Journal of Hydrology最新文献_第4页

Urbanization-induced changes in rainfall and drought patterns: a study across six Indian states with mega-cities 城市化引起的降雨和干旱模式的变化：一项对印度六个大城市的研究

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-05 DOI: 10.1016/j.jhydrol.2026.135077

I.S. Ijas , Narayana Reddy Karrevula , Satyaban Bishoyi Ratna , Saket Dubey , Paleru Samyuktha

Urbanization is one of the most prominent consequences of human activity. Studies have shown that it significantly alters rainfall patterns in cities across the globe. A basic understanding remains limited for many Indian cities, both from observational and modelling perspectives. The present study significantly emphasizes the extent to which urbanization impacts rainfall patterns in India. It seeks to address this by investigating the influence of urbanization on rainfall and drought patterns across India, employing both statistical and model-based approaches. A dynamic classification system was utilized to categorize rain gauges into three distinct groups, facilitating a comparison of their pattern changes. The analysis is mainly focused on six states in India − Karnataka, Maharashtra, Tamil Nadu, Telangana, West Bengal, and Delhi (a union territory) − encompassing six mega-cities. Statistical analysis reveals a pronounced upward trend in heavy rainfall and annual monsoon precipitation over urban areas in six cities compared to their rural counterparts. In recent years, Mumbai has experienced a median increase of 18.72 mm/year in heavy rainfall, while the surrounding rural areas have only experienced an increase of 9.50 mm/year. Drought occurrences are noted to exacerbate in both urban and rural areas. In Kolkata, there has been a more than one-fold increase in the number of drought months when comparing the last two twelve-year study periods. Employing the dynamical mesoscale model also unveils the influence of land cover changes on rainfall patterns in urban areas. The observed higher increasing trend of heavy and total rainfall in urban areas compared to rural areas, particularly in megacities like Mumbai, Bengaluru, and Hyderabad, underscores the urgent need for enhanced urban flood management systems.

城市化是人类活动最显著的后果之一。研究表明，它显著改变了全球城市的降雨模式。从观察和建模的角度来看，对许多印度城市的基本了解仍然有限。本研究着重强调了城市化对印度降雨模式的影响程度。为了解决这一问题，它采用了统计和基于模型的方法，调查了城市化对印度各地降雨和干旱模式的影响。采用动态分类系统将雨量计分为三组，以便比较它们的模式变化。该分析主要集中在印度的六个邦——卡纳塔克邦、马哈拉施特拉邦、泰米尔纳德邦、特伦加纳邦、西孟加拉邦和德里（联邦属地）——包括六个大城市。统计分析显示，与农村地区相比，六个城市城市地区的强降雨和年季风降水有明显的上升趋势。近年来，孟买经历了18.72毫米/年的强降雨中位数增长，而周边农村地区仅经历了9.50毫米/年的增长。城市和农村地区的干旱情况都在加剧。在加尔各答，与过去两个12年的研究期相比，干旱月份的数量增加了一倍多。采用动态中尺度模式还揭示了土地覆盖变化对城市地区降雨模式的影响。与农村地区相比，特别是在孟买、班加罗尔和海德拉巴等特大城市，城市地区的强降雨和总降雨的增长趋势更高，这突显了加强城市洪水管理系统的迫切需要。

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引用次数: 0

DHRFLUT: A scenario-controlled framework for decoupling runoff responses from land use transitions – a case study in China’s Wei River basin 径流响应与土地利用转型解耦的情景控制框架——以中国渭河流域为例

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-05 DOI: 10.1016/j.jhydrol.2026.135092

Congcong Yao , Hongbo Zhang , Tian Lan , Xinghui Gong , Chongfeng Ren , Dongyong Sun , Shangdong Liu , Fengguang Lyu

