Journal of Hydrology-Regional Studies最新文献_第10页

Cluster-based XGBoost framework for short-term rainfall–runoff prediction under uncertainty in the Sieber watershed, Germany 基于簇的XGBoost框架在不确定条件下对德国Sieber流域的短期降雨径流进行预测

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-02-05 DOI: 10.1016/j.ejrh.2026.103160

Ozgur Kisi , Salim Heddam , Sovan Sankalp , Andrea Petroselli , Christoph Külls , Mohammad Zounemat-Kermani

{"title":"Cluster-based XGBoost framework for short-term rainfall–runoff prediction under uncertainty in the Sieber watershed, Germany","authors":"Ozgur Kisi , Salim Heddam , Sovan Sankalp , Andrea Petroselli , Christoph Külls , Mohammad Zounemat-Kermani","doi":"10.1016/j.ejrh.2026.103160","DOIUrl":"10.1016/j.ejrh.2026.103160","url":null,"abstract":"<div><h3>Study region</h3><div>The study focuses on the Sieber River watershed in northern Germany, a small mountainous catchment characterized by rapid rainfall–runoff response, limited hydrological data availability, and substantial short-term flow variability. These characteristics make the region an ideal testbed for developing robust, data-efficient short-term runoff prediction models.</div></div><div><h3>Study focus</h3><div>This research proposes a novel hybrid modeling framework combining eXtreme Gradient Boosting (XGBoost) with clustering algorithms (K-means and X-means) to improve multi-step-ahead rainfall–runoff forecasting under uncertainty. Hourly precipitation–runoff data and lagged precipitation inputs (P<sub>t</sub> to P<sub>t–36</sub>) are used to generate predictions at 1-, 2-, 3-, and 6-hour horizons. The hybrid models are benchmarked against standalone XGBoost, Principal Component Regression (PCR), and the conceptual Event-Based Approach for Small and Ungauged Basins (EBA4SUB). Model performance is evaluated using RMSE, MAE, NSE, R², and uncertainty bounds.</div></div><div><h3>New hydrological insights for the region</h3><div>Clustering rainfall–runoff conditions into homogeneous hydrometeorological regimes considerably enhances prediction accuracy. The XGBoost–K-means model provides the best performance, achieving low predictive error (6-hour ahead: RMSE = 0.580 m³/s, NSE = 0.954) and the narrowest uncertainty range (WUCB = 2.274). These findings demonstrate that cluster-enhanced machine learning models offer a reliable and computationally efficient solution for operational short-term forecasting in small catchments like the Sieber watershed. The hybrid approach supports improved flood early warning, real-time water management, and decision-making in data-scarce environments.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103160"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Karst carbon sink in a subalpine catchment of Eastern Qinghai-Tibetan Plateau: Influences of anthropogenic and natural factors 青藏高原东部亚高山集水区岩溶碳汇：人为与自然因素的影响

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-02-05 DOI: 10.1016/j.ejrh.2026.103187

Ziling Zhong , Xue Qiao , Weiyang Xiao , Ting Liu , Jiancheng Liu , Ya Tang

{"title":"Karst carbon sink in a subalpine catchment of Eastern Qinghai-Tibetan Plateau: Influences of anthropogenic and natural factors","authors":"Ziling Zhong , Xue Qiao , Weiyang Xiao , Ting Liu , Jiancheng Liu , Ya Tang","doi":"10.1016/j.ejrh.2026.103187","DOIUrl":"10.1016/j.ejrh.2026.103187","url":null,"abstract":"<div><h3>Study region</h3><div>Jiuzhaigou, a subalpine karst catchment located on the eastern margin of the Qinghai-Tibetan Plateau, China.</div></div><div><h3>Study focus</h3><div>This study quantifies KCS in Jiuzhaigou World Natural Heritage Site, a subalpine catchment on the eastern Qinghai-Tibetan Plateau, and compares KCS intensities across China’s major karst regions.</div></div><div><h3>New hydrological insights for the region</h3><div>At the catchment scale, KCS flux (t CO<sub>2</sub> yr<sup>–1</sup>) comprises riverine dissolved inorganic carbon export (F<sub>DIC</sub>), riverine autochthonous organic carbon export (F<sub>AOC</sub>), and lacustrine autochthonous organic carbon burial (F<sub>SOC</sub>). Jiuzhaigou exhibited a total KCS flux of 22510 ± 1400 t CO<sub>2</sub> yr<sup>–1</sup> and intensity of 35.0 ± 2.2 t CO<sub>2</sub> km<sup>−2</sup> yr<sup>–1</sup>. F<sub>DIC</sub> dominated KCS (91.7 %), followed by F<sub>AOC</sub> (6.54 %) and F<sub>SOC</sub> (1.79 %). Seasonally and annually, autochthonous organic carbon constituted > 75 % of total organic carbon in surface water and sediments, while dissolved organic carbon represented > 90 % of aquatic total organic carbon. Climatic factors position Jiuzhaigou’s export intensities of dissolved inorganic and organic carbon between the Qinghai-Tibetan Plateau and South China Karst Region, exceeding the North China Karst Region. Conversely, Jiuzhaigou’s lacustrine organic carbon burial rates significantly surpassed those in all the three regions (<em>p</em> < 0.05), partially enhanced by anthropogenic land use/cover changes and geohazards, which elevated organic carbon burial. This study fills the KCS knowledge gap in subalpine catchments and highlights its sensitivity to anthropogenic and geohazard disturbances.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103187"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146173780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identifying flush and transport patterns driving particle export and elemental composition of stormwater from a German urban catchment 确定驱动德国城市集水区雨水颗粒出口和元素组成的冲刷和运输模式

