Suchergebnisse

Report on landslides triggered by the 2008 Wenchuan earthquake -- Earthquake-induced landslides and ground failure in Chile: The Aysen 2007 and Maule 2010 earthquakes -- Earthquake-Induced landslides in the Nepal Himalaya -- Landslides triggered by the 2002 M 7.9 Denali Fault earthquake, Alaska, USA -- Recent earthquake-triggered landslide events in Central Asia, evidence of seismic landslides in the Lesser Caucasus and the Carpathians -- Some earthquake-induced rockslides in the Central Asia region -- Some recent coseismic landslides in Japan -- Co-Seismic Landslides in Greece, a Review -- Characteristics of Landslides and Cases of Severe Landslides on Gentle Slopes Triggered by the Chi-Chi Earthquake, Taiwan, 1999 -- Landslides triggered by recent earthquakes in Italy -- Earthquake-induced landslides and related problems -- Characteristics of sites response of a series of monitored slopes in Sichuan mountain area -- Post-earthquake landscape response -- Earthquake-induced landslide susceptibility and hazard assessment approaches -- Numerical Evaluation of the Effect of Drainage Wells on the Stability of the Ichiba No.1 Landslide during an Mj6.7 Earthquake -- Displacement predictive relationships for earthquake triggered landslides and structural vulnerability models for buildings exposed to co-seismic ground movements -- A prototype earthquake-induced landslide forecast tool for New Zealand -- Coseismic landslide susceptibility and triggering analyses.

Abstract. We present a quantitative risk analysis (QRA) case study from the Kā Roimata o Hine Hukatere / Franz Josef Glacier and Te Moeka o Tuawe / Fox Glacier valleys, on the west coast of the South Island, Aotearoa / New Zealand. The glacier valleys are important tourist destinations that are subject to landslide hazards. Both valleys contain actively retreating glaciers; experience high rainfall; and are proximal to the Alpine Fault, which is a major source of seismic hazard on the west coast. We considered the life safety risk from rockfalls, soil/rock avalanches, and flows that either are seismically triggered or occur aseismically. To determine the range in risk values and dominant contributing variables to the risk, we modelled nine different risk scenarios where we incrementally changed the variables used in the risk model to account for the underlying uncertainty. The scenarios represent our central estimate of the risk, e.g. neither optimistic nor conservative, through to our upper estimate of the risk. We include in these estimates the impact time-variable factors, such as a recently reactivated landslide, have had on locally increasing risk and the time-elapsed since the last major earthquake on the nearby Alpine Fault. We disaggregated our risk results to determine the dominant drivers in landslide risk, which highlighted the importance of considering dynamic time-variable risk scenarios and the changing contributions to risk from aseismic versus seismic landslides. A detailed understanding of the drivers of landslide risk in each valley is important to determine the most efficient and appropriate risk management decisions.

Abstract. Rockfall modelling is an important tool for hazard analysis in steep terrain. Calibrating terrain parameters ensures that the model results more accurately represent the site-specific hazard. Parameterizing rockfall models is challenging because rockfall runout is highly sensitive to initial conditions, rock shape, size and material properties, terrain morphology, and terrain material properties. This contribution examines the mechanics of terrain impact scarring due to rockfall on the Port Hills of Christchurch, New Zealand. We use field-scale testing and laboratory direct shear testing to quantify how the changing moisture content of the loessial soils can influence its strength from soft to hard, and vice versa. We calibrate the three-dimensional rockfall model RAMMS by back-analysing several well-documented rockfall events that occurred at a site with dry loessial soil conditions. We then test the calibrated "dry" model at a site where the loessial soil conditions were assessed to be wet. The calibrated dry model over-predicts the runout distance when wet loessial soil conditions are assumed. We hypothesize that this is because both the shear strength and stiffness of wet loess are reduced relative to the dry loess, resulting in a higher damping effect on boulder dynamics. For both realistic and conservative rockfall modelling, the maximum credible hazard is usually assumed; for rockfall on loess slopes, the maximum credible hazard occurs during dry soil conditions.

Abstract. Coastal hillslopes often host higher concentrations of
earthquake-induced landslides than those further inland, but few studies
have investigated the reasons for this occurrence. As a result, it is
unclear if regional earthquake-induced landslide susceptibility models
trained primarily on inland hillslopes are effective predictors of coastal
susceptibility. The 2016 Mw 7.8 Kaikōura earthquake on the
northeastern South Island of New Zealand resulted in ca. 1600 landslides > 50 m2 on slopes > 15∘ within 1 km of
the coast, contributing to an order of magnitude greater landslide source
area density than inland hillslopes within 1 to 3 km of the coast. In this
study, logistic regression modelling is used to investigate how landslide
susceptibility differs between coastal and inland hillslopes and to determine
the factors that drive the distribution of coastal landslides initiated by
the 2016 Kaikōura earthquake. Strong model performance (area under the
receiver operator characteristic curve or AUC of ca. 0.80 to 0.92) was
observed across eight models, which adopt four simplified geology types. The
same landslide susceptibility factors, primarily geology, steep slopes, and
ground motion, are strong model predictors for both inland and coastal
landslide susceptibility in the Kaikōura region. In three geology types
(which account for more than 90 % of landslide source areas), a 0.03 or
less drop in model AUC is observed when predicting coastal landslides using
inland-trained models. This suggests little difference between the features
driving inland and coastal landslide susceptibility in the Kaikōura
region. Geology is similarly distributed between inland and coastal
hillslopes, and peak
ground acceleration (PGA) is generally lower in coastal hillslopes. Slope angle,
however, is significantly higher in coastal hillslopes and provides the best
explanation for the high density of coastal landslides during the 2016
Kaikōura earthquake. Existing regional earthquake-induced landslide
susceptibility models trained on inland hillslopes using common predictive
features are likely to capture this signal without additional predictive
variables. Interestingly, in the Kaikōura region, most coastal
hillslopes are isolated from the ocean by uplifted shore platforms. Enhanced
coastal landslide susceptibility from this event appears to be a legacy
effect of past erosion from wave action, which preferentially steepened
these coastal hillslopes.

