Quantitative Landslide Hazard Research Articles

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.

Analysis of Infiltration-Suction Response in Unsaturated Residual Soil Slope in Gelugor, Penang

Rainfall infiltration on residual soil slope may impair slope stability by altering the pore-water pressure in the soil. A study has been carried out on unsaturated residual soil slope in Gelugor, Penang to determine the changes in matric suction of residual soils at different depth due to rainwater infiltration. The sequence of this study includes the site investigation, field instrumentation, laboratory experiment and numerical modeling. Void ratio and porosity of soil were found to be decreasing with depth while the bulk density and dry density of soil increased due to lower porosity of soil at greater depth. Soil infiltration rate and matric suction of all depths decrease with the increase of volumetric water content as well as the degree of saturation. Numerical modeling was used to verify and predict the relationship between infiltration-suction response and degree of saturation. Numerical models can be used to integrate the rainfall scenarios into quantitative landslide hazard assessments. Thus, development plans and mitigation measures can be designed for estimated impacts from hazard assessments based on collected data.

Evaluation of Remote-Sensing-Based Landslide Inventories for Hazard Assessment in Southern Kyrgyzstan

Large areas in southern Kyrgyzstan are subjected to high and ongoing landslide activity; however, an objective and systematic assessment of landslide susceptibility at a regional level has not yet been conducted. In this paper, we investigate the contribution that remote sensing can provide to facilitate a quantitative landslide hazard assessment at a regional scale under the condition of data scarcity. We performed a landslide susceptibility and hazard assessment based on a multi-temporal landslide inventory that was derived from a 30-year time series of satellite remote sensing data using an automated identification approach. To evaluate the effect of the resulting inventory on the landslide susceptibility assessment, we calculated an alternative susceptibility model using a historical inventory that was derived by an expert through combining visual interpretation of remote sensing data with already existing knowledge on landslide activity in this region. For both susceptibility models, the same predisposing factors were used: geology, stream power index, absolute height, aspect and slope. A comparison of the two models revealed that using the multi-temporal landslide inventory covering the 30-year period results in model coefficients and susceptibility values that more strongly reflect the properties of the most recent landslide activity. Overall, both susceptibility maps present the highest susceptibility values for similar regions and are characterized by acceptable to high predictive performances. We conclude that the results of the automated landslide detection provide a suitable landslide inventory for a reliable large-area landslide susceptibility assessment. We also used the temporal information of the automatically detected multi-temporal landslide inventory to assess the temporal component of landslide hazard in the form of exceedance probability. The results show the great potential of satellite remote sensing for deriving detailed and systematic spatio-temporal information on landslide occurrences, which can significantly improve landslide susceptibility and hazard assessment at a regional scale, particularly in data-scarce regions such as Kyrgyzstan.

A subaqueous hazard map for earthquake-triggered landslides in Lake Zurich, Switzerland

The awareness of geohazards in the subaqueous environment has steadily increased in the past years and there is an increased need to assess these hazards in a quantitative sense. Prime examples are subaqueous landslides, which can be triggered by a number of processes including earthquakes or human activities, and which may impact offshore and onshore infrastructure and communities. In the literature, a plenitude of subaqueous landslide events are related to historical earthquakes, including cases from lakes in Switzerland. Here, we present an approach for a basin-wide earthquake-triggered subaquatic landslide hazard assessment for Lake Zurich, which is surrounded by a densely populated shoreline. Our analysis is based on high-resolution sediment-mechanical and geophysical input data. Slope stabilities are calculated with a grid-based limit equilibrium model on an infinite slope, which uses Monte Carlo sampled input data from a sediment-mechanical stratigraphy of the lateral slopes. Combined with probabilistic ground-shaking forecasts from a recent national seismic hazard analysis, subaquatic earthquake-triggered landslide hazard maps are constructed for different mean return periods, ranging from 475 to 9975 years. Our results provide a first quantitative landslide hazard estimation for the lateral slopes in Lake Zurich. Furthermore, a back-analysis of a case-study site indicates that pseudostatic accelerations in the range between 0.04 and 0.08 g were needed to trigger a well-investigated subaqueous landslide, dated to ~2210 cal. years B.P.

