At many petroleum hydrocarbon spill sites, residual spilled product forms a long-term source of groundwater contamination. The phrase source zone natural depletion is used to refer to the mass loss rates. Overall mass lost under environmental conditions was analyzed using conservative biomarker concentrations for a 1979 oil spill in northern Minnesota, USA. After 40–41 years, an average of 50% of the mass was lost with values ranging from 22% to 57% depending on location. It is also important to understand the composition changes in the source. To understand controls on the losses of individual compounds, concentrations of volatile hydrocarbons in oil samples were compared with aqueous solubilities, and pore-space oil saturations. The results of the comparison show that losses of the oil compounds were controlled by pore-space oil saturations, solubility, and susceptibility to degradation under methanogenic conditions. Compounds that degrade under methanogenic conditions, including toluene, o-xylene, and n-alkanes are more depleted compared to benzene, ethylbenzene, and m- and p-xylene for which losses are dominated by dissolution. These rates and compound-specific behaviors form a foundation for improved modeling approaches and risk analyses.
{"title":"Natural Source Zone Depletion of Crude Oil in the Subsurface: Processes Controlling Mass Losses of Individual Compounds","authors":"Barbara A. Bekins, William N. Herkelrath","doi":"10.1029/2025wr041964","DOIUrl":"https://doi.org/10.1029/2025wr041964","url":null,"abstract":"At many petroleum hydrocarbon spill sites, residual spilled product forms a long-term source of groundwater contamination. The phrase source zone natural depletion is used to refer to the mass loss rates. Overall mass lost under environmental conditions was analyzed using conservative biomarker concentrations for a 1979 oil spill in northern Minnesota, USA. After 40–41 years, an average of 50% of the mass was lost with values ranging from 22% to 57% depending on location. It is also important to understand the composition changes in the source. To understand controls on the losses of individual compounds, concentrations of volatile hydrocarbons in oil samples were compared with aqueous solubilities, and pore-space oil saturations. The results of the comparison show that losses of the oil compounds were controlled by pore-space oil saturations, solubility, and susceptibility to degradation under methanogenic conditions. Compounds that degrade under methanogenic conditions, including toluene, <i>o</i>-xylene, and <i>n</i>-alkanes are more depleted compared to benzene, ethylbenzene, and <i>m</i>- and <i>p</i>-xylene for which losses are dominated by dissolution. These rates and compound-specific behaviors form a foundation for improved modeling approaches and risk analyses.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"47 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894497","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}
Deep learning (DL) models such as Long-Short-Term-Memory (LSTM) networks have achieved exceptional predictive accuracy in rainfall–runoff modeling. Yet these models learn from statistical correlations rather than hydrologic insights, raising the question of whether their internal functional reasoning is physically reliable. Despite previous studies highlighting unexpected outcomes from LSTMs under long-term climate shifts, functional realism—defined as the extent to which a model's internal functioning aligns with defensible mechanisms of streamflow generation—remains largely underexplored. We introduce a hydrology-specific Explainable AI (XAI) framework that opens the black-box of LSTM. It extracts nonlinear, lag-dependent, and time-varying Impulse Response Functions (IRFs) which quantify the functional relationships that LSTM uses to reflect the isolated influence of precipitation (P), temperature (T), and potential evapotranspiration (PET) on simulated streamflow. IRFs reveal how LSTMs internalize streamflow generation during events, offering a catchment hydrology perspective for evaluating model realism. Applying this framework to 672 North American catchments with strong LSTM predictive skill, we find that high accuracy often masks hydrologically implausible reasoning: in over 70% of rain-dominated basins, short-term temperature rises unexpectedly raise simulated streamflow and enhance celerity rate even without rainfall; in snow-dominated regions, PET is misattributed as a driver of snowmelt-related flow and enhances the catchment's celerity rate. We conclude that correlation-driven learning can compromise the robustness of LSTM-based forecasts under weather extremes and short-term and long-term climatic shifts. Our framework bridges deep learning with hydrologic understanding and offers a scalable diagnostic for assessing the functional realism of DL models across diverse catchment types.
