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ISSN: 2167-0587
Journal of Geography & Natural Disasters
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Real Time Monitoring for Diagnosis and Prevention of Extreme Rainfall Events: An Application to Intense Rainfalls on the Coastal City of Naples, Italy

Tranfaglia Giuseppe1*, Braca Giovanni1, Monacelli Giuseppina1, Biafore Mauro2, Porfido Sabina3 and Mazzarella Adriano4

1Italian National Institute for Environmental Protection and Research - ISPRA, 6000144 Rome, Italy

2Hydrometeorological Centre of Campania Region, 80143 Naples, Italy

3National Research Council - CNR, Institute for Marine Coastal Areas - IAMC, 80133 Naples, Italy

4University of Naples Federico II, Department of Earth, Environment and Resources Sciences, 80138 Naples, Italy

*Corresponding Author:
Tranfaglia Giuseppe
Italian National Institute for Environmental
Protection and Research - ISPRA, 6000144 Rome, Italy
Tel: 339 1726052; +39 06 5007 4711
E-mail:
[email protected]

Received Date: August 29, 2016; Accepted Date: September 01, 2016; Published Date: September 02, 2016

Citation: Tranfaglia G, Braca G, Monacelli G, Biafore M, Porfido S, et al. (2016) Real Time Monitoring for Diagnosis and Prevention of Extreme Rainfall Events: An Application to Intense Rainfalls on the Coastal City of Naples, Italy. J Geogr Nat Disast 6:180. doi:10.4172/2167-0587.1000180

Copyright: © 2016 Tranfaglia G, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

The rainfall monitoring network of the Naples Department of Hydrographic and Oceanographic Service (NDHOS) was inadequate to measure the alluvial event occurred at Sarno on 5 May 1998, when a low rainfall amount of 101 mm was considered responsible for a dramatic landslide. To improve the measuring capability of this network, 50 new monitoring stations were later on added and located in such a way to increase significantly the fractal dimension of their areal distribution. The enlargement of the network allowed the correct measurement of the extreme event occurred in Naples on 15 September 2001. The paper reports also the risk of landslide phenomena (not catastrophic but however not negligible) inside the metropolitan area of Naples, frequently subjected to rock falls and to collapse of underground cavities.

Keywords

Real time network; Intense rainfalls; Extreme events; Fractal dimension

Introduction

The NDHOS began its activity of the collection and the elaboration of data for the editing of the Hydrologic Annals in the year 1918. The real-time rainfall monitoring system started in 1993, when the first 19 stations were installed and connected to the Master Control Center (MCC) in Naples. Since then, other groups of rainfall gauging stations have been installed following several plans carried out after the alluvial events of Sarno (May 1998), Cervinara (December 1999) and Naples (September 2001).

In September 2002 the monitoring network consisted of 136 remote control stations. Real-time rainfall data from these stations are transmitted to the MCC of Naples, within a 10-min delay time, by a radio-communication system based on 10 repeaters in UHF frequencies. A data acquisition system and a set of software packages are implemented in order to evaluate the hydro-meteorological situation.

The occurrence of intense and alluvial phenomena in autumn and winter over the Mediterranean area depends on cyclonic small areas whose dynamics follow the genesis of tropical cyclones (hurricanes) that show a lower energetic level. Such meteorological systems, together with convective systems and orographic rainfall, can be intensified by a big contribution of heat at the surface and, often, determine sudden alluvial events on the coast and the mountains exposed to the winds of sea.

It here shown that the fractal methodology can offer a valid contribution to an enlargement of an existing meteorological network and to an optimal location of additional stations. The areal sparseness of the historical rain-gauge network belonging to the NDHOS has been measured by means of the fractal dimension D that overcomes the limits of the Euclidean geometry [1]. The measurement of meteorological extreme events requires the increase of the capability of a network through its strategic enlargement, resulting in a compromise between the increase of fractal dimension and topographic necessities.

