The meteorological event that brought torrential rainfall in the Gargano area began on 1 September 2014, when a perturbed nucleus originating from northern Europe moved to lower latitudes and impacted the Italian peninsula, starting from the northern and eastern sectors. In the early afternoon of 1 September, the central and southern parts of the Italian peninsula were first affected (Fig. 2a). Between 2 and 3 September, the low-pressure vortex moved towards the Ionian Sea and then to the Balkans and the Hellenic peninsula. The meteorological situation determined an inflow of perturbed masses of air over most of the Adriatic regions (Fig. 2b, c). The anticlockwise circulation affected most of central and southern Italy and persisted until 6 September. Residual perturbed meteorological conditions remained over the southern Italian regions; in particular those facing the Ionian Sea, with isolated minor precipitations until the late morning of 7 September (Fig. 2d).

The perturbed meteorological conditions over Italy resulted in torrential precipitation in the Gargano Promontory, with cumulated rainfall exceeding 500 mm in the 6-day period 1–6 September (Fig. 3). To study the intense rainfall period, we used hourly rainfall records available for 39 rain gauges pertaining to the national network of rain gauges operated in the area by the Italian National Department of Civil Protection and the Puglia Regional Government. Inspection of the rainfall records and of the geographical distribution of the precipitation (Fig. 3) revealed that (i) heavy rainfall persisted for the entire observation period, hitting different parts of the promontory at different times, and that (ii) seven periods could be singled out, including four rainfall (wet) periods and three no-rainfall (dry or nearly dry) periods (Fig. 3). The rainfall periods ranged from 8 to 49 h and were separated by dry periods lasting between 11 and 19 h (Table 1).

The first rainfall period (I) lasted 8 h, from 12:00 to 20:00 UTC+2 on 1 September. In this wet period, around 50 mm of rain was measured by most of the rain gauges, for an average rainfall intensity of about 6.25 mm h-1 (Fig. 3, Table 1). After a period of 19 h without rainfall (II), the second rainfall period started (III) and was particularly severe in the SW part of the promontory. About 400 mm was measured at the San Giovanni Rotondo and the San Marco in Lamis rain gauges, corresponding to an average intensity exceeding 8.2 mm h-1, with peak values exceeding 40 mm h-1. Relatively smaller amounts of rainfall were recorded at the Cagnano Varano (240 mm, most of which between 05:00 and 12:00 UTC+2 on 4 September) and the Monte Sant'Angelo (200 mm) rain gauges. The Vico del Gargano and the Bosco Umbra rain gauges, located in the NE part of the promontory, recorded approximately 50 mm of rain in the period (Figs. 1, 3).

Following a dry period of 12 h (IV), rainfall started again on 5 September (V), and this time it was most abundant in the NE part of the promontory. In this period, the Bosco Umbra and Vico del Gargano rain gauges measured slightly more and slightly less than 100 mm of rain, respectively, corresponding to a rainfall intensity exceeding 8.0 mm h-1. On the opposite, southern side of the promontory, the San Marco in Lamis rain gauge recorded only 10 mm of rainfall. In the same period (V), the San Giovanni Rotondo and Monte Sant'Angelo rain gauges, in the SE part of the promontory, measured about 50 mm of rainfall. Period V was followed by an 11 h nearly dry period (VI) which ended at 03:00 UTC+2 of 6 September 2014, when intense rainfall started again. The last rainfall period (VII) lasted until 14:00 UTC+2. In the 11 h period all the considered rain gauges measured more than 50 mm of rain, with the maximum cumulated value recorded by the Vico del Gargano rain gauge, where 140 mm of rain was measured, corresponding to a rainfall intensity exceeding 12.0 mm h-1.

A rank analysis of rainfall measurements for six rain gauges in the 7-year period from April 2009 to April 2016, highlighted the severity of the 6-day rainfall period (Fig. 4). Except for the Monte Sant'Angelo rain gauge, located in the southern part of the promontory, the 1–6 September rainfall period exhibited the highest cumulated rainfall in the observation period. Adopting the classification proposed by Alpert et al. (2002), the rainfall was “torrential” in all the considered rain gauges and, for three of the rain gauges, it was the only torrential event in the (short) record available (Fig.  4).

