Advances in Water Resources最新文献

{"title":"In search of non-stationary dependence between estuarine river discharge and storm surge based on large-scale climate teleconnections","authors":"Georgios Boumis ,&nbsp;Hamed R. Moftakhari ,&nbsp;Danhyang Lee ,&nbsp;Hamid Moradkhani","doi":"10.1016/j.advwatres.2024.104858","DOIUrl":"10.1016/j.advwatres.2024.104858","url":null,"abstract":"<div><div>Compound floods may happen in low-lying estuarine environments when sea level above normal tide co-occurs with high river flow. Thus, comprehensive flood risk assessments for estuaries should not only account for the individual hazard arising from each environmental variable in isolation, but also for the case of bivariate hazard. Characterization of the dependence structure of the two flood drivers becomes then crucial, especially under climatic variability and change that may affect their relationship. In this article, we demonstrate our search for evidence of non-stationarity in the dependence between river discharge and storm surge along the East and Gulf coasts of the United States, driven by large-scale climate variability, particularly El-Niño Southern Oscillation and North Atlantic Oscillation (NAO). Leveraging prolonged overlapping observational records and copula theory, we recover parameters of both stationary and dynamic copulas using state-of-the-art Markov Chain Monte Carlo methods. Physics-informed copulas are developed by modeling the magnitude of dependence as a linear function of large-scale climate indices, i.e., Oceanic Niño Index or NAO index. After model comparison via suitable Bayesian metrics, we find no strong indication of such non-stationarity for most estuaries included in our analysis. However, when non-stationarity due to these climate modes cannot be neglected, this work highlights the importance of appropriately characterizing bivariate hazard under non-stationarity assumption. As an example, we find that during a strong El-Niño year, Galveston Bay, TX, is much more likely to experience a coincidence of abnormal sea level and elevated river stage.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"195 ","pages":"Article 104858"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142793907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Investigating Steady Unconfined Groundwater Flow using Physics Informed Neural Networks” [Advances in Water Resources Volume 177 (2023), 104445]","authors":"Mohammad Afzal Shadab ,&nbsp;Dingcheng Luo ,&nbsp;Eric Hiatt ,&nbsp;Yiran Shen ,&nbsp;Marc Andre Hesse","doi":"10.1016/j.advwatres.2024.104886","DOIUrl":"10.1016/j.advwatres.2024.104886","url":null,"abstract":"","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"195 ","pages":"Article 104886"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142902112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relating flow resistance to equivalent roughness","authors":"Octavia Crompton ,&nbsp;Gabriel Katul ,&nbsp;Sally E. Thompson","doi":"10.1016/j.advwatres.2024.104855","DOIUrl":"10.1016/j.advwatres.2024.104855","url":null,"abstract":"<div><div>Describing flow resistance using the physical properties of an underlying surface is a recalcitrant problem in overland flow models. If discharge measurements are available, an equivalent roughness (e.g., Manning’s <span><math><mi>n</mi></math></span>) can be calibrated to represent the effects of surface properties within the domain with a single numerical value. Alternatively, the flow resistance can be estimated from discharge and velocity measured at a point, typically a runoff plot outlet. However, such experimental estimates are often inconsistent with the equivalent roughness determined from calibration to discharge, even if both derive from the same dataset. For example, if Manning’s equation is used to parameterize flow resistance, the Manning’s <span><math><mi>n</mi></math></span> obtained by calibrating a model to discharge differs from the value of <span><math><mi>n</mi></math></span> calculated from measured flow and velocity at the hillslope outlet.</div><div>Here, this discrepancy is resolved by deriving a correction factor relating experimentally-determined flow resistance to the equivalent roughness. The derived correction factor is tested for four commonly-used resistance formulations using 129 rainfall simulator experiments. The correction factor is necessary to reproduce measured velocities, and yields minor improvements in discharge prediction.</div><div><strong>Plain Language Summary</strong></div><div>Accurate runoff prediction is needed for land and water management in dryland regions, where sporadic and limited rainfall necessitate efficient water use and drought mitigation strategies. The skill of runoff models is known to be hindered by out ability to estimate flow resistance, which is the quantity that describes how energy is lost from flowing water to the underlying surface. Typically, models represent flow resistance with an equivalent roughness, e.g., Manning’s <span><math><mi>n</mi></math></span>, that is adjusted until the model can reproduce available discharge observations at watershed scale. However, the flow resistance measured in plot-scale experiments (1–10 m) often exceeds equivalent roughness coefficients by a factor of 10. This means that the direct use of plot-scale experimental data to parameterize runoff models could cause errors in discharge and runoff velocity predictions.