Search Results (77)

Flooding due to dam failures is a critical issue with significant impacts on human safety, infrastructure, and the environment. This study assessed the potential flood hazard that could be generated from breaching of the Alacranes dam in Villa Clara, Cuba. Thirteen reservoir breaching scenarios were simulated under several criteria for modeling the flood wave through the 2D Saint Venant equations using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS). A sensitivity analysis was performed on Manning’s roughness coefficient, demonstrating a low variability of the model outputs for these events. The results show that, for all modeled scenarios, the terrain topography of the coastal plain expands the flood wave, reaching a maximum width of up to 105,057 km. The most critical scenario included a 350 m breach in just 0.67 h. Flood, velocity, and hazard maps were generated, identifying populated areas potentially affected by the flooding events. The reported depths, velocities, and maximum flows could pose extreme danger to infrastructure and populated areas downstream. These types of studies are crucial for both risk assessment and emergency planning in the event of a potential dam breach. Full article

This study presents a scenario-based, two-dimensional flood modeling approach to assess the potential downstream impacts of a piping-induced dam failure triggered by seismic activity. The case study focuses on the Doğantepe Dam in northwestern Türkiye, located near an active branch of the North Anatolian Fault. Critical deformation zones were previously identified through PLAXIS 2D seismic analyses, which served as the physical basis for a dam break scenario. This scenario was modeled using the HEC-RAS 2D platform, incorporating high-resolution topographic data, reservoir capacity, and spatially varying Manning’s roughness coefficients. The simulation results show that the flood wave reaches downstream settlements within the first 30 min, with water depths exceeding 3.0 m in low-lying areas and flow velocities surpassing 6.0 m/s, reaching up to 7.0 m/s in narrow sections. Inundation extents and hydraulic parameters such as water depth and duration were spatially mapped to assess flood hazards. The study demonstrates that integrating physically based seismic deformation data with hydrodynamic modeling provides a realistic and applicable framework for evaluating flood risks and informing emergency response planning. Full article

Suyukou Gully, located on the eastern slope of the Helan Mountains in northwest China, is a typical debris-flow-prone catchment characterized by a steep terrain, fractured bedrock, and abundant loose colluvial material. The area is subject to intense short-duration convective rainfall events, which often trigger destructive debris flows that threaten the Suyukou Scenic Area. To investigate the dynamics and risks associated with such events, this study employed the FLO-2D two-dimensional numerical model to simulate debris flow propagation, deposition, and hazard distribution under four rainfall return periods (10-, 20-, 50-, and 100-year scenarios). The modeling framework integrated high-resolution digital elevation data (original 5 m DEM resampled to 20 m grid), land-use classification, rainfall design intensities derived from regional storm atlases, and detailed field-based sediment characterization. Rheological and hydraulic parameters, including Manning’s roughness coefficient, yield stress, dynamic viscosity, and volume concentration, were calibrated using post-event geomorphic surveys and empirical formulations. The model was validated against field-observed deposition limits and flow depths, achieving a spatial accuracy within 350 m. Results show that the debris flow mobility and hazard intensity increased significantly with rainfall magnitude. Under the 100-year scenario, the peak discharge reached 1195.88 m³/s, with a maximum flow depth of 20.15 m and velocities exceeding 8.85 m·s⁻¹, while the runout distance surpassed 5.1 km. Hazard zoning based on the depth–velocity (H × V) product indicated that over 76% of the affected area falls within the high-hazard zone. A vulnerability assessment incorporated exposure factors such as tourism infrastructure and population density, and a matrix-based risk classification revealed that 2.4% of the area is classified as high-risk, while 74.3% lies within the moderate-risk category. This study also proposed mitigation strategies, including structural measures (e.g., check dams and channel straightening) and non-structural approaches (e.g., early warning systems and land-use regulation). Overall, the research demonstrates the effectiveness of physically based modeling combined with field observations and a GIS analysis in understanding debris flow hazards and supports informed risk management and disaster preparedness in mountainous tourist regions. Full article

