Himalayan earthquakes have deep societal and economic impact. In this article, we implement a surrogate method of nowcasting (Rundle et al., 2016) to determine the current state of seismic hazard from large earthquakes in a dozen populous cities from India and Pakistan that belong to the west-northwest part of Himalayan orogeny. For this, we (1) perform statistical inference of natural times, intersperse counts of small-magnitude events between pairs of succeeding large events, based on a set of eight probability distributions; (2) compute earthquake potential score (EPS) of 14 cities from the best-fit cumulative distribution of natural times; and (3) carry out a sensitivity testing of parameters—threshold magnitude and area of city region. Formulation of natural time (Varostos et al., 2005) based on frequency–magnitude power-law statistics essentially avoids the daunting need of seismicity declustering in hazard estimation. A retrospective analysis of natural time counts corresponding to M≥6 events for the Indian cities provides an EPS (%) as New Delhi (56), Chandigarh (86), Dehradun (83), Jammu (99), Ludhiana (89), Moradabad (84), and Shimla (87), whereas the cities in Pakistan observe an EPS (%) as Islamabad (99), Faisalabad (88), Gujranwala (99), Lahore (89), Multan (98), Peshawar (38), and Rawalpindi (99). The estimated nowcast values that range from 38% to as high as 99% lead to a rapid yet useful ranking of cities in terms of their present progression to the regional earthquake cycle of magnitude ≥6.0 events. The analysis inevitably encourages scientists and engineers from governments and industry to join hands for better policymaking toward land-use planning, insurance, and disaster preparation in the west-northwest part of active Himalayan belt.

Large devastating events such as earthquakes often display frequency–magnitude statistics that exhibit power-law distribution. In this study, we implement a recently developed method called earthquake nowcasting (Rundle et al. in Earth Space Sci 3: 480–486, 2016) to evaluate the current state of earthquake hazards in the seismic prone Sulawesi province, Indonesia. The nowcasting technique considers statistical behavior of small event counts between successive large earthquakes, known as natural times, to infer the seismic progression of large earthquake cycles in a defined region. To develop natural-time statistics in the Sulawesi Island, we employ four probability models, namely exponential, exponentiated exponential, gamma, and Weibull distribution. Statistical inference of natural times reveals that (i) exponential distribution has the best representation to the observed data; (ii) estimated nowcast scores (%) corresponding to M ≥ 6.5 events for 21 cities are Bau-bau (41), Bitung (70), Bone (44), Buton (39), Donggala (63), Gorontalo (49), Kendari (27), Kolaka (30), Luwuk (56), Makassar (52), Mamuju (58), Manado (70), Morowali (37), Palopo (34), Palu (62), Pare-pare (82), Polewali (61), Poso (42), Taliabu (55), Toli-toli (58), and Watampone (55); and (iii) the results are broadly stable against the changes of magnitude threshold and area of local regions. The presently revealed stationary Poissonian nature of the underlying natural-time statistics in Sulawesi brings out a key conclusion that the seismic risk is the same for all city regions despite their different levels of cycle progression realized through nowcast scores. In addition, though the earthquake potential scores of the city regions will be updated with the occurrence of each small earthquake in the respective region, the seismic risk remains the same throughout the Sulawesi Island.

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Large devastating events such as earthquakes often display frequency-magnitude statistics that exhibit power-law distribution. In this study, we implement a new method of nowcasting (Rundle et al. 2016) to evaluate the current state of earthquake hazards in the seismic prone Sulawesi province, Indonesia. The nowcasting technique considers statistical behavior of small event counts, known as natural times, to infer the seismic progression of large earthquake cycles in a defined region. To develop natural time statistics in the Sulawesi Island, we employ four probability models, namely exponential, exponentiated exponential, gamma, and Weibull distribution. Statistical inference of natural times reveals that (i) exponential distribution has the best representation to the observed data; (ii) estimated nowcast scores (%) corresponding to M≥6.5 events for 21 cities are Bau-bau (41), Bitung (70), Bone (44), Buton (39), Donggala (63), Gorontalo (49), Kendari (27), Kolaka (30), Luwuk (56), Makassar (52), Mamuju (58), Manado (70), Morowali (37), Palopo (34), Palu (62), Pare-pare (82), Polewali (61), Poso (42), Taliabu (55), Toli-toli (58), and Watampone (55); and (iii) the results are broadly consistent to the changes of magnitude threshold and area of local regions. Therefore, the present nowcasting analysis, similar to the traditional earthquake hazard assessment techniques, offers a simple yet versatile metric to the scientists, engineers and policymakers to examine the current state of earthquake hazards in the thickly populated Sulawesi Island.