Gorum, Tolga

Kirschbaum, Dalia

Lombardo, Luigi

Tanyaș, Hakan

English

Various mechanisms are proposed to explain landslide recovery time in the time following major earthquakes. However, research on prescribing possible recovery times following an earthquake is still relatively new. This paper provides an insight into factors governing landslide recovery time, which could be considered as a step forward in predictive modeling for landslide recovery time. To accomplish this, we examined 11 earthquake-affected areas based on the characteristics of both landslide events and landslide sites associated with diverse morphologic and climatic conditions. Our analyses indicate that the dominant characteristics of post-seismic landslide mechanisms determine the recovery time. The characteristics can be identified based on: (i) the fraction of area affected by landslides (%), (ii) mean relief and its standard deviation (m), (iii) average daily accumulated precipitation (mm) and (iv) rainfall seasonality index. If there are not enough co-seismic landslide deposits or not enough relief to trigger large deposits on hillslopes, then the recovery processes are mostly controlled by new landslides caused by a strength reduction of hillslope materials. In most of the cases, this brings a relatively quick recovery process in which the majority of post-seismic landslides may happen within a year or even in a month if sufficient intense rainfalls occur soon after the earthquake. If the predisposing factors create large co-seismic landslide deposits, then remobilization of material takes the role of the dominant mechanism and recovery may take years. Overall, our analyses show that the recovery takes relatively longer if a large amount of co-seismic landslide material is deposited within a high-relief mountainous environment where precipitation rate is low and not persistent