Precisely quantifying the independent runoff effects of different land use transitions is a critical challenge in addressing complex human-land interactions and formulating targeted watershed management strategies. This study proposes a scenario-controlled framework named DHRFLUT (Decoupling Hydrological Responses from Land Use Transitions), which simulates individual transition scenarios reflecting regional development trends by establishing a land use transition decoupling mechanism. By coupling with the SWAT model, the runoff depth response coefficient (RDRC, mm/%) was quantified at the sub-basin scale, resulting in a decoupled RDRC matrix. In a case study in the Upper and Middle Reaches of the Wei River Basin on China’s Loess Plateau, urban expansion was identified as the dominant driver of runoff change, with RDRC values significantly exceeding those of vegetation transitions. Coupled topography and climate are key drivers of spatial heterogeneity in the runoff response. Specifically, precipitation gradients dominate the runoff effects of agricultural land-to-pasture and pasture-to-forest transitions, whereas geomorphic features (e.g., minimum elevation and elevation range) govern the spatial differentiation patterns of RDRC for pasture-to-agricultural land and agricultural land-to-forest transitions. Ultimately, the integrated RDRC matrix developed in this study enables the transition from qualitative understanding to quantitative management of runoff responses, thereby providing a core quantitative tool for assessing the potential hydrological impacts of land planning schemes. This research not only offers a universal methodological framework for decoupling the runoff effects of land use transitions but also provides scientific evidence for harmonizing ecological restoration with urban development and advancing sustainable watershed management.

精确量化不同土地利用转变的独立径流效应是解决复杂的人地相互作用和制定有针对性的流域管理战略的关键挑战。本研究提出了一个情景控制框架DHRFLUT (Decoupling Hydrological Responses from Land Use Transitions)，通过建立土地利用转型脱钩机制，模拟反映区域发展趋势的个别转型情景。通过与SWAT模型的耦合，在子流域尺度上量化径流深度响应系数（RDRC, mm/%），得到解耦的RDRC矩阵。以黄土高原渭河流域中上游为例，城市扩张是径流变化的主导驱动力，其RDRC值显著超过植被变迁的RDRC值。地形和气候的耦合作用是径流响应空间异质性的关键驱动因素。具体而言，降水梯度主导着农用地向牧场和牧场向森林过渡的径流效应，而地貌特征（如最低海拔和高程范围）支配着农用地向农田和农用地向森林过渡的空间分异格局。最终，本研究开发的综合RDRC矩阵使径流响应从定性理解过渡到定量管理，从而为评估土地规划方案的潜在水文影响提供了核心定量工具。该研究不仅为解耦土地利用转型径流效应提供了一个通用的方法框架，而且为协调生态恢复与城市发展、推进流域可持续管理提供了科学依据。

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引用次数: 0

An impact-based drought classification method using real-world agricultural drought records and explainable automated machine learning 一种基于影响的干旱分类方法，使用真实农业干旱记录和可解释的自动化机器学习

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-05 DOI: 10.1016/j.jhydrol.2026.135078

Keke Zhou , Jianzhu Li , Ting Zhang , Xiaogang Shi , Ping Feng

Given the destructive impacts of drought, the development of accurate and practical drought assessment frameworks is critical for risk mitigation. This study presents a novel impact-based framework that synergizes causal inference algorithm with explainable Automated Machine Learning (AutoML) to classify drought severity and uncover its primary causal drivers in China. By linking observed drought impact records with a comprehensive set of drought-related variables, the AutoML model outperforms conventional machine learning approaches across multiple evaluation metrics. Compared to widely used standardized drought indices, the AutoML-based drought classification model demonstrates superior performance in depicting both in-sample and out-of-sample drought events and well captures drought impacts on vegetation and ecosystems. Explainability and causal analysis, conducted using the Shapley Additive Explanations (SHAP) and the PCMCI+ (Peter and Clark Momentary Conditional Independence plus) algorithm, jointly reveal that (1) two non-climatic variables, latitude and geopotential height, exert the strongest influence on the model’s drought classifications; (2) soil moisture and evaporation from bare soil emerge as the most influential climatic drivers of drought severity, with soil moisture exhibiting particularly strong influence across South China. Trend analysis indicates a significant intensification of drought severity across China between 1980 and 2024, with marked increases observed in Yunnan, Henan, and Hebei. Furthermore, incorporating antecedent climatic information consistently improves classification performance, with AutoML models exhibiting the greatest gains. Collectively, the incorporation of real-world drought impact records enhanced the accuracy and practical relevance of the proposed drought classification model, while the integration of SHAP and PCMCI+ methodologies advanced its transparency and interpretability.

