Spatial variation of the aftershock activity across the Kachchh Rift Basin and its seismotectonic implications

We analyzed 3365 relocated aftershocks with magnitude of completeness (Mc) ≥1.7 that occurred in the Kachchh Rift Basin (KRB) between August 2006 and December 2010. The analysis of the new aftershock catalogue has led to improved understanding of the subsurface structure and of the aftershock behaviour. We characterized aftershock behaviour in terms of a-value, b-value, spatial fractal dimension (D s ), and slip ratio (ratio of the slip that occurred on the primary fault and that of the total slip). The estimated b-value is 1.05, which indicates that the earthquake occurred due to active tectonics in the region. The three dimensional b-value mapping shows that a high b-value region is sandwiched around the 2001 Bhuj mainshock hypocenter at depths of 20–25 km between two low b-value zones above and below this depth range. The D s -value was estimated from the double-logarithmic plot of the correlation integral and distance between hypocenters, and is found to be 2.64 ± 0.01, which indicates random spatial distribution beneath the source zone in a two-dimensional plane associated with fluid-filled fractures. A slip ratio of about 0.23 reveals that more slip occurred on secondary fault systems in and around the 2001 Bhuj earhquake (Mw 7.6) source zone in KRB

Successful monitoring of the 11 April 2012 tsunami off the coast of Sumatra by Indian Tsunami Early Warning Centre

The Indian Tsunami Early Warning Centre (ITEWC) in Hyderabad monitored the 11 April 2012 tsunami off the coast of Sumatra, which was generated by a shallow strike-slip earthquake and it largest aftershock of magnitude Mw (mB) 8.5 and 8.2 respectively, that occurred inside the subducting slab of the Indian plate. The earthquake generated a small ocean-wide tsunami that has been recorded by various tide gauges and tsunami buoys located in the Indian Ocean region. ITEWC detected the earthquake within 3 min 52 s and issued six advisories (bulletins) according to its Standard Operating Procedure. The ITEWC performed well during the event, and avoided false alarms and unnecessary public evacuations, especially in the mainland part of India region

Probabilistic Assessment of Tsunami Recurrence in the Indian Ocean

The Indian Ocean is one of the most tsunamigenic regions of the world and recently experienced a mega-tsunami in the Sumatra region on 26 December 2004 (M W 9.2 earthquake) with tsunami intensity I (Soloviev-Imamura intensity scale) equal to 4.5, causing heavy destruction of lives and property in the Indian Ocean rim countries. In this study, probabilities of occurrences of large tsunamis with tsunami intensities I ≥ 2.0 and I ≥ 3.0 (average wave heights H ≥ 2.83 m and H ≥ 5.66 m, respectively) during a specified time interval were calculated using three stochastic models, namely, Weibull, gamma and lognormal. Tsunami recurrence was calculated for the whole Indian Ocean and the special case of the Andaman-Sumatra-Java (ASJ) region, excluding the 1945 Makran event from the main data set. For this purpose, a reliable, homogeneous and complete tsunami catalogue with I ≥ 2.0 during the period 1797–2006 was used. The tsunami hazard parameters were estimated using the method of maximum likelihood. The logarithm of likelihood function (ln L) was estimated and used to test the suitability of models in the examined region. The Weibull model was observed to be the most suitable model to estimate tsunami recurrence in the region. The sample mean intervals of occurrences of tsunamis with intensity I ≥ 2.0 and I ≥ 3.0 were calculated for the observed data as well as for the Weibull, gamma and lognormal models. The estimated cumulative and conditional probabilities in the whole Indian Ocean region show recurrence periods of about 27–30 years (2033–2036) and 35–36 years (2039–2040) for tsunami intensities I ≥ 2.0 and I ≥ 3.0, respectively, while it is about 31–35 years (2037–2041) and 41–42 years (2045–2046) for a tsunami of intensity I ≥ 2.0 and I ≥ 3.0, respectively, in the ASJ region. A high probability (>0.9) of occurrence of large tsunamis with I ≥ 2.0 in the next 30–40 years in the Indian Ocean region was revealed

A new insight into crustal heterogeneity beneath the 2001 Bhuj earthquake region of Northwest India and its implications for rupture initiations

