Risk assessment of landslides and debris flows during the construction and exploitation of the Volovets wind farm in the Western part of the Polonina Borzhava (Zakarpattia region, Ukraine)

Author(s):  
M. Yaremovych
2021 ◽  
Author(s):  
Shin-Ping Lee ◽  
Yuan-Jung Tsai ◽  
Yun-Chung Tsang ◽  
Ching-Ya Tsai ◽  
Shang-Ming Wang ◽  
...  

<p>Under climate change impact, the frequency of extreme hydrological events increases. The occurrence of extreme rainfall events may lead to large-scale flooding or sediment disasters resulting in serious property damage and casualties. Large-scale sediment disasters include large-scale landslides and debris flows which are the main types of disasters causing casualties. In Taiwan, during Typhoon Morakot in 2009, the long duration and high-intensity rainfall led to a large-scale sediment disaster resulting in heavy casualties. A disaster with certain magnitude and complexity cannot be coped with a single disaster management approach. In this study, a risk assessment method considering climate change impacts proposed by the Intergovernmental Panel on Climate Change (IPCC) was adopted. By analyzing hazard, exposure, and vulnerability indicators of large-scale sediment disasters in Xinfa catchment of Kaohsiung City, Taiwan, a disaster risk adaptation strategy was proposed based on the impact of disaster factors.</p><p>Two scenarios were applied for the catchment sediment hazards risk assessments including 50-year recurrence period (high frequency and low impact) and extreme scenario (low frequency and high impact). Multiple factors for hazard (impact area of landslides and debris flows), exposure (lifeline roads and land use intensity), and vulnerability (disaster prevention and relief resources and settlement population characteristics) assessments were considered. The correlation factor selection and weighting analysis was calibrated by the 2009 Typhoon Morakot event. All disaster-recorded locations were above moderate risk indicating that the risk assessment method was reasonable. A risk map for Xinfa catchment was completed based on the validated risk assessment model to identify the high-risk settlements. After analyzing the spatial characteristics and disaster risk impact factors of high-risk settlements, both software and hardware disaster prevention measures and adaptation strategies were suggested. According to the analyzed results, although the hardware measures were effective in reducing sediment hazards generally, under extreme hydrologic events, those measures could be ineffective due to limited protection capacity of the engineering facilities. Hence, reducing exposure and vulnerability is essential to deal with the impact of extreme events.</p><p><strong>Keywords</strong>: <strong>Large-scale sediment disasters, Risk assessment, Adaptation strategies</strong></p>


2013 ◽  
Vol 33 (4) ◽  
pp. 1 ◽  
Author(s):  
Xingmin MENG ◽  
Guan CHEN ◽  
Peng GUO ◽  
Muqi XIONG ◽  
Wasowski Janusz

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Haruka Tsunetaka ◽  
Slim Mtibaa ◽  
Shiho Asano ◽  
Takashi Okamoto ◽  
Ushio Kurokawa

