80 Years of research on tsunamigenic earthquakes in the Makran subduction zone (1945–2025): a review- part C: tsunami hazard and risk assessments

Abstract

This paper constitutes Part C of a three-part review series addressing tsunamigenic earthquakes in the Makran Subduction Zone (MSZ), with a specific focus on tsunami hazard and risk assessment methodologies. It provides a comprehensive, multidisciplinary synthesis of probabilistic and deterministic tsunami hazard assessments and associated risk analyses developed for the MSZ, integrating advances in numerical modelling techniques. Emphasis is placed on Probabilistic and Deterministic Tsunami Hazard assessments (PTHA and DTHA) frameworks, which are pivotal for quantifying uncertainties in inundation forecasts, particularly integrating historical data, paleotsunami records, and multi-scenario simulations. This review part also evaluates how improvements in source characterization, bathymetric resolution, and hydrodynamic modeling have enhanced tsunami forecasting capabilities in the region, while also highlighting persistent limitations related to offshore data scarcity and constrained observational records. In addition, spatial patterns of vulnerability and exposure across coastal communities, highlighting how socioeconomic conditions, coastal geomorphology, and infrastructure distribution interact to shape tsunami risk. Mitigation strategies, including tsunami early-warning systems, coastal land-use planning, evacuation, and emergency preparedness, are reviewed in the context of their effectiveness and applicability to the MSZ. By synthesizing the evolution of tsunami hazard and risk assessment approaches, this study offers a scientific foundation for improved coastal resilience and helps guide future research directions. The findings support disaster-risk-reduction objectives, aligning with the United Nations Sendai Framework and UNDRR Goal 2030 toward safer and more sustainable coastal communities in seismically active regions.

1 Introduction

The MSZ is a region capable of generating large tsunamigenic earthquakes with basin-wide tsunami impacts. Extending along the southeastern margin of Iran and southwestern Pakistan, the MSZ accommodates the subduction of the Arabian Plate beneath the Eurasian Plate and poses a persistent tsunami hazard to the coastlines of Iran, Pakistan, Oman, India, and the United Arab Emirates (UAE) (Figure 1). Despite relatively low rates of instrumental seismicity, geological and historical evidence indicates that the MSZ has generated multiple destructive tsunamis over centennial to millennial timescales, underscoring the region’s potential for rare but high-consequence events (reviewed in Hamidatou et al., 2026a; Hamidatou et al., 2026b).

FIGURE 1

This Part C of the three-part review (Hamidatou et al., 2026a; Hamidatou et al., 2026b) provides a detailed review of tsunami hazard and risk assessments conducted within the MSZ. The review synthesizes advances in deterministic and probabilistic tsunami hazard assessment (DTHA and PTHA), focusing on the estimation of tsunami sources, wave propagation, inundation extents, and run-up heights along near-field and far-field coastlines. Emphasis is placed on how hazard models have integrated MSZ-specific geological and tectonic constraints, including segmented seismogenic structures, coupling variations, splay faults, and sediment deformation processes.

Uncertainties remain a defining challenge in MSZ tsunami assessments. This review examines historical earthquake–tsunami records, paleotsunami evidence, and multi-scenario numerical simulations reflecting potential megathrust ruptures and submarine landslides unique to the MSZ.

2 The 1945 Makran tsunami

The tsunami generated by the 27 November 1945 Makran earthquake (M_w 8.1) is widely regarded as the most devastating tsunami event in the Arabian Sea and remains the benchmark for tsunami hazard assessment in the MSZ. The earthquake produced widespread coastal inundation and significant loss of life along the coastlines of Pakistan, Iran, Oman, and western India, highlighting the far-reaching consequences of tsunamigenic earthquakes in this region. Owing to its scale and societal impact, the 1945 Makran tsunami has been the subject of extensive scientific investigation.

Numerous studies have examined this event using a variety of analytical approaches, including archival analysis of historical documents, post-event field surveys, geoseismological investigations, and both analytical and numerical tsunami modelling (e.g., Akbarpour Jannat, 2021). These studies report considerable variability in estimated source parameters, tsunami wave heights, and inundation extents, reflecting uncertainties in rupture geometry, slip distribution, and the relative contribution of coseismic deformation versus submarine landslides. Published estimates of coastal run-up generated by the 1945 Makran tsunami vary substantially among studies due to differences in assumed rupture geometry, slip distribution, bathymetric representation, and modelling approach. Reported maximum run-up values along the central Makran coast range from a few metres to more than 10 m, reflecting persistent uncertainty in reconstructing the source characteristics and coastal amplification processes of the event. A comparison of literature-derived run-up estimates for the 1945 tsunami is shown in Figure 2. Reported maximum tsunami run-up values from multiple studies show substantial variability (≈2–15 m) due to differences in rupture geometry, slip distribution, and modelling approaches. Horizontal bars indicate the range of estimates for each study, illustrating persistent uncertainty in reconstructing the 1945 event and its coastal impact.

FIGURE 2

Part C synthesizes all previously published deterministic and probabilistic tsunami hazard assessments related to the 1945 Makran event, providing a critical comparison of modelling assumptions, data inputs, and resulting hazard estimates. This synthesis highlights key sources of uncertainty, including limited offshore geophysical data, poorly constrained slip distributions, and sparse near-field observations. At the same time, it demonstrates how the 1945 event has shaped current understanding of tsunami generation mechanisms in the MSZ and continues to inform scenario-based hazard modelling across the region.

Beyond hazard characterization, this review evaluates tsunami risk by examining patterns of exposure and vulnerability along MSZ-adjacent coastlines. Rapid coastal urbanization, expanding port infrastructure, and limited evacuation capacity significantly amplify tsunami risk in several population centers. Existing mitigation measures such as early-warning systems, tsunami hazard zoning, and emergency preparedness initiatives are assessed, while critical research gaps are identified. These include the need for high-resolution bathymetric and topographic data, more extensive paleotsunami investigations, and improved constraints on earthquake recurrence intervals and maximum credible magnitudes.

Overall, the current review provides an integrated assessment of tsunami hazard and risk in the MSZ, demonstrating how lessons from the 1945 Makran tsunami continue to shape modern hazard modelling. The review underscores the necessity of refined numerical models, enhanced offshore observations, and interdisciplinary data integration to strengthen tsunami resilience and support effective risk reduction strategies across the northern Arabian Sea.

2.1 Tsunami hazard assessment

Given the seismic and tsunami hazard associated with the MSZ, scientists and researchers actively monitor the area to gain deeper insights into its behavior and enhance earthquake and tsunami forecasting and preparedness efforts.

2.1.1 Review Methodology

This study compiles and synthesizes research on tsunamigenic earthquakes in the MSZ, published between 1945 and 2025. It includes key studies addressing tsunami hazard assessment, both PTHA and DTHA related to near- and far-field impacts across the region, as well as risk assessment. The literature was collected from major scientific databases, including Web of Science, Scopus, Google Scholar, and Dimensions. Only relevant peer-reviewed articles, review papers, conference proceedings, and book chapters were considered to ensure scientific relevance and consistency (Hamidatou and Alebri, 2026).

A structured search strategy was applied using combinations of keywords such as: Makran Subduction Zone; tsunami; tsunamigenic earthquake; tsunami hazard; PTHA; DTHA; travel time; wave height; inundation; vulnerability; and risk. The selected studies were then critically reviewed and grouped according to their thematic focus, including source characterization, tsunami modeling, hazard assessment approaches, and risk and vulnerability analyses. This approach ensures a comprehensive and coherent synthesis of both the physical processes and the societal implications of tsunamigenic earthquakes in the MSZ (Hamidatou and Alebri, 2026). A comprehensive bibliometric study of the 80 years of research on tsunamigenic earthquakes in the MSZ has been recently published by Hamidatou and Alebri (2026).

2.1.2 Probabilistic tsunami hazard assessment (PTHA)

MSZ can generate large tsunamigenic earthquakes (M ∼ 9). Owing to the limited geologic, seismic, and geodetic data, uncertainties exist when characterizing the tsunami sources. PTHA is the most commonly used method to address these uncertainties, and it provides more reliable tsunami hazard estimates (Zafarani et al., 2023). A compilation of PTHA studies along the Arabian coast was presented by Zafarani et al. (2023) and updated by Gardezi et al. (2024).

Heidarzadeh et al. (2008a) and Heidarzadeh et al. (2009a) evaluated the tsunami hazard in the northwestern Indian Ocean by calculating the maximum regional earthquake magnitude using the method developed by (Kijko, 2004) and by assessing the recurrence parameters for the MSZ, following the procedure developed by Kijko and Sellevoll (1992). They estimated the probability of MSZ earthquakes of varying magnitudes for the next 1, 50, 100, and 1,000 years. Based on the results of seismic hazard analysis, the maximum regional earthquake magnitude in the MSZ was determined to be M_w 8.3, and a series of tsunamis were simulated. An M_w 8.3 earthquake would have a return period of ∼ 1,000 years; the probability of experiencing such an earthquake within the next 50 and 100 years is ∼ 5% and 10%, respectively (Heidarzadeh et al., 2009a). Burbidge et al. (2009) presented a PTHA for Indian Ocean nations from three subduction zones of the Makran, Sumatra–Andaman, and South Sandwich, by illustrating hazard curves and tsunami hazard maps for a return period of 2,000 years, assuming the maximum magnitude as that of the largest earthquake globally, M_w 9.5 (the 1960 South Chile earthquake). According to the study, the Northwest Indian Ocean nations are the most vulnerable to the MSZ. The maximum offshore amplitude with a 1 in 2,000-yr chance of being exceeded was 3.8 m for Oman, 2.8 m for Pakistan, 2.7 m for Iran, while for the UAE, it was 0.8 m (Burbidge et al., 2009; reviewed in Rashidi et al., 2020). Heidarzadeh and Kijko (2011) assessed the PTH at the MSZ from three 1945-type (M_w 8.1) sources along the coastlines of Iran, Pakistan, and Oman, using the seismic probabilistic method of Kijko and Sellevoll (1992) for tsunamis. The results demonstrated that the southern coasts of Iran, Pakistan, and Oman (Muscat) were the most vulnerable areas, with a probability of tsunami waves exceeding 5 m during the next 50 years being 17.5%. Furthermore, a probability value as high as 45% is observed for moderate tsunamis (1 ≤ h < 2 m) along the same coasts during the next 50 years. In Karachi, the probabilities of waves exceeding 1 and 2 m are ∼ 32% and 18%, respectively, whereas those for many adjacent cities are zero. Dababneh et al. (2012) studied the probable maximum tsunami because of an earthquake in the MSZ using the Delft3D numerical model (From Sowmya et al., 2018); however, no data is available. Höchner et al. (2014) modelled the historic Balochistan (1945) event and its effects on coastal wave heights, generating various synthetic earthquake and tsunami catalogues, including the possibility of large events, to assess the tsunami hazard in the affected coastal regions. However, no data was shared. Hochner et al. (2015) and Hochner et al. (2016) conducted a PTHA for the MSZ using Sørensen et al. (2012) method, which involved different synthetic earthquake catalogues generated for a time length of 300,000 years. All the events in the catalogues (M_w 7.4–9.4) were simulated to estimate probabilistic wave tsunami heights and hazard curves along the Makran coastlines in Iran, Pakistan, and Oman. For Iran and Pakistan, the probabilistic tsunami hazard for some specific location in the central region was ∼ 12 m in 5,000 years and 2 m in 500 years, while the PTH for the whole coastline as a whole is much higher, ∼ 21 and 9 m, respectively, with Jiwani showing the highest hazard. For Oman, the hazard in general was lower. Additionally, the Probability of Exceedance (POE) for 2 m/50 years, 8 m/500 years, and 15 m/5,000 years are used for comparison. The effect of the assumed maximum magnitude for the synthetic seismic catalogue on tsunami hazard was demonstrated. For Iran and Pakistan, the POE 15 m in 5,000 years increased from 21% for M_Max = 8.2–75% for M_Max = 8.6 and 93% for M_Max = 9.0. To investigate breakwater stability on the northern coastlines of the Sea of Oman in the event of a major tsunami, Banijamali et al. (2017) employed a PTHA approach, as described by Rikitake and Aida (1988). At Jask, Konarak, and Beheshti ports, the POE 1 m became close to zero. Comparatively, Zar-Abad experienced relatively large tsunami amplitudes exceeding 5 m, associated with a 20% probability over the next 100 years. For the sake of comparison, while the POE 2 m is almost zero for many of the considered breakwaters, it reaches ∼ 40% at Zar-Abad. El-Hussain et al. (2016) performed a PTHA for the coast of Oman from a range of small and large scenarios (M_w 7.5–9.1 with a 0.2 interval) in the MSZ using a logic-tree approach. They presented a set of probability hazard exceedance maps for the Oman shoreline, covering different time periods of 100, 250, 500, and 1,000 years. Their results indicate that the POE 1 m somewhere along the coast of Oman reaches, respectively, 0.7 and 0.85 for 100 and 250 exposure times, and it is up to 1 for 500-year and 1,000-year exposure times. The POE 1 m reaches 100% at some locations along the northern Omani coast. These probability values decrease significantly toward the Southern coast of Oman as the reaching wave amplitudes are less than 1 m.

Davies et al. (2017) conducted a PTHA on a global scale, including the MSZ for M_w 7.5–8.1 and M_w 8.8–9.5, showing that the probabilistic tsunami wave height along the Makran coastlines is generally in the same range; however, it decreases towards the Strait of Hormuz. They revealed that tsunami wave amplitude varied between 1 and 5 m and between 5 and 10 m for return periods of 500 and 2,500 years, respectively (reviewed by Zafarani et al., 2023). El-Hussain et al. (2018) conducted a high-resolution PTHA for Sur, Oman, of a near-field tsunami using the earthquake scenario database with magnitudes ranging from M_w 7.5 to 8.8. A benchmarked numerical model and a high-resolution coastal Digital Elevation Model (DEM) were combined with seismic source probability models and a logic-tree framework, generating local hazard maps displaying the probability of tsunami wave height/flow depth exceeding different thresholds within given exposure times of 100 and 500 years. The probabilistic analysis showed that for an average return time of 100-year, the POE 0.5 m reaches 100% along the entire target coast. This probability ranges from 50% to 80% and from 20% to 60% for maximum wave height thresholds of 1 and 1.5 m, respectively. In the 500-year exposure time, the POE 1.5 m wave height reaches 100% at some locations. Additionally, in a 500-year average return period, the likelihood of tsunami flood occurrence in Sur reaches 100% and 80%, respectively, with a flow depth of 1 m. Sarker (2019) showed that in Pasni, Pakistan, movements on the MSZ resulted in an initial rise in the sea surface (above the fault of 1 m on a one in 100-year event and 2 m on a 1 in 1,000-year event), with the West segment being the worst fault area, generating a higher rise in sea level and stronger currents compared with the 1945 fault area. Rashidi and Farajkhah (2019) assessed the PTH along the Southeastern coast of Iran, considering the entire, Western, and Eastern Makran tsunamigenic sources and a range of magnitudes, 7.5–8.8 and 7.5–8.9 for the Western and Eastern Makran, respectively, and 7.5–9.1 for the entire Makran. The annual number of earthquakes was computed via the truncated Gutenberg-Richter relation (Cosentino et al., 1977; Weichert, 1980), while the tsunamis were modelled using the COMCOT algorithm (Liu et al., 1998). The PTHA results showed that the Konarak and Sirik coastlines are the most and least at risk from tsunamis, respectively. The POE 1 and 3 m increased with time. The POE 3 m in 500-year is ∼ 63% and 0% near the Konarak and Sirik coastlines, respectively. The maximum POE for 3 m belongs to the area between Beris and the West of Kereti. The annual POE rates are 100%, 40%, and 20%, respectively, for POE 1, 2, and 3. Momeni et al. (2020) assessed the tsunami hazard of the 1945 MSZ event using 1,000 stochastic earthquake scenarios with magnitudes ranging from M_w 8.1 to 8.3, considering uncertainties in rupture geometry and slip heterogeneity. The identified source model was 270 km in length, 130 km in width, with a mean slip of 2.9 m and a maximum slip of 19.3 m. The results showed maximum tsunami heights of 0.3–7 m and coseismic deformation of −2.7 to 1.1 m at Ormara. Rashidi et al. (2020) performed a PTHA in the near-field for all synthetic scenarios along the coastlines of Iran, Pakistan, and Oman by generating a series of random heterogeneous slip models for a non-planar fault geometry of the MSZ. Tsunami probability maps were created for 0.5 and 3 m wave heights over 50, 250, and 1,000 years, along with hazard curves for the studied coastlines. Results showed similar POE distributions along shorelines, with POE for 3 m waves increasing over time. Between Jask and Ormara, POE ranged from 0 to 0.56 in 50 years, reaching 1 in 1,000 years. Muscat-Sur showed POE up to 0.99 in 250 years, decreasing westward. For Iran-Pakistan and Oman, POE for 3 m was ∼0.6 in 50 years, reaching 1 in 250 and 1,000 years. POE 9 m at the coast of Iran-Pakistan were 0.33, 0.86, and 1 in 50, 250, and 1,000 years, and 0.11, 0.43, and 0.9 for Oman, respectively. The annual POE for 1 and 5 m waves remained constant at 0.018, dropping exponentially for larger waves. Slip heterogeneity influenced wave height variation, especially around rupture asperities. Maximum peak run-up was ∼ 16 m on the coast of Iran, 11 m in Konarak, 10 m in Chabahar, 5 m in Jiwani, and 2 m in Jask. Rashidi et al. (2022) assessed PTH along the shorelines of Iran, Pakistan, and Oman for fault sources in the Western Makran, utilizing the interpretation of seismic reflection data, the structural restoration technique, and a logic-tree approach. The results showed a lower hazard level for the Pakistan coastline compared with that of Iran and Oman, with the areas between Jask and Beris, and Muscat and Sur being the most hazardous. Southern Oman comprised a lower POE than that of northern Oman. The POE 3 m along the coastlines of Iran and Oman in 10, 50, and 250 years reaches ∼ 30%, 70%, and 90% respectively. The estimated POE 1 m along the Iran-Pakistan and Oman coastlines in 50 and 250 years is up to 100%. The annual POE 1, 2, and 3 m along the Iran-Pakistan shoreline is 45%, 16%, and 6%, respectively, and along the Oman coastline it is 35%, 10%, and 6%, respectively. Short-term tsunami hazard along the Makran coastlines is not very significant due to the current low seismicity of MSZ. However, the tsunami hazard probability increases with time and reaches its peak in the mid-term (250 years).

