Nat. Hazards Earth Syst. Sci., 20, 2547–2565, 2020 https://doi.org/10.5194/nhess-20-2547-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Assessment of the physical vulnerability of buildings affected by slow-moving landslides Qin Chen1, Lixia Chen2, Lei Gui1, Kunlong Yin1, Dhruba Pikha Shrestha3, Juan Du4, and Xuelian Cao2 1Engineering Faculty, China University of Geosciences, Wuhan, 430074, China 2Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, 430074, China 3Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, the Netherlands 4Three Gorges Research Center for Geohazards, China University of Geosciences, Wuhan, 430074, China Correspondence: Lixia Chen ([email protected]) Received: 27 September 2019 – Discussion started: 16 October 2019 Revised: 25 July 2020 – Accepted: 6 August 2020 – Published: 29 September 2020 Abstract. Physical vulnerability is a challenging and funda- hope that the established physical vulnerability curves can mental issue in landslide risk assessment. Previous studies serve as tools for the quantitative risk assessment of slow- mostly focus on generalized vulnerability assessment from moving landslides. landslides or other types of slope failures, such as debris flow and rockfall, while the long-term damage induced by slow- moving landslides is usually ignored. In this study, a method was proposed to construct physical vulnerability curves for 1 Introduction masonry buildings by taking the Manjiapo landslide as an example. The landslide’s force acting on the buildings’ foun- Physical vulnerability is a fundamental and indispensable dation is calculated by applying the landslide residual-thrust item in the risk definition presented by Varnes (1984). It can calculation method. Considering four rainfall scenarios, the be defined as the degree of loss to a given element or set buildings’ physical responses to the thrust are simulated in of elements within an area affected by a hazard (UNDRO, terms of potential inclination by using Timoshenko’s deep- 1984). Physical vulnerability is measured on a continuous beam theory. By assuming the landslide safety factor to be scale ranging from 0 (no loss) to 1 (total loss). For quantify- landslide intensity and inclination ratio to be vulnerability, a ing physical loss, such as the structural damage, the physical physical vulnerability curve is fitted and the relative function vulnerability of the elements at risk can be achieved by as- is constructed by applying a Weibull distribution function. sessing the damage degree, resulting from the occurrence of To investigate the effects of buildings’ parameters that influ- a landslide of a given type and intensity (van Westen et al., ence vulnerabilities, the length, width, height, and founda- 2006). tion depth and Young’s modulus of the foundation are anal- Recently, physical vulnerability has still been a chal- ysed. The validation results on the case building show that lenge, and there has been a growing interest in quantifying the physical vulnerability function can give a good result risk due to natural hazards (van Westen et al., 2006). To in accordance with the investigation in the field. The results quickly and easily analyse physical vulnerability, researchers demonstrate that the building length, width, and foundation have developed various types of tools or software such as depth are the three most critical factors that affect the physi- HAZUS-MH (FEMA, 2003), RiskScape (King and Bell, cal vulnerability value. Also, the result shows that the higher 2005), ARMAGEDOM (Sedan et al., 2013), and CAPRA the ratio of length to width of the building, the more seri- (https://ecapra.org/, last access: 10 August 2019). HAZUS- ous the damage to the building. Similarly, the shallower the MH (FEMA, 2003) is considered to be the initially intro- foundation depth is, the more serious the damage will be. We duced and the most popularly applied software. RiskScape is a national-scale multi-hazard impact model in New Zealand, Published by Copernicus Publications on behalf of the European Geosciences Union. 