Search Results (129)

Accurate spatial identification of check dams is a key prerequisite for evaluating soil and water conservation benefits and optimizing dam system planning on the Loess Plateau. Current deep learning models face severe misclassification and omission issues under complex terrain due to the scarcity of check dam samples and the lack of prior geographic knowledge. This study proposes a recognition method based on Faster R-CNN, constrained by suitable areas and microtopography. The Xiliugou watershed in Inner Mongolia was selected as the study area. Based on Google Earth imagery and field survey data, a check dam sample dataset was constructed, integrating the morphological features of “linear dam body with a trapezoidal slope.” Using the construction suitable area constraints defined by the Technical Specifications for Check Dams and microtopography standard deviation (δ) derived from DEM as dual spatial filtering mechanisms, these were deeply embedded into the Faster R-CNN model to limit the search space and enhance geographic plausibility. Experimental results show that the constrained Faster R-CNN model achieved a precision and recall of 92.86% and 96.89%, compared with the accuracy rate of only deep learning model recognition (60.61%), which significantly increased by 32.25%, indicating that geographical constraints have an enhancing effect. Using this method, a total of 191 embankment dams were identified in the Xiliugou Basin. New 30 unrecorded embankment dams (21 small dams and 9 micro-dams) were discovered. The model’s good generalization ability was verified in the Han Tiechuan geographical isolation area, which contained 153 embankment dam samples, with an accuracy rate of 72.94%. Spatial analysis further revealed the “successive interception along tributaries” distribution pattern and strong spatial aggregation characteristics (box dimension D ≈ 0.36) of check dams in the Xiliugou watershed. This study confirms the critical role of suitable area and microtopography constraints in improving the accuracy and reliability of deep learning models and provides a transferable technical paradigm for automated, high-precision surveys of regional soil and water conservation projects. Full article

Nature-based tourism in protected areas brings economic benefits but can also lead to negative environmental impacts, such as trail degradation. This study aimed to quantify hiking-induced degradation on the Mvubu and Nkonkoni trails in Enseleni Nature Reserve, South Africa. Data were collected through systematic sampling at 20 points along each trail, with 50-m intervals between sampling locations. Several trail degradation indicators were recorded, including: trail grade (TG), landform grade (LG), cross-sectional area (CSA), soil compaction, surface composition, soil texture, and soil moisture. Maximum incision depth (MID) and trail width (WID) were treated as response variables. Statistical relationships between degradation indicators and response variables were analysed using linear regression and partial least squares regression (PLSR). The results indicated significant differences (p < 0.05) between the two trails for several degradation indicators, including surface composition (specifically soil cover), soil compaction, soil texture, and soil moisture. PLSR models explained 19–20% of the variance in MID and 12–55% of the variance in WID. Such weak model performance suggests that trail degradation may be influenced by additional factors not measured in this study. In particular, human behavioural factors, such as hiker avoidance of muddy sections, may play an important role in shaping patterns of trail degradation beyond the measured environmental variables. Early signs of rill erosion were observed on the Mvubu Trail, while informal trail formation was evident on the Nkonkoni Trail. Consequently, the study recommends a dual-track strategy involving revegetation along with the installation of water bars and check dams on the Mvubu Trail to prevent rilling, and “Leave-No-Trace” visitor education for the Nkonkoni Trail to reduce informal path formation. Full article

Flood events are major drivers of soil erosion and sediment yield on the Loess Plateau, where extensive ecological restoration has been implemented. This study investigates runoff–sediment dynamics by analyzing 215 flood events recorded in the Chabagou watershed (1959–2022), with a focus on changes under intensifying restoration efforts. Using long-term hydrological and rainfall data, we applied cluster and discriminant analyses to classify flood events based on sediment hysteresis loops and evaluated variations across three management periods (1959–1979, 1980–1999, and 2000–2022), characterized by progressive increases in check dam construction and vegetation recovery. The results show that the floods characterized by short duration, low peak flow, and low sediment concentration were predominant, accounting for 77.7% of the recorded 215 events. A clear decreasing trend was observed, with average sediment yield and peak discharge declining by approximately 68% and 52%, respectively. Anticlockwise hysteresis loops were most common (45.6%), followed by complex (27.9%) and figure-of-eight loops (23.7%). The proportion of figure-of-eight loops increased notably from 17% to 39%, indicating reduced sediment connectivity due to large-scale ecological restoration. Extreme rainfall events consistently produced complex hysteresis patterns, influenced mainly by rainfall intensity but increasingly modulated by human interventions. These results highlight adaptive watershed management strategies that target figure-of-eight and complex flood events to mitigate erosion and flood risks. Full article

