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 Q1 WATER RESOURCES

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

Study region

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.

Study focus

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_t to P_t–36) 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.

New hydrological insights for the region

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.

研究区域研究集中在德国北部的西贝尔河流域，这是一个小的山地集水区，其特点是降雨径流响应迅速，水文数据有限，短期流量变化很大。这些特点使该地区成为开发稳健、数据高效的短期径流预测模型的理想试验台。本研究提出了一种将极端梯度增强（XGBoost）与聚类算法（K-means和X-means）相结合的新型混合建模框架，以改进不确定性下的多步超前降雨径流预测。每小时降水径流数据和滞后降水输入（Pt至Pt - 36）用于生成1小时、2小时、3小时和6小时的预测。混合模型的基准是独立的XGBoost、主成分回归（PCR）和小型和未测量盆地的基于事件的概念方法（EBA4SUB）。使用RMSE、MAE、NSE、R²和不确定性界限来评估模型性能。将降雨-径流条件聚类为均匀的水文气象条件大大提高了预测精度。XGBoost-K-means模型表现最佳，预测误差低（提前6小时：RMSE = 0.580 m³/s, NSE = 0.954），不确定性范围最小（WUCB = 2.274）。这些发现表明，集群增强的机器学习模型为Sieber流域等小流域的短期预报提供了可靠且计算效率高的解决方案。这种混合方法支持在数据匮乏的环境中改进洪水预警、实时水资源管理和决策。

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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 Q1 WATER RESOURCES

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

Study region

Jiuzhaigou, a subalpine karst catchment located on the eastern margin of the Qinghai-Tibetan Plateau, China.

Study focus

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.

New hydrological insights for the region

At the catchment scale, KCS flux (t CO₂ yr^–1) comprises riverine dissolved inorganic carbon export (F_DIC), riverine autochthonous organic carbon export (F_AOC), and lacustrine autochthonous organic carbon burial (F_SOC). Jiuzhaigou exhibited a total KCS flux of 22510 ± 1400 t CO₂ yr^–1 and intensity of 35.0 ± 2.2 t CO₂ km⁻² yr^–1. F_DIC dominated KCS (91.7 %), followed by F_AOC (6.54 %) and F_SOC (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 (p < 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.

九寨沟是位于青藏高原东部边缘的亚高山喀斯特流域。本研究量化了青藏高原东部亚高山集水区九寨沟世界自然遗产的KCS，并比较了中国主要喀斯特地区的KCS强度。在流域尺度上，KCS通量（t CO2年- 1）包括河流溶解无机碳输出（FDIC）、河流原生有机碳输出（FAOC）和湖泊原生有机碳埋藏（FSOC）。九寨沟KCS总通量为22510 ± 1400 t CO2年- 1，强度为35.0 ± 2.2 t CO2 km - 2年- 1。FDIC主导KCS(91.7 %)，其次是FAOC（6.54 %）和FSOC（1.79 %）。地表水和沉积物中原生有机碳占季、年总有机碳的比例>； 75 %，溶解有机碳占水体总有机碳的比例>； 90 %。气候因素使九寨沟的溶解无机碳和有机碳输出强度介于青藏高原和华南喀斯特地区之间，超过华北喀斯特地区。相反，九寨沟湖相有机碳埋藏率显著高于3个区域（p <； 0.05），人为土地利用/覆被变化和地质灾害导致有机碳埋藏率升高，这在一定程度上增强了湖泊有机碳埋藏率。本研究填补了亚高山流域的KCS知识空白，并突出了其对人为和地质灾害干扰的敏感性。

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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 Q1 WATER RESOURCES

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

Study region

Dresden, Germany

Study focus

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.

New hydrological insights from the region

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.

研究区域：德累斯顿，德国研究重点：雨水径流运输颗粒和污染物，它们在城市水系中是高度流动的。它们的输出显示出污染物冲刷类型所描述的显著的时间变异性。了解这种变化对于改善城市集水区尺度的监测和提出雨水污染控制策略至关重要。因此，我们在降雨事件期间使用抓取样本和高分辨率监测数据，对德累斯顿（德国）一个雨水出口的沉积物出口和元素模式进行了表征。我们的研究结果表明，该地区的雨水排放主要由细颗粒物（< 63 µm）和无机沉积物组成，占悬浮沉积物的~ 80% %。两两关联和分层聚类分析显示，细粒和粗粒悬浮沉积物及其有机含量和元素（即Al， Ba, Cu, Fe, Mg, Mn, Zn）之间存在很强的肯德尔相关性，表明类似的运输机制。这些变量与浊度聚集在一起，强调其作为通过连续监测评估颗粒结合污染物动态的易于测量的代理的潜力。水文描述符可以解释冲刷类型的可变性。在分析的流域中，第二次冲水事件可能与先前的高强度降雨有关，突出了先前条件对运输动力学的影响。全年两种污染物冲刷类型的发生以及逆时针和顺时针两种滞后模式的存在提供了对延迟运输机制的见解，突出了在雨水管理中需要灵活的基础设施。

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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 Q1 WATER RESOURCES

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

Study region

Karst springs draining the Hochschwab massif, Eastern Alps, Austria.

