Civil and Environmental Engineering

Editors' Note Volume 9 Issue 2

Magnetorheological elastomers (MREs) are smart composite materials with tunable mechanical properties by ferromagnetic particle interactions. This study applied the microstructure-based dipole and Maxwell methods to evaluate the magneto-mechanical coupling and magnetostrictive responses of MREs, focusing on various particle distributions. The finite element modeling of representative volume elements with fixed volume fractions revealed that the straight chain microstructure exhibits the most significant magnetostrictive effect due to its low initial shear stiffness and significant magnetic force contributions. For particle separations exceeding three radii, the dipole and Maxwell methods yield consistent results for vertically or horizontally aligned particles. For particle separations greater than three radii, the dipole and Maxwell methods produce consistent results for vertically and horizontally aligned particles. However, discrepancies emerge for angled configurations and complex microstructures, with the largest deviation observed in the hexagonal particle distribution, where the two methods differ by approximately 27%. These findings highlight the importance of selecting appropriate modeling methods for optimizing MRE performance. Since anisotropic MREs with straight-chain alignments are the most widely used, our results confirm that the dipole method offers an efficient alternative to the Maxwell method for simulating these structures.

Flood hazards pose a significant threat to communities and ecosystems alike. Triggered by various factors such as heavy rainfall, storm surges, or rapid snowmelt, floods can wreak havoc by inundating low-lying areas and overwhelming infrastructure systems. Understanding the feedback between local geomorphology and sediment transport dynamics in terms of the extent and evolution of flood-related damage is necessary to build a system-level description of flood hazard. In this research, we present a multispectral imagery-based approach to broadly map sediment classes and how their spatial extent and relocation can be monitored. The methodology is developed and tested using data collected in the Ahr Valley in Germany during post-disaster reconnaissance of the July 2021 Western European flooding. Using uncrewed aerial vehicle-borne multispectral imagery calibrated with laboratory-based soil characterization, we illustrate how fine and coarse-grained sediments can be broadly identified and mapped to interpret their transport behavior during flood events and their role regarding flood impacts on infrastructure systems. The methodology is also applied to data from the 2022 flooding of the Yellowstone River, Gardiner, Montana, in the United States to illustrate the transferability of the developed approach across environments. Here, we show how the distribution of soil classes can be mapped remotely and rapidly, and how this facilitates understanding their influence on local flow patterns to induce bridge abutment scour. The limitations and potential expansions to the approach are also discussed.

UNLABELLED: Alongside global climate change, many freshwater ecosystems are experiencing substantial shifts in the concentrations and compositions of salt ions coming from both land and sea. We synthesize a risk framework for anticipating how climate change and increasing salt pollution coming from both land and saltwater intrusion will trigger chain reactions extending from headwaters to tidal waters. Salt ions trigger chain reactions, where chemical products from one biogeochemical reaction influence subsequent reactions and ecosystem responses. Different chain reactions impact drinking water quality, ecosystems, infrastructure, and energy and food production. Risk factors for chain reactions include shifts in salinity sources due to global climate change and amplification of salinity pulses due to the interaction of precipitation variability and human activities. Depending on climate and other factors, salt retention can range from 2 to 90% across watersheds globally. Salt retained in ecosystems interacts with many global biogeochemical cycles along flowpaths and contributes to fast and slow chain reactions associated with temporary acidification and long-term alkalinization of freshwaters, impacts on nutrient cycling, CO2, CH4, N2O, and greenhouse gases, corrosion, fouling, and scaling of infrastructure, deoxygenation, and contaminant mobilization along the freshwater-marine continuum. Salt also impacts the carbon cycle and the quantity and quality of organic matter transported from headwaters to coasts. We identify the double impact of salt pollution from land and saltwater intrusion on a wide range of ecosystem services. Our salinization risk framework is based on analyses of: (1) increasing temporal trends in salinization of tributaries and tidal freshwaters of the Chesapeake Bay and freshening of the Chesapeake Bay mainstem over 40 years due to changes in streamflow, sea level rise, and watershed salt pollution; (2) increasing long-term trends in concentrations and loads of major ions in rivers along the Eastern U.S. and increased riverine exports of major ions to coastal waters sometimes over 100-fold greater than forest reference conditions; (3) varying salt ion concentration-discharge relationships at U.S. Geological Survey (USGS) sites across the U.S.; (4) empirical relationships between specific conductance and Na+, Cl-, SO4 2-, Ca2+, Mg2+, K+, and N at USGS sites across the U.S.; (5) changes in relationships between concentrations of dissolved organic carbon (DOC) and different salt ions at USGS sites across the U.S.; and (6) original salinization experiments demonstrating changes in organic matter composition, mobilization of nutrients and metals, acidification and alkalinization, changes in oxidation-reduction potentials, and deoxygenation in non-tidal and tidal waters. The interaction of human activities and climate change is altering sources, transport, storage, and reactivity of salt ions and chain reactions along the entire freshwater-marine continuum. Our salinization risk framework helps anticipate, prevent, and manage the growing double impact of salt ions from both land and sea on drinking water, human health, ecosystems, aquatic life, infrastructure, agriculture, and energy production. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10533-025-01219-6.

