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In the network‐based on‐site earthquake early warning system (EEWS), the 'blind zone', namely the zone where the issued warning arrives later than the destructive S and surface waves, is one of the challenges affecting its effectiveness. The 'blind zone' is determined by the interstation distance, or equivalently the density of seismic stations, of the network. In this paper, we suggest a practical approach according to which, when in a region a temporary increase of seismic hazard is declared, additional stations are deployed in such a way that the blind zone is temporarily reduced. In the procedure, the time‐dependent neo‐deterministic seismic hazard assessment (TD‐NDSHA) plays a vital role in the identification of the regions potentially exposed to high macroseismic intensities. As a showcase example, we consider the scenario of year 2014 at the Sichuan‐Yunnan border of southwest China. The TD‐NDSHA is based on the standard NDSHA procedure at regional scale (bedrock conditions), with the 'controlling earthquakes' defined on the basis of the Annual Consultation. We show that the 'blind zone' can be reduced in the identified areas of interest (e.g., MMI ≥ VI), by deploying a limited number of additional seismic stations. In the case where false alarms can be tolerated, significant reduction of the 'blind zone' can be implemented by moving from a network‐based EEWS to a single‐sensor‐based EEWS and skipping the process of location and magnitude‐determination/prediction procedures. [ABSTRACT FROM AUTHOR]

In this paper, we discuss a possible combination of Earthquake Early Warning (EEW) and Neo-deterministic Seismic Hazard Assessment (NDSHA), and propose a new warning model, EEW2.0. The aim is to provide a differentiated warning alert to various end-users based on the results of seismic hazard assessment evaluation. The implementation of such a system contains three basic steps: (a) classification of "potential to cause hazard" in terms of magnitude; (b) determination of the source areas and building a hazard database in terms of Modified Mercalli Intensity (MMI) maps, considering all possible earthquake scenarios in the source area, for the whole protected area; (3) equipping unique decision framework for specific end-users. When a damaging earthquake (M ≥ 5.0) is detected, EEW2.0 quickly matches the prepared MMI map by estimated magnitude and epicenter, then directly extracts the MMI value and issues an early warning to the public. With the great attention and resources put into the reduction in seismic and its secondary risk in the 21st century, the proposed EEW2.0 will likely play an active role in protecting lives and reducing economic losses. [ABSTRACT FROM AUTHOR]

A seismic hazard map of the territory of India and adjacent areas has been prepared using a deterministic approach based on the computation of synthetic seismograms complete with all main phases. The input data set consists of structural models, seismogenic zones, focal mechanisms and earthquake catalogues. There are few probabilistic hazard maps available for the Indian subcontinent, however, this is the first study aimed at producing a deterministic seismic hazard map for the Indian region using realistic strong ground motion modelling with the knowledge of the physical process of earthquake generation, the level of seismicity and wave propagation in anelastic media. Synthetic seismograms at a frequency of 1 Hz have been generated at a regular grid of by the modal summation technique. The seismic hazard, expressed in terms of maximum displacement , maximum velocity , and design ground acceleration (DGA), has been extracted from the synthetic signals and mapped on a regular grid over the studied territory. The estimated values of the peak ground acceleration are compared with the observed data available for the Himalayan region and are found to be in agreement. Many parts of the Himalayan region have DGA values exceeding 0.6 g. The epicentral areas of the great Assam earthquakes of 1897 and 1950 in northeast India represent the maximum hazard with DGA values reaching 1.2–1.3 g. The peak velocity and displacement in the same region is estimated as 120–177 cm s−1 and 60–90 cm, respectively. [ABSTRACT FROM AUTHOR]

Examines the numerical modelling of waveforms in heterogeneous anelastic media. Seismic microzonation of urban areas; Factors contributing to seismic signal; Use of synthetic computations in determining the properties of seismic input.