Open access peer-reviewed chapter

Modeling Antecedent Soil Moisture to Constrain Rainfall Thresholds for Shallow Landslides Occurrence

By Maurizio Lazzari, Marco Piccarreta, Ram L. Ray and Salvatore Manfreda

Submitted: February 3rd 2020Reviewed: May 5th 2020Published: August 14th 2020

DOI: 10.5772/intechopen.92730

Downloaded: 667


Rainfall-triggered shallow landslide events have caused losses of human lives and millions of euros in damage to property in all parts of the world. The need to prevent such hazards combined with the difficulty of describing the geomorphological processes over regional scales led to the adoption of empirical rainfall thresholds derived from records of rainfall events triggering landslides. These rainfall intensity thresholds are generally computed, assuming that all events are not influenced by antecedent soil moisture conditions. Nevertheless, it is expected that antecedent soil moisture conditions may provide critical support for the correct definition of the triggering conditions. Therefore, we explored the role of antecedent soil moisture on critical rainfall intensity-duration thresholds to evaluate the possibility of modifying or improving traditional approaches. The study was carried out using 326 landslide events that occurred in the last 18 years in the Basilicata region (southern Italy). Besides the ordinary data (i.e., rainstorm intensity and duration), we also derived the antecedent soil moisture conditions using a parsimonious hydrological model. These data have been used to derive the rainfall intensity thresholds conditional on the antecedent saturation of soil quantifying the impact of such parameters on rainfall thresholds.


  • landslides
  • soil saturation
  • geomorphology
  • hydrogeological risk
  • Basilicata

1. Introduction

Rainfall-induced shallow landslides are critical issues of scientific and societal interest, causing billions of euros in damages and thousands of deaths every year [1]. A large number of studies investigated the functional relationship between rainfall characteristics and landslide events [2]. One of the main results is the definition of empirical rainfall thresholds associated with the triggering of the shallow landslide, such as total event rainfall, intensity-duration, event-duration, and event-intensity thresholds ([3] and reference therein) [4, 5]. However, these approaches lead to a limited understanding of the geomorphological process and, if used for warning purposes, they can produce a large number of false positives alarms [6]. In fact, rainfall thresholds approach evaluates only the amount of cumulated rainfall and it neglects the primary role of other vital parameters, such as evapotranspiration, soil moisture, rainfall infiltration, soil porosity, and permeability.

In order to consider predisposing hydrological factors on empirical threshold calculation, recent studies have focused on the role of the antecedent daily rainfall in landslides triggering [7, 8, 9, 10, 11, 12]. These approaches have found a strong relationship between the hourly rainfall data triggering landslides and the initial soil moisture contributing to improving the predictive accuracy of empirical thresholds. Those results have also stimulated a critical revision of the intensity/duration thresholds in the last few years [6, 13, 14, 15]. In particular, Bogaard and Greco [6] introduced the cause-trigger concept for defining hydro-regional thresholds for predicting landslide occurrence, also suggesting taking into consideration the slope water balance. Starting from this new perspective, we aim to contribute to this discussion by evaluating the correlation between antecedent soil moisture conditions and rainfall intensity during shallow landslide events. In particular, we would like to explore better how much the initial saturation degree of soil affects the intensity/duration (I/D) relationships in landslide prediction. For this purpose, it is very important to use reliable databases in the literature or otherwise build a specific one.

There are many soil moisture datasets that have been successfully used to calibrate and validate catchment or watershed scale models of infiltration, soil-moisture storage, and in some ways, even to examine the first landslide trigger [16, 17, 18, 19].

In this chapter, we addressed this issue by reconstructing and leveraging a dataset of 326 landslide events that occurred in the Basilicata region (southern Italy, Figure 1 , and Appendix), from January 2001 to March 2018. For each georeferenced landslide, we derived the rainfall event characteristics and antecedent soil moisture conditions using a parsimonious physically-based distributed model applied at the regional scale with a spatial resolution of 200 m and a daily and hourly time scale. This approach allowed us to reconstruct all of the main forcing factors that may have produced a change in the slope stability and to detect the impact of antecedent soil moisture on the rainfall intensity/duration relationship. The numerical simulation has been needed to reconstruct the antecedent soil moisture values not available for the whole study area.

Figure 1.

Geographical distribution of the weather stations and landslide events for the study area. The graph in the inset shows the monthly distribution of landslides in Basilicata from 2001 to 2018.


2. Data and methods

This study was carried out within a research agreement with the Civil Protection of the Basilicata region, which supported in part the reconstruction of the list of landslide events used for the analysis. The database was constructed with the primary aim of creating an updated description of the most recent landslides and the associated rainfall events. Therefore, the present section will be devoted to the description of the study area, the methodology adopted to build the database, and the modeling approach used to reconstruct the antecedent soil saturation conditions.

2.1 Study area

Basilicata is a region of southern Italy covering an area of 9.992 km2 characterized by different topographical and geomorphological contexts, landscape types (47% mountains, 45% hillocks, and 8% plains) and geolithological conditions. The north-western and south-western regions are characterized by mountain landscapes (southern Apennines) with significant elevations of the relief (between 1300 and 2000 m of altitude) and steep slopes, particularly where Mesozoic successions (dolomite and siliceous limestones) outcrop. The eastern region shows a hilly landscape characterized by soft shapes or tabular hills (alternating ridges and valleys in conglomeratic sandstone—clayey—marly), usually with low gradients of the slopes, often modeled in foredeep Plio—Pleistocene units with clayey dominant [20, 21].

Precipitation values are typical of the Mediterranean, with distinct dry and wet seasons [22]. Higher precipitation totals occur during the last autumn-winter period when landslides and floods usually take place (more than 70%). A near real-time hydrometeorological network covers the territory uniformly with a density of one station every 80 km2. It has been operating over a time interval of about 70 years, providing temperature and precipitation data at the resolution of 10 minutes.

2.2 Landslide and rainfall data

Based on detailed bibliographical research [23, 24, 25], which explored all available sources including national and local newspapers and journals, Internet blogs, and the scientific and technical literature, we have collected a database of 326 shallow landslide events (landslide event is a single landslide) from January 2001 to March 2018.

The information collected and stored in the inventory includes ( Figure 1 ):

  • accurate or approximate location of the landslide event;

  • accurate or approximate time, date, or period of the failures;

  • rainfall conditions that resulted in slope failures collected from the nearest rain gauge, including the total event rainfall, the rainfall duration, the mean rainfall intensity, and the antecedent rainfall for 2001–2018;

  • landslide type;

  • a generic description of the lithology.

In addition to this data that is also reported in Appendix in a tabular format, meteorological data and the output of the hydrological model have been used for the subsequent elaborations. In particular, hourly rainfall and temperature data were obtained from the rain gauges of the Civil Protection of the region. The hydrological model proposed on a regional scale considers homogeneous soil moisture conditions in the space and the first meters of depth in the areas affected by each landslide identified in our database.