The sequence of intense rainfall events resulted in a number of floods, flash floods, landslides and sinkholes and caused two flood fatalities at Peschici and at Carpino (http://polaris.irpi.cnr.it/) and severe socio-economic damage (Fig. 5). Throughout the promontory, the road and railway networks were interrupted at several sites by inundations (Fig. 6a) and landslides, and many road underpasses were clogged by debris and sediments (Fig. 6b). In several towns and dwellings the inhabitants were evacuated from their homes, and a number of touristic resorts were inundated by water, mud and debris.

The consequences of the storm of September 2014 were reported soon after their occurrence, and a first analysis was carried out immediately in its aftermath. The collection of information was obtained searching different sources: (i) field surveys, (ii) technical reports produced by geologists, and (iii) online national, regional and local newspapers.

The collected information allowed the geographical coordinates of each phenomenon, its occurrence date and the type of hazard to be reconstructed.

No geological and geomorphological details were available for the landslides, especially when the information was found in newspapers. A specific landslide catalogue was built and managed in a GIS environment. The catalogue lists the following items: (i) event identification code, (ii) source of information, (iii) landslide location (geographic coordinates, municipality, province), (iv) occurrence date and time (if available), (v) spatial and temporal accuracy and (vi) landslide type.

As concerns floods, the main information consisted of the areas of interest, the reported damage and the extent of the flooded territory. Information on sinkholes included the occurrence site obtained through field surveys (high geographical accuracy) and the occurrence time, which was mostly based upon interviews with local inhabitants (low to medium temporal accuracy).

Flooding was widespread in the Candelaro catchment that bounds to the SW the Gargano Promontory (Fig. 5). Two hydrological gauging stations, one located where the Candelaro River crosses State Road SS 272 (W of the Gargano range) and one where it crosses the Provincial Road SP 60 near to the outlet in the Manfredonia Gulf (Fig. 5), measured very high water levels. The upstream gauge along the SS 272 measured a first peak of 5.30 m at 02:00 UTC+2 on 4 September, followed by a slightly higher peak of 5.50 m at 06:30 UTC+2. The water level remained very sustained until 09:00 UTC+2 and then it diminished (Fig. 3h). At the downstream gauging station located along SP 60, about 30 km downstream from the upstream gauge, a peak of 3.77 m was measured at 16:00 UTC+2 on 4 September, about 10 h later than the peak measured by the upstream gauge. We justify the (significant) time difference in the peak discharge by the widespread inundation of the Candelaro River plain (Fig. 6a).

Inundations were also severe along the northern coastal area, between Varano Lake and Vieste, and particularly between the towns of Cagnano Varano and Carpino (Fig. 5). Near Varano Lake, large agricultural areas were inundated. Along the northern coast of the promontory, flash floods produced by small torrents occurred mostly on 5–6 September. In the morning of 5 September, the Macchio Torrent overflowed and inundated Vieste, and several touristic sites. Overflowing of minor torrents and ditches was reported in the early hours of 6 September in the towns of Peschici, Vico del Gargano and Rodi Garganico.

The torrential rain caused a number of landslides, mostly shallow landslides (Fig. 6c, e, f). Overall, we collected information on 46 landslides, including 14 earthflows, 14 debris flows, 11 soil slides, 4 rockfalls, 1 mudflow and 2 slope failures of undetermined type. This is a subset of all the event landslides in the Gargano Promontory. Based on the type of failures, we hypothesise that all the landslides were from rapid to extremely rapid. Most of the mapped landslides were in the municipalities of San Marco in Lamis, Ischitella and Cagnano Varano. Landslides were also reported near San Giovanni Rotondo, Rignano Garganico and Rodi Garganico (Fig. 5).

We searched information on the time or period of occurrence of the landslides. However, for most of the landslides the time or period of occurrence remains unknown or suffers from very large uncertainty. For only nine landslides we obtained reasonably accurate information on the period of occurrence of the slope failures. On 3–4 September, four landslides occurred near San Marco in Lamis, along SS 272, most probably in the 3 h period between 23:00 and 02:00 UTC+2. We consider these landslides representative of a larger cluster in the same area (cluster A). On 4 September, a landslide occurred between 05:00 and 16:00 UTC+2 near Cagnano Varano (cluster B). In the same day, a single landslide occurred in the municipality of San Giovanni Rotondo at an undetermined time between 14:00 and 21:00 UTC+2 (cluster C). Lastly, three landslides occurred in the night between 5 and 6 September and most probably between 23:00 and 05:00 UTC+2, in the municipalities of Ischitella and Rodi Garganico (cluster D). We attribute the scarce temporal information and the poor accuracy of the information on the time of occurrence of the failures to the difficulty of reaching some of the places where the landslides occurred and to the fact that many landslides occurred in the evening or during the night and were reported only several hours after the event.