Torrential flows are hazardous hydro-geomorphological phenomena characterized by sudden water discharge and intense sediment transport. They occur in mountainous areas where hydrometeorological monitoring is often limited or absent. The lack of such data hinders the identification of flow types and sediment transport conditions, reducing the effectiveness of mitigation measures. To address this issue, the current study focuses on geomorphic characteristics of torrential watersheds and identifies indirect indicators of torrential activity. The sedimentological and geomorphic signatures of torrential flows in the lower Damdere River catchment (Eastern Rhodopes Mountains, southern Bulgaria) were characterized. To capture inter-annual variability in torrential activity and differences between the Damdere and its tributary the Duandere, we sampled riverbed deposits. We also sampled areas upstream and downstream of the check dam to assess its influence. Samples were analyzed for grain size distribution, petrography, and mineralogy (X-ray diffraction). Results show contrasting controls on sediment supply and transport: the Duandere delivers relatively coarse material, whereas the Damdere attains higher transport capacity during torrential events. The check dam is largely infilled and exerts only local effects by trapping finer sediments upstream. Downstream, the channel retains its torrential character. Inter-annual comparison upstream of the structure shows sediment fining linked to lower flows. Petrographic and XRD data point to mechanically driven erosion and rapid sediment transfer. The results underline the importance of geological–geomorphological indicators in the lack of long-term monitoring in similar mountain catchments and can support flood risk management. Full article

Background: As a key structure for gully control on the Loess Plateau, check dams are designed to intercept sediment and reduce flood peaks without intentional water storage. However, persistent ponding zones have often formed upstream of dams in the Niejia River Basin, exceeding their intended functionality. Methods: This study examines the basin using hydrogen and oxygen stable isotopes to trace hydrological processes. Based on 251 water samples, mixing models and exponential fitting were applied to quantify water sources and transmission times. Results: Results show that precipitation (47.07%) and groundwater (34.48%) are the main sources of channel water. Check dams extended water transmission time in dammed tributaries to 489 days—2.8 times longer than in undammed ones. Conclusions: This delay enhances watershed storage capacity, providing insight into the hydrological impacts of check dams on the Loess Plateau. Full article

The systematic regulation of Polish gravel-bed watercourses, notably intensified in the latter half of the 20th century, coupled with extensive gravel extraction, have become one of the main factors leading to severe channel incision and degradation of hydromorphological features. This paper investigates river renaturalization as a pivotal strategy to restore channel-riparian water connectivity in incised gravel-bed streams of Southern Poland. The river restoration projects were categorized into passive and active techniques. Passive methods, though less common, involve cost-effective methods like the restoration of erodible corridors, island-braided channel patterns, and woody debris presence, while active methods include mainly fish passes, check dam lowering, and artificial riffles. A total of 27 major activities carried out on rivers of Southern Poland were assessed, revealing a trend towards comprehensive renaturalization in collaboration with scientists, pro-environment organizations, and local authorities and communities. Despite the lack of long-term data for most projects, results demonstrated sustained improvements in hydromorphological features, including the shallowing and stabilization of deeply incised channels. Using a natural section of the Czarny Dunajec river, a brief case study was presented to explain the mechanism of spontaneous river renaturalization. It was also shown that a good restoration project should take into account the views of all river stakeholders, anticipate possible development trajectories of a freely migrating river, and assess the potential benefits for both nature and people. Increased deposition of macroplastics together with woody debris in naturally widened river sections, as well as the possible remobilization of pollutants previously trapped in bank sediments, presents an additional challenge for future projects. Full article

Deteriorating check dams pose significant threats to human safety and property, while impeding eco-environmental restoration in soil–water conservation systems in vulnerable watersheds like the Jiuyuangou Basin on China’s Loess Plateau. This study aimed to develop a comprehensive risk assessment framework for the check dam system in the Jiuyuangou Basin, China, to mitigate its threats to safety and eco-environmental restoration. A multi-index and multilevel risk evaluation system was established for check dam systems in the Jiuyuangou Basin, utilizing data gathering, hydrological statistics, numerical computation, and various methodologies. The index weights were determined via the fuzzy analytic hierarchy process with an integrated modeling framework for key parameters. Finally, the risk level of the check dam system in the Jiuyuangou Basin was assessed based on the comprehensive score. The results show that (1) nearly half of the check dams are at mild risk, approximately 25% are at moderate risk, and a few are basically safe. (2) Among various types of risk, the distribution of engineering risk is relatively uniform, environmental risk is generally high, loss risk is relatively concentrated, and management risk is particularly prominent. This research provides a scientific foundation for optimizing check dam governance, enhancing sediment control, and strengthening ecological service functions in vulnerable watersheds. Full article

