Development of magnitude correlation equations for the tsunamigenic zones of the Indian Ocean

Abstract

There is a pressing need for a homogonous tsunami catalogue for the Indian Ocean as nearly 20 per cent of tsunami events worldwide affect the region. Any study on tsunami hazard assessment necessitates a homogenous tsunamigenic earthquake catalogue. The existing records of strong tsunamigenic earthquakes have the magnitudes expressed in Moment magnitude (M W ), Body wave magnitude (m b ), Local magnitude (M L ) and Surface wave magnitude (M S ). This study deals with developing regional magnitude correlation equations for tsunamigenic earthquakes of the Indian Ocean.The present investigation estimates the threshold magnitude and focal depth for an earthquake to turn tsunamigenic. It is found that earthquakes above M W ≥ 5.2 and focal depth ≤ 80 km have the potential to generate a tsunami in the region. Since the moment magnitude is the most scientific and reliable scale that describes earthquakes' physical size, equations have been developed to convert surface wave magnitude (M S ) to moment magnitude (M W ). Three types of regression models have been used, viz. Orthogonal Standard Regression (OSR), Standard Regression (SR) and Inverse Standard Regression (ISR). The efficacy of these models has been compared in terms of R-Squared and residual analysis. This study indicates that OSR (Orthogonal Standard Regression) is the best-suited regression model for developing magnitude correlation equations for the region. Magnitude conversion equations for three zones of the Indian Ocean have been created. Additionally, a single unified conversion equation for the whole of the Indian Ocean has also been derived with rational accuracy. Article Highlights The magnitude and focal depth ranges have been identified for the earthquakes to turn potentially tsunamigenic. Magnitude conversion equations have been developed for the Indian Ocean Region. Orthogonal standard regression has been identified as the best fitting regression model.

Forecasting the Future Tsunami Potential of the Indo-Pacific Region Using Artificial Neural Network

“…The use of Arti cial Neural Networks (ANN) in tsunami forecasting has gained attention as a promising approach to improve the accuracy and e ciency of studies on tsunamigenic earthquake potential and forecast (Romano et al 2009;Makinoshima et al 2021). This work is in the continuation of the previous work (Sabah & Shanker 2023a;Sabah & Sil 2020) in which a part of the detailing of the zones and region-speci c magnitude homogenisation relationships have been extended further to investigate the tsunami potential, i.e. the probability of occurrences of tsunamigenic earthquakes of the Indo-Paci c region by integrating stochastic tools and Arti cial Neural Networks.…”

“…In this study, tsunamigenic earthquake magnitudes are homogenised to the Moment Magnitude scale (M W ) de ned by Hanks & Kanamori (1979). For the study Zones 1, 2 and 3, the homogenisation relation developed by Sabah & Shanker (2023a) for converting M S to M W using the OSR approach has been adopted. For the remaining ve zones (Zones 4-8), magnitude correlation equations have been developed using the OSR approach (Fig.…”