Susceptibility and triggering scenarios at a regional scale for shallow landslides

The work aims at identifying susceptible areas and pluviometric triggering scenarios at a regional scale in Calabria (Italy), with reference to shallow landsliding events. The proposed methodology follows a statistical approach and uses a database linked to a GIS that has been created to support the various steps of spatial data management and manipulation. The shallow landslide predisposing factors taken into account are derived from (i) the 40-m digital terrain model of the region, an  15,075 km² extension; (ii) outcropping lithology; (iii) soils; and (iv) land use. More precisely, a map of the slopes has been drawn from the digital terrain model. Two kinds of covers [prevalently coarse-grained (CG cover) or fine-grained (FG cover)] were identified, referring to the geotechnical characteristics of geomaterial covers and to the lithology map; soilscapes were drawn from soil maps; and finally, the land use map was employed without any prior processing.Subsequently, the inventory maps of some shallow landsliding events, totaling more than 30,000 instabilities of the past and detected by field surveys and photo aerial restitution, were employed to calibrate the relative importance of these predisposing factors.The use of single factors (first level analysis) therefore provides three different susceptibility maps. Second level analysis, however, enables better location of areas susceptible to shallow landsliding events by crossing the single susceptibility maps.On the basis of the susceptibility map obtained by the second level analysis, five different classes of susceptibility to shallow landsliding events have been outlined over the regional territory: 8.9% of the regional territory shows very high susceptibility, 14.3% high susceptibility, 15% moderate susceptibility, 3.6% low susceptibility, and finally, about 58% very low susceptibility.Finally, the maps of two significant shallow landsliding events of the past and their related rainfalls have been utilized to identify the relevant pluviometric triggering scenarios. By using 205 daily rainfall series, different triggering pluviometric scenarios have been identified with reference to CG and FG covers: a value of 365 mm of the total rainfall of the event and/or 170 mm/d of the rainfall maximum intensity and a value of 325 mm of the total rainfall of the event and/or 158 mm/d of the rainfall maximum intensity are able to trigger shallow landsliding events for CG and FG covers, respectively.The results obtained from this study can help administrative authorities to plan future development activities and mitigation measures in shallow landslide-prone areas. In addition, the proposed methodology can be useful in managing emergency situations at a regional scale for shallow landsliding events triggered by intense rainfalls; through this approach, the susceptibility and the pluviometric triggering scenario maps will be improved by means of finer calibration of the involved factors.     

Probabilistic landslide risk analysis considering direct costs in the area north of Lisbon (Portugal)

The purpose of the present study is the analysis of landslide risk for roads and buildings in a small test site (20 km²) in the area north of Lisbon (Portugal). For this purpose, an evaluation is performed integrating into a GIS information obtained from multiple sources: (i) landslide hazard; (ii) elements at risk; and (iii) vulnerability. Landslide hazard is assessed on a probabilistic basis for three different types of slope movement (shallow translational slides, translational slides and rotational slides), based on some assumptions such as: (i) the likelihood of future landslide occurrence can be measured through statistical relationships between past landslide distribution and specified spatial data sets considered as landslide predisposing factors; and (ii) the rainfall combination (amount–duration) responsible for past slope instability within the test site will produce the same effects (i.e. same type of landslides and similar total affected area), each time they occur in the future. When the return period of rainfall triggering events is known, different scenarios can be modelled, each one ascribed to a specific return period. Therefore, landslide hazard is quantitatively assessed on a raster basis, and is expressed as the probability for each pixel (25 m²) to be affected by a future landslide, considering a rainfall triggering scenario with a specific return period. Elements at risk within the test site include 2561 buildings and roads amounting to 169 km. Values attributed to elements at risk were defined considering reconstruction costs, following the guidelines of the Portuguese Insurance Institute. Vulnerability is considered as the degree of loss to a given element resulting from the occurrence of a landslide of a given magnitude. Vulnerability depends not only on structural properties of exposed elements, but also on the type of process, and its magnitude; i.e., vulnerability cannot be defined in absolute terms, but only with respect to a specific process (e.g. vulnerability to shallow translational slides). Therefore, vulnerability was classified for the three landslide groups considered on hazard assessment, taking into account: (i) landslide magnitude (mean depth, volume, velocity); (ii) damage levels produced by past landslide events in the study area; and (iii) literature. Finally, a landslide risk analysis considering direct costs was made in an automatic way crossing the following three layers: (i) Probabilistic hazard map for a landslide type Z, considering a particular rainfall triggering scenario whose return period is known; (ii) Vulnerability map (values from 0 to 1) of the exposed elements to landslide type Z; and (iii) Value map of the exposed elements, considering reconstruction costs.     

