Search Results (41)

Check dams play a pivotal role in soil and water conservation engineering as they mitigate debris flow and decelerate the slope of the river channel by intercepting sediments, thereby preventing disasters. However, as ecological conservation and landscape integration have become significant, functions, safety, harmony, and aesthetics with the surroundings must be considered in the design of check dams. In this study, a questionnaire survey was conducted based on scenic beauty estimation (SBE) and image segmentation using artificial intelligence to evaluate the landscape quality of soil and water conservation projects. Data were collected from the photos which were segmented into vegetation, structure, sky, land, and water. The proportion of each segment was calculated to explore the relationship with the scenic beauty of the landscapes. Regions with prevalent vegetation and water received favorable evaluations, whereas areas with a higher proportion of land were less preferred. Even when vegetation was present in high quantities, an unorganized arrangement was less desirable. Identified key factors influencing the scenic beauty of the landscape can be considered in the design of soil and water conservation engineering projects. Full article

Sediment disasters, triggered by heavy rainfall, have resulted in significant human casualties and economic damage annually worldwide. Therefore, the promotion and implementation of disaster prevention strategies have emerged as crucial measures to mitigate the human and financial losses inflicted by these disasters. This article examines case studies in the mountainous regions of China and Japan, encompassing terrain conditions, local disaster risk factors, and residents’ awareness of disaster prevention, as well as their living conditions. The CAUSE model was employed to cultivate a relationship of mutual trust and cooperation with the residents through activities that promote disaster prevention and reduction. Feedback was also collected from the residents. In addition, relevant disaster prevention personnel were organized to participate in disaster prevention technical training, and feedback was collected through questionnaires (CAUSE is an acronym derived from the first letter of Confidence, Awareness, Understanding, Satisfaction with proposed Solutions, and Enactment). From the above inspection and analysis techniques used in the case studies in China and Japan, it is confirmed that disaster prevention and promotion work is closely linked. This analysis underscores the importance, necessity, and effectiveness of promoting disaster prevention at the local level. Furthermore, it offers crucial technical support for the local government’s efforts in disaster reduction and prevention. Full article

Debris flows are rapid, destructive landslides that pose significant risks in mountainous regions. This study presents a novel algorithm to simulate debris flow dynamics, focusing on sediment transport from 0-order basins to depositional zones. The algorithm integrates the D8 flow direction method with an adjustable friction coefficient to enhance the accuracy of debris flow trajectory and deposition modeling. Its performance was evaluated on three real-world cases in the Otoishi River basin, affected by rainfall-induced debris flows in July 2017, and the Aso Bridge landslide triggered by the 2016 Kumamoto Earthquake. By utilizing diverse friction coefficients, the study effectively captured variations in debris flow behavior, transitioning from fluid-like to more viscous states. Simulation results demonstrated a precision of 88.9% in predicting debris flow paths and deposition areas, emphasizing the pivotal role of the friction coefficient in regulating mass movement dynamics. Additionally, Monte Carlo (MC) simulations enhanced the identification of critical slip surfaces within 0-order basins, increasing the accuracy of debris flow source detection. This research offers valuable insights into debris flow hazards and risk mitigation strategies. The algorithm’s proven effectiveness in simulating real-world scenarios highlights its potential for integration into disaster risk assessment and prevention frameworks. By providing a reliable tool for hazard identification and prediction, this study supports proactive disaster management and aligns with the goals of sustainable development in regions prone to debris flow disasters. Full article

Revealing geological environment resilience (GER) under seawater intrusion (SWI) hazards is a prerequisite for solving groundwater resource depletion, land salinization, and ecological degradation in coastal cities. This study applies the resilience design approach based on urban complex adaptive systems theory to understand the impact of SWI on the geological environment. Taking SWI as the research object, the GER evaluation method under SWI disaster was established by selecting five elastic indexes: disturbance intensity, geological environment vulnerability, stress resistance, recovery, and adaptability. This method is used to evaluate the GER level of the coastal areas of Shenzhen in recent years under the impact of SWI hazards. The study found that there is a negative correlation between the intensity of disturbance and precipitation amount. The vulnerability is greater the closer the distance to the coastline and the shallower the depth of bedrock burial. Resistance is composed of early warning ability and disaster prevention ability, and the result is 10.07, which belongs to the medium level. The recovery is 1.49, which is at a relatively high level, indicating a high capacity for restoration ability. The adaptability increased from 3.03 to 3.13, so that the area of seawater intrusion is becoming smaller. GER is affected by precipitation amount and depth of bedrock burial; the greater the precipitation and the shallower the bedrock burial, the lower the GER. Precipitation amount significantly impacts the SWI situation in the eastern coastal area of Shenzhen. In the central region, the impact of precipitation on GER is less significant. However, in the western region, the depth of bedrock burial primarily affects GER. Compared to completely weathered granite, Pleistocene fluvial plain sediments are more susceptible to SWI effects in freshwater environments. This study contributes to a deeper understanding of the impact of SWI on the geological environment in coastal areas, providing decision-makers with the necessary knowledge to develop targeted and effective governance and prevention strategies. Full article

