Journal of Hydrology最新文献

{"title":"Revising the SCS-CN model by using the effect of biocrusts to refine the results","authors":"Kangmin Gu ,&nbsp;Yunge Zhao ,&nbsp;Kai Yang ,&nbsp;Shanshan Wang ,&nbsp;Jingyi Ji ,&nbsp;Jingrong Song ,&nbsp;Jianqiao Han","doi":"10.1016/j.jhydrol.2025.133080","DOIUrl":"10.1016/j.jhydrol.2025.133080","url":null,"abstract":"<div><div>Water resource shortage typically creates serious challenges in dryland ecosystems. Accurate prediction of runoff during rainfall events is intrinsic to the scientific management of water resources and soil erosion control especially in dryland ecosystem where the vascular plant is sparse. Furthermore, biological soil crusts (biocrusts), the ubiquitous surface coverings in many dryland ecosystems, play a vital role in the water cycle and thus in runoff generation. However, the relationship between biocrust coverage and runoff yield and the effect of biocrust on SCS-CN model were not fully researched. Accordingly, we collected 364 sets of runoff data from 13 rainfall events across three watersheds of the Loess Plateau of China. The relationship between runoff yield and biocrust coverage under natural rainfall was examined, and the revised SCS-CN model, which accounted for the previously proposed biocrust coverage, was verified. We found that (1) runoff decreased as biocrust coverage increased at rainfall intensities below 43.2 mm·h⁻¹. Specifically, a 10 % increase in biocrust coverage resulted in a runoff reduction ranging from 6.9 % to 19.8 %. (2) The simulation accuracy of the revised SCS-CN model was significantly improved by considering the effect of biocrusts. Compared with that of the classic model, the Nash-Sutcliffe efficiency coefficient (NSE) of the revised model increased by 100.2 %, while the Percent bias (PBIAS) and the Root mean square error (RMSE) decreased by 97.0 % and 65.7 %, respectively. (3) The revised SCS-CN model showed better accuracy for runoff when the coverage of biocrusts ranged between 40 % and 60 %. Accordingly, we recommend using a curve number (CN) of 66 and an initial abstraction ratio (λ) of 0.05 for sites with biocrust coverage ranging between 40 % and 60 %. This study confirmed that biocrusts inhibit runoff under natural rainfall conditions. In addition, for the first time, the revised SCS-CN model that accounted for biocrust coverage was verified by natural rainfall in three watersheds. These results advance the understanding of the runoff effect of biocrusts and demonstrate that the revised SCS-CN model is effective for runoff prediction in dryland ecosystems.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133080"},"PeriodicalIF":5.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the performance of three 1-D lake models in simulating thermal dynamics of diverse water bodies in the Yangtze River Basin","authors":"Omarjan Obulkasim ,&nbsp;Shulei Zhang ,&nbsp;Xiaofan Yang ,&nbsp;Lei Sun ,&nbsp;Yuan He ,&nbsp;Yongjiu Dai","doi":"10.1016/j.jhydrol.2025.133094","DOIUrl":"10.1016/j.jhydrol.2025.133094","url":null,"abstract":"<div><div>Understanding the thermal processes of lakes and reservoirs is essential due to their profound influence on local climate and environment, as well as their sensitivity to climate change and human activities. This study aims to systematically compare the performance of three one-dimensional lake models (FLake, CoLM-Lake, and Simstrat) in simulating the thermal dynamics of different water bodies in the Yangtze River Basin, which contains the highest water bodies density in China. The results showed that while all models performed well for shallow water bodies, significant challenges and variability emerged for deep water bodies, with Simstrat outperforming CoLM-Lake and FLake in capturing thermal structure. Specifically, Simstrat demonstrated superior performance in simulating the vertical layering of water caused by differences in temperature and density (i.e., thermal stratification) in Lake Qiandaohu (RMSE: 1.44 °C) and surface temperatures across deep water bodies (average RMSE: 2.16 °C). CoLM-Lake effectively reproduced surface temperatures in deep water bodies (average RMSE: 2.36 °C) but overestimated vertical mixing, leading to less accurate stratification simulations (RMSE: 3.16 °C). FLake exhibited limitations in simulating temperatures and thermal stratification in deep water bodies but performed relatively well in shallow systems. Moreover, all three models exhibited diminished accuracy in reservoirs simulations compared to lakes, possibly due to inadequate representation of key processes. Additionally, we explored the impacts of different surface flux schemes and parameter calibration strategies on model performance. This study offers crucial insights into enhancing the simulation of thermal processes in lakes and reservoirs, particularly for deep-water environments, thereby advancing our understanding of thermal dynamics and their implications across the Yangtze River Basin.