The seismic characteristics of the 2001 Bhuj earthquake (Mw 7.6) has been examined from the proxy indicators, relative size distribution (3D b-value mapping) and seismic tomography using a new data set to understand the role of crustal heterogeneities in rupture initiations of the 2001 Bhuj earthquake of the Gujarat (India), one of the disastrous Indian earthquakes of the new millennium. The aftershocks sequence recorded by 22 seismograph stations of Gujarat Seismic Network (GSNet) during the period from 2006 to 2009, encompassing approximately 80 km × 70 km rupture area had revealed clustering of aftershocks at depth of 5–35 km, which is seismogenic layer responsible for the occurrence of continued aftershocks activity in the study region. The 3D b-value mapping estimated from a total of 3850 precisely located aftershocks with magnitude of completeness Mc ⩾ 2.7 shows that a high b-value region is sandwiched within the main shock hypocenter at the depth of 20–25 km and low b-value region above and below of the 2001 Bhuj main shock hypocenter. Estimates of 3-D seismic velocity (Vp; Vs) and Poisson’s ratio (б) structure beneath the region demonstrated a very close correspondence with the b-value mapping that supports the similar physicochemical processes of retaining fluids within the fractured rock matrix beneath the 2001 Bhuj mainshock hypocenter. The overall b-value is estimated close to 1.0 which reveals that seismogenesis is related to crustal heterogeneity, which, in turn also supported by low-Vs and high-б structures. The high b-value and high-б anomaly at the depth of 20–25 km indicate the presence of highly fractured heterogeneous rock matrix with fluid intrusions into it at deeper depth beneath the main shock hypocenter region. Low b-value and high-Vp in the region is observed towards the north-east and north-west of the main shock that might be an indication of the existence of relatively competent rock masses with negligible volume of cracks that may have contained over-pressurized fluids without molten rocks

Stochastic finite fault modelling of M w 4.8 earthquake in Kachchh, Gujarat, India

The modified stochastic finite fault modelling technique based on dynamic corner frequency has been used to simulate the strong ground motions of M w 4. 8 earthquake in the Kachchh region of Gujarat, India. The accelerograms have been simulated for 14 strong motion accelerographs sites (11 sites in Kachchh and three sites in Saurashtra) where the earthquake has been recorded. The region-specific source, attenuation and generic site parameters, which are derived from recordings of small to moderate earthquakes, have been used for the simulations. The main characteristics of the simulated accelerograms, comprised of peak ground acceleration (pga), duration, Fourier and response spectra, predominant period, are in general in good agreement with those of observed ones at most of the sites. The rate of decay of simulated pga values with distance is found to be similar with that of observed values. The successful modelling of the empirical accelerograms indicates that the method can be used to prepare wide range of scenarios based on simulation which provide the information useful for evaluating and mitigating the seismic hazard in the region

Earthquake Generated Tsunami in the Indian Ocean and Probable Vulnerability Assessment for the East Coast of India

The tsunami hazard for the east coast of India is assessed. The Sumatra-Andaman 1300 km long fault is divided into five segments, each segment assumed to have different fault parameters. The initial vertical displacement of the sea bottom is calculated with the Mansinha and Smylie algorithm. Modeling of tsunami amplitude, travel time, run-up and directivity has been done. We compared simulated tsunami travel times and elevation with data measured at tide gauges and coastal runup. The model results show that the distribution of maximum amplitude in the Indian Ocean basin is primarily controlled by the classical effects of the directivity and by refraction and focusing along bathymetric features. The results suggest 7-8 m run up height at Nagapatanam, Tamil Nadu, which was the worst affected region in the mainland of India during the 2004 Indian Ocean tsunami

An application of regional time and magnitude predictable model for long-term earthquake prediction in the vicinity of October 8, 2005 Kashmir Himalaya earthquake