The torrential rainfall also caused sinkholes. We mapped 10 small sinkholes near the villages of San Marco in Lamis and Monte Sant'Angelo (Fig. 5). Based on their morphology and shape, the sinkholes were classified as collapse or cover-collapse sinkholes (Gutiérrez et al., 2008, 2014). At San Marco in Lamis, four sinkholes affected the lower part of a pre-existing karst depression. The deepest sinkhole was about 6 m deep, 5 m wide and exposed limestone and residual terra rossa deposits that represent the upper part of the epikarst (Williams, 2008) (Fig. 6d). Other sinkholes were less developed and were detected and mapped locally only based upon morphological considerations. Due to the remote areas where the sinkholes occurred, their limited sizes (Fig. 6g) and the difficulty of detecting them, no accurate information is available on the time or period of occurrence of the sinkholes.

To help investigate the effect of the changing spatial and temporal distribution of the rainfall on the location of the landslides, floods and sinkholes, we prepared Fig. 7, which portrays, for each period in the sequence of rainfall events (Sect. 3.2), maps showing the spatial distributions of the mean rainfall intensity (in mm h-1), the cumulated rainfall for the single period and from the beginning of the event (in mm) and the location of the landslides that occurred in each period and in previous periods.

An inspection of Fig. 7 reveals that the total cumulated rainfall, exceeding 100 mm in large parts of the promontory, was the result of separate rainfall events that hit different parts of the promontory at different times. The first rainy period (I) was more widespread but characterised by an overall moderate cumulated rainfall not exceeding 50 mm and rainfall intensity not exceeding 6.2 mm h-1. No landslides or floods were reported during the first rainy period. The second (III) and the third (V) rainy periods were more localised; the second was in the central part of the promontory (San Marco in Lamis and San Giovanni Rotondo) and the third was in the NE sector of the promontory (Ischitella, Vico del Gargano and Vieste), and were both characterised by high values of cumulated rainfall (exceeding 400 mm in the second and 130 mm in the third period) and of rainfall intensity ( exceeded 8.5 mm h-1 for the second period and 10.5 mm h-1 for the third period, respectively). Landslides were reported in the central (cluster A) and in the northern (cluster B) parts of the promontory during the second rainfall period (III). In the same period the upstream hydrological gauging station along the Candelaro River measured high water flows exceeding 5.0 m (Fig. 2), about 2 h after the maximum hourly rainfall measured at the San Marco in Lamis rain gauge, at 24:00 UTC+2 on 3 September. The landslides occurred in areas where the total event cumulated rainfall exceeded 400 mm (for cluster A) and 200 mm (for cluster B).

In the central part of the promontory, landslides were also reported (cluster C) during the second dry period (IV). Given the poor temporal accuracy of these landslides (i.e. between 14:00 and 21:00 UTC+2 on 4 September), we cannot exclude that the failures occurred during the last few hours of the previous rainfall period (III). The hypothesis is supported by the fact that the San Giovanni Rotondo rain gauge measured rainfall until 15:00 UTC+2 on 4 September (Fig. 2). The last rainfall period (VII) was again characterised by widespread rainfall throughout most of the promontory with a distinct peak in the NE sector exceeding 130 mm. Where rainfall intensity was particularly intense (> 11 mm h-1) in the NE part of the promontory, between Rodi Garganico and Peschici, landslides were also reported (cluster D).

