Journal of Hydrology最新文献

{"title":"Multi attribute refined identification of flood-affected bodies based on multi-source data fusion","authors":"Yutie Jiao ,&nbsp;Zongkun Li ,&nbsp;Wei Ge ,&nbsp;Meimei Wu ,&nbsp;Bo Wang ,&nbsp;Yadong Zhang ,&nbsp;Pieter van Gelder","doi":"10.1016/j.jhydrol.2026.135104","DOIUrl":"10.1016/j.jhydrol.2026.135104","url":null,"abstract":"<div><div>Lands and populations are the most direct and core disaster-bearing bodies in floods. Accurate and comprehensive identification their attributes is critical for differentiated flood prevention and mitigation strategies. However, two key challenges persist in current practices. First, the accuracy of urban land function (ULF) identification based on machine learning is constrained by data and grid scale, yet research on their impacts remains insufficient. Second, location-based service (LBS) data has sampling bias and nighttime distortion in characterizing dynamic population distribution, and its spatial resolution is insufficient for high-precision flood simulations. For ULF identification, abundant comparison schemes are generated through data traversal and multi-scale fusion, and an ensemble learning model is constructed to select the optimal ULF identification scheme. This avoids the accuracy uncertainty caused by subjective selection, and the results provide reliable data support for economic loss assessment and subsequent population spatial interpolation. For dynamic population distribution, a human-land relationship matching method based on spatiotemporal behavioral laws is proposed to reduce the impact of data bias. Meanwhile, spatial downscaling is achieved through regional division, land type and area weight calculation, generating dynamic population distribution maps with high spatiotemporal resolution. The results support the analysis of population mobility’s impact on flood risk. Hydraulic simulation is coupled with GIS (geographic information system) analysis to construct a grid-based diagnostic framework for multi-attributes of disaster-bearing bodies, including land function, population size, water depth, and spatial location. Case studies show that this framework provides reliable support for the accurate and comprehensive identification of flood disaster-bearing bodies.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135104"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146138394","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":"Multiscale simulation and machine learning sensitivity analysis of pore-structure controls on solute transport in heterogeneous porous media","authors":"Sida Jia ,&nbsp;Yuyang Huang ,&nbsp;Junjun Chen ,&nbsp;Zhongjun Ma ,&nbsp;Jian Tian ,&nbsp;Zhenxue Dai","doi":"10.1016/j.jhydrol.2026.135043","DOIUrl":"10.1016/j.jhydrol.2026.135043","url":null,"abstract":"<div><div>Subsurface solute transport processes are strongly governed by the morphology of the porous media that the solute passes through. Quantifying the dynamic mechanisms of subsurface solute transport across different spatial scales remains a challenge. This study developed an innovative deep learning (DL) based multiscale modeling framework that integrated physics-based Finite Element Method (FEM) simulations with DL to link pore-scale structural parameters directly to macroscopic solute transport characteristics. High-fidelity datasets of velocity fields and concentration breakthroughs were generated by solving the Navier-Stokes and advection–dispersion equations, providing a rigorous basis for benchmarking three DL architectures: ResNet, U-Net, and a hybrid U-Net Transformer. The optimal surrogate model, which achieved a significant speedup of over five orders of magnitude (10⁵×) compared to FEM, was coupled with Sobol global sensitivity analysis and DL assisted regression. This integrated approach not only quantifies the individual impacts of microscopic geometric features such as porosity, pore size, connectivity, and tortuosity on macroscopic transport parameters and breakthrough curves (BTCs) characteristics, but also derives approximate quantitative relationships linking pore-scale microstructures to their corresponding macroscopic transport responses. Systematic sensitivity analysis revealed cross-scale controlling mechanisms; throat size played a dominant role in controlling solute transport and adsorption behavior, and microscopic geometric features exhibited high sensitivity to dispersion coefficient. Temporal dynamics analysis indicated that the minimum pore-throat diameter determined the breakthrough time, and nucleation density influenced the initial solute arrival. Moreover, quantitative relationships between key parameters were established through individual-parameter effect analysis, revealing nonlinear controlling relationships among porosity, tortuosity, sorting coefficient, and other factors that governed solute transport. Overall, this study advances the current mechanistic understanding of how multiscale pore structures influence solute transport behavior, providing a predictive framework for subsurface environmental and energy-related applications.