{"title":"Evaluating the Functional Realism of Deep Learning Rainfall-Runoff Models Using Catchment Hydrology Principles","authors":"Ara Bayati, Ali A. Ameli, Saman Razavi","doi":"10.1029/2025wr040076","DOIUrl":"https://doi.org/10.1029/2025wr040076","url":null,"abstract":"Deep learning (DL) models such as Long-Short-Term-Memory (LSTM) networks have achieved exceptional predictive accuracy in rainfall–runoff modeling. Yet these models learn from statistical correlations rather than hydrologic insights, raising the question of whether their internal functional reasoning is physically reliable. Despite previous studies highlighting unexpected outcomes from LSTMs under long-term climate shifts, functional realism—defined as the extent to which a model's internal functioning aligns with defensible mechanisms of streamflow generation—remains largely underexplored. We introduce a hydrology-specific Explainable AI (XAI) framework that opens the black-box of LSTM. It extracts nonlinear, lag-dependent, and time-varying Impulse Response Functions (IRFs) which quantify the functional relationships that LSTM uses to reflect the isolated influence of precipitation (<i>P</i>), temperature (<i>T</i>), and potential evapotranspiration (<i>PET</i>) on simulated streamflow. IRFs reveal how LSTMs internalize streamflow generation during events, offering a catchment hydrology perspective for evaluating model realism. Applying this framework to 672 North American catchments with strong LSTM predictive skill, we find that high accuracy often masks hydrologically implausible reasoning: in over 70% of rain-dominated basins, short-term temperature rises unexpectedly raise simulated streamflow and enhance celerity rate even without rainfall; in snow-dominated regions, <i>PET</i> is misattributed as a driver of snowmelt-related flow and enhances the catchment's celerity rate. We conclude that correlation-driven learning can compromise the robustness of LSTM-based forecasts under weather extremes and short-term and long-term climatic shifts. Our framework bridges deep learning with hydrologic understanding and offers a scalable diagnostic for assessing the functional realism of DL models across diverse catchment types.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"6 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894495","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}
Ruolan Yu, Chen Zhang, Mengfen Liu, Michael T. Brett
The role of periphyton in lake phosphorus cycling has long been overlooked or simplified, as water quality models often classify periphyton parameters as non-sensitive, thereby masking their key roles in phosphorus cycling. Therefore, to quantify how periphyton influence phosphorus cycling and related limnological processes, we conducted over 11,000 sensitivity analyses across a wide range of hydrologic and seasonal variations, comparing simulations with and without periphyton processes (PERI vs. noPERI) in the Spokane River and Lake Spokane model. Results showed that excluding periphyton increased spring average epilimnetic total phosphorus (TP) by up to ∼15% due to orthophosphate (PO4) accumulation, while early summer TP decreased by up to ∼7% because of reduced labile dissolved organic matter phosphorus (LDOMP). Concurrently, the chlorophyll-a (Chla) peak advanced from early July to late May (∼41 days), and minimum volume-weighted hypolimnetic dissolved oxygen concentration (DOMIN) decreased by ∼7% in spring. Periphyton regulate phosphorus cycling primarily through two mechanisms: (a) reducing PO4 via growth-driven uptake while enhancing LDOMP through mortality-driven release, leading to seasonally varying contributions to TP; and (b) influencing sediment–water phosphorus exchange and shaping cycling dynamics through direct and indirect competition with phytoplankton. Although sediment oxygen demand parameters were the most sensitive overall and phytoplankton parameters contributed substantially, periphyton parameters that were initially non-sensitive became sensitive under winter conditions and at both low and high flows. This study shows that periphyton can play an important role in long-term phosphorus dynamics, and that dynamically incorporating periphyton processes in models of seasonally stratified lakes can improve water quality management.