Understanding the effectiveness of engineering measures in mitigating surface erosion is crucial for sustainable land management. However, studies explicitly quantifying the combined effects of large-scale engineering measures and environmental factors remain limited. In this study, multisource remote sensing data were integrated with interpretable machine learning to quantify and analyze the regional influence of erosion control measures. We constructed a comprehensive indicator system encompassing spectral, textural, and topographic variables derived from high-resolution satellite imagery and DEM data. To address model transparency and enhance the interpretability of the results, we employed an interpretable machine learning framework capable of both accurate prediction and explicit attribution of feature importance. The results indicate that the implementation of engineering measures substantially reduces erosion intensity across the study area. Spatial heterogeneity in erosion mitigation effectiveness was closely associated with the distribution patterns of engineering measures and site-specific environmental conditions. Basins with a high proportion of check dams showed average elevation gains of up to 2.5 m compared with those without check dams, and terraces contributed to elevation increases of ~1.9 m in typical loess hilly regions. The interpretable machine learning model achieved R² = 0.62 at Basin 1 (average area ~100 km²) and R² = 0.73 at Basin 2 (~600 km²), demonstrating reliable predictive capability. The findings not only validate the role of engineering interventions in erosion mitigation but also provide a transparent analytical framework that connects remote sensing analytics with process-based geomorphological understanding. Full article

This study presents a methodology for extracting precise insights on sediment transport in the minor bed of a watercourse using MIKE 21 hydrodynamic modelling software. By integrating geotechnical, geomorphological, and hydrological datasets with a good-resolution Digital Terrain Model (DTM), sediment quantities along a 4.9 km stretch of the Șolea stream—spanning from its source to its confluence with the Vâlsan River (Argeș hydrographic basin)—were determined. A three-month simulation using MIKE 21’s “Mud Transport Module” enabled the comparison of pre- and post-simulation terrain models, yielding detailed information on sediment distribution across the riverbed. These results offer predictive capabilities regarding erosional dynamics and inform mitigation measures to address sedimentary erosion within the study area. The study also presents proposals for land reclamation necessary to prevent the degradation of the riverbed and slopes, such as gabion retaining walls and check dams in the riverbed. Full article

Southern Kazakhstan, particularly the Zhambyl Region, is facing increasing groundwater stress due to climate change, degradation of irrigation infrastructure, and unsustainable water use. Despite substantial renewable groundwater reserves (8.33 km³/year), irrigation still relies on ephemeral surface flow. This study delineates priority zones for Managed Aquifer Recharge (MAR) using a GIS-based Multi-Criteria Decision Analysis framework integrated with the Analytic Hierarchy Process (AHP). Nine hydrogeological criteria were incorporated: shallow aquifer depth, groundwater salinity, precipitation, terrain slope, soil texture, land use/land cover, Normalized Difference Vegetation Index (NDVI), drainage density, and lineament density. Each parameter was normalized to a five-class suitability scale and weighted through expert-informed pairwise comparisons. The MAR suitability map identifies about 19% of the region (27,060 km²) as highly favorable for implementation. Field investigations at eleven groundwater sites in 2024 corroborate model results, providing aquifer depth, quality, and infiltration data. The most suitable areas are concentrated on Quaternary alluvial–proluvial fans near the Kyrgyz Alatau foothills and the Talas-Assa interfluve. Three hydrostratigraphic settings were identified: unconfined alluvial aquifers, Neogene–Quaternary unconsolidated sediments, and fractured Carboniferous carbonates. Recommended MAR methods include infiltration galleries, check dams, and injection wells. The proposed approach, validated through consistency analysis (Consistency Ratio ≤ 0.1), demonstrates the applicability of integrated geospatial and field methods for site-specific MAR planning. Strategic MAR deployment could restore productivity to 37,500 ha of degraded irrigated lands and improve groundwater resilience. These findings provide a practical framework for policymakers and water management authorities to optimize groundwater use and enhance agricultural sustainability under changing climatic conditions. Full article

This study examines research trends and identifies key gaps relevant to the field of structural safety and resilience; additionally, a systematic literature review (SLR) guided by the PRISMA methodology was conducted, analyzing 4188 documents ranging from 1975 to 2025. The research revealed key trends, including a focus on various aspects of the structural stability and resilience of buildings affected by earthquakes through analysis of various innovative methods and materials. The present study encompasses work describing the use of steel–wood composite columns to improve building stability, assessment of the impact of wood accumulation on bridges during floods, and the effect of debris flow on the stability of check dams. In addition, this study also evaluates the seismic performance of school buildings in Mexico, a method of diagnosing cracks in concrete dams, and the application of recycled materials from old tires for seismic disaster mitigation. Acoustic emission monitoring methods in medieval towers and the design of seismic isolation systems with variable damping are also discussed. Bibliometric analysis highlighted increased collaboration and a thematic shift towards green and data-driven approaches. However, significant gaps were identified. The findings explain that the use of innovative materials and methods can improve the stability and resistance of building structures with respect to dynamic loads, such as those associated with earthquakes and floods. The findings provide guidance for the design and maintenance of safer and more sustainable infrastructure in the future. Full article