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 135043"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146072676","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":"Differences in organic matter sources between suspended particulates and sediments in a lake during the frozen period","authors":"Xiaohui Ren ,&nbsp;Ruihong Yu ,&nbsp;Yanjie Mi","doi":"10.1016/j.jhydrol.2026.135094","DOIUrl":"10.1016/j.jhydrol.2026.135094","url":null,"abstract":"<div><div>Elucidating organic matter sources in lakes during the frozen period (FP) is crucial for understanding carbon and nitrogen cycling in global cold-region lakes. However, limited information exists on the sources and differences between suspended particulate organic matter and sediment organic matter in lakes during the FP. This study examined the stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotopic compositions of organic matter in suspended particulates and sediments from Daihai Lake to investigate the sources and implications of organic matter during the FP (January). Organic carbon in suspended particulates and total nitrogen in suspended particulates ranged from 0.45 to 1.22 mg/L and 0.08 to 0.20 mg/L, respectively, while organic carbon in sediments and total nitrogen in sediments ranged from 3.57 to 14.90 g/kg and 0.44 to 1.68 g/kg, respectively. Based on organic index (OI) and organic nitrogen (ON), suspended particulates (OI: 0.10 mg/L; ON: 0.12 mg/L) were slightly contaminated, whereas sediments (OI: 13.13 g/kg; ON: 1.08 g/kg) were heavily contaminated. The suspended particulate organic matter exhibited mixed source signatures, with exogenous inputs (sewage: 27.9% and soil: 22.2%) and endogenous production (phytoplankton: 25.8%). In contrast, sediment organic matter was predominantly exogenous inputs (soil: 40.3% and sewage: 26.6%). This discrepancy highlights a key process in organic matter transport and transformation under ice-covered conditions: phytoplankton-derived organic matter underwent preferential degradation during sedimentation, whereas terrestrial organic matter was more readily deposited and preserved. Notably, significant nitrogen isotope fractionation during sedimentation indicates that preferential mineralization of organic nitrogen and denitrification played key regulatory roles in the nitrogen cycling. The findings highlight the need to prioritize controlling exogenous organic matter inputs to lakes to ensure sustainable ecosystem.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135094"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110449","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":"A causality-informed and Copula-based framework for predictive assessment of downstream water-quality risks under extreme scenarios","authors":"Quan Zhou ,&nbsp;Jiajia Zhang ,&nbsp;Tian Lan ,&nbsp;Yongqin David Chen ,&nbsp;Siye Wei ,&nbsp;Xiuwen Ren ,&nbsp;Wenjing Wang ,&nbsp;Chunju Zheng ,&nbsp;Renren Wu","doi":"10.1016/j.jhydrol.2026.135123","DOIUrl":"10.1016/j.jhydrol.2026.135123","url":null,"abstract":"<div><div>In view of heightened hydroclimatic extremes and increasing human activities, aquatic ecosystems have been increasingly exposed to extreme water quality and hydrometeorological disturbances, with downstream dissolved oxygen (DO) dynamics affected by multiple water quality and meteorological drivers. To evaluate these risks, a downstream water-quality risk assessment framework is established to quantify the probability of future hypoxic events and to examine the transmission pathways of multi-source stressors. A CA-LSTM water quality prediction model is developed, integrating features derived from causal discovery and time–frequency analysis into a gated-memory attention architecture, thereby enhancing interpretability and predictive performance of DO dynamics. Joint variations of water-quality and meteorological factors that exert the strongest influence on predicted downstream DO are incorporated into the analytical framework. Vine Copula structure is employed to characterize the dependency structure between selected indicators and predicted downstream DO, which allowed the quantification of tail risks under extreme conditions. Application to the Shatiansisheng Station demonstrated that the CA-LSTM model achieved DO forecasts with an RMSE of 0.52 mg/L and an R² of 0.91, accurately reproducing both long-term patterns and short-term fluctuations. Single-factor analysis indicated that