Materials and Methods

Real-time hydrological monitoring network

Until September 2002 the rainfall gauging network [2-4] consisted of 136 stations, 10 repeaters and the MCC in Naples, controlling a total of 259 sensors (50 ultrasonic hydrometers placed on bridges, 112 rain gauges, 54 thermometers and many others meteorological and hydrological sensors) (Figure 1). The repeater systems are in compliance with the EEC regulations; the network frequencies are in the 437-447 MHz range and the transmitting antennas are interference-free; their power supply is provided by generators because of adverse weather conditions for long periods of the year.

geography-natural-disasters-Hydrometeorological-network-Naples

Figure 1: Hydrometeorological network of Naples Department of Hydrographic and Oceanographic Service (NDHOS).

The MCC is composed by 3 functional blocks: (1) the DAS (Data Acquisition System) front-end and its peripherals; (2) the MARTE (Meteorological Analysis and Real Time Evaluation) computer (with special software for real-time hydrometeorological applications) and its peripherals, and (3) the communications channels.

The DAS acquires and performs a preliminary analysis of the data from the peripheral stations: it calls the stations periodically (every 10 minutes) and records all the data on magnetic media ascertaining if some alarm threshold, linked to absolute levels or to some tendency in the data, has exceeded. The DAS also allows a real-time visualisation and printing of data and reports to be done, as well as selective calls, reconfiguration of the network and all the required other operations necessary for its correct management.

Each of the 136 remote stations is equipped with a data logger system, an automated tipping bucket gauge, a solar panel and a radio device with a transmitting antenna (Figure 2). The peripheral stations have multitasking processors, EPROM and RAM buffered memories. They can control up to 16 sensors. The data are transferred to the Centre by radio, but transmission by modem-phone line is also possible. The power supply is given by batteries charged by solar panels. A battery supplies power for about 30 days, performing the measurements and transmitting the results. Apart for the slightest problems, all the stations worked regularly; only routine half-yearly maintenance has been made, during which sensors were checked and memory buffers were changed. Rarely electromagnetic noise generated spikes on the transmitted signals, mainly in the line from the repeaters to the remote stations. The software of the DAS can easily detect these spikes as anomalies in the signals and then eliminates them.

geography-natural-disasters-remote-station-equipped-logging

Figure 2: The remote station is equipped by a data logging system, an automated tipping bucket rain gauge, a solar panel and a radio device with a transmitting antenna.

After the Sarno disaster the NDHOS, in co-operation with the Civil Protection Department and the National Group for Hydrogeological Disaster Prevention of the University of Salerno, organised a hydrometeorological warning system for preventing extreme rainfall events [4,5]. The system has been designed to manage the emergency after the event and to reduce the risk in the territories of five towns: Sarno, Quindici, San Felice a Cancello, Siano and Bracigliano.

For a more detailed monitoring of the damaged zone, four raingauge stations and one meteorological station (Torriello) were installed in an area of about 70 km2 (Figure 3).

geography-natural-disasters-Rain-gauge-stations-monitoring

Figure 3: Rain-gauge stations for detailed monitoring of the damaged zone in the Sarno area (the tectonic sketch map of the area is shown at the top left).

The warning system is based on two level threshold schemes for 24, 48, and 72 hours precipitation: the alert warning level and the alarm warning level (Figure 4).

geography-natural-disasters-Theoretical-scheme-threshold

Figure 4: Theoretical scheme of precipitation threshold parameters.

Precipitation thresholds of duration d depend mainly on total precipitation from the first of September (that we assume as the beginning of the wet season) until the last d hours (precipitation before the event), PAd, and on total precipitation in the last d hours (precipitation during the event), PEd, (Figure 5). Such a threshold scheme was designed to simulate a memory-like mechanism triggering landslide.

geography-natural-disasters-thresholds-Sarno-district

Figure 5: Precipitation thresholds in the Sarno district.

The precipitation threshold is referred by each district taking into account the mean value of precipitation measured on a selected group of rain-gauges.

Networks for monitoring extreme rainfall events: a fractal areal distribution

The rainfall physical phenomenon taking place over an area is a termination stage of a number of different processes occurring on different scales and the derivation of its areal-estimates from point observations has been, and probably will remain, one of the most difficult issues within geophysics. Although an ideal network of stations should be spatially homogeneous, in most cases it is almost impossible to realise, perhaps due to practical circumstances which hinder measurements being taken from pre-established points and to a multistage decision process involved in establishing the same network. This inevitably results in interpolation errors in the computation of a regular grid from the observed data. The areal clustering of point sets can be measured by different statistical indices but when the interstation distances are scale-invariant it can be well characterised by its fractal dimension [1].

