Pore clogging and unclogging in porous media are ubiquitous in subsurface hydrologic processes, which have been studied extensively at various scales ranging from a single pore to porous-medium samples. However, it remains unclear how fluid flow, particle rearrangement, and the arching effect typical of cone-shaped pore geometry interact and how they are captured by a pressure drop model at the macroscopic scale. Here, we investigate the pore-scale feedback mechanisms between fluid flow and pore clogging and unclogging using a fully resolved fluid-particle coupling approach (lattice Boltzmann method-discrete element method). We first propose to use a truncated-cone pore to represent realistic pore geometries revealed by X-ray images of prepared sand packing. Then, our simulations indicate that the pore cone angle significantly influences the pressure drop associated with the clogging process by enhancing particle contacts due to arching. A modified Ergun equation is developed to consider this geometric effect. At the microscale, clogging can be explained by the interparticle force statistics; a few particles in an arch (or a dome) take the majority of hydrodynamic pressure. The maximum interparticle force is positively proportional to the particle Reynolds number and negatively associated with the tangent of the pore cone angle. Finally, a formula is established utilizing fluid characteristics and pore cone angle to compute the maximal interparticle force. Our findings, especially a modified pressure drop model that accounts for pore geometry resistance, provide guidance for applying pore-scale models of clogging and unclogging to large-scale subsurface fines transportation issues, including seepage-induced landslides, stream bank failure, and groundwater recharge.
多孔介质中的孔隙堵塞和疏通在地下水文过程中无处不在，从单个孔隙到多孔介质样本等不同尺度的孔隙堵塞和疏通已被广泛研究。然而，目前仍不清楚流体流动、颗粒重新排列和锥形孔隙几何典型的拱形效应是如何相互作用的，也不清楚宏观尺度的压降模型是如何捕捉到它们的。在此，我们采用完全解析的流体-颗粒耦合方法（晶格玻尔兹曼法-离散元法）研究了流体流动与孔隙堵塞和疏通之间的孔隙尺度反馈机制。我们首先建议使用截顶锥孔隙来表示制备砂填料的 X 射线图像所显示的真实孔隙几何形状。然后，我们的模拟结果表明，孔隙锥角由于拱起而增强了颗粒接触，从而极大地影响了与堵塞过程相关的压降。为了考虑这种几何效应，我们建立了一个修正的厄尔贡方程。在微观尺度上，堵塞可以用颗粒间力统计来解释；拱形（或圆顶）中的少数颗粒承受了大部分流体动力压力。最大颗粒间力与颗粒雷诺数成正比，与孔锥角正切成反比。最后，利用流体特性和孔锥角建立了一个计算最大粒子间力的公式。我们的研究结果，特别是考虑到孔隙几何阻力的修正压降模型，为将孔隙尺度的堵塞和疏通模型应用于大规模地下细粒输送问题（包括渗流引发的山体滑坡、河岸崩塌和地下水补给）提供了指导。
{"title":"Clogging and Unclogging of Fine Particles in Porous Media: Micromechanical Insights From an Analog Pore System","authors":"Yanzhou Yin, Yifei Cui, Lu Jing","doi":"10.1029/2023wr034628","DOIUrl":"https://doi.org/10.1029/2023wr034628","url":null,"abstract":"Pore clogging and unclogging in porous media are ubiquitous in subsurface hydrologic processes, which have been studied extensively at various scales ranging from a single pore to porous-medium samples. However, it remains unclear how fluid flow, particle rearrangement, and the arching effect typical of cone-shaped pore geometry interact and how they are captured by a pressure drop model at the macroscopic scale. Here, we investigate the pore-scale feedback mechanisms between fluid flow and pore clogging and unclogging using a fully resolved fluid-particle coupling approach (lattice Boltzmann method-discrete element method). We first propose to use a truncated-cone pore to represent realistic pore geometries revealed by X-ray images of prepared sand packing. Then, our simulations indicate that the pore cone angle significantly influences the pressure drop associated with the clogging process by enhancing particle contacts due to arching. A modified Ergun equation is developed to consider this geometric effect. At the microscale, clogging can be explained by the interparticle force statistics; a few particles in an arch (or a dome) take the majority of hydrodynamic pressure. The maximum interparticle force is positively proportional to the particle Reynolds number and negatively associated with the tangent of the pore cone angle. Finally, a formula is established utilizing fluid characteristics and pore cone angle to compute the maximal interparticle force. Our findings, especially a modified pressure drop model that accounts for pore geometry resistance, provide guidance for applying pore-scale models of clogging and unclogging to large-scale subsurface fines transportation issues, including seepage-induced landslides, stream bank failure, and groundwater recharge.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"6 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139379795","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}