2548 Q. Chen et al.: Assessment of the physical vulnerability of buildings affected by slow-moving landslides and ARMAGEDOM is a tool for seismic risk assessment that 2018; Dong et al., 2018; Wang et al., 2018), the USA (Esser, has three different precision levels (regional territorial scale, 2000), and Australia (Jworchan et al., 2008). district scale, and the district scale with more detailed haz- Fell et al. (2008) suggested the estimation of the physical ard description and physical vulnerability estimation). The vulnerability of elements at risk for various landslide types. majority of the software is employed to analyse the physical The slow-moving landslides may cause partial damage to vulnerability of earthquakes or multi-hazards, and very little buildings due to local displacement. The assessment meth- can be utilized for landslide hazard assessment. To solve this ods for the physical vulnerability of slow-moving landslides problem, Papathoma-Köhle et al. (2015) developed an inte- are still limited. The aforementioned approaches are not very grated toolbox designed for buildings subjected to landslides. suitable since slow-moving landslides have different inten- In the past decades, researchers have worked on landslide sity indicators and different types of damage as compared to physical vulnerability assessment techniques, which can be those from debris flows, rockfalls, or fast-moving landslides. grouped into four main approaches as follows: expert judge- Performance analysis of buildings during the landslide and ment (Sterlacchini et al., 2007; Winter et al., 2014; God- taking an inventory of the observed damage comprise a fea- frey et al., 2015; Guillard-Gonçalves et al., 2016), statistical sible methodology (Faella and Nigro, 2003). To investigate (Ciurean et al., 2013, 2017), mechanics-based (Luna et al., the physical vulnerability of the buildings impacted by land- 2014; Liang and Xiong, 2019; Nicodemo et al., 2020), and slides, numerous studies have been conducted regarding the integrated (Li et al., 2010; Uzielli et al., 2015b). The results acquisition of landslide deformation displacement or finding of these approaches include matrices, indicators, and fragility the statistical relation between the damage degree of build- or physical vulnerability curves or functions. For example, ings and landslide intensity (Mansour et al., 2011; Abdul- by utilizing the procedures motivated by the seismic risk wahid and Pradhan, 2017; Nicodemo et al., 2017; Peduto analysis, Negulescu and Foerster (2010) introduced a simpli- et al., 2017, 2018; Chen et al., 2016). For example, Man- fied methodology to evaluate the mechanical performances sour et al. (2011) investigated the relationship between the of buildings subjected to landslide hazards. Also, Totschnig movement and the expected extent of damage to urban set- et al. (2011) presented physical vulnerability curves for de- tlements. Based on the persistent scatterer interferometry, Lu bris flow and torrent hazards. Wu et al. (2011) constructed et al. (2014) obtained the slow-moving landslide velocity physical vulnerability curves for landslides by considering for estimating buildings’ economic risk with a total affected the landslides’ impact energy and impact impulse as the area of more than 800 km2. Ferlisi et al. (2015) reported that intensity indicators. By utilizing FLO-2D (hydrologic and combining the differential interferometry (DInSAR) data and hydraulic modelling software of debris flow propagation), the results of supplementary damage surveys on the slow- Luna et al. (2014) discussed the physical vulnerability func- moving landslides allowed for the preliminary generation of tions of buildings at debris flow risk. Based on the physi- a (maximum velocity) cause–effect (damage) relation. Pe- cal vulnerability assessments proposed by Li et al. (2010), duto et al. (2017) applied landslide deformation (cumulative Uzielli et al. (2015b) modified the method by integrating surface displacement and differential settlement) as the in- the assessment of landslide intensity and building resilience. put variables to construct the empirical fragility and physical Papathoma-Köhle et al. (2015) related hazard intensity (de- vulnerability curves for buildings. By applying the horizon- bris flow depth) with the loss caused by building damage tal strains and angular distortions to the numerical model, In- to buildings’ physical vulnerability curves. Del Soldato et fante et al. (2016) generated physical vulnerability for build- al. (2017) studied the empirical physical vulnerability curves ings. Nicodemo et al. (2020) employed the equivalent frame for buildings by considering the debris flow depth, the flow method to analyse the damage of a representative building in velocity, and the impact pressure. Mavrouli et al. (2017) the case of a slow-moving landslide by numerical modelling. quantified the masonry buildings’ damage induced by rock- However, a detailed study on the physical vulnerability of falls by calculating the impact force of falling rocks on ma- buildings using mechanical analysis is not yet available. sonry buildings. This study proposes a method for assessing physical vul- The slow-moving landslides are particular types of land- nerability from the perspective of mechanics and obtains its slides with a slow