{"title":"The Masked Role of Periphyton in Phosphorus Cycling: Mechanistic Insights Under Large-Scale Hydrologic and Seasonal Variability","authors":"Ruolan Yu, Chen Zhang, Mengfen Liu, Michael T. Brett","doi":"10.1029/2025wr041368","DOIUrl":"https://doi.org/10.1029/2025wr041368","url":null,"abstract":"The role of periphyton in lake phosphorus cycling has long been overlooked or simplified, as water quality models often classify periphyton parameters as non-sensitive, thereby masking their key roles in phosphorus cycling. Therefore, to quantify how periphyton influence phosphorus cycling and related limnological processes, we conducted over 11,000 sensitivity analyses across a wide range of hydrologic and seasonal variations, comparing simulations with and without periphyton processes (PERI vs. noPERI) in the Spokane River and Lake Spokane model. Results showed that excluding periphyton increased spring average epilimnetic total phosphorus (TP) by up to ∼15% due to orthophosphate (PO<sub>4</sub>) accumulation, while early summer TP decreased by up to ∼7% because of reduced labile dissolved organic matter phosphorus (LDOMP). Concurrently, the chlorophyll-a (Chl<i>a</i>) peak advanced from early July to late May (∼41 days), and minimum volume-weighted hypolimnetic dissolved oxygen concentration (DO<sub>MIN</sub>) decreased by ∼7% in spring. Periphyton regulate phosphorus cycling primarily through two mechanisms: (a) reducing PO<sub>4</sub> via growth-driven uptake while enhancing LDOMP through mortality-driven release, leading to seasonally varying contributions to TP; and (b) influencing sediment–water phosphorus exchange and shaping cycling dynamics through direct and indirect competition with phytoplankton. Although sediment oxygen demand parameters were the most sensitive overall and phytoplankton parameters contributed substantially, periphyton parameters that were initially non-sensitive became sensitive under winter conditions and at both low and high flows. This study shows that periphyton can play an important role in long-term phosphorus dynamics, and that dynamically incorporating periphyton processes in models of seasonally stratified lakes can improve water quality management.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"55 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894496","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}
Han Jiang, Bowen Shi, Chao-Zhong Qin, Christoph Arns, S. Majid Hassanizadeh
Understanding two-phase flow in laminated sandstones is important for fluid migration control and operational strategy determination in underground energy and hydrology engineering projects. Digital core analysis provides unparalleled understanding of two-phase flow in complex porous media, but the integration into field analytical workflow is obstructed by the huge computational burden and imaging limitations on a standard rock core. To address this challenge, we propose a novel pore-scale rock-typing and upscaling approach for fast computation of two-phase flow properties on large three-dimensional digital rock images that contain billions of voxels. Firstly, a heterogeneous rock sample is divided into several homogeneous rock types through data clustering of regional 3D morphological parameters, and their two-phase flow properties are calculated from selected subsamples using in-house pore-network model. The capillary pressure and relative permeability curves of the full digital image are then estimated through quasi-static modeling on the rock type distribution. The excellent agreement between the upscaling results and pore-scale simulations on the full image has verified the effectiveness of this two-phase flow upscaling strategy. With largely reduced computational demands and clearly defined lamination heterogeneity, this approach has demonstrated good potential in bridging the gap between pore-scale and core-scale fluid flow mechanisms. In addition, due to the laminated structural characteristics, we also find a significant reduction in phase mobility over a range of saturations in the relative permeability curves of this highly permeable rock sample.