The regional pedological map is depicted in Figure 2 with the spatial distribution of landslides ( Figure 2 ). This maps provides a nested description of soil classes that indentifies four regions at the first level (soil map of Italy, scale 1: 5,000,000), the 15 provinces, and 75 soil units (scale 1: 250,000). Based on the pedological characteristics of the regions, it was observed that the highest number of landslides (56 landslides) occurred in the soil province n.6. It is also worthy to mention a high number of events occurred on the soil unit 12.4 (33 landslides) and 10.2 (21 landslides). These last two soil units correspond to:

  • 12.4—hilly clay soils with steep slopes, badlands, intended for grazing or arable land, with low permeability (Vertic Haploxerepts; Inceptisol);

  • 10.2—hilly sandy-conglomerate soils, intended for pasture, vineyards or shrubs (Typic Xerorthents; Inceptisol).

Figure 2.

Pedological regions and shallow landslides distribution over the Basilicata region.

The number of event recorded in each soil unit is described in the histogram of Figure 3 .

Figure 3.

Histogram with the distribution of the number of landslides in the various regional soil units. Red circles, units with multiple landslides; black dotted rectangle, landslides included in unit 6.

2.3 Reconstruction of rainfall events

The rainfall duration (D) was determined by measuring the time between the moment of the beginning of each rainfall event, which triggered a shallow landslide, considered in the database, and rainfalls ending time. The rainfall ending time was taken to coincide with the time of the last rainfall measurement of the day when the landslide occurred. As suggested by Brunetti et al. [26], the starting time was considered a minimum period without rain (a 2-day period without rainfall was selected for late spring and summer, May–September, and a 4-day period without rainfall was selected for the other seasons, October–April) to separate two consecutive rainfall events. Once the duration of the rainfall event was established, the corresponding rainfall mean intensity I (mm h−1) was calculated dividing the cumulated (total) rainfall (mm) in the considered period by the length of the rainfall period (hours). The full list of events is given in the Appendix of the present chapter (Table 1—Appendix). In recent studies, authors [27, 28, 29] have used an approach that provides the seasonality criterion (April-October for the “dry/warm” season and November-March for the “wet/cold” season) to calculate the rainfall events. In this chapter, the proposed method is different from that proposed by Peruccacci et al. [29], because the saturation value and condition are a parameter regardless of seasonality. It provides a more detailed parameter, overcoming the possibility that in the same season, it can have more dry or wet phases.

2.4 Modeling soil water content

Although antecedent soil moisture can be obtained by in-situ measurements at a point scale, measurements on a regional scale are time-consuming and expensive. Recently, more information is available from satellite data, but they are too coarse to provide local estimates of soil water content on a specific landslide [30]. Thus, we used the hydrological model AD2 to describe the temporal evolution of soil water content over the entire Basilicata region using a distributed approach at 240 m spatial resolution.

The AD2 model is a 1D model capable of describing the soil water budget along the vertical direction, but its physically based nature allows to associate physical characteristics such as soil texture, land cover, and mean slope to each pixel/location that affects the model parametrization.

The model parameters were obtained from physical maps such as national and regional pedological maps of Italy and Basilicata [31], the III level of the CORINE Land Cover map [32], and the Shuttle Radar Topography Mission Digital Elevation Model (SRTM-DEM) extracted from HydroSHEDS (

The model was run at 1 h temporal resolution using rainfall and temperature data derived from the rainfall network of the Civil Protection for the period January 1, 2001 to March 28, 2018 [32].

This approach is straightforward and can be easily replicated elsewhere after a simple calibration against the local soil moisture and landslide datasets. It must be stated that obtained values can be affected by several errors due to model structure, parametrization, and climatic data, but at present, such an approach offers a realistic description of the expected relative saturation of the soil providing a synthesis of the state of the system according to the available information on soil texture, antecedent rainfall, and evolution of temperatures. Moreover, several evidences suggesting that the use of a physically based approach allows obtaining more robust outputs [33, 34].

2.4.1 AD2 model structure

Model simulations carried out using at least 1 year of rainfall and temperature data recorded before each landslide event to reach a reliable estimate of the relative soil water content at the date of the considered event. AD2 [34] provides a hydrological prediction that considers several hydrological components such as infiltration, surface runoff, sub-surface runoff, deep percolation, and evapotranspiration. Soil water balance is described by the following Equation [35]:


where: St is the basin soil water content at the generic instant of time t, which represents a key variable of the model influencing runoff production, leakage, and evapotranspiration; It is the infiltration; Rout,t is the sub-surface runoff production; Lt is the leakage to the groundwater; and ET is the actual evapotranspiration.

The infiltration is derived from the difference between the rainfall amount, Pt, and the surface runoff, Rt, at time t (mm):


Runoff is calculated using the equation proposed by De Smedt et al. [36], which takes into account the potential saturation of the soil:


where, Smax is the maximum water storage capacity of the bucket, Pc is the critical rainfall producing the surface soil saturation, and C the default runoff coefficient that is parameterized as a function of soil type, soil cover, and slope [37].

The sub-surface runoff production is assumed to be a linear function of the soil water content above the field capacity reference parameter:


where Sc is the threshold water content for sub-surface flow production, assumed here equal to 0.6 Smax, and c is the sub-surface coefficient, which is generally assumed 0.05.

The evapotranspiration is assumed to be a bi-linear function of the soil content and potential evapotranspiration. It may be described by the following equation:


where EP is the potential evapotranspiration, 0.75Sc is an estimate of the water content at which the stomata closure starts to reduce the evapotranspiration.

Leakage is computed using the expression derived by Manfreda et al. [38] integrating the power-law function of leakage by Eagleson [39] over a time-step ∆t:


where Lt is the groundwater recharge in ∆t, Ks is a parameter that interprets the soil permeability at saturation, and β is a dimensionless exponent.

It must be clarified that all the parameters mentioned in the model equations reported above can be estimated using the existing literature values that associate this parameter to physical features of the area such as soil texture, land use and mean slope using [37, 40, 41].

2.5 Rainfall thresholds

To determine rainfall thresholds for shallow landslide occurrence, we adopted the Frequentist method [26]. The threshold curve is assumed to follow a power law:


where, I is the rainfall mean intensity (mm h1), D is the rainfall event duration (h), α is the intercept, and β defines the slope of the power law function. Empirical data were log-transformed to calculate the best-fit line by means of a linear equation log(I) = log(α) − β log(D), equivalent to that described above.

Following the methods adopted in previous studies [9, 12, 15], we identified the rainfall events associated with each landslide event and the corresponding degree of soil saturation at the starting time of each event. Including this additional information in the database, it was possible to explore its role in the general behavior of the rainfall events triggering landslides under different initial conditions.


3. Results and discussion

The comparison between the rainfall intensity and the relative saturation before each event is depicted in Figure 4 . Figure 4 provides the temporal evolution of the rainfall and relative soil saturation of three different sites (Lauria, Vietri di Potenza and Pisticci; see Appendix) characterized by different lithological conditions during the period from January 1, 2009 to December 31, 2015. This window was extracted from the model simulation to emphasize the seasonal dynamics of soil moisture over the considered sites. Such a seasonality is clearly one of the motivations to conduct this study because such a dynamic strongly affects the hydraulic processes in the soil profile.

Figure 4.

Daily rainfall (blue) and simulated daily soil degree saturation (red) at (a) Lauria, (b) Vietri, and (c) Pisticci from January 1, 2009 to December 31, 2016. Dark stars represent the data of the occurrence of shallow landslide events in the monitored areas.

