Water-retaining structures, such as earth dams, require a careful assessment of seepage behavior to ensure structural stability and prevent failure. This study presents a comprehensive numerical investigation of sheet pile cutoff walls as seepage control measures in earth dam foundations using finite element analysis with SEEP/W software. An earth dam model with varying sheet pile configurations was analyzed to evaluate the effects of sheet pile position and length on seepage parameters, including flow rate, water pressure head, and hydraulic gradient. Four different sheet pile lengths (6, 8, 10, and 12 m) were positioned at various distances from the dam heel (25.5, 51, 77, and 102.5 m) to assess optimal placement strategies. Results demonstrate that sheet piles significantly reduce seepage in all scenarios of the research. Sheet piles positioned closer to the downstream toe achieved superior seepage control performance compared to those at upstream positions. Increasing sheet pile length results in a substantial rise in water pressure head loss and hydraulic gradient by about 13 and 15%, respectively, whereas seepage discharge diminishes (about 9%). Moreover, it was deduced that the sheet pile length has a higher impact on changes in the studied parameters and earth dam safety compared to sheet pile distance.

Estimating unknown parameters from incomplete transient temperature histories is a fundamental inverse heat conduction problem encountered in thermal diagnostics, condition monitoring, material characterization, and post-event thermal history reconstruction. The problem becomes particularly challenging when temperature measurements begin after an unknown delay and are affected by measurement uncertainty. This study presents a joint Bayesian inference framework for recovering spatial, thermal, and temporal parameters directly from transient temperature measurements acquired at multiple spatial locations. The forward model is based on the one-dimensional transient conduction equation with convective boundary conditions and is approximated using the first-term analytical series approximation. Within a unified probabilistic framework, the primary eigenvalue ($\lambda_1$), a grouped thermal parameter ($\alpha'=\alpha/L^2$), and an unknown temporal offset ($t_{\mathrm{lag}}$) are inferred simultaneously from noisy temperature histories. Unlike conventional approaches that require prior specification of the Biot number or convective heat-transfer coefficient, the proposed formulation estimates $\lambda_1$ directly from the measured data. By treating all unknown quantities as random variables, the framework accounts for measurement uncertainty, parameter correlations, and model-form uncertainty while avoiding sequential parameter estimation and heuristic signal filtering. The methodology is evaluated using a full-factorial validation matrix comprising 162 synthetic cooling cases spanning a range of Biot numbers, thermal time scales, measurement noise levels, and higher-order series truncation errors. Across the validation cases, the inferred values of $\lambda_1$, $\alpha'$, and $t_{\mathrm{lag}}$ remain in good agreement with the prescribed parameters used to generate the synthetic data.

Global ocean warming continued unabated in 2025 in response to increased greenhouse gas concentrations and recent reductions in sulfate aerosols, reflecting the long-term accumulation of heat within the climate system, with conditions evolving toward La Niña during the year. In 2025, global upper 2000 m ocean heat content (OHC) increased by ∼23 ± 8 ZJ relative to 2024 according to IAP/CAS estimates. CIGAR-RT, and Copernicus Marine data confirm the continued ocean heat gain. Regionally, about 33

Chute aeration is an efficient method for protecting chute structures from cavitation-induced erosion. Various types of chute aerators are utilized to aerate high-velocity flows. The protection provided by the aeration to the chute bottom and sidewalls is primarily influenced by the aerator design and by air diffusion. However, detailed comparisons of the air concentrations produced by different chute aerator designs, as well as the determination of the optimal spacing between aerators, are limited. In this study, the characteristics of different chute aerators and flow hydraulic properties for determining the distance of the chute aerators are simulated using Computational Fluid Dynamics (CFD). The numerical models include ramps, offsets, ramps with offsets, and bottom and side wall ramps. By preparing numerical models of the spillway using the RNG k–ε turbulence model and the mixture model, a hydraulic analysis of the flow is completed. A comparison between experimental data with the numerical models is carried out to verify the performance of the numerical simulations. This comparison is based on the air concentration distribution downstream of the chute spillway aerator. The results show that the combination of bottom and side wall ramp aerators provides better aeration than other designs because they create a cavity zone in both the bottom and side wall chute. The length of the cavity area in the chute when there is a side wall ramp is approximately 50

