Journal of Hydrology最新文献

{"title":"Revealing the spatial–temporal patterns of hydropeaking induced by the Three Gorges Dam, China","authors":"Xueqin Liu ,&nbsp;Taiji Tian","doi":"10.1016/j.jhydrol.2025.134269","DOIUrl":"10.1016/j.jhydrol.2025.134269","url":null,"abstract":"<div><div>Hydropeaking, a common consequence of hydropower dam operation, causes frequent, rapid and short term fluctuations in water flow and water levels. As the number of hydropower dams continues to increase, characterizing the highly variable hydropeaking regimes has become an important topic. However, features of hydropeaking are not well studied for many rivers with a hydropower dam, especially those large hydropower dams. Here, we explored the spatial–temporal patterns of hydropeaking induced by the Three Gorges Dam (TGD), the world’s largest hydropower dam to date, based on long term water level data of ∼450 km downstream reaches. To detect and quantify hydropeaking signals, we used an integrated methodology that combined wavelet analysis with the range of variability method. Results showed that the TGD induced hydropeaking occurred at 1-day and 0.5-day cycles, and the maximum amplitude was 3.43 m, 95 % quantile 1.91 m and 90 % quantile 1.52 m at Yichang gauging station. Amplitude of hydropeaking decreased with distance from the TGD but increased from initial to normal stage of dam operation. Hydropeaking varied seasonally as its amplitude and frequency were higher during the wet season (May–November) than those of the dry season. Operation of the TGD strongly reduced the annual cycle of water level in downstream reaches after removing the effects of precipitation. Our results provide new insights into understanding the effects of large hydropower dams as well as environmental flow management in hydropeaking affected rivers.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134269"},"PeriodicalIF":6.3,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096112","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":"Seasonal and inter-annual dynamics of water vapor flux based on five-year eddy covariance measurements over an alpine grassland in arid Central Asia","authors":"Baoxiang Fan ,&nbsp;Haijun Peng ,&nbsp;Hu Yao ,&nbsp;Kaihui Li ,&nbsp;Bing Hong","doi":"10.1016/j.jhydrol.2025.134259","DOIUrl":"10.1016/j.jhydrol.2025.134259","url":null,"abstract":"<div><div>Extensive arid and semi-arid ecosystems in Central Asia are threatened by aridification and desertification owing to intensified evaporation and extreme climates. To understand the mechanisms of water vapor (H₂O) transformations and assess the water balance under climate change in Central Asian grasslands, knowledge of H₂O ecosystem-scale flux and its seasonal and interannual dynamics is important. Based on the eddy covariance technique, this study measured the five-year H₂O flux over the Bayinbuluk Grassland in Central Asia and investigated its environmental controls. The results showed that the grassland was a net source of H₂O flux, emitting 1432 ± 93 mm y⁻¹ from 2017 to 2021, with a mean annual precipitation of 237 ± 69 mm. Seasonal changes in H₂O fluxes were higher during the growing season than that during the non-growing season, with annual maxima generally occurring from July to August. A clear unimodal diurnal pattern in the H₂O flux was observed during both seasons from 2018 to 2021, with peak values appearing at approximately 14:30. We further conducted a wavelet analysis on this long-term quasi-continuous H₂O flux time series and investigated its temporal variability and wavelet coherence with environmental variables. Daily periodicity in H₂O fluxes was detected during most of the growing season. The variations in H₂O fluxes were in phase with changes in air temperature and solar radiation on a daily timescale, with relative humidity showing a negative correlation with H₂O flux. Changes in precipitation, air temperature, soil temperature, and photosynthetically active radiation exhibited stronger positive correlations with H₂O fluxes at monthly and annual timescales than daily timescales. In addition, annual evapotranspiration increased at a rate of ∼100 mm y⁻¹ during the study period, despite precipitation and air temperature showing no apparent increasing trends. Grassland ecosystems in arid Central Asia are expected to emit more H₂O under a warming climate, leading to greater water scarcity and heightened aridity. Our study highlights the importance of conducting long-term continuous eddy covariance and time-series analyses to enhance our understanding of the temporal variability in grassland H₂O exchanges.