Abstract: Salt marshes are among the most important coastal wetlands and provide critical ecological services, including climate regulation, biodiversity maintenance, and blue carbon sequestration. However, most salt marshes worldwide are shrinking, owing to the effects of natural and human factors, such as climate change and artificial reclamation. Therefore, it is essential to understand the decline in the morphological processes of salt marshes, and accordingly, the likely evolution of these marshes, in order to enable measures to be taken to mitigate this decline. To this end, this study presented an extensive systematic review of the current state of morphological models and their application to salt marshes. The emergence of process-based (PB) and data-driven (DD) models has contributed to the development of morphological models. In morphodynamic simulations in PB models, multiple physical and biological factors (e.g., the hydrodynamics of water bodies, sediment erosion, sediment deposition, and vegetation type) have been considered. The systematic review revealed that PB models have been extended to a broader interdisciplinary field. Further, most DD models are based on remote sensing database for the prediction of morphological characteristics with latent uncertainty. Compared to DD models, PB models are more transparent but can be complex and require a lot of computational power. Therefore, to make up for the shortcomings of each model, future studies could couple PB with DD models that consider vegetation, microorganisms, and benthic animals together to simulate or predict the biogeomorphology of salt marsh systems. Nevertheless, this review found that there is a lack of unified metrics to evaluate model performance, so it is important to define clear objectives, use multiple metrics, compare multiple models, incorporate uncertainty, and involve experts in the field to provide guidance in the further study.
Abstract: To our knowledge, precise data concerning the pollution in terms of qualitative and quantitative fluctuations in discharge water from the laundry sector have seldom been reported. This study investigated the chemical composition of the discharge water from a laundry industry. Over 160 chemical substances and 15 standard water parameters were monitored. The results showed that the discharge water presented both inorganic and organic polycontamination with a high degree of qualitative and quantitative variability. However, of all monitored substances, only five metals (Al, Cu, Fe, Sr, and Zn), five minerals (P, Ca, K, Na, and S), and alkylphenols were systematically present and quantifiable. For a daily average water flow of 129 m3, the released metal flux was 356 g/d. Substances, such as trichloromethane, brominated diphenyl ether (BDE) 47, and fluorides, were occasionally found and quantified. Other substances, such as chlorophenols, organo-tins, and pesticides were never identified. All the samples had quantifiable levels in the chemical oxygen demand (COD), biological oxygen demand (BOD), and hydrocarbons. Only the concentrations of Zn (8.3 g/d), Cu (21.4 g/d), and BOD (57.4 g/d) were close to or above the regulatory values: 74.0 g/d for Zn, 9.0 g/d for Cu, and 57.0 kg/d for BOD. The data obtained from this study are useful to the choice of additional treatments for the reduction of pollutant fluxes.
Abstract: Clean drinking water is one of the United Nations Sustainable Development Goals. Despite significant progress in the water purification technology, many regions still lack access to clean water. This paper provides a review of selected water contaminants and their impacts on human health. The World Health Organization (WHO) guidelines and regional standards for key contaminants were used to characterise water quality in the European Union and UK. The concept of safe drinking water was explained based on the non-observed adverse effect level, threshold concentrations for toxic chemicals, and their total daily intake. Various techniques for monitoring water contaminants and the drinking water standards from five different countries, including the UK, USA, Canada, Pakistan and India, were compared to WHO recommended guidelines. The literature on actual water quality in these regions and its potential health impacts was also discussed. Finally, the role of public water suppliers in identifying and monitoring drinking water contaminants in selected developed countries was presented as a potential guideline for developing countries. This review emphasised the need for a comprehensive understanding of water quality and its impacts on human health to ensure access to clean drinking water worldwide.