</div><div>Here, we resolve these differences by deriving an analytic correction factor that relates flow resistance to the equivalent roughness required for models to reproduce experimental velocity and discharge data. This correction factor is tested using rainfall simulator data from 129 experiments performed in the US Southwest covering a wide range of precipitation intensities, soil textures and vegetation types. Use of the correction factor substantially improves model prediction of flow velocity, which is needed for reproducing the timing of flood events and the estimation of erosion.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"195 ","pages":"Article 104855"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical analysis of solute transport and longitudinal dispersion coefficients in vegetated flow","authors":"Chenhao Zhang ,&nbsp;Mingliang Zhang","doi":"10.1016/j.advwatres.2024.104854","DOIUrl":"10.1016/j.advwatres.2024.104854","url":null,"abstract":"<div><div>Reasonable estimates of longitudinal dispersion coefficients are essential for predicting solute dispersion processes. However, the current knowledge of solute dispersion processes in vegetated waters is limited. In this work, we coupled a refined hydrodynamic model with scalar transport equations to simulate the flow field and dispersion process of solutes in water under the effect of vegetation. First, the proposed numerical model was verified using laboratory experiments, revealing the excellent performance of the coupled model in complex conditions. Eight different cases were subsequently simulated to analyse the effects of the upstream flow rate and vegetation height on the streamwise velocity, solute concentration, and longitudinal dispersion coefficients. The simulation results show that the upstream flow variation exerts a marked effect on the streamwise velocity and flow field within the vegetation zone, with a velocity difference within the shear layer reaching 54.7 % for an upstream flow of 0.018 m³·s^-1. The height of the vegetation affects both the velocity profile and solute dispersion. Placing emergent vegetation upstream can enhance solute dispersion in the longitudinal direction. The correlation analysis reveals that the longitudinal dispersion coefficients obtained using the routing producer are close to those determined using the theoretical method, with correlation coefficients reaching 0.75. This work presents the appropriate application range and parameters that must be considered in deriving formulas for longitudinal dispersion coefficients.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"194 ","pages":"Article 104854"},"PeriodicalIF":4.0,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermodynamically consistent interfacial curvatures in real pore geometries: Implications for pore-scale modeling of two-phase displacement processes","authors":"Yanbin Gong ,&nbsp;Bradley William McCaskill ,&nbsp;Mohammad Sedghi ,&nbsp;Mohammad Piri ,&nbsp;Shehadeh Masalmeh","doi":"10.1016/j.advwatres.2024.104853","DOIUrl":"10.1016/j.advwatres.2024.104853","url":null,"abstract":"<div><div>In conventional Pore-network Modeling (PNM) approaches, fluid flow and transport are solved in a network of pore elements with idealized geometries. Such simplification can lead to inaccurate predictions when the original pore space features complex geometries. To overcome this limitation, this study introduces a novel workflow that integrates four key components: (i) an enhanced pore network extraction (PNE) platform capable of identifying and extracting pore cross-sections from high-resolution micro-computed tomography (micro-CT) images of the pore space, (ii) a computationally-efficient semi-analytical model that can faithfully predict capillary entry pressure and the corresponding fluid configuration of piston-like displacements using real two-dimensional cross-sections of pores, (iii) a PNM approach for two-phase flow modeling that utilizes the capillary entry pressure of pores predicted by the semi-analytical model, and (iv) an Artificial Intelligence (AI)-driven model that paves the way for future advancements in efficiently predicating fluid displacement properties in intricate pore structures. To validate this new workflow, we constructed various pore networks containing real pore and throat cross-sections over a diverse group of sandstone and carbonate rock samples. Subsequently, we simulate capillary pressure curves of Mercury Intrusion Capillary Pressure (MICP) and oil–water primary drainage displacements in Bentheimer and Berea sandstones, respectively, using both the conventional and enhanced PNM approaches. The latter demonstrated improved prediction accuracy compared to conventional methods. Next, primary drainage simulations are conducted for two carbonates, and the resulting capillary pressure curves from both PNM approaches are compared. In addition, we conduct an in-depth analysis of fourteen geometric features of the pore space, identifying key factors of hydraulic radius, circumradius, sphericity, and area, that significantly impact capillary entry pressure of pores. After that, we construct an Artificial Neural Network (ANN) to predict the capillary entry pressure of pores using their critical geometric features. This AI model, trained using data derived from the semi-analytical model, exhibits excellent predictive accuracy (with a R2 of 0.995 for the test data set) in estimating capillary entry pressure of pores. Overall, our newly proposed, integrated workflow represents a significant step forward in the field of digital rock technology (DRT), offering an accurate and efficient method for modeling fluid flow in rock samples with complex pore geometries.