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133094"},"PeriodicalIF":5.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative assessment and analysis of the impact of inter-basin water transfer on regional water resource stress","authors":"Lichuan Wang ,&nbsp;Fan He ,&nbsp;Yong Zhao ,&nbsp;Jianhua Wang ,&nbsp;Meng Hao ,&nbsp;Peiyi Lu ,&nbsp;Yage Jia ,&nbsp;Kuan Liu ,&nbsp;Haodong Deng","doi":"10.1016/j.jhydrol.2025.133090","DOIUrl":"10.1016/j.jhydrol.2025.133090","url":null,"abstract":"<div><div>With the increasingly serious water shortage and other problems, Inter-basin water transfer (IBWT) has become an important measure to alleviate regional water stress. In this study, based on the improved water stress index (WSI), we comprehensively assessed the multi-scale (urban, tertiary basin zones) spatio-temporal status of WSI in the four major basins of the Huang, Huai, Hai and Yangtze River Basins (HHHYRB) from 1965 to 2020, and analysed the contribution of Inter-basin water transfer to alleviate regional water stress. The Dagum Gini coefficient method was used to determine the differences and sources of WSI distribution. Finally, the impact of each water transfer project was quantitatively analysed through bottom-up scenario derivation. The results show that 35.8% of the cities in the HHHYRB, and 40.4% of the tertiary basins are at medium or higher risk of water stress. The impacts of external inter-basin water transfers in the HHHYRB are all less than 0.002. The IBWT effectively mitigated the WSI in the Hai River Basin (75%) and the Huaihe River Basin (15.6%), negatively affected the WSI in the Yellow River Basin (−6.4%), and had only a 2% impact on the Yangtze River Basin. There is obvious spatial heterogeneity in the WSI of the HHHYRB, and the coefficients between groups (48.3%–66%) are higher than the coefficients within groups (17.3%–23.7%) and hypervariable density coefficients (10.8%–31%). IBWT projects effectively moderate the degree of inequality in water resources, with intra-basin impacts ranging from 1.77% to 33.69% and inter-basin impacts reaching 2.29%–7.28%. Most of the IBWT projects tend to transfer water from areas with low WSI to areas with high WSI with positive impacts, but there are still 10 water transfer projects with negative impacts. Therefore, the impacts of IBWT should be considered comprehensively when formulating water resources management policies in order to achieve long-term sustainable use of water resources.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133090"},"PeriodicalIF":5.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing compound flood hazards in the Pearl river Delta: A Scenario-Based Integration of trivariate fluvial conditions and extreme storm events","authors":"Haoxuan Du ,&nbsp;Kai Fei ,&nbsp;Liang Gao","doi":"10.1016/j.jhydrol.2025.133104","DOIUrl":"10.1016/j.jhydrol.2025.133104","url":null,"abstract":"<div><div>In coastal delta regions, typhoons not only generate storm surges but also threaten local communities by causing extreme fluvial flooding due to intense rainfall. Traditionally, upstream river discharges are neglected and not linked to these compound events, leading to an underestimation of flood extent and impacts. Quantifying the joint occurrences of extreme fluvial and coastal conditions is essential for accurately predicting future compound flood hazards. This study proposes an integrated statistical-numerical modeling approach to assess compound fluvial-coastal flood hazards. The approach combines a trivariate statistical analysis to characterize extreme fluvial conditions with a numerical model to simulate coastal storm surges and their compound effects. The methodology is applied to the Pearl River Delta in southern China, a region highly vulnerable to compound flooding. Trivariate joint statistical relationships are developed using historical river discharge records during typhoon events from 1957 to 2022 to characterize extreme fluvial conditions. While the correlation among the three connected rivers is weak under low flow conditions, a