Advances in Water Resources最新文献

Climate change poses significant challenges for decision-making processes across a range of sectors. From the water resources planning and management perspective, the interest is often in evaluating the performance of a water supply system in a future state considering the potential changes in rainfall and streamflow characteristics. With observed climate change signals, scenario-based projections of rainfall and streamflow simulations are crucial for evaluating the potential impacts of climate change on water resource systems. Given the complexity of the existing approaches, their applications for generating scenario-based projections of streamflow and rainfall are limited. We developed a non-parametric bootstrapping approach, NPScnGen, for future scenario generation of any hydroclimatic variable. The developed approach is flexible and can be used with any physical hydrological or data-driven stochastic model that provides simulations of hydroclimatic variables of interest for the historical climate condition. In NPScnGen, samples of any set of time-series characteristics, such as mean and standard deviation, are generated from a multivariate Gaussian process for the considered scenario, and then bootstrapping is performed to select the closest sample from the historical simulation of that hydroclimatic variable. We have also proposed a modified wavelet-based model, Wavelet-HMM, and used that model to synthetically generate historical climate time-series as a baseline. We present the application of the developed framework consisting of historical climate simulation and future climate projection approaches on rainfall and streamflow datasets for the Tampa Bay region in Florida.

Plain Language Summary: Water resources managers require a wide range of hypothetical but potential changes in hydroclimatic variables such as streamflow and rainfall to evaluate the sustenance of water supply systems in future. Existing scenario generation approaches are limited by either the complexity of statistical models or dependency on climate models which have their own limitations. In such a scenario, the developed non-parametric scenario generation framework in this study, NPScnGen, can be very useful. The developed framework can be applied with any sophisticated time-series generation model that can generate synthetic hydroclimatic traces for baseline climate condition, and it is also flexible in generating a wide range of potential climate change scenarios. We show the application of the framework on both streamflow and rainfall datasets.

Knowledge of the parameterization of the dry surface layer (DSL) is essential for evaluating near-surface water flow and water balance in arid and semi-arid areas. Existing studies have parameterized DSL thickness and vapor flow as functions of the soil moisture content (SMC) in the surface layer to predict soil evaporation. However, hydrochemical processes related to DSL development have been ignored, including changes in hydrochemistry, the underlying hydrochemical mechanism, and the role of dissolved substances in the DSL development. Herein, we performed a series of soil evaporation experiments for 260 days and explored the factors influencing DSL development (e.g., soil texture, atmospheric temperature, SMC, solutes). Evaporation experiments were performed using silty loess, sandy loess, and fine sand with a 60-cm water table. Results showed that the cumulative evaporation of silty loess, sandy loess, and fine sand over the experimental period were 1,391.52, 460.10, and 185.53 mm, respectively, which determined by the maximum height of liquid flow continuity. The content of total dissolved solids (TDS) and major ions at the surface soil were significantly higher than the values at deep depths of 5‒55 cm, which largely depend on evaporative water loss. Evolutionary trends of chemical facies in sand media along the liquid water migration were from HCO₃-Ca type to SO₄·Cl-Na type. This was attributed to mineral dissolution at a depth of 5–55 cm and their transport with liquid water, resulting in the precipitation of salt crystals at the surface soil. Furthermore, a consolidated DSL with a thickness of 3.0–3.5 cm in the sandy loess and a loose DSL with a thickness of 1.5–2.0 cm in fine sand were observed at the end of the experiments. The accumulation of solutes at the surface leads to a reduction in effective porosity and the aggregation of soil particles during continuous drying, which facilitates the consolidation of DSL in sandy loess. This overestimated the DSL thickness, resulting in a difference between the experimental and predicted evaporation rates by Fick's law. Overall, these results highlight the limitations of considering DSL thickness as a function of SMC only, providing new insights into hydrochemical processes and dissolved solutes involving DSL parameterization during continuous soil drying.

An accurate assessment of the hydraulic properties of aquifers is required to represent groundwater flow and solute transport. This study investigates periodic hydraulic tomography performed between wells to obtain accurate images of hydraulic properties. Tomographic experiments with different period and amplitude of sinusoidal test flow, hydraulic properties and well configurations were simulated with a numerical flow model. An l-curve analysis of the obtained heads and sensitivities identified the optimal parameter resolution and served as a basis for comparing the experiments. The results show that the transient phase of signals with short periods provides the most information about the resolution of the aquifer. The resolution could be further improved if tests with different periods were properly combined in the analysis. The study concludes that periodic tomography provides valuable insight into the spatial resolution of hydraulic conductivity and its vertical anisotropy and specific storage, but the choice of signal characteristics is critical.