Salt marsh vegetation significantly changes water motion and sediment transport in coastal wetlands, which further influences the geomorphological evolution of coastal wetlands. Accurate determination of the vegetation drag coefficient (Manning’s roughness coefficient) is critical to vegetation flow resistance research. Previous studies on the vegetation roughness coefficient mainly conducted flume experiments under the one-dimensional steady flow condition, which could not reflect the two-dimensional unsteady flow condition in salt marsh vegetated zones. Through theoretical formula analysis and synchronized field observations in a salt marsh vegetated zone, we propose a novel method for calculating the roughness coefficient of salt marsh vegetation especially under the two-dimensional unsteady flow condition. The results indicate that the vegetation roughness coefficient under the two-dimensional unsteady flow condition can be obtained by integrating the flow resistance equation with the discretized momentum conservation equation. Then, in combination with field observation data, the temporal variations in the vegetation roughness coefficient can be derived. The salt marsh vegetated zone in the Jiuduansha Wetland is dominated by flooding currents, and ebbing currents are of secondary importance. The flow resistance of vegetation on flooding and ebbing currents is remarkable. Moreover, the roughness coefficient shows an inverse power-law relationship with the product of flow velocity and water depth (i.e., U_fh_f) at the control volume center. Under the same U_fh_f scenario, due to the increase in the water-facing area of vegetation, the roughness coefficient during the submerged period is generally greater than that during the non-submerged period. The calculated roughness coefficients and their relationships with U_fh_f are consistent with those shown in previous flume experiments, indicating that our proposed method is reasonable. This new method could help determine vegetation flow resistance accurately (particularly under the two-dimensional unsteady flow condition), and it may provide implications for eco-geomorphological simulations of coastal wetlands. Full article

Riparian vegetation reduces the conveyance capacity and increases the likelihood of floods. Studies that consider vegetation in flow modeling rely on unmanned aerial vehicle (UAV) data, which restrict the covered area. In contrast, this study explores advances in remote sensing and machine learning techniques to obtain vegetation data for an entire river by relying solely on satellite data, superior to UAVs in terms of spatial coverage, temporal frequency, and cost effectiveness. This study proposes a machine learning method to obtain key vegetation parameters at a resolution of 10 m. The goal was to evaluate the applicability of remotely sensed vegetation data using the proposed method on a dynamic roughness distributed runoff model in the Abukuma River to assess the effect of vegetation on the typhoon Hagibis flood (12 October 2019). Two machine learning models were trained to obtain vegetation height and density using different satellite sources, and the parameters were mapped in the river floodplains with 10 m resolution based on Sentinel-2 imagery. The vegetation parameters were successfully estimated, with the vegetation height overestimated in the urban areas, particularly in the downstream part of the river, then integrated into a dynamic roughness calculation routine and patched into the RRI model. The simulations with and without vegetation were also compared. The machine learning models for density and height obtained fair results, with an R² of 0.62 and 0.55, respectively, and a slight overestimation of height. The results showed a considerable increase in water depth (up to 17.7% at the Fushiguro station) and a decrease in discharge (28.1% at the Tateyama station) when vegetation was considered. Full article

The accurate estimation of Manning’s roughness coefficient (n) is critical for hydraulic modeling in open channels. In fish passes designed as close-to-nature structures, this coefficient has a strong influence on the overall design and operation. This study evaluates n for the Veľké Kozmálovce fish pass using high-resolution drone imagery and image analysis techniques to determine riverbed surface characteristics and extract a grain size distribution curve. Various empirical equations based on Strickler’s formula were applied to specific grain sizes, yielding average n values of 0.036 and 0.037. Cowan’s method, which considers surface material, irregularities, vegetation, obstructions, and meandering, provided an upper-bound estimate of 0.040. However, this method is known to overestimate roughness in some cases. The Step-by-Step method, applied with hydraulic field measurements, resulted in a narrower range of n from 0.027 to 0.037. Overall, estimated values across all methods ranged between 0.023 and 0.040, reflecting the structural complexity of the fish pass, which includes boulders embedded in concrete and coarse gravel infill. These findings highlight the limitations of using generalized tabulated values for artificial channels and demonstrate that drone-based photogrammetry combined with empirical and analytical approaches can effectively capture spatial variability in hydraulic roughness. Full article

