Forecasting seismic activity rates in northwest Himalaya through multivariate autoregressive forecast of seismicity algorithm

Chingtham, Prasanta; Tiwari, Anurag; Yadav, Arabind Kumar

doi:10.1007/s11600-019-00267-5

Artykuł - szczegóły

Tytuł artykułu

Forecasting seismic activity rates in northwest Himalaya through multivariate autoregressive forecast of seismicity algorithm

Autorzy

Chingtham Prasanta , Tiwari Anurag , Yadav Arabind Kumar

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-019-00267-5

Warianty tytułu

Języki publikacji

Abstrakty

In this study, a model based on multivariate autoregressive forecast of seismicity (MARFS) algorithm is adopted to forecast seismic activity rates in northwest Himalaya, using the compiled homogenized moment magnitude (MW) based catalogue. For this purpose, each source zone delineated by Yadav et al. (Pure Appl Geophys 170:283–295, 2012) is divided into a spatial grid interval of 0.5° × 0.5° while the entire catalogue span (1975–2010) is segregated into six time periods/grids to estimate seismic activity rates spatially and temporally. These seismic activity rates which are estimated from spatial density map of hypocenters exhibit high values in Chaman Fault (Zone 1), Hindukush-Pamir region (Zone 3) and the mega thrust systems, i.e., Main Central Thrust, Main Boundary Thrust and Himalayan Frontal Thrust (Zone 4). Then, the seismic activity rates during 2011–2016 could be forecasted by extrapolating (through auto-regression procedure) those observed for previous time periods. The forecast seismic activity rates are estimated within the values of 0 and 7.57 with high values primarily observed in Hindukush-Pamir region of Zone 3 and the gently north-dipping thrust fault systems (Main Central Thrust, Main Boundary Thrust, Himalayan Frontal Thrust) of Zone 4. Finally, the associated area under the curve of receiver operating characteristics graph suggests the superiority of forecasting model with respect to random prediction, whereas results of the data-consistency test, i.e., N test of our model, exhibit consistency in between the observed and simulated likelihoods. Moreover, the hypothetical t test performed in between the spatial grids of forecast seismic activity rates and observed seismic activity rates confirms that the former is consistent with the latter.

Słowa kluczowe

seismicity autoregression forecast model Northwest Himalaya

sejsmiczność autoregresja model prognostyczny Himalaje północno-zachodnie

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2019

Tom

Vol. 67, no. 2

Strony

465--476

Opis fizyczny

Bibliogr. 70 poz.

Twórcy

autor

Chingtham Prasanta

prasantachingtham@gmail.com

National Center for Seismology, Ministry of Earth Sciences, New Delhi 110003, India

autor

Tiwari Anurag

National Center for Seismology, Ministry of Earth Sciences, New Delhi 110003, India

autor

Yadav Arabind Kumar

Geological Survey of India, Kolkata 700016, India

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).

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