scholarly journals Stem deformation and bend resistivity of leaned deciduous broad-leaved trees on steep slopes in heavy snow region.

1995 ◽  
Vol 57 (2) ◽  
pp. 155-162
Author(s):  
Chiko BOJO ◽  
Toshiaki NAGATA ◽  
Yoshinori KOYAMA ◽  
Hiroshi MATSUDA ◽  
Kaoru TOGASHI ◽  
...  
2016 ◽  
Vol 12 (4) ◽  
Author(s):  
Ari Sandyavitri

This paper objectives are to; (i) identification of risky slopes (within 4 Provinces in Sumatra including Provinces of Riau, West Sumatra, Jambi and South Sumatra encompassing 840 kms of the “Jalan Lintas Sumatra” highway) based on Rockfall Hazard Rating Systems (RHRS) method; (ii) developing alternatives to stabilize slope hazards, and (iii) selecting appropriate slopes stabilization techniques based on both proactive approach and value engineering one. Based on the Rockfall Hazard Rating Systems (RHRS) method, it was identified 109 steep slopes prone to failure within this highway section. Approximately, 15 slopes were identified as potential high-risk slopes (RHRS scores were calculated >200 points). Based on the proactive approach, seven riskiest slopes ware identified. The preferred stabilization alternatives to remedy most of these slopes are suggested as follow; either (i) a combination of retaining wall and drainage, or (ii) gabion structure and drainage. However, different approaches may yield different results, there are at least 2 main consideration in prioritizing slope stabilization; (i) based on the riskiest slopes, and(ii) the least expensive stabilization alternatives.


2018 ◽  
Vol 10 (4) ◽  
pp. 35-41
Author(s):  
P.N. Proyezdov ◽  
◽  
D.A. Mashtakov ◽  
A.N. Avtonomov ◽  
◽  
...  

2013 ◽  
Vol 13 (2) ◽  
Author(s):  
Heru Sri Naryanto

Karanganyar District is a hilly area with steep slopes, rock constituent of young volcanic deposits of Lawu Volcano products, thick soil and relatively high rainfall, so it is potential for large landslides in this region. The landuse in the Karanganyar District including the Tengklik Village is generally dominated by rice fields, seasonal gardens and settlements. Plantation made up in areas with steep topography has great influence on erosion and landslides. Similarly, many settlements are built on a slope so that the area is very vulnerable to the threat of landslides. In the rainy season landslides are common. The potential hazard of landslidesoccurred in 14 sub districts in Karanganyar District. Large landslides have occurred in Karanganyar on December 26, 2007 which claimed the lives of 62 people, with the greatest victims were in the Ledoksari Village, Tawangmangu. The Tengklik Village has already experienced creep type landslides, which have destroyed settlements, roads, seasonalgardens and all existing infrastructure in the area. In order to do the proper handling and anticipation of a catastrophic landslide, a variety of technological applications landslides using geographic information system (GIS) was then carried out, to detect the configuration of 2D geoelectrical subsurface prone areas for landslide risk study and regional planning.


Author(s):  
Matheus Souisa ◽  
Paulus R. Atihuta ◽  
Josephus R. Kelibulin

Ambon City is a region consisting of hilly areas and steep slopes with diverse river characteristics. Research has been carried out in the Wae Ruhu watershed in Ambon City which starts from upstream (water catchment) to downstream. This study aims to determine the magnitude of river discharge and sediment discharge in the Wae Ruhu watershed. This research was conducted in several stages including, secondary data collection, research location survey, preparation of research tools and materials as well as field data retrieval processes which included tracking coordinates at each station point and entire watershed, calculation of river flow velocity, river geometry measurements, and sampling sediment. The results showed that the average river discharge in the Wae watershed in the year 2018 was 1.24 m3 / s, and the average sediment discharge was 6.27 kg / s. From the results of this study and the field observations proposed for flood prevention and the rate of sediment movement are the construction of cliffs with sheet pile and gabions.


