Journal of Hydrology最新文献

{"title":"A methodology for development of flood-depth-velocity damage functions for improved estimation of pluvial flood risk in cities","authors":"Dorothy Pamela Adeke,&nbsp;Seith N. Mugume","doi":"10.1016/j.jhydrol.2025.132736","DOIUrl":"10.1016/j.jhydrol.2025.132736","url":null,"abstract":"<div><div>Globally, flooding is a persistent challenge in many rapidly urbanising cities. Effective flood risk management requires reliable and accurate approaches for quantifying potential flood damages, yet city specific flood damage functions are often unavailable in many cities. Due to this, estimation of flood damages in most data scarce cities is undertaken using global averaged flood − depth − damage functions and does not consider complex interactions between flood depth, velocity and urban form that influence the resulting flood damages. In this research, a new methodology that combines field questionnaire surveys, coupled 1D-2D modelling and polynomial regression was applied to derive three absolute flood damage functions that is; flood depth-damage, flood velocity-damage and flood depth-velocity-damage functions for a highly urbanised catchment in Kampala City, Uganda. The performance of the developed functions in describing the expected flood damage at given flood depths and velocities was evaluated using the coefficient of determination <em>(R²),</em> Akaike Information Criterion <em>(AIC)</em> and the modified Akaike Information Criterion <em>(AIC_c)</em>. The study results suggest that the developed flood-depth-velocity damage function provides a more accurate means of estimating direct tangible flood damages when compared to individual flood depth-damage and flood velocity functions. Furthermore, the developed methodology incorporates flood flow velocity, a key factor in structural damage and loss of life during flooding conditions and thus provided empirical evidence that consideration of both flood depth and velocity parameters can lead to more accurate estimation of annual expected flood damage in cities.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132736"},"PeriodicalIF":5.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077736","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":"Effect of sediment particle size distribution characteristics on hyporheic exchange under different riverbed topography","authors":"Yuchen Zhang ,&nbsp;Jinxi Song ,&nbsp;Dandong Cheng ,&nbsp;Hangzhen Zhang ,&nbsp;Chaosong Zhang ,&nbsp;Haoying Zhang ,&nbsp;Bin Tang","doi":"10.1016/j.jhydrol.2025.132752","DOIUrl":"10.1016/j.jhydrol.2025.132752","url":null,"abstract":"<div><div>Hyporheic exchange, the intricate interplay between groundwater and surface water near the riverbed or riverbank, is highly influenced by the natural features of riverbeds and sediment deposition. Of the structural configurations commonly encountered in aquatic environments, straight and meandering channels are of particular interest for hydrological and geomorphological studies. However, little attention has been given to understanding how sediment particle size distribution affects hyporheic exchange in different riverbed morphologies. In this study, we focused on two sections of the lower Beiluo River in northwestern China, representing meandering and straight channels. By analyzing sediment structure and using the hydraulic gradient method to estimate vertical permeability, we were able to assess how riverbed morphology and sediment grain sizes impact water exchange in the hyporheic zone. Our results showed that the meandering channel morphology significantly influenced water flow in the hyporheic zone, particularly in terms of water volume moving downwards. Additionally, sediment grain size distribution played a role in streambed permeability, with different particle sizes like clay, fine sand, and coarse sand having distinct effects on water exchange. Changes in streambed permeability can also affect hyporheic exchange flux, which is further influenced by anthropogenic structures, river topography, and runoff conditions. Furthermore, hyporheic exchange impacts the vertical distribution of clay particles in the hyporheic zone. This research contributes to enhancing river ecosystem health, improving water purification and pollution control strategies, advancing water resource management practices, and establishing a scientific foundation for ecological conservation and sustainable water resource utilization.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132752"},"PeriodicalIF":5.