Assessment of the M8 Algorithm by Spatial Integrating of Alarms (Case Study: Sarpol-e Zahab Earthquake)

On average, a large and destructive earthquake occurs in the Iranian plateau every few years, in which, usually causes lots of damages. The Van, Saravan and Sarpol-e Zahab earthquakes are three recent events that occurred in this region from 2011 to 2017. According to premonitory phenomena, using earthquake prediction algorithms can be effective in reducing the damages of such events. In this paper, the intermediate-term M8 algorithm is used for retrospective prediction of the Sarpol-e Zahab earthquake. The aim of this research is to evaluate and complete the M8 algorithm performance background in the prediction of the major Iranian plateau earthquakes, and achieve precursory seismic pattern before the Sarpol-e Zahab earthquake. In addition, providing an approach to obtain alarm areas independent of the M8 input values is another important goal in this study. To achieve this propose, the results of alarm areas from different M8 input values were integrated in two ways.  Both approaches were successful in predicting the target earthquake. The results showed that the Sarpol-e Zahab earthquake was predictable using the M8 algorithm, also the integration of alarm areas from various M8 statues reduces the area of the total alarm and stabilize it against the changes in the input parameter values. Finally, by considering the M8 functions values, it was found that reaching to the highest value of the maximum aftershocks number was the major precursory phenomena of this earthquake.

History of the Iranian plateau seismicity shows that this region is usually vulnerable to the large earthquakes. Therefore, considering the prediction of large earthquakes in this area in order to increase preparedness and reduce damages is necessary. The M8 is an Intermediate-term middle-range prediction algorithm that has yielded good results around the world. The low annual seismicity rate in the Iranian plateau is one of the challenges of using the M8 algorithm in Iran. The recent earthquake in Sarpol-e Zahab with a magnitude of 7.3 is a reason to the re-evaluation of the M8 algorithm. Therefore, the purpose of this paper is to re-evaluate the M8 algorithm in predicting major Iranian plateau earthquakes and also provide a suitable solution to reduce uncertainty and increase the reliability to alarm areas.

The M8 is an Intermediate-term algorithm designed to predict earthquakes with magnitudes greater than  (target magnitude). To run the algorithm in an investigation circle, a series of time from (start time of earthquake catalog) to (end time) by half-year's increase is formed. From  (start time of measurement) and in each  (time i), seven values are calculated using four functions. These seven values are obtained by changing the seismic rate threshold () in the form of two parameters  = 20 and  = 10 in four functions within the investigation circle. In either case, the lower limit magnitudes are selected, in the way that, the average number of annual earthquakes in the investigation circle is equal to .
The values of the functions that are greater than Q percent of their values over time are labeled as very large values. The value of Q depends on the type of function. If at least six very large values including the seventh function exist at the time window , and it repeats in two consecutive times  and , the investigation circle for 5 years will be in alarm status.

The 7.3 magnitude Sarpol-e Zahab earthquake occurred in Kermanshah province, near Iran and Iraq border, on November 12, 2017. This event was selected as a target earthquake in the M8 algorithm. The characteristics of target and computation earthquakes were selected from the NEIC earthquake catalog. The value of  is equal to 1965 and  is 01/01/2017.
A dense grid of investigation points was created around the target earthquake. Then, the algorithm was implemented in six modes (1,2), (1,3), (1,4), (2,3), (2,4), (3,4) by changing the values of  and  from one to four,. Consequently, the results of these six modes were integrated by two approaches at . In the first method, intersection of the alarm areas at  were selected as the final alarm area and in the second one, the alarm investigation points at  in all six modes were selected. Finally, the union of their circle were considered as the final alarm area (Figure 1). Checking the values of the functions in the joint investigation points showed that the value of the seventh function (maximum aftershocks) reaches its maximum value over time before the target earthquake (Figure 2).
 
Fig. 1. Integrated alarm maps, the gray regions are alarm areas, the star sign is Sarpol-e Zahab earthquake epicenter, A) The alarm investigation points at  in all six modes and union of their circles, B) intersection of the alarm areas at
 
Fig. 2. The value of of the M8 algorithm functions over time for the joint investigation points and ,  (time of the target earthquake is shown using a thick vertical line)

The retroactive use of the M8 algorithm showed that the SarPol-e-Zahab earthquake was predictable, and another retroactive successful prediction was added to the M8 algorithm achievements in the Iranian plateau. The results showed that the use of a dense grid of investigation points and integration of the M8 results are effective in reducing the spatial uncertainty of the alarm areas. This approach can reduce the effect of selecting input values in M8 results and lead to more stable results. Results also showed that the increase in maximum aftershocks was important premonitory phenomena for the Sarpol-e-Zahab earthquake.