high dependence exists during extreme events, increasing the likelihood of concurrent flooding. The trivariate fluvial conditions are then integrated with univariate coastal storm surge conditions to project the compound flood hazard scenario. The results show that high-risk scenarios (100-year river discharge combined with 100-year storm tide) could inundate over 24% of the Pearl River Delta’s land area. Neglecting river discharges underestimates the floodplain extent by up to 32%. Transition zones influenced by both river flow and storm surges are identified along midstream river networks and upstream floodplains. These regions experience significant expansion with rising hazard levels, suggesting larger compound flood areas under future extreme conditions. This scenario-based approach provides valuable insights into characterizing and mapping compound flooding risks in vulnerable coastal regions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133104"},"PeriodicalIF":5.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143654643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating the Maximum Entropy Production model and airborne imagery for understorey evapotranspiration mapping","authors":"Wenjie Liu ,&nbsp;Okke Batelaan ,&nbsp;David Bruce ,&nbsp;Jingfeng Wang ,&nbsp;Hugo Gutierrez ,&nbsp;Hailong Wang ,&nbsp;Robin Keegan-Treloar ,&nbsp;Jianfeng Gou ,&nbsp;Robert Keane ,&nbsp;Jessica Thompson ,&nbsp;Huade Guan","doi":"10.1016/j.jhydrol.2025.133076","DOIUrl":"10.1016/j.jhydrol.2025.133076","url":null,"abstract":"<div><div>While extensive research has focused on evapotranspiration (ET) from land surface, the spatial distributions of ET of the woodland and forest understorey remain poorly understood. This study developed a method for estimating spatially distributed understorey ET by integrating the Maximum Entropy Production model with airborne thermal imagery. Validation against ground-truth estimation showed good model performance (R² = 0.93, RMSE = 0.03 mm/h), confirming its efficacy across different land cover types, including open and understorey areas. The results revealed significant spatial heterogeneity in understorey ET with varying vegetation cover and topographic attributes, and distinct responses to wetting events. This method provides a new tool for estimating the important understorey water consumption in forests and woodlands, contributing to assessing ecosystem water use efficiency and improving water resource and vegetation management strategies.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133076"},"PeriodicalIF":5.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Widespread consistent but rapid response of terrestrial ecosystem photosynthesis and respiratory to drought","authors":"Wenwen Guo ,&nbsp;Shengzhi Huang ,&nbsp;Laibao Liu ,&nbsp;Feilong Hu ,&nbsp;Liang Gao ,&nbsp;Jianfeng Li ,&nbsp;Qiang Huang ,&nbsp;Guohe Huang ,&nbsp;Mingjiang Deng ,&nbsp;Guoyong Leng ,&nbsp;Ji Li ,&nbsp;Xiaoting Wei ,&nbsp;Yifei Li ,&nbsp;Jian Peng","doi":"10.1016/j.jhydrol.2025.133107","DOIUrl":"10.1016/j.jhydrol.2025.133107","url":null,"abstract":"<div><div>Drought significantly threatens terrestrial ecosystems health, through influencing both photosynthesis and respiratory processes. However, whether these processes have changed in response to intensified drought and the driving mechanisms remain unclear, even though the inconsistent responses may indicate an increased potential for unstable carbon sinks. The knowledge gap would hinder accurate prediction of the size of China’s future terrestrial ecosystems carbon sink under increasing extreme droughts, thus impacting the realization of China’s carbon neutrality goal. Here, we combined observational-based data and dynamic global vegetation model data to explore the response time (RT) of Gross Primary Productivity (GPP) and Ecosystem Respiration (TER) to meteorological drought in China and their dynamics over the past 40 years. Results reveal consistent spatial distribution patterns in GPP and TER responses to drought. During 1982–2021, widespread declines in the RT of both GPP and TER to drought were observed, indicating an increased likelihood of vegetation converting from a carbon sink into a carbon source under droughts. GPP responds slightly faster than TER, notably in arid regions influenced by land cover change and climate change. Hotspots of decreasing RT trends, such as the Tibetan Plateau and Yellow River Basin, underscore the diverse impacts of climate and land cover changes. Our findings shed new insights into ecosystem carbon fluxes mechanisms, thus providing accurate carbon budget for China’s carbon neutrality goal.