# Earthquake Magnitude and Frequency Forecasting in Northeastern Algeria using Time Series Analysis
## 1 Introduction  
Earthquakes are one of the most challenging natural disasters for populations to manage. Even though earthquakes are unpredictable and typically occur without warning, a detailed analysis of the seismic hazard and risk-reduction measures can help to reduce subsequent economic and social losses after the occurrence of an earthquake. The north of Algeria is located on the border of the Nubian Plate, which is in a compressional movement with the Eurasian Plate [1, 2, 3] (Figure 1a). The origin of the seismicity in this region is the compressional movement between these two plates. Known seismic activity (Figure 1b) includes several damaging earthquakes, especially in the last 50 years, where severe earthquakes have been recorded in the El Asnam region (now Chleff), including the earthquakes of 9 September 1954 (Mw 6.8) and 10 October 1980 (Ms 7.3) (see [4]). The most recent significant event was the Zemmouri/Algiers earthquake 21 May 2003 (Mw 6.9), occurring roughly 50 km offshore from the northeast of Algiers (e.g., [5, 6]). In addition, in this period, several earthquakes affected regions close to important cities and caused some damages, such as the Constantine (northeast Algeria) earthquake (Ms 5.9) of 27 October 1985. The interest of the scientific community in approaches to reduce the risk of damaging earthquakes and related seismic risk assessments of urban areas in Northern Algeria is steadily growing in response to this seismic activity. There is always a pressing need for studies on earthquake forecasting, the implementation of building regulations, and safe constructions, especially in developing countries like Algeria, due to the severity of large earthquakes and the damage they produce. The resulting improvement in earthquake risk assessment and hazard management leads to significant savings in human life and properties. The effects of the earthquakes previously mentioned in Northern Algeria [7] indicate the importance of improving estimates of the forecasting from different source zones. Due to its complex tectonics, the Northeastern region of Algeria was chosen as the studied area. On both short- and long-term time periods, earthquake forecasting has significant social and economic consequences. In addition, it plays a main role in earthquake preparedness. On the basis of the quantification of patterns in seismicity data, a wide range of forecasting methods have been proposed with varied degrees of effectiveness [8; 9; 10; 11; 12; 13; 14; 15; 16; 17]. For instance, [PERSON] [17] develops an analysis of the steady increase in seismic activity around a potential earthquake epicenter, known as the accelerating moment release (AMR) approach, while [PERSON] [8] presents and analyses step-by-step the topic of the earthquake prediction. A significant advance in this research field is the earthquake forecasting method based on Regional Earthquake Likelihood Models (RELM) [18; 19; 20; 21]. Nowadays, a new algorithm known as pattern informatics (PI) is also emerging as an advanced method [14]. In addition, new methods based on deep learning are being developed to find a static-stress-based criterion predicting the location of aftershocks [22], as well as the interest in real-time post-seismic forecasting based on ground velocity recorded within the first hour after the mainshock by means of the perceived magnitude [23]. Several studies have been conducted from the perspective of seismic hazard assessment and forecasting. The Gutenberg Richter (GR) model [24] is widely used and states that the logarithm of the cumulative number of events is linearly proportional to the magnitude. Figure 1: Tectonic and seismicity frame. (**a**) Tectonic sketch for the studied region. (**b**) Sha-low seismicity with depth less than 30 km and magnitude above magnitude Mw 4.0. (**c**) Distribution of seismicity with magnitude above Mw 4.0 and distribution of focal mechanism solutions.