Determining the friction coefficients for uniform flows over very rough bottoms is a long-standing problem in open-channel hydraulics and river engineering. This experimental study presents measurements of the surface deformation as well as Darcy–Weisbach and Manning friction coefficients for steady, turbulent (6058 $\le \mathcal{R}e\le$ 28,502), and subcritical flows (0.14 $\le \mathcal{F}r\le$ 0.52) over large roughness elements, where $\mathcal{F}r$ and $\mathcal{R}e$ denote the Froude and Reynolds numbers, respectively. The experiments were conducted in a rectangular, inclined flume with a train of half-cylinders mounted on the bed, with radii in the range 20 mm $\le a\le$ 50 mm. These obstacles yield a relative submergence 1.45 $\le h_N/a\le$ 4.41 and a constant spacing ratio $e/a=12.8$ across all experimental runs, where $h_N$ and e denote the normal flow depth and the center-to-center spacing between cylinders, respectively. The relative amplitude of the surface profiles, ($\Delta h/a$), was analyzed and found to correlate strongly with $h_N/a$, $\mathcal{R}e$ and $\mathcal{F}r$. The results reveal very high values of the Darcy friction factor, f, which follows scaling laws of the form ${f\propto (h_N/a)}^{\widehat{n}}$, with $\widehat{n}<0$, independent of a, and ${f\propto \mathcal{R}e}^{\beta }$, where $\beta <0$ is closely linked to a. Scaling relationships for the Manning roughness coefficient, (n), were also investigated and are reported herein. Full article

River ice formation is common in high-latitude areas, where it significantly impacts the accuracy of river flow measurements. The most commonly used method to solve the ice-covered channel flow measurement problem is to combine physical boundary conditions, which effectively reduces the large amount of work required for measuring flow in frozen channels, especially for hard-to-obtain flow characteristic data. Through theoretical analysis, this study proposes a general formula applicable to flow discharge prediction in ice-covered channels. It is unaffected by the shape of the channel and somewhat unifies the flow prediction formulas for ice-covered channels. Two simplified flow discharge prediction formulas are proposed based on the general formula. Experimental data from the literature are collected to verify the applicability of the general formula and the two simplified formulas, which are compared with the Lotter, Sabaneev, Larsen, and Pavlovskiy formulas. The results show that the proposed general formula and the two simplified formulas are more accurate in estimating flow in ice-covered channels compared to traditional formulas. Full article

Accurate river hydraulic characterization is fundamental to assess flood risk, parametrize flood forecasting models, and develop river maintenance workflows. River hydraulic roughness and riverbed/floodplain geometry are the main factors controlling inundation extent and water levels. However, gauging stations providing hydrometric observations are declining worldwide, and they provide point measurements only. To describe hydraulic processes, spatially distributed data are required. In situ surveys are costly and time-consuming, and they are sometimes limited by local accessibility conditions. Satellite earth observation (EO) techniques can be used to measure spatially distributed hydrometric variables, reducing the time and cost of traditional surveys. Satellite EO provides high temporal and spatial frequency, but it can only measure large rivers (wider than ca. 50 m) and only provides water surface elevation (WSE), water surface slope (WSS), and surface water width data. UAS hydrometry can provide WSE, WSS, water surface velocity and riverbed geometry at a high spatial resolution, making it suitable for rivers of all sizes. The use of UAS hydrometry can enhance river management, with cost-effective surveys offering large coverage and high-resolution data, which are fundamental in flood risk assessment, especially in areas that difficult to access. In this study, we proposed a combination of UAS hydrometry techniques to fully characterize the hydraulic parameters of a river. The land elevation adjacent to the river channel was measured with LiDAR, the riverbed elevation was measured with a sonar payload, and the WSE was measured with a UAS radar altimetry payload. The survey provided 57 river cross-sections with riverbed elevation, and 8 km of WSE and land elevation and took around 2 days of survey work in the field. Simulated WSE values were compared to radar altimetry observations to fit hydraulic roughness, which cannot be directly observed. The riverbed elevation cross-sections have an average error of 32 cm relative to RTK GNSS ground-truth measurements. This error was a consequence of the dense vegetation on land that prevents the LiDAR signal from reaching the ground and underwater vegetation, which has an impact on the quality of the sonar measurements and could be mitigated by performing surveys during winter, when submerged vegetation is less prevalent. Despite the error of the riverbed elevation cross-sections, the hydraulic model gave good estimates of the WSE, with an RMSE below 3 cm. The estimated roughness is also in good agreement with the values measured at a gauging station, with a Gauckler–Manning–Strickler coefficient of M = 16–17 m^1/3/s. Hydraulic modeling results demonstrate that both bathymetry and roughness measurements are necessary to obtain a unique and robust hydraulic characterization of the river. Full article