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077821","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":"Global-scale gap filling of satellite soil moisture products: Methods and validation","authors":"Chunlin Zhang ,&nbsp;Jiangyuan Zeng ,&nbsp;Pengfei Shi ,&nbsp;Hongliang Ma ,&nbsp;Husi Letu ,&nbsp;Xiang Zhang ,&nbsp;Panshan Wang ,&nbsp;Haiyun Bi ,&nbsp;Jiaming Rong","doi":"10.1016/j.jhydrol.2025.132762","DOIUrl":"10.1016/j.jhydrol.2025.132762","url":null,"abstract":"<div><div>The utility of satellite soil moisture products is often limited by their missing values, and thus it is crucial to develop gap-filling methods to obtain soil moisture datasets with high-precision and spatiotemporal coverage. Previous studies often used a single gap-filling method in specific regions without analysis of the factors affecting the gap-filling accuracy. To narrow this research gap, this study first compared the correlation of SMAP soil moisture products with five spatially seamless model-based soil moisture datasets globally. Then based on the optimal ERA5 data from 2016 to 2019, the performance of four machine learning methods in filling the SMAP missing values was compared. The best-performing random forest (RF) method was compared with other five traditional bias-corrected methods. Subsequently, twelve auxiliary data were incorporated into the RF to improve the accuracy of gap-filled SMAP data, which were validated by ground measurements from 1071 sites worldwide. Finally, the environmental factors affecting the filling accuracy of SMAP data were analyzed on a global scale. The results indicate: 1) RF generally performs the best among the four machine learning approaches. When only using the ERA5 dataset for the model input, RF achieves higher accuracy compared to the other five bias-corrected methods during the training phase, but its skill degrades noticeably in the validation phase. The performance of RF improves significantly after adding auxiliary data; 2) against globally distributed <em>in situ</em> data, the gap-filled products show improved skill over the original SMAP data, with smaller ubRMSE of 0.049 m³m⁻³ (<em>vs.</em> 0.060 m³m⁻³), demonstrating the RF method with auxiliary data can effectively fill the missing values of SMAP data; 3) the gap-filling accuracy is mainly affected by vegetation cover, soil moisture conditions, and land cover heterogeneity. Specifically, the filling accuracy is lower in denser vegetation coverage, wetter soil, and larger land cover heterogeneity.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132762"},"PeriodicalIF":5.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143077820","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 new multivariate composite drought index considering the lag time and the cumulative effects of drought","authors":"Mengjia Yuan ,&nbsp;Guojing Gan ,&nbsp;Jingyi Bu ,&nbsp;Yanxin Su ,&nbsp;Hongyu Ma ,&nbsp;Xianghe Liu ,&nbsp;Yongqiang Zhang ,&nbsp;Yanchun Gao","doi":"10.1016/j.jhydrol.2025.132757","DOIUrl":"10.1016/j.jhydrol.2025.132757","url":null,"abstract":"<div><div>Frequent and intense droughts pose significant threats to ecosystem health and human society under global change, making timely and rapid detection of such events crucial. Drought index is an essential tool for drought monitoring and risk assessment. Univariate drought indices cannot effectively characterize comprehensive drought characteristics and rarely account for the time lag between different types of droughts as well as their cumulative effects. Considering this, we developed a multivariate composite drought index (MCDI) using the Gringorten empirical formula based on four drought indices representing meteorological drought (Standardized Precipitation Actual Evapotranspiration Index, SPAEI), agricultural drought (Standardized Soil Moisture Index SSI), and hydrological drought (Standardized Runoff Index (SRI), and Water Storage Deficit Index (WSDI)). To verify the effectiveness of MCDI, we first calculated the Pearson correlation coefficients (PCC) between scPDSI (Self-calibrating Palmer Drought Severity Index) and MCDI in China. The results showed that the percentage of pixels with PCC greater than 0.5 was 70.02 % (p &lt; 0.05). Then we analyzed the spatial/temporal drought trends in China and different hydroclimatic zones. Drought indices performed differently, and MCDI generally exhibited a “dry areas become wetter, wet areas become drier” pattern in China based on the trends shown by regional means. However, in terms of spatial distribution, the wet and dry trends in China are highly spatially heterogeneous. In addition, we selected two typical drought events that occurred in Arid/Semi-Arid (Inner Mongolia) and Humid/Semi-Humid (Yunnan Province) zones, respectively, to assess the ability of the MCDI to characterize drought. Compared with other drought indices and drought indicators (Soil Moisture and Solar-induced Chlorophyll Fluorescence), MCDI characterized the drought event most consistently with official records and responded faster to drought. Overall, the MCDI has good potential for drought monitoring and assessment.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132757"},"PeriodicalIF":5.