El-Hussain et al. (2021) performed a PTHA for Dibba-Oman and Dibba-Al-Emirates using the logic tree approach to estimate the POE of 0.25, 0.5, 0.75, and 1 m wave height in 100- and 500-year exposure times. The 100-year PTHA results attribute a low-to-moderate tsunami hazard to the Dibba coast, which increases with the average return period (500 years). In 100 years, the exposure time at the POE of 0.05 m is high (90%–100%), significantly decreasing to 40%–80% for the threshold of 0.25 m, to 10%–40% for 0.5 m, and to 0%–10% for 1 m. The 500-year PTHA revealed a POE of 100% along the entire coast of Dibba for a 0.05 m wave height. This probability ranges from 70% to 100% and from 30% to 80% for maximum wave height thresholds of 0.25 m and 0.5 m, respectively, and from 0% to 10% for a threshold of 1 m. Salah et al. (2021) estimated the PTH posed to the coasts of Iran and Pakistan by the MSZ, accounting for sources of epistemic uncertainties and employing event tree and ensemble modelling. Aleatory variability was also considered via the use of the probability density function. Funwave-TVD was employed to propagate small to large magnitude scenarios. The results demonstrated the large spread of hazard curves for the different coasts. The POE 3 m reaches 13.5, 25, 52, 74, and 91 for return periods of 50, 100, 250, 500, and 1000 years, respectively, along the coast. The POE could be higher in the western part of Makran for an extended return period, if considered as active as the eastern part of the MSZ. Gopinathan et al. (2020) and Gopinathan et al. (2021) quantified PTH for Karachi port of possible future tsunamis originating from the MSZ using statistical emulation with 1 million predictions and numerical modelling via the 3D subduction geometry Slab2, fault segmentation, first sediment enhancements of seabed deformation (up to 60% locally), and bespoke unstructured meshing algorithm. The results showed maximum velocities and wave heights of up to 16 ms^-1 and 8 m, respectively, for the range M_w 7.5–8.8. Near the mouth of the harbour, the reduction in hazard is ∼ 61% for maximum velocity, but only ∼ 38% for maximum wave height. POE around the port was 18%, 10%, and 4% for 3, 6, and 9 knots, respectively, and 10%, 1%, and 0.1% for 3.1, 7.5, and 10.3 ms^-1, respectively. Rashidi et al. (2022) evaluated the PTH in the Sea of Oman by interpreting splay faults using reflection seismic data in the Western Makran region. The deaggregation analysis indicated an unusually large contribution from normal faults to the local tsunami hazard. The POE 1 and 3 m in 250 years reached 1 and 0.8 in the Sea of Oman Basin. Using geodetic and structural constraints, Qiu et al. (2022) studied great earthquake and tsunami potential in the Eastern MSZ, and their impacts on Gwadar Port, Pakistan. They showed that the accumulated elastic strain on the megathrust could generate an M_w 8.1–8.4 earthquake, assuming a steady current coupling rate over a 170-yr cumulative time period. They revealed that the imbricate thrusts of the outer wedge are more efficient at exciting tsunamis than the sub-horizontal megathrust, as they increase the wave height by at least 1 m (50%) when included. These findings emphasize the importance of incorporating outer wedge thrusts in tsunami hazard models, as they may significantly amplify wave heights and inundation levels. Rastgoftar et al. (2023) conducted a sensitivity analysis of MSZ’s seismic parameters for optimizing the number of potential tsunami scenarios by analysing the variation effect of previous studies’ values on tsunami waves through numerical modelling. The study suggested using a minimum magnitude interval of M_w 0.1 for earthquake magnitude in tsunami scenarios. 2–3 values in the range of 2°–20° for dip angles, and 10–30 km for depths are sufficient, or simplified to 10°–15° and 10 km, respectively. A constant rake angle of 90° is acceptable. Zafarani et al. (2023) performed PTHA for Western Makran Coasts, Southeast Iran, including all possible uncertainties and earth subsidence effects of M_w 7.7–9.3 using the logic tree approach, deriving tsunami hazard maps for two return periods of 475 and 2,475 years for two confidence levels, the mean and the 84th percentile. According to the PTHA results, Chabahar and Sirik towns were identified as comprising the highest and lowest tsunami risks, respectively. The results are illustrated in hazard maps. A comparative table was compiled to consolidate all the data from Haider et al. (2023), which employed a multi-proxy approach to assess MSZ tsunami hazard in Pakistan, including a PTHA. The results implied that the MSZ can potentially trigger ≥ M_w 9 tsunamigenic earthquake with a recurrence interval between 500 and 1,000 years, which may generate a tsunami up to ≥15 m.

Probabilistic tsunami hazard levels in the MSZ are strongly dependent on assumptions regarding maximum earthquake magnitude and recurrence behavior. Larger maximum magnitude scenarios substantially increase the probability of exceeding damaging tsunami wave heights over long exposure periods. The spread of hazard estimates across studies reflects epistemic uncertainty in source segmentation, slip distribution, and recurrence intervals. These probabilistic relationships are summarized in Figure 3. Probability-of-exceedance curves for tsunami wave heights derived from probabilistic hazard scenarios with different assumed maximum earthquake magnitudes (M_w 8.1–9.0). The shaded region represents epistemic uncertainty associated with source characterization and modelling assumptions. Larger maximum magnitude scenarios produce substantially higher long-term tsunami hazard levels.

FIGURE 3

Rehman and Zhang (2023) analysed the maximum annual earthquake magnitude in the MSZ using extreme value theory by implementing the block maxima method, with seismic data ranging from 1934 to 2022. The estimated return levels for different return periods, 10, 20, 50, and 100 years, were 6.35, 6.81, 7.58, and 8.31, respectively, indicating that the maximum magnitude of an earthquake is increasing over the next 100 years. Besides, the M_w 8.1 Makran earthquake of 1945 revealed an occurrence of once every 100 years. Next year, Rehman and Zhang (2024a) conducted a seismicity analysis using a return period ranging from 1934 to 2022, with M_w and depth ranging from 4 to 8.1 and 0–115 km, respectively. The b-values for Eastern and Western Makran were estimated using the maximum likelihood technique, yielding 0.7 ± 0.04 and 0.764 ± 0.04, respectively. The earthquake return periods for magnitudes 5 and 5.5 varied from 1 – 2.7 and 2–8 years, respectively. For magnitudes 6 and 6.5, the return periods ranged from 5–30 and 10–60 years, respectively. The earthquake return periods for magnitudes 7 and 7.5 varied from 20–120 years and from 50–300 years, respectively. The return periods for magnitudes 8 and 8.5 ranged from 100–600 years and from 200–1,200 years, respectively. Same year, Rehman and Zhang (2024b) studied probabilistic forecasting of the next earthquake event in the MSZ using the Weibull distribution and seismic data from 1934 to 2017 with M_w ≥ 6. Statistically, the mean interval for the MSZ seismic data was 4.5 years. The calculated probability for the Weibull distribution reached 0.92 after 10 years since the last strong earthquake in 2021, indicating that the Weibull distribution within and around the studied area in 2031 will be 92%. Momeni and Goda (2024) conducted a PTHA for the MSZ using stochastic tsunami simulations of 7.7–9.1 M_w earthquake scenarios, with a total of 15,000 simulated source models, considering single- or two-segment rupture scenarios. The M_w 8.5–8.7 stochastic sources of Western MSZ generated tsunami heights varying between 1 and 10 m with a mean of ∼4.5 m in the affected areas. Furthermore, the estimated 475, 975, and 2475-year tsunami heights resulted in significant variability. The 2475-year tsunami height in Chabahar is in the range of 3–7.4 m at 10 m water depth. Further detailed results are available in the study. More recently, El-Hussain et al. (2025) performed PTHA to estimate wave height probabilities over various exposure times for Wudam As-Sahil, Northern Oman. The study involved a range of 6.5–8.8 M_w earthquake scenarios for the Eastern MSZ and a range of 6.5–7.2 M_w earthquake scenarios for the Western MSZ, for exposure times of 100, 250, 500, and 1,000 years. The findings indicate a relatively low probability (<40%) of tsunami waves exceeding 1 m in height over a 100-year return period, but an extremely high chance (40%–100%) that waves of this height or lower will occur at some point during that same period. A PTHA summary is reported in Table 1. Figure 4 shows a comparative plot of maximum tsunami wave heights reported in published probabilistic tsunami hazard assessments for the MSZ. Results demonstrate substantial variability among studies reflecting differences in seismic source assumptions, modelling approaches, and return period selections.

FIGURE 4

2.1.3 Deterministic Tsunami hazard assessment (DTHA)

Deterministic tsunami numerical modelling is a mathematical description of the tsunami life cycle, including generation, propagation, and run-up (Synolakis, 2003). The generation phase includes the calculation of the vertical seafloor deformation due to a submarine earthquake. Then, the seafloor deformation field is translated directly to the water surface and is used as an initial condition for the propagation and run-up phases (Heidarzadeh et al., 2008a). The present study focuses exclusively on tsunamis generated by seismic sources; all datasets, simulations, and analyses are based on earthquake-generated tsunamis within the MSZ. Non-seismic sources were not considered in the scope of this work. It is widely assumed that Near-field tsunamis are those whose propagation distance is less than 1000 km, and Far-field tsunamis, also called transoceanic tsunamis, are those that propagate distances more than 1000 km. Considering these values as relative guidelines, we classified the study areas relative to the 1945 MSZ ruptured segment and to each other in a manner that seems most appropriate for our analysis, given the specific context of our review. Thus, Pakistan and Iran will be considered as Near-field tsunami areas, while India, the Gulf countries, and African countries will be studied as Far-field tsunami areas. The following chapter discusses all the gathered DTHA studies and all the modelled scenarios, including the Realistic (1945 scenario) and Hypothetical Tsunami scenarios in the MSZ, particularly. It is also noteworthy to emphasize to readers that in the deterministic studies discussed below, not all first-arriving waves with the shortest tsunami travel time (TTT) are the strongest (with the largest wave heights and highest run-ups). Not all the largest waves (with the highest wave heights and highest run-ups) arrive on shore first (shortest TTT). Thus, in each study, we report the maximum travel times, maximum wave heights, and/or run-ups independently. Hence, for each reference, we state the TTT of the first wave, and the wave height and/or run-up of the largest wave. A compilation of various deterministic models used for hazard assessment along the Arabian Coastlines is provided by Haider et al. (2023) and updated by Gardezi et al. (2024), comprising fault parameters and the software and codes. Figure 5 shows the relationship between earthquake magnitude and simulated tsunami run-up heights for deterministic MSZ scenarios. Larger magnitudes produce nonlinear increases in run-up, illustrating the sensitivity of coastal impact to source scaling. Compiled deterministic tsunami simulations show a nonlinear increase in maximum coastal run-up with earthquake magnitude. The regression curve represents empirical scaling derived from published MSZ scenarios, and the shaded band indicates epistemic uncertainty associated with rupture geometry, bathymetry, and coastal amplification effects. Larger megathrust events (M_w ≥ 8.5) produce disproportionately higher near-field run-up along the central Makran coast.

FIGURE 5

2.1.3.1 Near-field DTHA

2.1.3.1.1 DTHA in Pakistan

To the best of our knowledge, Mahar and Nayyar (2006) were the first to review the mechanism of tsunami generation and propagation along the coastal zone of Makran and Karachi. The created maps showed that any tsunamigenic MSZ thrusting will direct tsunamis northward to the Makran coast and Southward to the Indian Ocean. The tsunami will take a few minutes to arrive on the Makran coast, with a more significant impact on Makran compared to Karachi, due to the distinct geographic nature of both cities. Heidarzadeh et al. (2006) study is the first to employ a hypothetical scenario-based deterministic approach for the MSZ. Empirical relations presented by Wells and Coppersmith (1994) and a numerical model based on the finite difference technique with a leap-frog scheme were used to simulate 13 earthquakes with magnitudes ranging from 6.5 to 8.5 M_w. Earthquake scenarios with a magnitude greater than 7.5 generated a maximum seafloor uplift of 0.5–3.7 m, indicating a high possibility for tsunami generation. According to the published maps, Pakistan would be hit by the highest tsunami waves of more than 2 m, arriving at the coast within the first 10 min (self-read values). Hafeez (2007) conducted a DTH study along the Pakistani coast, considering three scenarios. The M_w 7.5 tsunamigenic earthquake scenario generated a 0.15 m wave height hitting Ormara after 25 min, a 0.1 m wave height, with a 24 min travel time at Gawadar, and a 0.16 m wave height, with a TTT of 30 min in Pasni. The M_w 8 scenario caused a tsunami with a maximum wave height of 1.8 m, a 24 min TTT in Ormara, a maximum wave height of 0.25 m, a 28 min TTT in Gawadar, and a 1.7 m wave height, with a 32 min TTT in Pasni. No tsunami reached the Karachi coast in the first two scenarios. The worst-case scenario of M_w 8.5 generated a maximum tsunami wave height of 5 m, with a maximum travel time of 22.7 min in Ormara, a maximum tsunami wave height of 3.5 m, with a 21.5 min TTT in Gawadar, and a maximum tsunami wave height of 4.3 m, with a 30 min TTT in Pasni. In this case, Karachi was affected, experiencing a maximum wave height of 0.75 m with a TTT of 33 min. Later, Rajendran et al. (2008), studied hazard implications of the late arrival of the 1945 Makran tsunami using the finite difference code of TUNAMI-N2 to predict wave propagation based on the available rupture parameters and GEBCO bathymetry data. The 1945-like scenario simulation produced a tsunami arriving in 5 min at Pasni and Makran, causing a maximum wave height of 12–15 m, and at Karachi in 106 min, with a maximum wave height of 1.35 m. In the deterministic study by Heidarzadeh et al. (2008b), which utilized bathymetry data from the GEBCO digital atlas (IOC et al., 2003), six scenarios were simulated. The M_w 8.3 Eastern MSZ scenario would produce a tsunami reaching a height of 7.5 m along the Southern coasts of Pakistan, and 1–4.4 m along the Eastern coast of Makran. It would reach the nearest coast (e.g., Jiwani and Pasni) within ∼ 15 min, then Karachi in ∼ 75 min. The same year, Heidarzadeh et al. (2008a) employed the algorithm of Mansinha and Smylie (1971) to calculate seafloor deformation for tsunami generation modelling, and TUNAMI-N2 to simulate the propagation and coastal amplification of long waves. According to the 1945-like scenario simulation, the generated tsunami caused a maximum run-up height of 5 m in Pasni. In the scenario-based study by Heidarzadeh et al. (2009b), five M_w 8.1 tsunamigenic earthquakes spaced evenly along the MSZ (from the Westernmost to the Easternmost) were simulated using GEBCO data and TUNAMI-N3 model, relying on the following fault parameters for all scenarios: 7° dip, 89° and 5.3–6.6 m slip, 245° strike, 27 m depth, and 1.7–2 m uplift. The results indicated that by moving a 1945-type earthquake along the MSZ, the southern coasts of Pakistan will experience among the largest waves, with heights ranging from 5 to 7 m, depending on the location of the source. The largest tsunami wave arrives ∼ 20 min after the earthquake on the nearest coast. Runup modelling performed in Pasni revealed that the maximum inundation distance of the 1945 Makran tsunami on dry land was ∼ 1 km. Yanagisawa et al. (2009) performed DTHA along the coast of Pakistan by modelling the 1945 Makran tsunami (Byrne et al., 1992), to examine its hydrodynamic features. The modelling generated tsunami wave heights of 5–10 m at Ormara and Gwadar city. The authors observed the late arrival of the highest waves and inferred that the tsunami waves were trapped and reflected on the continental shelf with a gentle slope. Rafi and Mahmood (2010) performed numerical modelling of a tsunami for Gwadar for an M_w 8.5 scenario, with a 5.26 m rupture slip. The results showed a TTT of 22 min, with a maximum run-up of 3.7 m, a maximum flow depth of 5 m, and a maximum inundation of up to 1.46 km on the Gwadar coast, suggesting that any future MSZ earthquake with M_w 8.5 can generate a destructive tsunami for the region. The DTHA by Neetu et al. (2011), simulating a 1945-like tsunami (Byrne et al., 1992) along the Pakistani coast, resulted in a 2.5 m maximum wave height in Pasni, and ∼ 1.5 m in Ormara. In Karachi, the first wave arrived in 1 h 34 min, with a wave height of 28 cm. While the highest wave occurred in 2 h 48 m, with 44 cm. Waves of high amplitude persisted for more than 7 h after the arrival of the first wave due to trapped wave energy. Mahmood et al. (2012) ran a deterministic study on the Makran coast by modelling a range of earthquake source scenarios, using MOST (Method of Splitting Tsunami), based on SRTM land topography and GEBCO bathymetry data. The worst-case scenario M_w 9 generated a tsunami with a TTT of 12 min at Gwadar, 17 min at Ormara, and 21 min at Pasni, with maximum run-ups of 7.5 m, 6 m, and 5.4 m, respectively, causing a full inundation of the narrow land strips of Gwadar and Ormara, hammer shaped peninsulas, and a 1.2 km inundation on some locations at Pasni. The 8.5 M_w scenario caused a tsunami with a 20 min TTT to Gwadar and Ormara, and 31 min to Pasni, with maximum run-ups of 4.2 m, 3.9 m, and 3.7 m, respectively. Again, Gwadar and Ormara harbour areas were completely inundated, in addition to parts of Pasni. Maximum current velocities were in the range of 7–11 m/s and 4–6 m/s in the case scenarios of M_w 9 and 8.5, respectively. The M_w 8.1 scenario produced a tsunami arriving at Gwadar and Ormara in 21 min, and at Pasni in 35 min, with maximum run-ups of 1.7, 1.2, and 1 m, respectively, causing a slight inundation. Whereas the M_w 7.7 scenario created a tsunami that arrived at Gwadar and Ormara in 25 min and at Pasni in 40 min, with maximum run-ups of 0.5, 0.4, and 0.1 m, respectively, where none of the areas were inundated. TTTs of the largest wave heights were also reported. The M_w 9 and 8.5 tsunami scenarios had the most destructive effects on the studied region, causing severe inundation. Swapna and Srivastava (2014) studied the effect of Murray Ridge (MR) on tsunami propagation from MSZ on the Pakistani coast, through three scenarios. The 1945-like scenario generated a tsunami arriving in Karachi with a runup ranging from 0.5 to 2.4 m with MR and 0.5–2.2 m without MR and maximum wave heights of 0.44 m with MR and 0.43 m without MR, causing a maximum inundation of around 1262 m with MR and 1295 m without MR. The M_w 9 East MSZ scenario was focused on Karachi and resulted in a tsunami with a maximum wave height of 2.6 m with MR and 2.2 m without MR. While the M_w 9 West MSZ scenario generated a tsunami with a maximum wave height of 1.28 m in Karachi with MR, and 1.29 m without MR. They concluded that the presence of the Murray ridge alters the directivity, arrival times, and amplitudes of tsunami waves towards the South of the MSZ for tsunamis generated in the eastern MSZ, but not in the Western MSZ. Miranda et al. (2014) employed Green’s summation for tsunami waveform estimation under three scenarios in the MSZ. The M_w 8.6 full MSZ scenario generated a tsunami with a maximum wave amplitude reaching ∼4 m on the Pakistani coast. The M_w 7.7 West MSZ caused a tsunami with a <0.2 m wave amplitude. While the M_w 7.8 East MSZ’s triggered tsunami reached the coast with a <0.3 m wave amplitude. Oskamp et al. (2015) quantified the tsunami hazard in the Western Arabian Sea and within the Arabian Gulf (AG) due to seismic activity in the MSZ, assuming a full-length rupture, using a hydrodynamic model developed in Delft3D-FLOW. The resulting earthquake could have had an M_w of 9. The Hypothetical M_w 9 full MSZ scenario simulation resulted in large tsunami wave amplitudes of up to 6 m in some areas along the shorelines of the Western Arabian Sea, including Pakistan.