The available historical documents for the city of Alexandria indicate that it was damaged to varying degrees by several (historical and instrumentally recorded) earthquakes and by highly destructive tsunamis reported at some places along the Mediterranean coast. In this work, we applied the neo-deterministic seismic hazard analysis (NDSHA) approach to the Alexandria metropolitan area, estimating ground motion intensity parameters, e.g., peak ground displacement (PGD), peak ground velocity (PGV), peak ground acceleration (PGA), and spectral response, at selected rock sites. The results of this NDSHA zonation at a subregional/urban scale, which can be directly used as seismic input for engineering analysis, indicate a relatively high seismic hazard in the Alexandria region (e.g., 0.15 g), and they can provide an essential knowledge base for detailed and comprehensive seismic microzonation studies at an urban scale. Additionally, we established detailed tsunami hazard inundation maps for Alexandria Governorate based on empirical relations and considering various Manning’s Roughness Coefficients. Across all the considered scenarios, the average estimated time of arrival (ETA) of tsunami waves for Alexandria was 75–80 min. According to this study, the most affected sites in Alexandria are those belonging to the districts of Al Gomrok and Al Montazah. The west of the city, called Al Sahel Al Shamally, is less affected than the east, as it is protected by a carbonate ridge parallel to the coastline. Finally, we emphasize the direct applicability of our study to urban planning and risk management in Alexandria. Our study can contribute to identifying vulnerable areas, prioritizing mitigation measures, informing land-use planning and building codes, and enhancing multi-hazard risk analysis and early warning systems. Full article

Seasonal changes, sea level rise, and global warming make flood events more frequent, which necessitates watershed management and efficient use of water resources. In this context, understanding the hydrodynamic behavior of basins is critical for the development of flood prevention strategies. The contributions of hydrological and hydraulic modeling techniques in this process are among the key determinants of sustainable water resources management. The Filyos Sub-Basin, located in the Western Black Sea Basin, stands out as one of the regions where flood risk assessment is a priority, as it has two important floodplains. This study aims to analyze the flood risk in the Filyos River Sub-Basin with hydraulic modeling methods, and to determine the Manning roughness coefficient. In the study, the parameters affecting the roughness of the river bed were analyzed using the Cowan method, and the effects of vegetation on river bed resistance were evaluated in the laboratory environment. Flood simulations were carried out for four different flow rates (Q₁₀₀₀, Q₅₀₀, Q₁₀₀ and Q₅₀) using the HEC-RAS model, and the performance of flood protection structures were analyzed. The findings show that a significant portion of the existing protection structures are unable to meet the potential flood flows, which can cause serious damage to residential and agricultural areas. In basins with limited historical discharge data, such as the Filyos River, these findings provide important contributions to sustainable water resources management and regional planning processes. The results of the study serve as a reference for flood risk assessment, not only for the Filyos River Basin, but also for other basins with similar hydrodynamic characteristics. It is envisaged that future research, supported by larger data sets, can improve the accuracy of flood simulations. Furthermore, the Cowan method and HEC-RAS model used in this study are expected to contribute to strategic planning and engineering solutions to minimize flood risk in other watershed management projects. In future studies, we plan to further develop methodological approaches for determining the roughness coefficient, and to address applications to increase the effectiveness of flood protection structures. Full article

The hydraulic characteristics (such as velocity profiles, near-bed velocity profile, bed shear stress, and resistance coefficients) of shallow flows over rough surfaces were investigated using numerical simulations. A novel method is presented to simulate shallow flows over rough surfaces in a two-dimensional (2D) numerical domain, where the physical numerical domain represents bed topography. Results reveal that the model can accurately predict spatially averaged velocity profiles, turbulence characteristics, shear stresses, and uniform flow depths. The analysis identified two distinct flow regions based on mean and turbulent flow profiles. Results show that the turbulent shear stress profiles provide a more accurate estimation of the bed shear stresses. Resistance coefficients (friction factor or Manning’s roughness coefficient) vary with Froude number and submergence ratio (depth divided by roughness height). Full article

