Journal of Hydrology最新文献

{"title":"Mature stands of exotic tree species consume less water while sequester comparable carbon as those of native tree species: A 4-year monitoring study in South China","authors":"Yanqiong Li ,&nbsp;Liwei Zhu ,&nbsp;Huiying Ye ,&nbsp;Ping Zhao","doi":"10.1016/j.jhydrol.2025.133542","DOIUrl":"10.1016/j.jhydrol.2025.133542","url":null,"abstract":"<div><div>The wide application of fast-growing exotic and native tree species for reforesting degraded lands not only improves the ecological environment but more importantly, increases carbon sequestration to mitigate increasing atmospheric CO₂. Nevertheless, the controversial issue of changes in hydrology and carbon sequestration capacity that inevitably arise with the maturity of these fast-growing forests requires long-term monitoring research to clarify. This study investigated the water use and carbon assimilation patterns of exotic <em>Acacia auriculiformis</em>, <em>Eucalyptus citriodora</em>, and native <em>Schima superba</em> forests, based on 4-year sap flow monitoring combined with the multi-layer canopy conductance-constrained carbon assimilation model, and assessed their responses to environmental factors. The results reveal: (1) <em>S. superba</em> exhibited the highest average daily water use (<em>Q</em>_d) and forest transpiration (<em>E</em>_g). The average annual <em>E</em>_g for <em>E. citriodora</em>, <em>A. auriculiformis</em> and <em>S. superba</em> was 305.3, 359.9, 596.6 mm, respectively. (2) The average carbon assimilation rate (<em>A</em>_net) was 1.11, 1.13, 0.86 μmol·m⁻²·s⁻¹ and the mean annual forest carbon assimilation amount (<em>C</em>_stand) was 9.0, 10.7, 10.8 × 10³ t·ha⁻¹, for <em>A. auriculiformis</em>, <em>E. citriodora</em> and <em>S. superba</em>, respectively. (3) Environmental factors, along with the sap flux density and leaf photosynthetic parameters, explained 59 % to 75 % of forest <em>A</em>_net variance. The interaction of these factors explained 15 %, 9 %, and 18 % of <em>A</em>_net variance for <em>A. auriculiformis</em>, <em>E. citriodora</em> and <em>S. superba</em>, respectively. Despite consuming less water, mature exotic <em>A. auriculiformis</em> and <em>E. citriodora</em> forests sequestered comparable carbon to native <em>S. schima</em> forest, highlighting that exotics enhance carbon sequestration without adverse hydrological consequences as they mature.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133542"},"PeriodicalIF":5.9,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084688","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":"Synergistic estimates of global 4-day 500 m gross primary production, evapotranspiration, and ecosystem water use efficiency from satellite data","authors":"Yifei Sun ,&nbsp;Ronglin Tang ,&nbsp;Lingxiao Huang ,&nbsp;Meng Liu ,&nbsp;Yazhen Jiang ,&nbsp;Zhao-Liang Li","doi":"10.1016/j.jhydrol.2025.133506","DOIUrl":"10.1016/j.jhydrol.2025.133506","url":null,"abstract":"<div><div>Gross primary production (GPP) and evapotranspiration (ET) are essential components of global carbon and water cycles, respectively, while the ratio of GPP to ET, also known as ecosystem water use efficiency (WUE), reflects the trade-off between carbon gain and water loss in terrestrial ecosystems. Simultaneous estimates of GPP, ET, and WUE from satellite data with high accuracies are highly challenging due to negligence or inadequate representation of co-variation of GPP and ET in current models. This study develops a novel and practical model for Synergistic estimates of global 4-day 500 m gross primary Production, Evapotranspiration, and ecosystem water use Efficiency (SynPEE), by combining the multivariable convolutional neural network (MCNN) and a synthesis of in-situ observations at 314 globally distributed sites, satellite remote sensing datasets, and ERA5-land reanalysis datasets from 2000 to 2020. The newly proposed SynPEE model is prominently superior in (1) explicitly considering the synergistic relationship among the GPP, ET, and WUE; (2) achieving high-accuracy estimations of GPP, ET, and WUE simultaneously; and (3) avoiding the outliers of WUE estimates that are commonly found in the un-synergistic models. Validated against in-situ observations by a spatial 10-fold cross-validation scheme, the SynPEE model was proven to overall outperform the un-synergistic models (CNN_IN) constructed for separate estimates of GPP, ET and WUE. Moreover, the SynPEE model also showed much better performances than four state-of-the-art RS products, i.e., BESSv2, PMLv2, FLUXCOM, and MODIS. Furthermore, the spatio-temporal patterns of the 8-day and yearly GPP, ET and WUE estimates by the SynPEE model were generally consistent with those of the four state-of-the-art products. The SynPEE model has great potential of generating time-series products of high-accuracy global GPP, ET and WUE, which is promising to enhance our understanding of land–atmosphere interactions of carbon and water, thus better serving for terrestrial carbon and water