Journal of Hydrology最新文献_第5页

Prediction of phosphorus loads for ungauged basins using probabilistic export coefficient model 基于概率输出系数模型的未计量流域磷负荷预测

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-14 DOI: 10.1016/j.jhydrol.2026.134973

Li Zhang, Theodore A. Endreny

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.

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 (r), a decrease of 0.13 in the Index of Agreement (d), 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 d, 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.

观测到的排放量被用来估计进入接收水域的非点或扩散磷负荷的时间变化。鉴于大量河流流域的排放数据有限或没有，本研究评估了是否可以使用降水或模拟排放量的日概率时间序列来生成可靠的年总磷负荷估算。i-Tree概率输出系数模型使用每日概率时间序列模拟进入和通过河网的负荷，以模拟年总磷负荷。根据观测负荷对两种类型的多年代际概率时间序列进行了测试，并以观测流量驱动的模拟为基准：从观测降水中获得，代表未测量的流域；从模拟流量中获得，使用至少一年的河流流量观测进行校准。模型的性能在美国三个不同的河流流域进行了测试。与利用实测流量估算的年负荷相比，利用模拟流量估算的年负荷的Pearson相关系数(r)降低了0.25，一致性指数(d)降低了0.13，均方根误差（RMSE）和平均绝对误差（MAE）分别增加了13.3公吨和15.7公吨，百分比偏差（Pbias）增加了3.90%。基于观测降水的估算显示出更大的性能下降，d减少0.41，RMSE增加14.9公吨，MAE增加14.5公吨，Pbias减少6.6%。这些发现表明，虽然模拟的流量提供了更准确的估算，但基于降水的估算仍然是未测量流域的可行选择。

{"title":"Prediction of phosphorus loads for ungauged basins using probabilistic export coefficient model","authors":"Li Zhang, 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}

引用次数: 0

Recharge elevation, residence time and renewability of groundwater in the Upper Awash valley, Ethiopia: Applying environmental tracers in a highly populated volcanic basin 埃塞俄比亚上阿瓦什河谷地下水补给高度、停留时间和可再生性：在人口密集的火山盆地中应用环境示踪剂

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-23 DOI: 10.1016/j.jhydrol.2026.134989

W. George Darling , James P.R. Sorensen , Tilahun Azagegn , Behailu Birhanu , Seifu Kebede , Daren C. Gooddy , Koos Groen , Richard G. Taylor , Alan M. MacDonald

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 < 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.

埃塞俄比亚的上阿瓦什盆地（Upper Awash Basin）包含了迅速扩张的国家首都亚的斯亚贝巴（Addis Ababa），该地区正日益受到地下水开采的影响，导致许多地区的水位下降。由于对这个高起伏盆地下复杂火山含水层的详细（水文）地质特征缺乏共识，地下水管理受到损害。本文采用环境示踪剂（同位素、微量气体和水化学）对40个地下水样本进行了测量，以探索盆地的水文地质功能。稳定同位素δ18O和δ2H提供了可能补给高度（海拔1900-3500米）和地表水对补给的贡献程度（45%的采样点）的信息。微量气体CFCs和SF6表明现代水的比例一般为10%，但14C表明，目前对缓冲变化至关重要的地下水储存在大多数情况下是数百年而不是数千年，因此可能容易受到相对快速的改变。由于几乎没有证据表明单个井田的水文地球化学变化随深度的显著变化，我们得出结论，尽管在一些地方（主要是Mojo镇周围）存在较长的流动路径，但补给通常来自局部。水化学表明，目前无机地下水水质良好，地表水水质较差。这项研究的方法可以应用于其他依赖地下水的高起伏盆地，以表征缺乏详细地质模型和长期监测的抽取脆弱性。

{"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 , James P.R. Sorensen , Tilahun Azagegn , Behailu Birhanu , Seifu Kebede , Daren C. Gooddy , Koos Groen , Richard G. Taylor , 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 δ<sup>18</sup>O and δ<sup>2</sup>H 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 SF<sub>6</sub> show that proportions of modern water are generally < 10%, but <sup>14</sup>C 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}

引用次数: 0

Peridynamics modeling of multi-fissure occurrence in the subsiding North China plain 华北沉降平原多裂隙产状的周动力学模拟

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-21 DOI: 10.1016/j.jhydrol.2026.134970

Miao Ye , Lin Zhu , Andrea Franceschini , Huili Gong , Pietro Teatini

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.