Rehman et al. (2015) and Sultan and Ahmed (2017) estimated the MSZ tsunami hazard along the coast of Gwadar using the MOST model in the ComMIT software for 7 scenarios of magnitudes varying from 7 to 8.5 M_w, including the 1945-like earthquake of M_w 8.1. The M_w 7 earthquake scenario generated a tsunami that arrived in 28 min, with a nil runup. The M_w 7.5 earthquake scenario caused a tsunami with a 27 min TTT, causing a 3.35 m runup, inundating 91 m of Gwadar coast. The M_w 7.7 earthquake scenario tsunami arrived in 25 min, with a 6.1 m runup, inundating up to 160 m. The M_w 8 earthquake scenario tsunami arrived in 23 min, with a 7.01 m runup and a 205 m inundation. The M_w 8.3 scenario triggered a tsunami that arrived in 22 min, with a 7.62 m runup and 651 m of inundation. The M_w 8.5 scenario resulted in a tsunami with some of the highest values, characterized by the shortest arrival time of 20 min, the highest runup of 9.14 m, and causing 850 m of inundation. Nevertheless, the 1945-like scenario, with an M_w 8.1 earthquake triggering a tsunami with an arrival time of 28 min and a runup of 8.1 m, caused the highest inundation value of 994 m at Gwadar. The authors suggested that any event greater than M_w 8 can easily destroy Gwadar. In the study by Patel et al. (2016), the 1945 Makran tsunamigenic earthquake is modelled using rupture parameters suggested by Byrne et al. (1992), NAMIDANCE computer code, and GEBCO and SRTM data. The simulation was conducted over a duration of 360 min. The results revealed a maximum run-up of about 1.2–5.8 m along the Southern coast of Pakistan. The simulation generated a tsunami that first arrived at Pasni in 0 min, with a maximum wave amplitude of 1.25 m, which occurred 7.1 min later. The first wave arrived at Ormara in 60.6 min, with a maximum wave amplitude of 1.02 m, arriving in 67.3 min. Along the Karachi coast, the arrival time for the first wave was from 97.2 to 120.7 min, with maximum wave amplitudes of 1.55 and 0.88 m arriving in 252.5 and 135.3 min, respectively. Hasan et al. (2018) presented a DEM for simulating the 1945 Makran tsunami in Karachi Harbour, as a tool for calibrating tsunami models. The DEM bathymetry was derived from soundings collected primarily during the first 8 years following the tsunami. In the deterministic study by El-Hussain et al. (2018), the M_w 8.8 Eastern MSZ scenario, with a rupture length of 461 km, radiated most of the tsunami energy to the coast of Pakistan and the Southeast Indian Ocean. The dislocation along the fault plane, exceeding 10 m, generated maximum wave heights that can reach 8 m along the Pakistani coast. While in the 1945-like scenario simulation, most tsunami energy was steered similarly, the maximum wave amplitude was only about 2 m. Sarker (2019) performed numerical modelling of the 1945-like tsunami using a tidal hydrodynamic model, specifically the MIKE21 Flow Model FM from DHI. Five scenarios were employed. In Karachi, the M_w 8.4 with the 1945 fault EMSZ scenario generated a tsunami with a 1 h 5 min TTT and a 0.5 m wave height. The M_w 8.4 WMSZ scenario resulted in a TTT of 1 h 20 min and 0.2 m wave height. The M_w 8.4 middle fault caused a tsunami with 1 h 15 min TTTs and 0.23 m wave amplitude. In contrast, the M_w 8 WMSZ scenario simulated a TTT of 1 h 35 min, with a 0.1 m wave height. The M_w 7.8 WMSZ simulation resulted in a wave height of 0.06 m, with a 1 h 35 min TTT. In Pasni, the M_w 8.4 with the 1945 fault EMSZ scenario generated a tsunami that arrived in 35 min, causing a 4.3 m wave height. The M_w 8.4 WMSZ scenario resulted in a TTT of 33 min and 4.2 m wave height. The M_w 8.4 middle fault caused a tsunami with a 33-min TTT and a 4.4-m wave amplitude, representing the highest simulated values. While the M_w 8 WMSZ scenario simulated a TTT of 41 min, with 0.44 m wave height. On the other hand, the M_w 7.8 WMSZ simulation witnessed a wave height of 0.31 m, with a 43 min TTT. According to the author, a relatively higher rise in sea surface elevation was found in the shallower water depths due to shoaling effects. Rashidi et al. (2018b) performed near- and far-field DTHA in Western Makran using scenarios based on the world’s largest subduction zone earthquakes. Four scenarios were employed. In Pakistan, the 2006 Kuril Islands M_w 8.3 scenario produced a maximum uplift of 1.5 m and generated a tsunami with a 2 m coastal amplitude. The 2011 Tohoku-Oki M_w 9 scenario generated a maximum uplift of 15.5 m, causing a tsunami with an amplitude of 5 m. The 2011 Tohoku-Oki M_w 9.1 scenario caused a maximum uplift of 20 m. The generated tsunami wave amplitude was 9 m. The 2015 Chile M_w 8.3 scenario produced a 3 m maximum uplift and a 2 m tsunami amplitude. The 2011 Tohoku-type event, with an M_w 9.1 magnitude, would cause significant near- and far-field tsunami hazard in the Western Makran rupture area, representing the worst-case scenario.

Honarmand et al. (2019) and Honarmand et al. (2020) studied the effects of the 1945 tsunami on the Makran Coasts using the Okada algorithm and the CFD-based software Flow 3D for global and regional numerical simulations. Coarse meshes of 1,400 m–500 m size in the Indian Ocean. Finer meshes of 25 m and a very fine 2D mesh of 0.4 m were applied. The 1945-like tsunami 3D simulation generated a 4.25 m maximum wave run-up in Ormara, with a TTT of 16.67 min, a 3.95 m maximum wave run-up in Pasni, with a TTT of 18.33 min, a 1.78 m maximum wave run-up in Gwadar, with a 20 min TTT, and a 1.55 m maximum wave run-up in Jiwani, with a 25 min TTT. This is, to our knowledge, the first 3D DTHA study in MSZ. Rashidi et al. (2020) simulated all synthetic tsunami scenarios numerically using COMCOT and GEBCO data. The modelling generated a maximum peak run-up of about 8 m along the shores of Pakistan, in Ormara, and of ∼ 6 m in Pasni. According to Moradi (2021), an ideal data management system for a tsunami warning system should have three essential parts included: data converter, GIS, and Relational Database Management System (RDBMS). In his study, 3D, spatial, temporal, and statistical analyses of tsunami models’ data were exported to the proposed system, utilizing GIS capabilities and data processing routines. The ETOPO2 bathymetry data were employed for the Makran region. 3D modelling of the 1945-like tsunami showed that Pakistani coasts (and Indian coasts) will experience the highest wave heights, which will reach the coast in less than 10 min. The model showed that the Strait of Hormuz and Persian Gulf were not in the tsunami domain, due to the gentle slope at the neck of the Strait of Hormuz, which acts like a barrier against the propagation of tsunamis. Giles et al. (2021) employed an advanced tsunami simulation tool, Volna-OP2, using unstructured meshes accelerated on GPUs for real-time tsunami warning systems. One hundred generic scenarios, independent of the 1945-like ones, were simulated, affecting Karachi, Chahbarah, Iran, and Muscat, Oman. Qiu et al. (2022) DTHA study revealed that an M_w 8.1–8.4 earthquake scenario could generate a tsunami with ≥2 m wave height in Gwadar port. The worst-case of the M_w 9 megathrust model would result in >5 m waves, strong currents reaching 6 m/s, and >1 km inundation distance when rupturing to the trench. However, if the updip area of the 1945 event source region ruptured, it could amplify wave height by 0.2–1 m in the Gwadar port and generate a strong tsunami current (>2 m/s). Qiu and Barbot (2022) performed DTHA and studied the structural control of tsunami excitation by coseismic seafloor uplift using seismic reflection profiles and tsunami earthquake rupture models. The width of the outer wedge in the West segment offshore Iran is slightly larger than that of the Eastern segment offshore Pakistan; however, the latter exhibits significant variation along strike. Their model predicted a maximum run-up between 12 and 40 m for a hypothetical M_w 8 earthquake in Eastern Makran. For a hypothetical M_w 9 trench-breaking earthquake, the model implies a maximum run-up between 28 and 80 m.

More recently, Ali et al. (2023) and Ali Khan (2023) developed a tsunami source model and studied the Eastern MSZ segment hazard in Balochistan, using a new TSM method. The simulation of the 1945 tsunami with an M_w 8.2 earthquake scenario generated a tsunami arriving at Gwadar in 21 min, causing a wave amplitude of 0.7 m, to Ormara in 30 min, causing a wave amplitude of 4.8 m, and to Pasni in 37 min with a 3.4 m wave amplitude, with the first wave being the highest for the three regions. In Jiwani, the first wave arrived in 41 min, while the highest arrived in 81 min with an amplitude of 0.8 m. In Kund Malir, the first wave arrived in 49 min, the highest in 176 min, with a 3.2 m amplitude. On the Eastern coast of Pakistan, the arrival time of simulated waves was 37 min to Mubarak, followed by the highest wave in 61 min, causing a 1.5 m wave amplitude. In Sonmiani, the first arrived in 58 min, causing a 1.6 m wave runup. At Keti Bunder, the first wave arrived in 111 min, causing a 1.4 m wave runup. In Sir Creek, the first wave had a TTT of 184 min, causing a wave runup of 0.3 m, with the first wave being the highest for the three regions. The authors calculated the maximum credible earthquake for the Eastern MSZ. With a dislocation of 11 m, the FPs of the proposed New-TSM produce a seismic moment that results in an M_w 8.6 earthquake. This scenario generated tsunami waves that first arrived at the Western coast of Pakistan in less than 20 min (self-read values), the TTT on the Western coast ranged from around 15–50 min, causing a maximum wave amplitude of 7.71 m at Kund Malir, 6.61 m in Ormara, 4.85 m in Pasni, 1.43 m in Gwadar, and 0.99 m in Jiwani. On the eastern coast, the TTT ranged from slightly less than 60 min–180 min, causing maximum wave amplitudes of 4.82 m in Keti Bunder, 3.52 m in Sonmiani, 1.87 m in Mubarak, and 0.93 m in Sir Creek, with the first wave being the highest along the coast. The M_w 9.1 scenario generated a tsunami along the West coast with maximum wave amplitudes of 4.90 m in Ormara, 4.06 m in Gwadar, 3.26 m in Jiwani, 2.93 m at Pasni, and 2.73 m in Kund Malir. On the eastern coast, the scenario caused a tsunami with maximum wave amplitudes of 5.08 m in Keti Bunder, the highest value, followed by 3.1 m in Sonmiani, 2.21 m in Mubarak, and 0.95 m in Sir Creek. The authors indicated the insignificance of the M_w 9.1 earthquake scenario. Cheng et al. (2024) performed a DTHA following an M_w 9.2 whole-fault trench-rupturing earthquake scenario, generating a tsunami affecting coastal cities in the northern Arabian Sea region, including Pakistan, which experienced maximum wave heights reaching 2–4 m, with 2.37 m in Pasni, 2.57 m in Karachi, 2.68 m in Ormara, and 4.25 m in Gwadar (Cheng, 2022). Hasan et al. (2024) assessed tsunami hazard from seven hypothetical ruptures of the MSZ based on the 1945 tsunami, each varying in length and width. Scenario 800 × 355, rupturing the full-length MSZ fault, denoted the worst-case scenario, generating a tsunami with wave amplitudes of 7.76, 5.88, 4.58, and 3.77 m in Gwadar, Ormara, Pasni, and Karachi, respectively, and arriving in 32 min, 30 min, 35 min, and 1 h 26 min, respectively. Rashidi et al. (2025) conducted a DTHA by modelling an M_w 8.5 western Makran scenario. The stimulation would generate tsunami waves arriving at Gwadar in less than 30 min and at Ormara in 45 min, with maximum wave heights of 0.5 and ∼0.45 m, respectively. The DTHA by El-Hussain et al. (2025) following an M_w 8.8 East MSZ scenario resulted in a tsunami with a maximum wave height of 6 m on the coast of Pakistan. Table 2 summarizes all the outcomes of the deterministic hazard analyses in Pakistan.

The compiled deterministic tsunami simulations for the Pakistani coastline reveal substantial variability in predicted coastal impact metrics, reflecting differences in rupture geometry, magnitude scaling, bathymetric representation, and numerical modelling approaches. Nevertheless, several consistent patterns emerge. Maximum tsunami run-up generally increases nonlinearly with earthquake magnitude, while near-field locations experience the highest run-up despite short tsunami travel times. Coastal amplification also varies spatially, with Gwadar and Ormara repeatedly identified as the most exposed sites. These relationships are summarized in Figure 6, which synthesizes magnitude–run-up scaling, travel-time dependence, site-based hazard variability, and the overall envelope of deterministic scenario outcomes for the MSZ.

FIGURE 6

2.1.3.1.2 DTHA in Iran

Heidarzadeh et al. (2006) simulated 13 MSZ earthquakes with magnitudes ranging from 6.5 to 8.5 M_w; the MSZ M_w 8.1 scenario produced a tsunami wave that reached the Iranian coastlines ∼ 20 min later. Tsunami wave height in some parts of the Iranian Southern coastlines reached about 70 cm. The year after, Heidarzadeh et al. (2007) considered four source scenarios to reproduce 2 m uplift and 1.5 m subsidence for the case of an M_w 8.1 earthquake in the MSZ. These parameters were imposed on the dislocation model to calibrate the source parameters. Empirical relations presented by Wells and Coppersmith (1994) were employed, considering an M_w 8.1 earthquake with 234 km rupture length, 38 km width, 6.15 m displacement, 270° strike angle, 4°–8° dip angle, 90°–100° slip angle, and 20–25 km depth. In the M_w 8 scenario, propagation modelling produced a tsunami hitting the nearest coastline within 15 min, with a wave height of ∼ 4 m on coastlines located perpendicular to the fault strike. While in other locations, the predicted wave heights were less than 1 m. The year after, Heidarzadeh et al. (2008b) performed a simulation model of the M_w 8.3 East MSZ scenario, which produced a tsunami wave height of about 9.6 m along the southern coast of Iran, with a TTT of 35 min to Chabahar and 75 min to Jask. The following year (Heidarzadeh et al., 2009a), simulated two large tsunamis using TUNAMI-N2 model. The algorithm of Mansinha and Smylie (1971) was used to calculate the sea floor deformation. Both scenarios’ parameters were of 25 km depth, 7° dip, 90° slip, 265°–280° strike. The East MSZ M_w 8.6 scenario, with a rupture length of 500 km, produced a maximum seafloor uplift of about 4.5 m, causing a tsunami wave height of about 6–9 m along the coast, and an average runup of 12–18 m. Simultaneously, the full MSZ M_w 9 scenario caused wave amplitudes of 12–15 m, an average runup of 24–30 m, and horizontal penetration of about 1–5 km in various coasts. Furthermore, a hypothetical splay fault was modelled, revealing that it can locally increase the maximum wave height by a factor of two (×2). The same year, in the scenario-based study by Heidarzadeh et al. (2009b), five M_w 8.1 tsunamigenic earthquakes spaced evenly along the MSZ (from the Westernmost to the Easternmost) were simulated. The results indicated that the southern coasts of Iran would experience the largest waves, with heights ranging from 5 to 7 m, depending on the location of the source. The largest tsunami wave arrives ∼ 20 min after the earthquake on the nearest coast.

Jannat et al. (2011) performed numerical modelling using different source scenarios along the MSZ via ComMIT software. The first peak of the tsunami wave occurred after 65 min with a height of less than 60 cm. Although the source position of the earthquake is far from Chabahar Bay, the wave height recorded near Chabahar port was noticeably higher than the maximum wave height obtained from other sources. More than 10 m wave height was received at some locations near the coasts around Chabahar Bay. According to the 1945 Makran earthquake and using a non-point earthquake source (24.5°N, 63.0°E, length 200 km, width 100 km, strike 270), it took 15 min for the first tsunami wave to reach the Iranian coasts. Miranda et al. (2014) employed Green’s summation for tsunami waveform estimation under three scenarios in the MSZ. The M_w 8.6 full MSZ scenario generated a tsunami with a maximum wave amplitude reaching ∼3 m on the Iranian coast. While the M_w 7.7 West MSZ caused a tsunami with a <0.3 m wave amplitude. The M_w 7.8 East MSZ triggered tsunami was insignificant in the region. Layeghi and Faraji (2015) performed numerical modelling of a tsunami with an M_w 9 earthquake scenario generated at the MSZ, using MOST, ComMIT, and GEOWAVE methods. The results showed a maximum wave amplitude of 4.83 m at the Kacho coast. According to Soltanpour (2015), the small width of the Strait of Hormuz limits the ability for tsunami waves to enter the Persian Gulf from the Sea of Oman. Moreover, suppose any tsunami is generated within the Persian Gulf. In that case, the shallow water depth effectively limits the heights of the tsunami waves propagating to coastal areas due to the small shoaling effect and significant dissipation caused by bed friction. It can thus be concluded that the risk of tsunamis in the Persian Gulf is minimal. The hypothetical full MSZ M_w 9 tsunami simulation by Oskamp et al. (2015) resulted in large tsunami wave amplitudes of up to ∼ 6 m in some areas along the shorelines of the Western Arabian Sea, including those of Iran. Payande et al. (2015) performed numerical modelling using MIKE 21 FM numerical software to assess tsunami hazard on Chabahar Bay, Southeast of Iran. An unstructured triangular mesh with a higher level of refinement was employed. The M_w 7.5 scenario generated a tsunami with a 4.5 m maximum wave height in the Eastern headland of the Chabahar omega-shaped bay, and a 4.4 m maximum wave height in the inner part of the bay. The M_w 8.1 scenario caused a tsunami with an 8 m maximum wave height in the bay’s Eastern headland, and 5.5 m maximum wave height in its inner part. In contrast, the M_w 9.1 scenario produced a tsunami with 18 m maximum wave height in the bay’s Eastern headland, and 8.4 m maximum wave height in its inner part. The waves reached the bay first in 10 min, which faced inundation in 15 min; however, the interior coasts had a TTT of 35 min. According to the study, the Eastern headland was associated with no inundation or low inundation on cliffy shores, while Kenarak coasts with sandy beaches were the most vulnerable to tsunamis in all three scenarios, facing extensive inundation due to their low height above sea level. They pointed out that the W shape of the bay reduces the energy of tsunami waves, and the highest waves happen on the exterior coasts of the bay. In the studies by Jannat et al. (2015) and Rastgoftar et al. (2016), the worst-case possible earthquake scenarios of the MSZ are simulated using a fully nonlinear Boussinesq model and the GEOWAVE numerical model. The global and local numerical simulations were conducted based on 1-min and 3-arc-second resolution bathymetry data, respectively. The M_w 9.1 full MSZ scenario resulted in ∼ 8 m uplift and 6 m subsidence of the ocean surface, producing a tsunami wave height of ∼ 14 m at Jask port. The M_w 8.7 Eastern MSZ (half) scenario resulted in a tsunami wave height of ∼ 10 m. Both scenarios, M_w 9.1 and M_w 8.7 Eastern MSZ, tsunamis had a 20 min travel time, causing total inundation of the Jask port, capturing farther inland areas. However, the M_w 8.7 Western MSZ (half) scenario triggered a tsunami wave height of less than 0.4 m, with no run-up and no inundation at the Jask port. According to the 1945 Makran tsunamigenic earthquake modelling by Patel et al. (2016), using rupture parameters suggested by Byrne et al. (1992), the maximum generated tsunami run-ups were about 0.5–2.3 m along the Southern coast of Iran, arriving at Chabahar in 32.6 min, with a maximum 1.33 m runup arriving in 38.2 min. In Jask, the tsunami first arrived in 71.3 min, with a maximum wave amplitude arriving in 75.2 min, causing a 0.54 m runup.