It is noticed that most of the different landslide events (reported in the graph with a dark star) occurred after significant rainfall amounts and relatively high or moderate soil saturation degree. When the same rainfall amounts occurred in conditions of low antecedent soil moisture content, they have not produced shallow landslides. This finding aligns with the previous studies [7, 8, 9, 10, 11, 12, 13, 14, 15, 42].

This preliminary plot shows that there is an interplay between the antecedent soil moisture conditions and the amounts and the duration of the triggering rainfall. Moreover, it appears how the same degree of soil saturation and rainfall I/D conditions do not necessarily produce the same effects in different geopedological regions.

The role of the antecedent soil moisture condition on the triggering rainfall intensity is clearly shown in Figure 5 , where the rainfall intensity/duration has been plotted against the simulated antecedent soil saturation of each landslide event. This graph was developed following the trigger-cause concept of Bogaard and Greco [6] and highlights the role of both rainfall dynamics and antecedent soil moisture on the slope stability.

Figure 5.

Mean rainfall intensity/duration and the simulated initial degree of saturation for the 326 landslide events in Basilicata region (southern Italy) from 2001 to 2018.

In fact, there is a clear reduction of the rainfall intensity needed to trigger a landslide with the increase of the antecedent soil moisture. In this graph, the data grouped in the function of the rainfall duration trying to explore also the role of this additional parameter on the process. It is observed that the rainfall dynamics also matter, being shorter rainfall events more sensitive to the antecedent soil moisture respect to, while more extended events are less influenced by such parameter.

Similarly, previous studies [7, 8, 12, 43] also found a linearly decreasing trend between the mean rainfall intensity and the initial soil moisture conditions. The slope of the regression functions derived from a different subset of our database changes based on the relative duration of the rainfall events. It is higher for rainfall durations lower than 48 h, while the function becomes almost independent from the relative saturation when rainfall events have longer durations (more than 48 h). This is probably due to the nature of the long-lasting rain events, which are often characterized by a high total amount of rainfall. Results in high values both of the initial saturation degree and of low rainfall intensity that is averaged over longer periods. It must be clarified that the relative degree of saturation has been referred to as the starting time of the triggering rainfall event.

Figure 6 depicts a clear picture of the dependence between mean rainfall intensity of event of different durations and the antecedent soil moisture, where the rainfall intensity values of the 326 investigated events are associated to the simulated soil saturation degree using a color scale (from blue to yellow starting from lower to higher values of degree of saturation). This graph clearly shows that higher amounts of rainfall intensity are observed in correspondence to lower values of soil saturation and vice-versa. This tendency is not always consistent due to the presence of several spurious data relative to the occurrence of extraordinarily wet events, which resulted in both landslides and floods.

Figure 6.

Rainfall intensity as a function of the duration of the triggering rainfall events for the 326 landslide events recorded in Basilicata region (southern Italy) during the period 2001–2018. Each event is associated with a color that represents the simulated antecedent degree of saturation, whose range is given in the color bar on the right (ranging from 0 to 1). We also included the regression lines estimated for the two groups of events selected based on the antecedent soil saturation conditions. The solid line represents the regression function obtained using the observations with soil degree saturation lower than 0.70, while the dotted line represents the regression function obtained using the observations with degree soil of saturation equal or higher than 0.70.

To evaluate the role of degree of soil saturation on the regional mean rainfall intensity/duration function, we have identified two distinguished sub-samples based on the antecedent soil moisture conditions of each event. The two groups were distinguished using a sensitivity analysis, exploiting different antecedent soil saturation values. The selection was made using a subjective selection that tried to identify the most diverse groups of landslides using a given threshold of soil saturation. Therefore, we determined mean rainfall intensity/duration functions (rainfall thresholds) under middle-low antecedent soil moisture conditions that seemed to those that responded better to the data considered (soil degree saturation lower than 0.70), and moderate to high antecedent soil moisture conditions (soil degree saturation equal or higher than 0.70). In this way, it was possible to derive critical rainfall threshold functions conditional on the antecedent soil moisture conditions.

The two functions plotted in the graph ( Figure 6 ), which has significantly different slopes. This implies that they must cross somewhere in the space of rainfall intensities and event duration. In the present case, we observed that they cross in a point corresponding to the duration of about 200 h. At such duration, the impact of antecedent soil water content becomes not relevant, and this part of the curve should not be considered.

The proposed approach allows taking into account both rainfall characteristics (intensity and duration) and the antecedent soil moisture state in a specific study area, contributing to foresee a landslide event.

Of course, a methodology like this should be evaluated widely, also taking into consideration the ability of the method to distinguish between true and false alarms. Unfortunately, this field-test is challenging to be implemented in a region like Basilicata with a low density of population (as single possible observators), where a lot of landslide events are not reported or are missing.


4. Final remarks

We have explored the role and effects of antecedent soil moisture conditions on rainfall I/D thresholds triggering shallow landslides by using a dataset built for a region of southern Italy and a distributed modeling approach. By combining rainfall events data with the simulated antecedent soil moisture conditions, it was possible to derive I/D relationships, which can be used to discriminate the triggering conditions for landslides better.

Two distinct degree of soil saturation values [S < 0.7 and S ≥ 0.7] were identified to distinguish different classes of events. Such soil moisture conditions led to two distinct populations of events that identified statistically significantly different rainfall threshold functions. Our results are consistent with those found in the most recent studies on this topic, reinforcing the idea that simulated soil moisture provides better metrics than antecedent rainfall for the predisposing factors of landslide initiation.

Finally, a forthcoming extension of this research will aim to carry out a local downscaling to define the relations between I/D and the degree of soil saturation in the smallest territorial contexts characterized by the same climatic and lithotechnical conditions, in which the landslides inserted in our database have developed.

Moreover, it is also important to note that the proposed description of the landslide event may undoubtedly support the development of further studies and models for landslide prediction. In fact, the main results obtained in the present study are the fact that the information about the antecedent relative saturation of the soil may help to distinguish the dynamics of the process better. Therefore, it would be a good practice to include such parameters in all landslide database. This can happen with the support of remote sensing techniques that also allow deriving root zone soil moisture over large areas [10, 41, 44].



This work was carried out within a scientific agreement between the Civil Protection Department of Basilicata, the Interuniversity Consortium for Hydrology (CINID), and the University of Basilicata to the start-up the Basilicata Hydrologic Risk Center.


