Journal of Hydrology最新文献

{"title":"Vertical sediment stratification regulates dissolved nutrient dynamics and interface fluxes along the intertidal zone","authors":"Zhenyang Li ,&nbsp;Yueqi Wang ,&nbsp;Yashu Qi ,&nbsp;Kai Xiao ,&nbsp;Guangxuan Han ,&nbsp;Hailong Li ,&nbsp;Liang Liu ,&nbsp;Dejuan Jiang ,&nbsp;Xiaoying Zhang ,&nbsp;Chunmiao Zheng","doi":"10.1016/j.jhydrol.2026.134980","DOIUrl":"10.1016/j.jhydrol.2026.134980","url":null,"abstract":"<div><div>Sediment stratification is a ubiquitous feature in intertidal aquifers, yet its precise role in regulating dissolved nutrient dynamics remains poorly understood. This study examined two typical kinds of intertidal transects including the sandy beach and mudflat, each exhibiting distinct sediment stratification. We analyzed the multi-depth distribution patterns of dissolved nutrients (nitrogen, phosphorus, and silicon) and carbon in intertidal groundwater. We also identified the key drivers using stable isotope tracers (δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻) and multivariate statistics, and quantified the interface fluxes to the coastal ocean. The findings indicated that the distribution patterns of nutrients and carbon between fine- and coarse-grained sediments in both transects were synthetically influenced by hydrological dynamics and biogeochemical reactions. In the sandy beach, groundwater composition transitioned from being NO₃⁻-dominated in the deep coarse-grained sediments, where attenuation occurred via denitrification, to NH₄⁺-dominated in the surface fine-grained sediments due to organic matter mineralization. In the mudflat, organic-rich sediments and low water exchange rates favored NH₄⁺ dominance, with fine-grained sediments accumulating high concentrations of NH₄⁺, PO₄³⁻, and DSi in groundwater. Moreover, the sandy beach served as hotspots for groundwater discharge, delivering nutrient and dissolved carbon fluxes up to two orders of magnitude higher than the mudflat. The presence of a surface fine-grained sediments enhanced the export of groundwater-derived NH₄⁺ and DIC, potentially exacerbating coastal eutrophication and acidification. These findings demonstrate that sediment stratification fundamentally alters the composition and flux magnitude of nutrients and carbon discharged into coastal waters, thereby influencing coastal solute budgets.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134980"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146001372","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":"Retrieval of snow depth using synthetic aperture radar: past, current, and future","authors":"Zhen Li ,&nbsp;Haiwei Qiao ,&nbsp;Ping Zhang ,&nbsp;Yanan Bai ,&nbsp;Huadong Hu","doi":"10.1016/j.jhydrol.2026.135103","DOIUrl":"10.1016/j.jhydrol.2026.135103","url":null,"abstract":"<div><div>Snow is one of the most dynamic factors in the climate system. In recent years, as climate change has intensified, the distribution of the global snow cover and the timing of snowmelt have changed, seriously affecting the hydrological cycle, ecosystems, carbon balance, and human activities. Snow depth, as a key parameter for measuring snow changes, plays a crucial role in water storage estimation, disaster prediction, and research on global sustainability. Considering the limited spatial representativeness of ground observations and the insufficient spatial resolution of passive microwave remote sensing, synthetic aperture radar (SAR) offers a viable solution for the superior precision and fine-scale retrieval of spatiotemporally continuous snow depth. This paper begins with the interaction between SAR signals and snow, reviewing different types of snow backscattering models and surface scattering models. Then, the SAR data for snow depth retrieval are outlined. Thirdly, snow depth retrieval methods based on polarimetric SAR (PolSAR), interferometric SAR (InSAR), polarimetric interferometric SAR (PolInSAR), and tomographic SAR (TomoSAR) techniques in the last two decades are summarized. Finally, the current opportunities and challenges are envisioned to provide reliable references for future studies.