downstream water temperature (WT) exerted the strongest influence on downstream DO. Under combined extreme scenarios, when upstream DO fell below 5 mg/L and downstream WT exceeded the 90th percentile, the probability of downstream DO declining below the threshold within one day approached certainty. The proposed framework provides a quantitative basis for early warning of hypoxic events and offers methodological support for catchment-scale water-quality management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135123"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146186390","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":"Deep learning for groundwater level simulation in unconfined aquifers across the contiguous United States: Analyzing simulations at multiple lead times and integrating groundwater signatures","authors":"Kenneth Beng Wee Boo ,&nbsp;Ming Fai Chow ,&nbsp;Wai Peng Wong ,&nbsp;Ali Najah Ahmed ,&nbsp;Ahmed El-Shafie","doi":"10.1016/j.jhydrol.2026.134949","DOIUrl":"10.1016/j.jhydrol.2026.134949","url":null,"abstract":"<div><div>Simulating groundwater level accurately ahead of time is critical for various practical reasons. In this study, we simulate daily groundwater levels using meteorological data at 1-day to 7-day lead times across 249 unconfined wells in the contiguous United States. Our objectives include: 1) comparing LSTM-based Seq2Seq and Seq2One models for our simulation tasks, 2) investigating the efficacy of addressing failed models (where Nash Sutcliffe-Efficiency (NSE) &lt; 0) by using alternative training-validation splits, and 3) integrating groundwater signatures for a more thorough model evaluation process. Our results demonstrate satisfactory to good performance with our best performing models achieving median NSE scores of 0.744 and 0.603 for 1-day and 7-day lead simulations, respectively. Notably, we show that LSTM-based Seq2One model outperforms the Seq2Seq model at 1-day lead simulation, however the difference in their performance is not statistically significant for 4-day and 7-day lead simulation scenarios. We found that 14% of our models exhibit subpar performance, which may be attributed to modeling complex underlying groundwater systems without key anthropogenic forcing variables. And we show that simply changing the training-validation splits is generally not sufficient to address these failed models. Our analysis with groundwater signatures, which are statistical aggregates of groundwater level hydrographs, reveals that most groundwater dynamics are well captured by the model, and notable correlations between model NSE and groundwater signatures are found. These findings position us towards better interpreting the capabilities and limitations of our groundwater models.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134949"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957161","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":"Prediction of phosphorus loads for ungauged basins using probabilistic export coefficient model","authors":"Li Zhang,&nbsp;Theodore A. Endreny","doi":"10.1016/j.jhydrol.2026.134973","DOIUrl":"10.1016/j.jhydrol.2026.134973","url":null,"abstract":"<div><div>Observed discharge has been used to estimate the temporal variation in non-point or diffuse loads of phosphorus into receiving waters. Given that a large number of river basins have limited or no discharge data, this study evaluated whether reliable estimates of annual total phosphorus loads can be generated using daily probability time series derived from precipitation or modeled discharge. The i-Tree probabilistic export coefficient model uses a daily probability time series to simulate the load traveling into and through a riverine network to simulate annual total phosphorus loads. Two types of multi-decadal probability time series were tested against observed loads and benchmarked against simulations driven by observed discharge: derived from observed precipitation to represent ungauged basins, and derived from modeled discharge, calibrated using at least one year of streamflow observations.</div><div>Model performance was tested in three diverse U.S. river basins. Compared with annual loads estimated using observed discharge, those estimated with modeled discharge on average had a decrease of 0.25 in the Pearson correlation coefficient (<em>r</em>), a decrease of 0.13 in the Index of Agreement (<em>d</em>), an increase of 13.3 metric tons in root mean square error (RMSE) and 15.7 metric tons in mean absolute error (MAE), and an increase of 3.90% in percent bias (Pbias). Estimates based on observed precipitation showed a larger performance drop, with a decrease of 0.36 in a decrease of 0.41 in <em>d</em>, an increase of 14.9 metric tons in RMSE and 14.5 metric tons in MAE, and a decrease of 6.6% in Pbias. These findings suggest that while modeled discharge provides more accurate estimates, precipitation-based estimates remain a viable option for ungauged basins.