Evaluation of coseismic landslide hazard on the proposed Haast-Hollyford Highway, South Island, New Zealand

ABSTRACTCoseismic landsliding presents a major hazard to infrastructure in mountains during large earthquakes. This is particularly true for road networks, as historically coseismic landsliding has resulted in road losses larger than those due to ground shaking. Assessing the exposure of current and planned highway links to coseismic landsliding for future earthquake scenarios is therefore vital for disaster risk reduction. This study presents a method to evaluate the exposure of critical infrastructure to landsliding from scenario earthquakes from an underlying quantitative landslide hazard assessment. The method is applied to a proposed new highway link in South Island, New Zealand, for a scenario Alpine Fault earthquake and compared to the current network. Exposure (the likelihood of a network being affected by one or more landslides) is evaluated from a regional-scale coseismic landslide hazard model and assessed on a relative basis from 0 to 1. The results show that the proposed Haast-Hollyford Highway (HHH) would be highly exposed to coseismic landsliding with at least 30–40 km likely to be badly affected (the Simonin Pass route being the worse affected of the two routes). In the current South Island State Highway network, the HHH would be the link most exposed to landsliding and would increase the total network exposure by 50–70% despite increasing the total road length by just 3%. The present work is intended to provide an effective method to assess coseismic landslide hazard of infrastructure in mountains with seismic hazard, and potentially identify mitigation options and critical network segments.

The contribution of EMCA to landslide susceptibility mapping in Central Asia

<p>Central Asia is one of the most exposed regions in the world to landslide hazard. The large variability of local geological materials, together with the difficulties in forecasting heavy precipitation locally and in quantifying the level of ground shaking, call for harmonized procedures to better quantify the hazard and the negative impact of slope failures across the Central Asian countries. As a first step towards a quantitative landslide hazard and risk assessment, a landslide susceptibility analysis at regional scale has been carried out, by benefitting of novel seismic hazard outcomes reached in the frame of Earthquake Model Central Asia (EMCA) project. By combining information coming from diverse potential factors, it is possible to detect areas where a potential for landslides exists. Initial results allow the identification of areas that are more susceptible to landslides with a level of accuracy greater than 70%. The presented method is, therefore, capable of supporting land planning activities at the regional scale in places where only scarce data are available.</p>

Preface "Progress in landslide hazard and risk evaluation"

Federal Institute for Geosciences and Natural Resources, Hanover, GermanyCorrespondence to: P. Reichenbach (paola.reichenbach@irpi.cnr.it)The special issue of Natural Hazards and Earth SystemSciences entitled “Progress in landslide hazard and risk eval-uation” contains 9 out of more than 30 oral and poster con-tributions originally presented in the “NH3.11 Landslide haz-ard and risk assessment, and landslide management” sessionheld at the General Assembly of the European GeosciencesUnion, in Vienna (Austria), on 22–27 April 2012.The session was aimed at comparing qualitative or quanti-tative landslide hazard and risk estimates in different physio-graphic and geographical settings for different kinds of pro-cesses affecting the environment at different spatial scales.Presentations focusing on the adoption and integration ofdifferent modeling approaches for quantitative assessmentswere welcomed, and papers providing information on thequality, reliability and limitations of process-oriented or sta-tistical models were encouraged.The meeting proved to be a valuable opportunity to discussand compare methods, techniques and tools for the recog-nition, evaluation and mitigation of landslide hazards andthe related risks. In particular, the quality, the reliability andthe limitation of models, input variables and output mapshave been discussed for presented case studies at differentgeographical scales and in different physiographic environ-ments. This is important information for filling the gap be-tween academic research and application of the results inenvironmental planning and management. The special issuecontains the following selected papers presented and dis-cussed at the session.Voumard et al. (2013) have calculated risk along roadsusing a dynamic traffic approach that simulates the durationof the presence of vehicles inside hazardous areas during agiven time interval. The risk is analyzed along three roadsections threatened by different natural hazards (active land-slide, debris flows and dolines) along a mountain road: Aigle– Col du Pillon (western Switzerland). Two different scenar-ios were simulated: (1) a road without obstacles and (2) aroad regulated by traffic lights. Results of the dynamic riskassessment were compared with the static methodology thatconsiders an average number of vehicles per time unit and aconstant vehicle speed. The main advantage of the dynamicapproach is a better representation of the real traffic regardingthe interaction between different vehicles of different types(cars, trucks, coaches). The dynamic approach with a micro-scopic traffic simulator was well designed to analyze the riskon relatively short road sections (up to a few kilometers) indetail. At the regional scale, the risk estimations would beaveraged over the entire network (with large parts at no risk),and differences between static and dynamic risks may not beso pronounced. Thus, the interest of this method is to analyzehotspots, i.e., strongly hazardous short road sections, and tosee for example how the location of traffic lights can increaseor reduce the risk.Catani et al. (2013) have performed different tests to un-derstand how model tuning and model parameters can af-fect landslide susceptibility mapping. In the paper, the au-thors have adopted the random forest (RF) technique to pro-duce an ensemble of landslide susceptibility maps for a setof different models, input data types and observation scales.The RF model was initially applied using the complete set ofinput variables, then an iterative process was implemented,and progressively smaller subsets of the parameter spacewere considered to estimate the relative importance of sin-gle input parameters and to select the optimal configurationof the classification model. The main results are that (i) theoptimal number of parameters varies with scale and resolu-tion, (ii) the importance of each conditioning variable is in-fluenced by the model settings and the available data, andPublished by Copernicus Publications on behalf of the European Geosciences Union.