Banijamali et al. (2017) studied rubble-mound breakwaters’ stability against MSZ tsunamis. For this purpose, a total of 18 scenarios, with magnitudes varying from 7.5–9 M_w for all three sub-zones, Eastern, central, and Western, were simulated, using the ComMIT software based on the MOST numerical model of 2D Nonlinear Shallow Water (NSW) equations, which employs the finite-differences method of Titov and Gonzalez (1997). The SRTM and NASA topographic data, as well as GEBCO bathymetry data, were used. Upon simulation, scenarios generated tsunamis arriving at Jask shores in less than 30 min after the earthquake occurrence, reaching 15.16 m maximum wave height at Zar-Abad breakwater, 6.78 m at Karati breakwater, 2.71 m at Pasa-Bandar breakwater, 2.11 m at Beheshti breakwater, 1.92 m at Jask breakwater, and 1.35 m at Konarak breakwater. The authors referred to the relatively lower simulated wave heights in other breakwaters compared to Zar-Abad and Karati ones as being somewhat sheltered behind a headland, receiving diffracted tsunami waves. Akbarpour Jannat et al. (2017) simulated the tsunami effect on Chabahar Bay facilities using a numerical code that solves the nonlinear Boussinesq wave equations, as well as the GEOWAVE model. Tsunami features were transferred from the models of Grilli and Watts (1999) and Grilli et al. (2002) into analytical approximations of tsunami sources by TOPICS. ETOPO1 bathymetry and topography are used. Simulated scenarios included the following: M_w 7.5, M_w 8 West MSZ, M_w 8.3 West MSZ, M_w 8.7 West MSZ, M_w 8.7 East MSZ, and M_w 9.1 full MSZ. The M_w 9.1 full MSZ scenario induced about +8.43 m uplift and −5.86 m subsidence on the water surface elevation immediately, causing high waves reaching the East headland (near Chahbahar city) in 19 min with a leading wave elevation of 13 m, reaching the Western outer of the West headland (near Pozm Tiyab) in 29 min, with maximum wave height of 8 m, reaching the West headland (near Konarak) in 32 min, with maximum wave height of 9 m, and reaching the innermost of the bay (near Naserabad) in 34 min, causing a maximum wave height of 14 m. The highest maximum wave height reached 22 m at Chabahar Port in 31 min. The M_w 8.7 Western MSZ generated a tsunami with the highest maximum wave height of 8 m. The waves arrived near Chahbahar city in 20 min, causing a maximum wave height of 5 m, near Pozm Tiyab in 31 min, causing a maximum wave height of 4 m, near Konarak in 35 min, causing a maximum wave height of 1.5 m, and near Naserabad in 46 min, causing a maximum wave height of 2 m. The effect of the tide was modelled and found to be small, with a range of +1.7 m. Delavar et al. (2017) also simulated the impact of a tsunami on Chabahar port using the ComMIT model based on MOST. The modelling of the 1945 tsunami resulted in seafloor uplift and subsidence that reached a maximum of ∼ 1.84 m, and a maximum run-up of 3 m at Chabahar port, which, they suggest, agrees with eyewitness reports from the 1945 event. The simulated results showed that tsunami waves would reach the Chabahar coastline 11 min after generation. 9 min later, over 9.4 km² of the dry land would be flooded with a maximum wave amplitude reaching up to 30 m. According to Latcharote et al. (2018) study, which employed the numerical simulation using 4 worst-case scenarios, the results were as follows: an M_w 8.3 earthquake with a 200–220 km rupture length resulted in a maximum tsunami amplitude of 8.7–8.9 m in Makran. An M_w 8.6 earthquake with a 500 km rupture length resulted in a maximum tsunami amplitude of 16.5 m, while an M_w 9 full MSZ earthquake scenario resulted in 27.5 m amplitude. In the near- and far-field DTHA in Western Makran by Rashidi et al. (2018b), four scenarios were employed. In Iran, the 2006 Kuril Islands M_w 8.3 scenario generated a tsunami with a 4 m coastal amplitude. The 2011 Tohoku-Oki M_w 9 scenario generated a tsunami with an amplitude of 41 m. The 2011 Tohoku-Oki M_w 9.1 worst-case scenario generated tsunami waves that impressively affected the Persian Gulf, the Red Sea, and Eastern India, with Southeastern Iran being exposed to the highest risk, with 52 m wave amplitude. The 2015 Chile M_w 8.3 scenario produced a 5 m tsunami amplitude.

Recently, Honarmand et al. (2019) and Honarmand et al. (2020) studied the 3D simulation of the 1945 tsunami on Iranian coasts. According to the simulation, the first wave would arrive at Beris in 30 min, causing 0.75 m maximum wave run-up, to Chahbahar in 35 min causing 0.4 m maximum wave run-up, to Gurdim in 36.67 min causing 0.14 m maximum wave run-up, to Bir in 37.5 min causing 0.08 m maximum wave run-up, to Kalak in 38.33 min causing 0.06 m maximum wave run-up, to Kereti in 39.17 min causing 0.04 m maximum wave run-up, and to Jask in 40 min causing 0.01 m maximum wave run-up. Rashidi et al. (2018a) simulated the propagation and inundation of tsunami waves along the Southeastern coastline of Iran for an M_w 8.7 earthquake scenario in the Western Makran. The maximum tsunami amplitude reached 11 and 6 m inside the Sea of Oman and the Arabian Sea, respectively. The results of the maximum run-up for the western, middle, and eastern Iranian coast areas were 10, 17, and 19 m, with maximum inundation distances of 6, 6, and 4 km, respectively. This indicates that the Eastern area is the most hazardous. The considerable values of inundation distance were attributed to the low elevation topography of the affected coasts. Akbarpour Jannat (2021) evaluated the DTH of worst-case Makran seismic scenarios in Chabahar Bay, using numerical modelling, including GEOWAVE. The M_w 9.1 West MSZ scenario resulted in tsunami wave heights of 13 m at the Shahid Beheshti and Kalantary ports, which arrived 19 min after the earthquake. In contrast, the Konarak port experienced a tsunami wave height of 9 m, ∼ 32 min after the earthquake. The M_w 8.3 West MSZ scenario resulted in maximum tsunami wave heights of ∼ 6.5 m at the port entrances, with a maximum TTT of 26 min for the first wave. According to Moradi (2021) 3D modelling of the 1945-like tsunami showed a maximum wave height of less than 2 m on the Iranian coast, with a maximum arrival time of about 20 min. More recently, Cheng et al. (2024) performed a DTHA following an M_w 9.2 whole-fault trench-rupturing earthquake scenario, generating a tsunami affecting coastal cities in the Northern Arabian Sea region, including Iran, which experienced maximum wave heights reaching 4.99 m in Chahbahar (Cheng, 2022). Hasan et al. (2024) assessed tsunami hazard from seven hypothetical ruptures of the MSZ based on the 1945 tsunami, each varying in length and width. The scenario 800 × 355, involving the rupture of the full-length MSZ fault, represents the worst-case scenario, generating tsunamis with wave amplitudes of 8.47 and 4.91 m in Chahbahar and Jask, respectively, which arrive in 27 min and 32 min, respectively. Rashidi et al. (2025) conducted a DTHA for Jask Port by modelling an M_w 8.5 Western Makran scenario. The stimulation would generate tsunami waves that arrived at Jask in 10 min; however, it took 30 min for the waves to impact the entire Jask coastline, with a peak wave height of less than 2 m. In Gwadar, the maximum wave height was approximately >1.5 m. The DTHA by El-Hussain et al. (2025) Following an M_w 8.8 East MSZ scenario, a tsunami was generated with a maximum wave height of 6 m on the coast of Iran. Table 3 summarizes the deterministic hazard assessment in Iran.

2.1.3.2 Far-field DTHA (teletsunami)

2.1.3.2.1 DTHA in India

Dominey-Howes et al. (2007) simulated the tsunami generated by the 1945 Makran earthquake (M_w 8.1) using the fault parameters of Byrne et al. (1992), in comparison with historical records. The simulated tsunami had a low impact on the West coast of India near the Gulf of Cambay and Mumbai, with maximum wave heights of fewer than 25 cm, which did not corroborate the 2-m tsunami wave height observed after the 1945 Makran earthquake in Mumbai, causing significant damage and fatalities. The authors attributed the discrepancy between the computed and observed tsunami heights to either a larger possible earthquake magnitude or the triggering of a submarine landslide. The numerical modelling of the 1945-like event by Rajendran et al. (2008) resulted in a tsunami with a maximum TTT of 204 min at Goa, 215 min at Karwar, and 242 min at Mumbai, causing a maximum wave height of 2 m, and a maximum TTT of 259 min at Kerala. In the numerical study by Heidarzadeh et al. (2008a), simulating the 1945-like scenario, the results showed maximum run-up heights of 1.5 m in Raan of Kutch, and 0.7 m in the Gulf of Kutch and Mumbai. Jaiswal et al. (2009) also performed a numerical simulation for the 1945 tsunami using the TUNAMI-N2 model, with a duration of 300 min, utilizing 3 arc s or 90 m Shuttle Radar Topographic Mission (SRTM) data. The authors assumed a slip of ∼ 15 m, resulting in a seafloor deformation of 6–7 m. The tsunami wave initially propagated very fast in the Arabian Sea, then slowed as it reached the shallow region of the Gujarat Coast in less than an hour, the Dwarka Coast in 2 h and 10 min, and the Gulf of Kutch in 3 h and 10 min. The tsunami struck Kutch with a runup height of around 3–4 m, the Jakhau coast with more than 2.5 m, the Dwarka region with 2 m, and the Porbandar coast with an amplitude of 1.5 m. A map of potential inundations resulting from various wave heights was generated. The DTHA by Neetu et al. (2011), simulating a 1945-like tsunami (Byrne et al., 1992), resulted in a 34 cm wave height in Mumbai arriving in 3 h 7 min, with the first wave being the highest. Amplitudes of subsequent waves were less than one-third of the first wave. Arjun et al. (2011) used the TUNAMI-N2 model to numerically simulate the 1945-like tsunami propagation, run-up, and inundation on the Southwest coast of India. They selected locations in the Lakshadweep islands in the Arabian Sea. It took 145 min for the waves to reach the Indian coast, Kutch in Gujarat, precisely. Neendakara-Thottapally on the Kerala Coast showed the highest maximum run-up and maximum inundation values, being 2.5 and 500 m, respectively. A hypothetical case of shift in the source by 3° East did not significantly affect the nature of propagation and focusing pattern of the tsunami except for a minor enhancement in the run-up along the Kerala coast. Patel et al. (2010) attempted a numerical simulation of a tsunami from the MSZ, and its effect on the city of Porbandar in Gujarat. Eighty-six earthquake events based on the 1945-like scenario were simulated using TUNAMI-N2. The simulated scenarios resulted in tsunamis with a maximum wave height of up to 3.08 m, with a TTT of 2 h and 42 min. Travel time correlated positively with epicentre distance and negatively with width, length, dip angle, and water depth. In contrast, run-up height correlated negatively with epicentre distance, and positively with width, length, dip angle, and water depth. Patel et al. (2011) investigated the propagation of the 1945 tsunami into the Arabian Sea and its impact on Okha, using a numerical model implemented within the MIRONE framework over a simulation period of ∼ 4 h. The simulation for the Western Makran region showed a tsunami reaching Okha in 117.81 min, with a maximum wave height of 2.496 m. In the Central MSZ simulation, the generated tsunami arrived in 109.69 min with a peak wave height of 3.222 m. While the Eastern Makran simulation predicted a TTT of 105.63 min, accompanied by a maximum wave height of 2.213 m. Srivastava et al. (2011) performed a DTHA of an M_w 9 earthquake scenario in the Eastern MSZ along the West coast of India, using the TUNAMI-N2 model. The simulation generated a tsunami arriving at Dwarka in 106 min, Ratnagiri in 172 min, Mumbai in 180 min, Panaji (Goa) in 181 min, Mangalore in 196 min, Calicut in 204 min, Udipi in 209 min, Bhatkal in 213 min, Cochin in 234 min, Thiruvanthapuram in 241 min, and Thalessary in 250 min, with maximum wave heights observed at Dwarka and Udipi (<0.6 m). The authors attributed the 8-min late arrival of tsunami waves in Mumbai than Ratnagiri (despite the 244 km distance), to the 250 km wide shelf.

Kurian and Praveen (2010), Praveen (2012), and Praveen et al. (2013) ran a detailed numerical modelling of tsunami propagation and inundation along the Kerala coast, for each coastal city, for the 1945-like scenario and a hypothetical Sumatra-like earthquake in MSZ using TUNAMI-N2. The 1945-like scenario simulation generated a tsunami with wave heights that varied significantly between 0.5 and 2 m for most areas, resulting in negligible inundation, with a maximum wave height of up to 3 m in Kannur, causing a maximum inundation of ∼ 402 m. In contrast, the district of Ernakulam experienced a maximum inundation of over 1 km after a wave height of up to 2.5 m. The tsunami caused maximum wave heights and inundations of 1.5 m and 216 m in Thiruvananthapuram, 2 and 107 m in Kollam, and 2.5 m each in Alappuzha, Thrissur, Malappuram, Kozhikode, and Kasargod, with corresponding inundations of 600, 412, 396, 200, and 445 m, respectively. The hypothetical scenario modelling generated a tsunami with a maximum wave height of 3.5 m in Kannur, causing 669 m of inundation, and with the most considerable maximum inundation distance of 2,400 m after a 3 m maximum wave height in Ernakulam. The tsunami caused maximum wave heights and inundations of 3 m in Alappuzha and Kasargod, with 1,450 and 445 m, respectively, 2 and 243 m in Thiruvananthapuram, 2.5 m in Kollam, Thrissur, Malappuram, and Kozhikode, with 664, 898, 552, and 654 m, respectively (Praveen, 2012). Praveen et al. (2015) further compared these same scenarios with and without sea level rise, concluding that its contribution to the manifold increase in inundation in some stretches marked by relatively low backshore elevation. Patel et al. (2013) developed a deterministic model to assess the tsunami hazard of the MSZ along the Gujarat coast. The simulated model was trained on 76 test data and tested on 10 data sets. A run-up map was created using an ANN structure. An inundation map was created using the SRTM dataset and Surfer 8 software to plot elevation data. At Dwarka, the Western MSZ fault was the worst-case with the highest impact, followed by the complete rupture MSZ scenario, and then the Eastern MSZ scenario, with a TTT of 140–180 min. Swapna and Srivastava (2014) studied the effect of Murray ridge on tsunami propagation from MSZ on the Indian coast, through three scenarios. The 1945-like scenario generated a tsunami arriving on the Mumbai coast with wave heights ranging from 0.2 to 0.45 m, causing a maximum inundation of 389 m, with the presence of the MR. Without MR, the same scenario resulted in 0.2–0.4 m wave heights and a maximum inundation of 330 m on the same coast, with a relatively delayed arrival time. In Achu, the values of maximum wave heights were 0.56 m with MR and 0.5 m without MR. The M_w 9 East MSZ scenario caused a tsunami with maximum wave heights of 3.4 m with MR, and 2.6 m without MR in Achu. In contrast, the M_w 9 West MSZ scenario generated a tsunami with maximum wave heights of around 1 m with MR and 0.8 m without MR in Achu. The estimated run-up along the Mumbai coast ranged from 0.4 to 1.38 m with MR and from 0.4 to 1.28 m without MR, resulting in a maximum inundation of 875 m with MR and 842 m without MR. The authors depicted the effect of MR on tsunamis generated from Eastern MSZ, but not the Western MSZ. Patel et al. (2015) performed the 1945-like tsunami modelling using the TUNAMI-N2 model and SRTM and Bathymetric data. At t = 0, the simulation generated a 6–7 m tsunami at the moment of the earthquake, and then the water receded. Tsunami waves arrived within ∼2 h 10 min at Dwarka, and 3 h 10 min at the Gulf of Kutch, with a wave height of up to 2 m in the Gulf of Kutch. The analysis of the inundation area showed that an area of 7983.341 km² can be affected by tsunami waves up to 2 m in height. According to the 1945 Makran tsunamigenic earthquake modelling by Patel et al. (2016), using rupture parameters suggested by Byrne et al. (1992), maximum calculated tsunami run-ups were of 0.7–1.35 m along the Western coast of India, with 0.7 m and a TTT of about 146 min in Dwarka, 1.13 m at 159 min in Porbandar, 0.56 m at 187 min in Okha, 1.21 m at 206 min in Kutch, 1.01 m at 222 min in Goa, 240 min in the Gulf of Kutch, and 0.96 at 300 min in Mumbai. Roshan et al. (2016) conducted a tsunami hazard assessment of the West Indian coast and Gujarat, utilizing numerical modelling of the worst-case scenario, M_w 8.5. The simulated tsunami scenario showed wave heights under 2 m along the West coast, possibly due to the relative orientation of the Makran source; only refracted waves reached the coast. Maximum wave heights occurred along Gujarat’s West coast, closest to the source. Simultaneously, the Gulf of Khambhat and Northern Maharashtra were less vulnerable, possibly due to a wider continental shelf that dissipated wave energy, besides the shadowing effect from Gujarat. The East coast of India is shielded by the Indian peninsula landmass and the relative MSZ orientation, posing negligible tsunami hazard from this source.