management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133506"},"PeriodicalIF":5.9,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084687","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":"The spatial–temporal variability of methane emissions in a montane headstream: implication of precipitation, morphology and microhabitat","authors":"Honglin Chen ,&nbsp;Xiaofeng Wang ,&nbsp;Jilong Wang ,&nbsp;Xianxiang Li ,&nbsp;Chen Jian ,&nbsp;Dongfeng Li ,&nbsp;Yuewei Zhang ,&nbsp;Yixin He","doi":"10.1016/j.jhydrol.2025.133534","DOIUrl":"10.1016/j.jhydrol.2025.133534","url":null,"abstract":"<div><div>Headstreams are significant sources of atmospheric methane (CH₄). However, the high spatial–temporal variability presents significant challenges for inventory estimation of CH₄ emissions from headstreams. Particularly in mountainous headstreams with high heterogeneity of morphology and microhabitats, the key factors controlling CH₄ emissions remain unclear. This study conducted monthly surveys of dissolved CH₄ concentration (dCH₄) and CH₄ flux (fCH₄) in a montane headstream basin in southwestern China at high spatial resolution. It focused on the synthetic effects of morphology, microhabitat, and nutrients on the spatial–temporal variability in CH₄ fluxes. The overall mean dCH₄ and fCH₄ in the selected headstream were 79.4 ± 80.4 nmol L^-1 and 1.24 ± 0.98 mmol m⁻² d^-1, respectively, indicating it acts as a moderate source of CH₄ emission. The dCH₄ and fCH₄ displayed opposite temporal patterns: high concentrations but low fluxes during the dry season, and low concentrations but high fluxes during the wet season. These temporal patterns are primarily dominated by enhanced turbulent degassing driven by seasonal precipitation. From a watershed perspective, both dCH₄ and fCH₄ increased progressively from upstream to downstream. Total carbon and organic carbon in waters can explain over 60 % of the spatial variation in fCH₄ either in dry or rainy seasons, indicating that carbon accumulation downstream may account for the watershed variation in CH₄ emissions. River width and slope can influence dCH₄ and fCH₄ indirectly <em>via</em> disturbing nutrient distribution. In addition, from a local perspective, microhabitats (deep pools, shallows, or rapids) and substrate types in the headstream intensified the local heterogeneity of fCH₄ by affecting water turbulence and nutrient distribution, leading to multiple spatial variations. Given the complex habitat conditions of mountainous streams, especially in the context of global climate change, incorporating these variables into future models will enhance our understanding of the roles of headstreams in the global carbon cycle.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133534"},"PeriodicalIF":5.9,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071323","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":"Improving runoff modelling through strengthened snowmelt and glacier module enhances runoff attribution in a large watershed in Central Asia","authors":"Jianan Yu ,&nbsp;Bing Gao ,&nbsp;Mingliang Li ,&nbsp;Peng Xiao","doi":"10.1016/j.jhydrol.2025.133528","DOIUrl":"10.1016/j.jhydrol.2025.133528","url":null,"abstract":"<div><div>Understanding runoff changes at the catchment scale is important for water resources management. Particularly, accurate attribution of runoff changes poses a significant challenge for water resources management in cold and arid regions due to complex cryospheric processes. This study improved the physically based distributed Geomorphology-Based Hydrological Model (GBHM) through modified snow module and supplement of glacier melt module. The improved model was validated using streamflow observations and applied to simulate natural runoff in Central Asia’s Balkhash Lake Basin (1955–2020). By comparing simulated natural runoff with observed records, we quantified climate change and human activities impacts across three periods: Human activities dominated runoff reductions during 1970–1986 (80.11%) and 1987–2002 (67.55%), climate change and human activities showed comparable influences during the period of 2003–2020 (43.22% vs 56.78%). Scenario simulations demonstrated limited hydrological effects from land use changes, with no consistent directional trend. The improved GBHM provides a practical tool for cold region hydrology studies, offering critical insights for sustainable water management in transboundary basins over arid and cold region.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133528"},"PeriodicalIF":5.