AbstractAs wood pieces supplied by landslides and debris flows are one of the main components of ecological and geomorphic systems, the importance of quantifying the dimensions of the wood pieces is evident. However, the low accessibility of disturbed channels after debris flows generally impedes accurate and quick wood-piece investigations. Thus, remote-sensing measurements for wood pieces are necessitated. Focusing on sub-watersheds in coniferous and broadleaf forests in Japan (the CF and BF sites, respectively), we measured the lengths of wood pieces supplied by landslides (> 0.2 m length and > 0.03 m diameter) from orthophotos acquired using a small unmanned aerial vehicle (UAV). The measurement accuracy was analyzed by comparing the lengths derived from the UAV method with direct measurements. The landslides at the CF and BF sites were triggered by extremely heavy rainfalls in 2017 and 2018, respectively. UAV flights were operated during February and September 2019 at the CF site and during November 2018 and December 2019 at the BF site. Direct measurements of wood pieces were carried out on the date of the respective second flight date in each site. When both ends of a wood piece are satisfactorily extracted from an orthophoto acquired by the UAV, the wood-piece lengths at the CF site can be measured with an accuracy of approximately ±0.5 m. At the BF site, most of the extracted lengths were shorter than the directly measured lengths, probably because the complex structures of the root wad and tree crown reduced the visibility. Most wood pieces were discharged from landslide scars at the BF site, but at the CF site, approximately 750 wood pieces remained in the landslide scars approximately 19 months after the landslide occurrence. The number of wood pieces in the landslide scars of the CF site increased with increasing landslide area, suggesting that some wood pieces can be left even if large landslides occur. The lengths and locations of the entrapped wood pieces at both sites were not significantly changed between the two UAV flight dates. However, during this period, the rainfall intensities around the CF site measured by the closest rain-gauge of the Japan Meteorological Agency reached their second highest values from 1976 to 2019, which exceeded the 30-year return period. This suggests that most of the entrapped wood pieces rarely migrated even under intense rainfall.


2021 ◽  
Vol 10 (5) ◽  
pp. 315
Author(s):  
Hilal Ahmad ◽  
Chen Ningsheng ◽  
Mahfuzur Rahman ◽  
Md Monirul Islam ◽  
Hamid Reza Pourghasemi ◽  
...  

The China–Pakistan Economic Corridor (CPEC) project passes through the Karakoram Highway in northern Pakistan, which is one of the most hazardous regions of the world. The most common hazards in this region are landslides and debris flows, which result in loss of life and severe infrastructure damage every year. This study assessed geohazards (landslides and debris flows) and developed susceptibility maps by considering four standalone machine-learning and statistical approaches, namely, Logistic Regression (LR), Shannon Entropy (SE), Weights-of-Evidence (WoE), and Frequency Ratio (FR) models. To this end, geohazard inventories were prepared using remote sensing techniques with field observations and historical hazard datasets. The spatial relationship of thirteen conditioning factors, namely, slope (degree), distance to faults, geology, elevation, distance to rivers, slope aspect, distance to road, annual mean rainfall, normalized difference vegetation index, profile curvature, stream power index, topographic wetness index, and land cover, with hazard distribution was analyzed. The results showed that faults, slope angles, elevation, lithology, land cover, and mean annual rainfall play a key role in controlling the spatial distribution of geohazards in the study area. The final susceptibility maps were validated against ground truth points and by plotting Area Under the Receiver Operating Characteristic (AUROC) curves. According to the AUROC curves, the success rates of the LR, WoE, FR, and SE models were 85.30%, 76.00, 74.60%, and 71.40%, and their prediction rates were 83.10%, 75.00%, 73.50%, and 70.10%, respectively; these values show higher performance of LR over the other three models. Furthermore, 11.19%, 9.24%, 10.18%, 39.14%, and 30.25% of the areas corresponded to classes of very-high, high, moderate, low, and very-low susceptibility, respectively. The developed geohazard susceptibility map can be used by relevant government officials for the smooth implementation of the CPEC project at the regional scale.


2013 ◽  
Vol 13 (3) ◽  
pp. 795-808 ◽  
Author(s):  
N. Sh. Chen ◽  
G. Sh. Hu ◽  
W. Deng ◽  
N. Khanal ◽  
Y. H. Zhu ◽  
...  