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-01-29 DOI: 10.1016/j.ejrh.2026.103196

Karen L. Rojas-Gómez , Jakob Benisch , Björn Helm , Dietrich Borchardt , Peter Krebs

{"title":"Identifying flush and transport patterns driving particle export and elemental composition of stormwater from a German urban catchment","authors":"Karen L. Rojas-Gómez , Jakob Benisch , Björn Helm , Dietrich Borchardt , Peter Krebs","doi":"10.1016/j.ejrh.2026.103196","DOIUrl":"10.1016/j.ejrh.2026.103196","url":null,"abstract":"<div><h3>Study region</h3><div>Dresden, Germany</div></div><div><h3>Study focus</h3><div>Stormwater runoff transports particles and contaminants, which are highly mobile in the urban water system. Their export shows significant temporal variability described by pollutant flush types. Understanding this variability is essential for improving monitoring and proposing stormwater pollution control strategies at the urban catchment scale. Hence, we characterised the sediment export and element patterns from a stormwater outlet in Dresden (Germany) using both grab samples and high-resolution monitoring data during rainfall events.</div></div><div><h3>New hydrological insights from the region</h3><div>Our results showed that the stormwater discharge consisted mainly of fine (< 63 µm) and inorganic sediments, representing ∼80 % of suspended sediments. Pairwise associations and a hierarchical cluster analysis revealed strong Kendall correlations among fine and coarse suspended sediments, their organic content, and elements (i.e., Al, Ba, Cu, Fe, Mg, Mn, Zn), indicating similar transport mechanisms. These variables clustered with turbidity, emphasizing its potential as an easily measurable proxy for evaluating the dynamics of particle-bound contaminants through continuous monitoring. Hydrological descriptors may explain the variability of flush types. In the analysed catchment, second flush events could be linked to preceding higher-intensity rainfall, highlighting the influence of antecedent conditions on transport dynamics. The occurrence of two pollutant flush types through the year and the existence of both anti-clockwise and clockwise hysteresis patterns provide insights into delayed transport mechanisms, highlighting the need for flexible infrastructure in stormwater management.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103196"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving transparency in karst spring discharge and water quality forecasts using interpretable machine learning models in the Eastern Alps 利用可解释的机器学习模型提高东阿尔卑斯山喀斯特泉流量和水质预测的透明度

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-01-21 DOI: 10.1016/j.ejrh.2026.103147

Anna Pölz , Alfred Paul Blaschke , Katalin Demeter , Günter Blöschl , Margaret E. Stevenson , Helene Bauer , Liping Pang , Andreas H. Farnleitner , Julia Derx