The long-term safety and operational reliability of zoned earth dams depend on the structural integrity of their internal components, including core, filters, and shell zones. This is particularly relevant for old dams which have been operational for a long period of time. Such existing infrastructure systems are exposed to various loading types over time, including environmental, seepage-related, extreme event, and climate change effects. As a result, even when they look intact externally, changes might affect their internal structure, composition, and possibly functionality. Thus, it is important to delineate a comprehensive and cost-effective strategy to identify potential issues and derive the health status of existing earth dams. This paper outlines a systematic approach for conducting a comprehensive health check of these structures through the implementation of a multi-epoch geotechnical approach based on a variety of standard measured and monitored quantities. The goal is to compare current properties with baseline data obtained during pre-, during-, and post-construction site investigation and laboratory tests. Guidance is provided on how to judge such multi-epoch comparisons, identifying potential outcomes and scenarios. The proposed approach is tested on a well-documented case study in Southern Italy, an area prone to climate change and subjected to very high seismic hazard. The case study demonstrates how the integration of historical and contemporary geotechnical data allows for the identification of critical zones requiring attention, the validation of numerical models, and the proactive formulation of targeted maintenance and rehabilitation strategies. This comprehensive, multi-epoch-based approach provides a robust and reliable assessment of dams’ health, enabling better-informed decision-making workflows and processes for asset management and risk mitigation strategies. Full article

Glacial-lake outburst floods (GLOFs) threaten more than three million residents of south-east Kazakhstan, yet quantitative data on lake growth and storage are scarce. We inventoried 154 lakes on the northern flank of the Ile-Alatau and selected four moraine-dammed basins with the greatest historical flood activity for detailed study. Annual lake outlines (2016–2023) were extracted from 3 m PlanetScope imagery with a Normalised Difference Water Index workflow, while late-ablation echo-sounder surveys (2023–2024) yielded sub-metre bathymetric grids. A regionally calibrated area–volume power law translated each shoreline to water storage, and field volumes served as an independent accuracy check. The lakes display divergent trajectories. Rapid thermokarst development led to a 37% increase in the surface area of Lake 13bis, expanding from 0.039 km² to 0.054 km² over a 5-year period. In contrast, engineering-induced drawdown resulted in a 44% reduction in the area of Lake 6, from 0.019 km² to 0.011 km². Lakes 5 and 2, which are supplied by actively retreating glaciers, exhibited surface area increases of 4.8% and 15%, expanding from 0.077 km² to 0.088 km² and from 0.061 km² to 0.070 km², respectively. The empirical model reproduces field volumes to within ±25% for four lakes, confirming its utility for rapid hazard screening, but overestimates storage in low-relief basins and underestimates artificially drained lakes. This is the first study in Ile-Alatau to fuse daily 3 m multispectral imagery with ground-truth bathymetry, delivering an 8-year, volume-resolved record of lake evolution. The results identify Lake 5 and Lake 2 as priority targets for early-warning systems and demonstrate that sustained intervention can effectively suppress GLOF risk. Incorporating these storage trajectories into regional disaster plans will sharpen evacuation mapping, optimise resource allocation, and inform transboundary water-hazard policy under accelerating climate change. Full article

China’s Loess Plateau is characterized by dense and widely distributed check dams. However, there has been a lack of large-scale and high-temporal-resolution monitoring for the water-filled status of check dams, which is strongly related to their safe operation. In this study, a deep learning-based remote sensing image interpretation technique was developed, which enables long-term, large-scale, and high-frequency monitoring of the water-filled status of check dams. Using object detection algorithms based on deep learning and YOLOv3, an object-detection model was constructed and optimized. Leveraging high spatial resolution optical remote sensing images, the water-filled status of check dams can be identified. The model prediction indicates that the average precision for the check dam and water-filled check dam detection models reached 90.27% and 91.89%, respectively. Case studies were conducted on the check dams in the Jiuyuangou and Xiwuselang small watersheds. The monitoring result based on remote sensing images in the year 2021 shows a good agreement with the actual number of check dams. The proposed monitoring method for the water-filled status of check dams was proven feasible. This provides a reliable and efficient technical approach for monitoring the water-filled status of check dams, which is promising for their daily management and safe operation. 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