鉴于干旱的破坏性影响，制定准确和实用的干旱评估框架对于减轻风险至关重要。本研究提出了一个基于影响的框架，将因果推理算法与可解释的自动机器学习（AutoML）相结合，对中国干旱严重程度进行分类，并揭示其主要因果驱动因素。通过将观测到的干旱影响记录与一组全面的干旱相关变量联系起来，AutoML模型在多个评估指标上优于传统的机器学习方法。与广泛使用的标准化干旱指数相比，基于automl的干旱分类模型在描述样本内和样本外干旱事件方面表现优异，并能很好地捕捉干旱对植被和生态系统的影响。利用Shapley加性解释（SHAP）和PCMCI+ （Peter and Clark瞬时条件独立加）算法进行的可解释性和因果分析共同表明：(1)纬度和位势高度这两个非气候变量对模式的干旱分类影响最大；(2)土壤湿度和裸土蒸发是影响干旱严重程度的最主要气候驱动因素，其中华南地区土壤湿度的影响尤为强烈。趋势分析表明，1980 - 2024年，中国干旱程度显著增强，云南、河南和河北的干旱程度明显增加。此外，结合先验气候信息可以不断提高分类性能，其中AutoML模型的收益最大。总体而言，实际干旱影响记录的纳入提高了所提出的干旱分类模型的准确性和实际相关性，而SHAP和PCMCI+方法的整合提高了其透明度和可解释性。

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引用次数: 0

Storylines for the 1997 New Year’s Flood: The role of watershed antecedent conditions and future warming in shaping discharge in the Truckee River watershed 1997年新年洪水的故事情节：流域先决条件和未来变暖在特拉基河流域形成流量中的作用

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-05 DOI: 10.1016/j.jhydrol.2026.135080

Guo Yu , Alan M. Rhoades , Christine M. Albano , Julianne J. Miller , Mariana J. Webb , Travis Dahl , Ian Floyd

The 1997 New Year’s flood was among the most devastating floods in the Truckee River watershed located in western Nevada. This event resulted from complex interactions of flood drivers, such as extreme precipitation, wet antecedent watershed conditions, warm temperatures and rapid snowmelt. We leveraged simulated forcings from the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) and a process-based hydrological model to recreate the 1997 New Year’s flood for the Truckee River watershed across four climate warming levels ranging from the current temperatures to + 4° C. For each scenario, we conducted ensemble simulations with the same forcing but with 100 different seasonal watershed antecedent conditions, which were randomly sampled from long-term hydrological simulations. The results show that the 1997 New Year’s flood can be reproduced or exceeded consistently only when the antecedent watershed conditions are wet, specifically when streamflows are above the 75th percentile of the climatological value. There is negligible change in ensemble mean peakflows for Truckee River near Reno; however, there are increases of 18% and 14% under the warming levels of + 3° C and + 4° C, respectively. The increases in peakflows under future climate warming are attributed to wetter antecedent watershed conditions and enhanced snowmelt. Furthermore, the largest increases in peakflows occur at small, high-elevation headwater basins along the Sierra Nevada crest. This study highlights that changes in extreme flood events will result from the complex interplay of multiple flood drivers. It also demonstrates the potential of storyline approaches to analyze future realizations of these extreme events under different climate scenarios.

1997年的新年洪水是位于内华达州西部特拉基河流域最具破坏性的洪水之一。这一事件是洪水驱动因素的复杂相互作用的结果，如极端降水、潮湿的流域条件、温暖的温度和快速的融雪。我们利用能源百亿亿次地球系统模型（rmm - e3sm）的区域精细网格功能和基于过程的水文模型模拟了1997年特拉基河流域在四个气候变暖水平（从当前温度到+ 4°c）上的新年洪水。对于每个情景，我们使用相同的强迫进行了集合模拟，但有100个不同的季节性流域先决条件。这些样本是从长期水文模拟中随机抽取的。结果表明，1997年元旦洪水只有在前一流域条件湿润的情况下才能持续再现或超过，特别是当流量超过气候学值的第75百分位时。里诺附近特拉基河的总平均峰值流量变化可以忽略不计；然而，在+ 3°C和+ 4°C的升温水平下，分别增加18%和14%。在未来气候变暖的情况下，峰值流量的增加归因于先前更湿润的流域条件和融雪量的增加。此外，最大的峰值流量增加发生在内华达山脉峰顶的小而高海拔的源头盆地。该研究强调了极端洪水事件的变化是多种洪水驱动因素复杂相互作用的结果。它还证明了故事线方法在分析这些极端事件在不同气候情景下的未来实现方面的潜力。