The ensemble–non-exceedance probability (E-NEP) algorithm exploits a standard rainfall record obtained by a rain gauge to trace in time the probability of possible landslide occurrence and of related geohydrological hazards. For the purpose, for each time ti, E-NEP calculates the event rainfall duration D, and the corresponding event cumulated rainfall E, for increasing antecedent periods before ti, from ti to ti+T, in d time steps, with T the maximum length of the considered antecedent rainfall period and d the time step used to increment the duration of the antecedent rainfall period. For each rainfall-duration–event-cumulated-rainfall pair the corresponding non-exceedance probability (NEP) p(D,E) is obtained using the probabilistic approach proposed by Brunetti et al. (2010) and modified by Peruccacci et al. (2012) for the definition of empirical rainfall thresholds for possible landslide occurrence (Guzzetti et al., 2007). The set of the NEP values (i.e. {NEP} = {p(D,E)}) is then used to determine an ensemble of metrics, including the maximum value of the NEP (NEPmax), the 10th, 25th, 50th, 75th and 90th percentiles (NEP10, NEP25, NEP50, NEP75, NEP90), and the rainfall duration (DNEPmax) associated with NEPmax, that collectively are exploited for landslide forecasting. The process is repeated at regular time intervals (z, where ti+1= ti+z), allowing the temporal evolution of the probability of possible occurrence of rainfall-induced landslides and of related geohydrological hazards to be followed.

Figure 8 portrays the logical schema for the E-NEP algorithm, which consists of two nested loops. First, the maximum length of the considered rainfall period, T (in hours), the time step to increment the duration of the considered antecedent rainfall, d (in hours) and the time interval before the next set of (D,E) pairs is computed, z (in hours), are set to user-defined values. We stress that the three time (duration) variables are independent, with the only constraint that d≤T. Next, the external loop (cyan in Fig. 8) starts, the rainfall duration D is set to d and {NEP} is set to null (an empty set). Next, the internal loop (orange in Fig. 8) starts and for the given rainfall duration D, the corresponding cumulated rainfall E is determined, and the probability of landslide occurrence p(D,E) is computed adopting the method proposed by Brunetti et al. (2010) and Peruccacci et al. (2012) and stored in {NEP}. The rainfall duration D is then incremented (D=D+d) and tested to verify whether it is larger than T. If D≤T, the internal loop is repeated using the current value of D and the corresponding E; otherwise (D > T) the loop ends, and the ensemble of metrics of {NEP} (NEP10, NEP25, NEP50, NEP75, NEP90, NEPmax) and the value of DNEPmax are calculated. The external loop is then repeated after the user-defined time interval of z hours.

Figure 9 exemplifies the application of the E-NEP algorithm to a specific rainfall record, at a given time ti (i.e. the application of the orange internal loop of Fig. 8), for an antecedent period T= 96 h, with d= 1 h. E-NEP calculates the cumulated event rainfall E for increasing durations D from 1 (ti-1) to 96 h (ti-96), every hour (time step d= 1). The individual (D,E) pairs are plotted as grey dots in Fig. 9d. For each pair, the corresponding NEP, the non-exceedance probability of possible landslide occurrence, was calculated and is shown by the blue squares in Fig. 9d. To further clarify the operations performed by the E-NEP algorithm, the bar charts in Fig. 9a, b, c show, for the same time ti, three antecedent rainfall periods corresponding to durations of D= 6 h (red bars), D= 16 h (green bars) and D= 44 h (yellow bars). The corresponding cumulated event rainfall (red, green, yellow circles) and the associated non-exceedance probability values (red, green, yellow squares) are shown in Fig. 9d. Lastly, the box plot to the right of Fig. 9d portrays (i) the ensemble of metrics of {NEP}: NEP10, NEP25, NEP50, NEP75 and NEP90 and the maximum value of the non-exceedance probability, NEPmax. In Fig. 9d, the green square identifies NEPmax, i.e. the non-exceedance probability corresponding to the most critical rainfall condition for possible landslide occurrence in the considered rainfall period. The corresponding duration (D= 16 h) represents the DNEPmax value.

We applied the E-NEP algorithm to the 13-day period between 31 August and 12 September, which encompasses the entire series of rainfall events that hit the Gargano Promontory. We applied the algorithm to synthetic hourly rainfall records reconstructed for the locations of the four spatial-temporal landslide clusters identified in the study area (Fig. 7). To reconstruct the synthetic rainfall records, we interpolated the hourly rainfall measurements obtained by 39 rain gauges in the Gargano Promontory and the surrounding regions at the landslide locations. For that purpose, we used a standard inverse weighted distance (IDW) spatial interpolator (Shepard, 1968) to obtain hourly rainfall values on a regular 500 m × 500 m grid. Next, the hourly rainfall grids were sampled at the grid cells selected to represent the four landslide clusters A, B, C and D, and the synthetic hourly rainfall time series were reconstructed for each landslide cluster.