University of Twente Research Information

A Closer Look at Factors GoverningLandslide Recovery Time in Post-Seismic PeriodsHakan Tanyaş1,2, Dalia Kirschbaum1, Luigi Lombardo3, Tolga Görüm41NASA Goddard Space Flight Center, Hydrological Sciences Laboratory, Greenbelt, MD, USA2USRA, Universities Space Research Association, Columbia, MD, USA3University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), Enschede, Netherlands4Istanbul Technical University, Eurasia Institute of Earth Sciences, Istanbul, Turkey2020Vienna | Austria | 4-8 May 2020MotivationNear real-time global landslide hazard assessment methods are separately available forboth earthquake- (e.g., Jessee Nowicki et al., 2018) and rainfall-triggered (e.g.,Kirschbaum and Stanley, 2018) landslides although none of them are capable ofaccounting for the coupled effect of earthquakes and precipitation. However,characterizing these interactions is critical to advance effective landslide hazardassessment. To capture this coupled effect for a rainfall-triggered landslide hazardassessment, we need to consider the preconditioning effect of seismic shaking. Hence,we first need to understand the legacy effect of previous earthquakes (hillslope memory)(Parker et al., 2015) and its evolution through time under the control of site-specificfactors.Aim and ScopeOur study aims at better understanding the concept of landslide recovery in post-seismic periods considering the characteristics of both landslide events and landslide sites associated with diverse seismotectonic, morphologic and climatic conditions. To accomplish this, we analyze the recovery time from 11 earthquakes and their association with earthquake and landscape characteristics.We hypothesize that the dominant characteristics of post-seismic landslide is the key to understand the recovery time. BackgroundIn this study, we will often refer to two terms namely, landslide recovery and landslide recovery time. The former is equivalent to the common definition of hillslope healing whereas the latter consists of the time span in which the natural landslide susceptibility of a given area is restored after the disturbance of an earthquake. To better characterize different post-seismic landslide processes we use three key terms:1) New landslide refers to mass movements that occur in unfailed hillslopes before or during the seismic shaking or on hillslopes where there is no evidence of physical contact with previously occurred landslides. 2) A reactivated landslide refers to a landslide that occurred on a previously failed hillslope and 3) A remobilized landslide refers to a failure initiated from previously deposited landslide materials.  MethodWe extract the landslide recovery times from the literature for eight cases wherelandslide inventories are not available. If there is more than one article that examined theevent, or if there are some uncertainties either indicated by the authors or some that wenoticed, we use such findings as uncertainty bounds in our evaluation. For the threecases where we newly compiled the multi-temporal landslide inventories, we calculatedthe landslide rates as the total landslide area divided by the length of the scanned time-window.We analyze 11 earthquake-affected areas and examine the characteristics of post-seismic landslides associated with four environmental factors:(1) the fraction of area affected by co-seismic landslides,(2) mean relief,(3) average daily accumulated precipitation and(4) rainfall seasonality.Figure 1. (a) Distribution of examined earthquakes and areal extends of sites affected by: (b) 1993 Finisterre (Papua New Guinea, Mw=6.9), (c) 1999 Chi-Chi (Taiwan, Mw=7.7), (d) 2004 Niigata (Japan, Mw=6.6), (e) 2005 Kashmir (India-Pakistan, Mw=7.6), (f) 2008 Iwate (Japan, Mw=6.9), (g) 2008 Wenchuan (China, Mw=7.9), (h) 2012 Haida Gwaii (Canada, Mw=7.8), (i) 2012 Sulawesi (Indonesia, Mw=6.3), 2017 Kasiguncu (Indonesia, Mw=6.6) and 2018 Palu (Indonesia, Mw=7.5), (j) 2015 Gorkha (Nepal, Mw=7.8), (k) 2016 Reuleuet (Indonesia, Mw=6.5) and (l) 2018 Porgera (Papua New Guinea, Mw=7.5) earthquakes. Red starts show the epicenters of earthquakes. Study AreasResultsIf there are not enough co-seismic landslide deposits or not enough relief to trigger large deposits on hillslopes, then the recovery processes are mostly controlled by new and reactivated landslides caused by strength reduction of hillslope materials. This mostly results in a relatively quick recovery process in which most post-seismic landslides may happen within a year or less if sufficient intense rainfall events occur soon after the earthquake. If the predisposing factors create large co-seismic landslide deposits on hillslopes, then remobilization of material takes the role of the dominant mechanism and recovery may take years. Overall, our analyses show that the recovery takes relatively longer if a large amount of co-seismic landslide material is deposited within a high-relief mountainous environment where precipitation rates are low and strongly seasonal.ResultsAs a result, we can categorize the available cases in association with the dominant post-seismic landslide processes as: (i) Niigata, Iwate, Haida Gwaii, Kasiguncu, Reuleuet, Porgera (new landslides and reactivations), (ii) Wenchuan (remobilization) and (iii) Finisterre, Chi-Chi, Kashmir and Gorkha (transition between the two categories mentioned above). This category refers to cases where we observe not only new landslides and reactivations but also remobilizations.ConclusionThe cases examined in this work suggest that landslide recovery time in post-seismic periods is mainly controlled by the interactive relationship between characteristics of co-seismic landslide events and site-specific morphologic and climatic factors.We conclude that the longest landslide recovery times occur if a large amount of co-seismic landslide is deposited in mountainous regions where average daily precipitation is lower and seasonal. Thank You!The presented work is currently being revised. Please feel free to contact me if you have any question/comment or need any further information.Hakan Tanyaş (hakan.tanyas@nasa.gov)ReferencesJessee Nowicki, 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. 123. https://doi.org/10.1029/2017JF004494Kirschbaum, D., Stanley, T., 2018. Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness. Earth’s Futur. 6, 505–523. https://doi.org/10.1002/2017EF000715Parker, R.N., Hancox, G.T., Petley, D.N., Massey, C.I., Densmore, A.L., Rosser, N.J., 2015. Spatial distributions of earthquake-induced landslides and hillslope preconditioning in the northwest South Island, New Zealand. Earth Surf. Dyn. 3, 501–525. https://doi.org/10.5194/esurf-3-501-2015

A closer look at factors governing landslide recovery time in post-seismic periods

https://ris.utwente.nl/ws/files/252089136/EGU2020_8640_presentation_1_.pdf

A closer look at factors governing landslide recovery time in post-seismic periods

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