Topographic Evolution Involving Co-Seismic Landslide, Deformation, Long-Term Folding and Isostatic Rebound: A Case Study on the 2004 Chuetsu Earthquake

Co-seismic landslide volume information is critical to understanding the role of strong earthquakes in topographic and geological evolution. The availability of both pre- and post-earthquake high-resolution digital elevation models (DEMs) provides us with the opportunity to develop a new approach to obtain robust landslide volume information. Here, we propose a method for landslide volume estimation and test it in the Chuetsu region, where a Mw 6.6 earthquake occurred in 2004. First, we align the DEMs by reconstructing the horizontal difference. Then, we quantitatively obtain the landslide volume in the epicentral area by differencing the pre- and post-earthquake DEMs. We convert the landslide volume into the distribution of average catchment-scale denudation and the resulting long-term crustal rebound. Our findings reveal that the Chuetsu earthquake mainly roughens the topography in the low-elevation Chuetsu region. Our results indicate that the preserved topography not only is due to the uplift caused by fault-related folding on the hanging wall of the Muikamachi fault but also undergoes erosion caused by seismically induced landslides and crustal rebound also modifies the topography in the long term. This study confirms that the differential DEM method is a valuable approach for quantitative analysis of topographic and geological evolution.

Contribution of a new seismic amplification factor map approach for shakemaps improvement: the Croatia Mw=6.4 earthquake scenario.

<p>Estimation of site effects over large areas is a key-issue in a seismic risk mitigation perspective.</p><p>We prove here that the IGAG20 approach (Falcone et al., 2021), developed for the estimation of the stratigraphic Amplification Factors (AF) at a national scale for Italy, can be used in international context, as it is based on AF-V<sub>s30</sub> laws developed according to 40 geo-morphological clusters available globally after Iwahashi et al. (2018) and V<sub>s30 </sub>proxy laws after Mori et al. (2020).</p><p>The availability of AF maps is fundamental for the improvement of the estimates of surface shaking for the "shakemaps" produced after the seismic events, and for the consequent improvement of the preliminary estimates of coseismic effects (i.e. landslides and liquefaction) and damage of residential buildings.</p><p>The IGAG20 approach was implemented for evaluating the shaking maps for the recent Mw=6.4 Croatian seismic event, with a focus on the three most affected localities: Petrinjia, Sisak, and Glina. From the OpenQuake engine, Silva et al. (2014), a stochastic scenario analysis was performed and PGV and PGA shaking maps amplified with AF maps were produced. With the PGV map, landslide and liquefaction probability maps are produced respectively with the Nowicki et al. (2018) and Zhu et al. (2017) models. With the PGA map, a preliminary residential buildings damage estimation is produced and compared with the EMS98 damage distribution available from the grading maps produced by COPERNICUS (https://emergency.copernicus.eu/mapping/list-of-components/EMSR491 ). Finally, all the shaking maps are compared with USGS products (https://earthquake.usgs.gov/earthquakes/eventpage/us6000d3zh/executive).</p><p><strong>References </strong></p><p>Falcone, G., Mendicelli, A., Moscatelli, M., Romagnoli, G., Peronace, E., Naso, G., Acunzo G., Porchia, A., Tarquini, E., 2021. Seismic amplification maps of Italy based on site-specific microzonation dataset and one-dimensional numerical approach Eng. Geol. - Under review</p><p>Iwahashi, J., Kamiya, I., Matsuoka, M., Yamazaki, D., 2018. Global terrain classification using 280 m DEMs: segmentation, clustering, and reclassification. Prog. Earth Planet. Sci. https://doi.org/10.1186/s40645-017-0157-2</p><p>Mori, F., Mendicelli, A., Moscatelli, M., Romagnoli, G., Peronace, E., Naso, G., 2020. A new Vs30 map for Italy based on the seismic microzonation dataset. Eng. Geol. https://doi.org/10.1016/j.enggeo.2020.105745</p><p>Nowicki Jessee, M.A., Hamburger, M.W., Allstadt, K., Wald, D.J., Robeson, S.M., Tanyas, H., Hearne, M., Thompson, E.M., 2018. A Global Empirical Model for Near-Real-Time Assessment of Seismically Induced Landslides. J. Geophys. Res. Earth Surf. https://doi.org/10.1029/2017JF004494</p><p>Silva, V., Crowley, H., Pagani, M., Monelli, D., Pinho, R., 2014. Development of the OpenQuake engine, the Global Earthquake Model’s open-source software for seismic risk assessment. Nat. Hazards. https://doi.org/10.1007/s11069-013-0618-x</p><p>Zhu, J., Baise, L.G., Thompson, E.M., 2017. An updated geospatial liquefaction model for global application. Bull. Seismol. Soc. Am. https://doi.org/10.1785/0120160198</p>