{"title":"Pore-Scale Rock-Typing and Upscaling of Relative Permeability on a Laminated Sandstone Through Minkowski Measures","authors":"Han Jiang, Bowen Shi, Chao-Zhong Qin, Christoph Arns, S. Majid Hassanizadeh","doi":"10.1029/2025wr041036","DOIUrl":"https://doi.org/10.1029/2025wr041036","url":null,"abstract":"Understanding two-phase flow in laminated sandstones is important for fluid migration control and operational strategy determination in underground energy and hydrology engineering projects. Digital core analysis provides unparalleled understanding of two-phase flow in complex porous media, but the integration into field analytical workflow is obstructed by the huge computational burden and imaging limitations on a standard rock core. To address this challenge, we propose a novel pore-scale rock-typing and upscaling approach for fast computation of two-phase flow properties on large three-dimensional digital rock images that contain billions of voxels. Firstly, a heterogeneous rock sample is divided into several homogeneous rock types through data clustering of regional 3D morphological parameters, and their two-phase flow properties are calculated from selected subsamples using in-house pore-network model. The capillary pressure and relative permeability curves of the full digital image are then estimated through quasi-static modeling on the rock type distribution. The excellent agreement between the upscaling results and pore-scale simulations on the full image has verified the effectiveness of this two-phase flow upscaling strategy. With largely reduced computational demands and clearly defined lamination heterogeneity, this approach has demonstrated good potential in bridging the gap between pore-scale and core-scale fluid flow mechanisms. In addition, due to the laminated structural characteristics, we also find a significant reduction in phase mobility over a range of saturations in the relative permeability curves of this highly permeable rock sample.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"35 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894498","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}
Natural landslide dams pose severe hazards when they fail, and understanding their breach processes remain challenging because such events are rarely observed directly in the field. To address this gap, we conducted large-scale overtopping experiments with compacted (CP) and non-compacted (NCP) dams, supported by a synchronized multi-sensor framework that combined UAV and ground-based photogrammetry, particle tracking velocimetry, water level gauges, autonomous scouring particles, and seismic monitoring. In situ density tests confirmed that CP dams had higher dry bulk volumetric weight and lower water content (2.33 t/m3, 4.9%) than NCP dams (2.04–1.98 t/m3, 6.8%–4.4%), corresponding to compaction levels of ∼104% for CP and 88%–89% for NCP. The multi-sensor observations captured both surface and subsurface processes throughout failure, revealing that CP dams breached rapidly with sharp peak discharges and narrow, deeply incised channels, whereas NCP dams breached more gradually, producing flatter hydrographs and wider, shallower channels. Despite these differences, the underwater cross-sections consistently evolved toward parabolic geometries. In addition, several characteristic signatures were observed across data sets, including concentrated velocity jets in CP versus dispersed flows in NCP, and V-shaped seismic spectrograms observed during the processes of incision and widening. Because these experiments are approximately five times larger than typical laboratory flume studies, they captured scale-dependent behaviors not observable in smaller facilities, including slower incision rates, later peak discharges, and more gradual hydrograph development at larger scale. These findings clarify how compaction and scale jointly influence breach timing and erosion pathways and provide physically grounded constraints for improving numerical breach models and hazard assessments.
{"title":"Synchronized Multidisciplinary Observations in Large-Scale Dam Breach Experiments to Enhance the Understanding of Dam Failure Evolution","authors":"Su-Chin Chen, Chi-Yao Hung, Pei-Yi Chen, Samkele S. Tfwala, Min-Chih Liang, Chen-Han Jiang, Wei-An Chao","doi":"10.1029/2025wr040786","DOIUrl":"https://doi.org/10.1029/2025wr040786","url":null,"abstract":"Natural landslide dams pose severe hazards when they fail, and understanding their breach processes remain challenging because such events are rarely observed directly in the field. To address this gap, we conducted large-scale overtopping experiments with compacted (CP) and non-compacted (NCP) dams, supported by a synchronized multi-sensor framework that combined UAV and ground-based photogrammetry, particle tracking velocimetry, water level gauges, autonomous scouring particles, and seismic monitoring. In situ density tests confirmed that CP dams had higher dry bulk volumetric weight and lower water content (2.33 t/m<sup>3</sup>, 4.9%) than NCP dams (2.04–1.98 t/m<sup>3</sup>, 6.8%–4.4%), corresponding to compaction levels of ∼104% for CP and 88%–89% for NCP. The multi-sensor observations captured both surface and subsurface processes throughout