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071321","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":"Predicting hydrological drought indices using a hybrid data-driven model incorporating hydrological, geomorphological, and human activity impacts","authors":"Pin-Chun Huang","doi":"10.1016/j.jhydrol.2025.133491","DOIUrl":"10.1016/j.jhydrol.2025.133491","url":null,"abstract":"<div><div>This study presents a hybrid data-driven model to predict hydrological drought indices by integrating geomorphological, hydrological, and human activity factors. The model is trained using streamflow data simulated by the SWAT (Soil and Water Assessment Tool) and incorporates spatial zoning via Self-Organizing Map (SOM) networks to account for spatial variability across different zones. Each zone is trained independently using a ConvLSTM (Convolutional Long Short-Term Memory) model, which captures spatial and temporal information critical to hydrological time series data. Key input factors include geomorphological features such as drainage area, stream order, land cover, and hydrological and meteorological conditions like precipitation and evapotranspiration. Human activity factors, such as groundwater abstraction and industrial water consumption, are also integrated to reflect their impact on drought conditions. The trained model outputs two key hydrological drought indices, the standardized runoff index (SRI) and drought deficit volume, which are used to assess drought severity and further employed to calculate more metrics concerning drought termination. The hybrid model enhances drought prediction accuracy by leveraging the spatial and temporal dynamics of the watershed system without the additional use of a hydrological model. With a 30-day (1-month) prediction window, the model effectively captures temporal drought patterns while maintaining a balance between accuracy and computational efficiency. Furthermore, key evaluation metrics confirm the model’s accuracy and robustness. The Mean Relative Error (MRE) is less than 0.058, indicating minimal prediction error, while the Nash-Sutcliffe Efficiency (NSE) is greater than 0.905, demonstrating strong agreement with observed values. Additionally, the Pearson Correlation Coefficient (PCC) exceeds 0.976, highlighting a near-perfect correlation between predictions and actual data. These findings confirm the model’s reliability and effectiveness in drought prediction. These improvements provide valuable insights for efficient water resource management and drought impact mitigation.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133491"},"PeriodicalIF":5.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071326","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":"Facilitating sensitivity analysis of hydrological models through knowledge-driven configuration and distributed online model services","authors":"Peilong Ma ,&nbsp;Min Chen ,&nbsp;Shuo Zhang ,&nbsp;Zhiyi Zhu ,&nbsp;Zhen Qian ,&nbsp;Zaiyang Ma ,&nbsp;Fengyuan Zhang ,&nbsp;Wenwen Li ,&nbsp;Songshan Yue ,&nbsp;Yongning Wen","doi":"10.1016/j.jhydrol.2025.133406","DOIUrl":"10.1016/j.jhydrol.2025.133406","url":null,"abstract":"<div><div>Hydrological models (HMs) are essential for understanding the complexities of the water cycle and runoff dynamics. Sensitivity analysis (SA), an essential component of HMs, plays a key role in identifying the parameters that have the greatest impact on model outcomes. It helps to simplify the complexity of hydrological systems and provides a comprehensive understanding of the underlying physical processes. However, the complexity of HMs and the diversity of SA methods pose significant challenges for researchers, making the SA configuration process intricate and requiring substantial computational resources. To address these challenges, we propose a comprehensive strategy that integrates knowledge-driven configuration services with distributed online model services. First, we establish a rule-based knowledge repository and a case-based knowledge repository. These repositories provide general configuration guidance and similar SA case recommendations, respectively, to support decision-making in critical SA steps. This ensures that the configuration of SA is accurate and reliable. Secondly, we encapsulate HMs as web services and leverage distributed computing resources to optimize execution efficiency. Then, we integrate the HM services with the SA modules to achieve a complete SA experiment. Based on this strategy, we finally developed a prototype system that offers a user-friendly tool for conducting SA with enhanced computational performance and streamlined workflow. The watershed-scale HM, SWAT, was used to test the effectiveness of the prototype system. The results demonstrate that this strategy enables more comprehensive analysis and improves decision-making through configuration guidance, and holds promise for enhancing the reliability and efficiency of SA in hydrological modeling.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133406"},"PeriodicalIF":5.