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134973"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145962689","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":"Recharge elevation, residence time and renewability of groundwater in the Upper Awash valley, Ethiopia: Applying environmental tracers in a highly populated volcanic basin","authors":"W. George Darling ,&nbsp;James P.R. Sorensen ,&nbsp;Tilahun Azagegn ,&nbsp;Behailu Birhanu ,&nbsp;Seifu Kebede ,&nbsp;Daren C. Gooddy ,&nbsp;Koos Groen ,&nbsp;Richard G. Taylor ,&nbsp;Alan M. MacDonald","doi":"10.1016/j.jhydrol.2026.134989","DOIUrl":"10.1016/j.jhydrol.2026.134989","url":null,"abstract":"<div><div>The Upper Awash Basin in Ethiopia, which contains the rapidly-expanding national capital Addis Ababa, is being increasingly impacted by groundwater abstraction, leading to falling water levels in many areas. Groundwater management is impaired by the lack of consensus over detailed (hydro)geological characterisation of the complex volcanic aquifers that underlie this high-relief basin. Here we use an empirical study based on environmental tracers (isotopes, trace gases and hydrochemistry) measured on 40 groundwater samples collected from a selection of borehole sites, to explore the hydrogeological functioning of the basin The stable isotopes δ¹⁸O and δ²H provide information on likely recharge elevations (1900–3500 m above sea level) and extent to which surface waters are contributing to recharge (45% of sites sampled). The trace gases CFCs and SF₆ show that proportions of modern water are generally &lt; 10%, but ¹⁴C indicates that the groundwater storage currently critical for buffering change is in most cases of the order of hundreds rather than thousands of years old, and therefore may be vulnerable to comparatively rapid modification. With little evidence for significant variation in hydrogeochemical changes with depth across individual wellfields, we conclude that recharge is usually derived locally, though indications of longer flow paths exist in some locations, principally around the town of Mojo. Hydrochemistry shows that inorganic groundwater quality remains good at present, despite the existence of some poor-quality surface waters. The methodology of this study could be applied in other high-relief basins reliant on groundwater, to characterise vulnerability to abstraction where a detailed geological model and long-term monitoring are absent.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134989"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146033496","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":"Peridynamics modeling of multi-fissure occurrence in the subsiding North China plain","authors":"Miao Ye ,&nbsp;Lin Zhu ,&nbsp;Andrea Franceschini ,&nbsp;Huili Gong ,&nbsp;Pietro Teatini","doi":"10.1016/j.jhydrol.2026.134970","DOIUrl":"10.1016/j.jhydrol.2026.134970","url":null,"abstract":"<div><div>Understanding how excessive groundwater withdrawal and pumping trigger earth fissures at the land surface is essential for the sustainable management of subsurface resources in subsiding sedimentary basins. This hydrogeological hazard has become a growing global concern, affecting many countries (e.g., the USA, China, Iran, and Mexico). Predicting the transition from continuous land subsidence to discontinuous fissure presents a significant challenge. Here, we propose an effective procedure based on ordinary state-based peridynamics (PD) to simulate fissure evolution due to groundwater over-pumping. Initially, multi-fissure generation and propagation are analyzed in various hydrogeological configurations, i.e., outcropping bedrock, pre-existing faults offsetting a layered aquifer system, and bedrock ridges covered by alluvial deposits. Then, the approach is used to investigate fissure occurrences in the subsiding North China Plain around Beijing, which has been affected by thousands of earth fissures associated with pre-existing faults aseismically reactivated by excessive exploitation of aquifer systems over the last decades. PD modeling highlights that wider (up to 0.7 m) and deeper (up to 35 m) fissures develop with increasing fault dip, aquifer thickness, piezometric decline, and stiffness of surface deposits. The Young’s modulus and pore water pressure exert the most significant control over the scale of earth fissures, the thickness of the aquifer primarily influences the geometric characteristics of fissures, while the dip angle of the fault zone governs their spatial distribution pattern.