Journal of Hydrology最新文献

{"title":"Spatial downscaling of GRACE terrestrial water storage anomalies for drought and flood potential assessment","authors":"Gaohong Yin ,&nbsp;Jongmin Park ,&nbsp;Kei Yoshimura","doi":"10.1016/j.jhydrol.2025.133144","DOIUrl":"10.1016/j.jhydrol.2025.133144","url":null,"abstract":"<div><div>Terrestrial water storage anomaly (TWSA) from the Gravity Recovery and Climate Experiment (GRACE) mission provides invaluable information for quantifying changes in freshwater availability. However, the coarse spatial resolution of GRACE TWSA limits its application to sub-regional studies. The study proposed a systematic framework to spatially downscale GRACE TWSA retrievals using a long short-term memory (LSTM) model over the Texas-Gulf Basin. A synthetic experiment was conducted to demonstrate the robustness of the downscaling framework. The real-world experiment revealed that the downscaled TWSA from LSTM can represent the variation of TWSA at the basin (R_LSTM = 0.91) and sub-basin scales. The LSTM-based TWSA can better represent the early recovery from extreme droughts for the sub-basins along the coast. Moreover, the LSTM-based TWSA outperformed model-based TWSA in characterizing groundwater variation, especially for sub-basins with deep groundwater levels in the west. The flood analysis showed that the downscaled TWSA from LSTM yielded improved skill in predicting county-level floods, providing a larger true positive rate relative to GRACE TWSA retrievals (TPR_LSTM = 0.36 and TPR_GRACE = 0.31). Additionally, the trained LSTM models were used to predict fine-resolution TWSA without requiring GRACE observations. Results demonstrated that the accuracy of LSTM-based TWSA forecasts was slightly inferior to the downscaling case, but they still provided useful information for drought and flood predictions at sub-basin to local scales.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133144"},"PeriodicalIF":5.9,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739043","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":"Enhanced biogenic carbon emissions in inland waterways: Insights from the Beijing-Hangzhou Grand Canal, China","authors":"Boyi Liu ,&nbsp;Lin Zhu ,&nbsp;Runyu Zhang ,&nbsp;Chenjun Zeng ,&nbsp;Yixin Liu ,&nbsp;Huijian Yang ,&nbsp;Boqiang Qin ,&nbsp;Wenqing Shi","doi":"10.1016/j.jhydrol.2025.133148","DOIUrl":"10.1016/j.jhydrol.2025.133148","url":null,"abstract":"<div><div>Rivers, being the first recipients of terrestrial organic matter, actively decompose this material and serve as hotspots for biogenic carbon emissions, including carbon dioxide (CO₂) and methane (CH₄), a process that is often regulated by river hydrodynamics. Water transportation, a widely used economic mode, alters river hydrodynamics and potentially impacts biogenic carbon emissions. To explore this impact, this study investigated CO₂ and CH₄ emissions in the Beijing-Hangzhou Grand Canal (BHGC), the world’s longest canal, and compared them with those in its undisturbed tributaries. The results indicated that ship disturbances reduced CH₄ production but greatly enhanced CO₂ release, ultimately leading to an increase in the CO₂-equivalents (CO₂-eq). Compared to its tributaries, the BHGC exhibited a fourfold increase in CO₂-eq. Ship disturbances resuspended riverbed sediments, resulting in a 40% decrease in organic carbon burial per unit area of sediment. The suspended organic carbon promoted its decomposition in the water, leading to increased CO₂ production, while the oxygen-rich environment in the water reduced CH₄ production. These findings add our understanding of the impacts of shipping activities on river biogeochemical cycling.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133148"},"PeriodicalIF":5.9,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748106","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":"A modified multi-objective grey wolf optimizer for multi-objective flood control operation of cascade reservoirs","authors":"Chenye Liu ,&nbsp;Yangyang Xie ,&nbsp;Saiyan Liu ,&nbsp;Seyedali Mirjalili ,&nbsp;Jiyao Qin ,&nbsp;Jianfeng Wei ,&nbsp;Hongyuan Fang ,&nbsp;Huihua Du","doi":"10.1016/j.jhydrol.2025.133162","DOIUrl":"10.1016/j.jhydrol.2025.133162","url":null,"abstract":"<div><div>The issue of reservoir flood control optimization (RFCO) is inherently intricate as it involves a