了解过量的地下水抽取和抽水如何在地表引发地裂缝，对于沉降沉积盆地地下资源的可持续管理至关重要。这种水文地质灾害已成为全球日益关注的问题，影响了许多国家（如美国、中国、伊朗和墨西哥）。预测从连续地面沉降到不连续裂缝的过渡是一个重大挑战。在此，我们提出了一种基于普通状态周动力学（PD）的有效方法来模拟地下水超采引起的裂缝演化。首先，分析了不同水文地质配置下多裂隙的产生和扩展，即露头基岩、预先存在的断层与层状含水层系统相抵消、基岩脊被冲积沉积物覆盖。然后，该方法被用于调查北京周边华北平原的裂缝发生情况，该地区受到数千个与先前存在的断层相关的地裂缝的影响，这些裂缝是在过去几十年里由于含水层系统的过度开采而在地震中重新激活的。PD模型强调，随着断层倾角、含水层厚度、压力下降和地表沉积物刚度的增加，更宽（高达0.7 m）和更深（高达35 m）的裂缝会发育。杨氏模量和孔隙水压力对地裂缝的规模控制最为显著，含水层厚度主要影响地裂缝的几何特征，断裂带倾角支配地裂缝的空间分布格局。

{"title":"Peridynamics modeling of multi-fissure occurrence in the subsiding North China plain","authors":"Miao Ye , Lin Zhu , Andrea Franceschini , Huili Gong , 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}

引用次数: 0

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 考虑径流演化时空效应的耦合机制与数据驱动模型在梯级水电站水位预测中的应用

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-29 DOI: 10.1016/j.jhydrol.2026.135057

Yubin Zhang , Xiaoqun Wang , Jijian Lian , Pingping Luo

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.

由于梯级水电系统的径流演化和动态调节复杂，对其水位的准确预测具有一定的挑战性。本研究提出了一个耦合模型，该模型集成了水动力学模型（HD）、水平衡模型（WB）和反向传播神经网络（BP），结合了机制和数据驱动的方法来解决这些挑战。基于Saint-Venant方程建立了镇头大坝与沙坪二水电站之间的HD模型，该模型明确考虑了动态库容和径流演化效应，对短期预报精度有显著影响。WB通过物理平衡定律描述水位变化，而BP从历史数据中捕获非线性波动模式。为了结合这些优点，引入粒子群优化算法对模型输出进行动态加权，使框架能够实时自适应地纠正预测误差。应用结果表明，新方法的HD-WB-BP耦合模型显著提高了预测性能。与单独的WB和BP模型相比，新方法的均方根误差（RMSE）降低了约30%，Nash-Sutcliffe效率（NSE）始终高于0.90，相关系数(r)为0.96，平均绝对百分比误差（MAPE）为3.8%。该模型还有效地减小了预测滞后，在受动态蓄水量和径流演变影响的条件下提供了更准确的峰值估计。此外，新方法将P95延迟保持在= 10174.68 ms，安全地保持在5分钟的周期内。这证明了近实时操作的准确性和效率之间的良好平衡。总体而言，该方法为梯级水电系统的水位预测提供了一个强大且可扩展的框架，强调了将物理机制模型和数据驱动模型相结合的优势，以提高可靠性和运营决策。

{"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 , Xiaoqun Wang , Jijian Lian , 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}

引用次数: 0

A physically-based model for particle transport over urban road surface with consideration of raindrop erosion and runoff effect 考虑雨滴侵蚀和径流效应的城市路面颗粒运移物理模型

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-27 DOI: 10.1016/j.jhydrol.2026.135033

Taotao Zhang , Bin Luan , Chi Zhang , Yang Xiao , Chen Xu , Jingxiu Wu

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.

城市路面上的颗粒运输是城市雨水污染的一个重要因素。然而，现有的颗粒输运模型主要关注单个降雨效应，对雨滴侵蚀和径流效应的耦合效应认识不足。本研究通过引入考虑雨滴侵蚀和径流效应的双层概念模型，提出了一种新的基于物理的运移模型。模型假设静态控制层中的颗粒可以通过雨滴侵蚀和径流作用进入上层径流层。为了验证所提出的模型，我们进行了一系列的室内实验，考虑了有雨滴侵蚀和没有雨滴侵蚀以及混合颗粒的情况。结果表明，在各种条件下，模型预测结果与实验观测结果吻合良好。临界径流能与中位粒径呈正相关，效率系数随粒径的减小而增大。雨滴侵蚀使峰值浓度和输运速率提高了3 ~ 4倍，并显著提高了大颗粒的最终冲刷分数。敏感性分析表明，曼宁系数和控制层深度会减弱峰值输运率，而坡长和分离系数会增强峰值输运率。该研究促进了对城市环境中颗粒输运机制的认识，并为开发分布式集水区模型提供了基础。

