Landslide Mitigation Research Articles

LEVEL OF LANDSLIDE SUSCEPTIBILITY IN CIBAL DISTRICT OF MANGGARAI EAST NUSA TENGGARA

This research aims to determine the degree of susceptibility of landslides in Cibal Districts. The method used in this research is descriptive survey method. The population in this research is all of the land in Cibal Districts. data collection technique is done by using observation technique and documentation study. Data analysis technique in this research uses crosstab technique. The results of this study can be seen that the level of susceptibility of landslides in Cibal based on crosstab results, there are three categories of vulnerability of landslide , they are low, medium and high. Low landslide susceptibility rate of 6.979,65 hectares or 64.09% is found in Nine sub-districts / village. The moderate landslide susceptibility rate has an area of 3,634.67 hectares or 33.38%, in seven villages. While the high landslide susceptibility rate is found only in one village with an area of 275.65 hectares or 2.35% of the total area of Cibal districts.
 Keywords: Susceptibility, Landslide, Cibal District
 
 References
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Spatial and temporal analysis of a fatal landslide inventory in China from 1950 to 2016

Landslides result in severe casualties every year in China. However, there are few historical fatal landslide catalogs available to quantitatively assess the impact as well as the temporal and spatial patterns of landslides. The Fatal Landslide Event Inventory of China (FLEIC), which spans from 1950 to 2016, was compiled based on multiple data sources. The inventory contains 1911 non-seismically triggered landslides, which resulted in a total of 28,139 deaths in China during 1950–2016. The occurrence frequency of fatal landslides presented significantly different trends for different grades of events. Very large fatal landslide events (fatalities > = 30) were on the rise during 1950–1999 and declined from 2000 to 2016. The decreasing trend after 2000 can be attributed to the increase in landslide mitigation investments. The small and medium-sized fatal landslide events (fatalities < 10) showed a significant increasing trend between 1950 and 2016, especially during the period of 2000–2016. This significant increasing trend is partly due to the improvement of the availability of landslide data online and may also be related to other factors including an increase in extreme precipitation events, the effects of land urbanization, and so on. This suggested that the inherent incompleteness of the landslide time series should be considered when analyzing. The fatal landslides mainly occurred between April and September (82.15%), which is consistent with the monthly precipitation variation in China. Spatially, most of the fatal landslides occurred in 14 provinces: five southwestern provinces (Yunnan, Sichuan, Guangxi, Guizhou, and Chongqing), five southeastern provinces (Hunan, Guangdong, Fujian, Jiangxi, and Zhejiang), Shaanxi and Shanxi, Hubei and Gansu. These 14 provinces account for 86% of the total fatal landslides and their associated fatalities. The spatial association between the fatal landslide density and possible influencing factors was assessed based on a geographical detector method. The results showed that the interacting factors between the precipitation and topography, soil, lithology, vegetation and population density are more closely related to the spatial distribution of fatal landslides than each individual factor.

Utilizing crowdsourcing to enhance the mitigation and management of landslides

Landslides are mainly triggered by earthquakes and rainfall and have poor temporal predictability. Landslides pose significant threats to settlements and infrastructure in mountainous regions around the world. To mitigate this natural hazard, a new paradigm of landslide mitigation and management is required. Increasing smartphone ownership around the world, especially in developing countries, offers scientists an opportunity to embrace crowdsourcing so as to improve landslide research. This paper presents a new landslide information system (LIS) comprising a smartphone app and an administrative interface and database. The mobile app has been published for both iPhone and Android platforms. The interface of the smartphone app is powered by the highly-customizable Google Maps platform, which is overlaid with real-time landslide data. Users can choose between visualizing “known sites” and “contribution” of landslide data. The visualization option shows published landslides and areas that are susceptible. Users can contribute their GPS coordinates and multimedia to enhance landslide reports. A comparison with similar systems, potential applications, and challenges of using smartphone technology for mitigating landslides are also discussed.