Saha and Srivastava (2016) applied mathematical simulation of the impact of three tsunami scenarios on the Androth Island of Lakshadweep. The 1945-like scenario simulation uplifted the sea floor up to 3 m near the epicentre and produced run-up heights in the range of 0.8–1 m on the island, with a maximum travel time of 187.4 min. Both M_w 9 MSZ scenarios resulted in an initial sea floor displacement at the source of ∼ 4 m. The M_w 9 Western MSZ scenario induced run-up heights up to 1.2 m, with a maximum TTT of 186.5 min. At the same time, the M_w 9 Eastern MSZ scenario resulted in run-up heights of up to 3 m, with a maximum TTT of 169.6 min. A scenario was calibrated by adjusting the manning coefficient from 0.025 to 0.01, resulting in changes in run-ups of up to 4 m at several locations. Selvan and Kankara (2016) performed a tsunami model simulation for several scenarios to study their effect on the Koodankulam region of the Tamil Nadu coast. Among them was the Makran 1945-like scenario, which caused a tsunami with a maximum wave height of 2.20 m and an inundation of 90 m. Zuhair and Alam (2017) studied the effect of an MSZ-induced tsunami M_w 9 on nuclear power plants along the Western coast of India, using the TUNAMI-N2 code, designed for shallow water wave equations. The simulated tsunami struck the coast of Jaitapur Nuclear Power Plant (Maharashtra) after 210 min, with a run-up of 2.32 m, arrived at Tarapur Nuclear Power Plant (Maharashtra) in 215 min with a 2.12 m run-up height, at Kaiga Nuclear Power Plant (Karnataka) in 225 min with a 2.32 m run-up, and at Mithi-Virdi Nuclear Power Plant (Gujarat) in 230 min, with 0.93 m run-up. In the near- and far-field DTHA in Western Makran by Rashidi et al. (2018b), four scenarios were employed. In India, the 2006 Kuril Islands M_w 8.3 scenario generated a tsunami with a 1 m coastal amplitude. The 2011 Tohoku-Oki M_w 9 scenario resulted in a tsunami with an amplitude of 4 m. The 2011 Tohoku-Oki M_w 9.1 worst-case scenario generated tsunami waves with an amplitude of 8 m. The 2015 Chile M_w 8.3 scenario produced a 1 m tsunami amplitude. In the deterministic study by Sowmya et al. (2018), a series of earthquake source scenarios with magnitudes of M_w 8.0, M_w 8.5, and a mega thrust of M_w 9.1 were modelled using ComMIT based on the NOAA MOST model along the Karnataka West coast of India. The M_w 8 and M_w 8.5 scenarios caused tsunami wave heights of 6–12 cm and 21–46 cm, respectively. In contrast, the worst-case M_w 9.1 scenario generated a tsunami wave that struck the coast within 4–5 h of earthquake occurrence, causing a 95–158 cm wave height. All coastal locations were barely inundated, with maximum water levels in the range of 100–200 cm. At Maravanthe, Murudeshwar, and Om Beaches, the maximum wave heights were the second and third waves. More details are illustrated in (Table 4). The study by Mupparthi et al. (2019) presented the estimation of tsunami arrival times computed using GIS methods at different locations along the Western Coast of India and compared them with the arrival times calculated using the TUNAMI-N2 model. The obtained results were in good agreement with an R² value of ∼0.8.

Saha and Srivastava (2019) studied the simulated effect of two MSZ tsunamis along the Southwest Coast of India with and without the protection of the Lakshadweep Islands acting as a wave-barricade. In the 1945-like scenario simulation, the initial deformation of the sea floor at t = 0 s was around 3.2 m. While in the M_w 9 Eastern MSZ scenario simulation, the initial deformation of the sea floor at t = 0 s was around 4 m. With the presence of the Lakshadweep Islands, the tsunami waves were amplified in the vicinity, which increased the arrival time of the tsunami waves on the Southwestern Indian coast. In the absence of the Lakshadweep Islands, the TTT and wave amplitudes become less significant. However, due to this large continental shelf, the inundation was of a significantly lesser extent. They concluded that Lakshadweep acts as a wave barricade for the Southwest coast of India. In the DTHA study by Sarker (2019) on the Gujarat coast, five scenarios were simulated. The M_w 8.4 with the 1945 fault EMSZ scenario generated a tsunami with a maximum TTT of 2 h 15 min, causing a 0.31 m maximum wave height. The M_w 8.4 WMSZ scenario resulted in a TTT of 2 h 20 min and 0.23 m wave height. The M_w 8.4 middle fault caused a tsunami with a 2 h 15 min TTT and a 0.22 m wave amplitude. In contrast, the M_w 8 WMSZ and the M_w 7.8 WMSZ scenarios simulated maximum TTTs of 2 h 30 min each, with wave heights of 0.14 and 0.08 m, respectively. The M_w 8.4 1945 fault EMSZ caused the highest values, with the same TTT as the M_w 8.4 middle fault scenario. Matin and Praveen (2021) conducted a DTHA for the Gujarat Coast using the TUNAMI-N2 model in two scenarios. The M_w 8 1945-like MSZ fault scenario generated a tsunami with a maximum run-up of 2.5 m in Gojines and Madhavpur, and 1.5 m in Lamba, Miyani, Tukada Miyani, Ratdi, Javar, Porbandar, Tukada, and Utada, causing maximum inundation of 900 m in Porbandar, 400–500 m in Tukada, Utada, and Tukada Miyani, 100–200 m in Madhavpur and Lamba and nil in other areas. The M_w 9.3 MSZ (Sumatra-like) scenario resulted in a tsunami with a maximum run-up of 3.5 m in Ratdi, Javar, and Madhavpur, and 2.5 m in Gojines, Lamba, Miyani, Tukada Miyani, Porbandar, Tukada, and Utada, causing maximum inundation of 1,800 m at Porbandar, 700 m in Tukada, 400–550 m in Utada and Tukada Miyani, >300 m in Gojines and Lamba, >100 m in Madhavpur and Miyani, and nil in other areas. Various inundation models were used, with the Cartosat data described above showing the most significant inundation. Dani et al. (2023) conducted a DTHA to assess the possible impacts along the Western coasts of India using the TUNAMI-N2 code, by modelling six 1945-like tsunami scenarios. The simulation generated tsunamis reaching all the locations along the Gulf of Kutch (Gujarat) in nearly 2 h–5.30 h with amplitudes of 1–2.5 m, Mumbai in around 4.45 h with amplitude of 2 m, Goa in around 3.08 h with amplitude 1 m, Karwar (Karnataka) in around 3.12 h, and Mangalore in around 3.36 h with amplitudes of 1 m each. More details are reported in Table 4. More recently, Cheng et al. (2024) performed a DTHA following an M_w 9.2 whole-fault trench-rupturing earthquake scenario, generating a tsunami affecting cities on the West coast of India, experiencing maximum wave heights reaching about 1–1.5 m, with 0.82 m in Surat, 1.14 m in Kozhikode, 1.23 m in Mangalore, 1.36 m in Kochi, and 1.44 m in Mumbai (Cheng, 2022). Hasan et al. (2024) assessed tsunami hazard from seven hypothetical ruptures of the MSZ based on the 1945 tsunami, each varying in length and width. The scenario 800 × 355, involving the rupture of the full-length MSZ fault, represents the worst-case scenario, generating tsunamis with wave amplitudes of 1.94 and 1.55 m in Mandvi and Mumbai, respectively, which arrive in 3 h 11 min and 4 h 50 min, respectively. Table 4 summarizes the deterministic studies for Indian coasts.

2.1.3.2.2 DTHA in Oman

Heidarzadeh et al. (2006) simulated 13 MSZ earthquakes with magnitudes ranging from 6.5 to 8.5 M_w. The results showed that the Omani coast was hit after 30 min with a wave height of ∼ 0.5 m (self-read values). Okal and Synolakis (2008) evaluated far-field tsunami hazard in the Indian Ocean for ten megathrust earthquake scenarios, including two worst-case scenarios of the eastern and the entire MSZ. The first worst-case scenario considered the simultaneous rupture of the 1851–1864, 1945, and 1765 fault zones. The second scenario added another 450 km of rupture to include the probable 1483 fault zone. The study showed that two fields of maximum amplitude were not significantly different, which expressed the trapping, inside the Sea of Oman, of the wave generated by the additional fault segment in the second scenario. The 1945-like scenario simulation by Rajendran et al. (2008) on Oman generated a tsunami wave with a travel time of 45 min to Muscat. According to Heidarzadeh et al. (2008b), the M_w 8.3 East MSZ scenario would produce a tsunami reaching a height of 3–7 m along the Northern coast of Oman and 1–5 m along its Southern coast. The TTT was about 45 min for the Omani coast. In Heidarzadeh et al. (2009b)’s deterministic study, where they simulated five M_w 8.1 tsunamigenic earthquakes across the Western to Eastern MSZ. The findings showed that tsunamis could reach ∼ 5 m in height along the northern coast of Oman, particularly in scenarios focused on the Western region. Swapna and Srivastava (2014) investigated the impact of tsunami propagation from the MSZ through the Murray Ridge system on the Omani coast, considering three scenarios. The 1945-like scenario generated a tsunami with maximum wave heights of 0.5 m in Muscat and 0.52 m in Al Khuwaymah with MR, and 0.4 m in Muscat and 0.7 m in Al Khuwaymay without MR. The M_w 9 East MSZ scenario caused a tsunami with maximum wave heights of 0.7 m in Muscat and 1.2 m in Al Khuwaymah with MR, and 0.8 m in Muscat and 1.4 m in Al Khuwaymay without MR. The M_w 9 West MSZ scenario produced a tsunami with wave energy more concentrated towards Oman, causing maximum wave heights of 6.6 m in Muscat and around 3 m in Al Khuwaymah with MR, and 6.5 m in Muscat and 3 m in Al Khuwaymay without MR. Miranda et al. (2014) employed Green’s summation for tsunami waveform estimation under three scenarios in the MSZ. The M_w 8.6 full MSZ scenario generated a tsunami with a maximum wave amplitude reaching approximately >1 m on the Omani coast. While the M_w 7.7 West MSZ caused a tsunami with a <0.5 m wave amplitude. The M_w 7.8 East MSZ-triggered tsunami was insignificant in the region. Oskamp et al. (2015) used the hypothetical M_w 9 full MSZ tsunami simulation, and the results showed large tsunami wave amplitudes in some regions of Oman, reaching up to 6 m, while in other regions, the wave amplitudes varied between 1 and 3 m. In the Strait of Hormuz, the tsunami waves were generally between 0.5 and 1.5 m. The study indicated significant tsunami hazard on the shores of the Arabian Sea, but minimal tsunami energy enters the AG through the Strait of Hormuz. According to the 1945 Makran tsunamigenic earthquake modelling by Patel et al. (2016), using rupture parameters suggested by Byrne et al. (1992), the maximum calculated tsunami run-ups were about 0.4–1.16 m along the coast of Oman. The waves first arrived at Sur, within 38 min, causing a maximum wave amplitude of 1.16 m, 42.6 min after the earthquake. The waves then arrived at Muscat in 38.9 min, causing a wave amplitude of 0.53 m after 42.4 min. In Masirah, the first wave arrived at 61.33 min, with an amplitude of 0.28 m, and arrived in 63.9 min. Sohar had a TTT of 78.33 min, with a wave amplitude of 0.46 m after 82 min. Duqum had a TTT of 117.5 min with an amplitude of 0.56 m, arriving at 130.1 min. Using Google Earth and open-source GIS along with seismic databases, Browning and Thomas (2016) introduced a new THA method. The M_w > 8 earthquake scenario occurring East MSZ (24°N, 61.34°E) caused by a shallow focus (27 km) thrust fault mechanism would generate a tsunami arriving at the Omani continental shelf (415 km from source) in ∼38 min, where it slowed dramatically and took a further 10 min to impact the Muscat coast (48 min), producing maximum wave heights of 3.4 m. The tsunami was amplified by a 1.5 factor within Mutrah bay, reaching 5.1 m amplitude in the corniche, causing maximum inland inundation extending for ∼91 m (considering maximum tidal levels of 2.8 m). In the Sultan Qaboos Port area, maximum run up of 7.8 m and maximum inundation of 201 m (considering maximum tidal levels of 2.8 m) were observed, with the lowest values measured at the outermost walls, with unamplified waves. Salalah had a low tsunami inundation risk, except in low-lying beach areas. Suppasri et al. (2016) studied tsunamis generated by submarine earthquake scenarios with 8.3–9 M_w along the MSZ inside the AG, using the TUNAMI model. The M_w 8.3 scenarios had a low impact at locations inside the AG. M_w 8.6 scenario had a considerable impact primarily at the Gulf entrance. According to the study, only the tsunami generated by the M_w 9 earthquake could yield a significant impact on the whole AG region with a maximum tsunami height of around 2–3 m at the mouth of the AG, decreasing to less than 1 m at the innermost part of the AG.

El-Hussain et al. (2017) performed a tsunami hazard assessment along Dibba Oman coast following two worst-case scenarios for tsunamis. The M_w 8.8 Eastern MSZ would cause a maximum run-up of 1.16 m, a maximum inundation distance of 447 m, and a maximum flow depth of 1.37 m. Whereas, the M_w 8.2 Western MSZ scenario would cause a maximum run-up of 2.57 m, a maximum inundation distance larger than 420 m, and a maximum flow depth of about 2.34 m. They suggested thus a potentially higher hazard from the Western than from the Eastern Makran subduction for even a lower magnitude due to its close proximity to Dibba coasts. Next year, El-Hussain et al. (2018), studied two worst-case scenarios. The simulation of the M_w 8.8 Eastern MSZ scenario with a rupture length of 461 km produced wave heights in the range of 0.5–2.5 m on the Omani coast, with a maximum value reaching 2.5 m on the Sur coast, and a travel time of ∼25 min, inundating some low-lying coastal areas, with flow depths varying from few centimetres to about 1 m. The simulation of the 1945-like scenario showed a lesser tsunami hazard. The first wave reached the Omani coast in less than 1 h (∼50 min), with maximum wave heights in Sur of less than 0.5 m. The high-resolution simulations demonstrated the shoaling effect in shallow water areas, leading to increased wave amplitudes reaching 1.4 m at some locations. Aniel-Quiroga et al. (2018) developed a scenario database for tsunami hazard assessment for Oman by conducting a seismo-tectonic analysis to identify seismic areas capable of generating tsunamis. A database of 3,181 tsunamigenic sources was established. Scenarios with magnitudes ranging from 6.5 to 9.25, especially focused on MSZ, were numerically propagated. Seven worst-case scenarios were selected and simulated at national and local scales across nine municipalities in Oman. The aggregated maps showed a higher hazard in the northern part of the country than in the eastern part, where the inundation water depth remained low, being almost negligible in Salalah and Duqm. In the North, the maximum inundation depth in most coastal areas, including Wudam, Suwadi and Muscat, would reach 5–10 m. Sarker (2019) performed the 1945-like tsunami numerical modelling in the MSZ on the Omani coast, using a tidal hydrodynamic model, the MIKE21 Flow Model FM of DHI. Five scenarios were employed. The M_w 8.4 with the 1945 fault EMSZ scenario triggered a tsunami with a 2 h 19 min TTT with 0.31 m wave height in Duqum, 1 h 16 min with 0.26 m in Masirah, and 55 min with 0.2 m in Muscat. The M_w 8.4 WMSZ scenario resulted in a TTT of 2 h 11 min with 0.35 m wave height in Duqum, 1 h 8 min with 0.6 m in Masirah, and 41 min with 0.38 m in Muscat. The M_w 8.4 middle fault initiated a tsunami with 2 h 14 min TTTs with 0.35 m wave amplitude in Duqum, 1 h 12 min with 0.46 m in Masirah, and 48 min with 0.35 m in Muscat. While the M_w 8 WMSZ scenario simulated a TTT of 2 h 14 min with a 0.16 m wave height in Duqum, 1 h 10 min with a 0.36 m wave height in Masirah, and 34 min with a 0.27 m wave height in Muscat. On the other hand, the M_w 7.8 WMSZ simulation yielded wave heights of 0.09 m with a 2-h 15-min TTT in Duqum, 0.22 m with a 1-h 11-min TTT in Masirah, and 0.19 m with a 38-min TTT in Muscat. The M_w 8.4 WMSZ scenario had the most significant impact with the highest wave amplitudes in the three cities, and the shortest TTT in Duqum and Masirah. In the near- and far-field DTHA in Western Makran by Rashidi et al. (2018b), four scenarios were employed. In Oman, the 2006 Kuril Islands M_w 8.3 scenario triggered a tsunami with a 4 m coastal amplitude. The 2011 Tohoku-Oki M_w 9 scenario generated a tsunami with an amplitude of 23 m. The 2011 Tohoku-Oki M_w 9.1 worst-case scenario generated tsunami waves with an amplitude of 38 m. The 2015 Chile M_w 8.3 scenario produced 5 m tsunami amplitude. El-Hussain et al. (2019) evaluated the tsunami hazard of the Masirah Island by scenario simulation, using a validated shallow water numerical model over a high-resolution DEM. The Probable Maximum Tsunami (PMT) was established upon available scientific information. The M_w 6.9 WMSZ scenario generated a tsunami wave with an estimated height of about 0.6 m, a run-up of 0.2 m, resulting in an inundation of 80 m. While the M_w 8.8 EMSZ scenario produced a 2 m wave height and a 2.2 m run-up, it generated 300 m of inundation. The EMSZ dominated the tsunami hazard due to the location of the tsunamigenic source.

According to Honarmand et al. (2019) and Honarmand et al. (2020), the 1945-like tsunami 3D simulation generated a 0.055 m maximum wave run-up in Sur, with a TTT of 30 min, a 0.047 m maximum wave run-up in Muscat, with a TTT of 32.5 min, and a 0.033 m maximum wave run-up in Sohar, with a 35.83 min TTT. In the deterministic study by Rashidi et al. (2020), which simulated all synthetic scenarios, the main affected Omani coast was the area between Muscat and Sur, encountering the largest wave run-up heights. These heights attenuate to the South of the Oman coastline, especially around Masirah Island. The maximum peak-run-up was about 12 m for the Oman shoreline, 9 m in Sur, and 8 m in Muscat. While the mean run-up changes between 0 and 6 m along the Oman coast, with 5 m in both Muscat and Sur.

