Search Results (37)

Temporary vegetation measures are the most common methods for reducing soil erosion of spoil heaps during construction; however, their regulatory mechanisms on soil and water loss have not been sufficiently studied. This study compared the impacts of five temporary vegetation measures (turfing 300 cm (TF-300 cm), turfing 75 cm (TF-75 cm), grass seeding 300 cm (GS-300 cm), grass seeding 75 cm (GS-75 cm), and synthetic turf (ST)) on the dynamic processes of runoff and sediment yield as well as hydraulic parameters under simulated rainfall experiments. A 30° bare slope (BS) was set up as the control. The results indicated that (1) all measures delayed the onset of runoff by 57–233%, effectively decreasing the runoff rate and the average erosion rate by 45–49% and 91–99%, respectively; (2) these measures reduced the average Reynolds number by 45–52% and diminished both the average runoff shear force and runoff power by 44–60%; and (3) the effectiveness in reducing runoff and sediment loss ranked as follows: turfing > synthetic turf > grass seeding, When these measures are applied locally to the bottom 25% of the slope, the efficiency of runoff and sediment reduction can exceed 89% for the entire slope. Our findings provide valuable insights for designing temporary vegetation measures in construction. Full article

Limited by water and heat conditions, the southwest alpine valley area has a dry climate, complex terrain, low vegetation coverage, and a very fragile ecological environment. The runoff plots of different slope gradients (10°, 15°, and 20°), slope lengths (2, 5, and 10 m) and reverse slope terrace (RST) in the Lancang River arid valley were taken as the objects. Through in situ observation of the slope runoff and sediment yield of six natural erosive rainfalls, the contribution rate of different factors was quantified, and the effect mechanism was revealed. The main results were as follows: (1) Sediment yields of different rainfalls were closely correlated with rainfall type and duration. Under the conditions of heavy rain (rain II and III), there was a critical slope gradient, and the maximum sediment yield was achieved when the slope gradient was 15°. (2) The runoff and sediment reduction benefits of horizontal terraces were 24.88% and 46.25%, and these benefits were increased by 1.47 times and 1.30 times after setting the RST, and the sediment reduction benefits increased significantly with the increase in the number of RSTs (p < 0.05). (3) In this study, rainfall intensity contributed the most to the runoff yield rate (34.5%), followed by slope length (15.1%) and horizontal terrace (7.2%). Slope length, rain intensity, and horizontal terrace order contributed 25.9%, 18.0%, and 11.4% to the sediment yield rate, respectively. (4) There was a significant linear correlation between sediment yield and runoff yield on different slopes (p < 0.05). The critical runoff yield rate decreased with the increase in slope length, the RST significantly increased the critical runoff yield rate (2.91 times), and it increased with the increase in RST numbers. This study can provide a scientific basis and reference for the prevention and control of soil and water loss and ecological restoration on the slope of the arid valley in the southwest alpine and canyon area. Full article

Oil pipelines are susceptible to significant hydraulic erosion from mountain torrents during the flood season when passing through the mountain valley area, which can lead to soil erosion on the pipe surface and expose the pipeline. Accordingly, this study centers on investigating the critical issue of the failure mechanism caused by flash flood erosion in the exposed section of oil pipelines. Both indoor testing and numerical simulation research methods are employed to analyze the flow field distribution characteristics of flash floods in proximity to an exposed pipeline. This study explores the patterns of soil loss around pipelines of varying pipe diameters, levels of exposure, and pipe flow angles. In addition, the spatial and temporal evolution mechanism of pipelines overhang development under the action of flash floods was elucidated. The experimental observations indicate that as the pipe diameter increases, the failure rate of the soil surrounding the pipe accelerates, while the erosion effect on the soil around the executives becomes more pronounced. Additionally, a larger pipe flow angle leads to a reduced soil loss in the downstream direction of the pipe. During flash flood events, the scouring action on the soil surrounding the pipe leads to rapid compression of the flow field around the pipe, while the vortex at the pipe’s bottom exacerbates soil corrosion. Additionally, the maximum pressure exerted on pipeline surfaces at pipeline flow angles of 30°, 60°, and 90° is 14,382 Pa, 16,146 Pa, and 17,974 Pa, respectively. The research results offer valuable insights into pipeline, soil, and water conservation projects in mountain valley regions. Full article