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引用次数: 0

Decoding surface and root-zone soil moisture dynamics for agricultural drought assessment using multi-source climate records (1990–2019) 基于多源气候记录的地表和根区土壤水分动态解码（1990-2019）

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-05 DOI: 10.1016/j.jhydrol.2026.135095

Hao-Nan Zuo , Yingwei Sun , Pei Leng

Accurate monitoring and prediction are essential for mitigating the impacts of agricultural droughts resulting from water shortages. In many regions, insufficient soil moisture is the primary factor driving agricultural drought. However, the dominant factors that affect both long-term and short-term soil moisture variations at different depths remain not fully explored. In addition, although soil moisture is widely recognized as the most direct and sensitive indicator for agricultural drought monitoring and early warning, few studies have investigated satellite-based soil moisture climatological records for agricultural drought assessment. In this study, 30 years (1990–2019) climatological records of surface soil moisture (SSM) and root-zone soil moisture (RZSM) from the European Space Agency-Climate Change Initiative (ESA-CCI) were used to investigate the characteristics of agricultural drought events in three US states. The results indicate that during prolonged drought events, RZSM remains relatively stable and is mainly influenced by precipitation and infiltration from SSM, whereas SSM shows pronounced fluctuations. For short-duration drought events, precipitation consistently emerges as the dominant factor controlling both SSM and RZSM, and RZSM exhibits a lagged response to precipitation. Furthermore, a novel knowledge-guided machine learning model was developed for agricultural drought prediction. Compared with a standard machine learning model, the proposed model improves RZSM prediction performance by approximately 8% and more accurately reflects drought intensity across the study region. Overall, these findings provide new insights into soil moisture dynamics under drought conditions and offer a robust framework for improved agricultural drought monitoring and forecasting.

准确的监测和预测对于减轻水资源短缺造成的农业干旱的影响至关重要。在许多地区，土壤水分不足是导致农业干旱的主要因素。然而，影响不同深度土壤水分长期和短期变化的主导因素尚未得到充分探索。此外，虽然土壤湿度被广泛认为是农业干旱监测和预警最直接、最敏感的指标，但很少有研究将基于卫星的土壤湿度气候记录用于农业干旱评估。本研究利用欧洲空间局-气候变化倡议（ESA-CCI）的30年（1990-2019）表层土壤湿度（SSM）和根区土壤湿度（RZSM）的气候记录，研究了美国三个州农业干旱事件的特征。结果表明，在长时间干旱事件中，RZSM保持相对稳定，主要受SSM降水和入渗的影响，而SSM则表现出明显的波动。在短持续时间干旱事件中，降水始终是控制SSM和RZSM的主导因子，RZSM对降水的响应滞后。在此基础上，提出了一种基于知识引导的农业干旱预测机器学习模型。与标准机器学习模型相比，该模型将RZSM预测性能提高了约8%，并更准确地反映了整个研究区域的干旱强度。总的来说，这些发现为干旱条件下土壤水分动态提供了新的见解，并为改进农业干旱监测和预报提供了一个强有力的框架。

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引用次数: 0

Climate warming-induced glacier mass loss driving peak runoff variability and cryosphere service value decline 气候变暖引起的冰川质量损失驱动峰值径流变率和冰冻圈服务价值下降

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-04 DOI: 10.1016/j.jhydrol.2026.135084

Jingyao Sun, Jianxia Chang, Aijun Guo, Yimin Wang, Zhehao Li, Dingrong Zhai, Peipei Wang, Jiayang Wang