{"title":"A physically-based model for particle transport over urban road surface with consideration of raindrop erosion and runoff effect","authors":"Taotao Zhang , Bin Luan , Chi Zhang , Yang Xiao , Chen Xu , 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}

引用次数: 0

How much historical data do we need? The role of data recency and training period length in LSTM-based rainfall-runoff modeling 我们需要多少历史数据？数据近代性和训练周期长度在基于lstm的降雨径流模型中的作用

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-27 DOI: 10.1016/j.jhydrol.2026.135046

Qiutong Yu, Bryan Tolson

Rainfall-runoff models based on Long Short-Term Memory (LSTM) networks typically require extensive datasets for training. While increasing the number of watersheds generally improves model performance, the appropriate temporal scope of training data—especially under potential non-stationarity from climate change—remains unclear, and the importance of data recency remains underexplored. This study investigates whether decades of historical data are necessary when training with large numbers of watersheds, and whether shorter, more recent training periods can match the performance of extended records. Using hydrometeorological data from 1374 North American watersheds (spanning 1950–2023), we systematically evaluate the effect of data recency on LSTM performance through three complementary experimental designs: (1) backward-expanding training periods (fixed recent data + progressively older blocks), (2) forward-expanding periods (fixed old data + progressively newer blocks), and (3) sliding-window periods (fixed-length windows moving forward). Results reveal that newer data universally improves predictions, while older data contributes marginally or negatively to model performance. Notably, the benefit of increasing the number of watersheds is conditional on data recency, as Prediction in Ungauged Basins (PUB) performance improves most significantly with recent data. These findings provide the empirical evidence for the importance of data recency, demonstrating that data recency—not just data volume—is critical for LSTM-based streamflow prediction, underscoring the need for recency-aware training strategies.

基于长短期记忆（LSTM）网络的降雨径流模型通常需要大量的数据集进行训练。虽然增加流域的数量通常可以提高模型的性能，但训练数据的适当时间范围（特别是在气候变化潜在的非平稳性下）仍不清楚，数据近时性的重要性仍未得到充分探讨。本研究调查了在使用大量流域进行训练时，几十年的历史数据是否必要，以及更短、更近的训练周期是否可以与延长记录的表现相匹配。利用1374个北美流域（跨越1950-2023年）的水文气象数据，我们通过三个互补的实验设计系统地评估了数据近代性对LSTM性能的影响：(1)向后扩展的训练期（固定的近期数据+逐渐变老的数据块），(2)向前扩展的训练期（固定的旧数据+逐渐变新的数据块），以及(3)滑动窗口期（固定长度的窗口向前移动）。结果表明，新数据普遍提高了预测，而旧数据对模型性能的贡献很小，甚至是负的。值得注意的是，增加流域数量的好处取决于数据的近时性，因为未测量流域预测（PUB）的性能在最近的数据中得到了最显著的改善。这些发现为数据近代性的重要性提供了经验证据，表明数据近代性——而不仅仅是数据量——对于基于lstm的流预测至关重要，强调了对近代性感知训练策略的需求。

{"title":"How much historical data do we need? The role of data recency and training period length in LSTM-based rainfall-runoff modeling","authors":"Qiutong Yu, Bryan Tolson","doi":"10.1016/j.jhydrol.2026.135046","DOIUrl":"10.1016/j.jhydrol.2026.135046","url":null,"abstract":"<div><div>Rainfall-runoff models based on Long Short-Term Memory (LSTM) networks typically require extensive datasets for training. While increasing the number of watersheds generally improves model performance, the appropriate temporal scope of training data—especially under potential non-stationarity from climate change—remains unclear, and the importance of data recency remains underexplored. This study investigates whether decades of historical data are necessary when training with large numbers of watersheds, and whether shorter, more recent training periods can match the performance of extended records. Using hydrometeorological data from 1374 North American watersheds (spanning 1950–2023), we systematically evaluate the effect of data recency on LSTM performance through three complementary experimental designs: (1) backward-expanding training periods (fixed recent data + progressively older blocks), (2) forward-expanding periods (fixed old data + progressively newer blocks), and (3) sliding-window periods (fixed-length windows moving forward). Results reveal that newer data universally improves predictions, while older data contributes marginally or negatively to model performance. Notably, the benefit of increasing the number of watersheds is conditional on data recency, as Prediction in Ungauged Basins (PUB) performance improves most significantly with recent data. These findings provide the empirical evidence for the importance of data recency, demonstrating that data recency—not just data volume—is critical for LSTM-based streamflow prediction, underscoring the need for recency-aware training strategies.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 135046"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146072673","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}

