Nappe Flow Surges down a Rough-Stepped Sloping Channel

Nappe flow applies to small discharges, and investigation of nappe flow surges helps to understand the mechanism of water flow in stepped open channels. The objective of this paper is to investigate the nappe flow surge propagation down stepped open channels. First, an analytical solution of dam-break shock waves or flood waves is derived. Then, the theoretical solution is used to calculate the wavefront and celerity and is verified using experiments on surging waters down a stepped slope in a 20-m-long and 0.5-m-wide open channel under three conditions: one for smooth bed surface and the others for rough bed surface glued with uniform sediment (of diameter ds = 1.715 mm and ds = 3.5 mm). For calculating the wavefront propagation in a stepped open channel, a formula for resistance, composed of grain resistance and step geometry resistance, is developed. Unlike skimming flow, the roughness of step surface in the nappe flow regime influences the friction factor fs. Results show that the friction factor increases with the relative roughness height (ds/d0). The theoretical solution for the wavefront location and celerity is then revised by combining the friction formula, and the revised solution is tested for a wide range of experimental data. Test results show that the revised solution fits the measured data quite well. Comparing with the solution previously derived, the revised solution derived in this study more accurately predicts the wavefront location and celerity for the nappe flow condition

The Effects of Rainfall, Soil Type and Slope on the Processes and Mechanisms of Rainfall-Induced Shallow Landslides

Landslides are a serious geohazard worldwide, causing many casualties and considerable economic losses every year. Rainfall-induced shallow landslides commonly occur in mountainous regions. Many factors affect an area’s susceptibility, such as rainfall, the soil, and the slope. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient, and soil type on landslide susceptibility are studied. Variables including soil volumetric water content, matrix suction, pore water pressure, and the total stress throughout the rainfall were measured. The results show that, under the experimental conditions of this paper, no landslides occurred on a 5° slope. On a 15° slope, when the rainfall intensity was equal to or less than 80 mm/h with a 1 h duration, landslides also did not happen. With a rainfall intensity of 120 mm/h, the rainfall pattern in which the intensity gradually diminishes could not induce landslides. Compared with fine soils, coarser soils with gravels were found to be prone to landslides. As the volumetric water content rose, the matrix suction declined from the time that the level of infiltration reached the position of the matrix. The pore water pressure and the total stress both changed drastically either immediately before or after the landslide. In addition, the sediment yield depended on the above factors. Steeper slopes, stronger rainfall, and coarser soils were all found to increase the amount of sediment yield

Flash Floods: Forecasting, Monitoring and Mitigation Strategies

In recent decades, flash floods have become a major natural disaster and show a continuously increasing trend on a worldwide scale [...

The Effects of Rainfall, Soil Type and Slope on the Processes and Mechanisms of Rainfall-Induced Shallow Landslides

Landslides are a serious geohazard worldwide, causing many casualties and considerable economic losses every year. Rainfall-induced shallow landslides commonly occur in mountainous regions. Many factors affect an area’s susceptibility, such as rainfall, the soil, and the slope. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient, and soil type on landslide susceptibility are studied. Variables including soil volumetric water content, matrix suction, pore water pressure, and the total stress throughout the rainfall were measured. The results show that, under the experimental conditions of this paper, no landslides occurred on a 5° slope. On a 15° slope, when the rainfall intensity was equal to or less than 80 mm/h with a 1 h duration, landslides also did not happen. With a rainfall intensity of 120 mm/h, the rainfall pattern in which the intensity gradually diminishes could not induce landslides. Compared with fine soils, coarser soils with gravels were found to be prone to landslides. As the volumetric water content rose, the matrix suction declined from the time that the level of infiltration reached the position of the matrix. The pore water pressure and the total stress both changed drastically either immediately before or after the landslide. In addition, the sediment yield depended on the above factors. Steeper slopes, stronger rainfall, and coarser soils were all found to increase the amount of sediment yield

Impacts of Grass Coverage and Arrangement Patterns on Runoff and Sediment Yield in Slope-Gully System of the Loess Plateau, China

Both vegetation coverage rates and arrangement patterns have important influences on erosion. Very little previous research focuses on the impacts of spatial vegetation distribution patterns on erosion. The slope-gully system was taken as the research object, which is composed of a 5.0 m long hillslope with a slope gradient of 20° and a 3.0 m long gully slope with a gradient of 50°. A series of scouring experiments with two inflow discharges (3.2 L min−1, 5.2 L min−1) was carried out. The effects of the flow discharges, spatial grass arrangement patterns (US, MS, and DS represent the presence of grass covering on up-hillslope, middle-hillslope, and down-hillslope, respectively) and grass coverage rates (0%, 30%, 50%, 70%, and 90%) on runoff and sediment were studied in this paper. The results indicated that either runoff or sediment yielding was significantly decreased with the grass coverage rates increasing and with the variation of grass arrangement patterns on a hillslope. While grass coverage had more effectiveness in controlling erosion compared with runoff reduction, and DS can control erosion more effectively than US and MS erosion controlling. For the gully slope, erosion significantly increased with the grass coverage rates increasing no matter how the grass arrangement patterns on the hillslope. Therefore, both different grass coverage and different grass arrangement patterns have an influence on erosion processes; any research that only takes care of the single factor mentioned above is not enough to reveal the effects of grass on erosion. In the process of erosion control in the Loess Plateau, taking effective measures both on the hillslope and gully slope will be effective methods of reducing soil erosion

