Journal of Hydrology最新文献

{"title":"The propagation from atmospheric flash drought to soil flash drought and its changes in a warmer climate","authors":"Feng Ma ,&nbsp;Xing Yuan","doi":"10.1016/j.jhydrol.2025.132877","DOIUrl":"10.1016/j.jhydrol.2025.132877","url":null,"abstract":"<div><div>Soil flash droughts (SFDs), characterized by a rapid decline in soil moisture during drought onset, occurred frequently in recent decades and raised great challenges to drought monitoring and forecasting. Similar to traditionally slow-developing droughts, SFDs could originate from atmospheric droughts, but whether there is a connection between atmospheric flash droughts (AFDs) and SFDs remains unexplored. In this study, we identified AFDs and SFDs using 15-day mean vapor pressure deficit (VPD) and 5-day mean soil moisture (SM) respectively, and examined their occurrence frequency and propagation relationships during the growing seasons over global vegetated lands. Results show that the frequency of AFDs displays minor regional differences while SFDs are more frequent in humid regions. The global mean fractions of AFDs that trigger SFDs and SFDs that follow AFDs are 15 % and 31 % respectively, with significant spatial variability. Semi-humid and humid regions show higher propagation relationships between AFDs and SFDs. Antecedent SM conditions play critical roles in the propagation from AFDs to SFDs. Medium antecedent SM conditions (∼52nd percentile) accompanied by significantly elevated evapotranspiration (ET) at the onset of AFDs favor the occurrence of SFDs. High (∼69th percentile) and low (∼26th percentile) SM conditions limit the propagation from AFDs to SFDs. In a warmer future, the occurrence of AFDs is projected to increase globally, with a mean increase rate of 52.7 ± 4.27 % under a moderate emission scenario. The SFDs are projected to increase by 15.4 ± 7.03 %, with a larger increase in semi-humid and humid regions. The fraction of SFDs that follow AFDs is projected to increase by 33.33 ± 2.97 %, indicating a stronger link between SFDs and AFDs in a warmer climate. These findings improve our knowledge in the complicated propagation relationship between AFDs and SFDs and imply the urgency for adapting to flash droughts under climate warming.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132877"},"PeriodicalIF":5.9,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating rainfall severity and soil saturation indices to define hydro-meteorological thresholds for landslides","authors":"Sen Zhang ,&nbsp;Gaetano Pecoraro ,&nbsp;Da Huang ,&nbsp;Jianbing Peng ,&nbsp;Michele Calvello","doi":"10.1016/j.jhydrol.2025.132873","DOIUrl":"10.1016/j.jhydrol.2025.132873","url":null,"abstract":"<div><div>Rainfall thresholds identifying the meteorological conditions critical for landslides triggering are widely used within operational territorial landslide early warning systems (Te-LEWS). Recent studies demonstrated that hydro-meteorological thresholds, combining soil hydrological information and rainfall, can improve the prediction of landslide occurrences at territorial scale. Soil moisture is predominantly used to characterize the soil wetness conditions that predispose slopes to failure. In this study, we develop hydro-meteorological thresholds by investigating the potential use of both antecedent (i.e., before the beginning of the rainfall event) and triggering (i.e., during the rainfall event) saturation variables derived from a reanalysis product. A procedure based on a Bayesian probabilistic analysis of rainfall severity and soil saturation indices is designed and tested in an area of Campania region, southern Italy. Different hydro-meteorological thresholds demonstrate a good predictive capability, with those considering maximum saturation at the uppermost soil layer performing best. Overall, this study proves that hydro-meteorological thresholds employing antecedent and triggering saturation variables derived by time series analysis can improve the prediction of landslide occurrences at territorial scale.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132873"},"PeriodicalIF":5.9,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143446025","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":"An enhanced framework for simulating urban pluvial flooding: Integrating nested watersheds and urban areas with spatial heterogeneity","authors":"Chenlei Ye ,&nbsp;Weihong Liao ,&nbsp;Zongxue Xu ,&nbsp;Xiaoyan Li ,&nbsp;Xinyi Shu","doi":"10.1016/j.jhydrol.2025.132875","DOIUrl":"10.1016/j.jhydrol.2025.132875","url":null,"abstract":"<div><div>Urban pluvial flooding caused by rainstorms has become an increasingly threat to urban safety due to climate change and rapid urbanization. Coupled hydrological-hydrodynamic models are now widely used for urban flood simulations, enabling improved pluvial flood forecasting. However, existing research often focuses mainly on modeling urbanized surfaces, overlooking the heterogeneity within different functional zones of urban underlying surfaces. Additionally, most simulations treat urban areas in isolation, failing to incorporate upstream basins in a nested framework with the urban environment. This simplification can lead to an incomplete characterization of urban hydrological features and neglect the hydrological connectivity between catchments and urban areas. This research aims to develop a framework Hybrid Heterogeneous Urban-Catchment Flooding Model (HHUCFM) for simulating urban pluvial flooding that incorporates the heterogeneity of underlying surfaces and nested basin runoff modeling, and introduces a lightweight, semi-distributed hydrological model as a surrogate model for urban upstream basin scale. The framework consists of three main components: (1) optimization and uncertainty analysis of heterogeneous parameters based on urban functional zoning and heuristic algorithms; (2) the semi-distributed model FLOWS-Tank, which integrates 4 layers of series–parallel tanks and 2 nonlinear reservoirs to construct differential equation-based control equations, to connect runoff from upstream basins; and (3) a multi-process physically-based urban flood simulation approach incorporating FLOWS-Tank. HHUCFM was applied in Jinan, and the accuracy was validated through observed floods, identifying overflow nodes and surface inundation. The results reveal: First, incorporating zoning-based hydrological characteristics in areas with diverse underlying surfaces, critically highly urbanized, mountainous, and suburban zones, significantly enhances runoff prediction, as evidenced by improved Nash-Sutcliffe efficiency coefficient and increased interpretability of spatially heterogeneous parameters. Second, the proposed framework HHUCFM embedded with FLOWS-Tank, was successfully applied to the study area with hydrologically connected upstream basins and urban zones, demonstrating strong generalizability and interpretability in pluvial flooding simulation in urban scale. The current research provides valuable insights for analyzing urban flooding in regions with typical underlying surface heterogeneity.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132875"},"PeriodicalIF":5.9,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465093","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":"Hydrogeological and hydrochemical processes affecting groundwater quality on volcanic islands: Insights from El Hierro (Canary Islands, Spain)","authors":"Miguel Ángel Marazuela ,&nbsp;Jon Jiménez ,&nbsp;Carlos Baquedano ,&nbsp;Jorge Martínez-León ,&nbsp;Samanta Gasco-Cavero ,&nbsp;Noelia Cruz-Pérez ,&nbsp;Juan Carlos Santamarta ,&nbsp;Alejandro García-Gil","doi":"10.1016/j.jhydrol.2025.132874","DOIUrl":"10.1016/j.jhydrol.2025.132874","url":null,"abstract":"<div><div>Groundwater resources on volcanic islands are vital for societal and economic development, especially due to their scarcity and reliance on agriculture and tourism. This study examines the hydrogeological and hydrochemical processes shaping groundwater quality on volcanic islands, focusing on <em>El Hierro</em> Island (Canary Islands, Spain). The findings reveal that volcanic dykes play a critical role in controlling groundwater flow, creating freshwater reservoirs, and influencing flow paths. Four primary processes affecting groundwater quality are identified: seawater intrusion, volcanic CO₂ emissions, nitrate contamination from fertilizers, and CO₂-driven water–rock interactions. A 3D groundwater flow model shows that the anisotropy in hydraulic conductivity induced by volcanic dykes reduces seawater intrusion in specific areas, thereby protecting groundwater quality. Volcanic CO₂ emissions are found to lower pH, increasing acidity and altering groundwater chemistry. CO₂-driven water–rock interactions result in the dissolution of basaltic minerals, raising concentrations of key rock-forming elements such as sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), and silica (SiO₂) in groundwater. Additionally, nitrate pollution is linked to fertilizer use, particularly in agricultural regions. These insights highlight the need for sustainable water management to address the challenges posed by salinization, pollution, and volcanic activity. This research not only advances understanding of <em>El Hierro</em>’s groundwater system but also offers a framework applicable to other volcanic islands with similar hydrogeological conditions, supporting improved management strategies for freshwater resources.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132874"},"PeriodicalIF":5.9,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437742","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":"CHiRAD: A high-resolution daily net radiation dataset for China generated using meteorological and albedo data","authors":"Ye Jing ,&nbsp;Peng Bai ,&nbsp;Zelong Yang","doi":"10.1016/j.jhydrol.2025.132854","DOIUrl":"10.1016/j.jhydrol.2025.132854","url":null,"abstract":"<div><div>Surface net radiation (R_n) is a key variable for studying the energy available at the Earth’s surface, essential in atmospheric, water, and carbon cycle research. Despite the existence of global R_n products, they often encounter issues such as data gaps, low resolution, and significant uncertainty. In this study, we developed a high spatial resolution (0.05°×0.05°) daily R_n dataset for China from 2000 to 2019 using routine meteorological data and remotely sensed albedo. To ensure the reliability of the dataset, we tested various net shortwave and longwave algorithms with ground-based measurements and selected an optimal combination to generate this dataset (hereafter named CHiRAD). Validation against R_n observations from 43 flux towers across China demonstrated the remarkable accuracy of CHiRAD, with a Kling Gupta efficiency (KGE) of 0.81, a percentage of bias (Pbias) of 0.38 %, and a root mean square error (RMSE) of 37.10 W m⁻2. CHiRAD outperforms two commonly used R_n products: ERA5-Land (KGE = 0.73, Pbias = -7.81 %, RMSE = 41.24 W m⁻²) and GLASS-AVHRR (KGE = 0.73, Pbias = 1.92 %, RMSE = 36.76 W m⁻²). This dataset, available at <span><span><u>https://doi.org/10.5281/zenodo.12605405</u></span><svg><path></path></svg></span>, offers valuable input for various land surface and hydrological models, with broad application in hydrology, climatology, ecology, and other related fields.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132854"},"PeriodicalIF":5.9,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143452990","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":"Introducing time series features based dynamic weights estimation framework for hydrologic forecast merging","authors":"Md Rasel Sheikh ,&nbsp;Paulin Coulibaly","doi":"10.1016/j.jhydrol.2025.132872","DOIUrl":"10.1016/j.jhydrol.2025.132872","url":null,"abstract":"<div><div>Accurate and reliable hydrologic forecasting through multi-model ensemble averaging is crucial for reducing uncertainty, which aids in effective water resources management and flood risk mitigation. This study addresses the research gap of the limited application of time-varying weights in hydrologic forecast merging, as existing methods rely on weights that do not adapt to changes in model performance over time. We propose a novel framework utilizing time series features (TSFs) of daily streamflow and Bayesian model averaging (BMA) to dynamically adjust merging weights, referred to as TSF-Ws. The methodology involves generating ensemble forecasts, adjusting weights dynamically using TSFs, and comparing the accuracy of these forecasts with traditional streamflow-based weights, referred to as Q-Ws, merging across different forecast horizons. The results demonstrate that TSF-Ws significantly improve forecast performance, particularly for longer lead times, indicating more accurate and reliable deterministic and probabilistic forecasts. Moreover, TSF-Ws based merging achieves higher performance than Q-Ws for deterministic high and low flow forecasts. Furthermore, this newly developed approach reduces the uncertainty bound for probabilistic peak flow predictions. Overall, the proposed TSF-Ws estimation framework can serve as a robust tool for enhancing hydrologic forecast merging, providing significant improvements in accuracy and reliability over traditional methods. These improvements have important implications for water resource management and flood risk assessment.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132872"},"PeriodicalIF":5.9,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428191","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":"Understanding the linkages between seasonal variability and annual trends in groundwater levels in alluvial aquifers of Uttar Pradesh, India","authors":"Om Jee,&nbsp;Lalit Kumar Choudhary,&nbsp;Mayank Katiyar,&nbsp;Tushar Apurv","doi":"10.1016/j.jhydrol.2025.132858","DOIUrl":"10.1016/j.jhydrol.2025.132858","url":null,"abstract":"<div><div>In this study, we analyse the seasonal variability of groundwater table depths (GWTDs) to understand the drivers of annual groundwater trends in the state of Uttar Pradesh (UP), which has the largest groundwater withdrawal in India. We perform the analysis using observations of GWTDs in wells located in shallow aquifers during 2001–2019 without excluding wells with missing observations. We find higher seasonal variability of GWTD in southeast UP as compared to northwest UP due to higher groundwater recharge during monsoon. While there is significant groundwater withdrawal for irrigation in the dry season in both regions, it exceeds the monsoon recharge in northwest UP leading to an increasing trend in GWTD in the region. The groundwater depletion in shallow aquifers of northwest UP has led to a decrease in the number of shallow tubewells and a sharp increase in the number of deep tubewells in the region. There is a smaller increase in GWTDs in southeast UP as compared to northwest UP, as the groundwater abstraction in the non-monsoon season has been balanced by the high recharge received during monsoon. However, there has been a rapid increase in the number of both shallow and deep tubewells in southeast UP, which could accelerate groundwater depletion in the future. We also find that the wells with missing observations have a significant contribution to the depletion trend observed in northwest UP which highlights the importance of incorporating information from wells with missing observations in groundwater assessment studies.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132858"},"PeriodicalIF":5.9,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-stable isotope tracing of elevated sulfate export from a forested headwater wetland following an induced flood pulse event","authors":"David W. O’Connell ,&nbsp;Paul Coulson ,&nbsp;Feridoun Rezanezhad ,&nbsp;Angela Mills ,&nbsp;Ana T. Lima ,&nbsp;Alexander G.J. Driedger ,&nbsp;Hans H. Dürr ,&nbsp;Merrin Macrae ,&nbsp;Richard Elgood ,&nbsp;Chris T. Parsons ,&nbsp;Andre Roy ,&nbsp;Sherry Schiff ,&nbsp;Philippe Van Cappellen","doi":"10.1016/j.jhydrol.2025.132824","DOIUrl":"10.1016/j.jhydrol.2025.132824","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Headwater wetlands are significant in the conservation of water and water quality for downstream aquatic ecosystems. During flooding events following periods of drought in many headwater wetlands, significant quantities of sulfate (SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt;) can be exported which impacts downstream surface water quality. Such periodic flood pulses of SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; are rarely studied in detail but are a suggested cause of prolonged freshwater eutrophication. Flood pulsing events are exacerbated by the increasing severity and frequency of summer droughts along with episodic flooding. Specifically, many wetlands are fed by water from upstream reservoirs which can control wetland-stream and groundwater-surface water interactions that can impact downstream water quality. In this study, an induced flood pulse event of a forested wetland (Beverly Swamp) was arranged by scheduling an upstream reservoir drawdown event (Valens Reservoir). This orchestrated flooding event exhibited a seven-fold increase (38 to 270 mg L&lt;sup&gt;-1&lt;/sup&gt;) in surface water SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; concentrations discharging from the wetland. To elucidate the source and release time lag of these elevated SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; concentrations, high resolution surface water sampling and discharge monitoring were coupled with stable isotopes of S (δ&lt;sup&gt;34&lt;/sup&gt;S-SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt;) and water (δ&lt;sup&gt;18&lt;/sup&gt;O-H&lt;sub&gt;2&lt;/sub&gt;O and δ&lt;sup&gt;2&lt;/sup&gt;H-H&lt;sub&gt;2&lt;/sub&gt;O) along with scanning electron microscopy (SEM) analysis of the peat samples. Following the flood, a considerable increase in surface water SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; concentrations was observed at sampling locations with decreases in δ&lt;sup&gt;34&lt;/sup&gt;S-SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; values which is characteristic of oxidation following dissimilatory sulfate reduction (DSR). This indicates prior DSR resulted in the precipitation of mineral sulphides in the upper peat layers. During the pre-flood drought period, sulphides were re-oxidised to SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; and flushed from the wetland during flooding. δ&lt;sup&gt;18&lt;/sup&gt;O-H&lt;sub&gt;2&lt;/sub&gt;O values of surface and sub-surface peat soil waters reflected the horizontal and vertical travel time of reservoir water flooding the wetland and flushing SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; from the system. Surface water acidity increased shortly after the SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; pulse, but within a short time rebounded due to carbonate buffering capacity within the peat. A conceptual model of the SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; budget indicated ∼ 68.7 kg SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; ha&lt;sup&gt;−1&lt;/sup&gt; d&lt;sup&gt;-1&lt;/sup&gt; was released from Beverly Swamp during the post flood period. This study shows that Beverly Swamp contains significant stores of reduced sulfur (S), including iron sulfides. These reduced S stores will sustain recurrent release of particularly large quantities of SO&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;2-&lt;/sup&gt; through redox cycling to the downstream littoral wetlands of Lake","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132824"},"PeriodicalIF":5.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465092","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":"Deep learning model for drought prediction based on large-scale spatial causal network in the Yangtze River Basin","authors":"Huihui Dai ,&nbsp;Lihua Xiong ,&nbsp;Qiumei Ma ,&nbsp;Zheng Duan","doi":"10.1016/j.jhydrol.2025.132808","DOIUrl":"10.1016/j.jhydrol.2025.132808","url":null,"abstract":"<div><div>Developing accurate large-scale drought prediction models is challenging due to the complex temporal and spatial correlation patterns that govern drought dynamics, as well as the compounding effects of anthropogenic activities and global climate change. Although recent advances in deep learning have yielded effective drought prediction models, many struggle to fully capture the heterogeneous spatial linkages over large-scale regions. In this study, we proposed a novel large-scale drought prediction framework that considers spatial heterogeneity and leverages a causal network connecting regions delineated by drought centroids of severe agricultural events identified through dynamic drought analysis. Using the predefined causal network, we employed the state-of-the-art deep learning algorithm, the Spatio-Temporal Graph Convolutional Networks (STGCN) model, with a recursive multi-step forecasting strategy to predict root-zone soil moisture (RZSM) -based drought indices (DIs) up to four weeks in advance for the Yangtze River Basin (YRB). The results show that compared to the meteorological drought events, the corresponding agricultural drought has a later onset and smaller affected areas, yet greater intensity. The proposed model demonstrated robust predictive performance in drought predictions with an average root mean square error (RMSE) of 0.45 and an R2 value of 0.66 across the YRB for the spatial weekly agricultural DIs on the test dataset. Applying the STGCN with the recursive multi-step forecasting strategy can significantly improve the prediction performance, improving R2 values by 0.15 and reducing RMSE by 0.1 on average, with the most substantial improvements observed during the first three weeks (R2 increases of 0.32, 0.24 and 0.09, respectively). These findings underscore the importance of incorporating spatial correlations and demonstrate the advantages of the STGCN approach for large-scale agricultural drought prediction and inform water resource management at large-scale watersheds.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132808"},"PeriodicalIF":5.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445866","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 individual tree stemflow model integrating branch-leaf cluster structure and drainage processes from multi-platform LiDAR scanning","authors":"Yupan Zhang ,&nbsp;Yiliu Tan ,&nbsp;Chenwei Chiu ,&nbsp;Yuichi Onda ,&nbsp;Takashi Gomi","doi":"10.1016/j.jhydrol.2025.132838","DOIUrl":"10.1016/j.jhydrol.2025.132838","url":null,"abstract":"<div><div>Stemflow (<span><math><mrow><mi>SF</mi></mrow></math></span>) is essential for directing and concentrating intercepted water and nutrients from the canopy layer to the forest soil and root systems. Stemflow generation results from a complex series of dynamic interactions and is influenced more by plant structure than by meteorological conditions. However, there is still a gap in research on modeling stemflow using canopy structure. Investigating the roles and importance of structural metrics of individual canopy branches and leaves will contribute to our understanding of stemflow dynamics. In this study, we fused drones and terrestrial light detection and ranging (LiDAR) scanning to reconstruct the multilayered structures of three Japanese cypress trees. Using the point-cloud data, visible branches were fitted using line segments, whereas invisible branches within the canopy were estimated using a tree-form coefficient. Finally, the branch angles, lengths, and leaf cluster volumes were extracted for all branches to represent canopy information. The average branch number, inclination, length, and leaf volume were 81, 76.83°, 0.606 m, and 0.89 m³/m², respectively. Innovatively, we computed the connectivity between each branch and stem and introduced a physical runoff model to simulate stemflow production for individual leaf clusters after branch funneling. Compared with four years of observational data, our model achieved acceptable accuracy, with an R² = 0.6. Our research integrated a fine-scale architectural structure with canopy metrics influencing stemflow by employing physical models to elucidate the discrepancies in stem-scale stemflow yields. Our approach helps to gain a better<!--> <!-->understanding of the effect of canopy on forest hydrology and biogeochemical processes.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"654 ","pages":"Article 132838"},"PeriodicalIF":5.9,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419568","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}