Use of quantitative landslide hazard and risk information for local disaster risk reduction along a transportation corridor: a case study from Nilgiri district, India

The objective of analyzing hazard and risk in an area is to utilize the result in selecting appropriate landslide risk reduction strategies. However, this does not happen always, and most often results of the hazard and risk analysis remain at an academic level. The under or non-utilization of results in pre-disaster planning could be due to several reasons, including difficulties in understanding the scientific content/meaning of the models, and lack of information on the practical significance and utility of the models. In this study, an attempt is made to highlight the uses of hazard and risk information in different landslide risk reduction strategies along a transportation corridor in Nilgiri, India. At first, a quantitative analysis of landslide hazard and risk was made. The obtained information was then incorporated in risk reduction options such as land use zoning, engineering solutions, and emergency preparedness. For emergency preparedness, the perception of the local Nilgiri communities toward landslide risk was evaluated and simplified maps were generated for the benefit and understanding of end users. A rainfall threshold-based early warning system was presented, which could be used in risk awareness programs involving public participation. The use of quantitative risk information in the cost-benefit analysis for the planning of structural measures to protect the road and railway alignments was also highlighted, and examples were shown how the transport organizations could implement these measures. Finally, the study provided examples of the utility of hazard and risk information for spatial planning and zoning, indicating areas where the landslide hazard is too high for planning future developments.

Object-Oriented Change Detection for Landslide Rapid Mapping

A complete multitemporal landslide inventory, ideally updated after each major event, is essential for quantitative landslide hazard assessment. However, traditional mapping methods, which rely on manual interpretation of aerial photographs and intensive field surveys, are time consuming and not efficient for generating such event-based inventories. In this letter, a semi-automatic approach based on object-oriented change detection for landslide rapid mapping and using very high resolution optical images is introduced. The usefulness of this methodology is demonstrated on the Messina landslide event in southern Italy that occurred on October 1, 2009. The algorithm was first developed in a training area of Altolia and subsequently tested without modifications in an independent area of Itala. Correctly detected were 198 newly triggered landslides, with user accuracies of 81.8% for the number of landslides and 75.9% for the extent of landslides. The principal novelties of this letter are as follows: 1) a fully automatic problem-specified multiscale optimization for image segmentation and 2) a multitemporal analysis at object level with several systemized spectral and textural measurements.

Quantitative assessment of landslide hazard along transportation lines using historical records

In this paper, a quantitative landslide hazard model is presented for transportation lines, with an example for a road and railroad alignment, in parts of Nilgiri hills in southern India. The data required for the hazard assessment were obtained from historical records available for a 21-year period from 1987 to 2007. A total of 901 landslides from cut slopes along the railroad and road alignment were included in the inventory. The landslides were grouped into three magnitude classes based on the landslide type, volume, scar depth, and run-out distance. To calculate landslide hazard, we estimated the total number of individual landslides per kilometer of the (rail) road for different return periods, based on the relationship between past landslides (recorded in our database) and triggering events. These were multiplied by the probability that the landslides belong to a given magnitude class. This gives the hazard for a given return period expressed as the number of landslides of a given magnitude class per kilometer of (rail) road. The relationship between the total number of landslides and the return period was established using a Gumbel distribution model, and the probability of landslide magnitude was obtained from frequency–volume statistics. The results of the analysis indicate that the total number of landslides, from 1- to 50-year return period, varies from 56 to 197 along the railroad and from 14 to 82 along the road. In total, 18 hazard scenarios were generated using the three magnitude classes and six return periods (1, 3, 5, 15, 25, and 50 years). The hazard scenarios derived from the model form the basis for future direct and indirect landslide risk analysis along the transportation lines. The model was validated with landslides that occurred in the year 2009.