Abstract. The Kosi River is an important tributary of the Ganges River, which passes through China, Nepal and India. With a basin area of 71 500 km2, the Kosi River has the largest elevation drop in the world (from 8848 m of Mt Everest to 60 m of the Ganges Plain) and covers a broad spectrum of climate, soil, vegetation and socioeconomic zones. The basin suffers from multiple water related hazards including glacial lake outburst, debris flow, landslides, flooding, drought, soil erosion and sedimentation. This paper describes the characteristics of water hazards in the basin, based on the literature review and site investigation covering hydrology, meteorology, geology, geomorphology and socio-economics. Glacial lake outbursts are a huge threat to the local population in the region and they usually further trigger landslides and debris flows. Floods are usually a result of interaction between man-made hydraulic structures and the natural environment. Debris flows are widespread and occur in clusters. Droughts tend to last over long periods and affect vast areas. Rapid population increase, the decline of ecosystems and climate change could further exacerbate various hazards in the region. The paper has proposed a set of mitigating strategies and measures. It is an arduous challenge to implement them in practice. More investigations are needed to fill in the knowledge gaps.


2018 ◽  
Vol 175 ◽  
pp. 04025
Author(s):  
Pengyu Chen ◽  
Ying Kong

Luanchuan County, located in the mountains of Western Henan Province, is characterized by poor geological environment and abundant material sources and rainfalls. Debris flows have occurred many times in this county, and in some gully debris flows exhibit a large scale, requiring risk assessment. In the multi-factor comprehensive assessment methods for debris flow risk, it is really important to determine the weight of each factor since this affects the reliability of the assessment results. Given that the subjective weighting method can accurately reflect the importance of each factor, in order to improve the reliability of subjective weighting, the group decision making method is used to determine the weight of each factor. Group decision making is realized using the analytic hierarchy process and the data fusion algorithm. In this method, the expert combination weight is determined; on this basis, a model for comprehensive assessment of debris flow risk is established by the linear weighted sum method, and risk assessment is performed for gullies with medium to large-scale debris flows in the study area. The assessment results show that all debris flow gullies face minor to moderate risks. For gullies with high risk degree, it is suggested to timely clear material sources in channels and construct or reinforce retaining dams in order to prevent re-occurrence of debris flows.


Author(s):  
K. J. Beven ◽  
S. Almeida ◽  
W. P. Aspinall ◽  
P. D. Bates ◽  
S. Blazkova ◽  
...  

Abstract. This paper discusses how epistemic uncertainties are considered in a number of different natural hazard areas including floods, landslides and debris flows, dam safety, droughts, earthquakes, tsunamis, volcanic ash clouds and pyroclastic flows, and wind storms. In each case it is common practice to treat most uncertainties in the form of aleatory probability distributions but this may lead to an underestimation of the resulting uncertainties in assessing the hazard, consequences and risk. It is suggested that such analyses might be usefully extended by looking at different scenarios of assumptions about sources of epistemic uncertainty, with a view to reducing the element of surprise in future hazard occurrences. Since every analysis is necessarily conditional on the assumptions made about the nature of sources of epistemic uncertainty it is also important to follow the guidelines for good practice suggested in the companion Part 1 by setting out those assumptions in a condition tree.


Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 325
Author(s):  
Emad Mohamed ◽  
Parinaz Jafari ◽  
Simaan AbouRizk

Currently, input modeling for Monte Carlo simulation (MSC) is performed either by fitting a probability distribution to historical data or using expert elicitation methods when historical data are limited. These approaches, however, are not suitable for wind farm construction, where—although lacking in historical data—large amounts of subjective knowledge describing the impacts of risk factors are available. Existing approaches are also limited by their inability to consider a risk factor’s impact on cost and schedule as dependent. This paper is proposing a methodology to enhance input modeling in Monte Carlo risk assessment of wind farm projects based on fuzzy set theory and multivariate modeling. In the proposed method, subjective expert knowledge is quantified using fuzzy logic and is used to determine the parameters of a marginal generalized Beta distribution. Then, the correlation between the cost and schedule impact is determined and fit jointly into a bivariate distribution using copulas. To evaluate the feasibility of the proposed methodology and to demonstrate its main features, the method was applied to an illustrative case study, and sensitivity analysis and face validation were used to evaluate the method. The results demonstrated that the proposed approach provides a reliable method for enhancing input modeling in Monte Carlo simulation (MCS).


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