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135103"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146138399","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":"Imputation of continuous missing values in water quality data using a temporal embedding-based self-attention variational autoencoder","authors":"Xinghan Xu ,&nbsp;Lei Hu ,&nbsp;Xingyi Miao ,&nbsp;Peng Xiao ,&nbsp;Xiaohui Yan ,&nbsp;Jianwei Liu","doi":"10.1016/j.jhydrol.2026.134937","DOIUrl":"10.1016/j.jhydrol.2026.134937","url":null,"abstract":"<div><div>Missing values in water quality data (WQD), caused by sensor malfunctions, communication failures, and environmental disturbances, undermine the reliability of conventional imputation methods. To address these challenges, we propose the Temporal Embedding-based Self-Attention t-distributed Variational Autoencoder (TE-SAVAE-St), a model designed for robust and temporally consistent data reconstruction. The model incorporates a Student’s-t prior to handle outliers, temporal embeddings (TE) to capture chronological patterns, and multi-head self-attention (MSA) to model long-term dependencies and inter-variable correlations. Extensive experiments on real-world WQD datasets show that TE-SAVAE-St outperforms ten baseline methods under various missing data scenarios, reducing RMSE by 11.8% and SMAPE by 23.6% compared to state-of-the-art models. Ablation studies confirm the complementary benefits of TE, MSA, and Student’s-t components. Additionally, time complexity analysis demonstrates that TE-SAVAE-St achieves an optimal balance between computational efficiency and imputation accuracy, making it suitable for real-time and large-scale monitoring applications. Overall, TE-SAVAE-St offers a domain-aware framework for the accurate reconstruction of incomplete WQD, supporting continuous environmental monitoring.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134937"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957165","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 impact of rainfall characteristics on combined sewer overflows in wet weather","authors":"Hao Wang ,&nbsp;Zijian Wang ,&nbsp;Pengfei Zeng ,&nbsp;Zilong Liu ,&nbsp;Bin Chen ,&nbsp;Jinjun Zhou","doi":"10.1016/j.jhydrol.2026.134951","DOIUrl":"10.1016/j.jhydrol.2026.134951","url":null,"abstract":"<div><div>Combined sewer overflows (CSO) pose risks to both water quality and public health. However, the impact of varying rainfall characteristics on CSO remains unclear. This study aims to assess and analyze the correlations between CSO and rainfall characteristics, specifically rainfall depth, duration, and the proportion of rainfall occurring during peak periods. The objective is to identify and elucidate the impacts of each main rainfall characteristic on the frequency of CSO. To conduct this analysis, rainfall data spanning 71 years were divided into 1,435 rainfall events and categorized into five representative rainfall patterns based on their temporal distribution. A hydraulic model of sewer network was employed to simulate the CSO results under different rainfall patterns. An indicator termed “rainfall-CSO contribution rate” was introduced to reflect the impact of rainfall on CSO. The neural network method was utilized to establish a relationship model between rainfall characteristics and rainfall-CSO contribution rate (R² &gt; 0.94). Sensitivity analysis and model visualization techniques were used to reveal the relationship between rainfall characteristics and rainfall-CSO contribution rate. Significant differences in contribution rates across rainfall patterns were observed (p = 0.012), indicating a strong association with rainfall characteristics. Specifically, rainfall patterns with a higher proportion of peak period precipitation correspond to greater CSO contribution rates. Within each rainfall pattern, rainfall depth was identified as the most critical factor affecting the CSO contribution rate, followed by rainfall duration, with average sensitivity indices of 0.580 and 0.274, respectively. The peak-period rainfall ratio had a minimal impact on the results, with an average sensitivity index of just 0.024. Furthermore, the study noted that, variations in CSO contribution rates across different patterns intensified with increasing rainfall depth, while the impact of rainfall duration diminished with longer durations. This research provides a methodical approach for quantitatively analyzing the relationship between rainfall characteristics and CSO contribution rates, facilitating rapid assessments of CSO conditions and informing urban planning and drainage management decisions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134951"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957292","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":"Towards cooperation on transboundary rivers: achieving a win–win balance between upstream hydropower generation and downstream water demand under climate change","authors":"Tesfalem Abraham ,&nbsp;Tunde Olarinoye ,&nbsp;Andreas Hartmann ,&nbsp;Harrie-Jan Hendricks Franssen ,&nbsp;Yan Liu","doi":"10.1016/j.jhydrol.2026.135111","DOIUrl":"10.1016/j.jhydrol.2026.135111","url":null,"abstract":"<div><div>Transboundary river management is critical for international relations, sustainable energy development, and ecosystem management. Hydropower development, while meeting downstream water demand, is crucial for fostering cooperation among countries sharing water resources. However, addressing this challenge under the context of climate change poses significant complexities. This