IDMunicipalityDateUTM NUTM EH (mm)D (h)I (mm/h)Antecedent soil saturationWeather stationSources
1Rotondella14/01/20014,447,838,6630,012,0186,826,07,180,40Nova Siri SALEvalmet web site web site web site
2Montalbano Jonico20/01/20014,461,333,2632,500,766,616,04,160,48Montalbano SALCivil Protection
3Pisticci20/01/20014,472,103,8633,501,383,634,02,460,20Pisticci Scalo SALEvalmet web site
4Rotondella21/01/20014,447,722,3629,857,388,652,01,700,78Nova Siri SalEvalmet web site
5Tursi21/01/20014,456,520,6624,987,786,227,03,190,70Tursi SIEvalmet web site
6San Fele09/03/20024,518,711,1545,705,923,611,02,150,59San Fele PCCivil Protection
7Lagonegro12/01/20034,441,050,6565,797,2148,2140,01,060,89Lagonegro PCCivil Protection
8Acerenza25/01/20034,516,566,8579,515,543,043,01,000,20Acerenza SALCivil Protection
9Nova Siri25/01/20034,444,982,6631,308,480,056,01,430,91Nova Siri SALCivil Protection
10Pisticci25/01/20034,472,200,4631,782,954,248,01,130,82Pisticci Scalo SALLa Nuova Basilicata magazine
11Castronuovo di Sant’Andrea04/02/20034,449,625,0600,976,533,434,00,980,90Roccanova PCCivil Protection
12Muro Lucano08/02/20034,512,107,1540,718,1105,6172,00,610,87Muro Lucano PCCivil Protection
13Montescaglioso09/09/20034,490,159,8640,165,821,24,05,300,11Montescaglioso SALCivil Protection
14Venosa10/09/20034,535,319,9569,252,535,08,04,380,28Venosa SALCivil Protection
15Craco12/12/20034,467,134,0623,760,9117,678,01,510,24Craco PCPiccarreta et al., 2004
16Montescaglioso26/07/20044,490,946,3640,686,531,423,01,370,16Montescaglioso SALII Quotidiano magazine
17Nova Siri26/07/20044,445,645,0631,600,064,04,016,000,13Nova Siri SALCivil Protection
18Valsinni26/07/20044,448,638,8624,031,986,66,014,430,13Nova Siri SALCivil Protection
19Melfi20/09/20044,538,361,1555,130,7119,481,01,470,09MelfiCivil Protection
20Montalbano Jonico13/11/20044,460,236,3634,365,167,233,02,040,23Montalbano SALCivil Protection
21Montescaglioso13/11/20044,491,198,4641,477,5126,633,03,840,17Montescaglioso SALCivil Protection
22Pisticci13/11/20044,470,264,9643,085,094,634,02,780,25Pisticci da Castelluccio SALCivil Protection
23Tricarico13/11/20044,498,622,9582,231,546,231,01,490,32Albano di Lucania PCLa Gazzetta del Mezzogiorno magazine
24Tito24/01/20054,493,939,0556,898,440,017,02,350,72Satriano di Lucania
25Nemoli26/01/20054,435,028,2568,166,976,247,01,620,90Nemoli SALCivil Protection
26San Fele22/02/20054,518,910,4546,690,877,080,00,960,97San Fele PCCivil Protection
28Castronuovo di Sant’Andrea23/02/20054,449,641,7600,766,226,030,00,870,64Roccanova PCCivil Protection
30Tito24/02/20054,492,615,5557,165,560,855,01,110,86Satriano di Lucania
32Rionero in Vulture26/02/20054,527,555,0558,531,614,26,02,370,72Venosa
33Potenza26/02/20054,498,664,2567,834,764,498,00,660,87Potenza PCLa Gazzetta del Mezzogiorno magazine
34Potenza26/02/20054,504,521,5572,376,664,498,00,660,87Potenza PCCivil Protection
36Gallicchio27/02/20054,460,528,9596,783,321,012,01,750,83Guardia Perticara SALCivil Protection
37Laurenzana01/03/20054,482,440,8578,878,486,6148,00,590,93Laurenzana SALCivil Protection
38Pietrapertosa02/03/20054,485,954,8589,868,444,623,01,940,73Campomaggiore SALCivil Protection
40Barile29/03/20054,533,072,0557,767,625,829,00,890,64Venosa SALCivil Protection
41Accettura07/06/20054,483,267,3598,029,917,45,03,480,23San Mauro Forte PCCivil Protection
42Terranova del Pollino24/02/20064,426,066,5610,796,479,678,01,020,72Terranova del Pollino PCCivil Protection
43Bernalda28/02/20064,474,473,5648,787,644,011,04,000,72Bernalda SALLa Gazzetta del Mezzogiorno magazine
44Grottole28/02/20064,495,569,9617,180,795,4176,00,540,67Grottole da SerreLa Gazzetta del Mezzogiorno magazine
45Pisticci28/02/20064,533,072,0557,767,633,815,02,250,67Torre Accio PCLa Gazzetta del Mezzogiorno magazine
46Calvello12/03/20064,479,726,4575,486,350,629,01,740,92Laurenzano PCBasin Authority of Basilicata (AdB)
47Montalbano Jonico12/03/20064,472,188,9640,718,037,856,00,680,64Tursi SALEvalmet web site
48Rionero in Vulture13/03/20064,529,892,8556,341,5114,770,01,640,91MelfiCivil Protection
49Venosa13/03/20064,460,626,0633,605,6113,262,01,830,84Venosa SALCivil Protection
50Corleto Perticara23/03/20064,475,673,7588,722,543,643,01,010,83Guardia Perticara SALAdB
51Ripacandida24/03/20064,529,316,2560,944,230,558,00,530,77Venosa SALCivil Protection
52Picerno27/03/20064,499,289,0554,063,132,89,03,640,91Balvano PCCivil Protection
53Trecchina26/09/20064,430,915,4567,168,1133,072,01,850,63TrecchinaCivil Protection
54Rivello23/10/20064,533,947,8566,654,7140,250,02,800,35Nemoli SALIFFI Project ISPRA CNR IBAM
55Maratea19/12/20064,438,301,0564,922,4144,655,02,630,74Maratea PCinfocilento
56Maratea04/04/20074,473,927,4630,747,231,416,01,960,91Maratea PCinfocilento
57Tito25/11/20084,429,377,2561,850,977,4120,00,650,43Picerno PCCivil Protection
58Grassano11/12/20084,492,851,3557,094,779,416,04,960,45Matera PCLa Gazzetta del Mezzogiorno
59Calvello05/01/20094,480,624,6572,077,335,262,00,570,85Laurenzano PCCivil Protection
60Lagonegro06/01/20094,502,711,0621,802,2109,865,01,690,88Lagonegro PClucanianet
61Grottole13/01/20094,469,982,7634,601,887,895,00,920,59Grottole da SerreII Quotidiano
62Montescaglioso13/01/20094,489,561,2641,250,176,695,00,810,52Montescaglioso SALLa Gazzetta del Mezzogiorno
63Pisticci13/01/20094,487,771,2600,527,1105,2114,00,920,62Pisticci da Castelluccio SALCivil Protection
64Pisticci13/01/20094,495,207,5617,127,3104,6113,00,930,62Pisticci Scalo SALLa Gazzetta del Mezzogiorno
65Potenza13/01/20094,499,028,2571,863,417,620,00,880,94Potenza PCCivil Protection
66Laurenzana14/01/20094,477,838,6584,070,938,835,01,110,95Laurenzana SALCivil Protection
67Acerenza23/01/20094,515,988,0578,994,532,028,01,140,58Acerenza SALCivil Protection
