Surface wave methods gained in the past decades a primary role in many seismic projects. Specifically, they are often used to retrieve a 1D shear wave velocity model or to estimate the V_S,30 at a site. The complexity of the interpretation process and the variety of possible approaches to surface wave analysis make it very hard to set a fixed standard to assure quality and reliability of the results. The present guidelines provide practical information on the acquisition and analysis of surface wave data by giving some basic principles and specific suggestions related to the most common situations. They are primarily targeted to non-expert users approaching surface wave testing, but can be useful to specialists in the field as a general reference. The guidelines are based on the experience gained within the InterPACIFIC project and on the expertise of the participants in acquisition and analysis of surface wave data.

Today, surface-wave analysis is widely adopted for building near-surface S-wave velocity models. The surface-wave method is under continuous and rapid evolution, also thanks to the lively scientific debate among different disciplines, and interest in the technique has increased significantly during the last decade. A comprehensive review of the literature in the main scientific journals provides historical perspective, methodological issues, applications, and most-promising recent approaches. Higher modes in the inversion and retrieval of lateral variations are dealt with in great detail, and the current scientific debate on these topics is reported. A best-practices guideline is also outlined.

Summary. The analysis of surface wave propagation is often used to estimate the S-wave velocity profile at a site. In this paper, we propose a stochastic appro

Higher-mode contribution is important in surface-wave inversion because it allows more information to be exploited, increases investigation depth, and improves model resolution. A new misfit function for multimodal inversion of surface waves, based on the Haskell-Thomson matrix method, allows higher modes to be taken into account without the need to associate experimental data points to a specific mode, thus avoiding mode-misidentification errors in the retrieved velocity profiles. Computing cost is reduced by avoiding the need for calculating synthetic apparent or modal dispersion curves. Based on several synthetic and real examples with inversion results from the classical and the proposed methods, we find that correct velocity models can be retrieved through the multimodal inversion when higher modes are superimposed in the apparent dispersion-curve or when it is not trivial to determine a priori to which mode each data point of the experimental dispersion curve belongs. The main drawback of the method is related to the presence of several local minima in the misfit function. This feature makes the choice of a consistent initial model very important.