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175252","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":"Divergent responses of optimal land and water allocation to different hydrological regimes in the agricultural water-food-carbon nexus system","authors":"Haomiao Cheng ,&nbsp;Anan Wang ,&nbsp;Jian Zhang ,&nbsp;Xizhi Nong ,&nbsp;Xuecheng Jiang ,&nbsp;Hainan Wu ,&nbsp;Zhaoxia Chen ,&nbsp;Menglei Wang ,&nbsp;Jilin Cheng","doi":"10.1016/j.jhydrol.2025.132730","DOIUrl":"10.1016/j.jhydrol.2025.132730","url":null,"abstract":"<div><div>Frequent changes in the hydrological regimes lead to divergent responses of water, food, and carbon (C) emissions in agricultural production, which challenge sustainable agricultural development. Therefore, this study proposed a systematic multi-objective non-linear programming model for investigating divergent responses of optimal land and water allocation to different hydrological regimes from the perspective of the agricultural water-food-carbon (AWFC) nexus framework. The model was capable of simultaneously tackling the trade-offs among water consumption, economic benefit, and C emissions by integrating with spatial–temporal water footprint (WF) and carbon footprint (CF) theories. The universal cropping patterns in each spatial water function zone that adapted to the spatiotemporal variations of hydrological regimes could also be obtained. The applicability and effectiveness of the proposed methodology were verified by a real-world, provincial-scale case, <em>i.e.</em>, Jiangsu Province, southeast China. As for the actual scenario, the optimal scheme under normal, wet, and dry years highlighted the significance of improvement in water-saving (10.31%–12.26%), while showing a slight increase in net economic benefit (2.68%–2.85%) and low-carbon agricultural competitiveness (1.21%–3.58%). It was found that the wet year performed the greatest water-saving potential, and the dry year showed the strongest low-carbon agricultural competitiveness. The optimal cropping patterns suggested that it was a promising management strategy to enhance the comprehensive benefits related to the economy, water, and carbon by increasing the planting proportion of high-value crops with low WF and CF. This study provided scientific methodology and instructions for balancing the trade-off among economy, water, and environment components in sustainable agricultural development.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132730"},"PeriodicalIF":5.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143172864","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 elasticity functions explain divergent runoff sensitivity to rainfall errors in hydrological models","authors":"E. Dallan ,&nbsp;T. Perez-Ciria ,&nbsp;L. Giovannini ,&nbsp;S. Davolio ,&nbsp;D. Zardi ,&nbsp;M. Borga","doi":"10.1016/j.jhydrol.2025.132746","DOIUrl":"10.1016/j.jhydrol.2025.132746","url":null,"abstract":"<div><div>Despite numerous past and ongoing efforts towards characterizing the propagation of rainfall estimation uncertainties in rainfall-runoff hydrologic models, modelers struggle to identify the main features that impact how rainfall errors are transmitted to simulated runoff. With this work, we introduce the concept of the <em>rainfall elasticity function</em>, i.e. the measure of how responsive the simulated event runoff is to a change in rainfall. We analytically derive the functions for two well-known runoff generation model types: the Probability Distributed Model (PDM), where the Pareto distribution is used to describe the distribution of soil-moisture storage capacity, and the Soil Conservation Service – Curve Number (SCS-CN) model. These functions are explored to examine the propagation of rainfall errors through the two models. It is shown that the two models are characterized by very different elasticity functions, which results in diverging propagation features of the rainfall errors. For the PDM case, increasing the precipitation depth, or reducing the storage capacity, results in the elasticity growing from 1 to a peak whose value and location depend on the model parameters, and then asymptotically decreases again to 1. For the SCS-CN model, increasing the precipitation depth, or decreasing the maximum potential retention, makes the elasticity decrease from infinity to 1. The capability of the elasticity functions to describe the propagation of rainfall errors through the models is illustrated by using the data from the Vaia 2018 flood in the Eastern Italian Alps. Owing to the very dry initial conditions and the extremely high precipitation depth associated with the event, application to this case allows exploring the whole range of hydrological conditions characterizing the elasticity functions. It is shown that the analytical functions closely resemble the results obtained by forcing the models with the actual distribution of rainfall errors, thus paving the way for the practical application of this approach, such as in hydrological model calibration, and the use of multi-model ensemble for flood forecasting.