
Citation: | Vito Summa, Rosa Sinisi, Eleonora Paris, Agnese Emanuela Bonomo. Compositional Features of Fine Sediments Involved in the Montescaglioso Landslide (Southern Italy). Journal of Earth Science, 2022, 33(6): 1513-1525. doi: 10.1007/s12583-021-1579-8 |
This paper presents the multidisciplinary study of the southern Italy Plio-Pleistocene sediments involved in the large Montescaglioso Landslide. The principal aim of the work is to assess the compositional characters (i.e., grain-size, mineralogy, petrography and geochemistry) and some rheological features (Atterberg's limits, plasticity index and activity) of these sediments to enrich our knowledge about the Montescaglioso fine sediments and correlation among the lithological properties studied. Two types of sediments, from a deep geognostic borehole and from the surrounding landslide area, were collected and analysed. No significant compositional differences have been found between the core and landslide area sediments. Conversely, some changes have been detected in sediments along the core. Particularly, the -15 to -20 m lithostratigraphic level hosts the highest percentages of phyllosilicates and clay fraction (CF), commonly considered as possible hazard factors for the landslide triggering. Further more, in the studied core sediments, the CF contents correlate with the Atterberg's liquid and plastic limits and a CF value of about 38% was suggested as threshold value for the changing of index properties of sediments. Other factors, such as the weathering degree and clay mineral type, do not show significant correlations with the rheological properties of sediments here studied.
In China, due to the lack of comprehensive utilization of coal gangue, the majority of them had been stacked in open air and become one of the largest solid wastes (Bi et al., 2005). Coal gangue has done extensive damage to environment, such as land destruction, water and soil pollution, etc. (Wang et al., 2006). Furthermore, unstable slope of coal gangues may threaten life and do harm to human health.
Heshan, a city located in Guangxi Zhuang Autonomous Region, Southwest China, owns the largest coal mine in Guangxi with over hundred years of coal mining history (see Fig. 1). Due to low rate of resource reclamation, large amounts of coal gangue have been stacked on surface and became typical solid wastes. According to researches, due to the lack of long-time consolidation caused by multiple times of screening residual coal, the stability of coal gangue heaps under natural conditions is controlled by the surface friction of grains. Because the cohesion strength is almost zero, the natural angle of repose could be the main strength parameter of coal gangue heaps. However, it is impossible to obtain mechanical parameters through indoor tests due to the fact that the compositions of coal gangue are complex and uneven. In the past, the in-situ shear test or analogies of experience were generally applied to determine the strength parameter (Tang et al., 2012; Liu et al., 2006; Duncan et al., 1980).
In recent years, the Chinese government has provided large amount of fund to cities faced with resources exhaustion to help them to solve mining-related environmental problems and to develop economy. Coal-mining cities like Heshan have taken various measures to improve their environment, of which coal gangue management project is of great importance. Our research selects Dongkuang coal gangue heap, the largest one in Heshan, as its object. Through in-situ grain sieving method, the grain size of coal gangue was determined and the grading composition was calculated and on this basis we can evaluate the suitability of coal gangue for backfilling collapse pits and goaf and filling the roadbed. Besides, through in-situ mix proportion test, the repose angle of coal gangue was measured and a systematic study was made on the change rule of natural repose angle of coal gangue in different ranges of grain size to provide guidance for the design of Dongkuang large coal gangue heap management project.
The grain sieving experiment was conducted at the northwest of the large coal gangue heap in Dongkuang, where the side slope of coal gangue extends 300 m, the slope height is 20 m and the slope angle is about 40°. Due to the lack of protective measures, several fractures have been developed at the top of the northwestern slope with the major one about 20 m long and 2–3 cm wide. The top terrace of the slope is a catchment area with a gully formed by rainwater, and there are bulges in the middle of the slope. With the dormitories of mineworkers and producing mines at the foot of the side slope, the lives of miners and the safety production are exposed to the risks of land slide and debris flow in extreme weather.