引用次数: 0

Impacts of spatial-temporal rainfall structures and antecedent wetness on flood variability at the catchment scale 时空降水结构和前期湿度对流域尺度洪水变率的影响

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-29 DOI: 10.1016/j.jhydrol.2026.135019

Wencong Yang , Changming Li , Hanbo Yang

Rainfall amounts largely determine flood magnitudes, but the influence of spatial–temporal rainfall structures and antecedent wetness remains unclear. This study presents a new approach to derive flood variability using different combinations of “event indicators”, which describe spatial–temporal rainfall dynamics and antecedent wetness at the catchment scale, while holding rainfall intensity fixed. Specifically, a multivariate distribution generates synthetic event indicators conditioned on rainfall intensity for historical high-rainfall events, and a data-driven runoff model predicts flood peaks based on these indicators. Applied to daily flood events in 140 catchments (304–86,475 km²) across the Eastern Monsoon Region of China, the approach uncovers the effects of event indicators on event flood variability and flood quantile uncertainty. Single-peak temporal rainfall and spatial uniform rainfall are prevalent across events. Antecedent wetness has the greatest impact on flood peak variability, with an attributable coefficient of variance (CV) of 0.23, followed by temporal (CV = 0.16) and spatial rainfall structures (CV = 0.05). Spatial-temporal rainfall correlation has minimal effects. Antecedent wetness and spatial rainfall structures exhibit greater impact in drier catchments, while temporal structures have less impact in larger, elongated catchments. For flood quantiles, variability in event indicators results in a mean CV of 0.15 across catchments for 50-year flood estimates, while uncertainty associated with unobserved hydrologic conditions accounts for 79% of total sampling uncertainty. These findings emphasize the need to incorporate spatial–temporal rainfall variability and antecedent wetness into flood risk estimation and process understanding.

降雨量在很大程度上决定了洪水的大小，但时空降雨结构和前期湿度的影响尚不清楚。该研究提出了一种利用“事件指标”的不同组合来推导洪水变率的新方法，这些“事件指标”描述了流域尺度上的时空降雨动态和先前的湿度，同时保持降雨强度固定。具体而言，多变量分布生成以历史高降雨事件的降雨强度为条件的综合事件指标，数据驱动的径流模型根据这些指标预测洪峰。将该方法应用于中国东部季风区140个流域（304-86,475 km2）的日洪水事件，揭示了事件指标对事件洪水变率和洪水分位数不确定性的影响。单峰时间降水和空间均匀降水在各事件中普遍存在。前缘湿度对洪峰变率的影响最大，其归因方差系数（CV）为0.23，其次是时间（CV = 0.16）和空间降雨结构（CV = 0.05）。时空降水相关性影响最小。先前的湿度和空间降雨结构对干旱流域的影响更大，而时间结构对较大的狭长流域的影响较小。对于洪水分位数，事件指标的可变性导致各流域50年洪水估计的平均CV为0.15，而与未观测到的水文条件相关的不确定性占总采样不确定性的79%。这些发现强调了在洪水风险评估和过程理解中纳入降雨时空变率和前期湿度的必要性。

