Appraise the structural mitigation of landslide risk via numerical modelling: a case study from the northern Apennines (Italy)

The Ca’ Lita landslide is a large and deep-seated mass movement located in the northern Apennines, about 70 km west of Bologna (Northern Italy). It consists of a composite landslide that affects Cretaceous to Eocene flysch rock masses and chaotic complexes. Many of the sectors making up the landslide have resumed activity between 2002 and 2006, threatening some villages and an important road connecting several key industrial facilities located in the upper watershed. This paper presents the management of the emergency, dealing with the investigation campaigns (geological, geomorphological and LiDAR surveys, borehole drillings, seismic surveys), with the monitoring (in situ instrumentation) and with the design and construction of mitigation measures. The whole process, from landslide reactivation to date, has been modelled on a numerical basis with the finite difference code FLAC 2D, to assess the efficiency of the mitigation system and to propose further countermeasure works in different scenarios.     

Geochemical mapping based on geological units: a case study from the Marnoso-arenacea formation (Northern Apennines,Italy)

Geochemical maps can provide us with much information on geology, earth surface processes and anthropogenic pressure and are valuable tools for ore prospecting and land management. Stream sediments represent an integral of the various possible sources of sediments upstream from the sampling point therefore there can be multiple signal sources but generally the prevailing signal source is the one related to bedrock geology. Stream sediments collected from active second-order channels including singular geological units, were selected in order to determine the geochemical characteristics of each unit. The aim of this study was to analyze their potential for using them to integrate geological interpretation and produce a geologically-oriented geochemical map. From the 770 samples collected for a regional geochemical mapping program, we selected 149 samples whose catchment basin included only one of the members recognized within the Marnoso-arenacea formation. This middle–upper Miocene (Langhian–Tortonian) turbiditic unit forms the backbone of the Romagna Apennines and has been subdivided into 14 members according to age and lithostratigraphic criteria. The results indicate that there are marked differences in the composition of the members of the Marnoso arenecea formation which indicate the provenance of the sediment and the palaeogeographic evolution of the units. By means of univariate and multivariate statistical analyses (Factor analyzes) two main types of sediment compositions are identified: Tortonian members are characterized by sialic coarse grain-sediments while the Langhian–Serravallian members are richer in carbonate fraction, slightly enriched in a mafic contribution. This study elaborated the geochemical data from a geological point of view by integrating the information available in literature to spatially extend the interpretation based on limited site observation as for petrographic studies. In general, the geochemical map based on a geological unit could be a useful tool for carrying out the geological reconstruction of a complex area.     

Geochemical mapping based on geological units: A case study from the Marnoso-arenacea formation (Northern Apennines,Italy)

Geochemical maps can provide us with much information on geology, earth surface processes and anthropogenic pressure and are valuable tools for ore prospecting and land management. Stream sediments represent an integral of the various possible sources of sediments upstream from the sampling point therefore there can be multiple signal sources but generally the prevailing signal source is the one related to bedrock geology. Stream sediments collected from active second-order channels including singular geological units, were selected in order to determine the geochemical characteristics of each unit. The aim of this study was to analyse their potential for using them to integrate geological interpretation and produce a geologically-oriented geochemical map. From the 770 samples collected for a regional geochemical mapping program, we selected 149 samples whose catchment basin included only one of the members recognized within the Marnoso–Arenacea formation. This Middle-Upper Miocene (Langhian–Tortonian) turbiditic unit forms the backbone of the Romagna Apennines and has been subdivided into 14 members according to age and lithostratigraphic criteria. The results indicate that there are marked differences in the composition of the members of the Marnoso Arenecea formation which indicate the provenance of the sediment and the palaeogeographic evolution of the units. By means of univariate and multivariate statistical analyses (Factor analyses) two main types of sediment compositions are identified: Tortonian members are characterized by sialic coarse grain- sediments while the Langhian–Serravallian members are richer in carbonate fraction, slightly enriched in a mafic contribution. This study elaborated the geochemical data from a geological point of view by integrating the information available in literature to spatially extend the interpretation based on limited site observation as for petrographic studies. In general, the geochemical map based on a geological unit could be a useful tool for carrying out the geological reconstruction of a complex area.     