68Maratea28/01/20094,441,638,3566,470,6295,2185,01,600,93Maratea PCLa Siritide website
69Montalbano Jonico06/03/20094,460,493,9632,869,239,234,01,150,74Montalbano SALCivil Protection
70Pisticci06/03/20094,429,791,9561,758,040,634,01,190,85Torre Accio PCEvalmet web site
71Tursi06/03/20094,457,119,8624,774,744,433,01,350,82Tursi SALCivil Protection
73Gallicchio20/03/20094,528,878,0562,300,726,212,02,180,67Aliano SALCivil Protection
74Ripacandida26/03/20094,528,798,8561,165,222,836,00,630,79Venosa SALCivil Protection
75Tricarico24/04/20094,524,102,2555,355,775,0135,00,560,90Albano di Lucania PCCivil Protection
76San Martino D’Agri28/04/20094,455,394,2587,277,722,621,01,080,85Sarconi SALLa Gazzetta del Mezzogiorno
77Vietri di Potenza22/10/20094,500,015,6596,374,911,69,01,290,68VietriQuotidiano del sud, Metauronews
78San Severino Lucano18/12/20094,430,832,7596,722,012,28,01,530,60Viggianello SALCivil Protection
79San Chirico Raparo07/02/20104,448,987,6591,663,129,05,05,800,83Castelsaraceno PCLa Gazzetta del Mezzogiorno
80Maratea11/02/20104,427,557,0562,256,556,676,00,740,96Maratea PCCivil Protection
81Viggianello13/02/20104,424,622,3591,954,8145,8184,00,790,93Viggianello SALCivil Protection
82Latronico20/02/20104,472,103,8633,501,3112,2124,00,900,85Castelsaraceno PCII Quotidiano magazine
83Tursi11/10/20104,494,906,8541,098,215,811,01,440,22Tursi SITursi
84Ferrandina02/11/20104,485,211,8627,576,363,27,09,030,45Ferrandina SALCivil Protection
85Grottole02/11/20104,493,102,4615,427,5115,27,016,460,46Grottole da SerreCivil Protection
86Matera02/11/20104,502,417,4634,533,061,89,06,870,39Matera PCCivil Protection
87Montescaglioso02/11/20104,454,988,6623,153,845,212,03,770,37Montescaglioso SALII Quotidiano magazine
88Pisticci02/11/20104,491,414,3544,109,273,410,07,340,44Pisticci Scalo SALCivil Protection
89Rivello02/11/20104,437,163,0564,328,338,410,03,840,82Nemoli SALCivil Protection
90Salandra02/11/20104,486,232,1612,353,1108,06,018,000,32San Mauro Forte PCCivil Protection
91Tursi03/11/20104,456,064,4625,339,962,311,05,660,39Tursi SALCivil Protection
92Melfi10/11/20104,491,130,5640,684,355,557,00,970,59MelfiII Quotidiano magazine
93Potenza11/11/20104,539,263,4551,961,478,890,00,880,57Potenza PCLa Gazzetta del Mezzogiorno magazine
94Lauria22/11/20104,504,815,2572,162,3169,8140,01,210,87Nemoli SALLa Gazzetta del Mezzogiorno magazine
95Muro Lucano02/12/20104,440,667,8573,120,0135,4250,00,540,79Muro Lucano PCLa Gazzetta del Mezzogiorno magazine
96Rivello03/12/20104,512,300,7536,385,6248,2271,00,920,90Nemoli SALII Quotidiano del sud magazine
97Castelluccio Inferiore03/01/20114,428,643,1583,828,850,841,01,240,86Viggianello SALCivil Protection
98Alianello19/02/20114,437,455,5564,407,936,810,03,680,57Aliano SALANAS (National Istitution for Highways)
99Armento19/02/20114,462,213,4588,308,383,452,01,600,83Guardia Perticara SALCivil Protection
100Bernalda19/02/20114,474,641,9641,273,320,010,02,000,55Bernalda SALCivil Protection
101Montalbano Jonico19/02/20114,461,782,0633,367,928,417,01,670,48Montalbano SALCivil Protection
102Pisticci19/02/20114,456,984,3610,237,729,049,00,590,60Pisticci Scalo SALEvalmet web site
103Tursi19/02/20114,457,443,9626,287,330,824,01,280,39Tursi SALCivil Protection
104Valsinni20/02/20114,447,737,2622,905,022,816,01,430,59Nova Siri SALCivil Protection
105Cancellara01/03/20114,509,339,7577,969,242,814,03,060,93San Nicola D’Avigliano PCCivil Protection
106Ferrandina01/03/20114,485,235,5624,000,099,019,05,210,70Ferrandina SALCivil Protection
107Matera01/03/20114,501,551,8634,766,1103,023,04,480,58Matera Nord SALCivil Protection
108Teana01/03/20114,442,436,7598,621,864,221,03,060,90Episcopia PCCivil Protection
109Bernalda02/03/20114,474,369,9642,163,4102,421,04,880,58Bernaida SALCivil Protection
111Grassano02/03/20114,499,277,9609,377,8149,719,07,880,66Grassano SALEvalmet web site
112Irsina02/03/20114,456,172,0625,292,089,421,04,260,19Santa Marla d’Irsi
113Montalbano Jonico02/03/20114,471,789,5633,568,6153,624,06,400,52Montalbano SALEvalmet web site
114Pisticci02/03/20114,449,746,0630,633,381,418,04,520,65Pisticci Scalo SALII Quotidiano, Evalmet web site
115Rotondella02/03/20114,518,058,7611,730,4126,617,07,450,65Nova Siri SALCivil Protection
116Tricarico02/03/20114,496,864,3597,934,131,415,02,090,82Albano di Lucania
117Tursi02/03/20114,460,225,2632,086,0152,018,08,440,44Tursi SALEvalmet web site
118Valsinni02/03/20114,472,089,5632,234,9129,218,07,180,65Nova Siri SALEvalmet web site
119Laurenzana03/03/20114,478,608,5582,713,681,663,01,300,90Laurenzana SALEvalmet web site
120Lauria05/03/20114,432,403,8572,113,397,8114,00,860,84Nemoli SALCivil Protection
121Grottole05/05/20114,447,270,2625,680,962,8102,00,620,94Grottole da Castellanoprovincia di Matera
122Laurenzana (riatt.)05/05/20114,481,944,5581,225,0149,8210,00,710,78Laurenzana SALANAS
123Bella07/10/20114,512,353,3546,253,894,25,018,840,17Bella CasaliniCivil Protection
124Muro Lucano08/10/20114,511,194,6540,805,5127,66,021,270,07Muro Lucano PCLa Gazzetta del Mezzogiorno magazine
125Matera06/11/20114,502,097,8635,438,534,22,017,100,10Matera PCCivil Protection
126San Fele06/12/20114,515,972,5551,039,623,830,00,790,44San Fele PCCivil Protection
127Latronico15/11/20114,437,998,4586,199,865,044,01,480,89Episcopia PCCivil Protection
128Stigliano25/12/20114,473,739,4605,248,146,68,05,830,13Stigliano SALCivil Protection
129Lauria06/01/20124,431,454,0572,485,441,646,00,900,82Nemoli SALCivil Protection
130Rivello (2)20/01/20124,436,157,6558,533,016,610,01,660,80Nemoli SALCivil Protection
131Savoia di Lucania04/02/20124,490,321,5547,596,157,279,00,720,37VietriCivil Protection
132Craco08/02/20124,470,541,6622,549,937,424,01,560,38Craco PCCivil Protection