Mountain glaciers play a critical role in freshwater supply and hydrological regulation. Climate warming is projected to accelerate glacier melting in High Mountain Asia, threatening water resource sustainability, particularly in the arid and semi-arid regions. This study employs the integrated ice-dynamic Open Global Glacier Model to investigate glacier responses to past and future climate change. The annual mass balance series of 11,625 glaciers from 1990 to 2019 is reconstructed, revealing their spatiotemporal variability in alpine regions. Additionally, the long-term dynamics of glacier mass, area, and volume are assessed through 2100 under different climate scenarios, focusing on glacier runoff changes and the differences in the timing of peak runoff. Finally, the unit area service pricing method is applied to establish an index for quantifying the ecological value loss resulting from glacier retreat. The results show that climate warming will lead to substantial and irreversible mass loss. This process is characterized by initial thinning followed by retreat, resulting in an overall negative mass balance. By the end of the 21st century, glacier area and volume will decrease by more than 40% in most basins, with peak runoff expected around 2050 under low-emission scenarios. In contrast, delayed peaks are generally associated with high-emission scenarios and regions with substantial glacier reserves. Glacier service values are predicted to decline significantly or be entirely lost, with this trend intensifying from southwest to northeast in the Tarim River Basin. This study provides new insights into glacier dynamical and hydrological responses under climate warming, contributing to regional socio-ecological sustainability and optimized water resource management.

山地冰川在淡水供应和水文调节中发挥着关键作用。预计气候变暖将加速亚洲高山地区的冰川融化，威胁到水资源的可持续性，特别是在干旱和半干旱地区。本研究采用综合冰动力开放全球冰川模型研究冰川对过去和未来气候变化的响应。重建了11625条冰川1990 - 2019年的年质量平衡序列，揭示了高寒地区冰川质量平衡的时空变化特征。此外，评估了2100年不同气候情景下冰川质量、面积和体积的长期动态，重点关注冰川径流变化和径流峰值时间的差异。最后，运用单位面积服务定价法，建立了量化冰川退缩生态价值损失的指标。结果表明，气候变暖将导致大量不可逆转的质量损失。这一过程的特点是最初变薄，随后退缩，导致整体负质量平衡。到21世纪末，大多数流域的冰川面积和体积将减少40%以上，在低排放情景下，预计径流将在2050年左右达到峰值。相比之下，延迟峰值通常与高排放情景和具有大量冰川储量的地区有关。预计塔里木河流域冰川服务价值将显著下降或完全消失，趋势由西南向东北加剧。该研究为研究气候变暖下的冰川动力和水文响应提供了新的视角，有助于区域社会生态可持续性和优化水资源管理。

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引用次数: 0

Time-series hydrochemical analysis of an interwell flow test through a fractured aquifer and comparison against microbial community data 裂缝含水层井间流量测试的时间序列水化学分析及与微生物群落数据的比较

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-04 DOI: 10.1016/j.jhydrol.2026.135093

Yuran Zhang , Xiaoxuan Li , Adam J. Hawkins , Yiman Li , Qian Zhang , Tianming Huang , Zhonghe Pang , Anne E. Dekas , Roland N. Horne

Characterizing the geochemical processes during interwell flow through a fractured rock mass is helpful in understanding how geological reservoirs respond to fluid injection/production and how they can be better managed. In this work, we analyzed weekly time-series hydrochemistry data from a 10-month injection test through the EGS Collab Experiment-1 testbed, a well-characterized 1478-m-deep fractured metasedimentary rock formation located at the Sanford Underground Research Facility in Lead, South Dakota, USA. Exogenous low-salinity water was injected into the formation through one well, resulting in water production from four wells/intervals. Results revealed distinct spatiotemporal patterns in hydrochemical evolution in each water-producing well, highlighting the heterogenous nature of flowpaths in this fractured crystalline-rock formation. Mixing model analysis revealed evolving contributions from pre-existing formation water and an additional source of particular ions attributed to chemical reactions. Ionic ratio analysis combined with knowledge of local lithology pointed to specific reactions that may have occurred. Finally, hydrochemical data was compared to previously published microbial community history data collected simultaneously during the same flow test. It was found that hydrochemical and microbial data yield consistent interpretations on interwell flow. However, the between-sample chemical similarity is not coincident with microbial similarity, and the latter has much higher resolution when used as a natural “barcode”. We pointed out the complementary strengths of the two data types, whereby hydrochemical data has well-understood reactive/transport properties hence easily modeled, and microbial data has higher resolution due to its immense diversity. Our findings highlight the benefits of a combined hydrochemical/microbial analysis in reservoir monitoring.