Validation and evaluation of two multivariate statistical models for predictive shallow landslide susceptibility mapping of the Eastern Pyrenees (Spain)

This paper deals with the quality of two multivariate statistical models based on the Geographical Information System for shallow landslide susceptibility assessment in a test area at La Pobla de Lillet (Eastern Pyrenees, Spain). The quality, which was guaranteed by a rigorous methodology based on a suitable diagnosis, validation, and evaluation of the models, ensured a reliable contrast of the final susceptibility maps. This enables us to transfer the best results to the end user. Landslide susceptibility models were carried out by logistic regression and discriminant analysis of the significant conditioning factors related to the characteristics of the slope and the upslope contributing area captured from the digital elevation model and landslide distribution. The explanatory variables were tested (KS test, principal components and one-way and T-test) to select the most statistically significant ones before being introduced into the logistic and discriminant analyses. Accuracy statistics and the receiver operating characteristic curve used for diagnosis and validation showed similar prediction skills and a good fit to the data with more than 85% of unfailed cells properly classified for the two models. The evaluation of the study area and the correlation function (R ² = 0.83) between the models revealed that the discriminant model overestimated the susceptibility of the most stable zones with respect to the logistic model. Different methods of producing susceptibility maps showed marked differences in matching the models. Substantial spatial agreement (Kappa = 0.741) between binary maps produced by the standard cut-off value descended moderately (Kappa = 0.540) as a result of superimposing maps with five susceptibility levels defined by landslide percentage. Despite the fact that the two statistical models are similar in assessing susceptibility in the study area, the implications for hazard and risk management can be different because of the conservative nature of the discriminant model.     

Mapping landslide susceptibility with frequency ratio,statistical index,and weights of evidence models: a case study in northern Iran

The main objective of this study is to investigate potential application of frequency ratio (FR), weights of evidence (WoE), and statistical index (SI) models for landslide susceptibility mapping in a part of Mazandaran Province, Iran. First, a landslide inventory map was constructed from various sources. The landslide inventory map was then randomly divided in a ratio of 70/30 for training and validation of the models, respectively. Second, 13 landslide conditioning factors including slope degree, slope aspect, altitude, plan curvature, stream power index, topographic wetness index, sediment transport index, topographic roughness index, lithology, distance from streams, faults, roads, and land use type were prepared, and the relationships between these factors and the landslide inventory map were extracted by using the mentioned models. Subsequently, the multi-class weighted factors were used to generate landslide susceptibility maps. Finally, the susceptibility maps were verified and compared using several methods including receiver operating characteristic curve with the areas under the curve (AUC), landslide density, and spatially agreed area analyses. The success rate curve showed that the AUC for FR, WoE, and SI models was 81.51, 79.43, and 81.27, respectively. The prediction rate curve demonstrated that the AUC achieved by the three models was 80.44, 77.94, and 79.55, respectively. Although the sensitivity analysis using the FR model revealed that the modeling process was sensitive to input factors, the accuracy results suggest that the three models used in this study can be effective approaches for landslide susceptibility mapping in Mazandaran Province, and the resultant susceptibility maps are trustworthy for hazard mitigation strategies.     

GIS-based landslide susceptibility mapping using bivariate statistical analysis in Devrek (Zonguldak-Turkey)

Devrek town with increasing population is located in a hillslope area where some landslides exist. Therefore, landslide susceptibility map of the area is required. The purpose of this study was to generate a landslide susceptibility map using a bivariate statistical index and evaluate and compare the results of the statistical analysis conducted with three different approaches in seed cell concept resulting in different data sets in Geographical Information Systems (GIS) based landslide susceptibility mapping applied to the Devrek region. The data sets are created from the seed cells of (a) crowns and flanks, (b) only crowns, and (c) only flanks of the landslides by using ten different causative parameters of the study area. To increase the data dependency of the analysis, all parameter maps are classified into equal frequency classes based directly on the percentile divisions of each corresponding seed cell data set. The resultant maps of the landslide susceptibility analysis indicate that all data sets produce fairly acceptable results. In each data set analysis, elevation, lithology, slope, aspect, and drainage density parameters are found to be the most contributing factors in landslide occurrences. The results of the three data sets are compared using Seed Cell Area Indexes (SCAI). This comparison shows that the crown data set produces the most accurate and successful landslide susceptibility map of the study area.     