In the experiment, three profiles, namely profiles 1, 2 and 3, were selected on the unstable slope, each with three test sites, i.e., sites A, B and C, as presented in Fig. 1. Based on the actually measured grain sizes of coal gangue, we used special square mesh sieves for the sieving experiment, and the sieve sizes are 1.5, 3, 5, 12.5, 25, 35, 50, 65, 80, 100 and 150 mm, respectively. Since the grain sizes on the upper and middle part of the slope do not vary much, the same measuring scale was adopted, and the sieve sizes are 1.5, 3, 5, 12.5, 25, 35, 50, 80 and 100 mm, respectively. The grain sizes at the slope foot vary greatly, and therefore the sieve meshes of the sizes 35, 65 and 150 mm were added. Thirty kilogram of coal gangue was sampled at each test site and those of extremely irregular shape or giant grains were eliminated through the scalping method. Samples were sun dried, screened and weighed. The sample amount and test procedure comply with requirements of the Test Method of Soils and the Method for Size Analysis of Coal (Tangshan Research Institute of CCRI, 2009).
The grain size distribution of coal gangue at each test site is shown in Table 1. The mass distribution in each range of grain size indicates that there is more and wider range of fine grains at upper and middle test sites and those sized between 5–50 mm comprise over 60% of the total; and there are fewer fine grains at the bottom test site and the grain sizes vary greatly, ranging between 12.5–100 mm.
![]() |
Grain grading curves were drawn through EXCEL (see Fig. 2) and grading parameters were obtained by calculating the mean grain size d50, the uniformity coefficient Cu and the curvature coefficient Cc (see Table 2).
![]() |
Figure 2 shows that grading curves of the upper and middle test sites are smooth with wide range of grain size and homogeneous distribution of coarse and fine grains. The grading curve of the bottom test site has even step with deficiency in grain size and the content of fine grains is obviously lower than that of the other two test sites. According to Table 2, the grain size of the middle test site is a little larger than that of the upper test site, and there is a sharp increase of grain size at the bottom test site which means that there are fewer fine grains at the bottom slope. However, grain sizes from upper to bottom do not increase in linearity. Previous studies indicated that the average grain size of bulky grains of soil dumping site is in exponential relationship to the relative height of the sampling sites (Wang et al., 2012). This paper has demonstrated the exponential relationship of grain distribution though it can hardly obtain the quantitative relationship of the mean grain size because of the rather small number of test sites in present research.
In view of different grain gradations, engineering characteristics of coal gangue in the same place may be different. However, only typical parameters can be selected for subsequent stability analysis. The following is how the representative grading of coal gangue was acquired based on the above-mentioned experiment.
Common methods for determining representative grading are the grading curve envelope diagram method, the arithmetic mean method of grain grading, the classification statistics method of coarse grain content (d>5 mm), and the percentage statistics method (Guo, 1999). This paper adopted the statistics method of coarse grain content to determine the representative grading. Nine screening samples were regrouped, and the grading of first four groups with large percentages was averaged to get the representative grading of coal gangue. The grain composition of the representative grading is listed in Table 3.
![]() |
As is shown in Table 4 and Fig. 3, the representative grading curve of coal gangue in Dongkuang Mine is smooth with a wide-range grain size, its gradation parameters Cu>5 and 3>Cc>1. Therefore, the coal gangue is well graded, and is good to be used as filling materials (Hu et al., 2012; de Mello, 1977).
![]() |
The in-situ direct shear test once conducted in the large gangue heap of Dongkuang had failed to measure mechanical parameters of coal gangue because the loose grains of those test pits that had been dug up made it impossible to make sample preparation. In coarse grain theory and engineering practice at home and abroad, coal gangue is usually regarded as bulky material. Besides, grains of the shallow layer of the side slope of coal gangue leap are loose. So, a better option is to use the natural angle of repose as the internal friction angle to make related calculations.