failure, revealing that CP dams breached rapidly with sharp peak discharges and narrow, deeply incised channels, whereas NCP dams breached more gradually, producing flatter hydrographs and wider, shallower channels. Despite these differences, the underwater cross-sections consistently evolved toward parabolic geometries. In addition, several characteristic signatures were observed across data sets, including concentrated velocity jets in CP versus dispersed flows in NCP, and V-shaped seismic spectrograms observed during the processes of incision and widening. Because these experiments are approximately five times larger than typical laboratory flume studies, they captured scale-dependent behaviors not observable in smaller facilities, including slower incision rates, later peak discharges, and more gradual hydrograph development at larger scale. These findings clarify how compaction and scale jointly influence breach timing and erosion pathways and provide physically grounded constraints for improving numerical breach models and hazard assessments.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"3 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894501","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}
Pengdong Yan, Hongwei Lu, Yuxuan Wang, Yiming Yan, Zhucheng Zhang, Mengxi He, Hengchen Li, Jun Xia, Li He
Little has been known whether intensified global population aging has an independent effect on water use (which corresponds to the global water security). We here use panel analysis to quantitatively find out an obvious declining effect of global population aging (measured by proportion of aged population) on water use (measured by total water withdrawal (TWW)) based on the data of 168 countries in 1987–2018 and then analyze the potential mechanisms leading to the effect. We find that the estimated coefficient regarding the aging effect (β) is about −0.0217, indicating that each percent of increase in proportion of aged population caused 2.17 percent decline in TWW. We further demonstrate the obvious aging effect at the country scale using the gridded data from 2000 to 2010. We eventually project that the global aging effect will lead to about 15%–31% of declines in water use under scenarios SSP1 to SSP5 by 2050.
{"title":"The Global Declining Effect of Population Aging on Water Use","authors":"Pengdong Yan, Hongwei Lu, Yuxuan Wang, Yiming Yan, Zhucheng Zhang, Mengxi He, Hengchen Li, Jun Xia, Li He","doi":"10.1029/2024wr037685","DOIUrl":"https://doi.org/10.1029/2024wr037685","url":null,"abstract":"Little has been known whether intensified global population aging has an independent effect on water use (which corresponds to the global water security). We here use panel analysis to quantitatively find out an obvious declining effect of global population aging (measured by proportion of aged population) on water use (measured by total water withdrawal (TWW)) based on the data of 168 countries in 1987–2018 and then analyze the potential mechanisms leading to the effect. We find that the estimated coefficient regarding the aging effect (<i>β</i>) is about −0.0217, indicating that each percent of increase in proportion of aged population caused 2.17 percent decline in TWW. We further demonstrate the obvious aging effect at the country scale using the gridded data from 2000 to 2010. We eventually project that the global aging effect will lead to about 15%–31% of declines in water use under scenarios SSP1 to SSP5 by 2050.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"2020 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894500","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}
Max G. Rudolph, Thomas Wöhling, Thorsten Wagener, Andreas Hartmann
Groundwater model parameters need to be inferred on the basis of limited observation data, resulting in prediction uncertainty. The reduction of this uncertainty via future complementary observations is of high importance for many problems and can be guided by Bayesian experimental design. We employ a novel combination of Bayesian inversion, accelerated via multilevel methods, and Bayesian experimental design for this purpose. For a synthetic aquifer, we analyze the effect of including or excluding environmental tracer observations besides groundwater heads in two scenarios. In both scenarios, we study the effect of available data on distributions of model predictions after Bayesian inversion and subsequent experimental design. We demonstrate that posterior samples from Bayesian inversion can be reused to perform experimental design without additional model evaluations. In both scenarios, uncertainties and biases of flux-related and groundwater age-related predictions are substantially reduced through experimental design. Compared to the scenario with groundwater heads alone, including environmental tracer data in the observation data set leads to less uncertainty and bias in model outputs after Bayesian inversion, greater reduction of uncertainty and bias through experimental design, and reduced overestimation of complementary observation worth. Including environmental tracer observations at the beginning of combined Bayesian inversion and experimental design leads to more reliable predictions and more effective future data acquisition.