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"194 ","pages":"Article 104853"},"PeriodicalIF":4.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142696913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fully implicit bound-preserving discontinuous Galerkin algorithm with unstructured block preconditioners for multiphase flows in porous media","authors":"Jiali Tu ,&nbsp;Haijian Yang ,&nbsp;Rongliang Chen ,&nbsp;Li Luo","doi":"10.1016/j.advwatres.2024.104844","DOIUrl":"10.1016/j.advwatres.2024.104844","url":null,"abstract":"<div><div>Massively parallel simulation of multiphase flows in porous media is challenging due to the highly nonlinear governing equations with the complexity of various modeling features and the significant heterogeneity of material coefficients. In this paper, we introduce a fully implicit discontinuous Galerkin (DG) reservoir simulator designed for parallel computers to handle large-scale multiphase flow simulations. Our approach formulates a fully implicit DG scheme on 3D unstructured grids to discretize the nonlinear governing equations, which take into account capillary effects, permeability heterogeneity, gravity, and injection/production wells. A vertex-based slope limiter within the fully implicit DG framework is adopted to suppress oscillations near discontinuities and ensure the boundedness of the solution. We address the resulting nonlinear systems from the fully implicit discretization using a family of inexact Newton–Krylov algorithms with an analytic Jacobian. Moreover, we employ an unstructured block-type preconditioner with an efficient overlapping additive Schwarz approximation to accelerate the convergence of iterations and enhance the scalability of the simulator. Large-scale simulations of both benchmark and realistic reservoir problems on 3D unstructured grids are conducted to demonstrate the efficiency and scalability of the proposed reservoir simulator.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"194 ","pages":"Article 104844"},"PeriodicalIF":4.0,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling air sparging analysis in flow cells through the continuum approach","authors":"Ilan Ben-Noah","doi":"10.1016/j.advwatres.2024.104841","DOIUrl":"10.1016/j.advwatres.2024.104841","url":null,"abstract":"<div><div>We present various analytical solutions for a two-dimensional steady air source that demonstrate classical flow physics’ usefulness in air-sparging evaluation. These solutions capture different flow geometry and setup effects while offering accuracy, speed, and a deeper understanding of governing physics. Compared to empirical models, they excel with fewer physical parameters. We validate their accuracy by comparing these solutions to experimental air-sparging data from two-dimensional flow cells. This comparison underscores the applicability of the physical model and establishes a relationship between grain size and a key model parameter. Furthermore, this analysis enables predictive capabilities for scaled-up systems with diverse setup geometries.</div><div><strong>Plain Language Summary</strong> Air-sparging refers to the injection of air below the groundwater table, that is, to the water-saturated section of the aquifer. Air-sparging is used to facilitate the volatilization of organic pollutants (e.g., solvents, gasoline) and their extraction to the soil surface. However, evaluating and modeling the flow and distribution of air is limited by the complicated physics of unstable multiphase flow. These complexities drive researchers to search for empirical relations and rules of thumb to design air-sparging systems. In this research, we use previously published experimental data to demonstrate the capabilities and discuss the limitations of the classical physical solutions of steady single-phase flow to evaluate air flow through wet porous media such as aquifers.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"194 ","pages":"Article 104841"},"PeriodicalIF":4.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sub-daily precipitation returns levels in ungauged locations: Added value of combining observations with convection permitting simulations","authors":"Giuseppe Formetta ,&nbsp;Eleonora Dallan ,&nbsp;Marco Borga ,&nbsp;Francesco Marra","doi":"10.1016/j.advwatres.2024.104851","DOIUrl":"10.1016/j.advwatres.2024.104851","url":null,"abstract":"<div><div>Extreme rainfall events trigger natural hazards, including floods and debris flows, posing serious threats to society and the economy. Accurately quantifying extreme rainfall return levels in ungauged locations is crucial for improving flood protection infrastructure and mitigating water-related risks. This paper quantifies the added value of combining rainfall observations with Convection Permitting Model (CPM) simulations to estimate sub-daily extreme rainfall return levels in ungauged locations. We assess the performance of CPM-informed estimates of extreme return level against a traditional interpolation techniques. We find that kriging methods with external drift outperform