{"title":"Improving transparency in karst spring discharge and water quality forecasts using interpretable machine learning models in the Eastern Alps","authors":"Anna Pölz , Alfred Paul Blaschke , Katalin Demeter , Günter Blöschl , Margaret E. Stevenson , Helene Bauer , Liping Pang , Andreas H. Farnleitner , Julia Derx","doi":"10.1016/j.ejrh.2026.103147","DOIUrl":"10.1016/j.ejrh.2026.103147","url":null,"abstract":"<div><h3>Study region</h3><div>Karst springs draining the Hochschwab massif, Eastern Alps, Austria.</div></div><div><h3>Study focus</h3><div>Accurate forecasting of spring discharge and water quality is crucial for sustainable water resource management. Although machine learning (ML) models have shown considerable potential for forecasting hydrological variables, understanding the underlying processes remains limited. This study aimed to improve the transparency of ML models through an attribution analysis, which explores the contribution of local environmental factors to forecasts. Several ML models were deployed to predict spring discharge and water quality, measured by the spectral absorption coefficient at 254 nm (UV254), up to four days in advance at karst springs.</div></div><div><h3>Innovative insights</h3><div>The Deep SHAP method aided in identifying significant seasonal variations in model attributions, showing the most pronounced changes for snow depth, followed by physicochemical variables such as electrical conductivity and other meteorological variables. The Transformer model exhibited the best overall performance. Model uncertainty, assessed through the Deep Ensemble method, is greater in spring and summer, and both the model errors and uncertainties increase with variability of the target variables. To evaluate model applicability for selective water abstraction, we classified UV254 forecasts based on threshold exceedance, achieving high classification accuracy (>95 % for 1-day and >90 % for 2-day forecasts). Integrating Deep SHAP and Deep Ensemble methods enhanced ML transparency. This combined approach provides insights that can inform drinking water management decisions in karst systems.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103147"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deciphering the daily spatiotemporal dynamics and mechanisms of floods in the Tarim Basin desert region 解读塔里木盆地荒漠地区洪水日时空动态及机制

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-01-21 DOI: 10.1016/j.ejrh.2026.103158

Arken Tursun , Xianhong Xie , Hossein Azadi , Anwar Eziz , Yibing Wang , Bowen Zhu , Alishir Kurban

{"title":"Deciphering the daily spatiotemporal dynamics and mechanisms of floods in the Tarim Basin desert region","authors":"Arken Tursun , Xianhong Xie , Hossein Azadi , Anwar Eziz , Yibing Wang , Bowen Zhu , Alishir Kurban","doi":"10.1016/j.ejrh.2026.103158","DOIUrl":"10.1016/j.ejrh.2026.103158","url":null,"abstract":"<div><h3>Study region</h3><div>The study focuses on the Tarim River Basin in the hyper arid regions, where flooding events have become increasingly frequent and severe due to climate change. The desert–oasis transition zones are highly vulnerable because of their limited vegetation cover, low soil permeability, and strong hydrological variability, which together complicate flood monitoring and management.</div></div><div><h3>Study focus</h3><div>Comprehensive flood simulations that simultaneously capture flood extent and streamflow dynamics at high spatiotemporal resolution remain scarce in arid environments. To address this gap, we propose an interpretable deep learning framework for full-process flood modeling. The framework integrates daily 30 m Seamless Data Cube (SDC) remote sensing data with deep learning–based hydrological models. A U-shaped network (UNet) is used to extract daily flood extents, while hybrid and pure deep learning models simulate daily streamflow under data-scarce conditions. The integration of these models enables a consistent representation of flood processes from surface inundation to river discharge.</div></div><div><h3>New hydrological insights for the region</h3><div>Validation with Landsat imagery confirms that SDC-derived flood maps achieve an average bias below 5 %, while the streamflow simulations produce median Kling–Gupta Efficiency (KGE) and Nash–Sutcliffe Efficiency (NSE) values exceeding 0.8. The proposed framework successfully captures both the spatial and temporal dynamics of floods in arid regions. Furthermore, interpretability analysis reveals that accelerated snowmelt is the dominant driver of recent flood events. This study demonstrates a transferable and data-efficient approach for improving flood modeling and monitoring across arid regions worldwide.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103158"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Downstream fining and rounding in sand-bed river and its significance: A case study from the Ganjiang River, China 沙质河床下游的精细化和围化及其意义——以赣江为例

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-01-22 DOI: 10.1016/j.ejrh.2026.103156