Spatial patterns of old, deep-seated landslides: A case-study in the northern Ethiopian highlands

During the last decade, slope failures were reported in a 500 km² study area in the Geba–Werei catchment, northern Ethiopia, a region where landslides were not considered an important hazard before. Field observations, however, revealed that many of the failures were actually reactivations of old deep-seated landslides after land use changes. Therefore, this study was conducted (1) to explore the importance of environmental factors controlling landslide occurrence and (2) to estimate future landslide susceptibility. A landslide inventory map of the study area derived from aerial photograph interpretation and field checks shows the location of 57 landslides and six zones with multiple landslides, mainly complex slides and debris flows. In total 14.8% of the area is affected by an old landslide. For the landslide susceptibility modelling, weights of evidence (WofE), was applied and five different models were produced. After comparison of the models and spatial validation using Receiver Operating Characteristic curves and Kappa values, a model combining data on elevation, hillslope gradient, aspect, geology and distance to faults was selected. This model confirmed our hypothesis that deep-seated landslides are located on hillslopes with a moderate slope gradient (i.e. 5°–13°). The depletion areas are expected on and along the border of plateaus where weathered basalts rich in smectite clays are found, and the landslide debris is expected to accumulate on the Amba Aradam sandstone and upper Antalo limestone. As future landslides are believed to occur on inherently unstable hillslopes similar to those where deep-seated landslides occurred, the classified landslide susceptibility map allows delineating zones where human interventions decreasing slope stability might cause slope failures. The results obtained demonstrate that the applied methodology could be used in similar areas where information on the location of landslides is essential for present-day hazard analysis.     

Sedimentary impacts from landslides in the Tachia River Basin, Taiwan

A case study of coseismic landslides and post-seismic sedimentary impacts of landslides due to rainfall events was conducted in the Tachia River basin, Taichung County, central Taiwan. About 3000 coseismic landslides occurred in the basin during the M_L 7.3 Chi-Chi earthquake in 1999. The deposits from these landslides provided material for numerous debris flows induced by subsequent rainfall events. The estimated 4.1 × 10⁷ m³ of landslide debris produced in the upland area caused sediment deposition in riverbeds, and flash floods inundated downstream areas with sediment during torrential rains. The landslide frequency-size distributions for the coseismic landslides and the subsequent rainfall-induced landslides were analyzed to determine the sediment budgets of the post-seismic geomorphic response in the landslide-dominated basin. Both the coseismic and the rainfall-induced landslides show a power–law frequency-size distribution with a rollover. It was found that the rainfall-induced landslide magnitude was smaller than the coseismic one, and that both have comparable negative scaling exponents in cumulative form, of about − 2.0 for larger landslides (> 10^− 2 km²). This may be attributed to ongoing movement or reactivation of old landslides, and a natural stabilisation of small landslides between 10^− 4 and 10^− 2 km². It is proposed that the characteristics of geological formations and rainfall as well as changes in landslide area are reflected in the power–law distribution.     

Morphology and structure of a landslide complex in an active margin setting: The Waitawhiti complex, North Island, New Zealand

Multi-scale gravitational instabilities are widespread in the Coastal Ranges of the North Island of New Zealand. We document here a detailed analysis of the Waitawhiti landslide complex, located in the core of the Tawhero syncline, and investigate the potential landslides triggering factors in the area. Four contiguous large slides form the Waitawhiti complex. These slides involve fine-grained Miocene sandstones and massive fractured siltstones. Sliding occurs mostly along nearly horizontal strata. All slides are bounded laterally and/or distally by deep-incised valleys. Three gas seeps evidencing thermogenic gas release have been discovered in the vicinity of the slides. We propose that river incision, continuously removing distal buttresses, is the main destabilizing factor in the area. However, additional factors, such as tectonic activity and intense rainfall, cannot be excluded. We also propose that fluid overpressure, reducing the effective shear strength at the base of low-permeability layers, may have influenced the triggering of landslides in the Waitawhiti area.     