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133107"},"PeriodicalIF":5.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-GPU parallelization of shallow water modelling on unstructured meshes","authors":"Boliang Dong ,&nbsp;Bensheng Huang ,&nbsp;Chao Tan ,&nbsp;Junqiang Xia ,&nbsp;Kairong Lin ,&nbsp;Shuailing Gao ,&nbsp;Yong Hu","doi":"10.1016/j.jhydrol.2025.133105","DOIUrl":"10.1016/j.jhydrol.2025.133105","url":null,"abstract":"<div><div>Floods are one of the most devastating natural hazards globally, causing significant loss of life and extensive economic damage. Shallow water equation (SWE) models, due to their clear physical mechanism and good accuracy, can provide detailed predictions of flood behaviour, which are essential for flood risk evaluation and mitigation. However, traditional SWE models face significant limitations in supporting large-scale, long-duration, and high-resolution numerical simulations, which are increasingly demanded by modern applications such as flood forecasting and the establishment of warning systems. In response to the increasing demand for rapid and accurate flood modelling, this study presents a multi-GPU accelerated unstructured mesh SWE model. The proposed model employs MPI-OpenACC method to facilitate multi-GPU parallel computing for hydrodynamic simulations and incorporates a novel asynchronous communication strategy aimed at minimizing the overhead associated with parallel communication. Three representative flood cases were employed to assess the accuracy and efficiency of the proposed model. The results indicated that the speedup of the proposed model reached more than 800 when using eight GPUs in parallel, and the model could simulate a 30 h extreme flood in a 1,300 km² watershed within 0.35 h. Multi-GPU parallel computing holds great promise for applications in rapid flood simulation and real-time risk assessment.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133105"},"PeriodicalIF":5.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study of the spatial distribution of the tension water storage capacity and hydrological simulation effects in the upper reaches of the Yangtze River","authors":"Pingshan Qin,&nbsp;Xingnan Zhang,&nbsp;Yuanhao Fang,&nbsp;Rui Qian,&nbsp;Zhongye Xia,&nbsp;Kaiqi Shen","doi":"10.1016/j.jhydrol.2025.133055","DOIUrl":"10.1016/j.jhydrol.2025.133055","url":null,"abstract":"<div><div>Tension water storage capacity is a pivotal variable in conceptual hydrological models, and its spatial distribution significantly influences runoff calculations. However, accurately characterizing its spatial variability remains a significant challenge. This study, based on the physical significance of tension water storage capacity, quantitatively calculates the tension water storage capacity for 95 subwatersheds in the upper reaches of the Yangtze River. Utilizing the grid-based tension water storage capacity data, three types of tension water storage capacity curves were constructed: the calibrated parabolic linetype (CPL), the fitted parabolic linetype (FPL), and the fitted straight linetype (FSL). Theoretical comparisons and rainfall-runoff simulation experiments were carried out in eight actual subwatersheds. The results indicate that, in theoretical runoff calculations, FSL demonstrates the smallest relative error during grid-based runoff computation, with a relative error of −25.40 % before the intersection point and 1.00 % after the intersection point. Furthermore, during rainfall-runoff simulation validation, the overall average Nash-Sutcliffe Efficiency (NSE) for the eight subwatersheds using FSL was 0.85, compared to 0.80 for both CPL and FPL. This represents an improvement of 0.05 for FSL over CPL and FPL. Additionally, the average Kling-Gupta Efficiency (KGE) value for FSL was 0.83, while CPL and FPL achieved 0.77 and 0.75, respectively, indicating that FSL outperformed CPL and FPL by 0.06 and 0.08, respectively. Therefore, based on both theoretical runoff calculations and rainfall-runoff simulations, the FSL more accurately describes the spatial distribution of tension water storage capacity within the watershed. This study provides a new alternative method for the spatial distribution of tension water storage capacity in hydrological modeling, improves the calculation method of streamflow production, and contributes to the development of hydrological modeling, which is useful for the efficiency of water resources utilization and flood risk reduction.