large number of variables and multiple objectives. In the realm of RFCO, numerous multi-objective algorithms are prone to the dimensional disaster, often becoming ensnared in local optima and failing to provide decision-makers with diverse solutions. This paper introduces a modified multi-objective grey wolf optimizer (MMOGWO) that integrates multiple search strategy, enhancing the autonomous exploration capabilities of individual grey wolves. It addresses the weaknesses of original multi-objective grey wolf optimizer (MOGWO) in exploration and its propensity to converge to local optima. MMOGWO was evaluated on well-known multi-objective optimization benchmark functions UF8-UF10, DTLZ2 and DTLZ7. Experimental results from Wilcoxon signed-rank tests and Friedman tests demonstrate the algorithm’s strong competitiveness, as it holds an advantage in comparisons with MOGWO, non-dominated Sorting Dung Beetle Optimizer (NSDBO), multi-objective golden eagle optimizer (MOGEO), and multi-objective Manta ray foraging optimizer (MOMRFO). Subsequently, MMOGWO was applied to a flood control operation model that considers the safety of cascade reservoirs, the safety of downstream protected objects, and the ability of cascade reservoirs to manage consecutive floods. The results show that MMOGWO significantly outperforms widely-used algorithms such as NSGA-III and MOEA/D in high-dimensional RFCO problems. This can be attributed to MMOGWO’s broader solution coverage, whereas the solutions of NSGA-III and MOEA/D are mostly concentrated in a narrow range, indicating their entrapment in local optima while MMOGWO achieves global optimization and provides a more diverse set of feasible solutions. The MMOGWO algorithm presented in this paper emerges as a reliable optimizer for flood control operation of cascade reservoirs and can be regarded as a competitive multi-objective optimization algorithm.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133162"},"PeriodicalIF":5.9,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748112","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":"Wellbore-reservoir and multiphysics coupling model for liquid CO2 cyclic injection in a CCUS-EGR framework","authors":"Xinyuan Gao ,&nbsp;Shenglai Yang ,&nbsp;Beidong Wang ,&nbsp;Yiqi Zhang ,&nbsp;Jiangtao Hu ,&nbsp;Mengyu Wang ,&nbsp;Bin Shen ,&nbsp;Ermeng Zhao ,&nbsp;Zhenhua Rui","doi":"10.1016/j.jhydrol.2025.133188","DOIUrl":"10.1016/j.jhydrol.2025.133188","url":null,"abstract":"<div><div>Natural gas is a vital underground clean energy resource and inject CO₂ into gas reservoirs can enhance natural gas production while simultaneously reducing carbon emissions. In this study, we developed an extended wellbore-reservoir-thermo-hydro-mechanical-diffusion (WR-THMD) coupling model to establish a comprehensive closed-loop framework for carbon capture, utilization, and storage-enhanced gas recovery (CCUS-EGR). Utilizing this model, we investigated the operational conditions of the wellbore and reservoir, focusing on the effects of engineering parameters on system performance. The results indicate that to optimize system CO₂ storage capacity, stabilize the pressure differential between the wells, and enhance storage efficiency, we recommend employing relatively low injection mass flow rates and injection temperatures. When designing wellbore parameters, it is crucial to account for significant temperature losses in the production well, as these losses substantially raise the flow obstruction of the produced gas and direct to potential thermal energy loss. Lower injection mass flow rates can effectively minimize thermal losses and delay CO₂ breakthrough in the production well. This study provides a foundational framework for effectively managing CCUS-EGR systems, aiding in the advancement of underground clean energy production and CO₂ storage.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133188"},"PeriodicalIF":5.