A regional time and magnitude predictable model has been applied to estimate the recurrence intervals for large earthquakes in the vicinity of 8 October 2005 Kashmir Himalaya earthquake (25°-40°N and 65°-85°E), which includes India, Pakistan, Afghanistan, Hindukush, Pamirs, Mangolia and Tien-Shan. This region has been divided into 17 seismogenic sources on the basis of certain seismotectonics and geomorphological criteria. A complete earthquake catalogue (historical and instrumental) of magnitude Ms â 5.5 during the period 1853-2005 has been used in the analysis. According to this model, the magnitude of preceding earthquake governs the time of occurrence and magnitude of future mainshock in the sequence. The interevent time between successive mainshocks with magnitude equal to or greater than a minimum magnitude threshold were considered and used for long-term earthquake prediction in each of seismogenic sources. The interevent times and magnitudes of mainshocks have been used to determine the following predictive relations: logTt = 0.05 Mmin + 0.09 Mp - 0.01 log M0 + 01.14; and Mf = 0.21 Mmin - 0.01 Mp + 0.03 log M0 + 7.21 where, Tt is the interevent time of successive mainshocks, Mmin is minimum magnitude threshold considered, Mp is magnitude of preceding mainshock, Mf is magnitude of following mainshock and M0 is the seismic moment released per year in each seismogenic source. It was found that the magnitude of following mainshock (Mf) does not depend on the interevent time (Tt), which indicates the ability to predict the time of occurrence of future mainshock. A negative correlation between magnitude of following mainshock (Mf) and preceding mainshock (Mp) indicates that the larger earthquake is followed by smaller one and vice versa. The above equations have been used for the seismic hazard assessment in the considered region. Based on the model applicability in the studied region and taking into account the occurrence time and magnitude of last mainshock in each seismogenic source, the time-dependent conditional probabilities (PC) for the occurrence of next shallow large mainshocks (Ms â6.5), during next 20 years as well as the expected magnitudes have been estimated

Estimation of seismic hazard in Gujarat region, India

The seismic hazard in the Gujarat region has been evaluated. The scenario hazard maps showing the spatial distribution of various parameters like peak ground acceleration, characteristics site frequency and spectral acceleration for different periods have been presented. These parameters have been extracted from the simulated earthquake strong ground motions. The expected damage to buildings from future large earthquakes in Gujarat region has been estimated. It has been observed that the seismic hazard of Kachchh region is more in comparison with Saurashtra and mainland. All the cities of Kachchh can expect peak acceleration in excess of 500 cm/s2 at surface in case of future large earthquakes from major faults in Kachchh region. The cities of Saurashtra can expect accelerations of less than 200 cm/s2 at surface. The mainland Gujarat is having the lowest seismic hazard as compared with other two regions of Gujarat. The expected accelerations are less than 50 cm/s2 at most of the places. The single- and double-story buildings in Kachchh region are at highest risk as they can expect large accelerations corresponding to natural periods of such small structures. Such structures are relatively safe in mainland region. The buildings of 3-4 stories and tall structures that exist mostly in cities of Saurashtra and mainland can expect accelerations in excess of 100 cm/s2 during a large earthquake in Kachchh region. It has been found that a total of 0.11 million buildings in Rajkot taluka of Saurashtra are vulnerable to total damage. In Kachchh region, 0.37 million buildings are vulnerable. Most vulnerable talukas are Bhuj, Anjar, Rapar, Bhachau, and Mandvi in Kachchh district and Rajkot, Junagadh, Jamnagar, Surendernagar and Porbandar in Saurashtra. In mainland region, buildings in Bharuch taluka are more vulnerable due to proximity to active Narmada-Son geo-fracture. The scenario hazard maps presented in this study for moderate as well as large earthquakes in the region may be used to augment the information available in the probabilistic seismic hazard maps of the region

Regional variation of the ω-upper bound magnitude of GIII distribution in Hindukush-Pamir Himalaya and the adjacent regions: A perspective on earthquake hazard

The upper bound magnitude (ω) or maximum magnitude in 28 seismogenic source zones in the Hindukush-Pamir Himalaya and the adjacent regions have been computed with the help of a complete and homogeneous earthquake catalogue during the period 1900–2010 to estimate the earthquake hazards in the region. The Gumbel's third asymptotic distribution (GIII) of extreme value method is used to estimate this parameter. In this study, a comparison of maximum magnitude obtained by GIII distribution is carried out with Kijko–Sellevoll method. It is observed that the maximum earthquake magnitudes estimated by Kijko–Sellevoll and GIII methods are comparable to each other and the average of differences of their values is only 0.13. The results also estimate the most probable earthquake magnitude that can be expected in next 100 years (M100) in all 28 seismogenic source zones. An effort is made to make regression relations between ω and maximum magnitude estimated by Kijko–Sellevoll method (Mmax(KS)) and ω and maximum observed magnitude (Mmaxobs). The estimated ω values exceeded the value of 7.00 in 15 and 8.00 in 5 of the 28 seismogenic source zones. The geographical distribution of ω and M100 in 28 seismogenic source zones of the study region is visualized to analyze the localized seismicity parameters. It is observed that earthquake hazard level varies spatially from one zone to another, which suggests that examined region have high crustal heterogeneity and seismotectonic complexity