Abstract: The Chicago Area Waterway System (CAWS) is a 133.9 km branching network of navigable waterways controlled by hydraulic structures, in which the majority of the flow is treated wastewater effluent and there are periods of substantial combined sewer overflows. The CAWS comprises a network of effluent dominated streams. More stringent dissolved oxygen (DO) standards and a reduced flow augmentation allowance have been recently applied to the CAWS. Therefore, a carefully calibrated and verified one-dimensional flow and water quality model was applied to the CAWS to determine emission-based real-time control guidelines for the operation of flow augmentation and aeration stations. The goal of these guidelines was to attain DO standards at least 95% of the time. The “optimal” guidelines were tested for representative normal, dry, and wet years. The finally proposed guidelines were found in the simulations to attain the 95% target for nearly all locations in the CAWS for the three test years. The developed operational guidelines have been applied since 2018 and have shown improved attainment of the DO standards throughout the CAWS while at the same time achieving similar energy use at the aeration stations on the Calumet River system, greatly lowered energy use on the Chicago River system, and greatly lowered discretionary diversion from Lake Michigan, meeting the recently enacted lower amount of allowed annual discretionary diversion. This case study indicates that emission-based real-time control developed from a well calibrated model holds potential to help many receiving water bodies achieve high attainment of water quality standards.
Abstract: This study reported and discussed turbulence characteristics, such as turbulence intensity, correlation time scales, and advective length scales. The characteristic air–water time scale, including the particle chord time and length and their probability density functions (PDFs), was investigated. The results demonstrated that turbulence intensity was relatively greater on a rough bed in the roller length, whereas further downstream, the decay rate was higher. In addition, the relationship between turbulence intensity and dimensionless bubble count rate reflected an increase in turbulence intensity associated with the number of entrained particles. Triple decomposition analysis (TDA) was performed to determine the contributions of slow and fast turbulent components. The TDA results indicated that, regardless of bed type and inflow conditions, the sum of the band-pass (T'u) and high-pass (T″u) filtered turbulence intensities was equal to the turbulence intensity of the raw signal data (Tu). T″u highlighted a higher turbulence intensity and larger vorticities on the rough bed for an identical inflow Froude number. Additional TDA results were presented in terms of the interfacial velocity, auto- and cross-correlation time scales, and longitudinal advection length scale, with the effects of low- and high-frequency signal components on each highlighted parameter. The analysis of the air chord time indicated an increase in the proportion of small bubbles moving downstream. The second part of this research focused on the basic properties of particle grouping and clustering.
Abstract: A survey on bubble clustering in air–water flow processes may provide significant insights into turbulent two-phase flow. These processes have been studied in plunging jets, dropshafts, and hydraulic jumps on a smooth bed. As a first attempt, this study examined the bubble clustering process in hydraulic jumps on a pebbled rough bed using experimental data for 1.70 < Fr1 < 2.84 (with Fr1 denoting the inflow Froude number). The basic properties of particle grouping and clustering, including the number of clusters, the dimensionless number of clusters per second, the percentage of clustered bubbles, and the number of bubbles per cluster, were analyzed based on two criteria. For both criteria, the maximum cluster count rate was greater on the rough bed than on the smooth bed, suggesting greater interactions between turbulence and bubbly flow on the rough bed. The results were consistent with the longitudinal distribution of the interfacial velocity using one of the criteria. In addition, the clustering process was analyzed using a different approach: the interparticle arrival time of bubbles. The comparison showed that the bubbly flow structure had a greater density of bubbles per unit flux on the rough bed than on the smooth bed. Bed roughness was the dominant parameter close to the jump toe. Further downstream, Fr1 predominated. Thus, the rate of bubble density decreased more rapidly for the hydraulic jump with the lowest Fr1.
Abstract: Considering that we still do not fully understand the behavior of air pockets trapped in rainstorm systems and water flow changes inside pipes, the study of actual geysers presents many challenges. In this study, three-dimensional numerical models were developed to investigate the mechanisms of geyser events triggered by rapid filling flows at different scales. The results showed that, in the first stage of the water–air mixture of the prototype model, a large amount of air was released quickly, and the subsequent overflow lasted for a more extended period. The transport capacity of the downstream pipe, as a critical factor, significantly influenced the water–air interaction of the geyser. Restricting the outlet area and increasing the outlet pressure simultaneously resulted in a stronger geyser. The equivalent density of the water–air mixture increased as the scale decreased during the geyser event.