描述裂缝岩体井间流动过程中的地球化学过程，有助于了解地质储层对流体注入/生产的反应，以及如何更好地对其进行管理。在这项工作中，我们通过EGS Collab Experiment-1试验台分析了为期10个月的每周时间序列水化学数据，该试验台位于美国南达科他州Lead的Sanford地下研究设施，是一个具有良好特征的1478米深的裂缝性元沉积岩层。通过一口井向地层注入外源低矿化度水，得到了四口井/层段的产水。结果显示，每口产水井的水化学演化具有不同的时空模式，突出了裂缝性结晶岩层中流动路径的非均质性。混合模型分析显示，已有的地层水和化学反应产生的特殊离子的额外来源在不断演化。离子比分析结合对当地岩性的了解，指出了可能发生的特定反应。最后，将水化学数据与之前公布的在同一流量试验中同时收集的微生物群落历史数据进行比较。发现水化学和微生物资料对井间流动有一致的解释。然而，样品间的化学相似性与微生物相似性并不一致，后者作为天然的“条形码”具有更高的分辨率。我们指出了这两种数据类型的互补优势，其中水化学数据具有易于理解的反应/传输性质，因此易于建模，微生物数据由于其巨大的多样性而具有更高的分辨率。我们的研究结果强调了水化学/微生物联合分析在油藏监测中的好处。

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引用次数: 0

Intelligent diagnostic framework for sustainable urban groundwater governance: Insights from asynchronous solute migration 可持续城市地下水治理的智能诊断框架：来自非同步溶质迁移的见解

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-04 DOI: 10.1016/j.jhydrol.2026.135068

Yue Ding , Kangyouran Zhou , Yunhua He , Chao Jia , Xiao Yang

Urban expansion and rapid land transformation can reorganize recharge pathways and redox conditions in shallow alluvial aquifers, resulting in decoupled and asynchronous solute migration that complicates groundwater quality management. This study examines the co-migration of Mn²⁺, I⁻, NO₃⁻ and F⁻ in the Jinan Start-up Area (eastern China) using 54 groundwater samples and develops an integrated diagnostic framework that links process-based geochemical indicators with interpretable, data-driven zoning. Saturation indices and chloro-alkaline indices were combined with an Asynchronous Migration Index (AMI) and Normalized Mutual Information (NMI) to quantify nonlinear dependencies and decoupled transport among solutes. Unsupervised classification (K-means, Gaussian mixture models) and a geographically constrained self-organizing map (GeoSOM) were then used to delineate hydrochemical regimes and identify potential early-warning zones for management prioritization. Mn²⁺ and I⁻ exceed drinking-water thresholds in >90% of samples, forming widespread plumes consistent with reductive dissolution, whereas NO₃⁻ is restricted to narrow recharge corridors influenced by agricultural inputs. Although F⁻ remains below guideline values, >90% of samples are undersaturated with respect to fluorite, indicating latent mobilization potential under hydrochemical perturbations. Elevated AMI and moderate NMI values indicate pronounced asynchrony between redox-sensitive and mineral-controlled solutes, driven by overlapping redox stratification, mineral disequilibrium, and ion-exchange processes. Four hydrochemical regimes are identified, including a transition regime that aligns with entropy hotspots and acts as an early-warning front. The proposed framework offers a transferable approach for diagnosing groundwater-quality risks and supporting monitoring and early-warning design in rapidly urbanizing alluvial basins.

