A Transient in Surface Motions Dominated by Deep Afterslip Subsequent to a Shallow Supershear Earthquake: The 2018 Mw7.5 Palu Case

Nijholt, Nicolai; Simons, Wim; Efendi, Joni; Sarsito, Dina A.; Riva, Riccardo

doi:10.1029/2020gc009491

Cited by 3 publications

(4 citation statements)

References 53 publications

(86 reference statements)

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“…However, the misfit difference between the two mathematical functions is not very large, indicating that viscoelastic mechanisms may also contribute to the postseismic deformation in the last 3 years. This yields the same result where afterslip dominates the postseismic deformation in Palu, and viscoelastic mechanisms play a minor role [16].…”

Section: Afterslip Mechanismsupporting

confidence: 65%

“…Understanding postseismic displacements is important for studying fault stability and the rheological properties of the Earth's media in post-earthquake disaster risk assessment [15]. Previous research has been conducted to investigate postseismic deformations resulting from earthquakes, which showed that the displacements after the earthquake are dominated by afterslip, and the role of viscoelasticity in this phenomenon is limited [16]. However, this research is limited to utilizing GNSS methods in its observations.…”

Section: Introductionmentioning

confidence: 99%

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2.5D Time Series of Postseismic Deformation Following the 2018 Mw 7.5 Palu Earthquake Using Sentinel-1 InSAR

Yusiyanti,

Khasanah,

Trihandaru

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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The observed Displacement of Line of Sight (LOS) InSAR can only measure the displacement towards and away from the satellite sensor, making it difficult to provide an intuitive depiction of the deformation source. In the previous studies, research on the characteristics of postseismic deformation mechanisms was conduct by InSAR but only in the vertical component. Therefore, our study attempts to complement this deformation picture by considering both the horizontal and vertical components. It is hoped that this will provide a more comprehensive understanding of the postseismic deformation mechanism of the 2018 Palu earthquake. In this study, we attempted to estimate the 2.5-D surface deformation resulting from the 2018 Palu Earthquake using Sentinel-1 data. The data was then modeled using exponential and logarithmic functions to understand the characteristics of the postseismic deformation mechanism. The 2.5-D surface deformation exhibited variations in horizontal and vertical motions. The East-West (EW) displacement values showed a maximum value of -66.19 mm in the east direction, while the maximum value in the west direction is 75.23 mm. On the other hand, for the Up-Down (UD) displacement, there was a maximum subsidence of -73.40 mm and a maximum uplift of 67.28 mm. To study the characteristics of the transient postseismic deformation, observations were made at 14 points. Postseismic deformation was observed at all locations in the study area. During the period 2018-2021, the time series of the north and east components of the postseismic transients were analyzed using logarithmic and exponential functions. The modeling results showed that the Root Mean Square Error (RMSE) value for the exponential model is 81.80 mm, while for the logarithmic model is 81.38 mm. Therefore, the logarithmic model demonstrated a better fit, indicating that the postseismic deformation mechanism is influenced by afterslip.

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Section: Afterslip Mechanismsupporting

confidence: 65%

Section: Introductionmentioning

confidence: 99%

2.5D Time Series of Postseismic Deformation Following the 2018 Mw 7.5 Palu Earthquake Using Sentinel-1 InSAR

Yusiyanti,

Khasanah,

Trihandaru

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…All GPS and SAR observations have been acquired within a few weeks after the earthquake: 1-42 days for a few GPS sites, and within 4-27 days for the SAR data. Nijholt et al (2021) report post-seismic displacements on the order of a few cm in the first year since the event, which is two orders of magnitude smaller than the largest co-seismic estimates. So, while our observations are not purely co-seismic we expect relatively small contamination from post-seismic displacements.…”

Section: Fault Tracementioning

confidence: 79%

“…Nijholt et al. (2021) report post‐seismic displacements on the order of a few cm in the first year since the event, which is two orders of magnitude smaller than the largest co‐seismic estimates. So, while our observations are not purely co‐seismic we expect relatively small contamination from post‐seismic displacements.…”

Section: Discussionmentioning

confidence: 92%

A Tsunami Generated by a Strike‐Slip Event: Constraints From GPS and SAR Data on the 2018 Palu Earthquake

et al. 2022

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A devastating tsunami struck Palu Bay in the wake of the 28 September 2018 M w = 7.5 Palu earthquake (Sulawesi, Indonesia). With a predominantly strike-slip mechanism, the question remains whether this unexpected tsunami was generated by the earthquake itself, or rather by earthquake-induced landslides. In this study we examine the tsunami potential of the co-seismic deformation. To this end, we present a novel geodetic data set of Global Positioning System and multiple Synthetic Aperture Radar-derived displacement fields to estimate a 3D co-seismic surface deformation field. The data reveal a number of fault bends, conforming to our interpretation of the tectonic setting as a transtensional basin. Using a Bayesian framework, we provide robust finite fault solutions of the co-seismic slip distribution, incorporating several scenarios of tectonically feasible fault orientations below the bay. These finite fault scenarios involve large co-seismic uplift (>2 m) below the bay due to thrusting on a restraining fault bend that connects the offshore continuation of two parallel onshore fault segments. With the co-seismic displacement estimates as input we simulate a number of tsunami cases. For most locations for which video-derived tsunami waveforms are available our models provide a qualitative fit to leading wave arrival times and polarity. The modeled tsunamis explain most of the observed runup. We conclude that co-seismic deformation was the main driver behind the tsunami that followed the Palu earthquake. Our unique geodetic data set constrains vertical motions of the sea floor, and sheds new light on the tsunamigenesis of strike-slip faults in transtensional basins.

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Vertical deformation model on postseismic phase using exponential and logarithmic function based on InSAR

Yusiyanti¹,

Prajardi²,

Saputri³

et al. 2023

Geodesy and Geodynamics

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A Transient in Surface Motions Dominated by Deep Afterslip Subsequent to a Shallow Supershear Earthquake: The 2018 M_w7.5 Palu Case

Cited by 3 publications

References 53 publications

2.5D Time Series of Postseismic Deformation Following the 2018 Mw 7.5 Palu Earthquake Using Sentinel-1 InSAR

2.5D Time Series of Postseismic Deformation Following the 2018 Mw 7.5 Palu Earthquake Using Sentinel-1 InSAR

A Tsunami Generated by a Strike‐Slip Event: Constraints From GPS and SAR Data on the 2018 Palu Earthquake

Vertical deformation model on postseismic phase using exponential and logarithmic function based on InSAR

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