{"title":"The Effect of Available Data on the Worth of Future Observations for Groundwater Modeling","authors":"Max G. Rudolph, Thomas Wöhling, Thorsten Wagener, Andreas Hartmann","doi":"10.1029/2025wr041972","DOIUrl":"https://doi.org/10.1029/2025wr041972","url":null,"abstract":"Groundwater model parameters need to be inferred on the basis of limited observation data, resulting in prediction uncertainty. The reduction of this uncertainty via future complementary observations is of high importance for many problems and can be guided by Bayesian experimental design. We employ a novel combination of Bayesian inversion, accelerated via multilevel methods, and Bayesian experimental design for this purpose. For a synthetic aquifer, we analyze the effect of including or excluding environmental tracer observations besides groundwater heads in two scenarios. In both scenarios, we study the effect of available data on distributions of model predictions after Bayesian inversion and subsequent experimental design. We demonstrate that posterior samples from Bayesian inversion can be reused to perform experimental design without additional model evaluations. In both scenarios, uncertainties and biases of flux-related and groundwater age-related predictions are substantially reduced through experimental design. Compared to the scenario with groundwater heads alone, including environmental tracer data in the observation data set leads to less uncertainty and bias in model outputs after Bayesian inversion, greater reduction of uncertainty and bias through experimental design, and reduced overestimation of complementary observation worth. Including environmental tracer observations at the beginning of combined Bayesian inversion and experimental design leads to more reliable predictions and more effective future data acquisition.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"29 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894502","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}
Fiona S. Liu, Devon Kerins, Shreya Ramesh, Pamela L. Sullivan, Sharon A. Billings, Daniel R. Hirmas, Hoori Ajami, Alejandro Flores, Catalina Segura, Li Li
Forest plantations are widespread globally. Young forest plantations (hereafter young forests) differ from natural old-growth forests (hereafter old forests) in above- and below-ground structures, shaping water and carbon cycling processes. While above-ground differences are well studied, below-ground hydrology and biogeochemical processes remain poorly understood. Here we asked: How do hydrological flow paths and dissolved carbon processes belowground differ between young and old forests? Using a process-based hydro-biogeochemical model (BioRT-HBV) constrained by streamflow and dissolved organic and inorganic carbon (DOC and DIC) data, we analyzed three pairs of young-old forests at the H.J. Andrews Experimental Forest, Oregon, USA. Detailed simulations for a 57-year-old plantation (WS01) and a naturally regenerated ∼500-year-old forest (WS02) showed that the young forest had lower streamflow and smaller deep groundwater contributions (20%) than the old forest (30%). DOC was mainly produced in shallow soil but diverged with depth: transformed into DIC in the young forest and further produced in the old forest, yielding contrasting export patterns of flushing (DOC increases with discharge) and dilution (DOC decreases with discharge). These differences likely stem from variations in subsurface structures, supported by deeper, denser roots in old forest. Extending the analysis to two additional pairs showed (a) higher DOC and DIC concentrations in all old forests; (b) consistent DIC dilution patterns but variable DOC patterns. Numerical experiments indicate that these diverse DOC behaviors result from interactions among forest age, geology, and hydrological connectivity, and other factors, highlighting the overlooked role of forest development in subsurface carbon cycling.