This paper presents a unified, embedded finite element formulation for simulating transient fluid flow in fractured porous media while accounting for transverse and longitudinal directions. The transverse flow arises due to pressure variations on both sides of fractures, as these typically exhibit lower permeability in the perpendicular direction. A simple coupling framework is introduced to connect independent sets of finite element meshes, one for the bulk porous media and the other for natural discontinuities. Importantly, the proposed coupling technique does not introduce additional degrees of freedom, and discontinuities can arbitrarily intersect the background elements of the continuum domain. Additionally, standard quadrature rules for integration can be used without modifications, thus avoiding additional remediation steps found with nodal enrichment strategies. These advantageous features make our method a robust technique capable of modelling transient fluid flow as an integral part of a coupled hydro-mechanical formulation. The performance is assessed using several numerical examples. These encompass various cases of fracture orientation relative to the background elements. The results demonstrate a good agreement with reference solutions. The effects of the coupling parameter, as well as the transverse and longitudinal permeabilities, in the temporal domain, are also investigated. The results demonstrated that the proposed method is capable of handling any values of transverse or longitudinal permeability compared to the surrounding porous domain. Moreover, the findings confirmed that, as a rule of thumb, a coupling parameter should be selected 10 times larger than the highest permeability used in the model.

This work provides a new formulation of the one-dimensional augmented Shallow Water Equations system for open channels and rivers with arbitrarily shaped cross sections, suitable for numerical integration when discontinuous geometry is encountered. The additional variable considered can be the bottom elevation, a reference width, a shape coefficient, or a vector containing these or other geometric parameters. The appropriate numerical method, which is well suited to coupling with the mathematical one, is a path-conservative method, capable of reconstructing the behaviour of physical and geometrical variables at the cell boundaries, where the discrete solution of hyperbolic systems of equations is discontinuous. A nonlinear path suitable for the shallow water context is adopted. The resulting model is shown to be well-balanced and accurate to the second order and is further validated against analytical solutions related to channels with power-law cross-sections, specifically for dam break patterns over a variable-width channel and the run-up dynamics of long water waves over sloping bays.

Understanding multiphase flow in fractures filled with minerals and proppants is vital in various subsurface applications. Limited experimental data have led to reliance on correlations lacking physical basis. We conducted experiments to characterize relative permeability in rough-walled fractures packed with unconsolidated porous media. We tested fractures packed with water-wet 40/70 sand (silica) and surface-coated ceramic proppants. Brine and mineral oil were used as the wetting and non-wetting fluid phases, respectively. Steady-state (SS) drainage (non-wetting-phase displacing wetting-phase) and imbibition (wetting-phase displacing non-wetting-phase) tests were performed under a wide range of saturation histories (full-cycle and scanning-curves) to study relative permeability hysteresis of the propped fractures. Every SS drainage or imbibition test consisted of several discrete points at which fluid saturations and the corresponding relative permeability were measured by varying the fractional flow rates of fluids whilst maintaining a constant total flow rate. We analyzed residual non-wetting phase saturations and relative permeability trends to understand two-phase flow behavior in each proppant pack. High-resolution x-ray microtomography was used to understand the pore-scale topology, wettability, and to provide insights about the pore-scale displacement mechanisms involved in this study. The results showed that commonly used models to estimate relative permeabilities of fractures significantly overestimated the SS brine and oil relative permeabilities (denoted as k_rw and k_ro) measured in this study. Further analysis unveiled that the k_ro values during imbibition exceeded their drainage counterparts in both proppants, the ceramic proppant exhibited a lower initial water saturation and a higher end-point k_ro permeability at the end of the drainage displacement, as well as higher k_rw across all flooding processes. Updated fitting parameters for a Brooks-Corey-type relative permeability correlation are introduced. This study presents improved insights, extensive experimentally generated relative permeability data, and an updated relative permeability correlation, which can be collectively utilized to reduce uncertainties associated with continuum-scale forecasts of multiphase flow behavior in fractured subsurface formations.

Characterizing groundwater flow parameters is crucial for understanding complex aquifer systems, and inverse techniques play a fundamental role in modeling hydrogeological parameters and assessing their uncertainties. Nonetheless, the use of a forward model in these methods can be highly time-consuming, especially with an increasing number of model parameters. To address this issue, we propose a surrogate model based on a U-Net architecture that replaces the transient groundwater flow model, reducing runtime and enabling a fast quantification of uncertainties related to key parameters, including heterogeneous hydraulic conductivity, boundary conditions, specific storage, and pumping rate. The surrogate is trained using limited evaluations of the forward model to learn the physical relationship between hydraulic conductivity fields and transient hydraulic heads measured on-site. The physical principles of the studied problem, including boundary conditions, specific storage, and source terms, are also mapped and introduced as inputs to the model to enhance its understanding of the governing equation of transient groundwater flow. To speed up learning using image–image regression, the previously predicted transient hydraulic heads also serve as an input to predict the transient heads at the current time step. Once the model is trained, we use a spectral geostatistical method to solve the inverse problem, a pumping test of 12 h, using the surrogate model in place of the forward model. Our study demonstrates that the trained U-Net accurately reproduces the state variables corresponding to a specific parameter field, and in terms of computational demand, using U-Net as a surrogate model reduces the required computational time by approximately an order of magnitude for the defined problem. The proposed approach offers an efficient and accurate method for groundwater flow parameter characterization and uncertainty quantification in complex aquifer systems.