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134970"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146014995","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":"Application of a coupled mechanistic and data-driven model for water level prediction considering the temporal and spatial effects of runoff evolution in cascade hydropower stations","authors":"Yubin Zhang ,&nbsp;Xiaoqun Wang ,&nbsp;Jijian Lian ,&nbsp;Pingping Luo","doi":"10.1016/j.jhydrol.2026.135057","DOIUrl":"10.1016/j.jhydrol.2026.135057","url":null,"abstract":"<div><div>Accurate water level prediction in cascade hydropower systems remains challenging due to complex runoff evolution and dynamic regulation. This study proposes a coupled model that integrates a hydrodynamic model (HD), a water balance model (WB), and a backpropagation neural network (BP) combining mechanistic and data-driven approaches to address these challenges. The HD model, established between Zhentou dam (ZTB) and Shaping II Hydropower Station (SP) based on the Saint-Venant equations, explicitly accounts for dynamic storage capacity and runoff evolution effects that significantly influence short-term forecasting accuracy. The WB describes water level changes through physical balance laws, while the BP captures nonlinear fluctuation patterns from historical data. To combine these strengths, a particle swarm optimization algorithm is introduced to dynamically weight model outputs, allowing the framework to adaptively correct prediction errors in real time. Application results show that the coupled HD–WB–BP model (New method) markedly improves predictive performance. Compared with the individual WB and BP models, the New method achieves approximately 30% lower Root Mean Square Error (RMSE), with Nash–Sutcliffe efficiency (NSE) consistently above 0.90, a correlation coefficient (r) of 0.96, and a Mean Absolute Percentage Error (MAPE) of 3.8% for both 3-hour and 24-hour horizons. The model also effectively reduces prediction lag and provides more accurate peak estimation under conditions influenced by dynamic storage and runoff evolution. In addition, the new method keeps P95 latency at = 10174.68 ms, safely within the 5-minute cycle. This demonstrates a favorable balance between accuracy and efficiency for near real-time operation. Overall, the proposed approach provides a robust and scalable framework for water level forecasting in cascade hydropower systems, underscoring the advantages of combining physical–mechanistic and data-driven models to enhance reliability and operational decision-making.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 135057"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146072664","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":"A physically-based model for particle transport over urban road surface with consideration of raindrop erosion and runoff effect","authors":"Taotao Zhang ,&nbsp;Bin Luan ,&nbsp;Chi Zhang ,&nbsp;Yang Xiao ,&nbsp;Chen Xu ,&nbsp;Jingxiu Wu","doi":"10.1016/j.jhydrol.2026.135033","DOIUrl":"10.1016/j.jhydrol.2026.135033","url":null,"abstract":"<div><div>Particle transport over urban road surfaces is a critical contributor to urban stormwater pollution. However, existing particle transport models predominantly focus on individual rainfall effect, rendering the coupled effects of raindrop erosion and runoff effect inadequately understood. This study proposed a novel physically based transport model by introducing a two-layer conceptual model that incorporates both raindrop erosion and runoff effect. The model assumed that particles in the static control layer can enter the upper runoff layer through raindrop erosion and runoff effect. A series of laboratory experiments were performed to validate the proposed model, taking into account the conditions of with and without raindrop erosion, as well as mixed particles. Results demonstrated that model predictions exhibited excellent agreement with the experimental observations under various conditions. Critical runoff energy exhibited strong positive correlation with median particle size, while the efficiency coefficient increased with decreasing particle size. Raindrop erosion increased the peak concentration and transport rate by 3 to 4 fold, and significantly raised the final wash-off fraction of large-sized particles. Sensitivity analysis revealed that Manning’s coefficient and control layer depth attenuate peak transport rates, whereas slope length and detachment coefficient enhance them. This study advanced the understanding of particle transport mechanisms in urban environments and provided a foundation for developing distributed catchment models.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 135033"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146072672","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}