Fangen Hu , Xia Xiao , Yanjun Che , Qingbin Fan , Yun Xu

{"title":"Downstream fining and rounding in sand-bed river and its significance: A case study from the Ganjiang River, China","authors":"Fangen Hu , Xia Xiao , Yanjun Che , Qingbin Fan , Yun Xu","doi":"10.1016/j.ejrh.2026.103156","DOIUrl":"10.1016/j.ejrh.2026.103156","url":null,"abstract":"<div><h3>Study region</h3><div>The Ganjiang River in southern China.</div></div><div><h3>Study focus</h3><div>The ubiquitous pattern and mechanisms of downstream fining and rounding of sediments in gravel-bed rivers is well studied. However, little is known about these processes in sand-bed rivers. In this study, 37 river sand, 25 beach sand, and 17 dune sands samples across a 625 km transect from source to sink were analyzed, by dynamic image technique, and geochemical elements, to investigate the downstream evolution of particle size and shape in different sand fractions in a sand-bed river.</div></div><div><h3>New hydrological insights for the region</h3><div>Our results reveal that medium sand fractions and bulk samples gradually become rounder and finer with downstream distance, whereas fine sand fractions transported in suspension display no significant downstream trend. The medium sand fraction exhibits a much smaller diameter reduction rate, but a roughly equal shape improvement rate compared to the bulk samples. This indicates that abrasion dominates shape evolution and hydraulic sorting plays a key role in downstream fining. In addition, abrupt changes of the sediments in particle shape from source to sink demonstrate the occurrence of aeolian-fluvial interaction processes along the Poyang Lake, which significantly improved particle shape of beach sand. These findings have significant implications for predicting the downstream evolution of sediments, and utilizing particle size and shape to aid in paleoenvironment reconstruction and source area constraints.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103156"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimating probable maximum precipitation for the continental United States 估计美国大陆可能的最大降水量

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-01-13 DOI: 10.1016/j.ejrh.2026.103122

Mochi Liao, Ana P. Barros

{"title":"Estimating probable maximum precipitation for the continental United States","authors":"Mochi Liao, Ana P. Barros","doi":"10.1016/j.ejrh.2026.103122","DOIUrl":"10.1016/j.ejrh.2026.103122","url":null,"abstract":"<div><h3>Study region</h3><div>The entire continental United States (CONUS).</div></div><div><h3>Study focus</h3><div>The objective of this manuscript is to estimate Probable Maximum Precipitation (PMP) using multifractal analysis for CONUS and to evaluate the impact of recent extreme events on PMP estimation and associated return periods using high-resolution precipitation datasets, including model reanalysis ERA5L at 9 km resolution, and multi-sensor gauge-corrected reanalysis AORC at 4 km resolution.</div></div><div><h3>New hydrological insights for the region</h3><div>The results show a strong spatial alignment between extreme precipitation, multifractal parameters, topography, and weather regimes. There is a large magnitude gap in estimated PMP between model-based and multi-sensor gauge-corrected precipitation products. The 24-hour PMP with return periods of one thousand and one million years are approximately 400 mm and 2000 mm, respectively, when using ERA5L, and 800 mm and 6000 mm when using AORC. Precipitation accumulations from recent extreme events are in keeping with PMP estimates derived from multifractal analysis using AORC, with a return period of 10<sup>3</sup>.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103122"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flood sedimentation dynamics in dam-regulated river channels: A case study of the Lower Yellow River 坝控河道的洪水沉积动力学——以黄河下游为例

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-01-16 DOI: 10.1016/j.ejrh.2026.103136

Xueqin Zhang , He Qing Huang , Yong Li , Chunjin Zhang , Min Zhang

{"title":"Flood sedimentation dynamics in dam-regulated river channels: A case study of the Lower Yellow River","authors":"Xueqin Zhang , He Qing Huang , Yong Li , Chunjin Zhang , Min Zhang","doi":"10.1016/j.ejrh.2026.103136","DOIUrl":"10.1016/j.ejrh.2026.103136","url":null,"abstract":"<div><h3>Study region</h3><div>The Lower Yellow River (LYR), China.</div></div><div><h3>Study focus</h3><div>The construction and operation of large dams can significantly alter runoff and sediment transport processes in downstream river channels, resulting in long-term and long-distance adjustments in river sedimentation. Since the Xiaolangdi Reservoir began impoundment in late 1999, the runoff and sediment transport processes in the LYR have experienced significant changes. To comprehend the response of sedimentation in the LYR to the reservoir’s operation, this study provides a detailed analysis of the spatiotemporal variations in sedimentation and examines the effects of 159 floods released from the Xiaolangdi Reservoir during 2000–2023.</div></div><div><h3>New hydrological insights for the region</h3><div>The LYR reached dynamic equilibrium following a long period of erosion, the magnitude of channel erosion increased rapidly from 2000 to 2004, then gradually decreased from 2004 to 2017. Floods were categorized into three types based on average sediment concentration (<em>S</em><sub><em>av</em></sub>), which varied under different reservoir regulation modes. During 2000–2023, the low (<em>S</em><sub><em>av</em></sub><1 kg/m<sup>3</sup>) and medium (1 ≤<em>S</em><sub><em>av</em></sub>≤10 kg/m<sup>3</sup>) sediment concentration floods yielded erosion, while the high sediment concentration floods (<em>S</em><sub><em>av</em></sub>>10 kg/m<sup>3</sup>) caused either aggradation or erosion. For a stable dynamic equilibrium (both erosion and aggradation are minor) to be maintained in the LYR, it is recommended that the sediment concentration of floods released from the Xiaolangdi Reservoir be kept below 40 kg/m<sup>3</sup>.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103136"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Understanding the co-occurrence of heavy metals and nutrients in urban stormwater runoff in Johannesburg City: Implications for water quality management 了解约翰内斯堡城市雨水径流中重金属和营养物质的共存：对水质管理的影响

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-01-14 DOI: 10.1016/j.ejrh.2025.103064

Ndivhuwo Ramovha , Martha Chadyiwa , Meta Jonathan Mvita , Freeman Ntuli , Thandiwe Nastassia Sithole

{"title":"Understanding the co-occurrence of heavy metals and nutrients in urban stormwater runoff in Johannesburg City: Implications for water quality management","authors":"Ndivhuwo Ramovha , Martha Chadyiwa , Meta Jonathan Mvita , Freeman Ntuli , Thandiwe Nastassia Sithole","doi":"10.1016/j.ejrh.2025.103064","DOIUrl":"10.1016/j.ejrh.2025.103064","url":null,"abstract":"<div><h3>Study region</h3><div>Johannesburg, South Africa, is a rapidly urbanising metropolis where mixed residential, commercial, and industrial land uses generate highly variable stormwater runoff that threatens downstream water quality. This study monitored multiple storm events across contrasting urban catchments to characterise pollutant dynamics under real-world hydrological conditions.</div></div><div><h3>Study focus</h3><div>The research quantified the co-occurrence of heavy metals (Cu, Fe, Zn) and nutrients (N, P) in stormwater using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and ion chromatography. Artificial neural network (ANN) models were then applied to predict pollutant concentrations under different land-use and seasonal scenarios. The models performed strongly (R² > 0.85) for key pollutants, showing that 76 % of samples exceeded local water quality guidelines for at least one metal. Peak zinc and nitrogen loads were linked to industrial runoff.</div></div><div><h3>New hydrological insight</h3><div>The findings demonstrate that high-density urban areas function as hotspots for simultaneous heavy metal and nutrient pollution, intensifying risks of eutrophication and ecological degradation in receiving waters. By linking ANN-based pollutant prediction with specific land-use classes, the study presents the first transferable framework for integrated stormwater quality management in Johannesburg and similar African megacities, supporting more spatially explicit regulation and prioritisation of pollution control measures.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103064"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stable isotope signatures of precipitation and implications for groundwater recharge on Jeju volcanic island, South Korea 济州岛火山岛降水稳定同位素特征及其地下水补给意义

IF 5 2区地球科学

Journal of Hydrology-Regional Studies Pub Date : 2026-04-01 Epub Date: 2026-01-13 DOI: 10.1016/j.ejrh.2026.103141

Min-Chul Kim , Woo-Jin Shin , Eun-Hee Koh , Chang-Seong Koh , Go-Eun Kim , Kwang-Sik Lee

{"title":"Stable isotope signatures of precipitation and implications for groundwater recharge on Jeju volcanic island, South Korea","authors":"Min-Chul Kim , Woo-Jin Shin , Eun-Hee Koh , Chang-Seong Koh , Go-Eun Kim , Kwang-Sik Lee","doi":"10.1016/j.ejrh.2026.103141","DOIUrl":"10.1016/j.ejrh.2026.103141","url":null,"abstract":"<div><h3>Study region</h3><div>Jeju Island, South Korea, is a volcanic island where the population depends entirely on groundwater for freshwater supply, and the island exhibits unique hydrogeological characteristics.</div></div><div><h3>Study focus</h3><div>This study examines groundwater recharge processes by analyzing the stable isotopes of oxygen (δ¹⁸O) and hydrogen (δ²H) in monthly precipitation and groundwater.</div></div><div><h3>New hydrological insights for the region</h3><div>Precipitation isotopes showed clear seasonal variability, characterized by a strong summer monsoon effect. Northern-slope precipitation was slightly more depleted in <sup>18</sup>O and has lower <em>d</em>-excess values compared to other slopes. Groundwater in this area exhibited similarly depleted isotopic signatures, suggesting that high-elevation recharge moves downgradient along preferential flow pathways toward coastal areas. Mixing analysis indicates that high-elevation summer rainfall is the dominant source of groundwater recharge. These findings significantly enhance the understanding of the linkages between precipitation patterns and groundwater recharge dynamics on the island.</div></div>","PeriodicalId":48620,"journal":{"name":"Journal of Hydrology-Regional Studies","volume":"64 ","pages":"Article 103141"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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