Balancing the global mean sea level (GMSL) budget is essential for understanding sea level changes. Large uncertainty after 1960 is reduced by accounting for recent observational advances. Budget closure occurs within 0.18 millimeters per year for all periods analyzed (1960-2023, 1993-2023, and 2005-2023). Trends for these three periods are 2.06, 3.41, and 3.94 millimeters per year, revealing an increase in the rate. The annual residual between observed GMSL and the sum of contributions is only between -13 and 10 millimeters since 1960 and ±5 millimeters after 2005. Further, the GMSL acceleration budget is now closed. The principal drivers for the GMSL trend (acceleration) since 1960 are 43% (41%) from thermosteric ocean expansion, 27% (9%) from glacier melting, 15% (16%) from Greenland, 12% (13%) from Antarctic, and 3% (21%) from land water storage. Results highlight the importance of data processing and bias correction techniques in tracking GMSL and its contributions.

The inability to accurately estimate the Manning roughness coefficient (n) and the use of a constant value of n is a major source of uncertainty in flood simulations and flow-depth calculations. The main purpose of present study is to more precisely determine n for the Aji-Chai River upstream of the Vanyar hydrometric station. Results show that the lowest value of n is 0.034, corresponding to the discharge of 180 m3/s, while the highest value of n, corresponding to a discharge of 2.083 m3/s, is 0.119. As the discharge decreases, the roughness coefficient increases. The functional relationship between the roughness coefficient and discharge yields R2 = 0.80. The relationship between the hydraulic radius and the discharge yields R2 = 0.944, indicating a significant relationship. The roughness coefficient and the hydraulic radius have an inverse relationship. Every flood results in a different roughness with different sedimentation depending on variations in river bed particle diameter. Usually, rivers in arid regions are temporary and in the descending limb of the hydrograph, they leave coarser materials in the bed which cause errors in estimating n. In discharge where the flow depth is lower than D90, the Manning coefficient reaches its maximum value.

In this study, the characteristics of different chute aerators and flow properties including pressure, velocity, and turbulence intensity, are investigated for determining the cavitation index along the chute aerators. The numerical models include ramps, offsets, ramps with offsets, and bottom and side-wall ramps. By preparing numerical models of the spillway using the k-epsilon RNG turbulence model and the multiphase mixture method, a hydraulic analysis of the flow was completed. A comparison between experimental data with the numerical models was carried out to verify the performance of the numerical simulations. This comparison was based on the air concentration distribution downstream of the chute spillway aerator. The results show that the combination of bottom and side wall ramp aerators provides better aeration than other approaches because they create a cavity zone in both the bottom and side wall chute. Aeration efficiency increases for this type of aerator, and the distribution of air concentration in the chute is more uniform. Also, the cavitation index in the case where there is a bottom and side wall ramp is almost 55% higher than in the case where the chute spillway only has a bottom ramp.

Heating in the ocean has continued in 2024 in response to increased greenhouse gas concentrations in the atmosphere, despite the transition from an El Niño to neutral conditions. In 2024, both global sea surface temperature (SST) and upper 2000 m ocean heat content (OHC) reached unprecedented highs in the historical record. The 0–2000 m OHC in 2024 exceeded that of 2023 by 16 ± 8 ZJ (1 Zetta Joules = 1021 Joules, with a 95

