Journal of Hydrology最新文献

{"title":"On the synchronization of compound drought and heatwave events over global land regions","authors":"Wenkai Lyu ,&nbsp;Xinguang He ,&nbsp;Binrui Liu ,&nbsp;Mingming Qin ,&nbsp;Ajiao Chen ,&nbsp;Huade Guan","doi":"10.1016/j.jhydrol.2025.132836","DOIUrl":"10.1016/j.jhydrol.2025.132836","url":null,"abstract":"<div><div>As global compound drought and heatwave (CDHW) events have shown a trend towards multi-regional concurrency, quantifying their synchronous structures and exploring potential drivers for synchronizing CDHW events are crucial for disaster prevention and mitigation. This study identifies global CDHW events based on daily soil moisture and maximum temperature during 1979–2022, and investigates the topological characteristics of concurrent CDHW events through complex network (CN) analysis. Subsequently, the potential physical drivers causing the spatial concurrence of CDHW events are explored based on their synchronous structures. Results show that high-incidence regions for CDHW events include eastern North America, northern and southeastern South America, northern Eurasia, Southeast Asia and the central Yangtze River Basin. The CN coefficients derived from the synchronization network unveil a highly heterogeneous connectivity structure underlying global CDHW events. In northern and southeastern South America, synchronous CDHW events primarily occur at a regional scale. In contrast, regions such as the Amazon, the Congo Basin and the Yangtze River Basin, which serve as important hubs within the synchronization network, can synchronize CDHW events with other hubs at an inter-continental or even inter-hemispheric scale. Hubs at high latitudes in the Northern Hemisphere predominantly synchronize CDHW events with remote places at similar latitudes. Furthermore, the simultaneous occurrences of CDHW events in western North America, western Russia and the Yangtze River Basin are strongly associated with sea surface temperature anomalies in the central Pacific, North Pacific, North Atlantic, and Barents Sea, while the synchronous CDHW event onsets across multiple regions in the middle and high latitudes of the Northern Hemisphere are closely relevant to Rossby waves. These insights are valuable for proposing adaptation measures for spatially synchronous CDHW events and predicting such events in the future.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132836"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395831","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 ensemble multi-model approach for long-term river flow forecasting in managed basins of the Middle East: Insights from the Karkheh River Basin","authors":"Mohammad Fallah Kalaki ,&nbsp;Majid Delavar ,&nbsp;Ashkan Farokhnia ,&nbsp;Saeed Morid ,&nbsp;Vahid Shokri Kuchak ,&nbsp;Hamidreza Hajihosseini ,&nbsp;Ali Shahbazi ,&nbsp;Farhad Nourmohammadi ,&nbsp;Ali Motamedi ,&nbsp;Mohammad Reza Eini","doi":"10.1016/j.jhydrol.2025.132846","DOIUrl":"10.1016/j.jhydrol.2025.132846","url":null,"abstract":"<div><div>In this study, we evaluated the accuracy of weather and river discharge forecasts for the Karkheh River Basin on the Iranian plateau. We utilized weather parameters from the North American Multi-Model Ensemble (NMME)—specifically precipitation and maximum and minimum temperature—for long-term weather forecasting and assessed their accuracy in runoff simulations using the Soil and Water Assessment Tool (SWAT). The primary aim of the study was to explore the potential improvements in forecast accuracy through the application of NMME models, both individually and in combination, to hydrological forecasting. To achieve this, we employed two statistical approaches (MLR and KNN), for spatial and temporal downscaling of the NMME models, respectively. The results revealed that the combination of NMME models outperforms individual models in robustly predicting precipitation and temperature. Specifically, precipitation forecasts showed better accuracy during spring (with correlation coefficients ranging from 0.79 to 0.89) and fall (correlation coefficients ranging from 0.43 to 0.79), while their performance was weaker during summer. Temperature forecasts exhibited high accuracy, particularly in warmer periods (with correlation coefficients ranging from 0.75 to 0.99). Given the importance of accurately predicting precipitation during rainy seasons for runoff predictions and precise temperature forecasts during warm seasons, the NMME system demonstrated satisfactory performance and proved to be a valuable input for hydrological models. Furthermore, we used SWAT to predict river discharge with lead times of 1 to 3 months. Notably, the runoff forecast with a 1-month lead time showed the highest performance, as indicated by a correlation coefficient of 0.61.