城市扩张和快速的土地改造会重新组织浅层冲积含水层的补给途径和氧化还原条件，导致解耦和非同步的溶质迁移，使地下水质量管理复杂化。本研究利用54个地下水样本，研究了济南启动区（中国东部）Mn2+、I−、NO3−和F−的共迁移，并开发了一个综合诊断框架，将基于过程的地球化学指标与可解释的、数据驱动的分区联系起来。饱和度指数和氯碱性指数结合异步迁移指数（AMI）和归一化互信息（NMI）来量化溶质间的非线性依赖和解耦迁移。然后使用无监督分类（K-means，高斯混合模型）和地理约束自组织地图（GeoSOM）来描绘水化学制度，并确定潜在的预警区域，以便优先管理。在90%的样品中，Mn2+和I -超过了饮用水阈值，形成了与还原性溶解一致的广泛羽流，而NO3 -则局限于受农业投入影响的狭窄补给走廊。虽然F−仍低于指导值，但90%的样品相对于萤石是不饱和的，这表明在水化学扰动下潜在的动员潜力。AMI升高和中等NMI值表明氧化还原敏感溶质和矿物控制溶质之间存在明显的不同步，这是由重叠氧化还原分层、矿物不平衡和离子交换过程驱动的。确定了四种水化学机制，包括与熵热点一致并作为早期预警前沿的过渡机制。该框架为快速城市化冲积盆地的地下水质量风险诊断和监测预警设计提供了一种可转移的方法。

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引用次数: 0

Hybrid process-based and deep learning for river nutrient prediction under limited monitoring data 基于混合过程和深度学习的有限监测数据下河流养分预测

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-04 DOI: 10.1016/j.jhydrol.2026.135098

Jiayi Tang , Leyang Liu , Barnaby Dobson , Kwok Pan Chun , Ana Mijic

Accurate simulation of riverine nutrient dynamics remains challenging in catchments with limited monitoring data, where both process-based models (PBMs) and data-driven approaches face constraints. This study investigates hybrid modelling strategies that combine PBM simulations with long short-term memory (LSTM) networks to predict nitrogen and phosphorus concentrations at the outlet of Salmons Brook catchment, London, UK. We designed two scenario sets to evaluate (i) the role of extreme weather indices as input features and (ii) the value of integrating different outputs from the Water Systems Integrated Modelling framework (WSIMOD) into LSTM architectures. Results show that the selected hybrid PBM-LSTM models outperformed both empirical LSTM and standalone WSIMOD simulations. For phosphorus, incorporating extreme weather indices improved performance, reflecting its sensitivity to high air temperatures and intense precipitation, while nitrogen predictions degraded, suggesting that memory from past water quality observations carries more predictive value. Comparisons between hybrid designs further indicate that simulated pre-river nutrient loads provide stronger constraints for LSTM models than in-river nutrient processes. These findings emphasize the need for nutrient-specific observational inputs in LSTM frameworks and demonstrate that PBM-LSTM hybridization offers a promising pathway for improving predictions relative to standalone LSTM or PBM simulations. Moreover, the comparative performance of different modelling configurations offers insights into the types of signals LSTM networks retain or discard, thereby contributing to the interpretability of DL applications in river water quality prediction.

在监测数据有限的流域，准确模拟河流营养动态仍然具有挑战性，其中基于过程的模型（PBMs）和数据驱动的方法都面临限制。本研究探讨了将PBM模拟与长短期记忆（LSTM）网络相结合的混合建模策略，以预测英国伦敦萨尔蒙斯布鲁克集水区出口的氮和磷浓度。我们设计了两个情景集来评估(i)极端天气指数作为输入特征的作用和（ii）将水系统集成建模框架（WSIMOD）的不同输出集成到LSTM架构中的价值。结果表明，所选择的PBM-LSTM混合模型的性能优于经验LSTM和独立WSIMOD模拟。对于磷，结合极端天气指数提高了性能，反映了其对高温和强降水的敏感性，而氮的预测下降，表明过去水质观测的记忆具有更大的预测价值。混合设计之间的比较进一步表明，模拟河前养分负荷比河内养分过程对LSTM模型提供了更强的约束。这些研究结果强调了在LSTM框架中对营养特异性观测输入的需求，并表明相对于单独的LSTM或PBM模拟，PBM-LSTM杂交为改进预测提供了一个有希望的途径。此外，不同建模配置的比较性能提供了对LSTM网络保留或丢弃的信号类型的见解，从而有助于DL应用在河流水质预测中的可解释性。