Quantitative landslide hazard assessment along a transportation corridor in southern India

A quantitative model for landslide hazard assessment on natural slopes is presented for a transportation corridor of the Nilgiri Hills in southern India. The data required for the hazard assessment were mostly obtained from historical records. For the hazard modeling, a landslide inventory map was prepared from technical reports and maintenance records for a road and a railroad, available for a 21 year period from 1987 to 2007. Most landslides are shallow translational debris slides and debris flow slides triggered by rainfall. On natural slopes landslides occurred as first-time failures. A logistic regression model was used to determine the spatial probability of landslides for each pixel by taking the source area of the existing landslides as dependent, and slope angle, aspect, regolith thickness and land use as independent variables. The temporal probability of landslides was estimated indirectly using the exceedance probability of the rainfall threshold required to trigger landslides for the first time on natural slopes. The probability of landslide size was estimated as frequency percentage of landslide volume, a proxy for landslide magnitude, and the percentage values were then expressed as probability. By assuming independence among the three probabilities, a quantitative estimate of a landslide hazard was obtained as the joint probability of landslide volume, of landslide occurrence in an established time period and of spatial probability of a landslide initiation. The models were validated using the rainfall and landslide events that occurred during 2008 and 2009. Total 12 specific landslide hazard maps were generated considering six time periods (1, 3, 5, 15, 25 and 50 years), and two landslide volumes (volume exceeding 1000 m 3 and 10,000 m 3).

Area-scale landslide hazard and risk assessment

The paper deals with a methodology for quantitative landslide hazard and risk assessments over wide-scale areas. The approach was designed to fulfil the following requirements: (1) rapid investigation of large study areas; (2) use of elementary information, in order to satisfy the first requirement and to ensure validation, repetition and real time updating of the assessments every time new data are available; (3) computation of the landslide frequency of occurrence, in order to compare objectively different hazard conditions and to minimize references to qualitative hazard attributes such as activity states. The idea of multi-temporal analysis set forth by Cardinali et al. (Nat Hazards Earth Syst Sci 2:57–72, 2002), has been stressed here to compute average recurrence time for individual landslides and to forecast their behaviour within reference time periods. The method is based on the observation of the landslide activity through aerial-photo surveys carried out in several time steps. The output is given by a landslide hazard map showing the mean return period of landslides reactivation. Assessing the hazard in a quantitative way allows for estimating quantitatively the risk as well; thus, the probability of the exposed elements (such as people and real estates) to suffer damages due to the occurrence of landslides can be calculated. The methodology here presented is illustrated with reference to a sample area in Central Italy (Umbria region), for which both the landslide hazard and risk for the human life are analysed and computed. Results show the powerful quantitative approach for assessing the exposure of human activities to the landslide threat for a best choice of the countermeasures needed to mitigate the risk.

Quantitative Landslide Hazard and Risk Assessment:a case study

This paper is concerned with landslide hazard and risk assessment along a railway line south of Sydney in the State of New South Wales, Australia. Attention is focused on a quantitative assessment at a specific site where landslide movements have been triggered by significant rainfall. Although small in magnitude such movements are sufficient to cause train derailment and hence human casualty. Utilizing all available data, the relationship of slope instability to rainfall is first established. Slope stability analyses are carried out to validate the proposed geological-geotechnical model. The concept of landslide triggering critical rainfall magnitude (specific to a given site) is proposed in this paper. Detailed rainfall analysis reported elsewhere ( Ko Ko 2001 ) leads to the conclusion that the most significant period of antecedent cumulative rainfall for this site is 15 days. The historical rainfall data then leads to an estimation of landslide frequency or hazard. The risk to human casualty is then based on an analysis of train operations and their frequency. Different results are obtained for the tourist train service and the freight train service. Some attention is given to tolerable risk criteria proposed elsewhere in the literature.

GIS-based quantitative landslide hazard prediction modelling in natural hillslope, Agra Khola watershed, central Nepal

The influence of geological and geomorphological variables were spatially integrated to develop landslide hazard prediction model in the Agra Khola watershed of central Nepal where a large number of landslides triggered off due to extreme weather event of July 19-21, 1993. A quantitative technique of multivariate analysis was performed to predict elements or observations of landslides successfully into different hazard levels in the area. The predicted landslide hazard was validated and spatially relevancy of the prediction is established. The GIS-based prediction model possessed objectivity and reproducibility, and also improved the landslide hazard mapping in the natural hillslope. doi: 10.3126/bdg.v10i0.1421 Bulletin of the Department of Geology, Tribhuvan University, Kathmandu, Nepal, Vol. 10, 2007, pp. 63-70