Abstract: The unique structure and complex deformation characteristics of concrete face rockfill dams (CFRDs) create safety monitoring challenges. This study developed an improved random forest (IRF) model for dam health monitoring modeling by replacing the decision tree in the random forest (RF) model with a novel M5' model tree algorithm. The factors affecting dam deformation were preliminarily selected using the statistical model, and the grey relational degree theory was utilized to reduce the dimensions of model input variables. Finally, a deformation prediction model of CFRDs was established using the IRF model. The ten-fold cross-validation method was used to quantitatively analyze the parameters affecting the IRF algorithm. The performance of the established model was verified using data from three specific measurement points on the Jishixia dam and compared with other dam deformation prediction models. At point ES-10, the performance evaluation indices of the IRF model were superior to those of the M5' model tree and RF models and the classical support vector regression (SVR) and back propagation (BP) neural network models, indicating the satisfactory performance of the IRF model. The IRF model also outperformed the SVR and BP models in settlement prediction at points ES2-8 and ES4-10, demonstrating its strong anti-interference and generalization capabilities. This study has developed a novel method for forecasting and analyzing dam settlements with practical significance. Moreover, the established IRF model can also provide guidance for modeling health monitoring of other structures.
Abstract: The anti-sliding stability of a gravity dam along its foundation surface is a key problem in the design of gravity dams. In this study, a sensitivity analysis framework was proposed for investigating the factors affecting gravity dam anti-sliding stability along the foundation surface. According to the design specifications, the loads and factors affecting the stability of a gravity dam were comprehensively selected. Afterwards, the sensitivity of the factors was preliminarily analyzed using the Sobol method with Latin hypercube sampling. Then, the results of the sensitivity analysis were verified with those obtained using the Garson method. Finally, the effects of different sampling methods, probability distribution types of factor samples, and ranges of factor values on the analysis results were evaluated. A case study of a typical gravity dam in Yunnan Province of China showed that the dominant factors affecting the gravity dam anti-sliding stability were the anti-shear cohesion, upstream and downstream water levels, anti-shear friction coefficient, uplift pressure reduction coefficient, concrete density, and silt height. Choice of sampling methods showed no significant effect, but the probability distribution type and the range of factor values greatly affected the analysis results. Therefore, these two elements should be sufficiently considered to improve the reliability of the dam anti-sliding stability analysis.
Abstract: The material mechanical parameters of the dam body and foundation will change when a dam is reinforced during the aging process. This causes significant changes in the structural state of the project and makes it difficult to ensure its structural safety. In this study, a new deformation warning index for reinforced concrete dams was developed according to the prototype monitoring data, statistical models, three-dimensional finite element model (FEM) numerical simulation, and the critical conditions of the dam structure. A statistical model was established to separate the water pressure component. Then, a three-dimensional FEM of the reinforced concrete dam was constructed to simulate the water pressure component. Furthermore, the deformation components that affected the mechanical parameters of the dam under the same amount of reservoir water level change were separated and quantified accurately. In addition, the method for inversion of comprehensive mechanical parameters after dam reinforcement was used. The influence mechanisms of the deformation behavior of concrete dams under the reservoir water level and temperature changes were investigated. A new deformation warning index was developed by combining the forward-simulated critical water pressure component and temperature component in the period of extreme temperature decrease with the aging component separated by the statistical model. The new deformation warning index considers the structural state of the dam before and after reinforcement and links the structural strength criterion and the deformation evolution mechanisms. It provides a theoretical foundation and decision support for long-term service and operation management of reinforced dams.
Abstract: Numerical simulation of concrete-faced rockfill dams (CFRDs) considering the spatial variability of rockfill has become a popular research topic in recent years. In order to determine uncertain rockfill properties efficiently and reliably, this study developed an uncertainty inversion analysis method for rockfill material parameters using the stacking ensemble strategy and Jaya optimizer. The comprehensive implementation process of the proposed model was described with an illustrative CFRD example. First, the surrogate model method using the stacking ensemble algorithm was used to conduct the Monte Carlo stochastic finite element calculations with reduced computational cost and improved accuracy. Afterwards, the Jaya algorithm was used to inversely calculate the combination of the coefficient of variation of rockfill material parameters. This optimizer obtained higher accuracy and more significant uncertainty reduction than traditional optimizers. Overall, the developed model effectively identified the random parameters of rockfill materials. This study provided scientific references for uncertainty analysis of CFRDs. In addition, the proposed method can be applied to other similar engineering structures.