Gates are structures that permit water flow underneath the gate. They are important water-management structures and require careful design by engineers. The aim of this research is to numerically evaluate the effect of a sill on the hydraulic flow characteristics through sluice and tainter gates using the volume of fluid (VOF) method. Sills with various geometric characteristics were simulated. The findings indicated that the RNG turbulence model had the highest accuracy compared to k-ε, k-ω, and LES. The discharge coefficient (Cd) with a sill is higher than without a sill. Among the investigated sills, the semicircular sill Cd is greater than that of the rectangular one. In addition, the Cd of the tainter gate exceeds that of the sluice for regardless of whether a sill is used. Increasing the thickness of the sill leads to increases in the shear stress of the flow, and consequently, the flow rate decreases. The Cd with a gate with a sill always exceeds the value without a sill. On the other hand, the Cd increases with the increase of the sill height up to a certain level and then decreases thereafter.

Weirs play a crucial role as hydraulic structures in the regulation and control of water flow. This study investigates the relative energy dissipation in labyrinth weirs, examining various configurations, scales, and cycle types, using advanced computational models like Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). In SVM modelling, the results from different kernel functions reveal that the Radial Basis Function (RBF) kernel outperforms polynomial, linear, and sigmoid kernels in predicting relative energy dissipation. For the RBF kernel, the statistical metrics were found to be (R=0.907), (Mean RE%=1.38), (RMSE=0.0153), and (KGE=0.744) in test phase. where RE, Mean RE, RMSE and KGE represent the Relative Error, Mean Relative Error, Root Mean Square Error and Kling Gupta Efficiency, respectively. In contrast, in the ANN model, the multilayer perceptron (MLP) network showed higher accuracy than the RBF network, achieving 0.969, 0.73%, 0.007, and 0.968 for the same indicators. For the RF model, these values were recorded as 0.878, 1.78%, 0.0192, and 0.362, respectively. Comparative analysis indicates that the ANN model offers superior predictive performance over SVM and RF models. Additionally, non-linear polynomial regression equations, derived from dimensionless parameters, are proposed for estimating relative energy dissipation. Notably, single-cycle weirs exhibited the greatest energy dissipation among the configurations studied.

Sluice gates with a semi-cylindrical sill are flow control structures that are used in irrigation canals to regulate water level and flow discharge. To estimate the flow discharge through these structures, it is necessary to accurately estimate the discharge coefficient. The aim of this study is to present a new approach based on data- mining to accurately estimate the Cd based on experimental data. First, standalone data-mining models such as Artificial Neural Network (ANN) and Gaussian Process Regression (GPR) were developed. Then, to improve the performance of the standalone models, a multiple model (MM) strategy was used to develop new multiple models handled by ANN (MM-ANN) and GPR (MM-GPR). Next, an ensemble model (EM) strategy was developed. A total of 107 experiments were conducted to investigate the effect of the semi-cylindrical sill geometry on the discharge coefficient. 70 % of the data was reserved for the training phase, and the remaining 30 % for the testing phase. The ratio of energy head to sill width (h/b) and approach energy head to wetted parameter (h/P) were as input variables and the discharge coefficient (Cd) was an output variable. The outcomes of the multiple models and ensemble model were compared to the standalone methods using statistical metrics (R2, RE%, RMSE, and MAE) and graphical tools (Taylor, Violin, RE%, and scatter plots). The MM-ANN model with R = 0.951, R2 = 0.904, SI = 0.012, RE% = 0.891, MAE = 0.005, and RMSE = 0.007 outperformed the ANN, GPR, MM-GPR, and EM models in accuracy. The h/p variable had the greatest effect on the target variable of MM-ANN evidenced by a SNAP value of 0.45. The MM-ANN model provided reasonable estimates the experimental results. It is recommended to implement the multiple model strategy in order to improve the calculation accuracy of the models in this field.