In order to study the relationship between repose angle and grain grading to facilitate estimating the mechanical parameters of coal gangue under the condition that the grain size distribution is clear, a group of tests have been designed to analyze the relevance of repose angle to grain grading, and the relationship between physical and mechanical parameters of coal gangue, thus providing basis for qualitative and quantitative assessment of side slope stability of coal gangue.
This experiment was made in the northwestern side slope of large coal gangue heap in Dongkuang. Based on the preliminary survey and the data obtained in grain sieving experiment, the actual grain sizes were divided into five grades in descending order (see Table 5).
![]() |
By referring to the research method of coarse grained soil, the experiment focuses on the change rule of mechanical properties along with the change of coarse grain content. According to the data obtained in grain sieving experiment, the mean grain sizes d50 of coal gangue grains in Dongkuang are mostly distributed between 12.5 and 25 mm. To investigate the influence rule of coarse grain content on the repose angle, the grain content between 12.5 and 25 mm was maintained unchanged to keep regular changes between the smallest and smaller, and the largest and larger. On the basis of comprehensive consideration and calculations, a mix proportion was finally determined with better control of coarse grain content and fractal dimension (see Table 6 for the mix proportion and relevant gradation parameters). The coarse grain content controlled by the experimental design is within 65%–95%, exactly the same as the actual situation where coarse grains (≥5 mm) take up 65%–95% of the total in this area based on the data in grain sieving experiment.
![]() |
Natural samples of coal gangue were screened and separated by grain sizes and mixed well according to proportions designed for each group of test (see Table 6). In each group of test, the mix sample was 100 kg and water content was basically the same. Mix samples were piled up in different groups using self-made support and funnel. Six sets of slope angles were measured by goniometry around the sample coal gangue heap. Two sets of data with much larger deviations were eliminated, and the average value of the remained four sets were taken as the repose angle of the coal gangue heap, as presented in Table 6. The sample amount and test procedure comply with requirements of the Test Method of Soils and the Method for Size Analysis of Coal (Tangshan Research Institute of CCRI, 2009).
The repose angle of coal gangue changes along with the content of coarse grains and fine grains. Coarse grains influence the repose angle through the interface friction and occlusion of grains, while fine grains are internal friction to do it. The friction angle of coarse grains is mainly from the binding force of grain angularities, and that of fine grains is mainly from the friction force and cohesive force (very small one) on grain surface. They work in the following way.
1. When coarse grain content is very high, grains have good friction that can interlock each other and form a skeleton of good stability. There are only a small number of fine grains dispersing in the pores with almost no influence on the repose angle. In this situation, if coarse grain content decreases, the repose angle will become smaller.
2. When coarse grain content decreases to a certain value, fine grains fill most of the pores, compactness increases under self-weight and the binding force of coarse grains remains almost unchanged. The increase of fine grain content enhances the sliding friction force. In this situation, if coarse grain content decreases, the repose angle will become bigger.
3. If coarse grain content continues to decrease, there will be no resistance force from coarse grains, and the friction angle of bulk material is mainly from the sliding friction force. In this situation, the more and the thinner fine grains are and the better their fluidity is, the smaller the repose angle is.
Some researches indicate that two typical features of the change of mechanical properties of coarse grained soil are coarse grain content being 30% and 70%, respectively (Guo, 1999). The relationship curve of repose angle and coarse grain content shows that the content of 70% is the inflection point of ascent stage and 85% the inflection point of descent stage of the repose angle (see Fig. 4). The coarse gravel gives play to the repose angle through the interface friction and occlusion of grains, but the small gravel is internal friction to do it. At the peak point of 70%, the small gravel could fill the interspace of coarse gravel well, and both of them support the repose angle together. With the increasing of coarse gravel, the small gravel can't fill the interspace of coarse gravel and reduce the interface friction of coarse gravel, and result in the trough point of the curve at 85%. When the content of coarse gravel was more than 85%, the repose angle would enhance with increasing interface friction of coarse gravels.