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132846"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386665","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":"Spatiotemporal variability and dominant driving factors of satellite observed global soil moisture from 2001 to 2020","authors":"Yu-Xuan Li ,&nbsp;Pei Leng ,&nbsp;Abba Aliyu Kasim ,&nbsp;Zhao-Liang Li","doi":"10.1016/j.jhydrol.2025.132848","DOIUrl":"10.1016/j.jhydrol.2025.132848","url":null,"abstract":"<div><div>Soil moisture is a critical component of the global land-surface hydrological cycle, significantly impacting fields such as meteorology, agriculture, and water resource management. Understanding the spatiotemporal variability of global soil moisture and its dominant driving factors is essential for addressing global climate change and mitigating extreme climate events. This study investigates the spatiotemporal variability of the latest version of the satellite-based global soil moisture (ESA CCI v09.1) and its dominant driving factors across different temporal scales from 2001 to 2020. The results reveal that short-term scales (8-day and monthly) show higher variability, reflecting rapid climate events and soil responses, while long-term scale (annual) demonstrates more stable patterns. On an annual scale, over 5% of the global land area experienced significant drying, while another 5% showed increased wetness. Significant spatial differences in soil moisture were observed across various climate zones and latitudes. Using the Generalized Additive Model, the dominant factors influencing soil moisture trends were identified for each grid. On an 8-day scale, vapor pressure deficit is the primary driver factor in most regions, while evapotranspiration plays a key role in tropical areas. At the monthly scale, vapor pressure deficit influences high latitude regions, whereas precipitation is the main factor at low latitudes. The combined effect of dominant factors on soil moisture is stronger in low latitudes and weaker in high latitudes. These findings improve our understanding of soil moisture dynamics and offer valuable insights for managing water resources and mitigating the impacts of extreme climate events.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132848"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379207","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":"Quantifying the impacts of ENSO on Australian summer rainfall extremes during 1960–2020","authors":"Jinping He ,&nbsp;Shuangshuang Li ,&nbsp;Bin Wang ,&nbsp;Liwei Zhang ,&nbsp;Keqin Duan","doi":"10.1016/j.jhydrol.2025.132834","DOIUrl":"10.1016/j.jhydrol.2025.132834","url":null,"abstract":"<div><div>Global climate change has significantly altered extreme rainfall regimes in Australia. However, the spatiotemporal distribution of extreme dry and wet conditions, and their relationship with the El Niño–Southern Oscillation (ENSO), particularly within Australian broadacre zones (high rainfall, wheat-sheep, and pastoral zones), remains poorly understood. Hence, we analyzed the spatiotemporal variability of extreme dry and wet events with Standardized Precipitation Index (SPI) and quantified ENSO impacts on rainfall extremes over Australian broadacre zones. The results showed that high rainfall zone and wheat-sheep zone of eastern Australia became drier, while Western Australia (pastoral zone) became wetter from 1960 to 2020. In the past decade, the hotspot areas to extreme or severe dry and wet events constituted 6.5 % and 7.8 % of stations in Australia, demonstrating the widespread concurrence of extreme wet and dry conditions in the high rainfall and wheat-sheep zones. The hotspot areas of dry events shifted from the southeastern into central-eastern Australia, as well as dry conditions weakened in southwestern Australia and eastern Tasmania. In contrast, hotspot areas of wet events occurred more frequently in the southwest and east of continental Australia. The relationship between SPI and ENSO indexes identified that Niño 3.4 sea surface temperature anomaly (SSTA) Index, Niño 4 SSTA Index, cold-tongue ENSO Index and Southern Oscillation Index (SOI) in the preceding winter were robust precursors to summer extreme rainfall events over Australia. Spatially, the ENSO-rainfall relationship showed the eastern-western asymmetric pattern and eastern Australia was a key area affected by above four ENSO indexes. We further confirmed the northeast Australian rainfall was significantly affected by ENSO, but this robust relationship does not extend to the south of Great Dividing Range. Meanwhile, most of Great Artesian Basin and Murray-Darling Basin were significantly affected by 4 ∼ 6 ENSO indexes, which was effective in predicting summer rainfall extremes based on pre-occurred ENSO signals. Our findings provide insights for drought early warning, which are crucial for enhancing water usage and shaping the agricultural system to better adapt to climate extremes in Australia.