Landslide scar/soil erodibility mapping using Landsat TM/ETM+ bands 7 and 3 Normalised Difference Index: A case study of central region of Kenya

Landsat series multispectral remote sensing imagery has gained increasing attention in providing solutions to environmental problems such as land degradation which exacerbate soil erosion and landslide disasters in the case of rainfall events. Multispectral data has facilitated the mapping of soils, land-cover and structural geology, all of which are factors affecting landslide occurrence. The main aim of this research was to develop a methodology to visualize and map past landslides as well as identify land degradation effects through soil erosion and land-use using remote sensing techniques in the central region of Kenya. The study area has rugged terrain and rainfall has been the main source of landslide trigger. The methodology comprised visualizing landslide scars using a False Colour Composite (FCC) and mapping soil erodibility using FCC components applying expert based classification. The components of the FCC were: the first independent component (IC1), Principal Component (PC) with most geological information, and a Normalised Difference Index (NDI) involving Landsat TM/ETM+ band 7 and 3.The FCC components formed the inputs for knowledge-based classification with the following 13 classes: runoff, extreme erosions, other erosions, landslide areas, highly erodible, stable, exposed volcanic rocks, agriculture, green forest, new forest regrowth areas, clear, turbid and salty water. Validation of the mapped landslide areas with field GPS locations of landslide affected areas showed that 66% of the points coincided well with landslide areas mapped in the year 2000. The classification maps showed landslide areas on the steep ridge faces, other erosions in agricultural areas, highly erodible zones being already weathered rocks, while runoff were mainly fluvial deposits. Thus, landuse and rainfall processes play a major role in inducing landslides in the study area.     

Representative rainfall thresholds for landslides in the Nepal Himalaya

Measuring some 2400 km in length, the Himalaya accommodate millions of people in northern India and Pakistan, Nepal, Bhutan, and parts of other Asian nations. Every year, especially during monsoon rains, landslides and related natural events in these mountains cause tremendous damage to lives, property, infrastructure, and environment. In the context of the Himalaya, however, the rainfall thresholds for landslide initiation are not well understood. This paper describes regional aspects of rainfall thresholds for landslides in the Himalaya. Some 677 landslides occurring from 1951 to 2006 were studied to analyze rainfall thresholds. Out of the 677 landslides, however, only 193 associated with rainfall data were analyzed to yield a threshold relationship between rainfall intensity, rainfall duration, and landslide initiation. The threshold relationship fitted to the lower boundary of the field defined by landslide-triggering rainfall events is I = 73.90D^− 0.79 (I = rainfall intensity in mm h^− 1 and D = duration in hours), revealing that when the daily precipitation exceeds 144 mm, the risk of landslides on Himalayan mountain slopes is high. Normalized rainfall intensity–duration relationships and landslide initiation thresholds were established from the data after normalizing rainfall-intensity data with respect to mean annual precipitation (MAP) as an index in which N_I = 1.10D^− 0.59 (N_I = normalized intensity in h^− 1). Finally, the role of antecedent rainfall in causing landslides was also investigated by considering daily rainfall during failure and the cumulative rainfall to discover at what point antecedent rainfall plays an important role in Himalayan landslide processes. Rainfall thresholds presented in this paper are generalized so they can be used in landslide warning systems in the Nepal Himalaya.     

Determining landslide susceptibility in Central Taiwan from rainfall and six site factors using the analytical hierarchy process method

This work provides a landslide susceptibility assessment model for rainfall-induced landslides in Central Taiwan based on the analytical hierarchy process method. The model considers rainfall and six site factors, including slope, geology, vegetation, soil moisture, road development and historical landslides. The rainfall factor consists of 10-day antecedent rainfall and total rainfall during a rainfall event. Landslide susceptibility values are calculated for both before and after the beginning of a rainfall event. The 175 landslide cases with detailed field surveys are used to determine a landslide-susceptibility threshold value of 9.0. When a landslide susceptibility assessment value exceeds the threshold value, slope failure is likely to occur. Three zones with different landslide susceptibility levels (below, slightly above, and far above the threshold) are identified. The 9149 landslides caused by Typhoon Toraji in Central Taiwan are utilized to validate the study's result. Approximately, 0.2%, 0.4% and 15.3% of the typhoon-caused landslides are located in the three landslide susceptibility zones, respectively. Three villages with 6.6%, 0.4% and 4.9% of the landslides respectively are used to validate the accuracy of the landslide susceptibility map and analyze the main causes of landslides. The landslide susceptibility assessment model can be used to evaluate susceptibility relative to accumulated rainfall, and is useful as an early warning and landslide monitoring tool.     