For our analysis, and for each landslide cluster, ti ranged from 31 August, 00:00 UTC+2 to 11 September, 24:00 UTC+2, in regular 1 h time intervals (z), corresponding to a total of 288 time intervals. For each ti, E-NEP computed the NEP10, NEP25, NEP50, NEP75 and NEP90 percentiles, the NEPmax and the corresponding DNEPmax.

Results of the analysis of the four landslide clusters are shown in Fig. 10, in which the single plots show, from top to bottom, the temporal evolution of (i) the measured and the cumulated rainfall, (ii) the NEP10, NEP25, NEP50, NEP75, NEP90 percentiles (shown in ranges, by two different shades of blue and by the thick blue line) and NEPmax (purple line) and (iii) the corresponding DNEPmax (green line). Figure 10 also shows (i) with grey areas, the possible period of occurrence of the landslides, a measure of the uncertainty in the failure occurrence time and (ii) with a vertical blue line the time of the high peak measured by the Candelaro gauge along SS 272 (Fig. 10a, Fig. 3).

For cluster A, encompassing landslides occurred along State Road SS 272 and SP 48 near San Marco in Lamis; a short rainfall burst hit the landslide area at 12:00 UTC+2 on 1 September and stopped shortly afterward (Fig. 10a1, I in Fig. 3). In this period, the NEPmax increased rapidly to 0.15 and decreased immediately afterwards due to a lack of rainfall (Fig. 10 a2). Next, following a dry period of 19 h (II in Fig. 3), the main rainfall event started at 16:00 UTC+2 on 2 September (Fig. 10a1, III in Fig. 3). As a result of this second, intense rainfall event all the NEP percentiles increased abruptly and significantly (Fig. 10a2), with NEPmax exceeding 0.99 at 23:00 UTC+2 on 3 September. The landslides of cluster A followed shortly afterward.

Following the landslide occurrence, all the NEP values remained high for 12 h. When the rainfall stopped, at 14:00 UTC+2 on 4 September, the NEP percentiles decreased, beginning with NEP10 and continuing with the other (larger) percentiles. NEPmax decreased below 0.25 at 21:00 UTC+2 on 8 September. The analysis of the temporal trend of DNEPmax (Fig. 10a3), the rainfall duration corresponding to largest NEP, is of interest. DNEPmax (i) increased in response to the first rainfall period (I in Fig. 3), (ii) kept rising during the first dry period (II in Fig. 3), (iii) dropped to zero during the second (main) rainfall period and precisely when the rainfall intensity reached a maximum value of 7 mm h-1 (III in Fig. 3), (iv) increased steadily for 94 h and (iv) remained high until almost the end of the considered period.

We observe that landslides in cluster A occurred when the NEPmax was close to its maximum possible value (NEPmax= 1), a very critical condition for possible landslide initiation (Brunetti et al., 2010; Peruccacci et al., 2012). Just before the landslide occurrence (i) NEP50 was close to NEPmax; i.e. the median value was close to the maximum value of the non-exceedance probability, (ii) the inter-percentile ranges NEP10–NEP90 and NEP25–NEP75 were narrow and (iii) there was a sudden increase of all NEP values, particularly of the lower percentiles (i.e. NEP10, NEP25) (Fig. 10a2). We further observe that landslides in this cluster occurred after DNEPmax began to rise following a sudden drop (Fig. 10a3).

Inspection of the other plots in Fig. 10 reveals significant similarities in the temporal evolution of the metrics computed by the E-NEP algorithm for the other three landslide clusters, when compared to the same metrics computed for cluster A. Specifically, (i) all landslides occurred when the NEPmax was close to its maximum value, and immediately before landslide occurrence (ii) NEP50 was close to NEPmax, (iii) the range NEP25-NEP75 was narrow, (iv) there was a sudden increase of all NEP percentiles (Fig. 10a2) except NEP10 (Fig. 10c2) and (v) the landslides occurred after the DNEPmax had started to rise following a previous sudden drop. We consider these observations diagnostic of the rainfall conditions that have resulted in landslides (and other geohydrological hazards) in the Gargano Promontory in the period 1–6 September 2014.