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133055"},"PeriodicalIF":5.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient glacial lake mapping by leveraging deep transfer learning and a new annotated glacial lake dataset","authors":"Donghui Ma ,&nbsp;Jie Li ,&nbsp;Liguang Jiang","doi":"10.1016/j.jhydrol.2025.133072","DOIUrl":"10.1016/j.jhydrol.2025.133072","url":null,"abstract":"<div><div>Glacial lakes, crucial components of the cryosphere, are recognized as key sentinels of climate change. While satellite imagery offers a straightforward method for monitoring their dynamics, traditional approaches are often subjective and time-consuming. Deep learning techniques, though promising, have been hindered by the scarcity of labeled glacial lake datasets. To address this limitation, we present the Glacial Lake Image Dataset (GLID), the first publicly available collection of its kind. This dataset comprises 18,367 (512 × 512 pixels) sample pairs (lake polygons and corresponding images) derived from 36 scenes from across multiple sources (WorldView-2, Sentinel-2, Landsat-8, and Gaofen-2), covering the entire Himalayan region. We then propose a transferable deep learning network for glacial lake extraction. Our findings underscore the critical role of high-quality training data in model performance. The GLID-trained model achieved superior results, demonstrating a Precision of 95.36 %, Recall of 87.50 %, F1 score of 91.66 %, and mIoU of 82.07 %. Notably, this method exhibits promising transferability across diverse regions, including North America, South America, Greenland, and High Mountain Asia. The GLID dataset provides a valuable resource for advancing machine learning-based glacial mapping research. By offering a large-scale, publicly accessible collection of labeled data, we aim to facilitate the development of more accurate and efficient methods for monitoring and understanding the impacts of climate change on glacial lake ecosystems.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133072"},"PeriodicalIF":5.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"More sensitive signatures of DOM are stimulated by socioeconomic-related anthropogenic influences in a typical loess watershed","authors":"Yixuan Zhang ,&nbsp;Hangzhen Zhang ,&nbsp;Jinxi Song ,&nbsp;Dandong Cheng","doi":"10.1016/j.jhydrol.2025.133106","DOIUrl":"10.1016/j.jhydrol.2025.133106","url":null,"abstract":"<div><div>Dissolved organic matter (DOM) plays a critical role in carbon cycling within aquatic systems, and its dynamics are influenced by both natural and human-induced factors. How and to what extent these factors stimulate DOM dynamics, particularly socioeconomic-driven impacts on carbon cycling in aquatic systems, urgently need to be quantified. This study employed partial least squares structural equation modelling (PLS-SEM) to reveal that socioeconomic conditions were the dominant factors shaping the DOM components. Rapid socioeconomic development has led to higher concentrations of protein-like DOM (λ = 0.95) and lower concentrations of terrestrially-derived humic-like components (λ = -0.78), suggesting anthropogenic inputs have become the primary source of protein-like DOM in urban river systems. In contrast, climatic conditions had a strong positive effect on the relative abundance of terrestrial humic-like DOM, while exhibiting a significant negative impact on the protein-like components. Additionally, changes in hydrological conditions may have indirect impacts on DOM components by stimulating or inhibiting the transformation of DOM. Using protein-like components as anthropogenic tracers, the study identified non-point source pollution inputs as the main anthropogenic source of DOM in the Weihe River basin (48.3 %). This suggests that controlling the overflow of industrial wastewater and domestic sewage, as well as optimizing agricultural irrigation practices, are effective strategies to improve water quality and reduce the accumulation of protein-like DOM. Altogether, these results can help deepen the scientific understanding of how river DOM dynamics respond to global change, and provide a robust scientific basis to inform watershed water resource and ecohydrology issues management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133106"},"PeriodicalIF":5.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682740","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}