In Dongkuang, the mean content of coarse grains of the representative grading of coal gangue is 81.0% which is at the descent stage of the change curve of the repose angle. By fitting the curve, we estimate that the repose angle corresponding to the representative grading of coal gangue in this area is approximately 38.4° and this has guiding significance for side slope stability analysis and management project of coal gangue.
1. In the upper and middle part of coal gangue heap, there are more fine grains. Grains are wide-ranged and those with a size ranging between 5–50 mm take up over 60% of the total. At the bottom of the heap, there are fewer fine grains with large difference in grain gradation, distributed within the range of 12.5–100 mm.
2. The representative grading curve of coal gangue in Dongkuang is flat and smooth with a wide-range grain size. The uniformity coefficient Cu of coal gangue is 25.56 and the coefficient of curvature Cc is 2.72, which indicates that the coal gangue is well graded and easy to be compacted and therefore is good to be used as filling materials.
3. The repose angle of coal gangue is heavily influenced by the change of coarse grain content. In the wave-change curve of the repose angle, the content of coarse grains being 70% is the inflection point of ascent stage and 85% the inflection point of descent stage.
4. According to the change rule of the repose angle of coal gangue in Dongkuang, the one corresponding to the representative grading of coal gangue in this area is estimated to be approximately 38.4° and this has guiding significance for the design of management project of coal gangue.
Amanti, M., Chiessi, V., Guarino, P. M., et al., 2016. Back-Analysis of a Large Earth-Slide in Stiff Clays Induced by Intense Rainfalls. In: Aversa, S., Cascini, L., Picarelli, L., et al., eds., Landslides and Engineered Slopes. Experience, Theory and Practice. Proceedings of the 12th International Symposium on Landslides. June 12–19, 2016, Napoli, Italy. 317–324. https://doi.org/10.1201/9781315375007 |
ASTM, 2007. ASTM Book of Standards, PA. ASTM, Philadelphia |
Blott, S. J., Pye, K., 2012. Particle Size Scales and Classification of Sediment Types Based on Particle Size Distributions: Review and Recommended Procedures. Sedimentology, 59(7): 2071–2096. https://doi.org/10.1111/j.1365-3091.2012.01335.x |
Bonomo, A. E., 2015. Composition and Properties of Sediments Involved in the Montescaglioso Landslide (Basilicata, Southern Italy): [Disser-tation]. Geoenvironmental Resources and Risks, School of Science and Technology, Geology division, University of Camerino, Camerino |
Bozzano, F., Caporossi, P., Esposito, C., et al., 2017. Mechanism of the Montescaglioso Landslide (Southern Italy) Inferred by Geological Survey and Remote Sensing. Abstract in 4th World Landslide Forum. May 29–June 2, 2017, Ljubljana, Slovenia. 97–106. https://doi.org/10.1007/978-3-319-53498-5_12 |
Brondi, A., Colica, A., Conti, P., et al., 1993. Joints in Clays of the Neogenic Basin of Siena. Mineralogica et Petrographica Acta, 35: 51–65 |
Caporossi, P., Mazzanti, P., Bozzano, F., 2018. Digital Image Correlation (DIC) Analysis of the 3 December 2013 Montescaglioso Landslide (Basilicata, Southern Italy): Results from a Multi-Dataset Investigation. ISPRS International Journal of Geo-Information, 7(9): 372. https://doi.org/10.3390/ijgi7090372 |
