Detecting and Modelling Shallow Continental Earthquakes by InSAR Time Series Analysis: A Case Study in Iran

With the advancements of Synthetic Aperture Radar (SAR) missions and computing resources, Interferometric SAR (InSAR) is now an established method to observe the Earth's surface displacement caused by earthquakes. However, among many candidate earthquakes whose signals are strong enough to be visible on the interferograms, only a certain fraction of them are observed. This circumstance is mainly caused by the decorrelation and atmospheric noise during imaging, making the study of these earthquakes, especially for the small ones (M_w 5.0-6.5), more difficult. To exploit the InSAR potential in earthquake observation, we apply InSAR time series analysis to detect small continental earthquakes, using recent earthquakes in Iran (M_w 5.0+, 2014-2019) as a case study. We find that the coseismic deformation, which might be not easily visible within a single interferogram, can be confidently detected using InSAR time series analysis. By analyzing 5-year-long InSAR times series from Sentinel-1, we detect the majority of the earthquakes (M_w 5.0+) over the Iran-Iraq border area, achieving an enhanced level of detectability compared to using single interferogram. Additionally, we also show a case that earthquakes occurring close together in time and space (e.g. a pair of M_w 5.6 and M_w 6.3 earthquakes happened in Nov 2018 and Jan 2019 with 42 days and 30 km separation) can be separated via InSAR time series analysis. By fitting the seismic cycle surface displacement and removing the dominant postseismic deformation caused by the large 2017 M_w 7.3 Darbandikhan earthquake, coseismic interferograms of these small earthquakes are reconstructed, which reduces random noise and improves their visibility. We find that the reconstructed coseismic interferograms can achieve more robust and seismologically consistent earthquake modelling result compared to the original ones, with the validation being provided from the United States Geological Survey (USGS) catalogue. Our work suggests that InSAR time series analysis is an effective way to detect and model small or moderate magnitude earthquakes. In particular we demonstrate the use of this approach for detecting aftershocks in the presence of the postseismic signal following a major earthquake that otherwise might go undetected in single interferogram analysis.