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Supplementary information

The feedback of topsoil moisture (SM) content on convective clouds and precipitation is not well understood and represented in the current generation of weather and climate models. Here, we use functional decomposition of satellite-derived SM and cloud vertical profiles (CVP) to quantify the relationship between SM and the vertical distribution of cloud water in the central US. High-dimensional model representation is used to disentangle the contributions of SM and other land-surface and atmospheric variables to the CVP. Results show that the sign and strength of the SM-cloud-precipitation feedback varies with cloud height and time lag and displays a large spatial variability. Positive anomalies in antecedent 7-hr SM and land-surface temperature enhance cloud reflectivity up to 4 dBZ in the lower atmosphere about 1-3 km above the surface. Our approach presents new insights into the SM-cloud-precipitation feedback and aids in the diagnosis of land-atmosphere interactions simulated by weather and climate models.

Abstract: Huang and Merwade (2023), https://doi.org/10.1029/2023wr034947, hereafter conveniently referred to as HM23, wrongly claim improvement of their method for postprocessing multi‐model water stage predictions using Bayesian Model Averaging (BMA). Their results show all signs of a flawed implementation of the Metropolis algorithm. In this comment I will point out the many mistakes and shortcomings of the BMA methodology of HM23. Their method is deficient, inefficient and ineffective and wrongly quantifies BMA model parameter and predictive uncertainty. Furthermore, HM23 misrepresent BMA literature, articulate a poor understanding of Markov chain Monte Carlo methods and misuse the autocorrelation function for monitoring convergence of the sampled Markov chains. A proper implementation of the random walk Metropolis algorithm would have led HM23 to substantially different results and findings about their ensemble of water stage predictions. The MODELAVG toolbox of Vrugt (2018) https://www.researchgate.net/publication/299458373_MODELAVG_A_MATLAB_Toolbox_for_Postprocessing_of_Model_Ensembles satisfies all requirements of HM23 and provides robust estimates of BMA model parameter and prediction uncertainty for symmetric, skewed and truncated conditional forecast distributions of the ensemble members.

In this paper, a state-space method for double-beam systems with variable cross sections is developed, making it possible to calculate the transverse vibration of the double-beams accurately and effectively. Due to the variability in the double-beam cross sections with the viscoelastic interlayer in between, the governing equations of vibration for the systems become highly coupled partial differential equations, making the problem difficult to solve. A basic double-beam system is introduced to modify the original governing equations to two inhomogeneous differential equations. Given the separation of variables, several mode-shape coefficients and a state variable are defined to construct the state-space equations. The coupling terms and variables are transferred into the constant coefficient matrix of the state-space equations, decoupling them. Numerical procedures are presented to solve the state-space equations to obtain homogenous and inhomogeneous solutions, including the natural frequencies and mode shapes in free vibration and the dynamic responses in forced vibration, respectively. The method has substantial advantages in decoupling high-order partial differential equations and can be further extended to solve complex structural systems. Numerical results also demonstrate that the method is accurate and efficient. Finally, an engineering application with a rail-bridge with a floating slab track is discussed in detail with the method.