This paper investigates the impact of flood-induced hydrodynamic forces and high discharge on the masonry arch “Hannibal Bridge” (called “Ponte di Annibale” in Italy) using the Hydraulic Engineering Center’s River Analysis Simulation (HEC-RAS) v6.5.0. hydraulic numerical method, incorporating Unmanned Aerial Vehicle (UAV) photogrammetry and aerial Light Detection and Ranging (LIDAR) data for visual analysis. The research highlights the highly transient behavior of fast flood flows, particularly when carrying debris, and their effect on bridge superstructures. Utilizing a Digital Elevation Model to extract cross-sectional and elevation data, the research examined 23 profiles over 800 m of the river. The results indicate that the maximum allowable water depth in front of the bridge is 4.73 m, with a Manning’s coefficient of 0.03 and a longitudinal slope of 9 m per kilometer. Therefore, a novel method to identify the risks through HEC-RAS modeling significantly improves the conservation of masonry bridges by providing precise topographical and hydrological data for accurate simulations. Moreover, the detailed information obtained from LIDAR and UAV photogrammetry about the bridge’s materials and structures can be incorporated into the conservation models. This comprehensive approach ensures that preservation efforts are not only addressing the immediate hydrodynamic threats but are also informed by a thorough understanding of the bridge’s structural and material conditions. Understanding rating curves is essential for water management and flood forecasting, with the study confirming a Manning roughness coefficient of 0.03 as suitable for smooth open-channel flows and emphasizing the importance of geomorphological conditions in hydraulic simulation. Full article

Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks for which automation was analyzed consisted of estimating changes in the roughness coefficient of a mountain streambed and the extent of floods from images. The Segment Anything Model (SAM) developed in 2023 by Meta was used for this purpose. Images from many years from the Wielka Puszcza mountain stream located in the Polish Carpathians were used as the only input data. The model was not additionally trained for the described tasks. The SAM can be run in several modes, but the two most appropriate were used in this study. The first one is available in the form of a web application, while the second one is available in the form of a Jupyter notebook run in the Google Colab environment. Both methods do not require specialized knowledge and can be used by virtually any hydrologist. In the roughness estimation task, the average Intersection over Union (IoU) ranges from 0.55 for grass to 0.82 for shrubs/trees. Ultimately, it was possible to estimate the roughness coefficient of the mountain streambed between 0.027 and 0.059 based solely on image data. In the task of estimation of the flood extent, when selecting appropriate images, one can expect IoU at the level of at least 0.94, which seems to be an excellent result considering that the SAM is a general-purpose segmentation model. It can therefore be concluded that the SAM can be a useful tool for a hydrologist. Full article

This study attempts to back-calculate Manning’s roughness coefficients by repeating a two-dimensional flow simulation to fit the spatially and temporally dense river water-level data observed in Japan’s Yamatsuki River, a typical mountainous river with an average riverbed gradient of 1/50 and an average river width of 17.9 m. Furthermore, we aim to clarify the influence of the in-channel physical parameters on the coefficient of roughness obtained through the above method. In the Yamatsuki River, 16 water-level gauges were installed at intervals of about 40~80 m in the longitudinal direction in the study reach. Manning’s roughness coefficients were back-calculated by repeating two-dimensional flow simulations to match the observed water levels of a flood in 2021 (the estimated maximum flow rate is 11.5 m³/s). The back-calculated roughness coefficients approached a constant value in the range of 0.05 to 0.1 s/m^1/3 as the relative water depth increased, indicating that the roughness coefficient can be considered a constant value when performing plane two-dimensional flow calculations for flooding. The roughness coefficient during flooding was found to be correlated with the slope and step height (H)-step length (L)- channel slope (S) ratios (H/L/S). An equation for predicting the roughness coefficient during flooding based on the physical parameters of the channel is also proposed. Full article