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134259"},"PeriodicalIF":6.3,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096127","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 hybrid Capsule-Transformer Network for daily runoff forecasting","authors":"Zhaowang Wu,&nbsp;Hua Yan","doi":"10.1016/j.jhydrol.2025.134125","DOIUrl":"10.1016/j.jhydrol.2025.134125","url":null,"abstract":"<div><div>Accurate prediction of daily runoff is crucial for flood prevention and water resource management. However, there exists complex interaction between periodic patterns and sudden fluctuations in hydrological processes. This makes accurate prediction challenging, especially in forecasting extreme events. Current mainstream deep learning methods struggle to simultaneously capture both local temporal dependencies and global temporal correlations. To address this challenge, CTNet (<strong>C</strong>apsule-<strong>T</strong>ransformer <strong>N</strong>etwork) is proposed as a novel hybrid neural network architecture that combines the advantages of time capsule networks and transformers. Specifically, CTNet adopts dynamic routing policy to model different local capsule features, and self-attention mechanisms to learn long-term temporal dependencies, respectively. Furthermore, a cyclic embedding mechanism is proposed to assist in modeling temporal periodicity at different time scales. Extensive experiments was conducted on three datasets: the original Qingxi River basin dataset and two interpolation-enhanced datasets (DI-32 and DI-64). On the original dataset, the mean absolute error (MAE), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), correlation coefficient (CC), and Willmott’s index (WI) values of CTNet reached 2.79, 10.65, 0.89, 0.945, and 0.971, respectively. It comprehensively outperforms current state-of-the-art models in both runtime and performance.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134125"},"PeriodicalIF":6.3,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057388","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":"Coupling semi-empirical and machine learning model in high-resolution remote sensing soil moisture retrieval","authors":"Zhenghao Li ,&nbsp;Qianqian Yang ,&nbsp;Jie Li ,&nbsp;Qiangqiang Yuan ,&nbsp;Huanfeng Shen ,&nbsp;Liangpei Zhang","doi":"10.1016/j.jhydrol.2025.134255","DOIUrl":"10.1016/j.jhydrol.2025.134255","url":null,"abstract":"<div><div>As a critical parameter of the Earth surface system, surface soil moisture (SSM) plays a pivotal role in investigating the water cycle and land-air interaction. Synthetic aperture radar (SAR)-based active microwave remote sensing offers an effective method for acquiring high-spatial-resolution SSM data. In high-resolution SSM retrieval studies, retrieval based on physical or semi-empirical physical models follows physical mechanisms, and machine learning models-based retrieval has strong learning and nonlinear modeling capabilities for multi-source datasets. Nowadays, the retrieval study of coupling physical mechanisms and machine learning has attracted much attention. To address the challenges and opportunities in high-spatial-resolution SSM retrieval studies based on SAR, we summarized multiple fusion models in this study, which were classified into three categories: complementary fusion model, predictive fusion model, and constrained fusion model, according to the relative importance of machine learning models and physical mechanisms in coupling. Several specific retrieval models for high-resolution SSM retrieval were designed based on the categories, and various comparative assessments of these models were carried out across multiple study areas. Evaluations revealed that the differentiable retrieval model, which falls under the constrained fusion model category, exhibited robust retrieval performance and spatiotemporal generalization capacity, with the highest R² values of 0.853 and the lowest ubRMSE values of 0.041 m³·m⁻³ within the study areas. It also demonstrated excellent retrieval performance under the forest cover type. The design and comparative evaluation of various fusion models in high-resolution SSM retrieval provide valuable references for related studies and offer insights for developing a series of new application modes of fusion models in the future.