Seismic and geologic controls on spatial clustering of landslides in three large earthquakes

The large, shallow earthquakes at Northridge, California (1994), Chi-Chi, Taiwan (1999), and Wenchuan, China (2008), each triggered thousands of landslides. We have determined the position of these landslides along hillslopes, normalizing for statistical bias. The landslide patterns have a co-seismic signature, with clustering at ridge crests and slope toes. A cross-check against rainfall-induced landslide inventories seems to confirm that crest clustering is specific to seismic triggering as observed in previous studies. In our three study areas, the seismic ground motion parameters and lithologic and topographic features used do not seem to exert a primary control on the observed patterns of landslide clustering. However, we show that at the scale of the epicentral area, crest and toe clustering occur in areas with specific geological features. Toe clustering of seismically induced landslides tends to occur along regional major faults. Crest clustering is concentrated at sites where the lithology along hillslopes is approximately uniform, or made of alternating soft and hard strata, and without strong overprint of geological structures. Although earthquake-induced landslides locate higher on hillslopes in a statistically significant way, geological features strongly modulate the landslide position along the hillslopes. As a result the observation of landslide clustering on topographic ridges cannot be used as a definite indicator of the topographic amplification of ground shaking.

Topographic changes due to the 2004 Chuetsu thrusting earthquake in low mountain region

The co-seismic landslide volume information is critical to understanding the role of strong earthquake in topographic evolution. However, the co-seismic landslide volumes are mainly obtained using statistical scaling laws, which are not accurate enough for quantitative studies of the spatial pattern of co-seismically induced erosion and the topographic changes caused by the earthquakes. The availability of both pre- and post- earthquake high-resolution DEMs provide us the opportunity to try new approach to get robust landslide volume information. Here, we propose a new method in landslide volume estimate and tested it in Chuetsu region, where a Mw 6.6 earthquake occurred in 2004. Firstly, we align the DEMs by reconstructing the horizontal difference, then we quantitatively obtained the landslide volume in the epicentral area by differencing the pre- and post-earthquake DEMs. We convert the landslide volume into the distribution of average catchment-scale seismically induced denudation. Our results indicate the preserved topography is not only due to the uplifting caused by fault-related folding on the hangwall of Muikamachi fault, but also undergone erosion caused by the seismically induced landslides. Our findings reveal that Chuetsu earthquake mainly roughens the topography in the Chuetsu region of low elevation. This study also reveal that the differential DEM method is a valuable approach in analyzing landslide volume, as well as quantitative geomorphic analysis.

Seismic and geologic controls on spatial clustering of landslides in three large earthquakes

The large, shallow earthquakes at Northridge, California (1994), Chi-Chi, Taiwan (1999) and Wenchuan, China (2008) each triggered thousands of landslides. We have determined the position of these landslides along hillslopes, normalizing for statistical bias. The landslide patterns have a co-seismic signature, with clustering at ridge crests and slope toes. A cross check against rainfall-induced landslide inventories confirms that crest-clustering is specific to seismic-triggering. In our three study areas, seismic ground motion parameters, and lithologic and topographic features have limited bearing on the observed patterns of landslide clustering. However, we show that at the scale of the epicentral area, crest- and toe-clustering occur in areas with specific geological features. Toe-clustering of seismically-induced landslides tends to occur along major faults. Crest-clustering is concentrated at sites where the lithology along hillslopes is approximately uniform, or made of alternating soft and hard strata, and without strong overprint of geological structures. Although earthquake-induced landslides locate higher on hillslopes in a statistically significant way, geological features strongly modulate the landslide position along the hillslopes. As a result the observation of landslide clustering on topographic ridges cannot be used directly as an indicator of seismic parameters such as ground shaking.

Phased Reconnaissance Approach to Documenting Landslides following the 2016 Central Italy Earthquakes

The 2016 Central Italy earthquake sequence caused numerous landslides over a large area in the Central Apennines. As a result, the Geotechnical Extreme Events Reconnaissance Association (GEER) organized post-earthquake reconnaissance missions to collect perishable data. Given the challenging conditions following the earthquakes, the GEER team implemented a phased reconnaissance approach. This paper illustrates this approach and how it was used to document the largest and most impactful seismically induced landslides. This phased approach relied upon satellite-based interferometric damage proxy maps, preliminary published reports of observed landslides, digital imaging from small unmanned aerial vehicles (UAVs), traditional manual observations, and terrestrial laser scanning. Data collected from the reconnoitered sites were used to develop orthophotos and meshed three-dimensional digital surface models. These products can provide valuable information such as accurate measurements of landslide ground movements in complex topographic geometries or boulder runout distances from rock falls. The paper describes three significant landslide case histories developed and documented with the phased approach: Nera Valley, Village of Pescara del Tronto, and near the villages of Crognaleto and Cervaro.