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132834"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396238","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 hysteretic and gatekeeping depressions model − A new model for variable connected fractions of prairie basins","authors":"Kevin R. Shook,&nbsp;John W. Pomeroy","doi":"10.1016/j.jhydrol.2025.132821","DOIUrl":"10.1016/j.jhydrol.2025.132821","url":null,"abstract":"<div><div>The Prairie Pothole Region of western North America has unusual hydrology and hydrography. Its level, post-glacial topography means that many drainage basins are dominated by internally drained depressions, rather than having conventional dendritic drainage networks of stream channels. Modelling the hydrology of these regions is difficult because the relationship between depressional storage and the connected fraction of a basin is hysteretic. Existing models are either computationally intensive and require high-resolution Digital Elevation Model (DEM) data which may not exist or require calibration and cannot reproduce the hysteresis between the basin connected fraction and depressional storage. The Hysteretic and Gatekeeping Depressions Model (HGDM) has been developed to simplify modelling of prairie basins with variable connected/contributing fractions. The model uses “meta” depressions to model the hysteretic responses of small depressions and a discrete model of large depressions, which cause “gatekeeping”, meaning that they prevent upstream flows from reaching the outlet until the depressions are filled. The HGDM was added to the Cold Regions Hydrological Modelling (CRHM) platform which is one of the few models that has successfully simulated land surface hydrology in the Canadian Prairies. CRHM + HGDM is tested by modelling streamflows at Smith Creek, a basin in southeastern Saskatchewan, Canada. It is demonstrated that CRHM + HGDM can reproduce the relationship between the connected/contributing fractions of sub-basins and their depressional storage at least as well as existing models. Importantly, it appears that HGDM can be used with coarse-resolution DEMs, which may permit its use in the many locations where higher-resolution data is unavailable. The simplicity and limited parameterization needs of HGDM may allow for broader representation of depressions and variable contributing area in prairie hydrology.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132821"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395818","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":"A closed municipal landfill as a source of emerging contaminants in adjacent groundwater: pharmaceuticals and personal care products occurrence and environmental risk assessment","authors":"Kinga Ślósarczyk,&nbsp;Dominika Dąbrowska","doi":"10.1016/j.jhydrol.2025.132829","DOIUrl":"10.1016/j.jhydrol.2025.132829","url":null,"abstract":"<div><div>The aim of this study was to determine the occurrence and perform the environmental risk assessment (ERA) for emerging contaminants, primarily pharmaceuticals and personal care products (PPCPs), in the groundwater near a closed municipal landfill, on the example of a site in Tychy (southern Poland). Groundwater from a shallow aquifer was sampled in two seasons from eight piezometers located upstream, downstream, and on top of the landfill. The analysis covered 128 PPCPs. Additionally, surfactants, phenols, field parameters, and basic groundwater chemical composition were determined. ERA was performed using indices like the horizontal ratio (HR), risk quotient (RQ), frequency of a predicted no-effect concentration (PNEC) exceedance (F), prioritisation index (PI), and persistence-bioaccumulation-toxicity ranking (PBTr). The number of detected PPCPs in the groundwater reached up to 54, with total PPCP concentrations ranging from 492 to 3,230,036 ng/L. The study also revealed the presence of phenols (up to 62 mg/L) and surface active agents, particularly anionic surfactants (up to 77.7 mg/L). The highest concentrations of analysed compounds were observed in groundwater from a piezometer screened directly below the landfill bottom. The lowest values were recorded for the observation well located upstream of the landfill, confirming its negative impact and the release of PPCPs into the aquifer. The influence of the landfill was also reflected by low HR values (below 1) and high values of the site-specific risk quotient (above 1). Based on PI results, ibuprofen, bisphenol A, propyphenazone, and sulfamerazine were considered the compounds of highest risk. The same substances were among compounds with the highest PBTr values. The results showed that closed, unlined municipal landfills are a threat to groundwater in terms of organic micropollutants due to conditions that favour their persistence in the aquifer, and that concentrations of some contaminants still pose an environmental risk.