The origin of shallow landslides in Moravia (Czech Republic) in the spring of 2006

At the end of March 2006, the Czech Republic (CZ) witnessed a fast thawing of an unusually thick snow cover in conjunction with massive rainfall. Most watercourses suffered floods, and more than 90 shallow landslides occurred in the Moravian region of Eastern CZ, primarily in non-forested areas. This region, geologically part of the Outer Western Carpathians, is prone to landslides because the bedrock is highly erodible Mesozoic and Tertiary flysch.The available meteorological data (depth of snow, water equivalent of the snow, cumulative rainfall, air and soil temperatures) from five local weather stations were used to construct indices quantitatively describing the snow thaw. Among these, the Total Cumulative Precipitation (TCP) combines the amount of water from both thawing snow and rainfall. This concurrence of rain and runoff from snow melt was the decisive factor in triggering the landslides in the spring.The TCP index was applied to data of snow thaw periods for the last 20 years, when no landslides were recorded. This was to establish the safe threshold of TCP without landslides. The calculated safe threshold value for the region is ca. 100 mm of water delivered to the soil during the spring thaw (corresponding to ca. 11 mm day^− 1). In 2006, 10% of the landslides occurred under or at 100 mm of TCP. The upper value of 155 mm covered all of the landslides.     

Susceptibility assessment of shallow landslides on Oahu, Hawaii, under extreme-rainfall events

The deterministic Stability INdex MAPping (SINMAP) model, which integrates a mechanistic infinite-slope stability model and a hydrological model, was applied to assess susceptibility of slopes in 32 shallow-landslide-prone watersheds of the eastern to southern areas of Oahu, Hawaii, USA. Input to the model includes a 10-m Digital Elevation Model (DEM), an inventory of storm-induced landslides that occurred from 1949 to 2006, and listings of soil-strength and hydrological parameters including transmissivity and steady-state recharge. The study area of ca. 384 km² was divided into four calibration regions with different geotechnical and hydrological characteristics. All parameter values were separately calibrated using observed landslides as references. The study used a quasi-dynamic scenario of soil wetness resulting from extreme daily rainfall events with a return period of 50 years. The return period was based on almost-90-year-long (1919–2007) daily rainfall records from 26 raingauge stations in the study area. Output of the SINMAP model includes slope-stability-index-distribution maps, slope-versus-specific-catchment-area charts, and statistical summaries for each region.The SINMAP model assessed susceptibility at the locations of all 226 observed shallow landslides and classified these susceptible areas as unstable. About 55% of the study area was predicted as highly unstable, highlighting a critical island problem. The SINMAP predictions were compared to an existing debris-flow-hazard map. Areas classified as unstable in the current study were classified as low-to-moderate and moderate-to-high debris-flow hazard risks by the prior mapping. The slope-stability maps provided by this study will aid in explaining the causes of known landslides, making emergency decisions, and, ultimately mitigating future landslide risks. The maps may be further improved by incorporating heterogeneous and anisotropic soil properties and spatial and temporal variation of rainfalls as well as by improving the accuracy of the DEM and the locations of shallow landslide initiation.     

Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence

Landslide hazard mapping is a fundamental tool for disaster management activities in mountainous terrains. The main purpose of this study is to evaluate the predictive power of weights-of-evidence modelling in landslide hazard assessment in the Lesser Himalaya of Nepal. The modelling was performed within a geographical information system (GIS), to derive a landslide hazard map of the south-western marginal hills of the Kathmandu Valley. Thematic maps representing various factors (e.g., slope, aspect, relief, flow accumulation, distance to drainage, soil depth, engineering soil type, landuse, geology, distance to road and extreme one-day rainfall) that are related to landslide activity were generated, using field data and GIS techniques, at a scale of 1:10,000. Landslide events of the 1970s, 1980s, and 1990s were used to assess the Bayesian probability of landslides in each cell unit with respect to the causative factors. To assess the accuracy of the resulting landslide hazard map, it was correlated with a map of landslides triggered by the 2002 extreme rainfall events. The accuracy of the map was evaluated by various techniques, including the area under the curve, success rate and prediction rate. The resulting landslide hazard value calculated from the old landslide data showed a prediction accuracy of > 80%. The analysis suggests that geomorphological and human-related factors play significant roles in determining the probability value, while geological factors play only minor roles. Finally, after the rectification of the landslide hazard values of the new landslides using those of the old landslides, a landslide hazard map with > 88% prediction accuracy was prepared. The methodology appears to have extensive applicability to the Lesser Himalaya of Nepal, with the limitation that the model's performance is contingent on the availability of data from past landslides.     

Landslides in a densely populated county at the footslopes of Mount Elgon (Uganda): Characteristics and causal factors

Manjiya County on the Ugandan slopes of Mount Elgon is a densely populated mountainous area where landslides have been reported since the beginning of the twentieth century. The numerous fatalities and the damage done during the extreme rainfall events of 1997 to 1999 drew attention to this phenomenon. In order to better understand the causal factors of these landslides, 98 recent landslides in the study area, mostly debris slumps, were mapped and investigated. Together, they displaced 11 millions m³ of slope material. Statistical analysis shows that landslides dominate on steep concave slope segments that are oriented to the dominant rainfall direction (northeast) and at a relatively large distance from the water divide. Based on landslide occurrence and impact, four different zones can be distinguished within the study area. Causal factors as well as landslide characteristics differ greatly between the four zones.Besides the fact that steep slopes, high rainfall and typical soil properties and stratification turn Manjiya into an inherently unstable area, human interference cannot be neglected. Whereas deforestation has reduced the stability of the shallow soils on the eastern slopes of the study area, the excavation of slopes, mainly for house building, is an important destabilizing factor for the western slopes. The growing population density not only increases the risk on damage, but hampers the search for solutions for the landslide problem as well.     

Relationships between rainfall and landsliding in the Middle Hills,Nepal

Many studies have documented major landslide events in mountain areas following heavy rainfall amounts. In the Himalaya, landslides occur during every monsoon period, but the role of rainfall in triggering these failures is not clear. This paper reports the results of a three-year study (1991-1993) into landsliding in the Likhu Khola drainage basin, Middle Hills, Nepal. Considerable annual variability in numbers, types and sizes of landslides was noted. Some of this variability can be explained by fluctuations in rainfall amounts and intensities, but many landslides were explained more easily by other controlling factors. In situations where slopes are extensively terraced for agriculture, with some terraces being intensely irrigated and others not, relationships between landsliding and rainfall amounts are complex and no simple explanations can be made.     

Modeling typhoon- and earthquake-induced landslides in a mountainous watershed using logistic regression

Landslides can be caused by storms and earthquakes. Most logistic regression models proposed in recent years have been targeted at rainfall-induced landslides. In areas such as Taiwan, where landslides can be triggered by typhoons (tropical cyclones) and earthquakes, a rainfall-induced model is insufficient because it provides only a partial explanation of landslide occurrence and overlooks the potential effect of earthquakes on typhoon-triggered landslides. This study used landslides triggered by a major earthquake and a typhoon prior to the earthquake to develop an earthquake-induced model and a typhoon-induced model. The models were then validated by using landslides triggered by three typhoons after the earthquake. According to the results, typhoon-triggered landslides tended to be near stream channels and earthquake-triggered landslides were more likely to be near ridge lines. Moreover, a major earthquake could still affect the locations of typhoon-triggered landslides 6 years after the earthquake. This study therefore demonstrates that an earthquake-induced model both sheds light on the environmental factors for triggering landslides, and augments a rainfall-induced model in its predictive capability in areas such as Taiwan.     