Increasing the energy dissipation in stepped weirs requires more study to lower the risk for hydraulic structures. This research investigates stepped weirs with various geometries under flat, fully pooled, and zigzag pooled conditions. Simulations were performed using FLOW-3D with flow-rates of 0.007–0.025 m3/s and nested mesh sizes of 0.01 and 0.005 m. The results indicated that RNG turbulence model with Root Mean Square Error (RMSE) = 0.011 has higher accuracy compared to k–ε, k–ω and LES. Fully pooled steps dissipate more energy than flat and zigzag pooled steps, with a 5

Determining the uplift pressure at key points including the junctions of the floor and the cutoff wall beneath hydraulic structures and estimating the uplift force in these structures are vital issues in water engineering projects. The purpose of this study is to present a series of explicit and highly accurate formulas for determining these quantities for three different cutoff wall locations (at the upstream end, at intermediate locations, and the downstream end). In practice, the materials related to some types of cutoff walls may not be completely rigid due to their low permeability. In this study, the impact of permeability is incorporated into the analysis, and this is the novelty of this study. In order to include the effect of permeability, the capabilities of the SEEPW2D-numerical model that utilizes the FEM to solve the governing equations are used. After generating data sets, nonlinear regression equations are developed in order to estimate the uplift pressure at key points and the uplift force exerted on the hydraulic structures. To validate the results of the FEM, Khosla's approach is used. Khosla's solution is usable only for rigid cutoff walls, while proposed equations can be used for both impervious and pervious cutoff walls as an initial estimate in designs. Also, the results indicate that the decrease in the permeability of the cutoff wall is proportional to the value of the uplift pressure at the key points after the cutoff wall. This reduction is inversely related to the value of the uplift pressure at the key points before the cutoff wall. Accordingly, material that constitutes the cutoff wall has a great effect on seepage characteristics, and it is necessary to consider this in the analysis. Therefore, the permeability of the cutoff wall in any design should be selected depending on the case-specific conditions related to seepage and the stability of the structure.

Various factors influence seepage and stability in earth dams. One of the important factors in the analysis of earthen dams is the unsaturated condition of the soil. Accurately understanding soil behavior in earth dams necessitates the application of unsaturated soil mechanics principles. Typically, unsaturated soil mechanics is plagued by many unknowns because of the complexity of soil behavior in unsaturated conditions. In this study, the effect of unsaturated soils on seepage discharge and the safety factor of the downstream slope are numerically investigated. For this study, the Doiraj Dam, which is located in the southwest of Ilam province, Iran, is studied. The results show that use of a constant hydraulic conductivity causes the capillary fringe flow above the phreatic line in the saturated model to be greater than in the unsaturated–saturated model. The seepage rate in the saturated model is 3.60

The ocean is highly stratified. Warm, fresh water sits on top of cold, salty water, influencing vertical oceanic exchange of heat, carbon, oxygen and nutrients. In this Review, we examine observed and projected stratification shifts and their impacts. Changes in ocean temperature and salinity have altered the ocean density field, leading to a 0.8 ± 0.1% dec−1 (90% confidence interval) increase in stratification in the global upper 2,000 m since the 1960s. These increases are most pronounced in the tropics and are primarily temperature driven. Model simulations project ongoing stratification increases in the future, with global 0–2,000 m stratification increasing 0.7 [0.3,1.1; 13–87% confidence interval], 1.4 [0.9,1.8] and 2.9 [2.1,3.8]% dec−1 by 2090–2100 relative to 2010–2020 under Shared Socioeconomic Pathways SSP1-2.6, SSP2-4.5 and SSP5-8.5, respectively; regional patterns of projected stratification changes generally follow observed trends. These observed and projected ocean stratification changes have important climate and ecological consequences, including alterations in ocean heat uptake, ocean currents, vertical mixing, tropical cyclone intensity, marine ecosystems and elevation of marine extremes. Further research should better quantify stratification change at critical layers and understand their drivers and impacts. Ocean stratification — density-related layering of seawater — influences oceanographic and climatic processes. This Review outlines observed and projected changes in stratification, noting a 0.8% dec−1 increase in 0–2,000 m stratification from 1960–2024, and a further 1.4% dec−1 increase by 2100 under SSP2-4.5.