Debris flows are highly unpredictable and destructive natural hazards that present significant risks to both human life and infrastructure. Despite advances in machine learning techniques, current predictive models often fall short due to the insufficient and low-quality historical data available for training. In this study, we introduce a hybrid approach that combines physical model experiments with a gradient boosting regression model to enhance the accuracy and reliability of debris flow predictions. By integrating experimental data that closely simulate real-world flow conditions, the gradient boosting regression model is trained on a more robust foundation, enabling it to capture the complex dynamics of debris flows under various conditions. Selecting slide mass, slope length, yield stress, and slope angle as explanatory variables, we focus on quantify two critical debris flow parameters—frontal thickness and velocity—at indicated locations within the flow. The model demonstrates strong predictive performance in forecasting these key parameters, achieving coefficients of determination of 0.938 for slide thickness and 0.934 for slide velocity. This hybrid approach not only simplifies the prediction process but also significantly improves its precision, offering a valuable tool for real-time risk assessment and mitigation strategies in debris flow-prone regions. Full article

Mountain areas are prone to the occurrence of extreme events, especially torrential floods, amplified by climatic and environmental changes. In this context, it is mandatory to increase resilience and guide decision-makers toward more effective measures. Life cycle assessment (LCA) is considered as a decision support tool that can provide the qualitative and quantitative criteria required by the Do No Significant Harm, thus contributing to a more accurate assessment of environmental impacts of the torrent control structures. This study aimed to investigate the current state of the LCA applications in the torrent control to provide practitioners perspectives for new research and a pathway for optimized LCA analysis. Our analysis reveals that in the torrent control area, these studies are still limited. Most of the papers considered Ecoinvent as the main database source and cradle to grave as the main system boundary. This study suggests that restoring the functional capacity of dams and other torrent control structures instead of demolition or decommissioning from the end-of-life stage will ensure an orientation towards more sustainable and circular strategies. Although strong partnerships and consistent efforts are needed, general findings reveal that LCA is a useful tool for moving towards more sustainable construction practices. Full article

Sediment management is fundamental for managing mountain watercourses and their upslope catchment. A multidisciplinary approach—not limited to the discipline of hydraulics—is necessary for investigating the alterations in sediment transport along the watercourse by detecting those reaches dominated by erosion and deposition processes, by quantifying the sediment volume change, by assessing the functionality of the existing torrent control structures, and by delimitating the riparian vegetation patches. To pursue these goals, specific continuous monitoring is essential, despite being extremely rare in mountain catchments. The present study proposed an integrated approach to determine the hydro-morphological–sedimentological–ecological state of a mountain watercourse though field- and desk-based analyses. Such an integral approach includes a rainfall–runoff model, a morphological change analysis and the application of empirical formulations for estimating peak discharge, mobilizable sediment/large wood volume and watercourse hydraulic capacity, at reach and catchment scales. The procedure was tested on the Upper Adda River catchment (North Italy). The results identified where and with what priority maintenance and monitoring activities must be carried out, considering sediment regime, torrent control structures and vegetation. This study is an example of how it is possible to enhance all existing information through successive qualitative and quantitative approximations and to concentrate new resources (human and economic) on specific gaps, for drafting a scientifically robust and practical sediment management plan. Full article

Urban underground pipelines (UUPs) are critical infrastructure, and their safe operation has become a key concern in Chinese society. Currently, the tripartite social roles of the local people’s government, pipeline management departments, and the public are crucial in the informatization of urban underground pipelines. In this study, a survey was conducted among 126 professionals and technical personnel involved in underground pipeline informatization across eight cities in different regions of China. A quantitative weighted evaluation model was established using the Project Quantitative Index (PQI) and principal component analysis (PCA) to investigate the value of the tripartite aforementioned social groups in UUP informatization. The results indicate: (1) There is a significant positive correlation between the tripartite social roles and the promotion of UUP informatization. Moreover, the indicators with the highest PQI value are “Establishment of UUP informatization management departments” and “Support the work of the UUP informatization industry association” under the role of the local people’s government. (2) The informatization work of underground pipelines in different cities is affected differently by the tripartite social roles. This suggests that the local people’s government and professional management departments in different cities can proactively leverage their unique advantages in UUP informatization based on their specific circumstances. (3) PCA results showed that the indicators related to the public carried significant weight, indicating that the public also played an important role in UUP informatization. The degree of UUP informatization in the eight studied cities is ranked as follows: Guangzhou > Beijing > Qingdao > Kunming > Shanghai > Chengdu > Wuhan > Sian. This paper further discusses the unique roles and contributions of the tripartite social groups in UUP informatization, aiming to provide decision support for the future construction, management, and safe operation and maintenance of urban underground pipelines in China. Full article