Recently, El-Hussain et al. (2021) employed a deterministic approach to specific MSZ scenarios, focusing on sea level variations along the Dibba coast. The M_w 8.8 scenario from Eastern MSZ generated a tsunami with a TTT of 84 min, with runups of 1.20 and 2.80 m during mean sea level (MSL) and mean higher high water (MHHW), respectively, and causing maximum inundation distances of 220 and 305 m and maximum flow depths of 1.50 and 1.90 m during MSL and MHHW, respectively. On the other hand, following the occurrence of M_w 7.2 in the West MSZ scenario, the generated tsunami would arrive in about 45 min, with runups of 1.25 and 2.3 m during MSL and MHHW, respectively, causing 128 and 305 m inundation distances, and 1.6 and 1.8 m flow depths during MSL and MHHW, respectively. For both scenarios, the inundated areas were comparable, as flood limits almost coincided, with a lower impact on the Dibba coast from the M_w 7.2 scenario. The numerical simulation of the M_w 8.1 historic earthquake in Eastern MSZ initiated a tsunami arriving in 108 min, with a 0.2 m runup height, causing a maximum inundation distance of 70 m, and a maximum flow depth of 0.4 m, suggesting an insignificant impact on Dibba coasts (El-Hussain et al., 2021). Similarly, the sea level parameter was considered by Al-Habsi et al. (2022), who performed THA for Quriyat on the northeast Oman coast, using numerical modelling of worst-case credible tsunamigenic scenarios. A validated nonlinear shallow water numerical code with nested grids was employed. The M_w 7.2 western MSZ scenario produced a tsunami arriving in 18 min, with a 3.2 m wave height, leading to 2.8 m maximum run-up, 2.2 m maximum flow depth, and 233 m maximum inundation during MSL, and with higher values of run-up (3.4 m) and inundation (900 m) during MHHW, which was 0.9 m above MSL. Whereas the M_w 8.8 Eastern MSZ scenario caused tsunami waves arriving in 24 min, reaching 3.8 m wave height, leading to a maximum runup height of 3.1 m, maximum flow depth of 2.8 m, and maximum inundation of 900 m during MSL, while during MHHW, higher wave height (4.9 m), run-up (5.2 m), flow depth (3.8 m), and inundation (1.5 km) values were noticed. The M_w 8.8 Eastern MSZ scenario was classified as MPT, posing the highest threat under high tide conditions, with the North as Sahil and the northern coast of Quriyat being the most vulnerable areas, specifically Wadi Mijlas, characterized by low-lying regions that experienced a maximum inundation distance of 1512 m. The aggregated tsunami hazard scenario indicated maximum runup heights and flow depths of ∼ 5.2 and 3.8 m, respectively. More recently, Cheng et al. (2024) performed a DTHA following an M_w 9.2 whole-fault trench-rupturing earthquake scenario, which generated a tsunami affecting coastal cities in the Northern Arabian Sea region, including Oman. Muscat experienced maximum wave heights of 4.65 m (Cheng, 2022). Hasan et al. (2024) assessed tsunami hazard from seven hypothetical ruptures of the MSZ based on the 1945 tsunami, each varying in length and width. The scenario of 800 × 355, rupturing the full-length MSZ fault, represents the worst-case scenario, generating a tsunami with a wave amplitude of 9.09 m in Muscat, which arrives in 40 min. Rashidi et al. (2025) conducted a DTHA by modelling an M_w 8.5 Western Makran scenario. The stimulation generated tsunami waves arriving first in Muscat within 15 min, with a 3 m maximum wave height. Sur would experience a slightly later arrival, with a maximum wave height of 2.5 m. EL-Hussain et al. (2025) underwent DTHA for Wudam As-Sahil, Northern Oman. The study involved three scenarios. At high resolution, the M_w 7.2 West MSZ scenario, representing the worst-case scenario, triggered a tsunami arriving in a TTT of 35 min, with a maximum wave height exceeding 3 m, a maximum flow depth of 1.7 m, and an inundation of ∼ 820 m. The M_w 8.8 East MSZ scenario generated a tsunami with a maximum wave height of up to 2 m in the study area, arriving in a TTT of 1 h 5 min and causing an inundation that extended to ∼ 670 m inland. The historical M_w 8.1 1945-like scenario resulted in a tsunami with a lesser impact, characterized by insignificant wave heights that arrived within 1 h and 30 min. Table 5 presents the deterministic tsunami hazard assessment values for Oman. Deterministic tsunami simulations indicate that coastal run-up along Oman increases strongly with earthquake magnitude, with M_w 8–8.5 events typically producing run-up of several metres and full-margin megathrust scenarios (M_w ≥ 8.8) capable of exceeding 5–9 m along parts of the northern Oman coast. Published ranges from multiple modelling studies are summarized in Figure 7.

FIGURE 7

2.1.3.2.3 DTHA in the United Arab Emirates

Heidarzadeh et al. (2008a) and Heidarzadeh and Satake (2015) performed a DTHA by simulating an M_w 8.4 event in the Western MSZ. The generated tsunami arrived at the Eastern coast of the UAE in about 90 min with a run-up of ∼ 0.5 m. In the deterministic study by Heidarzadeh et al. (2009b), where five M_w 8.1 tsunamigenic earthquakes distributed from the Western to the Eastern MSZ were simulated, the Western scenarios triggered tsunamis reaching a height of ∼ 2 m on the eastern coast. Oskamp et al. (2015) used a hypothetical M_w 9 full MSZ scenario simulation to initiate tsunami waves of ∼ 1.5–2 m on the eastern coast. As the tsunami energy lowers while entering the Strait of Hormuz, the Northern UAE coasts, namely, Ras Al-Khaimah, Sharjah, Dubai, and Abu Dhabi witnessed 0.5–0.75 m tsunami waves. According to the M_w 8.3 scenario numerical simulation by Suppasri et al. (2016), there is an insignificant tsunami impact in terms of wave height inside the AG. Whereas the M_w 8.6 full MSZ earthquake simulation produced tsunami waves of around 1 m in height along the UAE coast, the M_w 9 scenario yielded waves of up to 2–3 m in the same area. As stated in the previous section, El-Hussain et al. (2017) performed THA along Dibba-Al Emirates, for two scenarios. The numerical simulation of the M_w 8.8 Eastern MSZ scenario generated a tsunami with a maximum run-up of 1.16 m, resulting in a maximum inundation distance of 447 m and a maximum flow depth of 1.37 m. While the M_w 8.2 Western MSZ scenario simulation triggered a tsunami with a 2.57 m maximum run-up, inducing a 420 m maximum inundation distance, and a 2.34 m maximum flow depth. According to Latcharote et al. (2018) An M_w of 8.6 earthquake at the MSZ with 500 km rupture length would cause a tsunami amplitude of ∼1 m along the coasts of the UAE. In contrast, an M_w 9 full MSZ earthquake would cause tsunami amplitudes of up to 2–3 m along the northern coasts. In this scenario, tsunami waves propagated to the AG and arrived in Dubai ∼ 3 h later, and in Abu Dhabi ∼ 5 h later. In the DTHA study by Sarker (2019) on the Fujairah coast, following the simulation of the five scenarios. The M_w 8.4 with the 1945 fault EMSZ scenario generated a tsunami with a maximum TTT of 1 h 32 min, causing a maximum wave height of 0.18 m. The M_w 8.4 WMSZ scenario resulted in a TTT of 1 h 15 min and a wave height of 0.29 m, the highest value among the simulations. The M_w 8.4 middle fault initiated a tsunami with 1 h 22 min TTT and 0.23 m wave amplitude. In contrast, the M_w 8 WMSZ scenario simulated the shortest maximum TTT of 1 h 6 min, with a 0.17 m wave height. On the other hand, the M_w 7.8 WMSZ simulation witnessed the least wave height of 0.12 m, with a 1 h 11 min TTT. Recently, El-Hussain et al. (2021), simulated three MSZ scenarios for the Dibba UAE and Dibba Oman region. The M_w 8.8 EMSZ scenario results showed a TTT of 1 h 24 min, with a 1.2 m maximum run-up, 1.5 m maximum flow depth, resulting in 220 m of inundation. The M_w 7.2 WMSZ scenario generated a tsunami arriving in 45 min, with a 1.25 m maximum run-up and a 1.6 m maximum flow depth, causing 128 m of maximum inundation. The M_w 8.1 EMSZ scenario triggered a tsunami with a TTT of 1 h 48 min, causing a 0.2 m maximum run-up and 0.4 m maximum flow depth, with 70 m of maximum inundation. Cheng et al. (2024) performed a DTHA following an M_w 9.2 whole-fault trench-rupturing earthquake scenario, generating a tsunami that slightly affected the UAE coasts, with maximum wave heights reaching 0.49 m in Abu Dhabi and 0.79 m in Dubai (Cheng, 2022).

More recently, Hamidatou et al. (2024) assessed tsunami hazard on the eastern coast of the UAE from the MSZ, following three scenarios. The worst-case M_w 9.2 earthquake rupturing the full MSZ scenario generated a tsunami with an average TTT of ca. 37 min, ranging between 36 and 40 min, with a maximum run-up of ∼2.55 m, a maximum flow depth of 2.2 m affecting the cities of Kalba, Al Fujairah, and Khor Fakkan, and ∼1.3 m affecting Dibba. Maximum inundation distances of 253 m, 153 m, 137 m, and 91 m were induced in Kalba, Al Fujairah, Khor Fakkan, and Dibba, respectively. The modelling of an M_w 8.2 earthquake scenario, rupturing Western MSZ, produced a tsunami with an average TTT of 39 min, ranging from 38 to 40 min, with a maximum run-up of ∼1.7 m, a maximum flow depth of 1.64 m at Kalba and Al Fujairah, and 0.8–1.2 m in Khor Fakkan and Dibba. Maximum inundation distances of 135, 105, 108, and 37 m were caused in Kalba, Al Fujairah, Khor Fakkan, and Dibba, respectively. The M_w 8.8 earthquake scenario, rupturing Eastern MSZ, triggered a tsunami arriving at an average TTT of 49 min (48–51 min), causing a maximum run-up of 1.3 m, a maximum flow depth of 1.05 m for Kalba, Al Fujairah, and Khor Fakkan, and 0.3–0.4 m in Dibba. Maximum inundation distances of 95, 71, 66, and 19 m were caused in Kalba, Al Fujairah, Khor Fakkan, and Dibba, respectively. Table 6 summarizes the deterministic assessments in the UAE. Deterministic tsunami simulations along the eastern UAE coast indicate a strong dependence of coastal impact on MSZ earthquake magnitude. Maximum run-up increases from less than 1 m for M_w ≈ 7.5–8 scenarios to more than 2 m for M_w ≥ 9 full-margin ruptures. Consistently, inundation distances across UAE east-coast zones (Kalba, Al Fujairah, Khor Fakkan, and Dibba) increase markedly from M_w 8.2 to M_w 9.2 events, with the largest inundation occurring along the Kalba–Khor Fakkan sector (Figure 8). These results demonstrate both the magnitude-dependent escalation of tsunami hazard and the spatial variability of coastal amplification along the UAE forearc coast.

FIGURE 8

2.1.3.2.4 DTHA in Kuwait

According to the deterministic study by Suppasri et al. (2016), M_w 8.3 and M_w 8.6 scenarios had a negligible impact on the inner parts of the AG, while the M_w 9 scenario caused less than 0.5 m wave height along the coasts of Kuwait. Al-Salem and Al-Enezi (2018) evaluated tsunami hazard along the Kuwaiti coastline due to possible earthquakes of magnitudes between M_w 8.3 and M_w 9 at MSZ. Tsunami numerical simulations were performed using new topography and bathymetry data at six different resolutions: 1,215, 405, 135, 45, 15, and 5 m. Tsunamis generated by the M_w 8.3 earthquake had a minimal effect on Kuwait City (<0.1 m), whereas the M_w 8.6 and M_w 9 earthquakes generated maximum tsunami heights of 0.2–0.5 m after 10 h in Kuwait City. Incorporating the effects of natural tide would cause a tsunami in the broader area, with a higher maximum deduced tsunami amplitude of more than 0.5 m in Kuwait for an M_w 9 earthquake with an earlier tsunami arrival time. This effect was evident in Kuwait rather than in other countries in the AG. Latcharote et al. (2018) also evaluated tsunami hazard in Kuwait from submarine earthquakes, following worst-case scenarios with M_w 8.3–9 along the MSZ. Four scenarios were employed: Case 1 (M_w 8.3), Case 2 (M_w 8.3 also), Case 3 (M_w 8.6), and Case 4 (M_w 9) with respective rupture lengths of 200 km, 220 km, 500 km, and 900 km, and maximum uplifts of 3, 3, 5, and 9 m, respectively. The results suggested that the tsunami waves from Cases 1 and 2 had an insignificant impact on the AG. While case 3 (M_w 8.6) could cause a tsunami amplitude of less than 0.5 m in Kuwait. The M_w 9 full MSZ earthquake scenario (case 4) had a remarkable impact on the entire Gulf region. It generated a maximum tsunami amplitude of up to 0.5 m along the Kuwaiti coastline after 12 h. The same study analysed the effect of ocean tide on tsunami propagation, focusing on case 4 (M_w 9 full MSZ earthquake). In the AG entrance, this combination resulted in a tsunami arrival time interval of ∼2–3 h, and a maximum tsunami amplitude of ∼2–3 m. Furthermore, along the Kuwaiti coastline, the tsunami arrival time became 1 h shorter, resulting in a 0.2–0.3 m increase in maximum tsunami amplitude. Recently, the DTH assessment following an M_w 9.2 whole-fault trench-rupturing earthquake scenario by Cheng et al. (2024) generated a tsunami that did not affect Kuwait, with a nil run-up registered at Kuwait City (Cheng, 2022). Table 7 summarizes the DTHA results for the Kuwait Region.

2.1.3.2.5 DTHA in Qatar

Oskamp et al. (2015) used a hypothetical M_w 9 full MSZ scenario simulation, which resulted in small tsunami waves on the Eastern coast of Qatar, reaching 0.5 m. According to the deterministic study by Suppasri et al. (2016), M_w 8.3 and M_w 8.6 scenarios had a negligible impact on the inner parts of the AG, while the M_w 9 scenario caused a 1 m wave height along the coasts of Doha. Similar results were achieved by Latcharote et al. (2018), where the M_w 9 full MSZ earthquake scenario resulted in tsunami waves that propagated to the AG and arrived at Doha after ∼6–7 h, causing a 1 m tsunami wave amplitude. In the studies by Al-Salem and Al-Enezi (2020) and Al-Salem and Al-Sarawi (2023) detailed topography and bathymetry data, along the Qatar coast, from the KISR Coastal Information System (Al-Salem and Al-Enezi, 2017). TUNAMI-N2KISR model (Imamura, 1989; 1996; Al-Salem and Al-Enezi, 2017) was applied to predict the tsunami propagation. The model employs the staggered leapfrog scheme to solve the shallow water equations, which describe nonlinear long-wave theory. Two scenarios were simulated. The M_w 8.6 MSZ earthquake scenario, with a 500 km rupture length, had a considerable impact mainly at the Gulf entrance with a maximum uplift of 5 m. The generated tsunami arrived at Al-Doha city at 9:00, with a wave amplitude of ∼0.2 m. The M_w 9 MSZ earthquake scenario, with a rupture length of 900 km, had a greater impact at the Gulf entrance, with a maximum uplift of 9 m. The tsunami arrived at the Ras Laffan and Al-Doha city coasts in 8 and 8.5 h, respectively, causing a wave amplitude of ∼0.6 m. The coupling of the 2D tide level and tsunami simulation showed a higher wave amplitude of ∼ 1.6 m at spring tide, with somewhat earlier arrival times. Recently, the DTH assessment following an M_w 9.2 whole-fault trench-rupturing earthquake scenario by Cheng et al. (2024) generated a tsunami with a very slight wave height of 0.28 m in Doha (Cheng, 2022). Table 8 summarizes the DTHA data for Qatar.

Far-field tsunami impact within the Arabian Gulf is substantially attenuated relative to the near-field Makran coast due to long propagation distances and energy dissipation across shallow basins. Oman may experience substantially larger far-field wave heights (up to ∼7 m) due to its direct exposure to Makran tsunami propagation, whereas modelling studies indicate that the eastern coast of the UAE may still experience significant wave heights exceeding 2 m for large Makran megathrust events, whereas Qatar, Bahrain, and Kuwait are exposed to considerably smaller amplitudes. This regional variability in far-field tsunami hazard across the Arabian Gulf is summarized in Figure 9.

FIGURE 9

2.1.3.2.6 Other far-field countries

In Bahrain, according to the deterministic study by Suppasri et al. (2016), M_w 8.3 and M_w 8.6 scenarios had a negligible impact on the inner parts of the AG, while the M_w 9 scenario caused a 1 m wave height along the coasts of Manama. Similar results were found by Latcharote et al. (2018), where the M_w 9 complete MSZ earthquake scenario resulted in tsunami waves that propagated to the AG and arrived at Manama after ∼9 h, with a 1 m tsunami wave amplitude. In Saudi Arabia, the DTH assessment following an M_w 9.2 whole-fault trench-rupturing earthquake scenario by Cheng et al. (2024) generated a tsunami with a very slight wave height of 0.15 m in Dammam (Cheng, 2022). Rastgoftar et al. (2025) evaluated tsunami hazards in the Persian Gulf. Using nonlinear shallow-water numerical modelling, the study found that far-field tsunamis from the MSZ are expected to remain below 0.5 m, suggesting limited impact on the Gulf’s interior shores.

In the Maldives, the numerical simulation of the 1945-like tsunami study by Arjun et al. (2011) showed a travel time of 197 min. In Sri Lanka,Wijetunge (2009) studied a worst-case scenario of simultaneous rupture of the entire Eastern segment of the Makran Trench, using a hydrodynamic model based on linear shallow-water equations. The simulation resulted in a tsunami with maximum wave amplitudes of 1 m along the coastal belts of the Western, North-Western, and Southern Provinces, and of 0.2 and 0.1 m in Eastern and Northern provinces, respectively. Tsunami waves will first hit the coastal belt of the Western Province about 280 min after the earthquake, followed by Southern and North-Western Provinces. Similar TTT of 283 min was deduced by the numerical simulation of the 1945-like tsunami by Arjun et al. (2011).

In the Eastern African coast,Salaree and Okal (2020) compared the potential effect of tsunami simulations from mega-earthquake sources in the Indian Ocean. Numerical simulations were carried out for several virtual gauges spanning the East African coast, from Socotra in the North to Port Elizabeth in the South, as well as adjoining islands (Madagascar, Comoros, and the Mascarenes). The 1945 earthquake was used as a source for MSZ. The study generally showed lower amplitudes simulated from the Makran sources with depths greater than 5 cm, concluding that the MSZ is not the primary contributor to tsunami hazard for the Eastern African coast. Salama et al. (2020) conducted a tsunami model simulation for several scenarios to investigate their impact on the African Coast. Among them was the Makran 1945-like scenario, M_w 8, following the fault parameters of Jaiswal et al. (2009). The studied scenario resulted in a tsunami with maximum wave heights of 1–2 m striking the Somali coast after 234 min. Recently, Cheng et al. (2024) also performed a DTHA following an M_w 9.2 whole-fault trench-rupturing earthquake scenario, generating a tsunami slightly affecting coastal cities bounding Eastern Africa, which experienced maximum wave heights reaching 0.6 m in Mogadishu, Somalia, 0.43 m in Dar es Salaam, Tanzania, and 0.09 m in Maputo, Mozambique (Cheng, 2022).