{"title":"Impacts of spatial-temporal rainfall structures and antecedent wetness on flood variability at the catchment scale","authors":"Wencong Yang , Changming Li , Hanbo Yang","doi":"10.1016/j.jhydrol.2026.135019","DOIUrl":"10.1016/j.jhydrol.2026.135019","url":null,"abstract":"<div><div>Rainfall amounts largely determine flood magnitudes, but the influence of spatial–temporal rainfall structures and antecedent wetness remains unclear. This study presents a new approach to derive flood variability using different combinations of “event indicators”, which describe spatial–temporal rainfall dynamics and antecedent wetness at the catchment scale, while holding rainfall intensity fixed. Specifically, a multivariate distribution generates synthetic event indicators conditioned on rainfall intensity for historical high-rainfall events, and a data-driven runoff model predicts flood peaks based on these indicators. Applied to daily flood events in 140 catchments (304–86,475 km<sup>2</sup>) across the Eastern Monsoon Region of China, the approach uncovers the effects of event indicators on event flood variability and flood quantile uncertainty. Single-peak temporal rainfall and spatial uniform rainfall are prevalent across events. Antecedent wetness has the greatest impact on flood peak variability, with an attributable coefficient of variance (CV) of 0.23, followed by temporal (CV = 0.16) and spatial rainfall structures (CV = 0.05). Spatial-temporal rainfall correlation has minimal effects. Antecedent wetness and spatial rainfall structures exhibit greater impact in drier catchments, while temporal structures have less impact in larger, elongated catchments. For flood quantiles, variability in event indicators results in a mean CV of 0.15 across catchments for 50-year flood estimates, while uncertainty associated with unobserved hydrologic conditions accounts for 79% of total sampling uncertainty. These findings emphasize the need to incorporate spatial–temporal rainfall variability and antecedent wetness into flood risk estimation and process understanding.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135019"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071823","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}

引用次数: 0

High-precision numerical simulation framework for the integrated modeling of urban “Source-Plant-Network-River” water environment 城市“源-植物-网络-河流”水环境一体化建模的高精度数值模拟框架

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-29 DOI: 10.1016/j.jhydrol.2026.135036

Guangxue Luan , Jingming Hou , Fuqiang Wang , Tian Wang , Donglai Li

Urban water environments are facing increasingly severe pollution challenges, and rigorous numerical models have become indispensable for mitigating urban water pollution. Building on the “Gridding + GPU acceleration + Dynamic Link Library (DLL)” approach, this study develops an advanced coupled model that integrates (i) two-dimensional (2D) surface-water hydrodynamics and water-quality transport, (ii) 2D non-point-source pollutant (NPSP) build-up and wash-off, and (iii) one-dimensional (1D) pipe-network drainage and pollutant discharge, thereby enabling integrated simulation of the urban “Source-Plant-Network-River” (SPNR) system. The model employs high-resolution structured grids and a spatiotemporal flux scheme for multi-component pollutants in surface runoff, allowing accurate representation of NPSP wash-off and transport driven by coupled hydrological-hydrodynamic processes. DLL-based bidirectional coupling is implemented to dynamically link 2D surface processes and 1D pipe network hydraulics and water quality processes while reducing distortions in parameter transfer across modules. GPU acceleration, together with optimized water-quality flux computations and removal of redundant operations, significantly improves computational efficiency. The model is applied to the main urban area of Changzhi City under three spatially distributed rainfall scenarios. Performance is evaluated against observations of inundation depth, zoned drainage/sewage discharge, and combined sewer overflow (CSO) flow and water quality. The results show that the Nash-Sutcliffe efficiency (NSE) exceeds 0.7 for inundation depths at four flood-prone locations and for flow and pollutant concentrations at three representative drainage-outfall zones and four CSO outfalls. On an RTX 3070 workstation, the optimized model completes a 7.22 h simulation on 8,484,785 uniform structured grids coupled with 32,982 pipe-network nodes in 8.15 h, reducing runtime by 12.6% compared with the pre-optimization model. The proposed modeling framework is robust and efficient, offering strong potential for high-precision integrated simulations of urban water environments from source to receiving waters, as well as for evaluation, forecasting, early warning, and comprehensive water-environment management from a watershed perspective.

城市水环境面临着日益严峻的污染挑战，严谨的数值模拟已成为缓解城市水污染不可缺少的手段。基于“网格+ GPU加速+动态链接库（DLL）”方法，本研究开发了一种先进的耦合模型，该模型集成了(i)二维（2D）地表水流体动力学和水质运输，（ii）二维非点源污染物（NPSP）的积累和冲刷，以及（iii）一维（1D）管网排水和污染物排放，从而实现了城市“源-植物-网络-河流”（SPNR）系统的综合模拟。该模型采用高分辨率结构网格和地表径流中多组分污染物的时空通量方案，可以准确表示由水文-水动力耦合过程驱动的NPSP冲刷和输送。基于dll的双向耦合实现了二维表面过程与一维管网水力和水质过程的动态连接，同时减少了模块间参数传递的失真。GPU加速，加上优化的水质通量计算和去除冗余操作，显著提高了计算效率。将该模型应用于长治市主城区三种降雨空间分布情景。性能是根据淹没深度、分区排水/污水排放、综合下水道溢流（CSO）流量和水质的观察来评估的。结果表明，在4个洪水易发区的淹没深度、3个代表性排水口和4个CSO排水口的流量和污染物浓度方面，Nash-Sutcliffe效率（NSE）超过0.7。在RTX 3070工作站上，优化后的模型在8.15 h内完成了8,484,785个均匀结构网格和32,982个管网节点的7.22 h的仿真，与优化前模型相比，运行时间减少了12.6%。该模型框架稳健高效，为实现城市水环境从源头到受水的高精度综合模拟，以及流域评价、预报、预警和综合水环境管理提供了强大的潜力。