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706125","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":"Incorporating geological zonal information by cluster analysis into hydraulic tomography in sandbox and field studies","authors":"Liqun Jiang ,&nbsp;Ronglin Sun ,&nbsp;Xing Liang","doi":"10.1016/j.jhydrol.2025.133174","DOIUrl":"10.1016/j.jhydrol.2025.133174","url":null,"abstract":"<div><div>Hydraulic tomography (HT) has been proven to be an effective technique for accurately mapping aquifer heterogeneity over the past few decades. Aquifer response data used for model calibration in HT inverse analysis are frequently sparse, so geological structures reflected by the estimated hydraulic conductivity (<em>K</em>) tomograms may be smoothed out and are discrepant from the actual structures. The locations and geometries of high-<em>K</em> and low-<em>K</em> zones, which impact groundwater flow and contaminant transport processes, need to be corrected. Although collecting geological or geophysical data could improve HT results, exploring an alternative approach without collecting additional data may be possible. Therefore, this study explores the possibility of using hierarchical cluster analysis to extract geological zonal information from HT <em>K</em> estimates to characterize the geological structures. For this purpose, this study treats the zonal information as prior information of HT inverse models. We first conducted laboratory sandbox experiments to test the effectiveness of the proposed approach. Afterward, this approach is applied at a highly heterogeneous site in a dam foundation. Results show that <em>K</em> tomograms obtained by the traditional HT inverse analysis can reflect both the interlayer and intralayer heterogeneity, but the geometries of the interlayer heterogeneity must be improved. Integrating the zonal information into the HT inverse model improves the reliability of <em>K</em> estimates to predict drawdowns of different pumping tests. It corrects the geometries of geological structures without additional data.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133174"},"PeriodicalIF":5.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724465","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 and predicting hydro-biogeochemical dynamics in the Weihe River basin in a shifting climate","authors":"Guangchuang Zhang ,&nbsp;Yiping Wu ,&nbsp;Georgii Alexandrov ,&nbsp;Huiwen Li ,&nbsp;Xiaowei Yin ,&nbsp;Xixi Lu ,&nbsp;Fubo Zhao ,&nbsp;Fan Wang ,&nbsp;Linjing Qiu ,&nbsp;Shuguang Liu ,&nbsp;Ji Chen ,&nbsp;Shantao An ,&nbsp;Zhangdong Jin ,&nbsp;Yongming Han","doi":"10.1016/j.jhydrol.2025.133189","DOIUrl":"10.1016/j.jhydrol.2025.133189","url":null,"abstract":"<div><div>The intricate interplay between hydrological and biogeochemical cycles underpins the sustainability of watershed resources, making it essential to comprehend their climate responses for adaptive strategies. Although climate change significantly influences the dynamics of the water-carbon cycle, understanding hydro-biogeochemical responses to climate change remains limited. In this study, we utilized the coupled hydro-biogeochemical model (SWAT-DayCent), known for its robust simulation of hydrological and biogeochemical processes, to evaluate how climate change influences water-carbon dynamics in the Weihe River Basin (WHRB), the largest tributary of the Yellow River. We further predicted the hydro-biogeochemical consequences using climate scenarios derived from four General Circulation Models under three Representative Concentration Pathways (low, medium, and high emissions pathways), with uncertainty analysis of future predictions. The results indicate that the net primary productivity (NPP) would rise under low and medium emissions pathway scenarios with rising temperatures and precipitation. Moreover, the WHRB shows that NPP and soil organic carbon (SOC) are more prominent in the southern parts and less in the northern parts. It is noteworthy that the continued air temperature rise could trigger a decline in SOC in the late century (2070–2099) under the high emissions scenario, though slight increments in precipitation and NPP might partially counterbalance this adverse effect. In summary, this study highlights the need for adaptive management strategies, especially under high emission scenarios, where rising temperatures may diminish SOC, necessitating policies that could enhance soil carbon sequestration and mitigate adverse climate impacts.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133189"},"PeriodicalIF":5.