Experimental study of groundwater level variation in soil slope using air-injection method

The rising of groundwater level induced by intense rainfall has significant influence on the slope stability. A new drainage method for landslide mitigation, namely the air-injection method, is proposed in this paper to control the quick rising of the groundwater under heavy rainfall to reduce the risk of landslides in a situation of emergency. A large-scale slope model is established in the laboratory to study the influence of the air-injection method on the groundwater level variations. The test results indicate that air injection divides the slope into three zones and forms a low permeability unsaturated zone to prevent the upstream groundwater flowing to the downstream slope. Two phases are identified during the air injection, (a) a formation phase of the unsaturated zone and (b) a steady-state phase of the unsaturated zone, and the unsaturated zone continues to intercept the upstream groundwater flow within a certain period of time after air injection is ceased. Furthermore, increasing the injection pressure appropriately can enhance the effectiveness of the air-injection method in intercepting groundwater.

Geo‐hydro‐mechanics for quantitative landslide hazard assessment (QHA)

AbstractLandslide risk represents a strong limitation to the social and economic development of civil society in chain areas. This is particularly the case in highly urbanized regions. The need for mitigation of landslide risk prompts landslide hazard mapping. The aim of the research work presented in the paper is the use of geo‐hydro‐mechanics for the assessment of landslide hazard from the site to the small scale. The geo‐hydro‐mechanical analysis of landslide hazard is first presented to diagnose single slope. To this aim, the procedure for the deterministic analyses of the internal/external slope factors and of the possible landslide processes bringing about instability is presented. The contribution offers an overview of the key steps of the deterministic procedure with the phenomenological interpretation of a landslide mechanism as first, and the numerical validation thereafter. A representative case study of application of the methodology is discussed. The case study is representative for chain slopes in the Italian Apennines and exemplifies the geo‐hydro‐mechanical diagnosis of landslide hazard in complex geological contexts. As second, a methodology for intermediate to regional scale landslide hazard assessment, based on geo‐mechanical interpretations, is also recalled. The methodology is the Multiscalar Method for Landslide Mitigation, MMLM (Cotecchia et al. 2016b; Cafaro et al. 2016). It uses the hydro‐mechanical diagnoses of landsliding at the slope scale as reference starting point. In this contribution, a brief example of the validation of the MMLM to the geologically complex Daunia‐Lucanian Apennines (Italy) is also shown.

LARAM School 2018: the doctoral school on “LAndslide Risk Assessment and Mitigation”

The international school for PhD students and young doctors on “LAndslide Risk Assessment and Mitigation” (LARAM) is presented and, specifically, information is provided about the next edition of the doctoral school that will held in Italy, at the University of Salerno, on September 3–14, 2018. The LARAM School is managed by the Geotechnical Engineering Group (GEG) of the University of Salerno, which recently became an Associate member of the International Consortium on Landslides (ICL). The 2018 edition of the LARAM School is organised as an ICL/IPL activity.

Landslide inventory and susceptibility modelling using geospatial tools, in Hunza-Nagar valley, northern Pakistan

A comprehensive landslide inventory and susceptibility maps are prerequisite for developing and implementing landslide mitigation strategies. Landslide susceptibility maps for the landslides prone regions in northern Pakistan are rarely available. The Hunza-Nagar valley in northern Pakistan is known for its frequent and devastating landslides. In this paper, we have developed a landslide inventory map for Hunza-Nagar valley by using the visual interpretation of the SPOT-5 satellite imagery and mapped a total of 172 landslides. The landslide inventory was subsequently divided into modelling and validation data sets. For the development of landslide susceptibility map seven discrete landslide causative factors were correlated with the landslide inventory map using weight of evidence and frequency ratio statistical models. Four different models of conditional independence were used for the selection of landslide causative factors. The produced landslides susceptibility maps were validated by the success rate and area under curves criteria. The prediction power of the models was also validated with the prediction rate curve. The validation results shows that the success rate curves of the weight of evidence and the frequency models are 82% and 79%, respectively. The prediction accuracy results obtained from this study are 84% for weight of evidence model and 80% for the frequency ratio model. Finally, the landslide susceptibility index maps were classified into five different varying susceptibility zones. The validation and prediction result indicates that the weight of evidence and frequency ratio model are reliable to produce an accurate landslide susceptibility map, which may be helpful for landslides management strategies.