{"title":"High-precision numerical simulation framework for the integrated modeling of urban “Source-Plant-Network-River” water environment","authors":"Guangxue Luan , Jingming Hou , Fuqiang Wang , Tian Wang , Donglai Li","doi":"10.1016/j.jhydrol.2026.135036","DOIUrl":"10.1016/j.jhydrol.2026.135036","url":null,"abstract":"<div><div>Urban water environments are facing increasingly severe pollution challenges, and rigorous numerical models have become indispensable for mitigating urban water pollution. Building on the “Gridding + GPU acceleration + Dynamic Link Library (DLL)” approach, this study develops an advanced coupled model that integrates (i) two-dimensional (2D) surface-water hydrodynamics and water-quality transport, (ii) 2D non-point-source pollutant (NPSP) build-up and wash-off, and (iii) one-dimensional (1D) pipe-network drainage and pollutant discharge, thereby enabling integrated simulation of the urban “Source-Plant-Network-River” (SPNR) system. The model employs high-resolution structured grids and a spatiotemporal flux scheme for multi-component pollutants in surface runoff, allowing accurate representation of NPSP wash-off and transport driven by coupled hydrological-hydrodynamic processes. DLL-based bidirectional coupling is implemented to dynamically link 2D surface processes and 1D pipe network hydraulics and water quality processes while reducing distortions in parameter transfer across modules. GPU acceleration, together with optimized water-quality flux computations and removal of redundant operations, significantly improves computational efficiency. The model is applied to the main urban area of Changzhi City under three spatially distributed rainfall scenarios. Performance is evaluated against observations of inundation depth, zoned drainage/sewage discharge, and combined sewer overflow (CSO) flow and water quality. The results show that the Nash-Sutcliffe efficiency (<em>NSE</em>) exceeds 0.7 for inundation depths at four flood-prone locations and for flow and pollutant concentrations at three representative drainage-outfall zones and four CSO outfalls. On an RTX 3070 workstation, the optimized model completes a 7.22 h simulation on 8,484,785 uniform structured grids coupled with 32,982 pipe-network nodes in 8.15 h, reducing runtime by 12.6% compared with the pre-optimization model. The proposed modeling framework is robust and efficient, offering strong potential for high-precision integrated simulations of urban water environments from source to receiving waters, as well as for evaluation, forecasting, early warning, and comprehensive water-environment management from a watershed perspective.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 135036"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071824","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}

引用次数: 0

Developing a radar-rain gauge hourly blended precipitation dataset for Great Britain using the Gauss Blending Method 利用高斯混合方法为英国开发雷达雨量计每小时混合降水数据集

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-01-19 DOI: 10.1016/j.jhydrol.2026.134954

X. Qiu , A.C. Green , S. Blenkinsop , H.J. Fowler

Blended rainfall datasets take advantage of the strengths of multiple sources of rainfall data, producing higher accuracy and broader coverage. However, current blending methods either suffer from low accuracy or are overly complex. Some focus solely on improving statistical performance, but sacrifice the spatial structure of rainfall. Here we develop a Gauss Blending Method (GBM), based on an adaptation of the Gauss-Seidel method, to merge radar and gauge rainfall (970 gauges) in Great Britain to produce a high-resolution (1 km) hourly blended precipitation product. A comparison to 194 independent gauges (2006–2018) demonstrates that the blended product reduces the RMSE, MAE and MRE, compared with the only radar data, by 14.5%, 14.5% and 22.1% respectively, while improving its CC and NSE by 7.8% and 23.2%. GBM also enhances rainfall detectability without introducing new systematic bias.