Improvement of statistical landslide susceptibility mapping by using spatial and global regression methods in the case of More and Romsdal (Norway)

Statistical models are one of the most preferred methods among many landslide susceptibility assessment methods. As landslide occurrences and influencing factors have spatial variations, global models like neural network or logistic regression (LR) ignore spatial dependence or autocorrelation characteristics of data between the observations in susceptibility assessment. However, to assess the probability of landslide within a specified period of time and within a given area, it is important to understand the spatial correlation between landslide occurrences and influencing factors. By including these relations, the predictive ability of the developed model increases. In this respect, spatial regression (SR) and geographically weighted regression (GWR) techniques, which consider spatial variability in the parameters, are proposed in this study for landslide hazard assessment to provide better realistic representations of landslide susceptibility. The proposed model was implemented to a case study area from More and Romsdal region of Norway. Topographic (morphometric) parameters (slope angle, slope aspect, curvature, plan, and profile curvatures), geological parameters (geological formations, tectonic uplift, and lineaments), land cover parameter (vegetation coverage), and triggering factor (precipitation) were considered as landslide influencing factors. These influencing factors together with past rock avalanche inventory in the study region were considered to obtain landslide susceptibility maps by using SR and LR models. The comparisons of susceptibility maps obtained from SR and LR show that SR models have higher predictive performance. In addition, the performances of SR and LR models at the local scale were investigated by finding the differences between GWR and SR and GWR and LR maps. These maps which can be named as comparison maps help to understand how the models estimate the coefficients at local scale. In this way, the regions where SR and LR models over or under estimate the landslide hazard potential were identified.     

Multivariate statistical comparison of Northern Apennines Paleozoic sequences: a case study for the formations of Monti Romani (Southern Tuscany-Northern Latium,Italy)

The Paleozoic quartzites and graphite-rich metapelites cropping out in the area of Monti Romani, in Central Italy, show very common mineralogical and petrographical features and are lacking of fossils. For this reason, their stratigraphic attribution in the general picture of the Tuscan Paleozoic is still debated.In this work 23 rock samples have been analyzed for major and trace (Li, Ni, Cu, Zn, Rb, Sr, Y, Zr, Nb, Ag, Ba, La, Ce and Pb) elements, in order to give a contribution to their stratigraphic interpretation. Using linear discriminant analysis (LDA) on major elements, the paleozoic formations of Monti Romani have been compared with 4 “reference groups”, representing the formations of: (1) Cambro-Ordovician; (2) Middle Ordovician; (3) Late Ordovician-Silurian; (4) Permo-Carboniferous age, cropping out in Tuscany (in total 136 samples).The application of LDA to real geological data is generally limited by (a) the deviation of the data from the normal (Gaussian) distribution model, which is an important basic assumption of LDA, and (b) the closure of compositional data (e.g., major elements sum to 100), which can induce false correlations between elements. With regards to both problems, the log-ratio transformation of the data suggested by Aitchison has resulted in a satisfactory solution for the application of LDA.The results of LDA show that most Paleozoic formations of Monti Romani closely resemble the Tuscan Permo-Carboniferous formations: the samples are in fact attributed to this group with probability ranging from 0.632 to 0.995. Only the data of the “Valle Tegolaie Carbonatic-Phyllitic Complex” give contradictory indications; this unit is in fact believed to be Devonian in age, on the basis of field evidence, and should be eventually compared with the other Silurian-Devonian formations of the Northern Apennines.Correlations between elements have been studied with the Spearman rank correlation coefficient ϱ, which is much less influenced by the non-normal distribution of the data than the Pearson coefficientr. The analysis of the Spearman's matrix allowed some inferences about mineralogy. The high correlation of Fe_tot and Na with K, Al and LOI should account for a phengitic-paragonitic composition of sericite. The same mineral strongly controls the distribution of most trace elements, namely Li, Ni, Rb, Sr, Y, Nb, Ag, Ba, La and Ce (coefficients between 0.600 and 0.877). In contrast, low coefficients for Cu, Pb and, to minor extent Zn, suggest that other minerals such as graphite or sulphides are probably important for the distribution of these elements. In the same way, Zr does not show any significant correlation, as expected, being concentrated mainly in the granoblastic layers (detrital zircon).     

Regional deformation of late Quaternary fluvial sediments in the Apennines foreland basin (Emilia,Italy)

International Journal of Earth Sciences - Our research is aimed at estimating the vertical deformation affecting late Quaternary units accumulated into the foreland basin of the Northern Apennines...     

PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz, Iran

In northern parts of Iran such as the Alborz Mountain belt, frequent landslides occur due to a combination of climate and geologic conditions with high tectonic activities. This results in millions of dollars of financial damages annually excluding casualties and unrecoverable resources. This paper evaluates the landslide susceptible areas in Central Alborz using the probabilistic frequency ratio (PFR) model and Geo-information Technology (GiT). The landslide location map in this study has been generated based on image elements interpreted from IRS satellite data and field observations. The display, manipulation and analysis have been carried out to evaluate layers such as geology, geomorphology, soil, slope, aspect, land use, distance from faults, lineaments, roads and drainages. The validation group of actual landslides and relative operation curve method has been used to increase the accuracy of the final landslide susceptibility map. The area under the curve evaluates how well the method predicts landslides. The results showed a satisfactory agreement of 91% between prepared susceptibility map and existing data on landslide locations.     

The role of rainfall in the landslide hazard: the case of the Avigliano urban area (Southern Apennines, Italy)

Mass movements varying in type and size, some of which are periodically reactivated, affect the urban area of Avigliano. The disturbed and remoulded masses consist of sandy–silty or silty–clayey plastic material interbedded with stone fragments and conglomerate blocks. Five landslides that were markedly liable to rainfall-associated instability phenomena were selected.

The relationships between landslides and rainfall were investigated using a hydrological and statistical model based on long-term series of daily rainfall data. The model was used to determine the return period of cumulative daily rainfall over 1–180 days. The resulting hydrological and statistical findings are discussed with the aim of identifying the rainfall duration most critical to landslides.

The concept of a precipitation threshold was generalized by defining some probability classes of cumulative rainfall. These classes indicate the thresholds beyond which reactivation is likely to occur. The probability classes are defined according to the return period of the cumulative rainfall concomitant with landslide reactivation.     

An approach for GIS-based statistical landslide susceptibility zonation—with a case study in the Himalayas

Landslide susceptibility zonation (LSZ) is necessary for disaster management and planning development activities in mountainous regions. A number of methods, viz. landslide distribution, qualitative, statistical and distribution-free analyses have been used for the LSZ studies and they are again briefly reviewed here. In this work, two methods, the Information Value (InfoVal) and the Landslide Nominal Susceptibility Factor (LNSF) methods that are based on bivariate statistical analysis have been applied for LSZ mapping in a part of the Himalayas. Relevant thematic maps representing various factors (e.g., slope, aspect, relative relief, lithology, buffer zones along thrusts, faults and lineaments, drainage density and landcover) that are related to landslide activity, have been generated using remote sensing and GIS techniques. The LSZ derived from the LNSF method, has been compared with that produced from the InfoVal method and the result shows a more realistic LSZ map from the LNSF method which appears to conform to the heterogeneity of the terrain.     

A new approach to use AHP in landslide susceptibility mapping: a case study at Yenice (Karabuk, NW Turkey)

This study aimed to investigate the parameter effects in preparing landslide susceptibility maps with a data-driven approach and to adapt this approach to analytical hierarchy process (AHP). For this purpose, at the first stage, landslide inventory of an area located in the Western Black Sea region of Turkey covering approximately 567?km² was prepared, and a total of 101 landslides were mapped. In order to assess the landslide susceptibility, a total of 13 parameters were considered as the input parameters: slope, aspect, plan curvature, topographical elevation, vegetation cover index, land use, distance to drainage, distance to roads, distance to structural elements, distance to ridges, stream power index, sediment transport capacity index, and wetness index. AHP was selected as the major assessment methodology since the adapted approach and AHP work in data pairs. Adapted to AHP, a similarity relation?Cbased approach, namely landslide relation indicator (LRI) for parameter selection method, was also proposed. AHP and parametric effect analyses were performed by the proposed approach, and seven landslide susceptibility maps were produced. Among these maps, the best performance was gathered from the landslide susceptibility map produced by 9 parameter combinations using area under curve (AUC) approach. For this map, the AUC value was calculated as 0.797, while the others ranged between 0.686 and 0.771. According to this map, 38.3?% of the study area was classified as having very low, 8.5?% as low, 15.0?% as moderate, 20.3?% as high, and 17.9?% as very high landslide susceptibility, respectively. Based on the overall assessments, the proposed approach in this study was concluded as objective and applicable and yielded reasonable results.     