Landslide susceptibility map using certainty factor for hazard mitigation in mountainous areas of Ujung-loe watershed in South Sulawesi

This study aims to build a landslide susceptibility map (LSM) by using certainty factor (CF) models for mitigation of landslide hazards and mitigation for people who live near to the forest. In the study area, the mountainous area of the Ujung-loe watersheds of South Sulawesi, Indonesia, information on landslides were derived from aerial photography using time series data images from Google Earth Pro© from 2012 to 2016 and field surveys. The LSM was built by using a CF model with eleven causative factors. The results indicated that the causative factor with the highest impact on the probability of landslide occurrence is the class of change from dense vegetation to sparse vegetation (4-1), with CF value 0.95. The CF method proved to be an excellent method for producing a landslide susceptibility map for mitigation with an area under curve (AUC) success rate of 0.831, and AUC predictive rate 0.830 and 85.28% of landslides validation fell into the high to very high class. In conclusion, correlations between landslide occurrence with causative factors shows an overall highest LUC causative factor related to the class of change from dense vegetation to sparse vegetation, resulting in the highest probability of landslide occurrence. Thus, forest areas uses at these locations should prioritize maintaining dense vegetation and involving the community in protection measures to reduce the occurrence of landslide risk. LSM models that apply certainty factors can serve as guidelines for mitigation of people living in this area to pay attention to landslide hazards with high and very high landslide vulnerability and to be careful to avoid productive activities at those locations.

Slope Safety Factor and Its Relationship with Angle of Slope Gradient to Support Landslide Mitigation at Jatinangor Education Area, Sumedang, West Java, Indonesia

In several studies on slope stability analysis, the FS (Factor of Safety) value plays an important role in determining the meaning of slope stability. Based on several landslide events, Table of Bowles (1989) gives FS < 1.07 for the usual occurrence of slope collapse, 1.07 <FS <1.25 for slope collapse ever occurred, and FS> 1.25 for collapse events are rare. FS is influenced by the angle of the slope (\\alpha, degree), then Table of Bowles (1989) can be modified based on analysis of relationship between FS value with slope angle. The result of stability analysis of soil slope in Jatinangor Education Area is found the equation α = 7.2300.FS−0.474, at outside of drainange area, but in drainage area shows a variety of different safety factors. So that the meaning of labile, critical, and stable in slope stability analysis at out of drainage area gives α > 56° for the usual occurrence of slope collapse (or labile slope); 56° > α > 41° for slope collapse ever occurred (or critical slope), and α < 41° for collapse events are rare (or relative stable slope). Furthermore, this modification can be used for landslide mitigation.

GIS-based landslide susceptibility evaluation using fuzzy-AHP multi-criteria decision-making techniques in the Abha Watershed, Saudi Arabia

Landslides are natural geological disasters causing massive destructions and loss of lives, as well as severe damage to natural resources, so it is essential to delineate the area that probably will be affected by landslides. Landslide susceptibility mapping (LSM) is making increasing implications for GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. It is considered to be an effective tool to understand natural disasters related to mass movements and carry out an appropriate risk assessment. This study is based on an integrated approach of GIS and statistical modelling including fuzzy analytical hierarchy process (FAHP), weighted linear combination and MCE models. In the modelling process, eleven causative factors include slope aspect, slope, rainfall, geology, geomorphology, distance from lineament, distance from drainage networks, distance from the road, land use/land cover, soil erodibility and vegetation proportion were identified for landslide susceptibility mapping. These factors were identified based on the (1) literature review, (2) the expert knowledge, (3) field observation, (4) geophysical investigation, and (5) multivariate techniques. Initially, analytical hierarchy process linked with the fuzzy set theory is used in pairwise comparisons of LSM criteria for ranking purposes. Thereafter, fuzzy membership functions were carried out to determine the criteria weights used in the development of a landslide susceptibility map. These selected thematic maps were integrated using a weighted linear combination method to create the final landslide susceptibility map. Finally, a validation of the results was carried out using a sensitivity analysis based on receiver operator curves and an overlay method using the landslide inventory map. The study results show that the weighted overlay analysis method using the FAHP and eigenvector method is a reliable technique to map landslide susceptibility areas. The landslide susceptibility areas were classified into five categories, viz. very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The very high and high susceptibility zones account for 15.11% area coverage. The results are useful to get an impression of the sustainability of the watershed in terms of landsliding and therefore may help decision makers in future planning and mitigation of landslide impacts.

