# A Geospatial Approach for Mapping the Earthquake-Induced Liquefaction Risk at the European Scale

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## Abstract

**:**

## 1. Introduction

## 2. Overview of the Methodology

## 3. Mega-Zonation of the Earthquake-Induced Liquefaction Risk in Continental Europe

#### 3.1. Mapping the Probability of Liquefaction by Applying A European Prediction Model

- The weighted-mean shear-wave velocity in the top 30 m (V
_{S30}), which was adopted as a proxy of soil stiffness since soft sandy soils are more susceptible to liquefaction (they are looser). The US Geological Survey (https://earthquake.usgs.gov/data/vs30/) provided the global topographic-slope based V_{S30}map and such a map was adopted for Europe; - The weighted-magnitude peak ground acceleration (PGAm), which was computed as

_{S30}map. In doing so, only 1D lithostratigraphic amplification was explicitly considered. MWF stands for Magnitude-Weighting Factor, which is defined by the following equation:

_{S30}). In the logistic regression, the probability of liquefaction is therefore calculated using the following equation:

_{k}are the explanatory variables and γ

_{k}the coefficients of the regression. By integrating the optimal geospatial predictors into Equation (4), the latter can be rewritten as follows:

#### 3.2. Exposure Model for Europe

^{2}unit, which is the most common format to express the population density. The data were grouped into five classes of exposure, as done for the probability of liquefaction in Section 3.1. In particular, the following classes for the population density (Pd) were adopted:

- very low: Pd < 400 inhab./km
^{2}; - low: 400 ≤ Pd 800 inhab./km
^{2}; - medium: 800 ≤ Pd < 2000 inhab./km
^{2}; - high: 2000 ≤ Pd < 5000 inhab./km
^{2}; - very high: Pd ≥ 5000 inhab./km
^{2}.

#### 3.3. Assessment of the Liquefaction Risk at the European Scale by Using the AHP Technique

_{max}− n)⁄(n − 1)

_{max}is the maximum eigenvalue of the judgement matrix and n is the rank of the matrix. CI is then compared with that of a Random Matrix (RI). The corresponding ratio, i.e., CI/RI, is termed the Consistency Ratio (CR). Saaty [8] suggested that the upper threshold value of CR should be 0.1.

#### 3.4. European Charts for Earthquake-Induced Liquefaction Risk

## 4. Discussion and Concluding Remarks

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 1.**Flowchart of the geospatial approach developed in this study for mapping the liquefaction risk at a continental scale.

**Figure 2.**Maps showing the liquefaction potential for the European territory referred to the return period of 475 years [7]. The results are expressed (

**a**) as a binary outcome, i.e., liquefaction or no liquefaction, and (

**b**) according to a chromatic scale based on five different classes of the probability of liquefaction. Locations of liquefaction occurrences (black dots) associated with a return period of about 475 years are superimposed to both charts. The grey areas are a priori excluded because of either the geological-based or the seismic-hazard based filters herein applied (the greyscale is based on Digital Elevation Model, DEM).

**Figure 3.**Exposure model for Europe adopted in this study by combining open-access data on population density and land cover in Europe, used as proxies for urbanized areas and strategic infrastructures, respectively.

**Figure 4.**European liquefaction risk maps were calculated in this study for the return periods of 475 (

**a**), 975 (

**b**), and 2475 (

**c**) years. The grey areas are a priori excluded because of the geological-based and seismic-hazard based filters applied (the greyscale is based on the DEM).

**Table 1.**Application of Analytical Hierarchy Process (AHP) method: relative importance for comparison between different alternatives [8].

Weight/Rank | Relative Importance |
---|---|

1 | equal |

3 | moderately dominant |

5 | strongly dominant |

7 | very strongly dominant |

9 | extremely dominant |

2, 4, 6, 8 | intermediate values |

Reciprocals | for inverse judgements |

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**MDPI and ACS Style**

Bozzoni, F.; Bonì, R.; Conca, D.; Meisina, C.; Lai, C.G.; Zuccolo, E.
A Geospatial Approach for Mapping the Earthquake-Induced Liquefaction Risk at the European Scale. *Geosciences* **2021**, *11*, 32.
https://doi.org/10.3390/geosciences11010032

**AMA Style**

Bozzoni F, Bonì R, Conca D, Meisina C, Lai CG, Zuccolo E.
A Geospatial Approach for Mapping the Earthquake-Induced Liquefaction Risk at the European Scale. *Geosciences*. 2021; 11(1):32.
https://doi.org/10.3390/geosciences11010032

**Chicago/Turabian Style**

Bozzoni, Francesca, Roberta Bonì, Daniele Conca, Claudia Meisina, Carlo G. Lai, and Elisa Zuccolo.
2021. "A Geospatial Approach for Mapping the Earthquake-Induced Liquefaction Risk at the European Scale" *Geosciences* 11, no. 1: 32.
https://doi.org/10.3390/geosciences11010032