GBM is compared with five standard approaches. The Multiplicative Adjustment Method and Mean Field Bias Adjustment Methods perform poorly and fail to improve radar rainfall. The Additive and Mixed Adjustment Methods show slightly worse performance and less stable rainfall detection skill, producing rainfall fields with artificial discontinuities and wedge-shaped artefacts. The only comparable method across most metrics is Kriging with External Drift. However, the GBM generates more complete data coverage, shows a better performance for extreme rainfall of ≥ 10 mm h⁻¹, better preserves rainfall structure and local variability, and is easy to apply. This is shown for several example extreme rainfall events. The resulting radar-gauge blended dataset will facilitate the analysis of spatial rainfall variability and extreme rainfall over GB, with significant advantages for extremes analysis, hydrological modeling, and flood risk assessment.

混合降雨数据集利用了多个降雨数据来源的优势，产生更高的准确性和更广泛的覆盖范围。然而，目前的混合方法要么精度低，要么过于复杂。有些只注重提高统计性能，而牺牲了降雨的空间结构。在这里，我们开发了一种高斯混合方法（GBM），基于高斯-塞德尔方法的改编，将英国的雷达和雨量计（970个雨量计）合并在一起，以产生高分辨率（1公里）每小时的混合降水产品。与194个独立仪表（2006-2018）的比较表明，与单一雷达数据相比，混合产品的RMSE、MAE和MRE分别降低了14.5%、14.5%和22.1%，而CC和NSE分别提高了7.8%和23.2%。GBM还在不引入新的系统偏差的情况下提高了降雨的可探测性。对五种标准方法进行了比较。乘法平差法和平均场偏置平差法对雷达降雨的改善效果较差。加性平差法和混合平差法表现出较差的性能和较差的降雨检测能力，产生的降雨场具有人工不连续面和楔形伪影。在大多数参数中唯一可比较的方法是Kriging与External Drift。而GBM的数据覆盖更全面，对≥10 mm h−1的极端降雨表现出更好的性能，更好地保留了降雨结构和局地变率，并且易于应用。这是几个极端降雨事件的例子。由此产生的雷达-测量混合数据集将有助于分析GB的空间降雨变异和极端降雨，在极端分析、水文建模和洪水风险评估方面具有显著优势。

{"title":"Developing a radar-rain gauge hourly blended precipitation dataset for Great Britain using the Gauss Blending Method","authors":"X. Qiu , A.C. Green , S. Blenkinsop , H.J. Fowler","doi":"10.1016/j.jhydrol.2026.134954","DOIUrl":"10.1016/j.jhydrol.2026.134954","url":null,"abstract":"<div><div>Blended rainfall datasets take advantage of the strengths of multiple sources of rainfall data, producing higher accuracy and broader coverage. However, current blending methods either suffer from low accuracy or are overly complex. Some focus solely on improving statistical performance, but sacrifice the spatial structure of rainfall. Here we develop a Gauss Blending Method (GBM), based on an adaptation of the Gauss-Seidel method, to merge radar and gauge rainfall (970 gauges) in Great Britain to produce a high-resolution (1 km) hourly blended precipitation product. A comparison to 194 independent gauges (2006–2018) demonstrates that the blended product reduces the RMSE, MAE and MRE, compared with the only radar data, by 14.5%, 14.5% and 22.1% respectively, while improving its CC and NSE by 7.8% and 23.2%. GBM also enhances rainfall detectability without introducing new systematic bias.</div><div>GBM is compared with five standard approaches. The Multiplicative Adjustment Method and Mean Field Bias Adjustment Methods perform poorly and fail to improve radar rainfall. The Additive and Mixed Adjustment Methods show slightly worse performance and less stable rainfall detection skill, producing rainfall fields with artificial discontinuities and wedge-shaped artefacts. The only comparable method across most metrics is Kriging with External Drift. However, the GBM generates more complete data coverage, shows a better performance for extreme rainfall of ≥ 10 mm h<sup>−1</sup>, better preserves rainfall structure and local variability, and is easy to apply. This is shown for several example extreme rainfall events. The resulting radar-gauge blended dataset will facilitate the analysis of spatial rainfall variability and extreme rainfall over GB, with significant advantages for extremes analysis, hydrological modeling, and flood risk assessment.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134954"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146001381","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}

引用次数: 0

Spatiotemporal dynamics of meteorological and groundwater droughts in Southwest China and their cumulative and lagged impacts on vegetation 西南地区气象和地下水干旱时空动态及其对植被的累积和滞后影响