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132829"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395825","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":"Performance evaluation of convolutional neural network and vision transformer models for groundwater potential mapping","authors":"Behnam Sadeghi ,&nbsp;Ali Asghar Alesheikh ,&nbsp;Ali Jafari ,&nbsp;Fatemeh Rezaie","doi":"10.1016/j.jhydrol.2025.132840","DOIUrl":"10.1016/j.jhydrol.2025.132840","url":null,"abstract":"<div><div>Due to excessive consumption and the increasing warming of the earth’s air, the level of groundwater in the world is decreasing, especially in arid and semi-arid countries that need water supply for various purposes from these sources. In this study, the data of 3546 wells and 15 spatial factors influencing the occurrence of groundwater, elevation, slope, plan curvature, profile curvature, terrain wetness index (TWI), valley depth, slope length (LS), river density, distance from river, distance from fault, geology, land cover, aspect, normalized difference vegetation index (NDVI), and rainfall have been used for modeling and groundwater potential mapping (GWPM). In the feature selection process, the wrapper base method, Boruta-XGBoost, and the variance inflation factor (VIF) test were used, and all factors except LS were confirmed and entered into the model. Convolutional neural network (CNN) and vision transformer (VIT) were used as learning models for Chaharmahal Bakhtiari province, one of Iran’s mountainous provinces. The area under receiver operating characteristic curve (AUC), root mean square error (RMSE), and some statistical metrics such as precision, recall and F1-score have been used for model validation. According to the obtained results, the VIT model is the most efficient with an AUC of 0.8530, RMSE (0.3900), precision (0.7740), recall (0.7600), and F1-score (0.7610) which gives the most promising values model, than the CNN model with an AUC of 0.8370, RMSE (0.4100), precision (0.7650), recall (0.7550) and F1-score (0.7560). These results show the appropriate power of both models in modeling and the relative superiority of the VIT method. Finally, the SHapley Additive exPlanations (SHAP) method was used to enhance model explainability. SHAP analysis highlighted land cover, rainfall, and geology as the most important factors in this study. Preparing the groundwater potential map helps managers and decision-makers manage these resources’ consumption and use the potential of groundwater as one of the practical criteria for allocating land use.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132840"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379205","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":"Groundwater–surface water exchange affects nitrate fate in a seasonal freeze–thaw watershed: Sources, migration and removal","authors":"Jiamei Wang ,&nbsp;Xin Hao ,&nbsp;Xinyi Liu ,&nbsp;Wei Ouyang ,&nbsp;Tianzhi Li ,&nbsp;Xintong Cui ,&nbsp;Jietong Pei ,&nbsp;Shangwei Zhang ,&nbsp;Weihong Zhu ,&nbsp;Ri Jin","doi":"10.1016/j.jhydrol.2025.132803","DOIUrl":"10.1016/j.jhydrol.2025.132803","url":null,"abstract":"<div><div>The interaction between groundwater and surface water (GW–SW) affects the hydrogeochemical cycle, leading to changes in nitrate sources, migration, and transformation within watersheds. Seasonal freeze–thaw cycles also complicate the above processes. This study employed hydrochemistry, stable isotope analysis, and statistical methods to investigate the dynamic characteristics of GW–SW exchange in a seasonal freeze–thaw watershed, identify the conversion intensities during different periods, and elucidate potential nitrate sources and their relative biogeochemical processes. GW and SW were replenished primarily by atmospheric precipitation, which switched to snowmelt water during the thawing period. Recharge sources and aquifer lithology controlled the seasonal variation in GW–SW exchange. From upstream to downstream, the conversion intensity ranges of SW loss into GW during the wet period were 54.6%, 32.7–55.5%, and 26.5–37.4%, respectively. The percentages of streams that gained GW during the dry period were 62.2–83.7%, 47.1–62.0%, and 35.2–46.0%, respectively. The primary sources of nitrate in GW and SW were fertilizers and livestock waste, with their contributions exhibiting seasonal variations with GW–SW interactions. Agricultural activities and livestock breeding led to high nitrate contents in groundwater, with manure and sewage accounting for up to 90% of the nitrate content during the dry period. Notably, GW–SW interactions during the wet and dry seasons enhanced the denitrification process, contributing to nitrate removal in groundwater. This study revealed that GW–SW interactions significantly impact the fate of nitrate in watersheds and the influence of human activities on watershed environments, providing technical support for watershed water resource management and diffuse pollution control.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132803"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379217","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":"Improved ALT retrieval in the Yellow River source region using time-series InSAR and multilayer soil moisture modeling","authors":"Zhengjia Zhang ,&nbsp;Qingguang Jin ,&nbsp;Lin Liu ,&nbsp;Mengmeng Wang ,&nbsp;Xuefei Zhang","doi":"10.1016/j.jhydrol.2025.132847","DOIUrl":"10.1016/j.jhydrol.2025.132847","url":null,"abstract":"<div><div>Ongoing climate warming and increased human activities have led to significant permafrost degradation on the Qinghai-Tibet Plateau (QTP). Mapping the distribution of active layer thickness (ALT) can provide essential information for understanding this degradation. Over the past decade, InSAR (Interferometric synthetic aperture radar) technology has been utilized to estimate ALT based