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132746"},"PeriodicalIF":5.9,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143172867","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":"Salty tide enhanced ecotoxicological risk of trace metals in the lower reach of the Pearl River, China via altering their phase partitioning and chemical speciation","authors":"Lei Gao ,&nbsp;Chao Yan ,&nbsp;Chenchen Yang ,&nbsp;Rui Li ,&nbsp;Qirui Wu ,&nbsp;Di Tian ,&nbsp;Lei Ouyang","doi":"10.1016/j.jhydrol.2025.132761","DOIUrl":"10.1016/j.jhydrol.2025.132761","url":null,"abstract":"<div><div>Estuaries are transitional aquatic systems characterized by large physicochemical gradients that strongly influence the migration, transformation, fractionation, and speciation of trace metals (TMs), ultimately affecting their bioavailability. In this study of the Jiaomen Waterway, a representative tidal river of the Pearl River, China, ultra-filtration and a thermodynamic chemical equilibrium model were applied to perform size fractionation and simulate chemical speciation of nickel (Ni), zinc (Zn), copper (Cu), and cadmium (Cd). The concentrations of labile metals were determined using the diffusive gradients in thin films technique (C_DGT), while their chemical speciation was assessed using the chemical dynamics (C_Dyn) approach. In rainy season, the particulate phase accounted for &gt; 50 % of the TMs concentration, after that, colloids (1 kDa−0.45 μm) become the major host phase (41–60 %) for TMs. With increasing water salinity, particulate Ni and Cd tended to desorb from suspended solids, whereas a uniform spatial distribution pattern was observed for Zn and Cu. Colloids were removed through deposition or transferred into the truly dissolved fraction (&lt;1 kDa). Soluble Ni, Zn, and Cd (&lt;0.45 μm) were predominantly found as free ions and inorganic species; however, &gt;98 % of Cu was present as humic substance complexes. A significant positive correlation (<em>p</em> &lt; 0.05) between C_DGT and C_Dyn confirmed the consistency of the bioavailability assessment for TMs. Labile Ni, with a risk quotient (RQ_HC1) of 1.95−10.2, presented moderate to high ecotoxicological risks to a few aquatic species especially in dry season with marked salty tide, whereas low risks were identified for Zn, Cu, and Cd (RQ_HC1: 0.03−2.09). The results are anticipated to provide a supplement for geochemistry of trace metals in estuarine waters.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132761"},"PeriodicalIF":5.9,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143172866","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":"Global anthropogenic effects on meteorological—hydrological—soil moisture drought propagation: Historical analysis and future projection","authors":"Siqi Wang ,&nbsp;Shuzhe Huang ,&nbsp;Chao Wang ,&nbsp;Xiang Zhang ,&nbsp;Jiefeng Wu ,&nbsp;Aminjon Gulakhmadov ,&nbsp;Dev Niyogi ,&nbsp;Nengcheng Chen","doi":"10.1016/j.jhydrol.2025.132755","DOIUrl":"10.1016/j.jhydrol.2025.132755","url":null,"abstract":"<div><div>Intensified anthropogenic activities in the 21st century have introduced profound and widespread impacts on drought dynamics and their propagation. However, the extent to which large-scale human-induced forces, such as greenhouse gas emissions (GHGs) and aerosols, influence the propagation of drought from meteorological to hydrological and soil moisture droughts at the global level remains insufficiently understood. To address this gap, we conducted a comprehensive quantitative analysis, integrating historical simulations of various anthropogenic and climatic drivers with future projections based on different Shared Socioeconomic Pathways (SSPs) from the CMIP6. Key features of drought propagation—such as propagation time, probability, and drought characteristics—were assessed across distinct historical and future scenarios to elucidate the anthropogenic influences. The findings indicate that human-driven forces, particularly GHG emissions, have significantly influenced both meteorological-hydrological and meteorological-soil moisture drought propagation. Notably, anthropogenic factors led to a general reduction in drought propagation time, with GHGs playing a dominant role. Furthermore, GHG emissions were found to markedly increase the probability, duration, and severity of propagated droughts, especially across northern North America, southern Africa, and northeastern Asia. Future projections reveal a slight decline in meteorological-hydrological drought propagation probability during 2015–2100, while meteorological-soil moisture drought propagation probability shows a pronounced upward trend. Additionally, our analysis underscores the critical role of global warming and vegetation changes in shaping drought propagation patterns. These results offer valuable insights for enhancing drought early warning systems in a changing climate.