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134255"},"PeriodicalIF":6.3,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096474","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":"Fusion of satellite and gauge precipitation observations through coupling spatio-temporal properties with tree-based machine learning","authors":"Fengxue Ruan ,&nbsp;Fengrui Chen ,&nbsp;Qiao Liu ,&nbsp;Zhaobo Song","doi":"10.1016/j.jhydrol.2025.134240","DOIUrl":"10.1016/j.jhydrol.2025.134240","url":null,"abstract":"<div><div>Merging satellite and gauge observations is a promising solution for obtaining accurate precipitation data. Although machine learning based merging methods have shown excellent potential, their insufficient consideration of the spatial–temporal properties of precipitation greatly limits the performance of merging models. To address this problem, a novel merging approach is proposed here that couples Spatio-Temporal Properties and the Tree-based Machine Learning model (STPTML), aiming to improve the accuracy of precipitation estimation. This method focuses on two important spatio-temporal properties of precipitation: spatial correlation and temporal heterogeneity. Leveraging the intrinsic characteristics of tree-based machine learning models, an adaptive spatio-temporal encoding strategy is designed to transform these spatio-temporal properties into features that can be fully utilized by the tree model to achieve their organic coupling. The features guide the tree model to explore the spatio-temporal distribution patterns of precipitation, thereby promoting the high-level integration of satellite and gauge observations. Taking Hai River Basin as an example, the effectiveness of STPTML was verified using four typical tree models: random forest, LightGBM, XGBboost, and Catboost. The results show that: (1) STPTML greatly improved the accuracy of original satellite precipitation products compared to the state-of-the-art merging methods. (2) The proposed adaptive spatio-temporal encoding strategy exhibited broad effectiveness for tree-based models (3) The merged results greatly enhanced the reliability of satellite precipitation products in estimating rainfall erosivity. Overall, STPTML is an effective approach for the accurate estimation of precipitation, which furnish a reliable data foundation for research in the fields of meteorology and environmental science.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134240"},"PeriodicalIF":6.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059799","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":"An analytical model for chloride transport in coastal sediments under long-term sedimentation","authors":"Jiadi Zou ,&nbsp;Xiuyu Liang ,&nbsp;Xingxing Kuang ,&nbsp;Enze Ma ,&nbsp;Kewei Chen","doi":"10.1016/j.jhydrol.2025.134237","DOIUrl":"10.1016/j.jhydrol.2025.134237","url":null,"abstract":"<div><div>Freshwater scarcity in coastal areas can be alleviated by exploiting groundwater in seabed sediments. Understanding the long-term distribution and transport of chloride in these sediments is essential for effective resource assessment. In this study, we develop an analytical model that captures the evolution of vertical chloride profiles in seafloor sediments under long-term sedimentation. The model simplifies the system by treating sediment burial as a moving boundary and allowing time-varying chloride concentrations at the seawater-sediment interface, while neglecting short-term hydrodynamic processes to focus on millennial-scale diffusion driven by long-term sedimentation. A semi-analytical solution is derived and validated against numerical simulations using COMSOL Multiphysics. Application to borehole data from the Pearl River Delta and offshore Hong Kong shows that the model captures key features of observed chloride profiles, with diffusion and sedimentation identified as dominant controls. While the model adopts simplified assumptions, it offers a computationally efficient framework that complements more detailed numerical approaches.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134237"},"PeriodicalIF":6.