Carlà, T., Raspini, F., Intrieri, E., et al., 2016. A Simple Method to Help Determine Landslide Susceptibility from Spaceborne InSAR Data: The Montescaglioso Case Study. Environmental Earth Sciences, 75(24): 1–12. https://doi.org/10.1007/s12665-016-6308-8 |
Casagrande, A., 1948. Classification and Identification of Soils. Transactions of the American Society of Civil Engineers, 113(1): 901–930. https://doi.org/10.1061/taceat.0006109 |
Cavalcante, F., Fiore, S., Lettino, A., et al., 2007. Illite-Smectite Mixed Layers in Sicilide Shales and Piggy-Back Deposits of the Gorgoglione Formation (Southern Appennines): Geological Inferences. Bollettino della Societa Geologica Italiana, 126: 241–254 |
Cestelli Guidi, C., 1987. Geotecnica e Tecnica delle Fondazioni (Geotechnical and Fundation Engineering). Hoepli, U., Milano. XXXII-864 (in Italian) |
Cuadros, J., Fiore, S., Huertas, F. J., 2010. Introduction to Mixed-Layer Clay Minerals. In: Fiore, S., Cuadros, J., Huertas, F. J., eds., Interstratified Clay Minerals: Origin, Characterization and Geochemical Significance. AIPEA Educational Series, Pub. No. 1, Digilabs, Bari, Italy. 175 |
Dai, F. C., Lee, C. F., Ngai, Y. Y., 2002. Landslide Risk Assessment and Management: An Overview. Engineering Geology, 64(1): 65–87. https://doi.org/10.1016/s0013-7952(01)00093-x |
D'Ecclesiis, G., Lorenzo, P., 2006. Relict Landslides in the Deposits of Adriatic Foredeep: The Landslide of Madonna della Nuova (Montescaglioso, Basilicata). Giornale di Geologia Applicata, 4: 257–262 (in Italian with English Abstract) |
Facciorusso, J., Madiai, C., Vannucchi, G., 2011. Dispense di Geotecnica (Lecture Notes of Geotechnics). Pisa University Press, Pisa (in Italian) |
Fedo, C. M., Wayne Nesbitt, H., Young, G. M., 1995. Unraveling the Effects of Potassium Metasomatism in Sedimentary Rocks and Paleosols, with Implications for Paleoweathering Conditions and Provenance. Geology, 23(10): 921–924https://doi.org/10.1130/0091-7613(1995)0230921:uteopm>2.3.co;2 doi: 10.1130/0091-7613(1995)0230921:uteopm>2.3.co;2 |
Ferrell, R. E. Jr., Aparicio, P., Forsman, J., 2010. Interstratified Clay Minerals in the Weathering Environment. In: Fiore, S., Cuadros, J., Huertas, F. J., eds., Interstratified Clay Minerals: Origin, Characterization and Geochemical Significance. AIPEA Educational Series, Pub. No. 1, Digilabs, Bari, Italy. 175 |
Franzini, M., Leoni, L., Saitta, M., 1972. A Simple Method to Evaluate the Matrix Effects in X-Ray Fluorescence Analysis. X-Ray Spectrometry, 1(4): 151–154. https://doi.org/10.1002/xrs.1300010406 |
Franzini, M., Leoni, L., Saitta, M., 1975. Revisione di una Metodologia Analitica per Fluorescenza X Basata sulla Correzione Completa degli Effetti di Matrice (Review of an Analytical Methodology for X-Ray Fluorescence Based on the Complete Correction of Matrix Effects). Società Italiana di Mineralogia e Petrologia, 31: 365–378 (in Italian) |
Gariano, S. L., Guzzetti, F., 2016. Landslides in a Changing Climate. Earth-Science Reviews, 162: 227–252. https://doi.org/10.1016/j.earscirev.2016.08.011 |
Giannecchini, R., Galanti, Y., D'Amato Avanzi, G., et al., 2016. Probabilistic Rainfall Thresholds for Triggering Debris Flows in a Human-Modified Landscape. Geomorphology, 257: 94–107. https://doi.org/10.1016/j.geomorph.2015.12.012 |
Guzzetti, F., Cardinali, M., Reichenbach, P., 1994. The AVI Project: A Bibliographical and Archive Inventory of Landslides and Floods in Italy. Environmental Management, 18(4): 623–633. https://doi.org/10.1007/bf02400865 |