Rheological properties of clayey soils originating from flow-like landslides

Flow-like landslides in clayey soils represent serious threats for populations and infrastructures and have been the subject of numerous studies in the past decade. However, despite the rising need for landslide mitigation with growing urbanization, the transient mechanisms involved in the solid-fluid transition are still poorly understood. One way of characterizing the solid-fluid transition is to carry out rheometrical tests on clayey soil samples to assess the evolution of viscosity with the shear stress. In this study, we carried out geotechnical and rheometrical tests on clayey samples collected from six flow-like landslides in order to assess if these clayey soils exhibit similar characteristics when they fluidize (solid-fluid transition). The results show that (1) all tested soils except one exhibit a yield-stress fluid behavior that can be associated with a bifurcation in viscosity (described by the critical shear rate $$ \dot{\gamma_c} $$ ) and in shear modulus G; (2) the larger the amplitude of the viscosity bifurcation, the larger the associated drop in G; and (3) the water content (w) deviation from the Atterberg liquid limit (LL) seem a key parameter controlling a common mechanical behavior of these soils at the solid-fluid transition. We propose exponential laws describing the evolution of the critical shear stress τc, the critical shear rate $$ \dot{\gamma_c} $$ , and the shear modulus G as a function of the deviation w-LL.

Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds

Abstract. Uncertainty in rainfall datasets and landslide inventories is known to have negative impacts on the assessment of landslide-triggering thresholds. In this paper, we perform a quantitative analysis of the impacts of uncertain knowledge of landslide initiation instants on the assessment of rainfall intensity–duration landslide early warning thresholds. The analysis is based on a synthetic database of rainfall and landslide information, generated by coupling a stochastic rainfall generator and a physically based hydrological and slope stability model, and is therefore error-free in terms of knowledge of triggering instants. This dataset is then perturbed according to hypothetical reporting scenarios that allow simulation of possible errors in landslide-triggering instants as retrieved from historical archives. The impact of these errors is analysed jointly using different criteria to single out rainfall events from a continuous series and two typical temporal aggregations of rainfall (hourly and daily). The analysis shows that the impacts of the above uncertainty sources can be significant, especially when errors exceed 1 day or the actual instants follow the erroneous ones. Errors generally lead to underestimated thresholds, i.e. lower than those that would be obtained from an error-free dataset. Potentially, the amount of the underestimation can be enough to induce an excessive number of false positives, hence limiting possible landslide mitigation benefits. Moreover, the uncertain knowledge of triggering rainfall limits the possibility to set up links between thresholds and physio-geographical factors.

Load-computational methods of anti-slide piles

Anti-slide piles composed of reinforced concrete are commonly used in landslide mitigation engineering. How to calculate the load acting on the piles plays a crucial role in their design process. To estimate the load exerted on anti-slide piles based on the partial safety factor numerical method and limit equilibrium method, the landslide body is subdivided into two independent parts according to the positions of piles: the lower part of the landslide body and the upper one of the landslide body. The corresponding loads acting on the anti-slide piles are respectively computed, and the shear strength of the upper section of the landslide body can be determined according to the given designed safety factors. The locations of the piles are set as the fixed boundary, and the horizontal stress exerted on the anti-slide piles from the upper one of the landslide body is taken as the landslide thrust. The thrust forces are then applied to the lower portion of the landslide body, and the maximum force that the lower of the landslide body can effectively resist, and that satisfies well the given designed safety factors is taken as the maximum resistance of the lower portion of the landslide body. Comparing the results of the numerical computational method, the strict slice method and transfer coefficient method, it is found that the computational results agree well with each other. However, the numerical computational method is employed here in this research because the load distribution can be directly derived, which favors the subsequent calculation process and shortens the computational time.