In this study, we investigated the effect mechanism of the grain material of artificial porous media coating quartz sand (SiO₂), titanium dioxide (n-TiO₂), zinc oxide (ZnO) and polystyrene (PS) on the motion and deposition of suspended particles. First, the relationship was deeply analysed between the DLVO potential energy and the physico-chemical properties of grain material, including the Hamaker constant and surface zeta potential. Second, the lattice Boltzmann method-immersed moving boundary-discrete element method (LBM-IMB-DEM) was used to investigate the motion characteristics of suspended particles and their effects, including the penetration rate, deposition rate, porosity reduction and the porosity-permeability relations. Third, the relations were innovatively explained between the energy barrier and the particles bridging and bridge collapse which cause the fluctuation of permeability reduction. The main results are as follows. (1) The descending order of the energy barrier between suspended particle and grain material is SiO₂, ZnO, PS and n-TiO₂, which is the same as that of the surface zeta potential of grain material. (2) For the suspended particles with the same size, the higher potential energy and Primary energy minimum (PEM) enhance the penetration rate. The particle deposition rate in porous media coating n-TiO₂ is higher than others. (3) The highest non-uniformity of the porosity reduction occurs in the porous media coating the material with the lowest energy barrier. (4) For the grain material with lower energy barrier, the fluctuation frequency of permeability reduction is lower owing to the longer bridging time.

Physics-informed neural networks (PINNs) have received great attention as a promising paradigm for forward, inverse, and surrogate modeling of various physical processes with limited or no labeled data. However, PINNs are rarely used to predict two-phase flow in heterogeneous and fractured porous media, which is critical to lots of subsurface applications, due to the significant challenges in their training. In this work, we present an Enriched Physics-Informed Neural Network (E-PINN) to overcome these barriers and realize the simulation of such flow. Specifically, the Embedded Discrete Fracture Model (EDFM) is adopted to explicitly represent fractures, and then the finite volume method (FVM) instead of the Automatic Differentiation (AD) is used to evaluate spatial derivatives and construct the physics-informed loss function, so that the flux continuity between neighboring elements with different properties (e.g. matrix and fracture) can be defined rigorously. Besides, we develop a novel physics-informed neural network (NN) architecture adopting the adjacency-location anchoring, adaptive activation function, skip connection and gated updating to enrich the pressure information and enhance the learning ability of NN. Additionally, the initial and boundary conditions are constrained through a hard approach, which encodes them into network design, to improve the accuracy and efficiency of network training. In order to further reduce the difficulty of training, the Implicit-Pressure Explicit-Saturation (IMPES) scheme is used to calculate pressure and saturation, in which only the pressure needs to be solved by training NN. Finally, the superiority and applicability of E-PINN to complex practical problems is demonstrated through the simulations of immiscible displacement in 2D/3D heterogeneous and fractured reservoirs.

The evolution of fluvial systems is greatly impacted by mid-channel bars, a typical morphodynamic process in natural rivers. Sometimes, the growth of vegetation over these bars complicates the morphological behaviour by interacting with the flow. It is therefore necessary to have a fundamental interpretation of the flow-turbulence structure around the mid-bar in presence of vegetation cover in order to understand braiding dynamics, still studies in this area are scarce. The present study investigates the process-form-vegetation-interaction through experimental investigation at a flume scale mid-channel bar model with different natural vegetation cover arrangements (paddy, leafy, and rigid stem). The flow-turbulence behaviour has been observed through the bifurcated channel using the three-dimensional Acoustic Doppler Velocimeter (ADV). Results showed that the longitudinal velocity component varies with the different vegetation cover, and it was highest with leafy vegetation (about 32%). Similarly, the Reynolds Stress and Turbulence Intensity were also observed to be higher in case of leafy vegetation. A unique pattern of flow-turbulence parameters was observed near the bar level, the lower canopy level, and the upper canopy level. Moreover, it was found that vegetation structure and its flexible nature influence both longitudinal velocity reduction and momentum transfer at and over the canopy, as well as the thickness of the shear layer region.