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-04-01 Epub Date: 2026-02-05 DOI: 10.1016/j.jhydrol.2026.135086

Yuanxiao Xing , Shunsheng Wang , Aili Wang , Donglin Wang

Drought is one of the most severe natural challenges in Southwest China, where complex karst hydrogeological conditions exacerbate its impacts on vegetation ecosystems. However, the mechanisms by which different drought types affect vegetation in this region remain unclear. This study integrated multiple datasets (GRACE, GLDAS, SPEI, and MODIS NDVI) to investigate the spatiotemporal evolution of meteorological drought, groundwater drought, and vegetation conditions across Southwest China from 2004 to 2023. Pearson correlation analysis was applied to quantify the cumulative and lag effects of the two drought types on vegetation in karst and non-karst areas. The results revealed that: (1) GRACE- and GLDAS-derived terrestrial water storage anomalies exhibited consistent patterns in Southwest China (r = 0.86, P < 0.001); (2) both drought types showed a slight overall alleviation, yet drought intensification remained pronounced in the western high-altitude areas; (3) compared with cumulative effects, the lag effects of drought appeared to be relatively more pronounced; and (4) vegetation in karst regions responded more rapidly to groundwater drought, while shallow-rooted grasslands were more sensitive to the cumulative effects of meteorological drought, with a typical response time of approximately one month. These findings provide valuable insights for drought monitoring and ecological conservation in ecologically fragile regions and offer new scientific evidence for understanding drought–vegetation interactions in both karst and non-karst landscapes.

干旱是西南地区最严峻的自然挑战之一，复杂的喀斯特水文地质条件加剧了干旱对植被生态系统的影响。然而，不同干旱类型影响该地区植被的机制尚不清楚。利用GRACE、GLDAS、SPEI和MODIS NDVI数据，研究了2004 - 2023年中国西南地区气象干旱、地下水干旱和植被条件的时空演变特征。采用Pearson相关分析量化两种干旱类型对喀斯特和非喀斯特地区植被的累积效应和滞后效应。结果表明：(1)GRACE-和gldas反演的中国西南地区陆地储水量异常具有一致性（r = 0.86, P < 0.001）；(2)两种干旱类型总体上略有缓解，但西部高海拔地区的干旱强度仍明显增强；(3)与累积效应相比，干旱滞后效应相对更为明显；(4)喀斯特地区植被对地下水干旱的响应更快，而浅根草原对气象干旱的累积效应更为敏感，典型响应时间约为1个月。这些发现为生态脆弱地区的干旱监测和生态保护提供了有价值的见解，并为理解喀斯特和非喀斯特景观中干旱与植被的相互作用提供了新的科学依据。

{"title":"Spatiotemporal dynamics of meteorological and groundwater droughts in Southwest China and their cumulative and lagged impacts on vegetation","authors":"Yuanxiao Xing , Shunsheng Wang , Aili Wang , Donglin Wang","doi":"10.1016/j.jhydrol.2026.135086","DOIUrl":"10.1016/j.jhydrol.2026.135086","url":null,"abstract":"<div><div>Drought is one of the most severe natural challenges in Southwest China, where complex karst hydrogeological conditions exacerbate its impacts on vegetation ecosystems. However, the mechanisms by which different drought types affect vegetation in this region remain unclear. This study integrated multiple datasets (GRACE, GLDAS, SPEI, and MODIS NDVI) to investigate the spatiotemporal evolution of meteorological drought, groundwater drought, and vegetation conditions across Southwest China from 2004 to 2023. Pearson correlation analysis was applied to quantify the cumulative and lag effects of the two drought types on vegetation in karst and non-karst areas. The results revealed that: (1) GRACE- and GLDAS-derived terrestrial water storage anomalies exhibited consistent patterns in Southwest China (r = 0.86, P < 0.001); (2) both drought types showed a slight overall alleviation, yet drought intensification remained pronounced in the western high-altitude areas; (3) compared with cumulative effects, the lag effects of drought appeared to be relatively more pronounced; and (4) vegetation in karst regions responded more rapidly to groundwater drought, while shallow-rooted grasslands were more sensitive to the cumulative effects of meteorological drought, with a typical response time of approximately one month. These findings provide valuable insights for drought monitoring and ecological conservation in ecologically fragile regions and offer new scientific evidence for understanding drought–vegetation interactions in both karst and non-karst landscapes.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135086"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146134977","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}

引用次数: 0