Frequent mountain torrent disasters have caused significant losses to human life and wealth security and restricted the economic and social development of mountain areas. Therefore, accurate identification of mountain torrent hazards is crucial for disaster prevention and reduction. In this study, based on historical mountain torrent hazards, a mountain torrent hazard prediction model was established by using Bayesian Model Average (BMA) and three classic machine learning algorithms (gradient-boosted decision tree (GBDT), backpropagation neural network (BP), and random forest (RF)). The mountain torrent hazard condition factors used in modeling were distance to river, elevation, precipitation, slope, gross domestic product (GDP), population, and land use type. Based on the proposed BMA model, flood risk maps were produced using GIS. The results demonstrated that the BMA model significantly improved upon the accuracy and stability of single models in identifying mountain torrent hazards. The F1-values (comprehensively displays the Precision and Recall) of the BMA model under three sets of test samples at different locations were 3.31–24.61% higher than those of single models. The risk assessment results of mountain torrents found that high-risk areas were mainly concentrated in the northern border and southern valleys of Yuanyang County, China. In addition, the feature importance analysis result demonstrated that distance to river and elevation were the most important factors affecting mountain torrent hazards. The construction of projects in mountainous areas should be as far away from rivers and low-lying areas as possible. The results of this study can provide a scientific basis for improving the identification methods of mountain torrent hazards and assisting decision-makers in the implementation of appropriate measures for mountain torrent hazard prevention and reduction. Full article

Climate change has intensified the risk of extreme precipitation, while mountainous areas are constrained by complex disaster mechanisms and difficulties in data acquisition, making it challenging for existing critical rainfall threshold accuracy to meet practical needs. Therefore, this study focuses on Yunnan Province as the research area. Based on historical flash flood events, and combining remote sensing data and measured data, 12 causative factors are selected from four aspects: terrain and landforms, land use, meteorology and hydrology, and population and economy. A combined qualitative and quantitative method is employed to analyze the relationship between flash floods and triggering factors, and to calibrate the parameters of the RTI (Rainfall Threshold Index) model. Meanwhile, machine learning is introduced to quantify the contribution of different causative factors and identify key causative factors of flash floods. Based on this, a parameter η coupling the causative mechanism is proposed to optimize the RTI method, and develop a framework for calculating county-level critical rainfall thresholds. The results show that: (1) Extreme rainfall, elevation, slope, and other factors are direct triggers of flash floods, and the high-risk areas for flash floods are mainly concentrated in the northeast and southeast of Yunnan Province. (2) The intraday rainfall has the highest correlation with the accumulated rainfall of the previous ten days; the critical cumulative rainfall ranges from 50 mm to 400 mm. (3) The county-level critical rainfall threshold for Yunnan Province is relatively accurate. These findings will provide theoretical references for improving flash flood early warning methods. Full article

The Lhasa to Nyingchi Expressway in Xizang made efforts to protect the ecological environment during its construction, but it still caused varying degrees of damage to the fragile ecosystems along the route. Accurately assessing the process of change in the ecological environment quality in this region holds significant research value. This study selected the Linzhi-to-Gongbo’gyamda section of the Lhasa-to-Nyingchi Expressway as the research area. Firstly, based on the remote sensing ecological index (RSEI), this study constructed an ecological environmental quality evaluation system for the Xizang region. Subsequently, using the Google Earth Engine (GEE) platform, sub-indicators were extracted, and the combination weighting method of game theory was employed to determine indicator weights. This process resulted in the calculation of the MRSEI for the study area from 2012 to 2020. Finally, by utilizing the spatial distribution of the MRSEI, monitoring the level of MRSEI changes, and employing the transition matrix, this study analyzed the changing trend of the ecological environmental quality from 2012 to 2020. The results indicate that the MRSEI are 0.5885, 0.5951, 0.5296, 0.6202, 0.59, 0.5777, 0.5898, 0.5703, and 0.5987, showing a gradual increasing trend with an initial decrease followed by an ascent. This trend is mainly attributed to concentrated road construction and subsequent ecological restoration, leading to an improvement in the restoration effect. Simultaneously, the ecological environmental quality remains relatively stable, with 69.5% of the region showing no change, and the remaining 30.5% experiencing improvement exceeding degradation. Specifically, there were significant improvements in the land with ecological quality levels categorized as poor, fair, moderate, and good. The types of degradation primarily involved lands originally classified as excellent and good degrading to good and moderate levels, respectively. The above results serve as a theoretical reference for the ecological restoration project of the Lhasa-to-Nyingchi Expressway. Full article

There are many mountain torrent disasters caused by melting icebergs and snow in Xinjiang, which are very different from traditional mountain torrent disasters. Most of the areas affected by snowmelt are in areas without data, making it very difficult to predict and warn of disasters. Taking the Lianggoushan watershed at the southern foot of Boroconu Mountain as the research subject, the key factors were screened by Pearson correlation coefficient and the factor analysis method, and the data of rainfall, water level, temperature, air pressure, wind speed, and snow depth were used as inputs, respectively, with support vector regression (SVR), random forest (RF), k-nearest neighbor (KNN), artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory neural network (LSTM) models used to simulate the daily average water level at the outlet of the watershed. The research results showed that the root mean square error (RMSE) values of SVR, RF, KNN, ANN, RNN, and LSTM in the training period were 0.033, 0.012, 0.016, 0.022, 0.011, and 0.010, respectively, and in the testing period they were 0.075, 0.072, 0.071, 0.075, 0.075, and 0.071, respectively. The performance of LSTM was better than that of other models, but it had more hyperparameters that needed to be optimized. The performance of RF was second only to LSTM; it had only one hyperparameter and was very easy to determine. The RF model showed that the simulation results mainly depended on the average wind speed and average sea level pressure data. The snowmelt model based on machine learning proposed in this study can be widely used in iceberg snowmelt warning and forecasting in ungauged areas, which is of great significance for the improvement of mountain flood prevention work in Xinjiang. Full article

