1,721,423 research outputs found
Landslide damming hazard susceptibility maps: a new GIS-based procedure for risk management
Full text linkA complete landslide dam hazard management incorporates two assessment phases: the damming probability and the breach hazard. A prompt evaluation of the dam stability is crucial during the emergency to mitigate its consequences, but a reliable risk assessment can be realized only after the event has occurred, when the available time is very short. Therefore, it is necessary to develop tools able to help in mapping the spatial probability of damming over large areas for land-use planning, in order to better constrain consequence analysis and risk scenarios for setting up mitigation measures. In this work, a semi-automated GIS-based mapping methodology, based on a statistical correlation of morphometric parameters described by a morphological index, is proposed to spatially assess the likelihood of a river obstruction by landslide damming through two main mechanisms: the reactivation of existing landslides and the formation of new landslides. The two mapping methods (damming predisposition and damming probability) were used on a test area, the Arno River basin in Italy. The Eastern part of the basin resulted as the most susceptible to damming events in the whole basin. These are the highest mountain ridges in the basin (about 1600 m a.s.l.), characterized by calcareous, arenaceous, and marl lithology. The results are confirmed by the high concentration of the known historical landslide dams in the area according to existing inventories
Artificial Neural Networks applied to landslide susceptibility assessment
No full textLandslide hazard mapping is often performed through the identification and analysis of hillslope instability factors, usually managed as thematic data within geographic information systems (GIS). In heuristic approaches, these factors are rated by the attribution of scores based on the assumed role played by each of them in controlling the development of a sliding process. Other more refined methods, based on the principle that the present and the past are keys to the future, have also been developed, thus allowing less subjective analyses in which landslide susceptibility is assessed by statistical relationships between past landslide events and hillslope instability factors. The objective of this research is to define a method with the ability to forecast landslide susceptibility through the application of Artificial Neural Networks (ANNs). The Riomaggiore catchment, a subwatershed of the Reno River basin located in the Northern Apennines (Italy), was chosen as an ideal test site, as it is representative of many of the geomorphological settings within this region. In the present application, two different ANNs, used in classification problems, were set up and applied: one belonging to the category of Multi-Layered Perceptron (MLP) and the other to the Probabilistic Neural Network (PNN) family. The hillslope factors that have been taken into account in the analysis were the following: (a) lithology, (b) slope angle, (c), profile curvature, (d) land cover and (e) upslope contributing area. These factors have been classified on nominal scales, and their intersection allowed 3342 homogeneous domains (Unique Condition Unit, UCU) to be singled out, which correspond to the terrain units utilized in this analysis. The model vector used to train the ANNs is a subset of that derived from the production of Unique Condition Units and consists of 3342 records organized in input and output variable vectors. In particular, the hillslope factors, once classified on nominal scales as binary numbers, represent the 19 input variables, while the presence/ absence of a landslide in a given terrain unit is assumed to be the output variable. The comparison between the most up-to-date landslide inventory of the Riomaggiore catchment and the hazardous areas, as predicted by the ANNs, showed satisfactory results (with a slight preference for the MLP). For this reason, this is an encouraging preliminary approach towards a systematic introduction of ANN-based statistical methods in landslide hazard assessment and mapping. © 2004 Elsevier B.V. All rights reserved
Monitoring and modelling of pore water pressure changes and riverbank stability during flow events
No full textPore water pressures (positive and negative) were monitored for four years (1996-1999) using a series of tensiometer-piezometers at increasing depths in a riverbank of the Sieve River, Tuscany (central Italy), with the overall objective of investigating pore pressure changes in response to flow events and their effects on bank stability. The saturated/unsaturated flow was modelled using a finite element seepage analysis, for the main flow events occurring during the four-year monitoring period. Modelling results were validated by comparing measured with computed pore water pressure values for a series of representative events. Riverbank stability analysis was conducted by applying the limit equilibrium method (Morgenstern-Price), using pore water pressure distributions obtained by the seepage analysis. The simulation of the 14 December 1996 event, during which a bank failure occurred, is reported in detail to illustrate the relations between the water table and river stage during the various phases of the hydrograph and their effects on bank stability. The simulation, according to monitored data, shows that the failure occurred three hours after the peak stage, during the inversion of flow (from the bank towards the river). A relatively limited development of positive pore pressures, reducing the effective stress and annulling the shear strength term due to the matric suction, and the sudden loss of the confining pressure of the river during the initial drawdown were responsible for triggering the mass failure. Results deriving from the seepage and stability analysis of nine selected flow events were then used to investigate the role of the flow event characteristics (in terms of peak stages and hydrograph characteristics) and of changes in bank geometry. Besides the peak river stage, which mainly controls the occurrence of conditions of instability, an important role is played by the hydrograph characteristics, in particular by the presence of one or more minor peaks in the river stage preceding the main on
Pore water pressures and strembank stability: results from a monitoring site on the Sieve River, Italy
No full textTo investigate the role of pore water pressures in the stability of a streambank, a series of tensiometers and piezometers was installed in a bank of the Sieve River, Tuscany, Italy. Fluvial entrainment at the bank toe was monitored by repeated cross-profiling, erosion pins and marked pebbles. Fluctuations in matric suction measured at the tensiometers reflected the overall response of pore water pressures to rainfall, evapotranspiration, rising and drawdown of the river stage, and variations in water table. An expression was derived for the safety factor with respect to mass movement of the upper bank, incorporating the failure criterion for unsaturated soils and the normal Mohr-Coulomb criterion for saturated conditions. Variations in matric suction have important effects on the stability of the streambank. During low-flow periods, the shear strength term due to the matric suction allows the bank to remain stable at a steep angle. However, during rainfall and flow events, reduction i..