Comparison of landslide susceptibility based on a decision-tree model and actual landslide occurrence: The Akaishi Mountains, Japan

This paper proposes a statistical decision-tree model to analyze landslide susceptibility in a wide area of the Akaishi Mountains, Japan. The objectives of this study were to validate the decision-tree model by comparing landslide susceptibility and actual landslide occurrence, and to reveal the relationships among landslide occurrence, topography, and geology. Landslide susceptibility was examined through ensemble learning with a decision tree. Decision trees are advantageous in that estimation processes and order of important explanatory variables are explicitly represented by the tree structures. Topographic characteristics (elevation, slope angle, profile curvature, plan curvature, and dissection and undissection height) and geological data were used as the explanatory variables. These topographic characteristics were calculated from digital elevation models (DEMs). The objective variables were landslide occurrence and reactivation data between 1992 and 2002 that were depicted by satellite image analysis. Landslide susceptibility was validated by comparing actual data on landslides that occurred and reactivated after the model was constructed (between 2002 and 2004).This study revealed that, from 2002 to 2004, landslides tended to occur and reactivate in catchments with high landslide susceptibility. The landslide susceptibility map thus depicts the actual landslide occurrence and reactivation in the Akaishi Mountains. This result indicates that the decision-tree model has appropriate accuracy for estimating the probabilities of future landslides. The tree structure indicates that landslides occurred and reactivated frequently in the catchments that had an average slope angle exceeding ca. 29° and a mode of slope angle exceeding 33°, which agree well with previous studies. A decision tree also quantitatively expresses important explanatory variables at the higher order of the tree structure.     

Morphology and internal structure of a dormant landslide in a hilly area: The Collinabos landslide (Belgium)

This study attempts to reconstruct the history of the Collinabos landslide, a landslide with a fresh morphology that is representative for more than 150 dormant, deep-seated (> 3 m) landslides in the Flemish Ardennes (Belgium). A geomorphological map was created based on LIDAR (Light Detection and Ranging)-derived maps and detailed field surveys. The map showed that the landslide consisted of three zones with significant differences in surface topography. The northern landslide zone 1 is characterised by at least five reverse slopes, whereas zones 2 and 3, the southern landslide zones, have only two reverse slopes and a convex foot. Electric resistivity profiles measured in zones 1 and 2 revealed that the differences in surface topography were not related to differences in internal structure as both parts of the landslide were initiated as a rotational earth slide with a surface of rupture at 15 m deep, where the displaced material broke apart in two blocks. However, two shear surfaces of reactivations within landslide debris were only distinguished in the accumulation area of zone 1. The observed differences in surface morphology can be caused by a temporary conversion of a forest into cropland in zone 2. It is suggested that reverse slopes of smaller reactivations within landslide debris were obliterated during the agricultural activities. AMS radiocarbon dating of organic material found in ponds located in reverse slopes generally resulted in relatively recent dates (i.e. 1400–1950 Cal AD) suggesting that several of the small local reactivations occurred in that period. One dating at 8700–8440 Cal BP of organic matter collected in a reverse slope in zone 1 suggests that an initiation under periglacial conditions cannot be excluded for the Collinabos landslide. By combining different technologies, this study provides valuable information for a better understanding of dormant landslides.     

Landslide events on the West Coast, South Island, 1867–2002

Abstract: A new landslide event inventory based on a literature search has been compiled for the West Coast of New Zealand. Rainfall has been identified as the most frequent reported landslide generating mechanism by far, followed by other/unknown means, then earthquakes. Small‐magnitude, high‐frequency, rainfall‐induced events have historically caused the most damage to property and infrastructure, with many of the region's highways and settlements being repeatedly affected by landslides. Since 1874, landslides have caused at least 36 fatalities in the region. More historical research is needed to fill chronological and geographical gaps in the record, and to complement scientific research. Such information is useful for hazard planning purposes.     