133Rapone10/02/20124,521,844,9542,278,720,117,01,180,53San Fele PCCivil Protection
134Montemurro11/02/20124,461,336,3583,827,5118,6254,00,470,54Grumento NovaCivil Protection
135Avigliano12/02/20124,509,076,7560,722,329,839,00,760,61Avigliano PCCivil Protection
136Bernalda23/02/20124,475,260,0643,993,152,442,01,250,48Bernalda SALCivil Protection
137Castronuovo di Sant’Andrea23/02/20124,448,673,1604,075,095,450,01,910,48Roccanova
139Montalbano Jonico23/02/20124,461,399,7632,113,046,843,01,090,51Montalbano SALCivil Protection
140Tursi23/02/20124,456,338,6624,326,053,843,01,250,63Tursi SALCivil Protection
141Pietrapertosa24/02/20124,440,620,5607,006,839,239,01,010,61Campomaggiore SALCivil Protection
142Vietri di Potenza08/03/20124,495,336,2543,776,210,07,01,430,50VietriQuotidiano del sud, Metauronews
143Avigliano09/03/20124,507,355,3561,591,131,418,01,740,71Avigliano PCCivil Protection
144Rivello14/04/20124,436,142,6554,613,5118,030,03,930,71Nemoli SALCivil Protection
145Rapone18/04/201245,873,9542,457,050,6KO0,560,76San Fele PCCivil Protection
146Avigliano20/04/20124,509,561,9561,009,020,433,00,620,76Avigliano PCCivil Protection
147Rivello21/04/20124,435,386,6565,318,9256,8192,01,340,71Nemoli SALCivil Protection
148Lauria06/06/20124,432,952,2570,399,658,211,05,290,76Nemoli SALCivil Protection
149Teana23/06/20124,442,695,5598,168,929,63,09,870,30Episcopia PCCivil Protection
150Lavello01/09/20124,545,949,2568,245,920,84,05,200,02Lavello SALCivil Protection
151Venosa02/09/20124,460,329,4633,421,4141,032,04,410,08Venosa SALCivil Protection
152Castelluccio Inferiore (3)03/10/20124,427,492,7587,471,19,02,04,500,12Viggianello SALCivil Protection
153Rotonda29/10/20124,423,198,3588,915,1111,228,03,970,27Rotonda SALCivil Protection
154Campomaggiore20/11/20124,491,247,0590,935,166,8106,00,630,24Campomaggiore SALCivil Protection
155Pisticci20/11/20124,533,376,1575,381,273,867,01,100,54Pisticci Scalo
156Roccanova20/11/20124,453,378,3603,847,396,290,01,070,30Roccanova PCCivil Protection
157Vietri di Potenza20/11/20124,494,560,8543,083,927,029,00,930,44VietriQuotidiano del sud, Metauronews
159Barile08/12/20124,532,258,7556,671,826,112,02,180,46Venosa SALCivil Protection
160San Severino Lucano17/01/20134,430,496,6596,772,9175,6177,00,990,85Viggianello SALCivil Protection
161Lauria18/01/20134,434,754,0571,329,9268,0180,81,490,79Nemoli SALCivil Protection
162Savoia di Lucania18/01/20134,491,704,0544,971,087,693,00,940,68VietriCivil Protection
163Vietri di Potenza18/01/20134,432,069,0573,009,387,693,00,940,73VietriQuotidiano del sud, Metauronews
164Sant’Angelo le Fratte19/01/20134,494,125,0541,429,199,6101,00,990,63Tito PCFonti Cronachistiche
165Lagonegro21/01/20134,488,383,1547,262,1266,8244,01,090,80Lagonegro PCLa Siritide
167San Severino Lucano03/02/20134,429,936,5596,946,028,226,01,080,90Viggianello SALCivil Protection
168Armento13/02/20134,462,461,3590,367,612,010,01,200,73Guardia Perticara SALCivil Protection
169Balvano13/02/20134,500,024,3543,479,734,431,01,110,74Balvano PCCivil Protection
170Avigliano24/02/20134,508,495,2559,778,818,427,00,680,95Avigliano PCCivil Protection
171Vietri di Potenza14/03/20134,437,619,1594,262,144,849,00,910,89VietriQuotidiano del sud, Metauronews
172Castelluccio Inferiore15/03/20134,428,429,2584,348,2136,0214,00,640,84Viggianello SALCivil Protection
173Lauria21/03/20134,495,266,6544,987,6339,2353,00,960,82Nemoli SALyoutube
174Castelluccio Inferiore10/04/20134,428,714,4584,450,112,23,04,070,83Viggianello SALCivil Protection
175Muro Lucano10/07/20134,510,677,3541,344,559,253,01,120,36Muro Lucano PCCivil Protection
176Vietri di Potenza21/07/20134,493,924,6541,919,013,84,03,450,32VietriQuotidiano del sud, Metauronews
177Accettura21/08/20134,428,008,9574,521,327,425,01,100,19Campomaggiore SALaccettura online
178Atella - Filiano21/08/20134,517,964,3559,520,943,65,08,720,21Atella PCCivil Protection
179Bernalda07/10/20134,474,073,6643,387,8190,456,03,400,08Bernalda SALQuotidiano del sud, Evilmet
180Montalbano Jonico07/10/20134,461,773,7634,506,484,22,902,900,10Montalbano SALCivil Protection
181Montescaglioso07/10/20134,490,286,3641,544,0135,235,03,860,07Montescaglioso SALCivil Protection
182Pisticci07/10/20134,487,593,1594,710,1105,657,01,850,11Torre Accio PCEvalmet web site
185Chiaromonte16/11/20134,433,677,5571,261,9238,2132,01,800,22Noepoli PCLa Siritide
186Pisticci16/11/20134,472,993,9631,724,0157,0135,01,160,24Pisticci Scalo SALCivil Protection
187San Fele22/11/20134,518,881,1545,411,7109,882,01,340,42San Fele PCCivil Protection
188Guardia Perticara (3)24/11/20134,468,838,7592,161,9103,6115,90,900,61Guardia Perticara SALCivil Protection
189San Severino Lucano24/11/20134,429,132,5594,345,3133,8100,01,340,58Viggianello
190Laurenzana26/11/20134,440,683,6606,559,589,094,00,950,61Laurenzana SALCivil Protection
191Valsinni26/11/20134,446,786,7622,424,8193,0115,01,680,25Nova Siri SALCivil Protection
192Miglionico30/11/20134,492,223,8627,675,220,08,02,500,48Ferrandina SALCivil Protection
193Chiaromonte01/12/20134,479,622,4582,489,765,025,02,600,85Episcopia PCFonti Cronachistiche
194Craco (7)01/12/20134,470,341,9623,096,0156,429,05,390,61Craco PCCivil Protection
195Gallicchio01/12/20134,489,127,2591,325,495,620,04,780,54Aliano SALCivil Protection
196Ginestra01/12/20134,531,394,8562,130,889,523,03,890,32Venosa SALCivil Protection
197Pomarico (4)01/12/20134,486,804,1631,164,0128,626,04,950,51Ferrandina SALCivil Protection
198Potenza01/12/20134,496,760,3571,166,463,225,02,530,60Potenza PCCivil Protection
199Savoia di Lucania01/12/20134,490,996,4546,572,9125,651,02,460,63VietriCivil Protection
200Tricarico01/12/20134,497,852,6597,122,7114,832,03,590,55Albano di Lucania PCCivil Protection