In Seychelles, Seng and Guillande (2008) modelled three scenarios: an M_w 8.8 with 8.89 m slip worst-case scenario, an M_w 8.3 with 1.58 m slip intermediate-case scenario (1945-like), and an M_w 7.5 with 0.79 m slip best-case scenario. The worst-case scenario generated a tsunami with a TTT of about 4 h 15 min for the Northern Island and <6 h for the Southwest Islands. The tsunami would cause a maximum wave height of 2–3 m in the bay of central Victoria, a maximum wave amplitude of 1–2 m on the East coast, Seychelles International Airport, Anse A La Mouche, and of <1 m maximum wave height in other areas. The intermediate case scenario generated a tsunami with a peak amplitude ranging from 5 to 10 cm before run-up, respectively, causing minor flooding on the Western coast of Mahe. The best-case scenario generated a tsunami with a peak wave amplitude before run-up of <10 cm, causing very little to no inundation for the main islands. The DTHA by Neetu et al. (2011), simulating a 1945-like tsunami (Byrne et al., 1992) On the Seychelles archipelago coasts, the result was a wave height of around 15 cm, arriving more than 6 h later at Port Victoria. The simulation demonstrated several hours of continued tsunami oscillations, influenced by the surrounding large, shallow shelf. The initial wave reached the shallow area, intensified, and became trapped there due to reflections from the shelf break. The trapped energy reverberated on the shelf for several hours and was scattered by the islands, creating a complex wave pattern. Recently, Hasan et al. (2024) assessed tsunami hazard from seven hypothetical ruptures of the MSZ based on the 1945 tsunami, each varying in length and width. The scenario 800 × 355, rupturing the full-length MSZ fault, represented the worst-case scenario, generating a tsunami with a wave amplitude of 0.9 m in Seychelles, arriving in 5 h 44 min.

In South Africa, Kijko et al. (2018) studied DTHA based on mega-earthquakes in remote subduction zones, including MSZ. Numerical simulations were performed using the GEOWAVE application (Watts et al., 2003). The worst-case scenario followed Byrne et al. (1992) configuration with a 280° fault strike and M_w 8.2. This scenario generated a tsunami with an amplitude of 0.13 m in Durban, 0.07 m in Port Elizabeth, and 0.06 m in Cape Town. Although still insignificant, the values are slightly larger than those obtained by the second scenario, which referred to the 1833 Sumatra subduction zone earthquake, but in MSZ, following Byrne et al. (1992) configuration, with M_w 7.5. This scenario generated a tsunami with a 0.009 m in Durban, 0.006 m in Port Elizabeth, and 0.003 m in Cape Town. Overall, the MSZ-generated tsunami impact on the selected sites in both scenarios remained minimal. The DTH assessment following an M_w 9.2 whole-fault trench-rupturing earthquake scenario by Cheng et al. (2024) generated a tsunami with a very slight wave height of 0.17 m in Durban, South Africa (Cheng, 2022). Table 9 summarizes the DTHA results for far-field countries.

3 Tsunami hazard assessment discussion

Tsunami hazard estimates in the MSZ exhibit extreme variability depending on the seismic source magnitude. For “1945-like” scenarios, DTHA generally predict near-field run-up values of ≤5 m in Pasni and Ormara, and approximately 0.5 to ≥2 m along the southern Iranian coast (Heidarzadeh et al., 2008a; Honarmand et al., 2019; 2020). However, some simulations for the same magnitude suggest higher peaks of 12–15 m for the Pakistani coastline (Rajendran et al., 2008). This spread indicates that even for similar source magnitudes, local run-up estimates remain highly sensitive to source parameterization and coastal configuration. In contrast, “worst-case” for extreme full-rupture megathrust scenarios produce a nonlinear increase in coastal impact. Predicted peak run-ups for these events range from 28 to 80 m in the near-field of Pakistan (Qiu and Barbot, 2022) to average run-ups of 24–30 m in Iran (Heidarzadeh et al., 2009a). Far-field impacts remain significant in these large scenarios, with peak values reaching 5–8 m along the northern coast of Oman (Browning and Thomas, 2016), and up to 12 m in some studies (Rashidi et al., 2020), whereas far-field areas such as the Arabian Gulf and western Indian Ocean generally remain below 5 m. The UAE is generally on the order of ∼2–3 m even for M_w ≥ 9 full-rupture scenarios (Suppasri et al., 2016; Latcharote et al., 2018; (Hamidatou et al., 2024). The compiled distribution indicate that a single representative mean for the whole region would be misleading; instead, at least two distinct hazard regimes should be resolved: a high-impact near-field regime (several to tens of metres) and a lower far-field Gulf regime (sub-metre to a few metres).

A similar separation appears in the probabilistic compilation. Offshore amplitudes for a 2000-year return period were reported as 3.8 m for Oman, 2.8 m for Pakistan, 2.7 m for Iran, and 0.8 m for the UAE (Burbidge et al., 2009), indicating a systematic decrease from the open Makran margin toward the Gulf. Similarly, stochastic PTHA results show that M_w 8.5–8.7 western MSZ sources generated tsunami heights of 1–10 m with a mean of ∼4.5 m, while the estimated 2475-year tsunami height in Chabahar ranges from 3 to 7.4 m (Momeni and Goda, 2024). These values quantitatively support a consistent decay in hazard with increasing distance from the source region. Importantly, this regional gradient is observed in both deterministic and probabilistic frameworks, reinforcing its robustness.

The deterministic studies further highlight pronounced spatial variability in tsunami impacts at the local coastal scale. In the near-field, coastal segments of Pakistan and Iran are consistently identified as the most exposed, with TTT as short as 5–15 min (Heidarzadeh et al., 2006; Rajendran et al., 2008; Moradi, 2021). Within Pakistan, Gwadar and Ormara repeatedly emerge as the most vulnerable sites, reflecting both short arrival times and high run-up potential. For example, in the M_w 9 scenario of Mahmood et al. (2012), maximum run-up reaches 7.5 m at Gwadar, 6 m at Ormara, and 5.4 m at Pasni, with corresponding arrival times of 12, 17, and 21 min. Similarly, Chabahar in Iran is also identified as a highly exposed urban center. In contrast, Karachi consistently exhibits lower wave amplitudes and longer travel times, largely due to dissipation across its wide continental shelf. Reported run-up values remain relatively modest, including 0.44 m in Neetu et al. (2011), 0.06–0.5 m across several scenarios in Sarker (2019), and 3.77 m even under the worst-case full-length rupture scenario of Hasan et al. (2024), although damaging inundation cannot be excluded under extreme conditions. At the far-field scale, the Gujarat coast represents the most vulnerable region in India due to its proximity to the eastern MSZ, with travel times of ≤2 h. Conversely, the other regions experienced delayed arrivals and reduced amplitudes (Jaiswal et al., 2009; Srivastava et al., 2011; Patel et al., 2016). The Lakshadweep Islands further play a protective role, acting as a natural “wave barricade” that reduces wave energy reaching the southwestern coast of India. Overall, these comparisons demonstrate that tsunami impact severity is strongly governed by local coastal configuration, bathymetry, and proximity to the source, underscoring the need to complement broad regional assessments with detailed site-specific analyses.

Across the wider region, the same spatial pattern persists, a robust regional pattern emerges from both deterministic and probabilistic studies: hazard is highest along the Makran margin and Gulf of Oman, then decreases toward the Strait of Hormuz and becomes distinctly weaker within the inner Arabian Gulf. This attenuation is attributed to geometric spreading, bathymetric dissipation, and partial shielding by the Strait of Hormuz. Within the Gulf, the UAE remains exposed to non-negligible far-field tsunami effects, but these are still substantially smaller than the near-field MSZ coastlines. Northern Oman, southeastern Iran, and the Pakistan coast are consistently ranked as the most exposed sectors, whereas southern Oman, the Strait of Hormuz, and the Arabian Gulf show lower hazard levels. Probabilistic results confirm the same pattern. For example, the POE of 1 m tsunami waves in Oman reaches 0.7 in 100 years, 0.85 in 250 years, and approaches one over 500–1,000 years, especially along the northern coast, whereas southern Oman remains markedly less exposed (El-Hussain et al., 2016). In southeastern Iran, Konarak is recognized as one of the highest-hazard site and Sirik as one of the lowest, with POE for 3 m in 500 years reaching about 63% at Konarak and 0% at Sirik (Rashidi and Keshavarz Farajkhah, 2019). These comparisons shows that tsunami hazard is spatially structured rather than uniformly distributed along the northern Arabian Sea margins.

The spread among published tsunami hazard estimates reflects fundamental differences in model assumptions and input parameters. Key sources of variability include source parameterization, rupture segmentation, slip heterogeneity, recurrence models, bathymetry, coastal morphology, and the choice of numerical modeling approach. Among these, source characterization particularly assumptions regarding maximum magnitude, rupture extent, and slip distribution appears to exert the strongest control on hazard variability. In probabilistic frameworks, larger assumed maximum magnitudes systematically lead to higher hazard levels, while the wide dispersion in results highlights significant epistemic uncertainty in both source characterization and recurrence intervals.

Quantitatively, this uncertainty is pronounced across multiple scales. For example, POEs for extreme run-up levels can vary dramatically depending on the assumed maximum magnitude, increasing from relatively low values to very high probabilities under larger magnitude scenarios. Similarly, site-specific hazard estimates may span broad ranges even for the same return period, with reported tsunami heights differing by several meters. At the regional scale, compiled datasets show that run-up values can extend from negligible amplitudes (<0.2 m) to extreme values exceeding 50 m. Deterministic scenarios further illustrate this variability, with outcomes ranging from minimal or no impact under less favorable conditions to several meters of run-up in near-field locations, and reaching several tens of meters in extreme, fully ruptured trench-breaking scenarios. Tsunami hazard estimates in the MSZ may vary by more than an order of magnitude depending on source assumptions and modeling choices.

Certain hazard estimates remain subject to considerable uncertainty and should therefore be interpreted with caution. Studies that lack sufficient methodological detail or do not report underlying datasets are difficult to evaluate and cannot be fully integrated into quantitative comparisons. Likewise, the most extreme deterministic run-up estimates should be explicitly framed as upper-bound exploratory scenarios rather than representative expectations, because they fall at the extreme upper edge of the compiled envelope and are highly sensitive to rupture geometry and structural assumptions.

A balanced interpretation distinguishes three categories of hazard estimates: (1) robust recurring patterns supported by multiple studies, such as higher hazard along the near-field Makran margin compared to the Arabian Gulf; (2) Site-specific but plausible high values associated with local amplification, such as at Gwadar, Ormara, Konarak, Muscat, and Sur; and (3) Upper-bound or weakly constrained estimates that depend strongly on extreme full-rupture or trench-breaking assumptions and should therefore be considered scenario-dependent rather than regionally representative.

Overall, tsunami hazard in the MSZ is characterized by strong spatial variability, sensitivity to source assumptions, and substantial epistemic uncertainty. The dominant regional pattern is robust, with hazard decreasing from the Makran margin toward the Arabian Gulf. However, uncertainty constitutes a first-order characteristic of tsunami hazard assessment in the region, rather than a secondary dispersion around a single representative estimate.

3.1 Tsunami risk, vulnerability assessment (TRVA) and early warning systems (EWS)

This section provides an overview of tsunami risk across the MSZ, integrating hazard characteristics with coastal exposure and societal vulnerability. All run-up values considered in the TRVA analysis are derived exclusively from tsunamis generated by tsunamigenic earthquakes within the MSZ.

On the global scale, Løvholt et al. (2012) performed a tsunami risk assessment using GloBouss model to demonstrate total and relative human and economic exposure to tsunamis for a return period of 475 years. The detailed results of modelling an earthquake of M_w 8.4 in the MSZ and its impact on Pakistan, Iran, India, and Oman are provided in the study.

3.1.1 TRVA and EWS in Pakistan

Ahrari-Roudi (2016) evaluated stability and marine hazards coastal zoning in the southern provinces of Sistan and Balochistan using GIS. Low and High-risk zones were identified based on geological structure, damage intensity, and topography, dividing the coast into 7 regions. Hasan et al. (2017) assessed tsunami risk to Karachi port through currents simulation produced by the 1945 Makran tsunami, utilizing the open-source code GeoClaw, with bathymetry and shorelines mapped before 1945, as well as newer bathymetry data. Results showed that the strongest currents coexisted during water receding, when the wave surface elevation was at its lowest. The strongest currents occurred over the 1939 bathymetry, ranging between 1.8 and 3 ms^-1, which is fast enough to cause minor to moderate damage in the seaward parts of Karachi Harbour. The simulated velocity field revealed large and intense gyres of high vorticity forming near the breakwater. The modern bathymetry and shorelines indicate weaker currents, likely due to the post-1945 extension of a breakwater. Mahar et al. (2019) analysed Pakistani Makran coast using bathymetry data, seismic record, tectonic situation, and modelling, to map i) bathymetry (with 50–500 m contour) with shelf profiles and aspect, ii) seismic activity (1905–2013) and faults with their locations and orientations, iii) Tsunami propagation to show wave directions along the faults, and iv) vulnerability with three risk zones of about 1,000 m, highlighting the exposure of four coastal settlements, Gwadar, Ormara, Pasni and Karachi. According to them, any tsunami generated along the coastal belt of Makran could cause disaster and result in significant losses. Recently, Haider et al. (2023) performed a multi-proxy approach to assess tsunami hazard and risk in Makran Coast, Pakistan, including the bathtub approach. Four wave scenarios (3, 7, 10, and 15 m) were used to demarcate risk areas through static inundation analysis. The results indicated minor to negligible damage potential with 3 m waves and moderate damage potential with 7 m waves. Whereas the 10 and 15 m waves would severely disrupt the area. Results indicate very high risk at Ormara, Pasni, and Gwadar due to their orientation, low topography, and proximity to the tsunami source, with Karachi being the most vulnerable to extreme waves. At least 0.7 million people would be at risk. Similarly, Haider et al. (2024) conducted a vulnerability analysis for the cities of Pasni and Gwadar using both hydrodynamic and static approaches, based on wave scenarios (7, 10, and 15 m) designed based on the evaluation of tsunamites’ paleomorphodynamic records. At Pasni, the maximum damage probabilities were 0.50, 0.95, and one for the 7, 10, and 15 m scenarios, respectively, with relatively lower probabilities in other points in Pasni. In Gwadar, damage probabilities were of 0.4, 0.8, and one for the 7, 10, and 15 m scenarios, respectively. Although lower values, vulnerability level was higher due to a wider impact touching most of the Gwadar area, except for Pishukan who witnessed lesser impact. Both cities were highly vulnerable to wave heights ≥7 m and wave lengths ≥15 km. The 15 m scenario would generate a near-total devastation. Coastal orientation and morphology exacerbate the impact through reflection, integration, and amplification, with intensity increasing positively with the approaching waveform size. Ali Khan (2023) performed tsunami risk assessment for the entire coast based on the aspects of hazard, vulnerability, and coping capacities using logic-tree. The results showed a destructive tsunami impact with a uniform high-risk rank. Physical vulnerability was also uniformly rated as very high due to the homogeneous urban planning of the region. However, social vulnerability and coping capacity showed considerable variation, with risk ranks ranging from low to very high. Ghaderi and Rahbani (2024) evaluated the shoreline vulnerability of the Eastern coast of Makran using geomorphological and hydrodynamic parameters. A Coastal Vulnerability Index (CVI) was employed, considering both physical and geological variables, using a GIS technique, the MIKE 21 model, and RS imagery. 52% of the coastline was ranked as highly vulnerable, and 15% as very highly vulnerable, with the Govater mangrove forest and Khowre Bahu estuary, as well as the protected area of Gando (Bahuklat), being the most vulnerable areas. Naeem et al. (2016) and Naeem (2020) provided detailed studies on tsunami risk mitigation plans in the coast of Pakistan. Table 10 summarizes the TRVA results for Pakistan.

3.1.2 TRVA and EWS in Iran

Lahijani et al. (2010) assessed the potential inundation areas for tsunamis, using the impact of past events. Based on the long wave height value, three flood zones were specified. A first zone associated with no considerable inundation on uplifted rocky shore, a second zone experiencing up to a few km inundations on the coast of Chabahar and Jask areas. And a third zone with areas of sandy beaches, supported by high cliffs, falls between two extreme regions. Madani et al. (2017) assessed building vulnerability to tsunami within Chabahar Bay, using the Papathoma Tsunami Vulnerability Assessment (PTVA)-3 model to calculate a relative vulnerability index (RVI) based on their physical and structural characteristics. In a postulated worst-case scenario, ∼60% of the residential buildings would be affected with a level of damage categorized as Average in the RVI classification, with a related economic loss equivalent to 16.5 million US$. Arasteh and Lari (2019) investigated the possibility of seismic noise transmission in the Sound Fixing and Ranging (SOFAR) channel. The sound travel time was one-seventh of the travel time of an earthquake-generated tsunami. In case a tsunami is triggered at the nearest point in MSZ, 150 km from the Iranian coast, the generated wave would approach the coast at 500 km/h, taking about 20 min to hit the beach. Three minutes are needed for the shore station to receive the generated seismic signal via the SOFAR channel, leaving only 17 min for the EWS to act. Ghanavati et al. (2021) conducted an analysis of the vulnerability of the Makran coastline of Iran to global sea-level rise, by developing a CVI for the studied area using satellite, instrumental and field data, with eight risk variables and 27 coastal segments. ∼50% of the coast was classified as less vulnerable due to rocky shores, ∼33% was ranked as highly vulnerable due to sandy beaches, tidal flats, and mangrove forests, while ∼12% of the coastline was demarcated as moderately vulnerable. Population centres and infrastructure were categorized as highly to moderately vulnerable, mostly in the Western part. Pourkerman et al. (2022) held a detailed study of the environmental risks impacts in Chabahar, demonstrating how climate change could accentuate socioeconomic damage caused by tsunamis in the Northwest Makran zone. Rashidi et al. (2025) created a vertical evacuation map for Jask port, based on a DTH study. The entire Southeastern coastline of Iran was affected by all the examined tsunami scenarios, with the maximum coastal amplitude being about 13 m near the Kereti coast. The inundation map for Jask port, based on modelling an M_w 8.5 Western Makran scenario, revealed an extensive reach of tsunami waves, with inundation distances up to 2 km and run-up heights reaching 6 m. Most areas were inundated -only for some locations protected by barriers-, reaching the Chabahar road. The study highlighted the potential impact on critical infrastructure, including schools, hospitals, main roads, and airports. Table 11 summarizes the TRVA results for Iran.