Climate change effects on landslides along the southwest coast of British Columbia

Antecedent rainfall and short-term intense rainfall both contribute to the temporal occurrence of landslides in British Columbia. These two quantities can be extracted from the precipitation regimes simulated by climate models. This makes such models an attractive tool for use in the investigation of the effect of global warming on landslide frequencies.In order to provide some measure of the reliability of models used to address the landslide question, the present-day simulation of the antecedent precipitation and short-term rainfall using the daily data from the Canadian Centre for Climate Modelling and Analysis model (CGCM) is compared to observations along the south coast of British Columbia. This evaluation showed that the model was reasonably successful in simulating statistics of the antecedent rainfall but was less successful in simulating the short-term rainfall.The monthly mean precipitation data from an ensemble of 19 of the world's global climate models were available to study potential changes in landslide frequencies with global warming. Most of the models were used to produce simulations with three scenarios with different levels of prescribed greenhouse gas concentrations during the twenty-first century. The changes in the antecedent precipitation were computed from the resulting monthly and seasonal means. In order to deal with models' suspected difficulties in simulating the short-term precipitation and lack of daily data, a statistical procedure was used to relate the short-term precipitation to the monthly means.The qualitative model results agree reasonably well, and when averaged over all models and the three scenarios, the change in the antecedent precipitation is predicted to be about 10% and the change in the short-term precipitation about 6%. Because the antecedent precipitation and the short-term precipitation contribute to the occurrence of landslides, the results of this study support the prediction of increased landslide frequency along the British Columbia south coast during the twenty-first century.     

A hydroclimatic threshold for landslide initiation on the North Shore Mountains of Vancouver, British Columbia

Landslides triggered by rainfall are the cause of thousands of deaths worldwide every year. One possible approach to limit the socioeconomic consequences of such events is the development of climatic thresholds for landslide initiation. In this paper, we propose a method that incorporates antecedent rainfall and streamflow data to develop a landslide initiation threshold for the North Shore Mountains of Vancouver, British Columbia. Hydroclimatic data were gathered for 18 storms that triggered landslides and 18 storms that did not. Discriminant function analysis separated the landslide-triggering storms from those storms that did not trigger landslides and selected the most meaningful variables that allow this separation. Discriminant functions were also developed for the landslide-triggering and nonlandslide-triggering storms. The difference of the discriminant scores, ΔCS, for both groups is a measure of landslide susceptibility during a storm. The variables identified that optimize the separation of the two storm groups are 4-week rainfall prior to a significant storm, 6-h rainfall during a storm, and the number of hours 1 m³/s discharge was exceeded at Mackay Creek during a storm. Three thresholds were identified. The Landslide Warning Threshold (LWT) is reached when ΔCS is −1. The Conditional Landslide Initiation Threshold (CTL_I) is reached when ΔCS is zero, and it implies that landslides are likely if 4 mm/h rainfall intensity is exceeded at which point the Imminent Landslide Initiation Threshold (ITL_I) is reached. The LWT allows time for the issuance of a landslide advisory and to move personnel out of hazardous areas. The methodology proposed in this paper can be transferred to other regions worldwide where type and quality of data are appropriate for this type of analysis.     

LIDAR monitoring of mass wasting processes: The Radicofani landslide, Province of Siena, Central Italy

The Radicofani Basin, stretching about 30 km NW–SE, is an intra-Central Apennine basin connected to Pliocene–Pleistocene extensional tectonics. It consists of an Early to Middle Pliocene succession including essentially shelf pelites. In the Radicofani area, province of Siena (Tuscany region), morphodynamic processes are very frequent with widespread badlands and rapidly evolving mudflows. In order to evaluate the general instability of the Radicofani area, geological and geomorphological surveys were carried out. The 1954, 1990 and 2003 aerial surveys allowed a comparison of the changes in the various morphological aspects of the study area, which suggested an increase in slope instability with time. A new complex translational landslide evolving into mudflows, activated during the winter of 2003, was monitored using an experimental system based on terrestrial LIDAR (Light Detection and Ranging) and GPS (Global Positioning System) technologies. This system allowed the monitoring of the morphologic and volumetric evolution of the landslide. A comparison of the monitoring data of October 2004, June 2005, May 2006 and May 2007 points out that the evolution is characterised by the sliding of displaced materials. A volume of about 1300 m³ of materials was removed during the period 2004–2005, 300 m³ for 2005–2006, and 400 m³ for 2006–2007. The greater initial mass movement probably reflects a greater static imbalance during the early period of landslide movement and increased rainfall. Therefore, the proposed monitoring system methodology allows the numerical evaluation of the landslide morphological evolution and to validate the landslide evolution model based on geological and geomorphological field surveys.