Mapping of Slope Failure Potential of Galiat area Pakistan using Fuzzy Logic Concept

The landslides in northern Pakistan are mainly occurring on Karakoram Highway, Swat, Kaghan, Neelum, and Jhelum valleys, Murree and Galiat areas. Galiat region forms the southern part of outer or sub-Himalayas. For such larger study areas having inherent geotechnical variability and inhomogeneity, coupled with high costs of investigations, the exclusive use of either deterministic or probabilistic approach has never remained valid. This study resulted in the development of the Slope Failure Potential (SFP) maps and provision of recommendations for the mitigation of landslides in Murree and Galiat area. The objectives were achieved through extensive field and laboratory investigations program, numerical and statistical modeling, and generation of fuzzy logic based computer models. In this study, we used both deterministic geotechnical and geophysical field and laboratory investigations to augment the probabilistic landslide hazard assessment using Fuzzy logic concept. The resulting SFP maps demarcated the study routes into different SFP (i.e., very high, high, medium, low, very low) zones under static loading conditions. These maps were intended to be used for the assessment of the landslide hazard and risk analysis for the existing infrastructure and the design of future construction and land use. The validity of the SFP maps was established through the follow-up of the type, nature and the damage associated with the several intensity level landslides occurred at different locations in the study area during the last ten years.

A Design Method For Landslide Surface Water Drainage Control

Abstract Infiltration of surface water increases pore water pressures in slopes and reduces their stability. Common landslide features such as tension cracks and sag ponds can act as preferential pathways for surface drainage and may increase infiltration and exacerbate pore pressure–induced instability. Surface water drainage control is likewise recommended by numerous authors as an effective and inexpensive landslide mitigation method and has been shown to reduce the risk of landslides. While robust design procedures for other geotechnical applications exist (e.g., slope reduction, subsurface drains), similar procedures for landslide surface water drainage control have remained largely ad hoc and vary among practitioners. The objective of this article is to summarize technical literature related to surface water drainage control and provide a coherent design procedure for landslides.

A method for assessing and managing landslide residual hazard in urban areas

On February 14, 2010, a large landslide affected the urban centre of San Fratello town (Sicily Island, Southern Italy), causing severe damage to buildings, roadways, and infrastructure, as well as about 2000 evacuees. This large complex landslide, covering more than 1 km2 in extension, represents one of the major phenomena that ever occurred in Sicily. In order to manage the landslide risk, the civil protection system was activated as part of the initial response to the emergency (the “emergency phase”). This involved the Civil Protection Departments both at national (DPC) and regional (DRPC) levels, as well as scientific institutions (namely “Competence centres”, CdCs), local administration personnel, and technicians. On March 8, 2010, during the post-event recovery phase, a ground-based synthetic aperture radar (GB-InSAR) system was installed in order to monitor the ground surface deformation, assess the landslide residual risk, and analyse its displacement trend. Accurate field surveys and building inspections were also performed for a validation of the GB-InSAR data, in order to map the ground deformation, plan building evacuation-demolishment, as well as check the efficiency of the landslide mitigation works. This paper describes the outcomes of the 57 month monitoring campaign (March 2010–December 2014), reporting the use of GB-InSAR data for near real-time monitoring, mapping, and post-emergency/recovery management activities. The final aim was to provide the civil protection personnel with a reliable, rapid, and easy communication system of the monitoring results, designed to an enhance understanding of the landslide phenomena, and to support the decision-making process.