on remotely-sensed surface deformation information. However, these methods are generally limited by their ability to accurate extract seasonal deformation and model subsurface water content of active layer. In this paper, an ALT inversion method considering both seasonal deformation from InSAR and smoothly multilayer soil moisture from ERA5 is proposed. Firstly, we introduce a ground seasonal deformation extraction model combining RobustSTL and InSAR, and the deformation extraction accuracy by considering the deformation characteristics of permafrost are evaluated, proving the effectiveness of RobustSTL in extracting seasonal deformation of permafrost. Then, using ERA5 soil moisture products, a smoothed multilayer soil moisture model for ALT inversion is established. Finally, integrating the seasonal deformation and multilayer soil moisture, the ALT can be estimated. The proposed model is applied to the Yellow River source region (YRSR) with Sentinel-1A images acquired from 2017 to 2021, and the ALT retrieval accuracy is validated with measured data. Experimental results show that the vertical deformation rate of the study area generally ranges from −30 mm/year to 20 mm/year, with seasonal deformation amplitude ranging from 2 mm to 30 mm. The RobustSTL method has the highest accuracy in extracting seasonal deformation of permafrost, with an RMSE (root mean square error) of 0.69 mm, and is capable of capturing the freeze–thaw characteristics of the active layer. The estimated ALT of the YRSR ranges from 49 cm to 450 cm, with an average value of 145 cm. Compared to the measured data, the proposed method has an average error of 37.5 cm, which represents a 21 % improvement in accuracy over existing methods.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132847"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143379208","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":"Measurement and modeling of canopy interception loss of evergreen, deciduous and mixed forests in a subhumid watershed on the Loess Plateau, China","authors":"Jiongchang Zhao ,&nbsp;Yang Yu ,&nbsp;Yawei Hu ,&nbsp;Matthias Beyer ,&nbsp;Jianjun Zhang","doi":"10.1016/j.jhydrol.2025.132820","DOIUrl":"10.1016/j.jhydrol.2025.132820","url":null,"abstract":"<div><div>Canopy interception, a significant yet inadequately comprehended hydrological phenomenon in terrestrial ecosystems, plays a crucial role in the water balance of forests. A profound understanding of the water retained and re-evaporated through interception storage is essential for developing a comprehensive understanding of forest hydrology. Integration this knowledge into hydrological models can help assess the effects of climate change on forests. In the Loess Plateau of China, extensive ecological restoration measures have been implemented to mitigate severe soil erosion and restore the fragile ecological environment. However, few studies have investigated the role of canopy interception in different tree species compositions (planted monoculture forests and mixed forests). This study monitored precipitation, throughfall, stemflow, and estimated canopy interception in three different forest stands during the 2021–2022 growing season in Shanxi Province, China. Canopy interception was quantified and simulated using the revised Gash model. The observed throughfall, stemflow and canopy interception for deciduous forest were 81.5 %, 1.6 % and 16.9 %, for evergreen forest were 84.2 %, 1.4 % and 14.4 %, respectively. The corresponding values for the mixed forest were 80.7 %, 2.0 % and 17.3 %. The revised model underestimated canopy interception to varying degrees in all three forest types, with the deciduous forest by 11.2 ± 1.8 %, evergreen forests by 21.1 ± 5.5 %, and mixed forest underestimating by, 16.7 ± 3.2 %. According to the statistical parameters (mean absolute error, mean bias error, root mean square error and Nash-Sutcliffe efficiency), the revised model can simulate the canopy interception dynamics of three forest types, with the best performance in simulating the deciduous forest, followed by mixed forest and evergreen forest. The study found that canopy interception loss was significantly influenced by a combination of canopy characteristics (including canopy storage capacity, canopy cover fraction, trunk storage capacity, and the percentage of precipitation diverted into stemflow) and climatic variables (such as average precipitation intensity and average evaporation rate). Among these factors, average precipitation intensity and canopy storage capacity were identified as the most influential variables across all three examined stands. Overall, the revised model was suitable for typical plantation forests and their mixed forests on Loess Plateau. Our study has important implications for understanding of the forest water balance in the Loess Plateau and also contributes to precipitation partitioning forecasts and efficient water resource management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132820"},"PeriodicalIF":5.9,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419515","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}