The multiphase components of natural ice contain gas, ice, unfrozen water, sediment and brine. X-ray computed tomography (CT) analysis of ice multiphase components has the advantage of high precision, non-destructiveness and visualization; however, it is limited by the segmentation thresholds. Due to the proximity of the CT value ranges of gas, ice, unfrozen water, sediment and brine within the samples, there is uncertainty in the artificial determination of the CT image segmentation thresholds, as well as unsuitability of the global threshold segmentation methods. In order to improve the accuracy of multi-threshold segmentation in CT images, a CT system was used to scan the Yellow River ice, the Wuliangsuhai lake ice and the Arctic sea ice. The threshold ranges of multiphase components within the ice were determined by watershed algorithm to construct a high-precision three-dimensional ice model. The results indicated that CT combined with watershed algorithm was an efficient and non-destructive method for obtaining microscopic information within ice, which accurately segmented the ice into multiphase components such as gas, ice, unfrozen water, sediment, and brine. The gas CT values of the Yellow River ice, the Wuliangsuhai lake ice and the Arctic sea ice ranged from −1024 Hu~−107 Hu, −1024 Hu~−103 Hu, and −1024 Hu~−160 Hu, respectively. The ice CT values of the Yellow River ice, the Wuliangsuhai lake ice and the Arctic sea ice ranged from −103 Hu~−50 Hu, −100 Hu~−38 Hu, −153 Hu~−51 Hu. The unfrozen water CT values of the Yellow River ice and the Wuliangsuhai lake ice ranged from −8 Hu~18 Hu, −8 Hu~13 Hu. The sediment CT values of the Yellow River ice and the Wuliangsuhai lake ice ranged from 20 Hu~3071 Hu, 20 Hu~3071 Hu, and the brine CT values of the Arctic sea ice ranged from −6 Hu~3071 Hu. The errors between the three-dimensional ice model divided by threshold ranges and measured sediment content were less than 0.003 g/cm³, which verified the high accuracy of the established microscopic model. It provided a scientific basis for ice engineering, ice remote sensing, and ice disaster prevention. Full article

Wind plays a crucial role in the formation of coastal dunes, and in China, these dunes are shaped by the combined effects of typhoons and winter monsoons. However, the unique characteristics of Chinese coastal dunes impacted by these forces remain poorly understood, as prior research has predominantly focused on their separate impacts. This study employed RTK-GPS technology to conduct 14 high-precision morphological assessments of coastal dunes in Tannan Bay, Pingtan Island, Fujian, China, between 2014 and 2017, aiming to investigate the response patterns of coastal dunes to typhoons and winter monsoons. Our findings indicate that coastal dunes respond variably to typhoons of differing intensities, with considerable height changes across different sections; however, winter monsoons contribute to an overall increase in dune height. Both dune volume and height increased due to continuous sediment accumulation at the base of the windward slopes. Additionally, the average high-water level advanced seaward by 3.0–4.0 m. We concluded that in Tannan Bay, typhoons exert only a temporary “braking” effect on dune morphology, whereas the winter monsoon is the primary driver of its long-term evolution. These findings contribute to a comprehensive understanding of coastal dune dynamics and provide insights for effective coastal sand management and disaster prevention strategies. Full article