{"title":"Young Versus Old: Does Forest Age Regulate Water and Dissolved Carbon Processes Belowground?","authors":"Fiona S. Liu, Devon Kerins, Shreya Ramesh, Pamela L. Sullivan, Sharon A. Billings, Daniel R. Hirmas, Hoori Ajami, Alejandro Flores, Catalina Segura, Li Li","doi":"10.1029/2025wr040838","DOIUrl":"https://doi.org/10.1029/2025wr040838","url":null,"abstract":"Forest plantations are widespread globally. Young forest plantations (hereafter young forests) differ from natural old-growth forests (hereafter old forests) in above- and below-ground structures, shaping water and carbon cycling processes. While above-ground differences are well studied, below-ground hydrology and biogeochemical processes remain poorly understood. Here we asked: <i>How do hydrological flow paths and dissolved carbon processes belowground differ between young and old forests?</i> Using a process-based hydro-biogeochemical model (BioRT-HBV) constrained by streamflow and dissolved organic and inorganic carbon (DOC and DIC) data, we analyzed three pairs of young-old forests at the H.J. Andrews Experimental Forest, Oregon, USA. Detailed simulations for a 57-year-old plantation (WS01) and a naturally regenerated ∼500-year-old forest (WS02) showed that the young forest had lower streamflow and smaller deep groundwater contributions (20%) than the old forest (30%). DOC was mainly produced in shallow soil but diverged with depth: transformed into DIC in the young forest and further produced in the old forest, yielding contrasting export patterns of flushing (DOC increases with discharge) and dilution (DOC decreases with discharge). These differences likely stem from variations in subsurface structures, supported by deeper, denser roots in old forest. Extending the analysis to two additional pairs showed (a) higher DOC and DIC concentrations in all old forests; (b) consistent DIC dilution patterns but variable DOC patterns. Numerical experiments indicate that these diverse DOC behaviors result from interactions among forest age, geology, and hydrological connectivity, and other factors, highlighting the overlooked role of forest development in subsurface carbon cycling.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"57 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894504","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}
This research introduces a new deep learning (DL) framework, multi-head self-attention-aided vision Transformer (MSA-ViT), for soil moisture (SM) retrieval using Cyclone Global Navigation Satellite System (CYGNSS) data. We first assess the sensitivity of CYGNSS reflectivity <span data-altimg="/cms/asset/97d7f44f-c0ba-48f7-9981-3428ca80aa8b/wrcr70626-math-0001.png"></span><mjx-container ctxtmenu_counter="130" ctxtmenu_oldtabindex="1" jax="CHTML" role="application" sre-explorer- style="font-size: 103%; position: relative;" tabindex="0"><mjx-math aria-hidden="true" location="graphic/wrcr70626-math-0001.png"><mjx-semantics><mjx-mrow data-semantic-children="1" data-semantic-content="0,2" data-semantic- data-semantic-role="leftright" data-semantic-speech="left parenthesis normal upper Gamma right parenthesis" data-semantic-type="fenced"><mjx-mo data-semantic- data-semantic-operator="fenced" data-semantic-parent="3" data-semantic-role="open" data-semantic-type="fence" style="margin-left: 0.056em; margin-right: 0.056em;"><mjx-c></mjx-c></mjx-mo><mjx-mi data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic- data-semantic-parent="3" data-semantic-role="greekletter" data-semantic-type="identifier"><mjx-c></mjx-c></mjx-mi><mjx-mo data-semantic- data-semantic-operator="fenced" data-semantic-parent="3" data-semantic-role="close" data-semantic-type="fence" style="margin-left: 0.056em; margin-right: 0.056em;"><mjx-c></mjx-c></mjx-mo></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display="inline" unselectable="on"><math altimg="urn:x-wiley:00431397:media:wrcr70626:wrcr70626-math-0001" display="inline" location="graphic/wrcr70626-math-0001.png" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow data-semantic-="" data-semantic-children="1" data-semantic-content="0,2" data-semantic-role="leftright" data-semantic-speech="left parenthesis normal upper Gamma right parenthesis" data-semantic-type="fenced"><mo data-semantic-="" data-semantic-operator="fenced" data-semantic-parent="3" data-semantic-role="open" data-semantic-type="fence" stretchy="false">(</mo><mi data-semantic-="" data-semantic-annotation="clearspeak:simple" data-semantic-font="normal" data-semantic-parent="3" data-semantic-role="greekletter" data-semantic-type="identifier" mathvariant="normal">Γ</mi><mo