Author(s): Ravindra Kumar Gupta; Mukat Lal Sharma; C. Lallawmawma And Mudit Srivastava
Linked Author(s): MUKAT LAL SHARMA, Ravindra Kumar Gupta
Keywords: Declustering Seismic Hazard Purvanchal Seismic Parameters and Dams
Abstract: Declustering is an important step in seismic hazard assessment because it separates earthquake catalogues into independent (mainshock) and dependent (clustered) occurrences. This ensures proper seismicity parameter estimation for hazard assessments. The present study compares three widely used declustering algorithms-Gardner and Knopoff (1974) (GK), Reasenberg (1985) (RN), and Zaliapin and Ben-Zion (2020) (NN) -to earthquake catalogues from the Purvanchal region of Uttar Pradesh, India (76°E-86°E, 20°N-30°N). The catalogue, which includes 4,202 events, shows significant differences in retained mainshocks across methods: GK retained 54.43% (removing 45.57%), NN kept 44.81% (removing 55.19%), and RN retained 82.41% (removing 17.59%). These differences demonstrate the susceptibility of declustering results to method selection and parameter modification. The study further examines the effect of declustering on the Gutenberg-Richter parameters, ‘a’ and ‘b’values, which significantly influence seismic hazard assessments. The results show that the choice of declustering algorithm has a significant impact on these parameters, altering the reliability of hazard assessment. This has significant consequences for applications such as dam safety, where precise seismic assessments are required to ensure infrastructure resilience. Careful algorithm selection and parameter optimization are thus required for robust and reliable seismic hazard assessment.
Year: 2025