Guzzetti, F., Tonelli, G., 2004. Information System on Hydrological and Geomorphological Catastrophes in Italy (SICI): A Tool for Managing Landslide and Flood Hazards. Natural Hazards and Earth System Sciences, 4(2): 213–232. https://doi.org/10.5194/nhess-4-213-2004 |
Harnois, L., 1988. The CIW Index: A New Chemical Index of Weathering. Sedimentary Geology, 55(3/4): 319–322. https://doi.org/10.1016/0037-0738(88)90137-6 |
Holtz, R. D., Kovacs, W. D., 1981. An Introduction to Geotechnical Engineering. Prentice-Hall, Englewood Cliffs, New Jersey, USA |
Igwe, O., Mode, W., Nnebedum, O., et al., 2014. The Analysis of Rainfall-Induced Slope Failures at Iva Valley Area of Enugu State, Nigeria. Environmental Earth Sciences, 71(5): 2465–2480. https://doi.org/10.1007/s12665-013-2647-x |
Igwe, O., 2015. The Geotechnical Characteristics of Landslides on the Sedimentary and Metamorphic Terrains of South-East Nigeria, West Africa. Geoenvironmental Disasters, 2: 1. https://doi.org/10.1186/s40677-014-0008-z |
Kenney, T. C., 1967. The Influence of Mineralogical Composition on the Residual Shear Strength of Natural Soils. In: Proc. Geotech. Conf. on Shear Strength Properties of Natural Soils and Rocks, Oslo. 123–129 |
Kenney, T. C., 1977. Residual Shear Strength of Mineral Mixtures. 9th International Conference on Soil Mechanics and Foundation Engineering, Tokyo. 155–160 |
Manconi, A., Casu, F., Ardizzone, F., et al., 2014. Brief Communication: Rapid Mapping of Landslide Events: The 3 December 2013 Montescaglioso Landslide, Italy. Natural Hazards and Earth System Sciences, 14(7): 1835–1841. https://doi.org/10.5194/nhess-14-1835-2014 |
Mesri, G., Cepeda-Diaz, A. F., 1986. Residual Shear Strength of Clays and Shales. Géotechnique, 36(2): 269–274. https://doi.org/10.1680/geot.1986.36.2.269 |
Napolitano, E., Fusco, F., Baum, R. L., et al., 2016. Effect of Antecedent-Hydrological Conditions on Rainfall Triggering of Debris Flows in Ash-Fall Pyroclastic Mantled Slopes of Campania (Southern Italy). Landslides, 13(5): 967–983. https://doi.org/10.1007/s10346-015-0647-5 |
Nesbitt, H. W., Young, G. M., 1982. Early Proterozoic Climates and Plate Motions Inferred from Major Element Chemistry of Lutites. Nature, 299(5885): 715–717. https://doi.org/10.1038/299715a0 |
Ohlmacher, G. C., 2000. The Relationship between Geology and Landslide Hazards of Atchison, Kansas, and Vicinity. Current Research in Earth Sciences, 244: 1–16. https://doi.org/10.17161/cres.v0i244.11833 |
Ohta, T., Arai, H., 2007. Statistical Empirical Index of Chemical Weathering in Igneous Rocks: A New Tool for Evaluating the Degree of Weathering. Chemical Geology, 240(3/4): 280–297. https://doi.org/10.1016/j.chemgeo.2007.02.017 |
Pellicani, R., Spilotro, G., Ermini, R., et al., 2016. The Large Montescaglioso Landslide of December 2013 After Prolonged and Severe Seasonal Climate Conditions. Abstract in 12th International Symposium on Landslides, June 12–19, Naples, Italy. 1591–1597 |
Pellicani, R., Argentiero, I., Manzari, P., et al., 2019. UAV and Airborne LiDAR Data for Interpreting Kinematic Evolution of Landslide Move-ments: The Case Study of the Montescaglioso Landslide (Southern Italy). Geosciences, 9(6): 248. https://doi.org/10.3390/geosciences9060248 |