Study focus

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.

Innovative insights

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.

研究区域：奥地利东阿尔卑斯山Hochschwab地块的喀斯特泉。研究重点泉水流量和水质的准确预测是水资源可持续管理的关键。尽管机器学习（ML）模型在预测水文变量方面显示出相当大的潜力，但对潜在过程的理解仍然有限。本研究旨在通过归因分析来提高机器学习模型的透明度，该分析探讨了当地环境因素对预测的贡献。利用光谱吸收系数在254 nm （UV254）处测量的几个ML模型，提前4天预测喀斯特泉的流量和水质。Deep SHAP方法有助于识别模式属性中显著的季节变化，显示出雪深最显著的变化，其次是物理化学变量，如电导率和其他气象变量。变形金刚模型表现出最好的综合性能。通过深度集合方法评估的模式不确定性在春季和夏季较大，模式误差和不确定性都随着目标变量的变率而增加。为了评估模型对选择性抽水的适用性，我们基于阈值超越对UV254预测进行了分类，获得了很高的分类精度（1天预测>；95 %，2天预测>；90 %）。集成深度SHAP和深度集成方法增强了机器学习的透明度。这种综合方法可以为喀斯特系统的饮用水管理决策提供信息。

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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 Q1 WATER RESOURCES

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

Study region

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.

Study focus

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.

New hydrological insights for the region

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.

研究区域研究的重点是位于极度干旱区的塔里木河流域，该地区受气候变化的影响，洪水事件日益频繁和严重。荒漠-绿洲过渡带由于植被覆盖有限、土壤渗透性低、水文变异性强，使洪水监测和管理变得十分复杂，因此具有高度脆弱性。研究重点在干旱环境下，能够在高时空分辨率下同时捕获洪水范围和河流动态的综合洪水模拟仍然很缺乏。为了解决这一差距，我们提出了一个可解释的深度学习框架，用于全流程洪水建模。该框架将每日30 m无缝数据立方体（SDC）遥感数据与基于深度学习的水文模型集成在一起。u形网络（UNet）用于提取每日洪水范围，而混合和纯深度学习模型在数据稀缺条件下模拟每日流量。这些模型的整合使得从地表淹没到河流流量的洪水过程得到一致的表示。Landsat图像验证证实，sdc衍生的洪水图的平均偏差低于5 %，而溪流模拟产生的中位数克林-古普塔效率（KGE）和纳什-苏特克利夫效率（NSE）值超过0.8。该框架成功地捕捉了干旱地区洪水的时空动态。此外，可解释性分析表明，加速融雪是最近洪水事件的主要驱动因素。这项研究为改善全球干旱地区的洪水建模和监测提供了一种可转移的、数据高效的方法。

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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 Q1 WATER RESOURCES

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

Study region

The Ganjiang River in southern China.

Study focus

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.

New hydrological insights for the region

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.

研究区域：中国南部的赣江流域。研究重点研究了砾石河床中普遍存在的沉积物下游细化和围成的规律和机制。然而，人们对砂床河流中的这些过程知之甚少。本研究利用动态图像技术和地球化学元素，分析了一条沙床河流从源到汇625 km样带的37个河砂、25个滩砂和17个沙丘砂样品，探讨了不同砂组分粒度和形状的下游演化规律。研究结果表明，随着下游距离的增加，中沙粒和散装沙粒逐渐变得更圆、更细，而悬浮运输的细沙粒则没有明显的下游趋势。中砂粒的直径减小率要小得多，但与大块样品相比，形状改善率大致相等。这表明磨蚀作用主导了岩石的形状演变，水力分选在下游细化过程中起着关键作用。此外，沉积物颗粒形态从源到汇的突变表明，鄱阳湖沿岸发生了风—河相互作用，显著改善了滩砂的颗粒形态。这些发现对于预测沉积物的下游演化，以及利用粒度和形状来帮助古环境重建和源区约束具有重要意义。

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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 Q1 WATER RESOURCES

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

Study region

The entire continental United States (CONUS).

Study focus

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.

New hydrological insights for the region

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 10³.