Recent improvements in remote sensing technologies have boosted building detection techniques from rough classifications using moderate resolution imagery to precise extraction from high-resolution imagery. Shadows frequently emerge in high-resolution urban images. To exploit shadow information, we developed a novel building detection and classification algorithm for images of urban areas with large-size shadows, employing only the visible spectral bands to determine the height levels of buildings. The proposed method, building general-classified by height (BGCH), calculates shadow orientation, detects buildings using seed-blocks, and classifies the buildings into different height groups. Our proposed approach was tested on complex urban scenes from Toronto and Beijing. The experimental results illustrate that our proposed method accurately and efficiently detects and classifies buildings by their height levels; the building detection rate exceeded 95%. The precision of classification by height levels was over 90%. This novel building-height-level detection method provides rich information at low cost and is suitable for further city scene analysis, flood disaster risk assessment, population estimation, and building change detection applications. Full article

The strata in the Shita Mountain, Yunkai region, are predominantly composed of clastic rocks with intercalated limestones. However, the precise stratigraphic age remains uncertain due to the scarcity of fossils. Previously, conglomerate layers in this region were considered indicative of the Yunan Orogeny during the Cambrian–Ordovician transition. However, through the identification of 12 lithofacies types and 5 lithofacies combinations in the conglomerate layers of the Shita Mountain section, it has been confirmed that these layers represent a fan delta depositional environment characterized by debris flow, traction flow, torrent, and rock flow. Based on the presence of brachiopod fossils dating to the Early–Middle Ordovician, we propose a novel two-episode model for the Yunan Orogeny. The first episode corresponds to submarine fan deposition, while the second episode involves tectonic uplift and a short-term sedimentary hiatus. Further analysis of the detrital zircon provenance reveals a strong affinity among the Yunkai area, India, Antarctica, the Lhasa, the Himalayas, Southern Qiangtang, and Western Australia during the Early–Middle Ordovician transition under the Gondwana assemblage background. Full article

The automatic identification of construction projects, which can be considered as complex scenes, is a technical challenge for the supervision of soil and water conservation in urban areas. Construction projects in high-resolution remote sensing images have no unified semantic definition, thereby exhibiting significant differences in image features. This paper proposes an identification method for construction projects based on the detection of detailed ground objects, which construction projects comprise, including movable slab houses, buildings under construction, dust screens, and bare soil (rock). To create the training data set, we select highly informative detailed ground objects from high-resolution remote sensing images. Then, the Faster RCNN (region-based convolutional neural network) algorithm is used to detect construction projects and the highly informative detailed ground objects separately. The merging of detection boxes and the correction of detailed ground object combinations are used to jointly improve the confidence of construction project detection results. The empirical experiments show that the accuracy evaluation indicators of this method on a data set of Wuhan construction projects outperform other comparative methods, and its AP value and F1 score reached 0.773 and 0.417, respectively. The proposed method can achieve satisfactory identification results for construction projects with complex scenes, and can be applied to the comprehensive supervision of soil and water conservation in construction projects. Full article

Floods are one of the most destructive natural hazards in Pakistan, causing significant damage. During monsoons, when westerly winds and concentrated rainfall occur in rivers’ catchments, floods become unmanageable. Given the limited resources of Pakistan, there has been minimal effort to quantify the amount of rainfall and runoff generated by ungauged catchments. In this study, ten hill torrents in Koh e Suleiman (District Rajanpur and DG Khan), an area affected by flash flooding in 2022 due to extreme precipitation events, were investigated. The Hydrologic Engineering Centre’s Hydrologic Modeling System (HEC-HMS), a semi-distributed event-based hydrological model, was used to delineate streams and quantify runoff. Statistical analysis of the rainfall trends was performed using the non-parametric Gumbel extreme value analysis type I distribution, the Mann–Kendall test, and Sen’s slope. The results of the study show that the total inflow to the river Indus is 0.5, 0.6, 0.7, and 0.8 MAF for 25, 50, 100, and 200 years of return period rainfall, respectively. This study presents appropriate storage options with a retention potential of 0.14, 1.14, and 1.13 MAF based on an analysis of the hydrology of these hill torrents to enhance the spate irrigation potential as flood control in the future. Full article