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069745","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":"Critical hydro-geomorphological characteristics related to lateral erosion–deposition difference within the multilevel bifurcation system of the Yangtze Estuary, China","authors":"Boyuan Zhu ,&nbsp;Shiyu Zhang ,&nbsp;Lingling Zhu ,&nbsp;Lingfeng Liu ,&nbsp;Wenjun Yu ,&nbsp;Jinwu Tang ,&nbsp;Yongzhou Cheng ,&nbsp;Yitian Li ,&nbsp;Alistair G.L. Borthwick","doi":"10.1016/j.jhydrol.2025.133497","DOIUrl":"10.1016/j.jhydrol.2025.133497","url":null,"abstract":"<div><div>Swings of ebb flow axes among branching channels alter the lateral hydrodynamics within bifurcating estuaries, causing the channels to undergo erosion–deposition transitions. This study examines the three-order bifurcation system of the Yangtze Estuary through integrated analysis of observed water–sediment and terrain data from 1950 to 2022 and simulations by a shallow flow model based on Delft 3D. The model is shown to perform well in hindcasting the flow behavior in the Yangtze Estuary and in identifying critical runoff discharges at which the ebb flow axis migrates between the north and south branching channels of each-order bifurcation under corresponding tidal ranges. These critical runoff discharges occur at mutation points where ebb partition ratios of the north/south branching channels increase/decrease abruptly with gradually increasing runoff. By applying linear regression to critical runoff discharges and corresponding tidal ranges at each bifurcation order, the value domain divides into two subareas corresponding to the position of the ebb flow axis in north and south branching channels. We find the multiyear average duration days of ebb-flow-axis location to be effective as an indicator of the mean and spread of erosion–deposition in the branching channels and detect the critical values at erosion–deposition transitions. Other influence factors, including peak river discharge, sediment flux, offshore dynamics, and local engineering projects, also impact on erosion–deposition in the branching channels. The ranked orders of critical runoff discharges and critical duration days among the three-order bifurcations are interpreted, and these critical indexes are linked to the water excavating force, indicating their reliability and effectiveness. Seasonal flattening of runoff discharge, controlled by large cascade reservoirs in the upper Yangtze, has greatly shortened and lengthened location duration of ebb flow axis in the north and south branching channels at each-order bifurcation, and is likely to maintain their respective deposition and erosion behaviors in the future.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133497"},"PeriodicalIF":5.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084684","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":"Microbial effects on flow rates and dissolved organic carbon migration through inactive supply wells: Insights into the mechanisms of biological clogging","authors":"Zhang Wen ,&nbsp;Xu Li ,&nbsp;Qi Zhu ,&nbsp;Jianlong Huang ,&nbsp;Hamza Jakada","doi":"10.1016/j.jhydrol.2025.133494","DOIUrl":"10.1016/j.jhydrol.2025.133494","url":null,"abstract":"<div><div>Inactive supply wells (ISWs) can act as preferential flow paths facilitating the transfer of dissolved nutrients, petroleum pollutants and other undesirable constituents between aquifers, which can degrade groundwater quality, through a process known as cross-contamination. Specifically, dissolved organic carbon (DOC) can migrate into deep aquifers through ISWs, influencing the migration and transformation of various contaminants. DOC also participates in biogeochemical reactions driven by microbial activity, which can foster biological clogging near ISWs, reducing flow rates and hindering the migration of contaminants. However, the role of biological clogging in altering flow rates and DOC migration through ISWs has not been exhaustively investigated. To address this gap, a novel cross-contamination model for DOC was developed, incorporating advection, radial dispersion, multispecies and multiphase reactive transport and biological clogging, with the aim of elucidating the effects of the microbial processes on flow rates and DOC migration. The finite-difference method was employed to solve the model, and discuss the impacts of biological clogging on hydraulic conductivity, flow rates, spatial concentration distribution and breakthrough curves (BTCs). Our results showed that microbial growth near ISWs results in a reduction in porosity (approximately 45 %) and hydraulic conductivity (approximately 64 %) in a confined aquifer. In addition, biological clogging decreases flow rates, while higher concentrations of dissolved oxygen (DO) exacerbate the clogging, further reducing flow rates. Finally, microbial consumption of DOC results in a reduction in its migration range. These biological effects play a crucial role in the protection of groundwater resources, and these findings provide valuable insights for the management of ISWs, especially regarding biological clogging mechanisms and the protection of deep groundwater resources.