To assess flood risks, we seek to estimate the probability distribution of the worst possible single-event over a contiguous period of N years rather than the cumulative losses expected over a planning horizon. For this we use the probability distribution FN of extreme flood events over a multi-year period, which is different from using the conventional single-valued exceedance probability of 1/N years. FN can be used to estimate the hazard and then proceed to the estimation of risk, which we define as the “largest expected damage” over the set period. It also allows for a more coherent determination of design values, which descend from fully acknowledging the aleatoric uncertainty of the underlying natural river flow process. The epistemic uncertainty is removed by marginalizing the aleatoric-epistemic uncertainty joint distribution over the parameter space. The advantage of the proposed Bayesian approach, which can be summarized in 12 steps, is demonstrated for the 2021 River Ahr flood in Germany, which caused casualties and huge material damage. Adopting the multi-year maxima extreme value distribution can potentially lead to the reclassification of vulnerability levels for flood-prone areas and reconsideration of current policy-making and flood risk communication.
{"title":"Toward a New Flood Assessment Paradigm: From Exceedance Probabilities to the Expected Maximum Floods and Damages","authors":"E. Todini, P. Reggiani","doi":"10.1029/2023wr034477","DOIUrl":"https://doi.org/10.1029/2023wr034477","url":null,"abstract":"To assess flood risks, we seek to estimate the probability distribution of the worst possible single-event over a contiguous period of N years rather than the cumulative losses expected over a planning horizon. For this we use the probability distribution <i>F</i><sub><i>N</i></sub> of extreme flood events over a multi-year period, which is different from using the conventional single-valued exceedance probability of 1/N years. <i>F</i><sub><i>N</i></sub> can be used to estimate the hazard and then proceed to the estimation of risk, which we define as the “largest expected damage” over the set period. It also allows for a more coherent determination of design values, which descend from fully acknowledging the aleatoric uncertainty of the underlying natural river flow process. The epistemic uncertainty is removed by marginalizing the aleatoric-epistemic uncertainty joint distribution over the parameter space. The advantage of the proposed Bayesian approach, which can be summarized in 12 steps, is demonstrated for the 2021 River Ahr flood in Germany, which caused casualties and huge material damage. Adopting the multi-year maxima extreme value distribution can potentially lead to the reclassification of vulnerability levels for flood-prone areas and reconsideration of current policy-making and flood risk communication.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"121 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139379852","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}
Anika Pinzner, Matthew Sturm, Jennifer S. Delamere, Andrew R. Mahoney
From April through June in 2019 and 2022, we monitored snow melt at three sites near Utqiaġvik, Alaska. Along 200-m lines we measured snow depth, density, stratigraphy, snow-covered area, and spectral albedo. Site 1 (ARM) was sloped tundra drained by water tracks. Site 2 (BEO) was flat polygonal tundra. Site 3 (ICE) was on undeformed landfast sea ice. All three sites were within a 6 km radius. Despite similar pre-melt snow distributions and weather, the melt progression differed markedly between sites. In 2019, by mid-melt, there was 40% less snow-covered area at ARM versus ICE, and 34% less snow-covered area at ARM versus BEO. The 2022 melt started 2 weeks later than in 2019 and was rapid, so smaller differences in snow-covered areas developed. In both years meltout dates varied by up to 25 days between sites, and more than 20 days within sites, with melt rates at locations only meters apart differing by up to a factor of seven. This melt diachroneity led to highly heterogeneous meltout patterns at all three sites. Our measurements and observations indicate that, in addition to reductions in snow reflective properties and wind-driven heat advection, the fate of meltwater plays a key role in producing melt diachroneity. We identify seven snow-water mechanisms that can enhance or inhibit melt rates, all largely controlled by the local topography and the nature of the substrate. These mechanisms are important because the most rapid changes in albedo coincide with the peak of water-snow melt interactions.
{"title":"An Examination of Water-Related Melt Processes in Arctic Snow on Tundra and Sea-Ice","authors":"Anika Pinzner, Matthew Sturm, Jennifer S. Delamere, Andrew R. Mahoney","doi":"10.1029/2022wr033440","DOIUrl":"https://doi.org/10.1029/2022wr033440","url":null,"abstract":"From April through June in 2019 and 2022, we monitored snow melt at three sites near Utqiaġvik, Alaska. Along 200-m lines we measured snow depth, density, stratigraphy, snow-covered area, and spectral albedo. Site 1 (ARM) was sloped tundra drained by water tracks. Site 2 (BEO) was flat polygonal tundra. Site 3 (ICE) was on undeformed landfast sea ice. All three sites were within a 6 km radius. Despite similar pre-melt snow distributions and weather, the melt progression differed markedly between sites. In 2019, by mid-melt, there was 40% less snow-covered area at ARM versus ICE, and 34% less snow-covered area at ARM versus BEO. The 2022 melt started 2 weeks later than in 2019 and was rapid, so smaller differences in snow-covered areas developed. In both years meltout dates varied by up to 25 days between sites, and more than 20 days within sites, with melt rates at locations only meters apart differing by up to a factor of seven. This melt diachroneity led to highly heterogeneous meltout patterns at all three sites. Our measurements and observations indicate that, in addition to reductions in snow reflective properties and wind-driven heat advection, the fate of meltwater plays a key role in producing melt diachroneity. We identify seven snow-water mechanisms that can enhance or inhibit melt rates, all largely controlled by the local topography and the nature of the substrate. These mechanisms are important because the most rapid changes in albedo coincide with the peak of water-snow melt interactions.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"29 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139101775","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}
Alessandra Marzadri, Valentina Ciriello, Felipe P. J. de Barros
The fate of nutrients and contaminants in fluvial ecosystems is strongly affected by the mixing dynamics between surface water and groundwater within the hyporheic zone, depending on the combination of the sediment's hydraulic heterogeneity and dune morphology. This study examines the effects of hydraulic conductivity stratification on steady-state, two-dimensional, hyporheic flows and solute residence time distribution. First, we derive an integral transform-based semi-analytical solution for the flow field, capable of accounting for the effects of any functional shape of the vertically varying hydraulic conductivity. The solution considers the uneven distribution of pressure at the water-sediment interface (i.e., the pumping process) dictated by the presence of dune morphology. We then simulate solute transport using particle tracking. Our modeling framework is validated against numerical and tracer data from flume experiments and used to explore the implication of hydraulic conductivity stratification on the statistics and pdf of the residence time. Finally, reduced-order models are used to enlighten the dependence of key residence time statistics on the parameters characterizing the hydraulic conductivity stratification.
{"title":"Hyporheic Flows in Stratified Sediments: Implications on Residence Time Distributions","authors":"Alessandra Marzadri, Valentina Ciriello, Felipe P. J. de Barros","doi":"10.1029/2023wr035625","DOIUrl":"https://doi.org/10.1029/2023wr035625","url":null,"abstract":"The fate of nutrients and contaminants in fluvial ecosystems is strongly affected by the mixing dynamics between surface water and groundwater within the hyporheic zone, depending on the combination of the sediment's hydraulic heterogeneity and dune morphology. This study examines the effects of hydraulic conductivity stratification on steady-state, two-dimensional, hyporheic flows and solute residence time distribution. First, we derive an integral transform-based semi-analytical solution for the flow field, capable of accounting for the effects of any functional shape of the vertically varying hydraulic conductivity. The solution considers the uneven distribution of pressure at the water-sediment interface (i.e., the pumping process) dictated by the presence of dune morphology. We then simulate solute transport using particle tracking. Our modeling framework is validated against numerical and tracer data from flume experiments and used to explore the implication of hydraulic conductivity stratification on the statistics and <i>pdf</i> of the residence time. Finally, reduced-order models are used to enlighten the dependence of key residence time statistics on the parameters characterizing the hydraulic conductivity stratification.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"101 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139101767","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}
L. Archer, S. Hatchard, L. Devitt, J. C. Neal, G. Coxon, P. D. Bates, E. J. Kendon, J. Savage
Rainfall intensity in the United Kingdom is projected to increase under climate change with significant implications for rainfall-driven (combined pluvial and fluvial) flooding. In the UK, the current recommended best practice for estimating changes in pluvial flood hazard under climate change involves applying a simple percentage uplift to spatially uniform catchment rainfall, despite the known importance of the spatial and temporal characteristics of rainfall in the generation of pluvial floods. The UKCP Local Convective Permitting Model (CPM) has for the first time provided the capacity to assess changes in flood hazard using hourly, 2.2 km CPM precipitation data that varies in space and time. Here, we use an event set of ∼13,500 precipitation events across the three UKCP Local epochs (1981–2000, 2021–2040, and 2061–2080) to simulate rainfall-driven flooding using the LISFLOOD-FP hydrodynamic model at 20 m resolution over a 750 km2 area of Bristol and Bath, UK. We find that both the event set and uplift approaches indicate an increase in flood hazard under near-term (2021–2040) and future (2061–2080) climate change. However, the event set produces markedly higher estimates of flood hazard when compared to the uplift approach, ranging from 19% to 49% higher depending on the return period. This suggests including the full spatiotemporal rainfall variability and its future change in rainfall-driven flood modeling is critical for future flood risk assessment.
{"title":"Future Change in Urban Flooding Using New Convection-Permitting Climate Projections","authors":"L. Archer, S. Hatchard, L. Devitt, J. C. Neal, G. Coxon, P. D. Bates, E. J. Kendon, J. Savage","doi":"10.1029/2023wr035533","DOIUrl":"https://doi.org/10.1029/2023wr035533","url":null,"abstract":"Rainfall intensity in the United Kingdom is projected to increase under climate change with significant implications for rainfall-driven (combined pluvial and fluvial) flooding. In the UK, the current recommended best practice for estimating changes in pluvial flood hazard under climate change involves applying a simple percentage uplift to spatially uniform catchment rainfall, despite the known importance of the spatial and temporal characteristics of rainfall in the generation of pluvial floods. The UKCP Local Convective Permitting Model (CPM) has for the first time provided the capacity to assess changes in flood hazard using hourly, 2.2 km CPM precipitation data that varies in space and time. Here, we use an event set of ∼13,500 precipitation events across the three UKCP Local epochs (1981–2000, 2021–2040, and 2061–2080) to simulate rainfall-driven flooding using the LISFLOOD-FP hydrodynamic model at 20 m resolution over a 750 km<sup>2</sup> area of Bristol and Bath, UK. We find that both the event set and uplift approaches indicate an increase in flood hazard under near-term (2021–2040) and future (2061–2080) climate change. However, the event set produces markedly higher estimates of flood hazard when compared to the uplift approach, ranging from 19% to 49% higher depending on the return period. This suggests including the full spatiotemporal rainfall variability and its future change in rainfall-driven flood modeling is critical for future flood risk assessment.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"66 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139101769","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}
Gianluca Botter, James McNamara, Nicola Durighetto
River networks are not steady blue lines drawn in a map, since they continuously change their shape and extent in response to climatic drivers. Therefore, the flowing length of rivers (L) and the corresponding catchment-scale streamflow (Qsur) co-evolve dynamically. This paper analyzes the relationship between the wet channel length and the streamflow of a river basin, formulating a general analytical model that includes the case of temporarily dry outlets. In particular, the framework relaxes the common assumption that when the discharge at the outlet tends to zero the upstream flowing length approaches zero. Different analytical expressions for the L(Qsur) law are derived for the cases of (a) a perennial outlet; (b) a non-perennial outlet that dries out only when the whole network is dry; and (c) a temporarily dry outlet, that experiences surface flow for less time than other network nodes. In all cases, the shape of the L(Qsur) relationship is controlled by the distribution of the specific subsurface discharge capacity along the network. For temporarily dry outlets, however, the relation between L and Qsur might depend on an unknown shifting factor. Three real-world examples are presented to demonstrate the flexibility and the robustness of the theory. Our results indicate that the whole shape of the L(Qsur) relation might not be empirically observable if a significant fraction of the network is perennial or some reaches in the network experience surface flow for longer than the discharge gauging station. The study provides a basis for integrating empirical L(Qsur) data gathered in diverse sites.
{"title":"Extending Active Network Length Versus Catchment Discharge Relations to Temporarily Dry Outlets","authors":"Gianluca Botter, James McNamara, Nicola Durighetto","doi":"10.1029/2023wr035617","DOIUrl":"https://doi.org/10.1029/2023wr035617","url":null,"abstract":"River networks are not steady blue lines drawn in a map, since they continuously change their shape and extent in response to climatic drivers. Therefore, the flowing length of rivers (<i>L</i>) and the corresponding catchment-scale streamflow (<i>Q</i><sub><i>sur</i></sub>) co-evolve dynamically. This paper analyzes the relationship between the wet channel length and the streamflow of a river basin, formulating a general analytical model that includes the case of temporarily dry outlets. In particular, the framework relaxes the common assumption that when the discharge at the outlet tends to zero the upstream flowing length approaches zero. Different analytical expressions for the <i>L</i>(<i>Q</i><sub>sur</sub>) law are derived for the cases of (a) a perennial outlet; (b) a non-perennial outlet that dries out only when the whole network is dry; and (c) a temporarily dry outlet, that experiences surface flow for less time than other network nodes. In all cases, the shape of the <i>L</i>(<i>Q</i><sub>sur</sub>) relationship is controlled by the distribution of the specific subsurface discharge capacity along the network. For temporarily dry outlets, however, the relation between <i>L</i> and <i>Q</i><sub>sur</sub> might depend on an unknown shifting factor. Three real-world examples are presented to demonstrate the flexibility and the robustness of the theory. Our results indicate that the whole shape of the <i>L</i>(<i>Q</i><sub>sur</sub>) relation might not be empirically observable if a significant fraction of the network is perennial or some reaches in the network experience surface flow for longer than the discharge gauging station. The study provides a basis for integrating empirical <i>L</i>(<i>Q</i><sub>sur</sub>) data gathered in diverse sites.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"45 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139112246","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}
Jonathan Garber, Karen Thompson, Matthew J. Burns, Joshphar Kunapo, Geordie Z. Zhang, Kathryn Russell
Bankfull channel extents are of fundamental importance in fluvial geomorphology, to describe the geomorphic character of a river, and to provide a boundary for further processing of morphologic and hydraulic attributes. With ever-increasing availability of high-resolution spatial data (e.g., lidar, aerial photography), manual delineation of channel extents is a bottleneck which limits the geomorphic insights that can be gained from that data. To address this limitation, we developed and tested two automated channel delineation methods that define bankfull according to different conceptualisations of bankfull extent: (a) a cross-sectional method called HydXS that identifies the elevation which maximizes hydraulic depth (cross-section area/wetted width); and (b) a neural network image segmentation model based on a pretrained model (ResNet-18), retrained with images derived from a digital elevation model. The cross-sectional method outperformed the neural network method overall. Its prediction accuracy varied according to channel size and type, with overall precision of 0.87 and recall of 0.80. The neural network method was strongest in larger streams, and outperformed the cross-sectional method in channel sections with inset benches. A tool to delineate morphological bankfull conditions can allow us to more efficiently implement high-resolution and large-scale analyses of channel morphology (e.g., regional hydraulic geometry, channel evolution, physical complexity/habitat surveys), and improve management of fluvial geomorphology and stressors.
{"title":"Artificial Intelligence and Objective-Function Methods Can Identify Bankfull River Channel Extents","authors":"Jonathan Garber, Karen Thompson, Matthew J. Burns, Joshphar Kunapo, Geordie Z. Zhang, Kathryn Russell","doi":"10.1029/2023wr035269","DOIUrl":"https://doi.org/10.1029/2023wr035269","url":null,"abstract":"Bankfull channel extents are of fundamental importance in fluvial geomorphology, to describe the geomorphic character of a river, and to provide a boundary for further processing of morphologic and hydraulic attributes. With ever-increasing availability of high-resolution spatial data (e.g., lidar, aerial photography), manual delineation of channel extents is a bottleneck which limits the geomorphic insights that can be gained from that data. To address this limitation, we developed and tested two automated channel delineation methods that define bankfull according to different conceptualisations of bankfull extent: (a) a cross-sectional method called HydXS that identifies the elevation which maximizes hydraulic depth (cross-section area/wetted width); and (b) a neural network image segmentation model based on a pretrained model (ResNet-18), retrained with images derived from a digital elevation model. The cross-sectional method outperformed the neural network method overall. Its prediction accuracy varied according to channel size and type, with overall precision of 0.87 and recall of 0.80. The neural network method was strongest in larger streams, and outperformed the cross-sectional method in channel sections with inset benches. A tool to delineate morphological bankfull conditions can allow us to more efficiently implement high-resolution and large-scale analyses of channel morphology (e.g., regional hydraulic geometry, channel evolution, physical complexity/habitat surveys), and improve management of fluvial geomorphology and stressors.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"71 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139091245","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}
Hang Wen, Si-Liang Li, Xi Chen, Caiqing Qin, Li Li
Understanding the origins and processes of riverine dissolved inorganic carbon (DIC) is crucial for predicting the global carbon cycle with projected, more frequent climate extremes yet our knowledge has remained fragmented. Here we ask: How and how much do DIC production and export vary across space (shallow vs. deep, uphill vs. depression) and time (daily, seasonal, and annual)? How do the relative contributions of biogenic (soil respiration) and geogenic (carbonate weathering) sources differ under different temperature and hydrological conditions? We answer these questions using a catchment-scale reactive transport model constrained by stream flow, stable water isotopes, stream DIC, and carbon isotope data from a headwater karstic catchment in southwest China in a subtropical monsoon climate. Results show climate seasonality regulates the timing of DIC production and export. In hot-wet seasons, high temperature accelerates soil respiration and carbonate weathering (up to a factor of three) via elevating soil CO2 and carbonate solubility, whereas high discharge enhances export by two orders of magnitude compared to cold-dry seasons. Carbonate weathering is driven more by soil CO2 than water flow. At the annual scale, 92.9% and 7.1% of DIC was produced in shallow and deep zone, respectively, whereas 64.5% and 35.5% of DIC was exported from shallow and deep zone, respectively. These results highlight the uniqueness of subtropical karst areas as synchronous reactors and transporters of DIC during the hot-wet monsoon, contrasting the asynchronous production and export in other climate regions. A future hotter and wetter climate with more intensive storms in the region may further intensify DIC production and export, accentuating the potential of subtropical karst regions as global hot spots for carbon cycling.
{"title":"Amplified Production and Export of Dissolved Inorganic Carbon During Hot and Wet Subtropical Monsoon","authors":"Hang Wen, Si-Liang Li, Xi Chen, Caiqing Qin, Li Li","doi":"10.1029/2023wr035292","DOIUrl":"https://doi.org/10.1029/2023wr035292","url":null,"abstract":"Understanding the origins and processes of riverine dissolved inorganic carbon (DIC) is crucial for predicting the global carbon cycle with projected, more frequent climate extremes yet our knowledge has remained fragmented. Here we ask: <i>How and how much do DIC production and export vary across space</i> (<i>shallow vs</i>. <i>deep</i>, <i>uphill vs</i>. <i>depression</i>) <i>and time</i> (<i>daily</i>, <i>seasonal</i>, <i>and annual</i>)? <i>How do the relative contributions of biogenic</i> (<i>soil respiration</i>) <i>and geogenic</i> (<i>carbonate weathering</i>) <i>sources differ under different temperature and hydrological conditions</i>? We answer these questions using a catchment-scale reactive transport model constrained by stream flow, stable water isotopes, stream DIC, and carbon isotope data from a headwater karstic catchment in southwest China in a subtropical monsoon climate. Results show climate seasonality regulates the timing of DIC production and export. In hot-wet seasons, high temperature accelerates soil respiration and carbonate weathering (up to a factor of three) via elevating soil CO<sub>2</sub> and carbonate solubility, whereas high discharge enhances export by two orders of magnitude compared to cold-dry seasons. Carbonate weathering is driven more by soil CO<sub>2</sub> than water flow. At the annual scale, 92.9% and 7.1% of DIC was produced in shallow and deep zone, respectively, whereas 64.5% and 35.5% of DIC was exported from shallow and deep zone, respectively. These results highlight the uniqueness of subtropical karst areas as synchronous reactors and transporters of DIC during the hot-wet monsoon, contrasting the asynchronous production and export in other climate regions. A future hotter and wetter climate with more intensive storms in the region may further intensify DIC production and export, accentuating the potential of subtropical karst regions as global hot spots for carbon cycling.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"55 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139091281","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}
The rise in smart water technologies has introduced new cybersecurity vulnerabilities for water infrastructures. However, the implications of cyber-physical attacks on the systems like urban drainage systems remain underexplored. This research delves into this gap, introducing a method to quantify flood risks in the face of cyber-physical threats. We apply this approach to a smart stormwater system—a real-time controlled network of pond-conduit configurations, fitted with water level detectors and gate regulators. Our focus is on a specific cyber-physical threat: false data injection (FDI). In FDI attacks, adversaries introduce deceptive data that mimics legitimate system noises, evading detection. Our risk assessment incorporates factors like sensor noises and weather prediction uncertainties. Findings reveal that FDIs can amplify flood risks by feeding the control system false data, leading to erroneous outflow directives. Notably, FDI attacks can reshape flood risk dynamics across different storm intensities, accentuating flood risks during less severe but more frequent storms. This study offers valuable insights for strategizing investments in smart stormwater systems, keeping cyber-physical threats in perspective. Furthermore, our risk quantification method can be extended to other water system networks, such as irrigation channels and multi-reservoir systems, aiding in cyber-defense planning.
{"title":"Flood Risks of Cyber-Physical Attacks in a Smart Storm Water System","authors":"Chung-Yi Lin, Yi-Chen Ethan Yang, Faegheh Moazeni","doi":"10.1029/2023wr034827","DOIUrl":"https://doi.org/10.1029/2023wr034827","url":null,"abstract":"The rise in smart water technologies has introduced new cybersecurity vulnerabilities for water infrastructures. However, the implications of cyber-physical attacks on the systems like urban drainage systems remain underexplored. This research delves into this gap, introducing a method to quantify flood risks in the face of cyber-physical threats. We apply this approach to a smart stormwater system—a real-time controlled network of pond-conduit configurations, fitted with water level detectors and gate regulators. Our focus is on a specific cyber-physical threat: false data injection (FDI). In FDI attacks, adversaries introduce deceptive data that mimics legitimate system noises, evading detection. Our risk assessment incorporates factors like sensor noises and weather prediction uncertainties. Findings reveal that FDIs can amplify flood risks by feeding the control system false data, leading to erroneous outflow directives. Notably, FDI attacks can reshape flood risk dynamics across different storm intensities, accentuating flood risks during less severe but more frequent storms. This study offers valuable insights for strategizing investments in smart stormwater systems, keeping cyber-physical threats in perspective. Furthermore, our risk quantification method can be extended to other water system networks, such as irrigation channels and multi-reservoir systems, aiding in cyber-defense planning.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"71 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139091306","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}
Yuanning Zhang, Xueping Gao, Bowen Sun, Xiaobo Liu
Benthic oxygen flux with complex spatiotemporal variations is essential for the global budget of carbon dioxide and the regional security of water quality and ecology, but its dominant driver under different circumstances has yet to be identified. In this study, a parametric scheme of oxygen flux was proposed and validated with aquatic eddy correlation measurements and then coupled with a diagenesis model and a water environment model. The coupled model was applied to a river-reservoir with significant environmental gradients in hydrodynamics, diagenesis, and hypoxia, which are three factors that competitively drive the variation in benthic oxygen flux. The results indicate that hydrodynamics dominate the flux in the riverine and thalweg areas, diagenesis is the dominant driver of the lacustrine and bank areas, and hypoxia shows dominance only in the hypolimnetic anoxic area. In general, diagenesis is the dominant driver of oxygen flux in river-reservoirs, followed by hydrodynamics, both of which are more prominent than hypoxia. If the operated reservoir experiences a wet year, the dominance of hydrodynamics tends to increase, while that of diagenesis and hypoxia decreases. The three divers exhibit similar but more stable dominance in riverine systems than in reservoirs, while diagenesis becomes the exclusive driver of oxygen fluxes in lacustrine systems.
{"title":"Hydrodynamics, Diagenesis and Hypoxia Variably Drive Benthic Oxygen Flux in a River-Reservoir System","authors":"Yuanning Zhang, Xueping Gao, Bowen Sun, Xiaobo Liu","doi":"10.1029/2023wr035449","DOIUrl":"https://doi.org/10.1029/2023wr035449","url":null,"abstract":"Benthic oxygen flux with complex spatiotemporal variations is essential for the global budget of carbon dioxide and the regional security of water quality and ecology, but its dominant driver under different circumstances has yet to be identified. In this study, a parametric scheme of oxygen flux was proposed and validated with aquatic eddy correlation measurements and then coupled with a diagenesis model and a water environment model. The coupled model was applied to a river-reservoir with significant environmental gradients in hydrodynamics, diagenesis, and hypoxia, which are three factors that competitively drive the variation in benthic oxygen flux. The results indicate that hydrodynamics dominate the flux in the riverine and thalweg areas, diagenesis is the dominant driver of the lacustrine and bank areas, and hypoxia shows dominance only in the hypolimnetic anoxic area. In general, diagenesis is the dominant driver of oxygen flux in river-reservoirs, followed by hydrodynamics, both of which are more prominent than hypoxia. If the operated reservoir experiences a wet year, the dominance of hydrodynamics tends to increase, while that of diagenesis and hypoxia decreases. The three divers exhibit similar but more stable dominance in riverine systems than in reservoirs, while diagenesis becomes the exclusive driver of oxygen fluxes in lacustrine systems.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"10 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139091204","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：