There has been a frequent occurrence of tailing dam failures in recent years, leading to severe repercussions. Flood overtopping is an important element contributing to these failures. Nevertheless, there is a scarcity of studies about the evolutionary mechanisms of dam breaches resulting from flood overtopping. In order to fill this knowledge vacuum, this study focused on the evolutionary characteristics and triggering mechanisms of overtopping failures, utilizing the Heshangyu tailings pond as a prototype. The process of overtopping breach evolution was revealed by the conduction of small-scale model testing. A scaled-down replica of the tailings pond was constructed at a ratio of 1:150, and a controlled experiment was conducted to simulate a breach in the dam caused by water overflowing. Based on the results, the following conclusions were drawn: (1) The rise in water level in the pond caused the tailings to become saturated, leading to liquefaction flow and local slope sliding at the initial dam. If the sediment-carrying capacity of the overflowing water exceeded the shear strength of the tailings, water erosion would accelerate landslides on the slope, generating a sand-laden water flow. (2) The breach was primarily influenced by water erosion, which subsequently resulted in both laterally widened and longitudinally deepened breach. As the breach expanded, the sand-carrying capacity of the water flow increased, leading to a faster rate of failure. The breach process of overtopping can be categorized into four distinct stages: gully formation stage, lateral broadening stage of gully, cracks and collapse on the slope surface, and stable stage of collapse. (3) The tailings from the outflow spread downstream in a radial pattern, forming an alluvial fan. Additionally, the depth of the deposited mud first increased and subsequently declined as the distance from the breach grew. The findings of this research provide an important basis for the prevention and control of tailings dam breach disasters due to overtopping. Full article

The spatial distribution of vegetation in a basin has a far-reaching influence on the potential for sediment separation and transport capacity. However, many landslides induced by strong earthquakes have greatly changed the existing pattern, which further increases the probability of debris flow in a basin during heavy rainfall and has a significant impact on the stability of the basin. Thus, this study selected the debris flow basin in the Qipan catchment of the Wenchuan earthquake area as the research object. Multisource and high-precision remote sensing images were used to analyze the land use changes in the basin, and the index of connectivity (IC) was introduced to analyze the evolution of sediment transport capacity. An ecosystem stability assessment method suitable for post-earthquake debris flow basins was proposed. Through quantitative assessment of the ecosystem stability of the basin after the Wenchuan earthquake in 2008 and the two debris flow events after the earthquake, the dynamic relationship between the debris-flow-prone area and the ecosystem stability of the basin was revealed. The results showed that the stability of the ecosystem in the Qipan catchment increased annually, indicating a stable and substable state. The spatial distribution characteristics were lower in the north and south and greater in the middle. By comparing the evaluation results with the actual terrain change trend, the accuracy and feasibility of the evaluation method are verified. The results of this study provide a scientific basis for the formulation of regional disaster prevention strategies and help to accelerate the improvement of regional stability in debris-flow-prone areas. Full article

In Japan, the heavy rain disaster that occurred in July 2018 revealed that about 70% of the streams affected by debris flows that resulted in human casualties were small, steep mountain streams with a catchment area < 0.05 km². Generally, many streams that are close to residential houses or roads do not have a constant flow of water and are known to pose a high risk of human fatalities when a debris flow occurs. This study aimed to promote sediment control as debris flow countermeasures in non-flowing mountain streams, utilizing secondary manufactured products (permeable debris flow barriers) with excellent constructability, focusing on the mechanism of sediment outflow from the gaps between a permeable debris flow barrier and mountain stream side banks. The necessity and effectiveness of preventative measures based on preliminary experimental results are presented. When impermeable structures were installed at both ends of the permeable debris flow barrier side, compared to using only a permeable debris flow barrier (covering the entire width with permeable debris flow barriers), we found that the capture function improved significantly, achieving a 200% increase in effectiveness. Full article

This study presents an in-depth analysis of the dynamic beach landscapes of Hainan Island, which is located at the southernmost tip of China. Home to over a hundred natural and predominantly sandy beaches, Hainan Island confronts significant challenges posed by frequent marine natural disasters and human activities. Addressing the urgent need for long-term studies of beach dynamics, this research involved the use of CoastSat to extract and analyze shoreline data from 20 representative beaches and calculate the slopes of 119 sandy beaches around the island for the period from 2013 to 2023. The objective was to delineate the patterns of beach evolution that contribute to the prevention of sediment loss, the mitigation of coastal hazards, and the promotion of sustainable coastal zone management. By employing multi-source remote sensing imagery and the CoastSat tool, this investigation validated slope measurements across selected beaches, demonstrating consistency between the calculated and actual distances despite minor anomalies. The effective use of the finite element solution (FES) in the 2014 global tidal model for tidal corrections further aligned the coastlines with the mean shoreline, underscoring CoastSat’s utility in enabling precise coastal studies. The analysis revealed significant seasonal variations in shoreline positions, with approximately half of the monitored sites showing a seaward progression in summer and a retreat in winter, which were linked to variations in wave height. The southern beaches exhibited distinct seasonal variations, which contrasted with the general trend due to differing wave impacts. The western and southern shores showed erosion, while the northern and eastern shores displayed accretion. The calculated slopes across the island indicated that the southern beaches had steeper slopes, while the northern areas exhibited more pronounced slope variations due to wave and tidal impacts. These findings highlight the critical role of integrated coastal management and erosion control strategies in safeguarding Hainan Island’s beaches. By understanding the mechanisms driving seasonal and regional shoreline changes, effective measures can be developed to mitigate the impacts of erosion and enhance the resilience of coastal ecosystems amidst changing environmental conditions. This research provides a foundational basis for future efforts aimed at the sustainable development and utilization of coastal resources on Hainan Island. Full article