data-semantic-="" data-semantic-operator="fenced" data-semantic-parent="3" data-semantic-role="close" data-semantic-type="fence" stretchy="false">)</mo></mrow>$({Gamma })$</annotation></semantics></math></mjx-assistive-mml></mjx-container> to SM, demonstrating a strong physical linkage through coherent scattering theory. The proposed MSA-ViT model integrates this physical understanding with DL to capture nonlinear interactions between SM, surface roughness, and vegetation attenuation. Using data from January 2020 to December 2024, we aggregated observations over multiple temporal scales (3–60 days) to capture diverse hydrological patterns. The MSA-ViT mo
We introduce a new hydrological index that enables assessment of extreme events every few days from the GRACE Follow‐On (GRACE‐FO) satellite mission. The Mass Change Index (MCI) was developed by standardizing instantaneous satellite gravity anomalies computed directly from orbit perturbations. It is based on hydrology‐related gravity change, namely, total water storage change, and thus equally sensitive to wet and dry anomalies. The key innovation of MCI is its sensitivity to instantaneous mass changes as opposed to monthly mean changes. GRACE‐FO's ground track permits MCI retrievals every 5–6 days in most low and mid latitude regions. We demonstrate the application of MCI to investigate hydrological extremes in the middle‐lower Yangtze River Basin (MLYRB). MCI detects extreme wet conditions (standardized index of 2.0–3.0) along the Yangtze River mainstream related to the catastrophic flood in 2020, consistent with daily streamflow observations. In contrast, a typical GRACE‐FO based monthly drought index significantly underestimates the severity of the event and misidentifies timing of the onset. MCI also detects extreme dry conditions (−2.0 to −2.5) prevailing within MLYRB, related to the unprecedented heatwave and drought event during the summer of 2022. A streamflow index and the monthly drought index both underestimate the severity of the event. MCI retains information in intersatellite range measurements that may be lost when processing monthly gravity solutions. It can also be processed more rapidly, increasing its potential value for hydrological monitoring systems and other operational applications.
{"title":"Mass Change Index for Characterizing Hydrological Extremes Every Few Days From Satellite Gravity Measurements","authors":"Miao Tang, Shin‐Chan Han, Linguo Yuan, Xinghai Yang, In‐Young Yeo, Matthew Rodell, Bailing Li, Eunjee Lee, Zhongshan Jiang","doi":"10.1029/2025wr040534","DOIUrl":"https://doi.org/10.1029/2025wr040534","url":null,"abstract":"We introduce a new hydrological index that enables assessment of extreme events every few days from the GRACE Follow‐On (GRACE‐FO) satellite mission. The Mass Change Index (MCI) was developed by standardizing instantaneous satellite gravity anomalies computed directly from orbit perturbations. It is based on hydrology‐related gravity change, namely, total water storage change, and thus equally sensitive to wet and dry anomalies. The key innovation of MCI is its sensitivity to instantaneous mass changes as opposed to monthly mean changes. GRACE‐FO's ground track permits MCI retrievals every 5–6 days in most low and mid latitude regions. We demonstrate the application of MCI to investigate hydrological extremes in the middle‐lower Yangtze River Basin (MLYRB). MCI detects extreme wet conditions (standardized index of 2.0–3.0) along the Yangtze River mainstream related to the catastrophic flood in 2020, consistent with daily streamflow observations. In contrast, a typical GRACE‐FO based monthly drought index significantly underestimates the severity of the event and misidentifies timing of the onset. MCI also detects extreme dry conditions (−2.0 to −2.5) prevailing within MLYRB, related to the unprecedented heatwave and drought event during the summer of 2022. A streamflow index and the monthly drought index both underestimate the severity of the event. MCI retains information in intersatellite range measurements that may be lost when processing monthly gravity solutions. It can also be processed more rapidly, increasing its potential value for hydrological monitoring systems and other operational applications.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"56 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830034","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}
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