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引用次数: 0

Differences in organic matter sources between suspended particulates and sediments in a lake during the frozen period 冰冻期湖泊中悬浮微粒和沉积物有机质来源的差异

IF 6.3 1区地球科学 Q1 ENGINEERING, CIVIL

Journal of Hydrology

Pub Date : 2026-02-03 DOI: 10.1016/j.jhydrol.2026.135094

Xiaohui Ren , Ruihong Yu , Yanjie Mi

Elucidating organic matter sources in lakes during the frozen period (FP) is crucial for understanding carbon and nitrogen cycling in global cold-region lakes. However, limited information exists on the sources and differences between suspended particulate organic matter and sediment organic matter in lakes during the FP. This study examined the stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotopic compositions of organic matter in suspended particulates and sediments from Daihai Lake to investigate the sources and implications of organic matter during the FP (January). Organic carbon in suspended particulates and total nitrogen in suspended particulates ranged from 0.45 to 1.22 mg/L and 0.08 to 0.20 mg/L, respectively, while organic carbon in sediments and total nitrogen in sediments ranged from 3.57 to 14.90 g/kg and 0.44 to 1.68 g/kg, respectively. Based on organic index (OI) and organic nitrogen (ON), suspended particulates (OI: 0.10 mg/L; ON: 0.12 mg/L) were slightly contaminated, whereas sediments (OI: 13.13 g/kg; ON: 1.08 g/kg) were heavily contaminated. The suspended particulate organic matter exhibited mixed source signatures, with exogenous inputs (sewage: 27.9% and soil: 22.2%) and endogenous production (phytoplankton: 25.8%). In contrast, sediment organic matter was predominantly exogenous inputs (soil: 40.3% and sewage: 26.6%). This discrepancy highlights a key process in organic matter transport and transformation under ice-covered conditions: phytoplankton-derived organic matter underwent preferential degradation during sedimentation, whereas terrestrial organic matter was more readily deposited and preserved. Notably, significant nitrogen isotope fractionation during sedimentation indicates that preferential mineralization of organic nitrogen and denitrification played key regulatory roles in the nitrogen cycling. The findings highlight the need to prioritize controlling exogenous organic matter inputs to lakes to ensure sustainable ecosystem.

阐明冻结期湖泊有机质来源对了解全球寒区湖泊碳氮循环具有重要意义。然而，关于FP期间湖泊中悬浮颗粒有机质和沉积物有机质的来源和差异的信息有限。本研究通过对滇东南东南东南东南地区沉积物和悬浮颗粒物中有机质的稳定碳（δ13C）和稳定氮（δ15N）同位素组成的分析，探讨滇东南东南东南东南地区FP（1月）的有机质来源及其意义。悬浮颗粒物中有机碳和总氮含量分别为0.45 ~ 1.22 mg/L和0.08 ~ 0.20 mg/L，沉积物中有机碳和总氮含量分别为3.57 ~ 14.90 g/kg和0.44 ~ 1.68 g/kg。以有机指数（OI）和有机氮（on）为指标，悬浮颗粒（OI: 0.10 mg/L, on: 0.12 mg/L）为轻度污染，沉积物（OI: 13.13 g/kg, on: 1.08 g/kg）为重度污染。悬浮颗粒有机质呈现混合来源特征，外源输入（污水占27.9%，土壤占22.2%）和内源产生（浮游植物占25.8%）。相比之下，沉积物有机质主要是外源输入（土壤：40.3%，污水：26.6%）。这种差异突出了冰覆盖条件下有机物运输和转化的一个关键过程：浮游植物来源的有机物在沉积过程中优先降解，而陆源有机物更容易沉积和保存。值得注意的是，沉积过程中显著的氮同位素分馏表明有机氮的优先矿化和反硝化作用在氮循环中起关键调节作用。研究结果强调，需要优先控制外源有机物质输入到湖泊，以确保可持续的生态系统。

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引用次数: 0