we bound evaporation rates and determine that a minimum annual water inflow approximately four times greater than modern levels was required to stabilize the lake. These results indicate significantly higher precipitation in the Dead Sea watershed during the LGM.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"679 ","pages":"Article 136226"},"PeriodicalIF":7.3,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148716432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"A prototype hyper-resolution groundwater digital twin for the contiguous United States: integrating physics-based modeling, machine learning, and observations","authors":"Yueling Ma ,&nbsp;Danielle Tijerina-Kreuzer ,&nbsp;Amy Defnet ,&nbsp;Georgios Artavanis ,&nbsp;Laura E. Condon ,&nbsp;Reed M. Maxwell","doi":"10.1016/j.jhydrol.2026.135189","DOIUrl":"10.1016/j.jhydrol.2026.135189","url":null,"abstract":"<div><div>To advance large-scale hyper-resolution groundwater modeling, we leverage existing physically-based simulation results and water table depth (WTD) observations to develop a prototype groundwater digital twin for the contiguous United States (CONUS). This framework represents a continuously updatable virtual representation that integrates observations with physics-based predictions to support operational decision making. An adjusted random forest model is trained to downscale 1 km simulation results from the integrated physically-based hydrologic model ParFlow-CLM to 1 arcsec (∼30 m) and bias-correct to observations, producing daily 1 arcsec WTD and associated uncertainties across the CONUS. Trained on water year 2003 (WY2003), the model reliably estimates temporal variations in WTD at most previously unseen grid cells, achieving a median Spearman’s ρ of 0.66. Over half of the grid cells that contain continuous daily records in WY2003 exhibit good performance, with ρ ≥ 0.5. At the subbasin scale, the digital twin captures more detailed groundwater variability than ParFlow-CLM, especially in areas with strong surface–groundwater interactions. During the future time period (WY2024), the model consistently outperforms ParFlow-CLM, increasing the median ρ by 0.13. Enabled by multi-GPU computing, the digital twin generates each daily 1-arcsec resolution WTD map in approximately 35 min of GPU time, providing insights into groundwater systems across multiple scales. The success of the physics-guided machine learning (ML) digital twin highlights the advantage of combining ML and physically-based modeling in groundwater applications. This groundwater digital twin demonstrates a path toward operational capability, enabling near-real-time monitoring, scenario exploration, and decision support at unprecedented spatial resolution.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"671 ","pages":"Article 135189"},"PeriodicalIF":6.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147279112","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":"Transport and retention mechanisms of microplastics at confluence: Focus on the effect of confluence ratio","authors":"Xiaolong Li ,&nbsp;Yuhan Shen ,&nbsp;Huanjie Cai ,&nbsp;Dehong Li","doi":"10.1016/j.jhydrol.2026.135243","DOIUrl":"10.1016/j.jhydrol.2026.135243","url":null,"abstract":"<div><div>Microplastic pollution has become a major human health threat. Influenced by complex three-dimensional hydrodynamics and discharge variations, river confluences are prone to microplastic accumulation and pollution hotspots. The purpose of this study is to elucidate the mechanisms by which the confluence ratio influences microplastic transport and retention at river confluences. A CFD–DEM approach was employed to develop a three-dimensional hydrodynamic–microplastic coupling transport model for the confluence zone. The study examined the effects of different confluence ratios on microplastic trajectory deflection, polluted area, and retention efficiency. The results indicate that the confluence ratio λ significantly affects microplastic transport and retention: in terms of transport, λ shows a power-law negative correlation with the dimensionless maximum curvature <em>k</em> and a linear positive correlation with the dimensionless polluted area <em>S</em>; regarding retention efficiency, the dimensionless retention efficiency <em>E</em> in the scour and recovery zones decreases with λ following a power-law trend, while in the separation zone it exhibits a quadratic pattern, first decreasing and then increasing. Moreover, different confluence ratios correspond to different dominant retention zones: when λ &lt; 0.65, retention is dominated by the stable flow field in the downstream recovery zone; when 0.65 &lt; λ &lt; 1.61, the scour zone becomes the primary accumulation area; and when λ &gt; 1.61, retention is dominated by the separation zone due to strong recirculation and low-velocity flow fields. This study provides scientific support for the regulation of microplastic pollution at river confluences.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"671 ","pages":"Article 135243"},"PeriodicalIF":6.3,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147359942","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}