The second-largest wildfire in the history of South Korea occurred in 2022 due to strong winds and dry climates. Quantitative evaluation of soil erosion is necessary to prevent subsequent sediment disasters in the wildfire areas. The erosion rates in two watersheds affected by the wildfires were assessed using the revised universal soil loss equation (RUSLE), a globally popular model, and the soil erosion model for mountain areas (SEMMA) developed in South Korea. The GIS-based models required the integration of maps of the erosivity factor, erodibility factor, length and slope factors, and cover and practice factors. The rainfall erosivity factor considering the 50-year and 80-year probability of rainfall increased from coastal to mountainous areas. For the LS factors, the traditional version (TV) was initially used, and the flow accumulation version (FAV) was additionally considered. The cover factor of the RUSLE and the vegetation index of the SEMMA were calculated using the normalized difference vegetation index (NDVI) extracted from Sentinel-2 images acquired before and after the wildfire. After one year following the wildfire, the NDVI increased compared to during the year of the wildfire. Although the RUSLE considered a low value of the P factor (0.28) for post-fire watersheds, it overestimated the erosion rate by from 3 to 15 times compared to the SEMMA. The erosion risk with the SEMMA simulation decreased with the elapsed time via the vegetation recovery and stabilization of topsoil. While the FAV of RUSLE oversimulated by 1.65~2.31 times compared to the TV, the FAV of SEMMA only increased by 1.03~1.19 times compared to the TV. The heavy rainfall of the 50-year probability due to Typhoon Khanun in 2023 generated rill and gully erosions, landslides, and sediment damage in the post-fire watershed on forest roads for transmission tower construction or logging. Both the RUSLE and SEMMA for the TV and FAV predicted high erosion risks for disturbed hillslopes; however, their accuracy varied in terms of the intensity and extent. According to a comparative analysis of the simulation results of the two models and the actual erosion situations caused by heavy rain, the FAV of SEMMA was found to simulate spatial heterogeneity and a reasonable erosion rate. Full article

Glacial lake outburst floods (GLOFs) are one of the most severe disasters in alpine regions, releasing a large amount of water and sediment that can cause fatalities and economic loss as well as substantial damage to downstream infrastructures. The risk of GLOFs in the Himalayas is exacerbated by glacier retreat caused by global warming. Critical economic corridors, such as the Rongxer Watershed, are threatened by GLOFs, but the lack of risk assessment specific to the watershed hinders hazard prevention. In this study, we propose a novel model to evaluate the risk of GLOF using a combination of remote sensing observations, GIS, and hydrological models and apply this model to the GLOF risk assessment in the Rongxer Watershed. The results show that (1) the area of glacial lakes in the Rongxer Watershed increased by 31.19% from 11.35 km² in 1990 to 14.89 km² in 2020, and (2) 18 lakes were identified as potentially dangerous glacial lakes (PDGLs) that need to be assessed for the GLOF risk, and two of them were categorized as very high risk (Niangzongmajue and Tsho Rolpa). The proposed model was robust in a GLOF risk evaluation by historical GLOFs in the Himalayas. The glacial lake data and GLOF risk assessment model of this study have the potential to be widely used in research on the relationships between glacial lakes and climate change, as well as in disaster mitigation of GLOFs. Full article

Extreme events are increasing in frequency and severity due to climate change, making the littoral zone even more vulnerable and requiring continuous monitoring for its optimized management. The low-lying Ebro Delta ecosystem, located in the NW Mediterranean, was subject to Storm Gloria in the winter of 2020, the most severe coastal storm registered in the area in decades and one of the most intense ever recorded in the Mediterranean. This event caused intense rainfall, severe flooding, the erosion of beaches, and the destruction of coastal infrastructures. In this study, the Landsat-8 and Sentinel-2 satellites were used to monitor the flooding impact and water quality status, including chlorophyll-a, suspended particulate matter, and turbidity, to evaluate the pre-, syn-, and post-storm scenarios. Image processing was carried out using the ACOLITE software and the on-the-cloud Google Earth Engine platform for the water quality and flood mapping, respectively, showing a consistent performance for both satellites. This cost-effective methodology allowed us to characterize the main water quality variation in the coastal environment during the storm and detect a higher flooding impact compared to the one registered three days later by the Copernicus Emergency Service for the same area. Moreover, the time series revealed how the detrimental impact on the water quality and turbidity conditions was restored two weeks after the extreme weather event. While transitional plumes of sediment discharge were formed, no phytoplankton blooms appeared during the study period in the delta. These results demonstrate that the workflow implemented is suitable for monitoring extreme coastal events using open satellite imagery at 10–30 m spatial resolution, thus providing valuable information for early warning to facilitate timely assistance and hazard impact evaluation. The integration of these tools into ecological disaster management can significantly improve current monitoring strategies, supporting decision-makers from the local to the national level in prevention, adaptation measures, and damage compensation. Full article

Landslides pose significant and serious geological threat disasters worldwide, threatening human lives and property; China is particularly susceptible to these disasters. This paper focuses on Pengyang County, which is situated in the Ningxia Hui Autonomous Region of China, an area prone to landslides. This study investigated the application of machine learning techniques for analyzing landslide susceptibility. To construct and validate the model, we initially compiled a landslide inventory comprising 972 historical landslides and an equivalent number of non-landslide sites (Data sourced from the Pengyang County Department of Natural Resources). To ensure an impartial evaluation, both the landslide and non-landslide datasets were randomly divided into two sets using a 70/30 ratio. Next, we extracted 15 landslide conditioning factors, including the slope angle, elevation, profile curvature, plan curvature, slope aspect, TWI (topographic wetness index), TPI (topographic position index), distance to roads and rivers, NDVI (normalized difference vegetation index), rainfall, land use, lithology, SPI (stream power index), and STI (sediment transport index), from the spatial database. Subsequently, a correlation analysis between the conditioning factors and landslide occurrences was conducted using the certainty factor (CF) method. Three landslide models were established by employing logistic regression (LR), functional trees (FTs), and random subspace functional trees (RSFTs) algorithms. The landslide susceptibility map was categorized into five levels: very low, low, medium, high, and very high susceptibility. Finally, the predictive capability of the three algorithms was assessed using the area under the receiver operating characteristic curve (AUC). The better the prediction, the higher the AUC value. The results indicate that all three models are predictive and practical, with only minor discrepancies in accuracy. The integrated model (RSFT) displayed the highest predictive performance, achieving an AUC value of 0.844 for the training dataset and 0.837 for the validation dataset. This was followed by the LR model (0.811 for the training dataset and 0.814 for the validation dataset) and the FT model (0.776 for the training dataset and 0.760 for the validation dataset). The proposed methods and resulting landslide susceptibility map can assist researchers and local authorities in making informed decisions for future geohazard prevention and mitigation. Furthermore, they will prove valuable and be useful for other regions with similar geological characteristics features. Full article

Different sediment-related disasters due to torrential hazards, such as flash floods, debris flows, and landslides, can occur in an Alpine torrential catchment. When protecting infrastructure and human lives, different structural and non-structural protection measures can be used to mitigate permanent and future risks. An overview of the mitigation measures constructed near the Krvavec ski resort in northwest Slovenia (Central Europe) is presented. In May 2018, an extreme debris flood occurred in this area, causing significant economic damage. After the May 2018 event, different field investigations (i.e., geological and topographic surveys) and modeling applications (e.g., hydrological modeling, debris flow) have been conducted with the purpose of preparing the required input data for the design of protection measures against such disasters in future—due to climate change, more disasters are expected to happen in this torrential watershed. The mitigation includes the restoration of local streams, the construction of a large slit check dam for sediment retention, the construction of several smaller check dams and the construction of 16 flexible net barriers with an estimated ~8000 m³ retention volume for controlling in-channel erosion in steep torrential streams. Additionally, in order to observe and monitor potential future extreme events, an extensive monitoring system has been established in the investigated area. This monitoring system will cover measurements of flexible net corrosion, the estimation of concrete abrasion at check dams, periodical geodetic surveys using small drones (UAV), hydro-meteorological measurements using rainfall gauges and water level sensors. The recent extreme floods of August 2023 also hit this part of Slovenia, and this combination of technical countermeasures withstood the event and prevented large amounts of coarse debris from being transported to the downstream section and devastating infrastructure, as was the case in May 2018 during a less extreme event. Therefore, such mitigation measures can also be used in other torrential catchments in the Alpine environment. Full article