Evidence of deep-water inflow in a tectonic window of the northern Apennines (Italy)

Water samples from the river network and from some shallow and brackish springs located in a tectonic window of the northern Apennines of Italy were studied in the frame of a comprehensive hydrogeological investigation in order to better understand the origin and the mixing processes between the two water types noticed also in previous studies (Ca–HCO₃ and Na–Cl). A sampling campaign covering the drought period during year 2010 was planned to gather electric conductivity, temperature and redox potential data along the river network and on groundwater occurrences located inside the tectonic structure. Additionally, eight water samples were collected for hydrochemical (major anions and cations: Na⁺, K⁺, Ca²⁺, Mg²⁺, HCO₃ ^?, Cl^?, SO₄ ^2? and trace ion B_tot) and isotopic (δ¹⁸O, δ²H, ³H) analyses and compared with other eighteen samples from shallow and brackish springs collected near the study site during the period 2005–2012. Moreover, river discharge and water balance estimations were carried out. Results confirmed the presence of old Na–Cl water with salinity progressively increasing up to 5.5 g l^?1 at the northern termination of the tectonic window. These values are in agreement with the ions contents of the most mineralized spring (Macognano spring: salinity of 7.6 g l^?1), which has been considered as having the deepest and longest flow-path. Stable isotopes and trace ions contents are consistent with rainfall and snowmelt water mixed with brines associated with a hydrocarbon reservoir hosted at depth. Considering as end-member the more mineralized Na–Cl water, a cumulate inflow in the range of 12.9 ± 5.9 l s^?1 has been estimated. This aliquot is released into the river network with different mixing proportions by the groundwater occurrences discharging from the autochthonous flysch unit.     

Large reactivated landslides in weak rock masses: a case study from the Northern Apennines (Italy)

This case study paper is about a large rotational rock and earth slide—earth flow located in the Secchia River Valley, in the Northern Apennines of Italy, that has displayed multiple reactivation phases between 2002 and 2004. The main geological constraints of the mass movement are related to the overlap of flysch rock masses over clayey complexes that allows rock slides to take place in the source area. The disarrangement and weathering of rock masses following slope movements causes large amount of fine-grained debris to be accumulated on the slope and mobilised by earth sliding and flowing. Analysis of rainfall data at the onset of reactivation events has proved that they occurred after periods with cumulated values higher than the averages of the last 30 years. The quantification of the morphological modifications induced by these reactivations has been made possible by comparing pre- and post-event digital elevation models. Depletion and accumulation has been in the range of 30 m in different parts of the slope. In particular, an advancement of the landslide toe of more than 400 m, which caused a 30-m thick landslide tip to deposit, has been clearly seen. Monitoring data regarding subsurface movements and surface tension crack widening (tension cracks so large as to be properly described at trenches) has shown that sliding surfaces as deep as 43 m exist in the upper part of the landslide, while the accumulation lobe has moved by sliding and flowing over surfaces as deep as some 10 m. Velocities of cm/day have been recorded in the deep surfaces and in widening trenches of the source area, while the advancement of the accumulation lobe has been estimated as having velocities of up to 10 m/day. Groundwater in the landslide body has been observed at depths of 5–15 m in the upper areas, while it is estimated as being at the ground level in the toe. On this basis, it is concluded that the landslide still has a high potential for further development, both in the upper landslide zone and in the toe area.     

Kinematic evolution of thrust-related structures in the Umbro-Romagnan parautochthon (northern Apennines, Italy)

In the internal part of the Umbro-Marchean-Romagnan Apennines, the foredeep clastic wedge constituting the Neogene part of the sedimentary cover is completely detached from the underlying Mesozoic–Palaeogene succession. The resulting (Umbro-Romagnan) parautochthon consists of tectonostratigraphic units with a general geometry of broad synclinal blocks separated by narrow faulted anticlines.
Thrust-related structures observed in the field require thrust ramp propagation to have occurred within already folded rocks; therefore, they cannot be restored using simple fault-bend fold or fault-propagation folding models. Evidence for a passive fold origin in the studied rocks suggests that an early detachment folding episode preceded ramp propagation. The latter was facilitated by the enhanced thickness of incompetent material in the cores of detachment anticlines, which became the preferential sites where thrust ramps cut up-section. Depending on the trajectory of such thrust ramps, different types of fault-related structures could develop. Hanging-wall anticlines which give way to monoclinal structures higher up in the section are associated with listric thrust ramps, whereas hanging wall monoclines approximately parallel to the underlying fault surface are associated with straight-trajectory ramps.
This kinematic evolution, which occurred partly during syn-depositional compression, also accounts for the observed lithofacies distribution. The latter reflects an early differentiation of the foredeep trough into sub-basins that are progressively younger towards the foreland. The detachment anticlines that originally bounded such sub-basins were the site of later thrust propagation, leading to a tectonic juxtaposition of different tectonostratigraphic units consisting of broad NW-SE elongate synclinal blocks.