研究区域整个美国大陆（CONUS）。本文的目的是利用CONUS的多重分形分析估计可能最大降水（PMP），并利用高分辨率降水数据集评估最近极端事件对PMP估计和相关回归期的影响，包括9 km分辨率的模型再分析ERA5L和4 km分辨率的多传感器测量校正再分析AORC。研究结果表明，极端降水、多重分形参数、地形和天气状况之间存在强烈的空间一致性。在基于模式的估计PMP和多传感器计校正的降水产品之间存在很大的数量级差距。ERA5L的24小时PMP分别约为400 mm和2000 mm， orc的24小时PMP分别约为800 mm和6000 mm。最近极端事件的降水积累与利用orc进行多重分形分析得出的PMP估计一致，回归期为103。

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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 Q1 WATER RESOURCES

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

Study region

The Lower Yellow River (LYR), China.

Study focus

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.

New hydrological insights for the region

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 (S_av), which varied under different reservoir regulation modes. During 2000–2023, the low (S_av<1 kg/m³) and medium (1 ≤S_av≤10 kg/m³) sediment concentration floods yielded erosion, while the high sediment concentration floods (S_av>10 kg/m³) 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/m³.

研究区域：中国黄河下游。研究重点大型水坝的建设和运行可以显著改变下游河道的径流和输沙过程，从而对河流的沉积产生长期和远距离的调节。自1999年底小浪底水库蓄水以来，三峡库区径流输沙过程发生了显著变化。为了解三峡库区泥沙淤积对水库运行的响应，本文详细分析了三峡库区泥沙淤积的时空变化特征，并考察了2000-2023年小浪底水库159次放水对三峡库区的影响。经过长时间的侵蚀，LYR达到了动态平衡，2000 - 2004年河道侵蚀幅度快速增加，2004 - 2017年逐渐减小。根据平均含沙量（Sav）将洪水分为三种类型，不同的水库调节模式下，平均含沙量有所不同。2000-2023年，低含沙量（Sav>1 kg/m3）和中含沙量（1 ≤Sav≤10 kg/m3）洪水发生侵蚀，高含沙量（Sav>10 kg/m3）洪水发生淤积或侵蚀。为使三峡库区保持稳定的动态平衡（侵蚀和淤积均较小），建议将小浪底水库泄洪泥沙浓度控制在40 kg/m3以下。

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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 Q1 WATER RESOURCES

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

Study region

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.

Study focus

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.

New hydrological insight

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.

研究区域南非约翰内斯堡是一个快速城市化的大都市，住宅、商业和工业用地混合使用产生高度变化的雨水径流，威胁下游水质。本研究监测了不同城市集水区的多次风暴事件，以表征真实水文条件下的污染物动态。本研究采用电感耦合等离子体质谱（ICP-MS）和离子色谱法定量分析了暴雨水体中重金属（Cu、Fe、Zn）和营养物质（N、P）的共生态。应用人工神经网络（ANN）模型对不同土地利用和季节情景下的污染物浓度进行预测。模型对主要污染物的表现很好（R²> 0.85），表明76% %的样本至少有一种金属超过了当地的水质标准。锌和氮负荷峰值与工业径流有关。研究结果表明，高密度城市地区是重金属和营养物质同时污染的热点地区，加剧了接收水域富营养化和生态退化的风险。通过将基于人工神经网络的污染物预测与特定的土地利用类别联系起来，该研究提出了约翰内斯堡和类似非洲大城市综合雨水质量管理的第一个可转移框架，支持更明确的空间监管和污染控制措施的优先级。

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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 Q1 WATER RESOURCES

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

Study region

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.

Study focus

This study examines groundwater recharge processes by analyzing the stable isotopes of oxygen (δ¹⁸O) and hydrogen (δ²H) in monthly precipitation and groundwater.

New hydrological insights for the region

Precipitation isotopes showed clear seasonal variability, characterized by a strong summer monsoon effect. Northern-slope precipitation was slightly more depleted in ¹⁸O and has lower d-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.

研究区域韩国济州岛是一个火山岛，人口完全依赖地下水供应淡水，岛上具有独特的水文地质特征。本研究通过分析月降水和地下水中氧（δ¹⁸O）和氢（δ²H）的稳定同位素，探讨地下水补给过程。降水同位素显示出明显的季节变化，其特征是强烈的夏季风效应。18O年北坡降水耗竭程度略高，d-excess值低于其他坡。该地区的地下水表现出类似的枯竭同位素特征，表明高海拔补给沿着优先流向沿海地区的流动路径向下梯度移动。混合分析表明，夏季高海拔降水是地下水补给的主要来源。这些发现大大加强了对岛上降水模式与地下水补给动态之间联系的认识。

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