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739042","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":"Characteristics of the water extent and width of endorheic Tibetan Plateau rivers revealed by Sentinel-2","authors":"Fanxuan Zeng ,&nbsp;Kai Liu ,&nbsp;Yongquan Zhao ,&nbsp;Pengju Xu ,&nbsp;Xinyuan Deng ,&nbsp;Tan Chen ,&nbsp;Chunqiao Song","doi":"10.1016/j.jhydrol.2025.133191","DOIUrl":"10.1016/j.jhydrol.2025.133191","url":null,"abstract":"<div><div>The endorheic Tibetan Plateau (TP) is a hotspot affected by climate change, yet the hydrological characteristics of rivers and the factors driving their development have not been clearly elucidated. To address this, we proposed a remote sensing framework to reveal river water extent and width across multiple spatial and temporal scales. A multi-temporal water frequency layer was generated using all Sentinel-2 MSI images observed in unfreezing periods between 2019 and 2021. Three river water inundation states, including the maximum state (10 % water frequency), the median state (50 % water frequency), and the instantaneous state (single-date observation in the wet-to-dry-transition season), were described separately. Water frequency maps were compared with global surface water datasets, and river width estimates were validated against field measurements. The results showed high consistency between the derived data and the reference dataset. The river width showed strong evaluation metrics, with a R² of 0.83, a root mean square error of 15.26 m, a mean absolute error of 12.71 m, and a mean absolute percentage error of 17.32 %. At maximum inundation, endorheic TP rivers (max. width &gt; 10 m) spanned 20,686.67 km, covering 1,514.92 km², with an average width of 87.53 m and a maximum of 3,763.82 m, yielding a drainage density of 0.02 km/km². In the median (instantaneous) states, the total river area, reach length, and average width accounted for 34.27 % (48.26 %), 60.16 % (79.49 %), and 32.29 % (41.51 %) of the maximum state. The development of these endorheic TP rivers was significantly influenced by tectonic landforms and glacier distribution, while climate conditions primarily shaped drainage density, showing a nonlinear trend with increasing aridity.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133191"},"PeriodicalIF":5.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724123","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":"Research on the in-situ permeability enhancement mechanism of loose porous medium using ultrasonic waves based on NMR","authors":"Yan Zhao ,&nbsp;Liu Yang ,&nbsp;Siyuan Li ,&nbsp;Shengke Yang ,&nbsp;Zhenkun Geng ,&nbsp;Mingxiu Ji ,&nbsp;Ruipeng Dong ,&nbsp;Yinyu Wen","doi":"10.1016/j.jhydrol.2025.133176","DOIUrl":"10.1016/j.jhydrol.2025.133176","url":null,"abstract":"<div><div>The permeability of aquifers is a key factor influencing the transport of agents within the pores, and therefore significantly determines the efficiency of in-situ groundwater remediation. It is known that ultrasonic waves can alter the pore size distribution characteristics, increase pore connectivity, and thereby improve the permeability of porous media, but the application of this technology in loose porous aquifer is rare. This paper investigates the transport laws of solutes in loose porous media before and after ultrasonic treatment within a one-dimensional sand column, and uses nuclear magnetic resonance (NMR) technology to quantitatively characterize the changes in pore structure and permeability of the medium. The results confirm that ultrasonic waves can enhance the in-situ permeability of loose porous media through thermal effects, cavitation effects, mechanical vibration, and acoustic streaming effects, and this enhancement is a result of the synergistic effects of ultrasonic waves on the matrix and fluid. The study also indicates that low-permeability media are more sensitive to the ultrasonic permeability enhancement, suggesting that this technology<!--> <!-->has the potential to improve the efficiency of groundwater pollutant degradation by enhancing the permeability and mass transfer efficiency of low-permeability aquifers.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133176"},"PeriodicalIF":5.