3.1.3 TRVA and EWS in India

Singh et al. (2008) conducted a risk assessment for Gujarat, using SRTM data and ETOPOv2v for inundation scenarios due to 5 and 10 m run-up heights. A 2 m run-up elevation would cause inundation in Jakhau and Kandla area of Gulf of Kutch region. A 3 m run-up height would induce inundation in Kandla port area due to its low elevation. In Gulf of Kutch, a 5 m run-up height would trigger the inundation of ∼623 km². Whereas, the Saurashtra region showed less possibility of inundation, being protected with high cliffs (20 m) made up of Miliolitic limestones. Devi and Shenoi (2012) provided a detailed review on tsunami effects on coastal morphology and ecosystems. They stated that tsunami waves can extensively change coastline topography owing to considerable erosion and subsequent deposition of substantial quantity of sediments and salt in relatively short time spans, substantially impacting the coastal ecosystem, such as mangroves, coral reefs, and forests. Patel D. M. et al. (2014) attempted to create an alert scheme and an evacuation map for Okha city, West of Gujarat, for tsunami EWS for the possible tsunami risk from MSZ, following the DTHA study by Patel et al. (2013). Stepwise procedure of evacuation mapping was followed. Hazard maps were created using ALTM data and RTK (Real Time Kinematic) GPS. Road map, Population map with existing routes, and Geo-reference map were generated. Vertical Evacuation Suggestions map was further derived based on the topography and geology of the study area. Patel et al. (2017) also documented a preliminary tsunami hazard mapping and strategy for tsunami evacuation for Diu city, Gujarat, pinpointing the most important locations. The 1945-like tsunami modelling in the Gulf of Kutch by Patel et al. (2015) gave maximum amplitudes along the creeks at the coast of Gujarat, proposing them as the most vulnerable areas, and thus greater protection was required when planning for preparedness. Mangrove forests are capable of dissipating wave energy, and thus they play an important role in coastal protection. The analysis of the inundation area showed that a 7983.341 km² area can be affected by tsunami waves up to 2 m in height. The dense mangrove area in the Gulf of Kutch covered up to 235.814 km². Deducing that planting mangrove species, such as Avicennia marina, Ceriops tagal, and Rhizophora mucronata rapidly growing up to heights of 3–5 m, can resist tsunami waves of higher altitudes. Zuhair and Alam (2017) studied the effect of a MSZ induced tsunami M_w 9, on nuclear power plants along the Western coast of India. They suggested the safety of the nuclear power plants, since Jaitapur one is located 1 km away from the sea with an altitude of 27 m, flooding chances along the Tarapur is negligible, and Kaiga one is situated 55 km away from the sea. Recently, Sahdev (2023) provided a report on tsunami disaster impact and mitigation in India. Table 12 summarizes the TRVA results for India.

3.1.4 TRVA and EWS in Oman

In the Scenario-based tsunami risk assessment study by Schneider et al. (2016), the PTVA model was employed for the infrastructure structural vulnerability for a 2 m tsunami scenario, depicting the 1945 tsunami, as well as a 5 m tsunami in Muscat. An RVI was introduced by the authors, who indicated a minor tsunami risk for a 2 m scenario, as flooding remains limited to beaches and wadis, while the prevalence of traditional brick buildings and a coast-parallel road network increased the vulnerability. In contrast, a 5 m scenario caused widespread flooding, affecting up to 48% of buildings, with an aftermath of 60,000 damaged buildings, and 380,000 directly affected residents, substantial loss of life, and critical infrastructure impairment in the Muscat Capital Area. Gonzalez et al. (2016) presented two computationally simulated scenarios at national and local scale, in 9 municipalities all along the coast of Oman, including the cities of Sohar, Wudam, Sawadi, Muscat, Quriyat, Sur, Masirah, Al Duqm, and Salalah. TRVA was conducted, considering different dimensions (human, structural). The study identified high-risk areas along the coast of Oman in which measures for risk reduction were proposed. Browning and Thomas (2016) calculated probable maximum loss utilizing a simple method of building identification and a revised building damage assessment technique. Reconstruction cost resulting from tsunami inundation, based on M_w > 8 East MSZ tsunami scenario, equates to 6,924,000 OMR. Aguirre-Ayerbe et al. (2018) applied the numerical modelling COMCOT (Wang, 2009) to solve shallow water equations using the Okada model (Okada, 1985). TRVA, considering both the hazard and vulnerability components, showed that the Northern area of Oman would be the most affected in terms of tsunami-prone flooded areas, especially Barka and As Seeb, as well as Mahawt and Al Jazir wilayats in the Eastern area. This area also concentrates nearly 50% of the hot spots identified throughout the country, with 70% being located in areas with a very high-risk rank. The study also mentioned the development of Tsunami Hazard, Vulnerability and Risk Atlas and the Risk Reduction Measures Handbook for Oman. According to Aniel-Quiroga et al. (2018), an online tool, the Multi-Hazard Risk Assessment System (MHRAS) was created based on the development of a scenario database and was integrated into Oman’s National Multi-Hazard Early Warning System (NMHEWS). Al-Habsi et al. (2022) performed tsunami risk zoning for Quriyat on the Northeast Oman coast. Five hazard levels, ranging from very low to very high, were implied for human stability zoning, and six damage levels, ranging from minor to washed away, were attributed to buildings’ classification, while vessels were classified upon weight and motor location. Fragility analysis showed that over 75% of buildings had a high probability of enduring minor to moderate damage. Outboard motor vessels weighing <5 tons would suffer greater loss than inboard and heavier vessels. Table 13 summarizes the TRVA results for Oman.

3.1.5 TRVA and EWS in UAE

Abdouli (2010) conducted a tsunami risk assessment for Fujairah city in the UAE, utilizing DEM and IKONOS satellite imagery. The study highlighted an increase in the number of buildings at risk from tsunami scenarios with run-up heights of 6–10 m and 11–15 m, primarily due to the concentration of residential and retail structures. Furthermore, the rebuilding cost for 1- 3 story buildings was less than that of higher taller buildings (10–30 stories), primarily due to the larger quantity of the former. Given Fujairah’s coastal location, with nearly 44% of its population residing within 2 km of the coastline, the city is significantly exposed to tsunami risk in case of >6 m run-up events. The spatial distribution of heritage sites by Yagoub and Al Yammahi (2022), indicated a risk on heritage areas in the UAE because of the indirect effect of tsunami through flood and water level rise, with the Northeastern region being the most vulnerable. In the tsunami hazard analysis performed by Jordan et al. (2005) along the coasts of the UAE, the geometry of the Gulf, demarcated by a shallow depth, attributes a low risk from tsunamis to the area. Nandasena et al. (2024) conducted a small-scale experimental and numerical studies to assess the Tsunami-Like Flow Impact and stability of the Fujairah Port Breakwater. According to the study, a 3 m tsunami wave height was safe on the breakwater. While 4–5 m wave heights damaged the leeside from the leeward end to the middle of the breakwater. A 6-m tsunami height caused severe damage to the lee- and the seasides with a major reshape to the breakwater. Rubbles were transported due to sliding, rolling, and saltation by overtopping and seepage, however, the breakwater remained un-breached. More recently, Nandasena et al. (2025) examined tsunami flow characteristics along the east coast of the UAE—an area with limited historical tsunami records but increasing seismic activity—using one-dimensional numerical modelling and Artificial Neural Networks (ANN). The study identifies Khor Fakkan and Mirbih as the most vulnerable sites, experiencing the greatest maximum tsunami depths. The analysis shows that seabed slope and still sea depth are more influential than the tsunami period in predicting shoreline inundation. Table 14 summarizes the TRVA results for the UAE.

4 Regional EWS discussion

The Indian Ocean has historically been a hotspot for tsunami activity, with numerous devastating events resulting in a considerable number of casualties and economic losses. Owing to their destructive nature, it is crucial to rapidly assess whether a tsunami has been generated following an earthquake by analysing key parameters such as earthquake magnitude, focal depth, and fault rupture characteristics. Following an earthquake, real-time seismic information can be accessed through specialized operational systems, such as the Indian Tsunami Early Warning System (ITEWS) and Meteorology, Climatology, and Geophysics Agency (BMKG), while more detailed scientific source parameters, encompassing moment tensor solutions, can be obtained from global datasets such as the Global Centroid Moment Tensor (CMT) catalog. These resources are fundamental for evaluating tsunami generation potential immediately following large earthquakes.

Modern tsunami EWS rely on pre-computed tsunami numerical simulations and scenario databases to issue timely alerts. A landmark development occurred in 1999, when the Japan Meteorological Agency (JMA) introduced a computer-aided tsunami forecasting system based on pre-calculated tsunami arrival times and wave heights for rapid post-earthquake forecasting (Imamura and Abe, 2009). However, despite these advancements, accurately predicting whether a given earthquake will generate a tsunami generation remains challenging. This uncertainty arises from limitations in resolving rupture dynamics, shallow fault slip, and seafloor deformation in near real time. Consequently, robust estimation of seismic parameters, including earthquake magnitude, focal depth, and rupture dynamics, are fundamental to assessing tsunami hazard assessment. Similar to that of earthquake magnitudes scales, early efforts to quantify tsunami size led to the development of the first attempt to establish a quantitative tsunami magnitude scale was made by Iida et al. (1967), laying the groundwork for modern tsunami intensity and hazard classification.

Since 1945, rapid coastal urbanization, population growth, and economic development have substantially increased the vulnerability of communities in the Makran region. This exponential rise in exposure emphasizes the urgent need of incorporating advanced tsunami hazard assessments into comprehensive disaster preparedness strategies (Mokhtari et al., 2019). The MSZ was extensively studied using historical earthquake records, sedimentological evidence of past tsunami deposits, and numerical modelling techniques to refine tsunami hazard (Heidarzadeh and Satake, 2015). Collectively, these studies highlight the variability of tsunami source mechanisms, influence of bathymetric and coastal geomorphology on wave propagation, and limitations of current predictive models, thereby necessitating the continuous refinement of risk assessment methodologies.

The EWS in the five nations bordering the northern Arabian Sea-India, Oman, UAE, Pakistan, and Iran exhibits a notable gradient maturity in technical infrastructure, institutional framework, and community preparedness. India operates one of the most advanced systems in the region, with the Indian National Centre for Ocean Information Services (INCOIS) providing real-time monitoring, modelling, and regional advisory services across the Indian Ocean (Srinivasa Kumar et al., 2010; Satake, 2014). Oman and the UAE have developed integrated multi-hazard early warning frameworks, incorporating tsunami monitoring within broader national risk management systems and benefiting from regional coordination mechanisms (Hamidatou et al., 2024; UNDRR, 2023). In contrast, Iran and Pakistan have made notable progress but their systems remain comparatively less mature, with ongoing efforts to enhance seismic and sea-level monitoring networks, warning dissemination, and institutional coordination, as well as recent shift toward improving public risk perception and evacuation logistics in critically short lead times regions (IOC-UNESCO, 2025). Overall, despite significant advances under the Indian Ocean Tsunami Warning and Mitigation System (IOTWMS) and the whole region advancement, disparities persist in infrastructure density, real-time data integration, and operational readiness, underscoring the need for strengthened regional collaboration and capacity development.

5 Regional context of Makran tsunami hazard

The compilation of reported tsunami impacts associated with MSZ earthquakes reveals pronounced spatial variability in maximum run-up heights across the northern Indian Ocean and Arabian Gulf regions (Figure 10A). The highest reported run-up values occur along the near-field coasts of Iran, Pakistan, and Oman, where several studies document run-up exceeding 30–50 m for extreme full-rupture scenarios. In contrast, far-field regions such as the Arabian Gulf and western Indian Ocean coasts exhibit substantially lower amplitudes, generally below 5 m.

FIGURE 10

This regional attenuation pattern reflects the combined effects of geometric spreading, bathymetric dissipation, and partial shielding by the Strait of Hormuz, which limits efficient tsunami energy transmission into the semi-enclosed Arabian Gulf basin. The compiled literature therefore supports the established interpretation that MSZ tsunamis pose the greatest hazard along the Makran margin and Gulf of Oman, with decreasing intensity toward the inner Gulf coastlines.

Within the Arabian Gulf region (Figure 10B), reported tsunami run-up heights remain relatively modest compared to near-field MSZ coastlines but still demonstrate measurable hazard potential. Maximum reported values range approximately from 0.15 m to ∼3 m across Gulf states. The United Arab Emirates (UAE) shows run-up values on the order of ∼2–3 m for M_w ≥ 9 full-rupture MSZ scenarios, comparable to or slightly exceeding estimates for neighboring Qatar, Bahrain, and Kuwait.

This regional pattern indicates that although the Gulf is partly protected from direct MSZ tsunami propagation, long-period waves can still enter through the Strait of Hormuz and produce coastal flooding along low-lying shorelines. Consequently, the compiled dataset confirms that extreme MSZ earthquakes remain capable of generating non-negligible tsunami impacts along UAE coasts, consistent with deterministic modeling results presented in this study.

Scenario-based comparison (Figure 10C) demonstrates a clear amplification of tsunami run-up between moderate 1945-type events and extreme M_w ≥ 9 full-rupture MSZ earthquakes. Across nearly all regions, M_w ≥ 9 scenarios yield substantially larger run-up heights than 1945-like sources. This scaling reflects the strong dependence of tsunami generation on rupture length, seafloor displacement, and seismic moment.

In the Arabian Gulf specifically, the transition from 1945-type to full-rupture MSZ events increases expected run-up from sub-meter to multi-meter levels, highlighting the importance of considering worst-case rupture scenarios in regional hazard assessments. The compiled literature therefore supports the deterministic scenario framework adopted in this study, in which full-segment MSZ rupture represents the controlling upper-bound hazard for the UAE coastline.

The distribution envelope of compiled run-up values (Figure 10D) illustrates the broad range of tsunami amplitudes reported for MSZ earthquakes, spanning more than two orders of magnitude from <0.2 m in far-field settings to >50 m along near-field Makran coasts. This wide dispersion reflects differences in source parameterization, coastal morphology, bathymetry, and modeling approaches among studies.

Despite this variability, scenario grouping reveals a consistent hierarchy: M_w ≥ 9 full-rupture MSZ earthquakes produce systematically larger run-up than 1945-type events. The envelope therefore provides an empirical literature-based constraint on plausible tsunami amplitudes across the region and reinforces the interpretation that extreme MSZ rupture represents the dominant regional tsunami hazard driver.

The compiled literature dataset indicates strong spatial variability in tsunami run-up associated with MSZ earthquakes (Figure 10). Near-field coasts of Iran, Pakistan, and Oman exhibit the highest reported run-up (>30–50 m), whereas Arabian Gulf shorelines show substantially lower values (<5 m), reflecting geometric attenuation and partial shielding by the Strait of Hormuz. Within the Gulf, UAE run-up estimates (∼2–3 m) are comparable to neighbouring states, confirming that extreme MSZ earthquakes can still generate measurable coastal flooding. Scenario comparison demonstrates clear amplification from 1945-type to M_w ≥ 9 full-rupture events, highlighting the importance of worst-case rupture scenarios in regional hazard assessment. The overall run-up envelope spans more than two orders of magnitude (<0.2 m to >50 m), but consistently shows larger amplitudes for full-segment MSZ rupture, supporting its interpretation as the controlling upper-bound tsunami hazard for the UAE coastline.

Furthermore, A clear spatial bias exists in the available literature, with a stronger focus on the Eastern Makran compared to the Western Makran, particularly in DTHA-based studies. This limitation is largely driven by uneven data availability. Highlighting this gap is an important outcome, as it emphasizes the need for future targeted investigations and improved data acquisition in underrepresented sub-regions of the MSZ.

6 Conclusion

This study represents the third and last part of a three-part review series (Hamidatou et al., 2026a; Hamidatou et al., 2026b) addressing tsunamigenic earthquakes in the MSZ. This part C reviewed the evaluation of both the tsunami hazards and the associated risks affecting coastal communities and infrastructure across the northern Arabian Sea. It discussed methodologies used to identify tsunami-prone regions, the estimated wave heights and inundation areas, and the assessed vulnerability of populations and built environments. Historical tsunami data, modeling approaches, and strategies for risk mitigation such as early warning systems, land-use planning, and emergency preparedness were also explored. The aim was to provide a comprehensive overview of how tsunami hazards translated into real-world risks and how these risks had been systematically addressed in past research.

Analogously, the DTHA for the MSZ revealed significant spatial variability in tsunami impact levels across different coastal regions, influenced by factors such as bathymetry, coastal geomorphological variations, earthquake source parameters, fault directivity effects, and potential full-margin rupture scenarios generating extreme wave heights.

Despite its significant tsunamigenic potential, the MSZ remains poorly understood, presenting substantial challenges for hazard assessment and risk mitigation in the northwestern Indian Ocean. More than 7 decades after the devastating 1945 tsunami, which resulted in hundreds of confirmed fatalities, critical uncertainties persist regarding the seismotectonic behavior of the MSZ and its capacity to generate future large-scale tsunamis.

In a worst-case scenario, a Makran-generated tsunami could reach neighbouring coastlines within tens of minutes, with wave heights exceeding several meters, leaving little time for effective evacuation and emergency response. The challenges of issuing timely tsunami warnings in such scenarios are emphasized by recent unexpected tsunamis, such as those triggered by the 2018 Palu and Sunda Strait events in Indonesia, which have demonstrated the limitations of current warning systems in cases involving complex tsunami generation mechanisms.

Furthermore, Rapid urbanization and prioritized national development plans for the coastal MSZ region should consider implementing natural and industrial barrier structures, such as mangrove forest plantations, and dikes and breakwaters’ construction, as part of tsunami risk mitigation. Mangrove forests were proven to play a critical role in saving human lives and property during tsunamis (Patel et al., 2015). This review aims to contribute to a better understanding of the seismotectonic setting and dynamics of the MSZ, which in turn will lead to a refined sense of the tsunami hazard in the region. This is crucial for enhancing resilience and reducing the vulnerability of communities at risk.

Conclusively, this review provides a comprehensive synthesis of current research on tsunamigenic hazard in the MSZ, contributing to a refined understanding of the region’s seismotectonic dynamics. By bridging scientific advancements with policy-driven risk mitigation measures, this study highlights the critical need for enhanced resilience strategies to reduce the vulnerability of coastal communities at risk. The integration of multidisciplinary research, advanced early warning capabilities, and sustainable risk management approaches is crucial for safeguarding populations and infrastructure against future tsunamigenic events in the MSZ and beyond. It will provide insights into the evolution of scientific contributions, highlight the most influential studies and authors, and identify emerging topics and gaps in the field. The aim is to offer a quantitative overview of how tsunami research has developed over time and to contextualize the scientific efforts reviewed in the previous and current parts A, B, and C.

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