The average of a rain field depends on both the scale and the dimension (for example, line, plane, volume or fractal set) over which it is averaged, so that intense and localised spatial phenomena with an extension smaller than the minimum detectable scale and with a dimension smaller than the minimum resolvable dimension will slip through the monitoring network undetected. For more reliable restoring of a physical phenomenon, it is necessary to analyse data recorded by a network with a high spatial and dimensional resolution. The fractal methodology can offer a valid contribution to an enlargement of an existing network and an application to the raingauge network of NDHOS is reported by Mazzarella and Tranfaglia [6]. The areal sparseness of the historical rain-gauge network belonging to the NDHOS has been measured by means of the fractal dimension D, that is an index that ranges progressively from 0 (when all the stations are distributed on a single point or on isolated points) through 1 (when all the stations are distributed on a line) up to 2 (when all the stations are distributed homogeneously or randomly on a plane). Particularly, Mazzarella and Tranfaglia [6] found that the value of D of the historical NDHOS network (Figure 6) was equal to 1.84 and not sufficiently high to get correct measurement of the event occurred at Sarno from 4 to 5 May 1998, when a low rainfall amount of 101 mm recorded at Sarno was considered responsible for a dramatic landslide [7]. The extremely high hourly time and space variability observed at the nearest stations with intensity peaks many times above the average was a direct consequence of sparse but intense rainy cells. To understand the problem caused by a network of stations distributed over an area with a fractal dimension less than 2, it has to be said that if the stations were located over a square of side X, the area effectively measured by the stations is not equal to X2 but to XD, and that all the rainy phenomena with area X(2-D) would slip through the network undetected [8].

geography-natural-disasters-Left-panel-map-locations

Figure 6: Left panel: sketch map showing the locations of the 215 historical rain gauges belonging to the NDHOS (the longitude is measured starting from Monte Mario meridian: 12°27’8” E); right panel: the log of numbers of pairs C of historical rain gauge network with mutual distance smaller than R, as a function of log(R) (km). The vertical dashed line represent the lower (8 km) and upper (64 km) limits of R, inside which the linear slope provides the best fitting to the investigated coordinates.

The addition of 50 new rain gauges, located according to the fractal geometry way, allowed the increase of the fractal distribution of the areal distribution of the stations from 1.84 to 1.89 and the achievement of the correct measurement of the rainfall that hit the city of Naples on 15 September 2001 (max recorded value 167 mm) and some of the surrounding towns, and which lasted about 3 hours. The storm was clustered in two very intensive showers (with a mean intensity greater than 50 mm/h). The meteorological event was undoubtedly the most intense event ever recorded, since 1866, on the territory of the Naples district. A comparison with historical events dated since 1821 has been carried out. The recorded monthly precipitation has been correlated with the landslide phenomena frequently occurred in the area of Naples.

It is useful to underline that the fractal dimension of the temporal and spatial structure of the rain depends largely on the threshold intensity [9]. Such a result, known as multifractality of the rainfall, suggests that a large-scale rainy cell is organized in smaller cells and at a later stage in sparser and more intense cells with a fractal dimension so low to make much difficult their identification by a network of stations.

An attempt to correlate the Mediterranean climate scale with the frequency of the extreme events has been carried out by [10]. The analysis of historical series of rainfall recorded inside the catchments of four large Italian rivers shows that more than 50% of their interannual variance is significantly explained by the 22-year harmonic. It is proposed that the solar magnetic activity of 22 years is able to modulate in cascade the zonal circulation over the Mediterranean basin and the relative rainfall.

The 15 September 2001 intense rainfall event

Landslide phenomena represent a significant aspect of geological hazard in Campania region, including the city of Naples. The storm of September 2001 (declared flood disaster), that hit the Neapolitan districts, has dramatically brought back to the attention the problem of the extreme embrittlement of the territory.