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748110","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":"Water level fluctuations control wetland hydrological connectivity in driving the integrity of wetlands","authors":"Qiang Liu ,&nbsp;Luoyang Gan ,&nbsp;Haitao Wu ,&nbsp;Liqiao Liang ,&nbsp;Denghua Yan ,&nbsp;Xuan Wang ,&nbsp;Chunhui Li ,&nbsp;Tao Sun","doi":"10.1016/j.jhydrol.2025.133095","DOIUrl":"10.1016/j.jhydrol.2025.133095","url":null,"abstract":"<div><div>Wetland hydrological connectivity, which is altered by water level fluctuations, can dramatically result in a series of changes in wetland structure and function. However, the responses of wetland habitats to changes in hydrological connectivity and its mechanisms remain unclear. This study provides a new concept of effective hydrological connectivity that considers wetland water level fluctuations. Wetland InSAR technology was used to investigate the structural connectivity of 14 wetland patches in combination with hydrological barriers and relative water levels in the Momoge National Nature Reserve, China. The 14 wetland patches were categorized into three types as follows: wetland patches with near-natural hydrological processes, wetland patches with hydrological processes under anthropogenic regulation and wetland patches with hydrological processes regulated by river flooding. Water level fluctuations further validated the consistent changes in hydrological regimes within three types of wetland patches to varying extent. Specifically, the coefficients of variation (CVs) of the water levels were 0.75 ≤ CV ≤ 0.90, CV &lt; 0.75, and CV &gt; 0.90 for the three types of wetland patches (from I to III), which induced differences in effective hydrological connectivity. Subsequently deviations in effective hydrological connectivity induced different ecological responses, i.e., the ecological resilience is accordingly −1.38, −0.78, and −0.76. The differences in water level thresholds for the intensity of hydrological connectivity provide further evidence of differences in the mechanisms of hydrological action that maintain different wetland habitats. Taken together, these results indicate that the formation and maintenance of wetland habitats depends on the existence of distinct hydrological conditions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133095"},"PeriodicalIF":5.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716282","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":"A runoff prediction approach based on machine learning, ensemble forecasting and error correction: A case study of source area of Yellow River","authors":"Jingyang Wang ,&nbsp;Xiang Li ,&nbsp;Ruiyan Wu ,&nbsp;Xiangpeng Mu ,&nbsp;Baiyinbaoligao ,&nbsp;Jiahua Wei ,&nbsp;Jie Gao ,&nbsp;Dongqin Yin ,&nbsp;Xin Tao ,&nbsp;Keyan Xu","doi":"10.1016/j.jhydrol.2025.133190","DOIUrl":"10.1016/j.jhydrol.2025.133190","url":null,"abstract":"<div><div>Accurately predicting river runoff holds substantial significance to meet several objectives, including basin water resource allocation, flood control, and drought relief. In this study, we introduced a novel multistep runoff prediction model featuring machine learning, ensemble forecasting, and error correction (EC). Five machine learning models served as base learners, providing multistep forecasting results. We introduced an ensemble forecasting strategy (EFS) to effectively combine the forecast results of the base learners. The EFS included scenario segmentation, which divided the runoff time series into flood and nonflood seasons and leveraged the strengths of different predictors to optimize weights individually, and weight combination optimization, which utilized nine optimization methods to fine-tune the weight combinations. Additionally, to further reduce predictable components in the error series, we constructed an EC model to limit forecasting errors. We conducted a series of experiments on the three hydrological stations (Jimai, Maqu, and Tangnaihai) in the source area of the Yellow River to comprehensively evaluate the effectiveness of the proposed runoff prediction approach. The 7-day experimental results demonstrated the following: (1) the EFS integrated base learners to achieve improved performance at each step compared with single models; (2) mean absolute error was notably produced following the EC, with a higher degree of improvement for longer lead days; and (3) the proposed model outperformed other existing models across all experimental stations and lead times.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133190"},"PeriodicalIF":5.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724128","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}