Modeling of the Guagua Pichincha volcano (Ecuador) lahars
No full textLahars, here defined as debris flows of volcanic origin, are rapid mass movements that pose a serious threat to cities located in the vicinity of many volcanoes. Quito, capital city of Ecuador and placed at the foot of the Pichincha volcano complex, is exposed to serious inundation hazard as part of the city is built on numerous deposits of large lahars that have occurred in the last 10,000 years. The objective of this paper is to model the potential lahars of the Pichincha volcano to predict inundation areas within the city of Quito. For this purpose two models that apply different approaches were utilized and their results were compared. The programs used were LAHARZ, a semi-empirical model conceived by the United States Geological Survey (USGS), and FLO-2D, a hydraulic model distributed by FLO Software Inc. LAHARZ is designed as a rapid, objective and reproducible automated method for mapping areas of potential lahar inundation (Proc. First Int. Conf. on Debris Flow Hazards Mitigation, San Francisco, USA, ASCE, 1998, p. 176). FLO-2D is a two-dimensional flood routing model for simulating overland flow on complex surfaces such as floodplains, alluvial fans or urbanized areas (FLO-2D Users manual, version 99.2). Both models run within geographical information systems (GIS). Fieldwork was focused on collecting all available information involved in lahar modeling. A total of 49 channel cross-sections were measured along the two main streams and stratigraphic investigations were carried out on the fans to estimate the volume of previous events. A global positioning system was utilized to determine the coordinates of each cross-section. Further data collection concerned topography, rainfall characteristics and ashfall thicknesses. All fieldwork was carried out in cooperation with the Instituto Geofisico of the Escuela Politecnica Nacional. Modeling in a GIS environment greatly aided the exportation of results for the creation of thematic maps and facilitated model comparison. Evaluation of the models was performed by comparing simulation results against each other and against the geometry of existing lahar deposits. © 2002 Elsevier Science Ltd. All rights reserved
Terrestrial laser scanner and geomechanical surveys for the rapid evaluation of rock fall susceptibility scenarios
No full textThe primary objective of this paper is to present a semiautomatic procedure that, integrated with traditional methods, can be useful for a rapid definition of rock fall susceptibility scenarios with the purpose of civil protection. Due to its morphology (steep slopes and narrow valleys), regional seismicity, and rock mass characteristics, the Nera Valley (Valnerina, Umbria Region, Italy) is characterized by high rock fall risk. With the aim of covering a wide range of features and investigating the main advantages and drawbacks of the proposed approach, data collection (terrestrial laser scanning (TLS) and geomechanical surveys) was carried out at three different slopes. Detailed three-dimensional (3D) models were created to reconstruct the shape and volume of the most unstable blocks, to define the position of the main rock fall source areas, and to precisely distinguish the outcropping materials and the position of the elements at risk for reliable runout analyses. The proposed approach can be useful in supporting proper maintenance and land management programs both in ordinary and in emergency circumstances
Analysing the relationship between rainfalls and landslides to define a mosaic of triggering thresholds for regional-scale warning systems
Full text linkWe propose an original approach to develop rainfall thresholds to be used in civil protection warning systems for the occurrence of landslides at regional scale (i.e. tens of thousands of kilometres), and we apply it to Tuscany, Italy (23 000 km2). Purpose-developed software is used to define statistical intensity-duration rainfall thresholds by means of an automated and standardized analysis of rainfall data. The automation and standardization of the analysis brings several advantages that in turn have a positive impact on the applicability of the thresholds to operational warning systems. Moreover, the possibility of defining a threshold in very short times compared to traditional analyses allowed us to subdivide the study area into several alert zones to be analysed independently, with the aim of setting up a specific threshold for each of them. As a consequence, a mosaic of several local rainfall thresholds is set up in place of a single regional threshold. Even if pertaining to the same region, the local thresholds vary substantially and can have very different equations. We subsequently analysed how the physical features of the test area influence the parameters and the equations of the local thresholds, and found that some threshold parameters can be put in relation with the prevailing lithology. In addition, we investigated the possible relations between effectiveness of the threshold and number of landslides used for the calibration. A validation procedure and a quantitative comparison with some literature thresholds showed that the performance of a threshold can be increased if the areal extent of its test area is reduced, as long as a statistically significant landslide sample is present. In particular, we demonstrated that the effectiveness of a warning system can be significantly enhanced if a mosaic of site-specific thresholds is used instead of a single regional threshold
Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system
Full text linkWe communicate the results of a preliminary investigation aimed at improving a state-of-the-art RSLEWS (regional-scale landslide early warning system) based on rainfall thresholds by integrating mean soil moisture values averaged over the territorial units of the system. We tested two approaches. The simplest can be easily applied to improve other RSLEWS: it is based on a soil moisture threshold value under which rainfall thresholds are not used because landslides are not expected to occur. Another approach deeply modifies the original RSLEWS: thresholds based on antecedent rainfall accumulated over long periods are substituted with soil moisture thresholds. A back analysis demonstrated that both approaches consistently reduced false alarms, while the second approach reduced missed alarms as well
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