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133494"},"PeriodicalIF":5.9,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071375","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":"Unraveling the influence of paleochannels in coastal environments vulnerable to saltwater intrusion: A synergistic approach of electrical resistivity tomography and groundwater modeling","authors":"Xiao Yang ,&nbsp;Shuai Shao ,&nbsp;Chao Jia ,&nbsp;Kaifang Kong","doi":"10.1016/j.jhydrol.2025.133500","DOIUrl":"10.1016/j.jhydrol.2025.133500","url":null,"abstract":"<div><div>Paleochannels play a dual role in coastal aquifers, acting as groundwater reservoirs while also serving as preferential pathways for seawater intrusion. Understanding their influence on groundwater salinization is crucial for coastal water resource management. This study integrates geophysical, geochemical, and isotopic methods to delineate paleochannel morphology and assess its role in saltwater migration. A petrophysical conversion model was developed to transform electrical resistivity anomalies into total dissolved solids (TDS) distributions, enhancing subsurface characterization. Electrical resistivity tomography (ERT), borehole data, hydrochemical analysis, and stable isotope tracers (δ¹⁸O, δ²H) were combined to identify groundwater sources and flow dynamics. A numerical solute transport model incorporating these datasets was established to investigate the role of paleochannels in controlling groundwater salinity. Results indicate that paleochannels significantly influence groundwater salinity, with TDS concentrations following the trend: unconfined &gt; semi-confined &gt; confined aquifers. Groundwater within paleochannels is predominantly derived from precipitation, but excessive pumping accelerates seawater intrusion, whereas increased recharge mitigates its effects. The integration of geophysical anomalies with hydrochemical data effectively identifies paleochannel structures, particularly in shallow aquifers, providing a robust approach for assessing their vulnerability to seawater intrusion. The integration of geophysical anomalies with hydrochemical data effectively identifies paleochannel structures, particularly in shallow aquifers, providing a robust approach for assessing their vulnerability to seawater intrusion. This multi-source data framework offers an improved methodology for mapping paleochannel distribution and quantifying its role in coastal groundwater salinization, providing critical insights for water resource management and aquifer protection.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133500"},"PeriodicalIF":5.9,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071373","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":"Physics-constrained machine learning for satellite-derived evapotranspiration in China","authors":"Chen Zhang ,&nbsp;Chang Zhou ,&nbsp;Geping Luo ,&nbsp;Su Ye ,&nbsp;Zhou Shi","doi":"10.1016/j.jhydrol.2025.133512","DOIUrl":"10.1016/j.jhydrol.2025.133512","url":null,"abstract":"<div><div>Evapotranspiration estimates for China derived from empirical and physical models exhibit limited agreement in magnitude and trends, due to the complexity of surface characteristics and climatic conditions. Advances in knowledge-guided data-driven methods allow hybrid models that integrate remote sensing-based ET algorithms with machine learning (ML) to mitigate these discrepancies effectively. We developed two hybrid models, ML_PM and ML_SEB, by coupling the Penman Monteith (PM) and surface energy balance (SEB) algorithm with three ML methods: Artificial Neural Networks (ANN), Random Forest (RF), and Light Gradient Boosting Machine (LGBM), and then simulated China’s ET from 2001 to 2022. The hybrid models ML_PM, ML_SEB, replaced empirical formulas of the critical but uncertain parameters: surface resistance (rs) and aerodynamic resistance (ra) with ML, respectively, considering energy balance and turbulent diffusion processes. Hybrid modeling enhanced the representation of physical processes while preserving high estimation accuracy. We evaluated the hybrid models using 63 eddy covariance (EC) sites across China and compared them with process-based physical models and pure ML. Results indicated that the hybrid models ML_PM and ML_SEB substantially improved the performance of the PM (NSE: 0.49) and SEB (NSE: −0.53), achieving NSE values of over 0.8 and 0.6, respectively. ML_PM, in particular, performed on par with pure ML overall and outperformed them for grassland and forest ecosystems, owing to its stronger physical foundation. Moreover, the hybrid models demonstrated greater robustness and generalization under sparse sampling and extreme events compared to pure ML. The optimal hybrid model (RF_PM) produced an annual mean ET of 580.33 ± 9.01 mm yr⁻¹ for China over 2001–2022, with a statistically insignificant increasing trend (0.52 mm yr⁻², p &gt; 0.05). Overall, hybrid modeling achieved an optimal balance between physical mechanism and estimation accuracy, offering a new perspective for ET estimation and enhancing our understanding of hydrological processes at regional and global scales under climate change.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"660 ","pages":"Article 133512"},"PeriodicalIF":5.9,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069738","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}