Abstract. Earth science information (data, knowledge, advice) can enhance the evidence base for land-use decision-making. The utility of this information depends on factors including the context and objectives of land-use decisions, the timeliness and efficiency with which earth science information is delivered, and the strength, relevance, uncertainties, and risks assigned to earth science information relative to other inputs. We investigate land-use decision-making practices in Christchurch, New Zealand, and the surrounding region in response to mass movement (e.g., rockfall, cliff collapses) and ground-surface fault rupture hazards incurred during the 2010–2011 Canterbury earthquake sequence (CES). Rockfall fatality risk models combining hazard, exposure, and vulnerability data were co-produced by earth scientists and decision makers and formed primary evidence for risk-based land-use decision-making with adaptive capacity. A public consultation and submission process enabled consideration of additional earth science information primarily via stakeholder requests. For fault rupture hazards, pre-disaster geotechnical guidelines and collaboration networks enhanced the ability of earth scientists to rapidly acquire relevant observational data to meet the demands of decision makers. Expeditious decision-making granted permissive consent for rebuilding in the fault rupture zone based on preliminary scientific advice that was subsequently supported by more comprehensive geological investigations. Rapidly fluctuating and diverse demands for post-disaster earth science information may be best met through the prior establishment of (i) land-use policies and technical guidelines tailored for a variety of diverse disaster scenarios, (ii) hazard and risk analyses in land-use plans, including acquisition of geospatial and other earth science data, and (iii) coordinated scientific networks that may comprise subgroups with diverse goals, operational perspectives, and protocols which allow the many facets of scientific information acquisition and delivery to be successfully addressed. Despite the collective knowledge shared here, some recent land-use practices in New Zealand continue to prioritize other (e.g., socioeconomic) factors above earth science information, even in areas of extreme disaster risk.

Tens of thousands of landslides were generated over 10,000 km2 of North Canterbury and Marlborough as a consequence of the 14 November 2016, Mw7.8 Kaikōura Earthquake. The most intense landslide damage was concentrated in 3500 km2 around the areas of fault rupture. Given the sparsely populated area affected by landslides, only a few homes were impacted and there were no recorded deaths due to landslides. Landslides caused major disruption with all road and rail links with Kaikōura being severed. The landslides affecting State Highway 1 (the main road link in the South Island of New Zealand) and the South Island main trunk railway extended from Ward in Marlborough all the way to the south of Oaro in North Canterbury. The majority of landslides occurred in two geological and geotechnically distinct materials reflective of the dominant rock types in the affected area. In the Neogene sedimentary rocks (sandstones, limestones and siltstones) of the Hurunui District, North Canterbury and around Cape Campbell in Marlborough, first-time and reactivated rock-slides and rock-block slides were the dominant landslide type. These rocks also tend to have rock material strength values in the range of 5-20 MPa. In the Torlesse 'basement' rocks (greywacke sandstones and argillite) of the Kaikōura Ranges, first-time rock and debris avalanches were the dominant landslide type. These rocks tend to have material strength values in the range of 20-50 MPa. A feature of this earthquake is the large number (more than 200) of valley blocking landslides it generated. This was partly due to the steep and confined slopes in the area and the widely distributed strong ground shaking. The largest landslide dam has an approximate volume of 12(±2) M m3 and the debris from this travelled about 2.7 km2 downslope where it formed a dam blocking the Hapuku River. The long-term stability of cracked slopes and landslide dams from future strong earthquakes and large rainstorms are an ongoing concern to central and local government agencies responsible for rebuilding homes and infrastructure. A particular concern is the potential for debris floods to affect downstream assets and infrastructure should some of the landslide dams breach catastrophically. At least twenty-one faults ruptured to the ground surface or sea floor, with these surface ruptures extending from the Emu Plain in North Canterbury to offshore of Cape Campbell in Marlborough. The mapped landslide distribution reflects the complexity of the earthquake rupture. Landslides are distributed across a broad area of intense ground shaking reflective of the elongate area affected by fault rupture, and are not clustered around the earthquake epicentre. The largest landslides triggered by the earthquake are located either on or adjacent to faults that ruptured to the ground surface. Surface faults may provide a plane of weakness or hydrological discontinuity and adversely oriented surface faults may be indicative of the location of future large landslides. Their location appears to have a strong structural geological control. Initial results from our landslide investigations suggest predictive models relying only on ground-shaking estimates underestimate the number and size of the largest landslides that occurred.