201Armento02/12/20134,449,866,2621,395,1120,057,02,110,81Guardia Perticara SALFonti Cronachistiche
202Bernalda02/12/20134,473,912,5643,362,6221,349,04,520,74Bernalda SALCivil Protection
203Cirigliano02/12/20134,472,564,9599,264,5162,056,02,890,59San Mauro Forte PCCivil Protection
204Colobraro02/12/20134,461,913,3596,895,9140,726,05,410,68Sinni a Valsinni SIemmenews
205Garaguso/Grassano02/12/20134,545,101,3565,137,4150,052,02,880,47Grassano SALLa Gazzetta del Mezz
206Grottole(3)02/12/20134,494,492,3616,732,9186,857,03,280,48Grottole da SerreCivil Protection
207Guardia Perticara02/12/20134,494,394,2605,039,5120,057,02,110,81Guardia Perticara SALCivil Protection
208Lavello02/12/20134,459,823,2599,087,0130,057,02,280,30Lavello SALFonti Cronachistiche
209Missanello02/12/20134,462,814,9590,380,8138,655,02,520,54Aliano SALFonti Cronachistiche
210Montalbano Jonico02/12/20134,457,687,7626,816,0174,828,06,240,66Montalbano SALCivil Protection
211Pietrapertosa02/12/20134,484,995,6589,793,9168,854,03v130,57Campomaggiore SALCivil Protection
212Pisticci02/12/20134,466,906,3594,785,7167,233,05,070,63Pisticci Scalo SALCivil Protection
213Rivello02/12/20134,436,644,0564,876,742,238,01,11088Nemoli SALCivil Protection
214Senise02/12/20134,445,683,3609,339,483,037,02,240,81Noepoli PCCivil Protection
215Accettura03/12/20134,488,048,3593,820,9211,458,03,640,57Campomaggiore SALLa Gazzetta del Mezzogiorno
216Accettura, Salandra03/12/20134,481,543,0598,406,7197,863,03,140,59San Mauro Forte PCLa Gazzetta del Mezzogiorno
217Ferrandina03/12/20134,436,089,0624,424,9161,059,02,730,51Ferrandina SALCivil Protection
218Ginestra03/12/20134,531,331,9561,335,0128,556,02,290,32Venosa SALCivil Protection
219Montescaglioso03/12/20134,489,336,0639,955,0224,256,04,000,54Montescaglioso SALPellicani et al., 2016
220Trivigno (4)03/12/20134,490,716,4583,663,1196,088,02,230,55Albano di Lucania PCCivil Protection
221Tursi03/12/20134,472,751,0632,461,7138,666,02,100,58Tursi SALEvalmet web site
222Viggianello04/12/20134,427,183,0589,852,674,861,01,230,85Viggianello SALCivil Protection
223Sarconi26/12/20134,457,355,0632,845,626,011,02,360,85Sarconi SALCivil Protection
224Aliano21/01/20144,463,968,1603,952,388,452,01,700,83Roccanova PCFonti Cronachistiche
225Calvera21/01/20144,454,657,0574,796,0193,669,92,810,86Episcopia PCLa Siritide
226Castronuovo di Sant’Andrea21/01/20144,450,030,0600,486,287,460,01,460,83Roccanova PCCivil Protection
227Rivello21/01/20144,436,820,3566,903,7114,841,02,800,86Nemoli SALCivil Protection
228Senise21/01/20144,444,739,2610,507,152,050,01,040,84Senise SALCivil Protection
229Latronico22/01/20144,436,079,5583,979,5194,970,02,770,86Episcopia PCLa Siritide website
230Lauria22/01/20144,444,641,2597,413,0267,286,03,110,86Nemoli SALFonti Cronachistiche
231Guardia Perticara24/01/20144,469,389,1594,580,2103,6128,00,810,85Guardia Perticara SALCivil Protection
232Maratea28/01/20144,427,583,9561,128,4234,6218,01,080,93Maratea PCCivil Protection
233Francavilla in Sinni30/01/20144,433,285,2569,276,0247,8238,01,040,86Episcopia
234Guardia Perticara02/02/20144,467,955,0593,670,046,446,01,010,95Guardia Perticara SALColdiretti webpage
235Potenza02/02/20144,496,094,5568,378,312,47,01,770,91Potenza PCCivil Protection
237Accettura03/02/20144,482,603,0600,241,7105,677,01,370,79San Mauro Forte PCaccettura online
238Castelluccio Inferiore03/02/20144,428,421,9583,511,5272,6381,00,720,78Viggianello
239Gallicchio03/02/20144,460,176,1597,304,588,067,01,310,92Roccanova PCCivil Protection
240Latronico03/02/20144,438,541,9586,536,247,668,00,700,94Episcopia PCCivil Protection
241Pisticci03/02/20144,458,130,1631,793,062,468,00,920,87Craco PCFonti Cronachistiche magazine
242San Giorgio Lucano03/02/20144,441,730,4618,593,460,274,00,810,94San Giorgio Lucano SALCivil Protection
243Aliano04/02/20144,462,662,3608,499,594,681,01,170,92Roccanova PCCivil Protection
244Gorgoglione04/02/20144,471,971,5597,509,086,274,01,160,95Guardia Perticara
245Guardia Perticara (2)04/02/20144,468,759,4593,490,191,885,01,080,95Guardia Perticara SALCivil Protection
246Missanello(2)04/02/20144,459,645,8598,794,796,681,01,190,79Aliano SALCivil Protection
247Noepoli04/02/20144,473,633,7637,169,5101,674,01,370,90Noepoli PCLa Siritide
248Sant’Arcangelo (3)04/02/20144,454,767,9612,151,094,681,01,170,92Roccanova PCCivil Protection
249Cirigliano05/02/20144,476,117,9599,525,8124,890,01,390,79San Mauro Forte PCsassiland
250Sarconi09/02/20144,473,389,5604,347,822,430,00,750,93Sarconi SALCivil Protection
251Stigliano09/02/20144,438,261,8613,374,0105,698,01,080,78Stigliano SALCivil Protection
252Armento25/03/20144,461,174,2591,120,817,414,01,240,81Guardia Perticara SALCivil Protection
253Guardia Perticara25/03/20144,455,948,6575,716,130,816,01,930,81Guardia Perticara SALCivil Protection
254Montemurro27/03/20144,462,003,7585,867,718,220,00,910,89Grumento NOvaCivil Protection
256San Severino Lucano06/04/20144,429,371,0597,800,068,049,01,390,89Viggianello
257Rionero in Vulture12/04/20144,530,903,2556,997,129,116,01,820,74MelfiCivil Protection
258Chiaromonte16/04/20144,470,704,8595,848,021,013,01,620,87Noepoli PCCivil Protection
259Montemurro17/04/20144,460,278,1587,345,413,27,01,890,83Grumento NovaCivil Protection
260San Severino Lucano30/04/20144,439,756,0605,195,537,447,00,800,87Viggianello SALCivil Protection
261Calvello24/07/20144,427,437,3600,212,211,01,011,000,31Laurenzana SALCivil Protection
262Rivello08/11/20144,435,948,7554,641,653,419,02,810,30Nemoli SALCivil Protection
263Rionero in Vulture (2)31/12/20144,530,984,6556,617,614,06,02,330,43MelfiCivil Protection
264Brienza30/01/20154,481,683,5553,437,489,824,03,740,76Brienza PCCivil Protection
265Chiaromonte30/01/20154,442,083,4603,091,636,853,00,690,58Senise SALCivil Protection