study investigates the cooperation regarding hydropower production and water releases under the potential impact of climate change. We project future streamflow by the calibrated HBV hydrological model in three transboundary rivers originating from Ethiopia: the Upper Blue Nile (UBN), Omo, and Tekeze rivers. Subsequently, we compute the hydropower potential (maximum hydropower energy within a specific period) by optimizing water release policies using the adapted ’Reservoir’ R package. The hydropower potential and water release are analyzed based on 11 scenarios of water releases ranging from favoring the upstream country (Scenario 1) to benefiting downstream countries (Scenario 11) for the three example dams on the studied transboundary rivers: the Grand Ethiopian Renaissance Dam (GERD), Omo-Gibe III, and Tekeze dams. Our focus lies in identifying the cooperation ranges that provide optimal hydropower in the upstream and water release to the downstream among the varying water release policies within this scenario spectrum. The findings indicate that within an appropriate range for the minimum monthly water release threshold, the hydropower potential for the three study sites only has a small decrease, while the water release to downstream, especially for the driest month, can be 1.14–2.45 times larger compared to no water release constraints. For GERD and Omo-Gibe III, maintaining the monthly water release threshold of 30%-50% of the monthly flow is assumed to define the cooperation range in the historical periods. However, for Tekeze, the cooperation range is from 20% to 40% of the monthly water release. Due to climate change, the cooperation range for GERD and Omo-Gibe III is projected to decrease to 20–30% in future periods, whereas no significant impact is expected for Tekeze. The study reveals that future energy production of the hydropower dams on the transboundary rivers are influenced by the monthly minimum water release threshold, underscoring the need for adaptive cooperative strategies for both upstream and downstream countries in the face of climate change.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135111"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146153059","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":"Geochemical dynamics and colloidal transfer of major and trace elements in the Hers-Mort − Girou watershed: distinction between natural and anthropogenic signatures evidenced by REE anomalies","authors":"Baptiste Alran ,&nbsp;Eva Schreck ,&nbsp;Rémy Berrabah ,&nbsp;Oleg S. Pokrovsky ,&nbsp;Aubin Yettou ,&nbsp;Jérôme Viers","doi":"10.1016/j.jhydrol.2026.134981","DOIUrl":"10.1016/j.jhydrol.2026.134981","url":null,"abstract":"<div><div>Small watersheds are highly sensitive to anthropization, which deeply alters elemental biogeochemical cycles. This study focuses on the Hers-Mort and Girou watersheds near Toulouse (SW France), originating in the rural Lauragais region. A sampling campaign in January 2025 combined laboratory ultrafiltration (0.22 μm, 0.025 μm, 3 kDa) with measurements of physicochemical parameters (conductivity, pH, alkalinity) and elemental concentrations (DOC, anions, major cations, and trace elements).</div><div>Results reveal a clear distinction between natural and anthropogenic signals. Linear relationships between carbonates, nitrates, and Ca–Mg highlight the dominant role of lithology, with carbonate dissolution naturally supplying major cations, further enhanced by nitrates. Ultrafiltration showed that most elements occur in the labile low-molecular-weight &lt;3 kDa (LMW &lt;3 kDa) fraction, indicating high potential bioavailability and little downstream variation in DOC, Fe, Mn, Cu, and As.</div><div>Conversely, Zn and Gd displayed strong co-variation in their colloidal patterns, with the &lt;3 kDa fraction increasing downstream in parallel with urbanization, reaching up to 80 % in the most impacted areas. These elements thus represent robust tracers of anthropogenic influence. Rare Earth Element (REE) patterns in headwaters were controlled by molassic lithology, whereas downstream sections showed pronounced positive Gd anomalies (0.89–25) and systematic LREE depletion with HREE enrichment. Anthropogenic Gd accounted for 10–90 % of total Gd, evidencing clear artificial inputs and the progressive shift from natural to anthropogenic geochemical dynamics.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 134981"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146015014","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":"Comparative analysis of GAMLSS modeling approaches for nonstationary runoff dynamics in the Yellow River Basin of China","authors":"Ben Niu ,&nbsp;Yi Li ,&nbsp;Yurui Fan ,&nbsp;Lei Gong ,&nbsp;Lei Wang ,&nbsp;Taishan Wang","doi":"10.1016/j.jhydrol.2026.135048","DOIUrl":"10.1016/j.jhydrol.2026.135048","url":null,"abstract":"<div><div>Quantifying the driving effects of climate change and human activities on nonstationary runoff dynamics is essential. However, the systematic assessments of nonstationary characteristics and their multiple driving mechanisms at the basin scale remain insufficient. This study compared two Generalized Additive Model for Location, Scale, and Shape (GAMLSS) modeling approaches–Continuous-series modeling (Mode1) and monthly-segmented modeling (Mode2)–to analyze the hydrological nonstationarity characteristics of the Yellow River Basin <em>in China</em> and elucidate the driving mechanisms of runoff processes by incorporating covariates of time, circulation, climate, and human factors. The results indicated that: (1) Taking time as a covariate, Mode2 significantly enhanced model robustness by isolating seasonal dynamics. Mode2 raised the average correlation of the location parameter (μ) with the monthly runoff series to R = 0.82 (range 0.70–0.90), a 30–50% increase over Mode1. Furthermore, the nonstationary standardized runoff index (NSRI) aligned more accurately with actual hydrological fluctuations. (2) Taking circulation indices as covariates, circulation indices (AMO, PDO and NINO3) predominantly governed large-scale hydrological trends, with PDO exerting a more pronounced regulatory effect on extreme events in the downstream region under Mode2. (3) The climate-human composite-driven model had the best fitting effect on runoff, particularly at lower timescales (1-, 3-, and 6-month scales) in the middle and lower reaches, where the interactions among total precipitation (TP), snowmelt (SMT), and soil water storage capacity (SWC) explained over 80% of runoff variations (This model yielded the lowest AICc—15% lower than the single climate model—and the highest explanatory power, with R² = 0.85 at 1-month, and 0.70 at 3-month scales). This study suggests that Mode2, with its precise characterization of seasonal differentiation and human dynamics, is more suitable for refined water resource management and extreme drought-flood prediction, whereas Mode1 remains efficient for analyzing interdecadal circulation effects. By addressing three key challenges—capturing monthly runoff nonstationarity, integrating multi-factor drivers, and validating runoff simulations—this study greatly improves runoff modeling and drought detection accuracy, laying a scientific foundation for adaptive management under the combined pressures of climate change and human activities.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135048"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071822","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":"Climate modulation and intensity-stratified moisture sources in major global river basins","authors":"Xingxing Zhang ,&nbsp;Zhaocai Wang ,&nbsp;Tomasz Janus ,&nbsp;Hou Jiang ,&nbsp;Zhaofei Liu ,&nbsp;Liguang Jiang ,&nbsp;Yizhu Zhu ,&nbsp;Yaozhi Jiang ,&nbsp;Zhijun Yao ,&nbsp;Hua Wu","doi":"10.1016/j.jhydrol.2026.135049","DOIUrl":"10.1016/j.jhydrol.2026.135049","url":null,"abstract":"<div><div>Understanding how atmospheric moisture pathways regulate precipitation variability is essential for basin-scale water security under climate change. Here we present a global, intensity-stratified analysis of moisture sources and transport across seven major river basins using ERA5 reanalysis and the WAM-2layers model. By combining precipitationshed diagnostics with empirical orthogonal function analysis, we identify dominant and higher-order moisture transport modes and assess their roles in seasonal and extreme precipitation. River basins are classified into ocean-dominated, mixed-source, and land-dominated regimes based on the structure and variability of moisture transport. Ocean-dominated basins exhibit coherent moisture pathways and strong coupling between precipitation and the leading transport mode, whereas land-dominated and high-latitude basins show weaker coupling and a greater reliance on higher-order modes, particularly during seasonal transitions and heavy precipitation events. Mixed-source basins maintain robust precipitation–transport relationships despite pronounced seasonal shifts. We further identify regime-dependent multi-decadal shifts in moisture source regions and seasonally varying climate influences on transport modes, demonstrating that mean moisture source fractions alone cannot explain precipitation variability and extremes. These findings improve our understanding of basin-specific hydroclimatic responses and offer valuable insights for future hydrological predictions and climate adaptation.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 135049"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071825","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":"Hydrological connectivity and landscape composition shape nutrient export: Evidence from SWAT and machine learning analysis in the Longxi River Basin","authors":"Shaojun Tan ,&nbsp;Jianfeng Xu ,&nbsp;Kai Wang ,&nbsp;Haiming Lu ,&nbsp;Xianqiang Tang ,&nbsp;Danyang Wang ,&nbsp;Lishan Ran ,&nbsp;Deti Xie ,&nbsp;Jiupai Ni ,&nbsp;Fangxin Chen ,&nbsp;Wendi Wang ,&nbsp;Eugenio Straffelini","doi":"10.1016/j.jhydrol.2026.135013","DOIUrl":"10.1016/j.jhydrol.2026.135013","url":null,"abstract":"<div><div>Understanding how hydrological connectivity and landscape patterns influence nutrient export is critical for clarifying the mechanisms driving non-point source pollution in river basins, especially where agriculture is largely practice. This study employed the Soil and Water Assessment Tool (SWAT) to simulate total nitrogen (TN) and total phosphorus (TP) export loads in the Longxi River Basin (LRB, in China) during 2021–2022. Using Random Forest (RF) and partial least squares structural equation modeling (PLS-SEM), the research explored the influences of terrain, landscape configuration, landscape composition, and aggregated hydrological connectivity (AIC) on TN and TP exports. Results indicated that average summer TN and TP exports accounted for 51.11% and 52.55% of the annual totals, respectively. Liangping and Dianjiang Countiy, along with the adjacent Changshou Lake reservoir, exhibited the highest hydrological connectivity indices within the watershed, especially during summer. RF model analysis identified landscape composition and hydrological connectivity as the primary factors governing TN and TP exports. Findings highlight the importance of managing hydrological connectivity and optimizing landscape composition as strategies for reducing nutrient losses and mitigating non-point source pollution in watershed management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 135013"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071826","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":"Global quantification of the bidirectional dependence between vegetation productivity and multi-layer soil moisture","authors":"Ying Liu,&nbsp;Jiumeilin Shi,&nbsp;Hui Yue,&nbsp;Xu Wang","doi":"10.1016/j.jhydrol.2026.135065","DOIUrl":"10.1016/j.jhydrol.2026.135065","url":null,"abstract":"<div><div>Soil moisture serves as a crucial water source for vegetation growth, while vegetation dynamics in turn regulate soil moisture through processes such as evapotranspiration and canopy interception. Quantitatively characterizing this mutual feedback is essential for optimizing hydrological processes and promoting coordinated vegetation–water management. However, the bidirectional interactions between soil moisture and vegetation productivity across different climate zones, vegetation types, and soil depths remain poorly understood. Based on Global Solar Induced Chlorophyll Fluorescence, soil moisture, the average air temperature at 2 m, and solar radiation datasets, this study employed trend analysis, causal inference, and multiple linear regression to explore the Granger causality between vegetation productivity and multi-layer soil moisture under different environmental conditions. Results revealed widespread bidirectional dependence between vegetation productivity and soil moisture across all soil layers, with interaction strength declining from 79.84% in the surface layer (0–10 cm) to 72.04% in the deep layer (100–200 cm). The magnitude of this bidirectional coupling varied significantly across climate zones: dependence peaked in surface soils within temperate regions (82.52%), while tropical zones exhibited maxima in the shallow (82.99%) and deep (78.05%) layers. Boreal zones showed the strongest dependence in the middle soil layer (76.25%). Furthermore, driven by differences in transpiration rates and water retention capacity, woody plants demonstrated higher average bidirectional dependence (79.4%) than herbaceous plants (75.75%), whereas shrubland vegetation exhibited relatively lower dependence (74%). Considering the spatial distribution of climate and vegetation types, tropical zones (dominated by evergreen broadleaf forests) and boreal zones (dominated by shrublands) both showed peak bidirectional dependence in the shallow soil layer. Other climate zones, primarily influenced by grassland vegetation, exhibited peak dependence within the surface soil layer. This study reveals the variability in bidirectional dependence between vegetation productivity and multilayer soil moisture across different climatic zones and vegetation types, which will provide a robust theoretical foundation for improving regional soil moisture regulation and guiding ecosystem restoration under changing climatic conditions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135065"},"PeriodicalIF":6.3,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089325","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}