inverse distance weighting for both traditional and CPM-informed approaches. We then assess the effectiveness of the two methods under different scenarios of station density. At the highest station density (1/196 km²), traditional interpolation methods outperform the CPM-informed method for durations under 6 h. The performance becomes comparable between 6 and 24 h. For lower station densities (1/400 and 1/800 km²), the CPM-informed method outperforms the traditional method, with average reductions in fractional standard error of 24 %, 13 %, and 8 % for return periods of 2, 10 and 50 years, respectively for a rain gauge density of 1/800 km², and 16 %, 8 %, and 3 % for density of 1/400 km². Information from CPM simulations can thus be useful for estimating sub-daily extreme rainfall events in ungauged sites, particularly in data-scarce areas in which the density of rain gauges is low.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"194 ","pages":"Article 104851"},"PeriodicalIF":4.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing parameter estimation in hydrological models with convolutional neural network guided dynamically dimensioned search approach","authors":"Ashlin Ann Alexander ,&nbsp;D. Nagesh Kumar","doi":"10.1016/j.advwatres.2024.104842","DOIUrl":"10.1016/j.advwatres.2024.104842","url":null,"abstract":"<div><div>Hydrological model calibration plays a crucial role in estimating optimal parameters for accurate simulation. Estimation of parameters is inevitable in hydrological modeling due to the challenge of directly measuring them, as most parameters are conceptual descriptions of physical processes. Modelers commonly employ optimization algorithms for calibrating hydrological models. However, these algorithms often pose computational challenges, especially when dealing with complex physics-based and distributed models. To address these challenges, our study introduces a novel approach called hydroCNN+DDS. By leveraging the strengths of Convolutional Neural Networks (CNN) and the Dynamically Dimensioned Search (DDS) algorithm, hydroCNN+DDS simplifies the model calibration process in complex physics-based models. This approach enables to capture the general patterns and relationships between discharge time series and parameters without compromising the underlying physics. We use hydroCNN+DDS to estimate parameters in the highly parameterized hydrological model, Structure for Unifying Multiple Modeling Alternatives (SUMMA) using hourly observed discharge. Notably, hydroCNN quickly generates sub-optimal parameters, serving as a good initial solution for DDS. This initialization aids DDS in converging faster towards an optimal solution. One of the notable advantages of the hydroCNN+DDS approach is its potential for spatial and temporal transferability. This feature proves valuable in dynamic systems and regions with limited historical data, expanding the applicability of the methodology. Furthermore, our proposed methodology is versatile and can be applied to any simple or complex models, accommodating any variables of interest. The best practices of good model calibration are followed in our approach.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"194 ","pages":"Article 104842"},"PeriodicalIF":4.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards improved understanding of spontaneous imbibition into dry porous media using pore-scale direct numerical simulations","authors":"Luka Malenica,&nbsp;Zhidong Zhang,&nbsp;Ueli Angst","doi":"10.1016/j.advwatres.2024.104840","DOIUrl":"10.1016/j.advwatres.2024.104840","url":null,"abstract":"<div><div>Traditional approaches to mathematically describe spontaneous imbibition are usually based on either macro-scale models, such as Richards equation, or simplified pore-scale models, such as the bundle of capillary tubes (BCTM) or pore-network modeling (PNM). It is well known that such models cannot provide full microscopic details of the multiphase flow processes and that many pore-scale mechanisms still lack proper mathematical descriptions. To improve the predictive capabilities of traditional models, a fundamental understanding of pore-scale dynamics is needed. The focus of this paper is obtaining detailed insight and consistent explanation of particular processes during capillary-controlled water imbibition into dry porous media. We use two-dimensional model geometries and perform fully dynamic volume-of-fluid based direct numerical simulations of air–water multiphase flow at the pore-scale, to study processes that generally are not considered in traditional models. More specifically, we investigate differences between converging and diverging geometries, dynamic pressure and meniscus reconfiguration during pore-filling events, and the influence of inertia and pore size on imbibition dynamics and the occurrence of capillary barriers. Furthermore, we perform a detailed comparison between non-interacting and interacting BCTM and study the impact of the narrow contractions on imbibition dynamics and the trapping of the non-wetting phase. Obtained knowledge can be used to improve predictive models, which are broadly relevant considering the importance of spontaneous imbibition in many different natural and industrial processes.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"194 ","pages":"Article 104840"},"PeriodicalIF":4.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}