266Senise30/01/20154,444,603,9607,201,736,853,00,690,58Senise SALLa Siritide website
267Castelsaraceno31/01/20154,435,933,3568,128,3157,636,04,380,81Castelsaraceno SICivil Protection
268Lagonegro31/01/20154,429,110,9594,311,5284,953,05,360,87Lagonegro PCCivil Protection
269Latronico31/01/20154,435,217,2590,205,7164,961,02,690,78Episcopia PCCivil Protection
271Nemoli31/01/20154,427,708,0574,027,3263,843,06,130,92Nemoli SALCivil Protection
272San Costantino Albanese31/01/20154,432,781,2612,691,061,680,00,770,49Terranova del Pollino PCCivil Protection
273San Martino D’Agri31/01/20154,454,871,1589,437,173,234,02,150,74Roccanova
275Montemurro04/02/20154,461,149,4584,066,8144,6132,01,100,54Grumento NovaFonti Cronachistiche magazine
276San Severino Lucano06/02/20154,426,488,0595,925,0315,8240,01,320,82Viggianello
277Trecchina08/02/20154,428,416,7568,127,6344,0248,01,390,95CastrocuccoFonti Cronachistiche
278Lauria06/03/20154,434,254,5570,436,999,282,01,210,86Nemoli SALLa Siritide website
279Tricarico06/03/20154,497,116,3597,635,040,440,01,010,66Albano di Lucania PCtricarico news
280Vietri di Potenza12/03/20154,494,061,7543,185,29,65,01,920,84VietriQuotidiano del sud magazine
281Terranova del Pollino16/03/20154,425,194,1607,145,485,2120,00,710,84Terranova del Pollino
282Salandra18/03/20154485066v9613,268,613,820,00,690,72San Mauro Forte PCCivil Protection
283Montemurro25/03/20154,461,303,7585,075,431,462,00,510,88Grumento Novarainews
284Colobraro26/03/20154,449,328,3620,218,230,29,03,360,76Sinni a Valsinni SICivil Protection
285Ferrandina27/03/20154,472,778,5627,699,599,272,01,380,80Ferrandina SALyoureporter
286Calvera28/03/20154,445,756,6595,749,280,6128,00,630,90Episcopia PCCivil Protection
287Castronuovo di Sant’Andrea28/03/20154,449,432,7600,769,283,480,01,040,91Roccanova PCCivil Protection
288Chiaromonte28/03/20154,441,944,5603,702,871,678,00,920,73Noepoli PCCivil Protection
289Colobraro28/03/20154,451,661,8625,343,578,577,01,020,76Sinni a Valsinni SILa Gazzetta del Mezzogiorno magazine
290Grottole28/03/20154,495,416,1614,736,1107,2123,00,870,64Grottole da SerreCivil Protection
291Terranova del Pollino28/03/20154,424,299,8606,589,5142,4129,01,100,86Terranova del Pollino PCCivil Protection
292Anzi06/04/20154,484,904,3579,311,831,666,00,480,89Laurenzana SALCivil Protection
293Sasso di Castalda12/06/20154,482,734,2556,250,0178,876,02,350,59Brienza PCCivil Protection
294Grassano11/08/20154,498,091,9608,264,6106,228,03,790,15Grassano SALCivil Protection
295Grottole11/08/20154,497,727,3612,882,286,035,02,460,15Grottole da
296Matera11/08/20154,500,866,1633,780,754,351,01,060,11Matera PCCivil Protection
297Melfi11/08/20154,538,822,6554,831,511,82,05,910,04MelfiCivil Protection
298Salandra11/08/20154,487,314,1610,376,521,826,00,840,22San Mauro Forte PCCivil Protection
299Venosa20/10/20154,537,376,0569,867,022,815,01,520,24Venosa SALCivil Protection
300Chiaromonte31/10/20154,442,678,8603,349,5108,051,02,120,30Senise SALCivil Protection
301Gallicchio06/01/20164,460,397,1596,927,310,63,03,530,39Aliano SALLa Siritide website
302Rotonda13/02/20164,423,399,8588,125,9117,091,01,290,77Rotonda SALCivil Protection
303Picerno15/02/20164,500,954,0549,546,093,2103,00,900,51Balvano PCCivil Protection
304Venosa18/02/20164,535,187,4568,991,410,78,01,340,38Venosa SALCivil Protection
305Castronuovo di Sant’Andrea13/03/20164,449,163,2601,141,5120,650,02,410,87Roccanova PCCivil Protection
306Terranova del Pollino14/03/20164,425,609,1607,819,763,446,01,380,79Terranova del Pollino PCCivil Protection
307Ferrandina16/03/20164,472,610,0638,594,0101,0150,00,670,40Ferrandina SALyoureporter
308Sant’Arcangelo (2 eventi)16/03/20164,452,238,1611,364,0145,648,03,030,38Aliano SALCivil Protection
309Colobraro17/03/20164,449,758,6620,171,4321,4144,02,230,63Sinni a Valsinni SICivil Protection
310Pisticci17/03/20164,482,354,3626,252,672,126,02,770,57Torre Accio PCyoureporter
311Stigliano17/03/20154,472,596,0604,150,0238,2142,01,680,36Stigliano SALCivil Protection
312Salandra18/03/20164,485,538,3613,656,0156,6192,00,820,41Salandra SICivil Protection
313Pisticci25/03/20164,471,998,1633,051,047,018,02,610,73Torre Accio PCCivil Protection
314Sant’Angelo le Fratte26/03/20164,487,108,9547,444,035,833,01,080,68Tito PCCivil Protection
315Miglionico26/07/20164,492,210,7626,535,013,61,013,600,17Ferrandina PCQuotidiano della Basilicata magazine
316Lavello11/09/20164,545,245,7564,838,831,819,01,670,21Lavello SIvulturenews
317Genzano21/09/20164,521,410,4590,384,919,46,03,230,33Genzano SALCivil Protection
318Maratea10/10/20164,426,721,0560,774,8113,470,01,620,27Maratea PCFonti Cronachistiche
319Colobraro23/01/20174,447,990,5622,489,0127,268,01,870,57Sinni a Valsinni SICivil Protection
320Campomaggiore25/01/20174,490,127,7591,486,167,267,01,000,67Laurenzano PCCivil Protection
323Montemilone15/07/20174,542,486,2581,337,027,42,013,700,05Montemilone PCvulture news
324Viggianello05/03/20184,426,435,3589,650,4123,0197,00,620,87RotondaCivil Protection
325Rivello07/03/20184,436,820,1565,132,1208,0360,00,580,88Lagonegro PCCivil Protection
326Laurenzana28/03/20184,479,367,5582,543,4108,2192,00,560,83LaurenzanaCivil Protection

Table 1.

Rainfall-triggered landslides in Basilicata during last 20 years.


Conflict of interest

The authors declare no conflict of interest.

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Maurizio Lazzari, Marco Piccarreta, Ram L. Ray and Salvatore Manfreda (August 14th 2020). Modeling Antecedent Soil Moisture to Constrain Rainfall Thresholds for Shallow Landslides Occurrence, Landslides - Investigation and Monitoring, Ram Ray and Maurizio Lazzari, IntechOpen, DOI: 10.5772/intechopen.92730. Available from:

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