2002 ◽  
pp. 42-62 ◽  
Author(s):  
A. I. Solomeshch ◽  
V. B. Martynenko ◽  
O. Yu. Zhigunov

Xerophillous pine-larch forests of the Southern Ural have been described as a new alliance Caragano fruti­cis—Pinion sylvestris. They occur on steep slopes of upper parts of mountain ridges with poorely developed stony soils. Alliance asigned to the class Brachypodio pinnati—Betuletea pendulae, order Chamaecytiso ruthe­nici—Pinetalia sylvestris. Associations Carici caryophyl­leae—Pinetum sylvestris and Ceraso fruticis—Pinetum sylvestris with four subassociations are described. Eco­logical and floristical peculiarities of new alliance in comparison with another alliances of the order Cha­maecytiso-Pinetalia and with siberian class Rhytidio rugosi—Laricetea sibiricae have been discussed.


Author(s):  
Ivan Pascal ◽  
Christophe Ancey ◽  
Patricio Bohorquez
Keyword(s):  

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 616
Author(s):  
Jie Gao ◽  
Xuguang Tang ◽  
Shiqiu Lin ◽  
Hongyan Bian

The ecosystem services (ESs) provided by mountain regions can bring about benefits to people living in and around the mountains. Ecosystems in mountain areas are fragile and sensitive to anthropogenic disturbance. Understanding the effect of land use change on ESs and their relationships can lead to sustainable land use management in mountain regions with complex topography. Chongqing, as a typical mountain region, was selected as the site of this research. The long-term impacts of land use change on four key ESs (i.e., water yield (WY), soil conservation (SC), carbon storage (CS), and habitat quality (HQ)) and their relationships were assessed from the past to the future (at five-year intervals, 1995–2050). Three future scenarios were constructed to represent the ecological restoration policy and different socioeconomic developments. From 1995 to 2015, WY and SC experienced overall increases. CS and HQ increased slightly at first and then decreased significantly. A scenario analysis suggested that, if the urban area continues to increase at low altitudes, by 2050, CS and HQ are predicted to decrease moderately. However, great improvements in SC, HQ, and CS are expected to be achieved by the middle of the century if the government continues to make efforts towards vegetation restoration on the steep slopes.


Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 14
Author(s):  
Mei Dong ◽  
Hongyu Wu ◽  
Hui Hu ◽  
Rafig Azzam ◽  
Liang Zhang ◽  
...  

With increased urbanization, accidents related to slope instability are frequently encountered in construction sites. The deformation and failure mechanism of a landslide is a complex dynamic process, which seriously threatens people’s lives and property. Currently, prediction and early warning of a landslide can be effectively performed by using Internet of Things (IoT) technology to monitor the landslide deformation in real time and an artificial intelligence algorithm to predict the deformation trend. However, if a slope failure occurs during the construction period, the builders and decision-makers find it challenging to effectively apply IoT technology to monitor the emergency and assist in proposing treatment measures. Moreover, for projects during operation (e.g., a motorway in a mountainous area), no recognized artificial intelligence algorithm exists that can forecast the deformation of steep slopes using the huge data obtained from monitoring devices. In this context, this paper introduces a real-time wireless monitoring system with multiple sensors for retrieving high-frequency overall data that can describe the deformation feature of steep slopes. The system was installed in the Qili connecting line of a motorway in Zhejiang Province, China, to provide a technical support for the design and implementation of safety solutions for the steep slopes. Most of the devices were retained to monitor the slopes even after construction. The machine learning Probabilistic Forecasting with Autoregressive Recurrent Networks (DeepAR) model based on time series and probabilistic forecasting was introduced into the project to predict the slope displacement. The predictive accuracy of the DeepAR model was verified by the mean absolute error, the root mean square error and the goodness of fit. This study demonstrates that the presented monitoring system and the introduced predictive model had good safety control ability during construction and good prediction accuracy during operation. The proposed approach will be helpful to assess the safety of excavated slopes before constructing new infrastructures.


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