In the early hours of 15 September 2001 the city of Naples and some of the surrounding towns were hit by a violent storm which lasted about 3 hours [11,12]. The storm which had originated in England, swiftly passed over France and Northern Italy finally reached Southern Italy at about 02:00 UTC. In Figure 7, the infrared image taken by the Meteosat satellite at 03:30 UTC on 15 September clearly shows the impact of the perturbation from the North with the hot and humid air sustained by a second perturbation coming from Southwest, originating in North Africa. The thunderstorm cell lingered over the Gulf of Naples from 02:00 to 05:00 UTC, and gave way to 170 mm of rain in a three hour time frame as a consequence of the condensation caused by the impact.

geography-natural-disasters-Meteosat-satellite-infrared

Figure 7: Meteosat satellite infrared image on 15 September 2001 at 03.30 UTC.

An analysis of this exceptional precipitation event was carried out on the basis of data collected from real time network and recordings. The rain gauge digital stations of Naples Capodimonte (Figure 8), Naples Camaldoli and Pozzuoli Solfatara recorded rainfall starting at 2.00 on 15 September and ending at 5.30 a.m. On the other hand, the Ischia Monte Epomeo stations recorded rainfall onset times about an hour earlier while those of Ottaviano and Torre del Greco, west of Naples, with a delay of about an hour. The event basically developed into two showers of about an hour each, separated by an interval of lighter rainfall. During the two showers very intense rainfall levels were reached: 24 mm in 10 minutes (144 mm/h) recorded at Naples- Capodimonte; 23.6 mm in 10 minutes (141.6 mm/h) at the Naples Camaldoli; 23.4 mm in 10 minutes (140.4 mm/h) at Pozzuoli and Ischia. Table 1 lists the maximum values recorded at the stations of the flooded areas.

geography-natural-disasters-every-ten-minutes-real-time

Figure 8: Precipitation (every ten minutes) measured in real time at Naples Capodimonte.

Rain gauge Type Altitude P10’,max P30’,max P1h,max P2h,max P3h,max Ptotal
NDHOS Pr 30 - - 76.8 96.8 166.4 167.4
Naples Posillipo Pr 170 - - 59.2 76.2 113.6 116.8
Naples Camaldoli Pe 385 23.6 53 63.2 102.4 118.2 119.2
Naples Capodimonte Pe 300 24 50.4 68.2 110 137.6 139.8
Pozzuoli (anfiteatro) Pr 57 - - 83 100 160 162.4
Pozzuoli (solfatara) Pe 110 23.4 59.6 80 121 160.6 161.6
Ischia Mt. Epomeo Pe 390 23.4 45.4 52.8 54.4 65.8 76.6
Torre del Greco Pe 332 12.2 33.6 54.2 67.2 82.4 82.6
Ottaviano Pe 192 23 40 46.6 77 91.2 91.2

Table 1: Maximum precipitation in the area interested by heavy-storm event of 15 September 2001 (Pr=traditional recording rain gauge; Pe=digital recording real time rain gauge).

The isohyetal map (Figure 9), drawn up on the basis of the recorded values, shows that the event was rather restricted. The flooded area comprised in the 80 mm isohyet (equal to the maximum rainfall ever recorded in a 3 hour time frame in more than 150 years in Naples) extends up to the northern slopes of the Vesuvius.

geography-natural-disasters-Isohyetal-map-precipitation

Figure 9: Isohyetal map of the total precipitation on 15 September 2001.

In order to verify the exceptional character of the meteorological event of the 15 September 2001 the observed phenomena have been compared with the historical observations available at the stations located in the city: Observatory of Capodimonte (started in 1821), Naples University (Department of Geophysics and Volcanology, started in 1866), and NDHOS (started in 1927). When the Observatory of Capodimonte station did not operate, the data was taken from the nearest station (Capodimonte reservoir); when the station of the Naples University did not operate, the data was taken from the station of Capodichino Airport. Therefore, we constructed a catalogue of 37 catastrophic events (Table 2) that have hit the area of Naples from 1866, simply verifying that a rain greater than 80 mm has fallen in 24 hours, in at least one of the 3 stations taken to reference [11,12].

Nr Year Month Day Capodimonte University NDHOS
1 1875 10 15 60 82  
2 1889 12 27 92 89  
3 1890 12 2 81 83  
4 1910 10 24 120 99  
5 1911 9 21 73 89  
6 1915 9 2 110 90  
7 1915 10 1 89 89  
8 1918 6 6 78 91  
9 1918 10 5 125 99  
10 1920 6 20 51 87  
11 1921 10 27 68 92  
12 1922 11 4 77 94  
13 1925 9 28 90 91  
14 1930 10 25 69 83  
15 1933 11 23 86 85 103
16 1947 9 6 126 103 >> 
17 1948 9 5 106 68 85
18 1951 9 25 75 63 80
19 1952 10 23 100 87 82
20 1953 12 20 77 81 85
21 1957 10 22 95 64 54
22 1961 10 7 82 68 75
23 1969 9 19 74 83 87
24 1973 1 1 91(2) 114 94
25 1978 9 5 82(1) 77 88
26 1979 10 28 119(1) 138 133
27 1980 11 13 60(1) 61 81
28 1981 10 21 68(1) 72 108
29 1985 11 16 95(1) 114 168
30 1986 11 21 22(1) 86 44
31 1986 11 23 68(1) 96 62
32 1987 11 9 76(1) 98(2) 136
33 1990 4 9 53(1) 59(2) 89
34 1995 4 15 62 114(2) 81
35 1996 9 20 58 57 87
36 2001 9 15 140 P> 100(2) 167
37 2003 9 9 86 73(3) 91

Table 2: Intense rainfalls of more than 80 mm occurred in Naples, measured in a day, at least for one of rain gauge station reported in the table [(1)Capodimonte reservoir; (2)Capodichino Airport; (3)Camaldoli].

Historical landslide phenomena in Naples and damage estimation

In the last century, numerous landslide phenomena were induced by heavy rainfall, and caused, at times, severe damages to the economical, social and infrastructural condition of the metropolitan area. We report a striking historical example of such phenomena.

An intensive search for contemporary sources was undertaken in national archives, libraries and private archives of the city. The investigated sources include technical reports, contemporary chronicles, administrative records, national and local newspapers, etc.

Newspapers provided the most useful and reliable source, in fact they provided a detailed description of the phenomena including information on human consequences, such as homeless people, injuries, and deaths and the identification of the damaged areas. Among all the gathered data a temporal window that covers the period ranging from 1821 to 2001 has been selected.

The city of Naples is located in the southern part of the Campanian Plain, which is prevalently composed of a large variety of pyroclastic deposits (tuff, pozzolane, pumices) related to both, Campi Flegrei and Somma-Vesuvius volcanic activity, whereas alluvial soils and sea shore sand are recognized along the coastline. Naples lies on an alternation of tuff, pozzolane, pyroclastic soil with interbedded pumices, which generally present an overall thickness of over 100 m. In particular, the Neapolitan Yellow Tuff Formation is either outcropping or is located some tens of meters below the surface and is characterised by an intricate network of artificial cavities which have been excavated as far as in Greek and Roman times.

The analysis of the historical data allows us to identify (Figure 10) more than 100 new landslide phenomena in the last century [12]. According to historical descriptions, five main types of effects have been identified: rock fall, earthflow (landslide), collapse, flood and lahar (the latter only occurred after the 1900 volcanic eruptions). Other rock types include those that occurred in quarries. Rock falls of Neapolitan Yellow Tuff were the most frequently observed phenomena (52% of the registered events), characterized by detachment of smallmedium volumes of material (max 200 m3); these landslides, located along the Capodimonte and Posillipo hill slopes and Neapolitan Yellow Tuff quarries (North-North West sector of the city), caused the death of 33 people between 1821 and 1964.

geography-natural-disasters-Landslide-phenomena-last-century

Figure 10: Landslide phenomena of the last century in Naples.

Only few cases of earthflow of pyroclastic soil have been recognized along the Posillipo hill slopes. This kind of phenomenon involves only the most external part of the slope where the weakest material collapses, reaching some hundreds of cubic meters of material.

The collapses (34%) were prevalently observed in the area of the ancient cavities underneath the historical center of the city. They caused severe damages to historical buildings and infrastructures. Flood events (10%), induced by heavy precipitation, occur about every ten years. These effects were largely diffused in the Southern and Eastern sectors of the city. Eleven lahar events (4%) caused many damages to buildings, railways, mainly due to the slide of thousands of cubic meters of material with thickness between 0.5 and 1.5 m.

Though not totally exhaustive, our present knowledge allows us to underline significant aspects of the vulnerability of the Naples urban territory.

Such phenomena have been compared to rainfall data since 1821. We analyzed all the monthly rainfall data from 1821 to 2003 recorded by the Capodimonte rain-gauge station, until 1986 for Naples University and until 2001 for the NDHOS.

With the aim of verifying that the historical series of pluviometric monthly data of the stations in the city of Naples were homogenous, we resorted to the classic analysis of the double-mass curve.

The values accumulated of the depths of rainfall measured in each station have been connected with the correspondent values of precipitation measured in the other stations.

The analysis between the stations of Naples University and NDHOS and between the stations of Naples Capodimonte and Naples University shows, besides an evident homogeneity of the historical series, a difference between the rainfalls values in the order of 5%. On the other hand, from the same analysis it becomes evident that between the station of Naples Capodimonte and NDHOS (Figure 11) there exists a significant homogeneity (constant slope of the double-mass curve), but also a substantial coincidence between the historical series (the curve of the double-mass overlaps the straight line with 45° slope).

geography-natural-disasters-Double-mass-curve-station-Naples

Figure 11: Double-mass curve between the station of Naples Capodimonte and NDHOS.

On the basis of such considerations, it has been possible to build for the city of Naples (Figure 12) a historical series of precipitations 182 years long (from 1821 until to 2003), integrating the lacking data into the series of Naples Capodimonte with those of the series of NDHOS. In more than 160 years, the maximum value of rainfall at Capodimonte (391.3 mm/month) was registered in October 1918 (Figure 13 and Table 3); in the same month the maximum value was registered at Naples University (391.0 mm/month). Perhaps due to the infrequent rainfalls in the nine previous months, no landslide phenomena were observed in relation to such values. The maximum rainfall at NDHOS was registered in November 1985 (397.8 mm/month). Values exceeding 300 mm/month occurred at Capodimonte five times between 1821 and 2003 (352.0 mm, November 1851; 302.0 mm, November 1862; 300.9 mm, October 1910; 328.9 mm, November 1980; 301.4 mm, November 1985). But values of 200 mm/month have been recorded 78 times with a concentration in the autumn season, 20 times in October, 18 times in November and 22 times in December.

geography-natural-disasters-Annual-rainfalls-Naples-Capodimonte

Figure 12: Annual rainfalls at Naples Capodimonte (1821-2003).

geography-natural-disasters-Maximum-monthly-Naples

Figure 13: Maximum monthly precipitation at Naples.

Month NDHOS Naples University Naples Capodimonte
Y. O. Aver. Max. Min. Y. O. Aver. Max. Min. Y. O. Aver. Max. Min.
Jan 71 104.1 269.8 4 117 101.5 280.2 2.8 168 99 276.4 0.1
Feb 71 81.9 236.6 0 118 77.7 228.6 0.2 166 75.2 219.1 0
Mar 71 70.1 254.2 0.8 118 72.7 203.6 1.1 169 71.7 222.2 0
Apr 71 64.5 185.4 3.1 118 64.7 186.8 1.5 168 62.9 217.3 0
May 71 48.1 151.1 0 118 47.3 161.3 1.9 169 48.9 191.2 0
Jun 71 30.4 124 0.2 117 32.2 169 0 169 32.8 170.8 0
Jul 71 16.1 82 0 118 17.3 155 0 168 16.2 147.2 0
Aug 71 30.3 119.6 0 117 26.4 98.4 0 169 28.6 174.1 0
Sep 70 77.3 258.2 0 116 72.4 244.9 0 169 76.2 223.5 0
Oct 70 110.4 243.2 1 117 119.9 391 0 168 115.3 391.3 2.6
Nov 70 136.2 397.8 11.8 117 125.4 319 9.6 168 122.8 352 10.2
Dec 70 116.1 262.4 10.8 117 123.4 284.6 12.8 166 117.6 282.2 0.4
Year 70 887 1374.8 613.8 117 879.9 1385.3 478.5 163 871.1 1410.9 415.4

Table 3: Summarizing table of statistical data of monthly precipitation at Naples (Y. O. years of observations).

These studies analyzed a particular period of time to compare groups of landslide phenomena and monthly precipitation. This correlation shows a correspondence between more severe sliding phenomena and periods of precipitation characterized by higher seasonal rain level rather than a maximum monthly precipitation. Geologic configuration and analysis of recurrent landslide phenomena characterizing the area led to refer the main mass movement occurred in conjunction with the storm events to soil slide debris/earth flows mechanisms.

Discussion and Conclusions

The meteorological events that hit Campania region highlighted that the ability to obtain accurate estimates of spatial variability in rainfall fields becomes crucial for the identification of locally intense storms that could lead to flash-floods or debris/mud flow.

The accurate estimation of the spatial distribution of rainfall during extreme events requires a very tight network of instruments. The intense phenomena, in fact, have often an extension smaller than the current areal resolution of the network so that they will slip through the network undetected.

The extremely high hourly time and space variability observed at the nearest stations, with intensity peaks many times above the average, was a direct consequence of sparse but intense rainy cells.

All the physical-mathematical efforts to overcome the network weakness were doomed to fail from the start. Inadequate network resolution could never be recovered by mathematical or stochastic procedures of interpolation. Such methods can perform accurate estimations of areal precipitation when the density of network is able to describe spatial variability in rainfall fields. The increase in the measuring capability of a measuring network must always occur through its strategic enlargement resulting in a compromise between the increase of fractal dimension and topographic necessities.

Appreciating the fractal dimension of a network and its limits of validity is the key to understand the limits of reliability of an inhomogeneous distribution of measuring stations. The areal distribution of the stations will be repeated on different scales in the same manner inside the scaling region, the main variable being the fractal dimension D. The areal phenomena, with an extension smaller than the areal resolution of the network or spatially clustered with a fractal dimension smaller than the dimensional deficit of the network, will slip through the network undetected even if the network is infinite. A good way to increase the measuring capability of an existing network is the addition of new stations able to increase both the fractal dimension and the relative scaling region.

Denser rain-gauge coverage of NDHOS network has been designed with the installation of new stations having as primary objective the achievement of hydrological necessities. This type of network enlargement may, however, determine an increase of the areal clustering of stations and so a decrease of the fractal dimension with all the above-mentioned negative consequences. To mitigate such a risk, it has been proposed that, as a preliminary measurement, one third of all additive stations be located in places whose co-ordinates allow also the increase of the historical fractal dimension. Mazzarella and Tranfaglia [6] obtained a network constituted by 300 stations with D=1.89+0.01, confident at a level higher than 99%, a linear resolution of 2 km and a dimensional deficit of 0.11. The enlarged network, which arose as a compromise between fractal and topographic necessities, shows a higher capability of rain-field restoring, with a dimensional deficit and a resolution ranging from 0.16 to 0.11 and from 4 km to 2 km, respectively.

The meteorological event that hit the cities of Naples and Pozzuoli on 15 September 2001 was undoubtedly one of the most intense events ever recorded on the territory of NDHOS.

The isohyetal map, drawn up on the basis of the recorded values, shows that the event was rather restricted. The flooded area comprised in the 80 mm isohyet (equal to the maximum rainfall ever recorded in a 3 hour time frame in more than 150 years in Naples) extends up to the northern slopes of the Vesuvius.

The metropolitan area of Naples is characterized by a widespread risk of landslide phenomena (not catastrophic but however not negligible), which occur with a certain frequency in the whole district. It has been observed that generally rock falls occur in the whole area, while collapse of underground cavities is mainly localised in the historical center. Floods are common in the whole area except in the historical center, where only four cases are reported and lahars only occurred in the eastern part of the city and are closely related to the 1906-1918 eruption cycles of the Somma-Vesuvius.

A correlation between monthly precipitation and type of sliding phenomena has been performed. It shows a relation between more severe sliding phenomena and periods of precipitation characterized by a higher seasonal rain level rather than a maximum monthly precipitation.

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1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

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1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

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1-702-714-7001Extn: 9039

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Stephanie Skinner

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1-702-714-7001Extn: 9039

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Nimmi Anna

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1-702-714-7001Extn: 9038

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Nathan T

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1-702-714-7001Extn: 9041

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Ann Jose

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1-702-714-7001Extn: 9007

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Steve Harry

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1-702-714-7001Extn: 9042

 
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