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096107","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":"Insight into the pollution potential of different ecological types of lakes from the perspective of dissolved organic matter characteristics: Field and experimental evidence","authors":"Yang Deng ,&nbsp;Longmian Wang ,&nbsp;Yueming Zhu ,&nbsp;Xiang Zhu ,&nbsp;Qingqing Pang ,&nbsp;Yuying Ma ,&nbsp;Fuquan Peng ,&nbsp;Lei Xie ,&nbsp;Xiaoguang Xu ,&nbsp;Qiu Jin ,&nbsp;Guoxiang Wang ,&nbsp;Fei Yang ,&nbsp;Jianying Chao","doi":"10.1016/j.jhydrol.2025.134249","DOIUrl":"10.1016/j.jhydrol.2025.134249","url":null,"abstract":"<div><div>The changes in dissolved organic matter (DOM) in freshwater lakes are crucial for understanding water quality dynamics and the carbon cycle, yet the mechanisms driving these changes remain unclear. In this study, six freshwater lakes were categorized into two ecological types: algae-dominated and hydrophyte-dominated. The characteristics of their DOM were found to be significantly different. Algae-dominated lakes exhibited a higher distribution ratio of C4 (tyrosine-like) fluorescence component. Notably, the emission fluxes of methane (CH₄) and carbon dioxide (CO₂) were significantly correlated with tyrosine-like substances the in algae-dominated lakes. Simultaneously, microcosms simulating algae and hydrophyte decomposition were cultured to represent these distinct ecological types. The characteristics of the DOM components aligned with the field survey results, and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) indicated that the algae-dominated microcosms contained higher protein content and greater variation. The relative abundance of <em>Bacteroidetes</em> was consistently higher in algae-dominated microcosms. Furthermore, this study identified that the high concentration of proteins produced by algae decomposition played a key role in promoting water quality deterioration. These findings illuminate the differences in DOM characteristics during hydrophyte and algae decomposition across various lake types, providing valuable insights for effective lake management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134249"},"PeriodicalIF":6.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145096108","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":"Satellite-based monitoring and hazard assessment of multiple flooding types in the Haihe river Basin induced by the July 2023 extreme rainstorm","authors":"Ziteng Xu ,&nbsp;Wentao Yang ,&nbsp;Xiya Zhang ,&nbsp;Changjun Gu ,&nbsp;Lingling Shen ,&nbsp;Haibo Hu","doi":"10.1016/j.jhydrol.2025.134243","DOIUrl":"10.1016/j.jhydrol.2025.134243","url":null,"abstract":"<div><div>In the context of global climate change, extreme rainstorms are increasingly frequent. In complex terrain, a single rainstorm often triggers different types of flooding, including flash floods, river floods, and waterlogging, posing threats to socioeconomic and human safety. Most studies treat these floods uniformly, relying on a single data source and method, inadequately capturing their heterogeneity and causes. Focusing on the July 2023 extreme rainstorm and flood in the Haihe River Basin, this study developed a framework to monitor different types of flooding using multi-source satellite data and to analyse their driving factors and hazards. In the plains, we used Sentinel-1 and GF-3 SAR data to extract inundated areas of river floods and waterlogging. In the mountain areas, flash flood-affected areas were identified by combining Sentinel-2 NDVI changes with terrain and hydrological analyses. Random forest models compared driving factors among flood types and assessed flood hazards. Results show flash floods in mountain areas concentrate in low-lying river valleys, with slope contributing 24.33%. In the plains, river floods expanded progressively, while waterlogging displayed significant differences in response between urban and rural areas, with distance to rivers (27.88%) and maximum daily rainfall (13.84%) identified as dominant factors. From these findings, we generated a flood hazard distribution map that accurately identifies areas with high flood hazard. By classifying flood types and analysing driving factors, this study reveals the heterogeneity of flooding induced by a single extreme rainstorm. Furthermore, it offers scientific insights and a novel framework for managing floods under extreme rainfall.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134243"},"PeriodicalIF":6.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059801","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 three-dimensional coupling evaluation model for carbon source-sink in riparian zones","authors":"Na Li,&nbsp;Juan Peng,&nbsp;Feng Yan","doi":"10.1016/j.jhydrol.2025.134254","DOIUrl":"10.1016/j.jhydrol.2025.134254","url":null,"abstract":"<div><div>Riparian zones, with high carbon sequestration capacity, play a critical role in watershed carbon cycles. Current riparian carbon sink assessments primarily focus on drawdown zones or only consider riparian ecological process, neglecting hydrological process. The objective of this study is to develop a three-dimensional coupling evaluation model for riparian carbon source-sink integrating ecological and hydrological processes, which include vertical, lateral, and longitudinal dimensions. (i) Vertical carbon source-sink: carbon release via respiration and carbon sequestration via photosynthesis. (ii) Lateral carbon source-sink: carbon loss via slope runoff erosion and carbon interception through soil conservation. (iii) Longitudinal carbon source-sink: carbon depletion by riverbank scouring of runoff and carbon sequestration by fluvial sediment deposition. Applied to the Fuhe River, the results show that: (i) The riparian zone of Fuhe River is a net carbon sink (593.0 t·a^-1), with an economic value of 25,410.1 CNY. Vertical carbon process is a net carbon sink (5,657.0 t·a^-1), while the lateral and longitudinal processes act as net carbon source (2,607.0 and 2,457.0 t·a^-1, respectively). (ii) By riparian zone sections, the water-level fluctuation zone acts as a net carbon source (3,680.3 t·a^-1), while the riverbank zone functions as a net carbon sink (4,273.3 t·a^-1). (iii) Spatially, the upstream and midstream are net carbon sinks (513.04 and 234.35 t·a^-1, respectively), while the downstream is a net carbon source (154.41 t·a^-1). (iv) Enhancing vegetation coverage to boost photosynthetic capacity is key to increase carbon sink, and strengthening soil conservation measures to cut organic carbon loss from soil erosion is crucial for reducing carbon source.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134254"},"PeriodicalIF":6.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059794","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":"Innovative groundwater disaster prevention and control systems for ultrawide working face mining in deeply buried confined aquifers","authors":"Fangying Dong ,&nbsp;Huiyong Yin ,&nbsp;Shaojie Chen ,&nbsp;Daolei Xie ,&nbsp;Wanfang Zhou ,&nbsp;Chenghao Han ,&nbsp;Jiuchuan Wei ,&nbsp;Fanhua Wang ,&nbsp;Tao Wu","doi":"10.1016/j.jhydrol.2025.134244","DOIUrl":"10.1016/j.jhydrol.2025.134244","url":null,"abstract":"<div><div>Coal mining in confined aquifers is generally threatened by water inrush disasters originating from the floor. As mining depth increases, the complexity of hydrogeological conditions, coupled with limited exploration accuracy, and ineffective prevention measures pose significant challenges to accurately managing mine water disasters. Especially, ultrawide working face mining in confined aquifers, the prevention methods of floor water disaster have not been systematically studied. Based on the mining of the working face (width more than 400 m) above the Ordovician limestone confined aquifer, this paper carried out joint exploration of hydrogeological conditions, numerical simulation of ultrawide working face mining, evaluation of water inrush potential of mining floor and dynamic monitoring of water coupling in working face. The results show that the hydrogeological and structural geological conditions of the working face and its surroundings are accurately identified by the multi-method joint exploration. The stress evolution rule of ultrawide working face before and after roof cutting is revealed. The failure depth, maximum shear stress, maximum principal stress, vertical stress and pore water pressure of the floor after roof cutting are reduced by 28.6 %, 30.9 %, 12.1 %, 15.5 % and 14.3 %, and the stress concentration factor is also reduced by 19.5 %. The prediction model of mining floor failure depth and the evaluation model of floor water inrush potential are constructed, with the accuracy of 94.0 % and 88.2 %, respectively. This study put forward a water prevention scheme of pre-mining treatment and dynamic monitoring in mining, establishes a dynamic multilevel geological guarantee system for ultrawide working face mining in confined aquifers, integrating “joint exploration, precise prevention and control, and water resources.” Finally, the system was successfully applied to the 21,609 working face of Binhu Coal Mine, liberating 359,000 tons of coal resources. Compared to traditional method, the failure depth of mining floor is reduced by 44.3 %, significantly decreasing the possibility of floor water inrush. The research results provide a typical demonstration for the secure, efficient and environmentally friendly coal mining operations in confined aquifers, enrich the theory of mining under pressure and the methods of water prevention.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"663 ","pages":"Article 134244"},"PeriodicalIF":6.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109446","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}