Perrone, A., Piscitelli, S., Gueguen, E., et al., 2014. Electrical Resistivity Tomographies for the Geophysical Characterization of the Montescag-lioso Slope (MT) Affected by the 3 December 2013 Landslide). [2021-8-20]. http://www.emergenza.regione.basilicata.it/emerg_alluv_2011/files/docs/10/05/16/DOCUMENT_FILE_100516.pdf (in Italian) |
Plank, T., Langmuir, C. H., 1998. The Chemical Composition of Subducting Sediment and Its Consequences for the Crust and Mantle. Chemical Geology, 145(3/4): 325–394. https://doi.org/10.1016/s0009-2541(97)00150-2 |
Raspini, F., Ciampalini, A., del Conte, S., et al., 2015. Exploitation of Amplitude and Phase of Satellite SAR Images for Landslide Mapping: The Case of Montescaglioso (South Italy). Remote Sensing, 7(11): 14576–14596. https://doi.org/10.3390/rs71114576 |
Rosi, A., Segoni, S., Catani, F., et al., 2012. Statistical and Environmental Analyses for the Definition of a Regional Rainfall Threshold System for Landslide Triggering in Tuscany (Italy). Journal of Geographical Sciences, 22(4): 617–629. https://doi.org/10.1007/s11442-012-0951-0 |
Schultz, L. G., 1964. Quantitative Interpretation of Mineralogical Composition from X-Ray and Chemical Data for the Pierre Shale. Professional Paper 391-C: 1–31. https://doi.org/10.3133/pp391c |
Shaw, D. B., Stevenson, R. G., Weaver, C. E., et al., 1971. Interpretation of X-Ray Diffraction Data. In: Carver, R. E., ed., Procedures in Sedimentary Petrology. Wiley, New York. 554–557 |
Skempton, A. W., 1964. Long-Term Stability of Clay Slopes. Géotechnique, 14(2): 77–102. https://doi.org/10.1680/geot.1964.14.2.77 |
Summa, V., 2000. Analisi Granulometrica dei Sedimenti. In: Metodi di Analisi di Materiali Argillosi. V Corso di Formazione AIPEA, Association Internationalle Pour l'Etude des Argiles, Gruppo Italiano. 19–29 |
Summa, V., Tateo, F., Medici, L., et al., 2007. The Role of Mineralogy, Geochemistry and Grain Size in Badland Development in Pisticci (Basilicata, Southern Italy). Earth Surface Processes and Landforms, 32(7): 980–997. https://doi.org/10.1002/esp.1449 |
Summa, V., Tateo, F., Giannossi, M. L., et al., 2010. Influence of Clay Mineralogy on the Stability of a Landslide in Plio-Pleistocene Clay Sediments near Grassano (Southern Italy). CATENA, 80(2): 75–85. https://doi.org/10.1016/j.catena.2009.09.002 |
Summa, V., Margiotta, S., Colaiacovo, R., et al., 2015. The Influence of the Grain-Size, Mineralogical and Geochemical Composition on the Verdesca Landslide. Natural Hazards and Earth System Sciences, 15(1): 135–146. https://doi.org/10.5194/nhess-15-135-2015 |
Summa, V., Margiotta, S., Medici, L., et al., 2018. Compositional Characterization of Fine Sediments and Circulating Waters of Landslides in the Southern Apennines-Italy. CATENA, 171: 199–211. https://doi.org/10.1016/j.catena.2018.07.009 |
Taylor, S. R., McLennan, S. M., 1985. The Continental Crust: Its Composition and Evolution. The Journal of Geology, 94(4): 57–72 |
Tropeano, M., Sabato, L., Pieri, P., 2002. Filling and Cannibalization of a Foredeep: The Bradanic Trough, Southern Italy. Geological Society, London, Special Publications, 191(1): 55–79. https://doi.org/10.1144/gsl.sp.2002.191.01.05 |
Whitney, D. L., Evans, B. W., 2010. Abbreviations for Names of Rock-Forming Minerals. American Mineralogist, 95(1): 185–187. https://doi.org/10.2138/am.2010.3371 |
Yalcin, A., 2007. The Effects of Clay on Landslides: A Case Study. Applied Clay Science, 38(1/2): 77–85. https://doi.org/10.1016/j.clay.2007.01.007 |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |