# Implementation and Use of a Mechanical Cone Penetration Test Database for Liquefaction Hazard Assessment of the Coastal Area of the Tuscany Region

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## Abstract

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## 1. Introduction

- structures resting on a liquefied soil could suffer relevant differential settlements, tilting, or overturning;
- buried structures are subject to hydraulic heave;
- in free-field conditions, pore water pressure increase and ejecta of sand could damage lifeline systems and several infrastructures;
- instabilities of both natural and artificial slopes can be triggered.

_{L}) at each investigated depth of the soil profile. The FS

_{L}is inferred by the ratio between the cyclic resistance ratio (CRR) and the cyclic stress ratio (CSR), which represent the shear strength of the soil and the earthquake-induced shear stress, respectively. Sampling in sandy deposits is very difficult, time consuming, and costly. Therefore, CRR is inferred from in situ tests, typically Standard Penetration Test SPT [14,15,17], cone penetration test (CPT) [18,19,22,23,24,25,26], shear wave velocity [27,28], self-boring pressuremeter test (SBPT) [29], and flat dilatometer test (DMT) [30,31]. The CSR, which represents the amplitude of the seismic demand, is generally assessed via simplified formulations defined in the LEPs.

_{L}has been evaluated at different depths, an index assessing the effects of liquefaction in terms of damage severity at ground level should be selected and then used for defining liquefaction hazard maps.

_{c}, sleeve friction f

_{s}, and pore pressure u

_{2}are measured every 1 or 2 cm of penetration). Additionally, the acronym CPTm indicates a static penetration test that has been carried out using a mechanical tip (also called Begemann-type tip in this paper), which provides q

_{c}and f

_{s}every 20 cm [35]. CPT-based LEPs were developed with reference to CPTu tests. However, in many countries, huge CPTm databases are available. Therefore, it has become important to develop specific procedures enhancing the liquefaction potential evaluation and soil profile reconstruction via existing CPTm databases.

_{c}and f

_{s}) and CPTu measurements (q

_{c}, f

_{s}, and u

_{2}) are available every 20 and 2 (or 1) cm, respectively. This results in difficulties, in the case of CPTm, in identifying very thin liquefiable layers as shown in [22,23] and in Boulanger and DeJong [36]. Moreover, CPTu allows users to measure excess pore pressure during the cone penetration, which is relevant for evaluating the total tip resistance (q

_{t}) and improving the capability of correctly identifying the soil behavior type (SBT) [37]. It is also possible to identify the normalized soil behavior type (SBTn), which is especially recommended at greater depths [35,38,39].

_{s}) measured by using the Begemann cone (CPTm) is systematically greater than that obtained with the piezocone (see, as an example, Lo Presti et al. [30]). As both f

_{s}and q

_{c}are used to identify the SBT (or SBTn), it is obvious that differences in terms of f

_{s}and q

_{c}could affect the assessment of the FS

_{L}. On the other hand, while differences in terms of f

_{s}are measurable, those in terms of q

_{c}are quite negligible [40].

_{C}), which was developed with reference to CPTu, tends to underestimate the grain size (for more details, see Section 4.3). Consequently, loose sands could be erroneously identified as silt mixtures [41,42,43], which in turn leads to an overestimation of the safety factor against liquefaction, FS

_{L}. Indeed, the presence of fines leads to an increase in the soil resistance according to the available LEPs.

_{s}measured with CPTm and that obtained from CPTu. Such a correlation was obtained by comparing some pairs of CPTu and CPTm that were carried out in the Pisa plain (Tuscany, Italy). In any case, it is worthwhile to remember that the considered stratigraphy involves both sand, clay, and silt mixture layers. The second correction procedure modifies I

_{C}as obtained from CPTm. The correction factor of the classification index (ΔI

_{C}) is a function of the measured cone tip resistance (q

_{c}).

## 2. Implementation of the CPT Database of the Tuscany Region

- CPT test database from the Tuscany region (managed by the consortium LaMMA), and available on [45];
- CPT test database available from the seismic microzonation studies of the municipalities of the Tuscany region;
- CPT test database from the provinces of the Tuscany region.

## 3. Main Geological Features and Historical Liquefaction of the Study Area

## 4. CPT-Based Assessment of Liquefaction Hazard

_{L}) within an LPI framework. The factor of safety was inferred by using the ratio between the cyclic resistance ratio (CRR) and the cyclic stress ratio (CSR) and applying the overburden correction factor (K

_{σ}) and the magnitude scaling factor (MSF). The CSR, which represents the seismic demand, is computed according to Equation (1) [1]:

_{v}and ${{\sigma}^{\prime}}_{v}$ are the total and effective geostatic stress, respectively; a

_{s}is the free-field peak ground acceleration at the ground surface of the site of interest; g is the gravity; and r

_{d}is a stress reduction factor accounting for the distribution along depth of the shear stress amplitude (soil flexibility). On the whole, both a

_{s}and r

_{d}should be inferred from site-specific true nonlinear seismic response analysis, accounting for soil strength [48,49,50]. This is difficult in the case of liquefiable deposits and out of the scope of the present paper. Therefore, in this work, a

_{s}was evaluated at each site following the Italian Building Code [46]. The Italian Building Code provides site-dependent parameters at the nodes of a squared grid of 0.05° size, which covers the entire Italian territory, to define the seismic hazard for each prescribed exceedance probability within a reference period, and thus for each return period. These parameters are as follows: a

_{g}, F

_{0}, and T

_{C}* and represent the maximum free-field acceleration for a rigid reference site with horizontal topographical surface, the maximum spectral amplification factor, and the period above which the spectral velocity is constant, respectively. The a

_{s}value for a given return period is then obtained as the product of a

_{g}and the amplification factors S

_{S}and S

_{T}, accounting for the stratigraphy and the topography of the considered site. In particular, the S

_{S}amplification factor depends on the ground type, thus on the average shear wave velocity of the first 30 m. In other words, the peak ground acceleration was evaluated on the basis of a probabilistic approach including all scenarios. Moreover, for the present study, three different LEPs were used, as more clearly specified later on. The Boulanger and Idriss [24] and the Juang et al. [19] approaches were applied exactly according to their original formulation. For these methods, the stress reduction factor r

_{d}was computed according to Equations (2) to (4) [21], in which M

_{W}is the earthquake moment magnitude. The Robertson and Wride [16] method does not clearly define the K

_{σ}, MSF, and r

_{d}factors. Indeed, Robertson and Wride [16] suggest, according to Youd et al. [17], to use the r

_{d}factor defined by Liao and Whitman [51] and the MSF according to the range suggested by Youd et al. [17]. No indication is given as for the K

_{σ}factor. Therefore, for this method, we decided to use the same factors as for the Boulanger and Idriss [24] LEP. Of course, such an assumption could be questionable.

_{1}= 1 − FS

_{L}for FS

_{L}≤ 1 and F

_{1}= 0 for FS

_{L}> 1; W(z) is a depth weighting function given by W(z) = 10 − 0.5z; and z is the depth in meters below the ground surface. The LPI can range thus from 0 to a maximum of 100 (i.e., where FS

_{L}is zero over the entire 20 m depth). The level of liquefaction severity can be defined according to the categories suggested by Sonmez [34] or by Iwasaki et al. [32]. In this work, the categories defined in [32] are considered, which assumes for LPI = 0 that a site is not likely to liquefy and for 0 < LPI < 5, 5 < LPI < 15, and LPI > 15 there is a low, high, and very high liquefaction severity, respectively.

#### 4.1. Definition of the Seismic Demand

_{R}) of 50 years was considered, and assuming an exceedance probability (p

_{L}) of 10% in the reference period, a return period (T

_{R}) of 475 years is obtained using Equation (6) [46]:

_{T}was assumed equal to 1, thus considering the topographic area as flat. The factor S

_{S}was inferred from the Italian Building Code [46], assuming a ground type C, which means a stratigraphic profile characterized by an average shear wave velocity of the first 30 m between 180 and 360 m/s. Table 4 shows the values of the free-field peak ground acceleration (a

_{s}) at each municipality considered in this study. The moment magnitude M

_{W}(necessary for determining the magnitude scaling factor (MSF)) was first determined by the disaggregation of the seismic hazard for a return period of 475 years [52]. For all the municipalities in the study area, the modal values of M

_{W}(from disaggregation) are between 4.5 and 5.0 (Figure 3). On the other hand, the average values of M

_{W}(Figure 4) for some municipalities are between 4.5 and 5.0, while for others they were between 5.0 and 5.5. For simplicity, it was decided to use a unique value, M

_{W}= 5.5 (corresponding to the upper limit), for all the municipalities of the study area. From a theoretical point of view, the assumption of a unique value of magnitude means considering a single-scenario earthquake. From a practical point of view, such an assumption is responsible, in some municipalities, for a negligible underestimation of the safety factor (less than 8%). It is worth mentioning that the moment magnitude affects the MSF. Indeed, the earthquake duration (i.e., the number of cycles of equivalent amplitude) increases with the magnitude, which in turn influences the CRR (i.e., the factor of safety against liquefaction). The factor of safety increases as magnitude (M

_{W}) decreases.

#### 4.2. Considered Liquefaction Evaluation Procedures (LEPs)

_{c1N,cs}is the normalized tip resistance corrected to account for the overburden stress and the fine content (FC) and is computed using Equations (9) and (10):

_{atm}is the atmospheric pressure, q

_{c}is the measured tip resistance; the n exponent is assumed equal to 1.0 for clayey soil, 0.5 for sandy soil, and 0.75 for silt mixtures; and K

_{C}is a correction factor that is computed through Equations (11) and (12):

_{C}is the soil classification index as defined by Robertson and Wride [16] (Equations (13)–(15)):

_{s}is the measured sleeve friction.

_{0}(=2.6 ± 0.2) is a fitting parameter and q

_{c1N,cs}is defined by Equation (17), which requires an iterative procedure by using Equations (18) to (22):

_{FC}is a fitting parameter (see Boulanger and Idriss [24] for the suggested value) and I

_{C}can be computed using Equation (13) or according to Robertson [38].

_{σ}) is computed by using Equations (23) and (24), whereas the MSF is computed by using Equations (25) and (26):

_{c1N,m}(Equation (28)) is the stress-normalized tip resistance q

_{c1N}(Equation (18)) adjusted for the fine effect. In the Juang et al. [19] LEP, q

_{c1N}is computed via an iterative procedure involving Equations (18) to (20). Please note that, in Equation (20), the term q

_{c1N,cs}is replaced by the term q

_{c1N}:

_{C}is defined in a slightly different way as compared to that defined by Robertson and Wride [16]:

_{σ}is computed again with Equation (23); nevertheless, C

_{σ}is defined by Equation (33):

_{L}) is computed with Equation (35):

_{s}and estimated I

_{C}become mandatory, according to the suggestions provided in the works of Meisina et al. [41,42] and briefly described in Section 4.3. These corrections are independent from each other.

#### 4.3. CPTm Correction Procedure

- the first correlation is between f
_{s}measured with CPTm and that obtained from CPTu; - the second correlation is between the correction factor (ΔI
_{C}) and the cone tip resistance (q_{c}), which is applied in the case of silt mixtures that are non-correctly identified by the SBTn classification system.

_{s}) measured with CPTm and of modifying the estimated value of the soil classification index (I

_{C}) as obtained by interpreting the CPTm data.

_{C}is only used for improving the soil classification (SBTn), thus it is not applied to Equations (11), (12), (22), and (29)–(31) in which the uncorrected value is still considered. In fact, the use of the SBTn classification system [16,38,39], which is based on CPTu, for the interpretation of CPTm leads on several occasions to an underestimation of the soil grain size, which in turn means an overestimation of I

_{C}.

_{C}correction is only intended to improve the identification of potentially liquefiable layers, i.e., those layers having an I

_{C}less than the I

_{C}cut-off value. The latter value (I

_{C}cut-off) is used to screen out clay-like soils and is commonly taken between 2.4 and 2.6 [24]. It is worthwhile to remember that those layers with I

_{C}higher than I

_{C}cut-off are assumed to be non-liquefiable, thus are not considered in the computation of the LPI.

#### 4.3.1. Sleeve Friction (f_{s}) Correction

_{s}(CPTm), and that from CPTu, f

_{s}(CPTu), as obtained from pairs of adjacent CPTm-CPTu tests. These tests were carried out at a site in Pisa (central Italy). At the Pisa site, a total of 12 penetration tests (3 CPTm and 9 CPTu) were carried out using a Pagani TG 73/200 penetrometer (Pagani Geotechnical Equipment, Piacenza, Italy) [53]. The capabilities of these tests in identifying the soil layering were also verified due to the availability of three continuous boreholes. The soil stratigraphy at the test site in Pisa is very similar to that existing beneath the Leaning Tower of Pisa [49,50,54,55] and consists of an upper thin layer of silty clay and a thick layer of marine soft clay with an interbedded layer of sand (between 7 and 8 m depth). The piezometric surface is located about 1 m below the ground level (GWT). The site was also characterized by a very low horizontal variability. Then, the empirical correlation between f

_{s}(CPTm) and f

_{s}(CPTu) was established after defining a reasonable strategy for coupling the measured values of f

_{s}via the two different test types (CPTm and CPTu). Each value of f

_{s}(CPTm) was coupled with an f

_{s}(CPTu) value obtained averaging the value of f

_{s}at the same depth of the f

_{s}(CPTm) with the two values immediately above and below this depth. Pairs of f

_{s}(CPTm) and f

_{s}(CPTu) values were excluded from the comparison when the corresponding tip resistances (q

_{c}(CPTm) and q

_{c}(CPTu)) exhibited a difference higher than 0.25 MPa. This limit was established to exclude the comparison between different soil types. Figure 5 shows the ratio f

_{s}(CPTu)/f

_{s}(CPTm) vs. f

_{s}(CPTu) and the obtained interpolation curve.

_{s}< 65 kPa. Thus, f

_{s}(CPTm) can be corrected according to Equations (36) and (37) in order to obtain a reasonable estimate of the corresponding value of f

_{s}(CPTu).

#### 4.3.2. Soil Classification Index I_{C} Correction

_{C}, as a function of the cone tip resistance (q

_{c}) was suggested by Meisina et al. [41]. ΔI

_{C}was defined by establishing a correspondence between the soil classes of the Schmertmann chart [56] and the SBTn classes [16,38,39] (Table 5). For this purpose, a database of 78 CPTm was used. Tests had been carried out in Mirabello, San Carlo, and Sant’Agostino (municipalities located in Emilia-Romagna region and hit by the 2012 Emilia-Romagna seismic sequence). Test results were interpreted using both the Schmertmann [56] and SBTn classification systems. A total of 6141 CPTm measurements were used and the correspondence between these two classification systems, as shown in Table 5, was checked. A perfect match between these systems was achieved in 35% of the cases, and was mainly observed for SBTn classes 3, 4, and 5. The SBTn system underestimated of one and two classes the Schmertmann [56] classification in 24% and 16% of the cases, respectively, while it overestimated of one and two classes the Schmertmann classification in 20% and 5% of the cases, respectively. The SBTn overestimate (OE) mainly concerned clayey soils and the SBTn underestimate (UE) was especially observed in sandy soils.

_{C}, to have a correct match between the two classification systems (Table 5) was thus defined. The proposed correction applies only when the Robertson [38] classification underestimates that of Schmertmann [56] (Equation (38)):

_{C}(OV) is the computed I

_{c}index (Equation (13)) according to the SBTn system (Robertson, [38]; Robertson and Wride [16]) and I

_{C}(PM) is the central value of I

_{C}(Table 5) corresponding to the SBTn class that matches the Schmertmann [56] classification (clayey soils were not considered). Figure 8 shows the correction factor ΔI

_{C}as a function of q

_{c}.

_{C}and the q

_{c}inferred by cone testing with a mechanical tip (CPTm) is defined by Equation (39) and should be applied to the I

_{C}index (Equation (13)), obtained according to Robertson [38] and Robertson and Wride [16], as shown in Equation (40):

## 5. Liquefaction Hazard Assessment: CPTu vs. CPTm

_{s}and estimated I

_{C}, permits to obtain LPI values which are closer to or higher than those obtained from CPTu tests (Figure 9). This is clearly shown in Figure 12 in which the LPI by CPTu and the LPI by CPTm (with and w/o corrections) are compared when considering the LEPs developed by Boulanger and Idriss [24] and Juang et al. [19]. In any case, there is no historical evidence of liquefaction phenomena in the study areas (Tuscany) to confirm the correctness of the predictive capacity of the considered LEPs.

_{c}, f

_{s}

_{,}and computed I

_{C}(Robertson and Wride [16]) profiles as obtained from CPTu (black continuous line) and CPTm (red dashed line). Corrected f

_{s}and I

_{c}values are those blue points that are not located above the red dashed lines (uncorrected CPTm data). In this site, the GWT was located 2.0 m below the ground level. The correction procedure mainly modifies the f

_{s}and I

_{C}values between 1–2 and 5–8 m in depth. Therefore, the corrected values of f

_{s}and I

_{C}modify the LPI.

## 6. Liquefaction Hazard Assessment for the Study Area

- (1)
- for the Versilia macro-area (Table 7, Figure 15), where most of the available tests were carried out down to depths of 5–8 m (31%) and 8–10 m (24%), the three LEPs without applying the f
_{s}and I_{c}corrections agree to recognize a zero or low severity for most of the tests. After applying the corrections described in Section 4.3 to the Robertson and Wride [16] method, the high severity and very high severity classes increase from 11.9% and 2.0% to about 45.5% and 20.8%, respectively (considering only those tests with depths equal to or higher than 15 m). When the corrections are applied to the Boulanger and Idriss [24] and Juang et al. [19] approaches, the increase in the high and very high severity classes is less dramatic, especially for the very high severity class (LPI > 15); - (2)
- for the macro-area of the Lucca plain (Table 8, Figure 16), where 40% and 24% of the available tests were carried out down to depths of 5–8 m and 8–10 m, respectively, the three LEPs without applying the f
_{s}and I_{c}corrections agree to classify all the tests in the zero or low severity classes. Very different results are obtained after applying the corrections. In fact, only 30.5% of the tests remain in the low, 42.4% fall in the high, and 23.7% in the very high severity class by using the LEP by Robertson and Wride [16] (considering only those tests with depths equal to or higher than 10 m). After applying the corrections to the Boulanger and Idriss [24] and Juang et al. [19] approaches, especially the very high severity class increases in a negligible way; - (3)
- for the macro-area of the Pisa plain (Table 9, Figure 17), where 49%, 17%, and 6% of the available tests were carried out down to depths of 8–10 m, 10–15 m, and greater than 20 m, respectively, the three LEPs without applying the f
_{s}and I_{c}corrections agree to classify most of the tests in the zero or low liquefaction severity classes. After applying the corrections, the three LEPs exhibit the same trend that was observed for the other two macro-areas, even though with different percentages.

- the study area could be split into two main classes: urbanized areas that have existed for many centuries and areas that were only urbanized after the Second World War. More specifically, the near-sea plains were uninhabited until the end of the Second World War. Indeed, these areas have only been urbanized since the 1960s. The database was developed mainly to help in evaluating the liquefaction risk in recently urbanized areas;
- on the other hand, there is no historical evidence of relevant liquefaction phenomena in the historically inhabited areas. Therefore, for those areas, a low to moderate liquefaction risk is expected;
- a similar or not very different picture is expected for recently urbanized areas in the case of the same geological features (Holocene, alluvial deposits mainly consisting of sand and silt mixtures);
- it has been shown that the Robertson and Wride [16] approach gives higher values of the LPI. On the other hand, the applied corrections have the only aim of obtaining the same predictions from both CPTm and CPTu. The results obtained with this approach could have been affected by the assumptions we made regarding some factors (i.e., r
_{d}, MSF and K_{σ});

## 7. Conclusions

- when the corrections are applied to CPTm, the three considered LEPs predict the same severity class inferred from CPTu;
- in any case, the Robertson and Wride [16] approach leads to a conservative estimate of LPI, whereas the Boulanger and Idriss [24] and Juang et al. [19] approaches lead to less conservative LPI estimates. Nevertheless, the estimates obtained by using the Boulanger and Idriss [24] and Juang et al. [19] methods are closer to those obtained from CPTu tests, at least for the CPTm-CPTu pairs compared herein.

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

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**Figure 2.**Areas geologically prone to liquefaction in the study area (adapted from Galli and Meloni [47]).

**Figure 6.**Soil classification from the CPTm results according to Robertson [38].

**Figure 7.**Soil classification from the CPTm results according to Schmertmann [56].

**Figure 9.**Comparison between the values of the Liquefaction Potential Index (LPI) obtained with CPTu by using all the considered liquefaction evaluation procedures (LEPs). B.I. = Boulanger and Idriss; R.W. = Robertson and Wride.

**Figure 10.**Comparison between the values of the LPI obtained with uncorrected CPTm data by using all the considered LEPs. B.I. = Boulanger and Idriss; R.W. = Robertson and Wride.

**Figure 11.**Comparison between the values of the LPI obtained with corrected CPTm data by using all the considered LEPs. B.I. = Boulanger and Idriss; R.W. = Robertson and Wride.

**Figure 13.**q

_{c}(z), f

_{s}(z), and I

_{C}(z) profiles (CPTu 13, CPTm 6, and CPTm 6 corrected, Vicchio site).

**Figure 14.**LPI(z) profiles obtained by using the three LEPs considered (CPTu 13, CPTm 6, and CPTm 6 corrected).

Municipality | n CPTm | n CPTu | 0 < z ≤ 5 m | 5 < z ≤ 8 m | 8 < z ≤ 10 m | 10 < z ≤ 15 m | 15 < z ≤ 20 m | >20 m |
---|---|---|---|---|---|---|---|---|

Camaiore | 103 | 13 | 2 | 31 | 63 | 19 | 0 | 1 |

Carrara | 18 | - | 2 | 12 | 2 | 0 | 2 | 0 |

Forte dei Marmi | 91 | - | 3 | 27 | 53 | 8 | 0 | 0 |

Massa | 77 | - | 19 | 30 | 20 | 7 | 1 | 0 |

Massarosa | 93 | - | 2 | 31 | 30 | 25 | 3 | 2 |

Montignoso | 79 | - | 9 | 14 | 9 | 26 | 21 | 0 |

Pietrasanta | 188 | - | 21 | 70 | 49 | 25 | 21 | 2 |

Serravezza | 33 | - | 5 | 7 | 13 | 8 | 0 | 0 |

Viareggio | 87 | - | 7 | 24 | 28 | 20 | 8 | 0 |

TOTAL | 769 | 13 | 70 | 246 | 267 | 138 | 56 | 5 |

Municipality | n CPTm | n CPTu | 0 < z ≤ 5 m | 5 < z ≤ 8 m | 8 < z ≤ 10 m | 10 < z ≤ 15 m | 15 < z ≤ 20 m | >20 m |
---|---|---|---|---|---|---|---|---|

Bientina | 347 | - | 5 | 85 | 170 | 58 | 15 | 14 |

Buti | 88 | - | 24 | 17 | 30 | 15 | 0 | 2 |

Calci | 22 | - | 15 | 5 | 2 | 0 | 0 | 0 |

Calcinaia | 206 | - | 1 | 21 | 148 | 23 | 13 | 0 |

Cascina | 510 | - | 7 | 79 | 299 | 69 | 22 | 34 |

Collesalvetti | 223 | - | 5 | 30 | 84 | 43 | 29 | 32 |

Crespina | 53 | - | 3 | 7 | 25 | 13 | 4 | 1 |

Fauglia | 50 | - | 4 | 7 | 24 | 8 | 6 | 1 |

Lari | 129 | - | 8 | 18 | 68 | 13 | 21 | 1 |

Livorno | 17 | - | 0 | 0 | 8 | 5 | 1 | 3 |

Pisa | 488 | - | 14 | 64 | 168 | 133 | 60 | 49 |

Ponsacco | 338 | - | 7 | 57 | 198 | 47 | 26 | 3 |

Pontedera | 534 | 3 | 8 | 83 | 301 | 88 | 25 | 32 |

San Giuliano Terme | 156 | - | 15 | 19 | 73 | 32 | 3 | 14 |

Vicopisano | 93 | - | 8 | 21 | 47 | 14 | 3 | 0 |

Vecchiano | 199 | - | 32 | 48 | 46 | 31 | 22 | 20 |

TOTAL | 3453 | 3 | 156 | 561 | 1691 | 592 | 250 | 206 |

Municipality | n CPTm | n CPTu | 0 < z ≤ 5 m | 5 < z ≤ 8 m | 8 < z ≤ 10 m | 10 < z ≤ 15 m | 15 < z ≤ 20 m | >20 m |
---|---|---|---|---|---|---|---|---|

Altopascio | 53 | - | 9 | 26 | 9 | 8 | 1 | 0 |

Capannori | 100 | - | 22 | 34 | 28 | 9 | 7 | 0 |

Lucca | 80 | - | 25 | 40 | 14 | 1 | 0 | 0 |

Porcari | 45 | - | 2 | 11 | 17 | 15 | 0 | 0 |

TOTAL | 278 | 0 | 58 | 111 | 68 | 33 | 8 | 0 |

**Table 4.**Free-field peak ground acceleration (a

_{s}) at each municipality, according to NTC (2018) [46].

Florence | Massa Carrara | ||

Municipality | a_{s} (g) | Municipality | a_{s} (g) |

Vicchio | 0.320 | Carrara | 0.206 |

Montignoso | 0.212 | ||

Massa | 0.200 | ||

Livorno | Pisa | ||

Municipality | a_{s} (g) | Municipality | a_{s} (g) |

Livorno | 0.182 | Bientina | 0.175 |

Collesalvetti | 0.208 | Buti | 0.180 |

Lucca | Calci | 0.179 | |

Municipality | a_{s} (g) | Calcinaia | 0.180 |

Altopascio | 0.191 | Cascina | 0.180 |

Camaiore | 0.188 | Crespina | 0.210 |

Capannori | 0.200 | Fauglia | 0.209 |

Forte dei Marmi | 0.192 | Lari | 0.210 |

Lucca | 0.196 | Pisa | 0.177 |

Massarosa | 0.189 | Ponsacco | 0.203 |

Pietrasanta | 0.196 | Pontedera | 0.190 |

Porcari | 0.195 | San Giuliano Terme | 0.182 |

Viareggio | 0.182 | Vicopisano | 0.178 |

Serravezza | 0.210 | Vecchiano | 0.181 |

Schmertmann [56] | I_{C} (PM) | SBTn [38] | I_{C} (SBTn) | SBTn Class Description |
---|---|---|---|---|

Organic clay and mixed soils | - | 2 | I_{C} > 3.60 | Organic soils, peats |

Insensitive non-fissured inorganic clays | 3.275 | 3 | 2.95 < I_{C} < 3.60 | Clays: clay to silty clay |

Sandy and silty clays | 2.775 | 4 | 2.60 < I_{C} < 2.95 | Silt mixtures: silty sand to sandy silt |

Clayey sands and silts | 2.325 | 5 | 2.05 < I_{C} < 2.60 | Sand mixtures: silty sand to sandy silt |

Silt–sand mixtures | 2.325 | 5 | 2.05 < I_{C} < 2.60 | Sand mixtures: silty sand to sandy silt |

Sands | 1.68 - | 6 7 | 1.31 < I_{C} < 2.05I _{C} < 1.31 | Sands: clean sand to silty sand Gravely sands to sands |

Dense or cemented sands | - | 8 | - | Very stiff sand to clayey sand |

Very shell sands, lime rocks | - | 8 | - | Very stiff sand to clayey sand |

CPTu | CPTm | Distance (m) | GWT (m) | Region | Municipality | a_{s} (g) | Magnitude |
---|---|---|---|---|---|---|---|

28000599_CPT_6688 | 28000599_CPT_6666 | 38.70 | 3.12 | Tuscany | Pontedera | 0.19 | 5.5 |

28000599_CPT_6690 | 28000599_CPT_6669 | 29.82 | 2.62 | Tuscany | Pontedera | 0.19 | 5.5 |

28000599_CPT_6689 | 28000599_CPT_9995 | 18.77 | 3.43 | Tuscany | Pontedera | 0.19 | 5.5 |

CPTU1 | 00405 | 159.58 | 2.00 | Tuscany | Camaiore | 0.188 | 5.5 |

CPTU4 | 00634 | 99.18 | 1.80 | Tuscany | Camaiore | 0.188 | 5.5 |

CPTU7 | 00224 | 147.80 | 1.95 | Tuscany | Camaiore | 0.188 | 5.5 |

CPTe11 | CPT1 | 2.00 | 2.0 | Tuscany | Vicchio | 0.32 | 6.37 |

CPTe12 | CPT3 | 2.00 | 2.0 | Tuscany | Vicchio | 0.32 | 6.37 |

CPTe13 | CPT6 | 2.00 | 2.0 | Tuscany | Vicchio | 0.32 | 6.37 |

CPTe15 | CPT9bis | 10.00 | 2.0 | Tuscany | Vicchio | 0.32 | 6.37 |

CPTu (203010U502) | CPT (203010C121) | 13.00 | 1.20 | Emilia-Romagna | Sant’Agostino | 0.21 | 5.9 |

CPTu (185130U508) | CPT (185130C142) | 36.00 | 3.80 | Emilia-Romagna | Sant’Agostino | 0.21 | 5.9 |

CPTu (185130U512) | CPT (185130C137) | 36.00 | 4.50 | Emilia-Romagna | Sant’Agostino | 0.21 | 5.9 |

CPTu (185130U514) | CPT (185130C135) | 24.00 | 4.55 | Emilia-Romagna | Sant’Agostino | 0.21 | 5.9 |

LPI | Boulanger and Idriss [24] | Boulanger and Idriss [24] Corrected | Robertson and Wride [16] | Robertson and Wride [16] Corrected | Juang et al. [19] | Juang et al. [19] Corrected |
---|---|---|---|---|---|---|

LPI = 0 | 21 (20.8%) | 6 (5.9%) | 16 (15.8%) | 2 (2.0%) | 24 (23.8%) | 13 (12.9%) |

0 < LPI ≤ 5 | 67 (66.3%) | 49 (48.5%) | 71 (70.3%) | 32 (31.7%) | 59 (58.4%) | 29 (28.7%) |

5 < LPI ≤ 15 | 13 (12.9%) | 35 (34.7%) | 12 (11.9%) | 46 (45.5%) | 17 (16.8%) | 46 (45.5%) |

LPI > 15 | 0 (0.0%) | 11 (10.9%) | 2 (2.0%) | 21 (20.8%) | 1 (1.0%) | 13 (12.9%) |

**Table 8.**Liquefaction severity classes for the macro-area of the Lucca plain (CPTs with depth ≥ 10 m).

LPI | Boulanger and Idriss [24] | Boulanger and Idriss [24] Corrected | Robertson and Wride [16] | Robertson and Wride [16] Corrected | Juang et al. [19] | Juang et al. [19] Corrected |
---|---|---|---|---|---|---|

LPI = 0 | 13 (22.0%) | 3 (5.1%) | 6 (10.2%) | 2 (3.4%) | 14 (23.7%) | 4 (6.8%) |

0 < LPI ≤ 5 | 46 (78.0%) | 37 (62.7%) | 53 (89.8%) | 18 (30.5%) | 45 (76.3%) | 40 (67.8%) |

5 < LPI ≤ 15 | 0 (0%) | 15 (25.4%) | 0 (0%) | 25 (42.4%) | 0 (0%) | 11 (18.6%) |

LPI > 15 | 0 (0%) | 4 (6.8%) | 0 (0%) | 14 (23.7%) | 0 (0%) | 4 (6.8%) |

**Table 9.**Liquefaction severity classes for the macro-area of the Pisa plain (CPTs with depth ≥ 15 m).

LPI | Boulanger and Idriss [24] | Boulanger and Idriss [24] Corrected | Robertson and Wride [16] | Robertson and Wride [16] Corrected | Juang et al. [19] | Juang et al. [19] Corrected |
---|---|---|---|---|---|---|

LPI = 0 | 178 (27.5%) | 9 (1.4%) | 145 (22.4%) | 10 (1.5%) | 160 (24.7%) | 8 (1.2%) |

0 < LPI ≤ 5 | 454 (70.1%) | 171 (26.4%) | 484 (74.7%) | 157 (24.2%) | 471 (72.7%) | 204 (31.5%) |

5 < LPI ≤ 15 | 12 (1.9%) | 275 (42.4%) | 11 (1.7%) | 242 (37.3%) | 12 (1.9%) | 260 (40.1%) |

LPI > 15 | 4 (0.6%) | 193 (29.8%) | 8 (1.2%) | 239 (36.9%) | 5 (0.8%) | 176 (27.2%) |

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**MDPI and ACS Style**

Stacul, S.; Magalotti, A.; Baglione, M.; Meisina, C.; Lo Presti, D.
Implementation and Use of a Mechanical Cone Penetration Test Database for Liquefaction Hazard Assessment of the Coastal Area of the Tuscany Region. *Geosciences* **2020**, *10*, 128.
https://doi.org/10.3390/geosciences10040128

**AMA Style**

Stacul S, Magalotti A, Baglione M, Meisina C, Lo Presti D.
Implementation and Use of a Mechanical Cone Penetration Test Database for Liquefaction Hazard Assessment of the Coastal Area of the Tuscany Region. *Geosciences*. 2020; 10(4):128.
https://doi.org/10.3390/geosciences10040128

**Chicago/Turabian Style**

Stacul, Stefano, Aurora Magalotti, Massimo Baglione, Claudia Meisina, and Diego Lo Presti.
2020. "Implementation and Use of a Mechanical Cone Penetration Test Database for Liquefaction Hazard Assessment of the Coastal Area of the Tuscany Region" *Geosciences* 10, no. 4: 128.
https://doi.org/10.3390/geosciences10040128