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132755"},"PeriodicalIF":5.9,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143173420","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":"Analyzing the effects of data splitting and covariate shift on machine learning based streamflow prediction in ungauged basins","authors":"Pin-Ching Li ,&nbsp;Sayan Dey ,&nbsp;Venkatesh Merwade","doi":"10.1016/j.jhydrol.2025.132731","DOIUrl":"10.1016/j.jhydrol.2025.132731","url":null,"abstract":"<div><div>Machine learning (ML) models are alternatives to traditional hydrologic modeling for streamflow predictions in ungauged basins (PUB). The variability in watershed characteristics of ungauged basins; however, adds uncertainties to PUB frameworks based on ML models. These uncertainties arise from the inconsistency in the statistical distributions between the dataset used to train and test a ML model, known as covariate shifts, and the real-world (global) dataset on which the trained model is implemented. In real-world applications, covariate shift is a widespread issue for ML that has not been investigated in hydrological applications. This study evaluates the uncertainty in ML-based PUB method including Random Forest (RF) and Artificial Neural Network (ANN) under the influence of covariate shift. The Monte Carlo method is applied to aggregate simulations of RF and ANN according to various data splitting configurations as predictive distributions. The results indicate that ML performance is not robust under covariate shifts. ML performance is influenced by watershed characteristics displaying heterogeneity, such as drainage area, dam density, and urbanized area. 20–48% simulation results show a departure from the normal distribution under different covariate shift scenarios Furthermore, the efficiency and limitation of Random Forest models for PUB are highlighted by investigating their biased predictions in watersheds with varying dam density, drainage area, and meteorological variables, such as annual snowfall and annual precipitation.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132731"},"PeriodicalIF":5.9,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143173639","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":"Experimental study on the spatial traits of sedimentation driven by discontinuous nearshore vegetation patches","authors":"Liu Yang,&nbsp;Yidan Ai,&nbsp;Wenxin Huai,&nbsp;Zhonghua Yang","doi":"10.1016/j.jhydrol.2025.132745","DOIUrl":"10.1016/j.jhydrol.2025.132745","url":null,"abstract":"<div><div>In the rivers, the growth of aquatic plants from initial individual patches to elongated formations, and subsequent merging with the downstream or adjacent patches, is intricately linked to the spatial pattern of sediment deposition. Understanding the mechanism of suspended load deposition influenced by these plant patches is crucial. Therefore, we conducted experimental investigations into the spatial traits of sedimentation driven by discontinuous nearshore vegetation patches and its relationship with flow rates and vegetation density. The results indicate that, although the limited length of discontinuous vegetation patches restricts the development of coherent vortices at the interface, both fast and slow currents were observed, similarly to scenarios with continuous vegetation. Additionally, a unidirectional suspended loads transport from vegetation regions to the main channel was observed, contributing to the minimal sedimentation within the vegetation region originating from the main channel. However, the sedimentation in the retention zones, where is formed by the blocking and sheltering effects of discontinuous vegetation patches, was found to be most pronounced, approximately 1.5 to 3 times higher than in patch regions and main channels, which ascribes to longer retention time and the weaker turbulence in retention zones compared to the main channel and the vegetation region. The velocity differential between the main channel and vegetation region increases with greater flow rates, leading to the greater difference in the total deposition in the several typical areas: the vegetation region, the interval region, and the main channel. The positive correlation between the sedimentation spatial heterogeneity and flow rates was observed and quantified by the normalized standard deviation of the total deposition. These findings suggest that vegetation-mediated sediment trapping, alongside associated interval regions, generates distinct spatial patterns of sedimentation, which plays a crucial role in facilitating the longitudinal growth of vegetation patches downstream, ultimately contributing to the establishment of continuous nearshore vegetation zones. These findings provide insights into the potential applications of vegetation patches, particularly in river ecosystem restoration and water resource management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"653 ","pages":"Article 132745"},"PeriodicalIF":5.9,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143286420","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}