Numerical Investigation on a Flash Flood Disaster in Streams with Confluence and Bifurcation

On 20 August 2019, a flash flood occurred in Sanjiang Town, Sichuan, China, and caused great damage to people living there. The town lies at the junction of five streams, with streams A, B, and C combining at the town and further dividing into streams D and E. The slope of streams A, B, and C is about 3~5%, while the slope of streams D and E is around 0.3%. The Sanjiang Town actually lies in the transition from supercritical slope to subcritical slope. During the flood, huge sediments were released to streams A, B, and C, and further transported to stream E. Due to the rapid change of velocity, only few sediments deposited at the supercritical slope parts of the stream, while plenty of them sedimented at the streams with subcritical slope. In order to simulate the flood with a hydrodynamic model, a field investigation was carried out to collect high DEM (digital elevation model) data, flood marks, sediment grading, etc., after the flood. The discharge curve of the flood was also obtained by the hydrometric station near Sanjiang Town. For the inlet sediment concentrations of streams A, B, and C, we made a series of assumptions and utilized the case which best fits the flood marks to set the inlet sediment concentration. Based on these data, we adopted a depth-averaged two-dimensional hydrodynamic model coupled with a sediment transport model to simulate the flash flood accident. The results revealed that the flash flood enlargement in confluence streams is mainly induced by the inflows, and the flash flood enlargement in bifurcation streams is largely affected by the sediment deposition. The bifurcation of flows can decrease the peak discharge of each branch, but may increase the flooded area near the streams. Flow in the supercritical slope runs at a very fast velocity, and seldom deposits sediment in the steep channel. Meanwhile, most sediment is transported to the streams with flat hydraulic slopes. Due to the functioning of the reservoir, the transition region from supercritical slope to subcritical slope has a much larger probability of being submerged during the flood

UNetGE: A U-Net-Based Software at Automatic Grain Extraction for Image Analysis of the Grain Size and Shape Characteristics

The shape and the size of grains in sediments and soils have a significant influence on their engineering properties. Image analysis of grain shape and size has been increasingly applied in geotechnical engineering to provide a quantitative statistical description for grain morphologies. The statistic robustness and the era of big data in geotechnical engineering require the quick and efficient acquirement of large data sets of grain morphologies. In the past publications, some semi-automation algorithms in extracting grains from images may cost tens of minutes. With the rapid development of deep learning networks applied to earth sciences, we develop UNetGE software that is based on the U-Net architecture—a fully convolutional network—to recognize and segregate grains from the matrix using the electron and optical microphotographs of rock and soil thin sections or the photographs of their hand specimen and outcrops. Resultantly, it shows that UNetGE can extract approximately 300~1300 grains in a few seconds to a few minutes and provide their morphologic parameters, which will ably assist with analyses on the engineering properties of sediments and soils (e.g., permeability, strength, and expansivity) and their hydraulic characteristics

A Novel Hybrid LMD–ETS–TCN Approach for Predicting Landslide Displacement Based on GPS Time Series Analysis

Landslide disasters cause serious property losses and casualties every year. Landslide displacement prediction is fundamental for mitigating landslide disasters. Several approaches have been used to predict landslide displacement, yet a more accurate and reliable displacement prediction still has a poor understanding of landslide early warning systems for landslide mitigation, due to limited data and mutational displacements. To boost the robustness and accuracy of landslide displacement prediction, this paper assembled a new hybrid model containing the local mean decomposition (LMD), innovations state space models for exponential smoothing (ETS), and the temporal convolutional network (TCN). The proposed model, which is based on over 10 years of long-term time series monitoring GPS data, was tested on the selected case—stepwise Baijiabao landslide in the Three Gorges Reservoir area of China (TGRA) was tested by the proposed model. The results presented that the LMD–ETS–TCN model has the best performance in comparison with other benchmark models. Compared with autoregressive integrated moving average (ARIMA), support vector regression (SVR), and long short-term memory neural network (LSTM), the accuracy was noticeably improved by an average of 40.9%, 46.2%, and 22.1%, respectively. The robustness and effectiveness of the presented approach are attested, and it has discernible improvements for landslide displacement prediction