Effectiveness of resistivity cone penetration tests in salt-treated highly sensitive clay

Salt wells filled with potassium chloride may be used as landslide mitigation in highly sensitive quick clays, as the changed pore-water composition permanently improves the remoulded shear strength. To verify improvements, resistivity cone penetration tests were conducted around salt wells installed at Dragvoll, Trondheim, Norway. The cone-test measurements for electric resistivity (or conductivity), tip resistance and pore pressure were combined with the results from laboratory tests on piston-core samples extracted around the wells. Salt content, soil and pore-water conductivity, pore-water composition and geotechnical properties were studied. Quick clay is defined as that having a remoulded shear strength of &lt;0·5 kPa, and the soil conductivity is often &lt;100 mS/m. Increased tip resistance was detected at soil conductivities exceeding 200 mS/m as a result of increased salt content, corresponding to a laboratory-determined remoulded shear strength of 3·5 kPa. At Dragvoll, improved non-quick clay is detected by a normalised tip resistance of 3·5 and a pore-pressure parameter of 0·9. Improved geotechnical properties around salt wells may be verified by cone testing, but a site-specific interpretation model based on geotechnical properties from laboratory tests correlated to cone-test results may be needed.

クロアチアの土砂・洪水災害軽減のための共同研究(1)

クロアチアの土砂・洪水災害軽減のための共同研究(1)

A Study of Landslide Areas Mitigation and Adaptation in Palupuah Subdistrict, Agam Regency, West Sumatra Province, Indonesia

The purpose of this research was to determine the alternative policies of landslide area mitigation and adaptation in Palupuah Subdistrict, Agam Regency, West Sumatra Province, Indonesia. This research was descriptive research using mixed method. The data collection used purposive sampling by adapting the sample to criteria. The samples were Palupuah Subdistrict government agencies (the Department of Social, the Head of Palupuah Subdistrict, National Disaster Management Agency), the experts, and the society leaders of Palupuah Subdistrict. The results and discussion of the alternative policies of landslide area mitigation in Palupuah Subdistrict, Agam Regency, West Sumatra Province, Indonesia are: (1) conducting the settlements management in areas with landslides risk of the greatest weight rated (0,795), (2) strengthening the slope vegetatively (0.792), (3) strengthening the slope mechanically (0.769), and (4) developing land allotment landslides based (0.750). The alternative policies of landslide area adaptation in Palupuah Subdistrict, Agam Regency, West Sumatra Province, Indonesia are: (1) avoiding building houses in the steep slopes area, (2) performing the agricultural pattern landslide mitigation based, (3) creating the sewerage in the ​​water cycle area, and (4) making the rules based on the local wisdoms that respond to the landslide.

Plant-Best: A novel plant selection tool for slope protection

Plant-Best is a novel tool for the selection of the most suitable plant cover against rainfall-induced shallow landslides. It explores the plant-derived likelihood of slope failure reduction under wetting and drying events, respectively. Plant-Best comprises five comprehensive open-source modules built in the freeware R. The modules’ objectives range from the spatial detection of landslide-prone zones to the integrated evaluation of plant-derived hydro-mechanical effects on sloped terrain; from the selection of the best performing plant species to the identification of sensitive plant traits. In this paper, we provide a detailed description of the Plant-Best modules and we show how this holistic tool can be effectively employed for plant cover selection in a shallow landslide context. To do so, we demonstrate the application of Plant-Best on a site with a history of slope failures in Northeast Scotland, where the tool is implemented using seven native plant species including both woody and herbaceous vegetation. The results reveal that different plant species were suitable for protection depending on the hydrological conditions – i.e. wetting or drying. Plant effects were limited to the topmost soil and, in general, underweight plants with dense root systems and broad thick canopies offered the best resistance to failure. This suggested that botanically diverse slopes with different plant functional groups are desirable for a more effective slope protection. Plant-Best proved to be a relatively simple but robust tool for the detection of landslide-prone zones, the selection and evaluation of plant covers, and the identification of relevant plant traits related to shallow landslides mitigation. The open-source nature of the tool confers a great versatility and applicability to the tool which can be deployed as a multi-disciplinary aid to the decision making process.