Geospatial Multicriteria Analysis for Earthquake Risk Assessment: Case Study of Fujairah City in the UAE

A clear understanding of the spatial distribution of earthquake events facilitates the prediction of seismicity and vulnerability among researchers in the social, physical, environmental, and demographic aspects. Generally, there are few studies on seismic risk assessment in United Arab Emirates (UAE) within the geographic information system (GIS) platform. Former researches and recent news events have demonstrated that the eastern part of the country experiences jolts of 3-5 magnitude, specifically near Fujairah city and surrounding towns. This study builds on previous research on the seismic hazard that extracted the eastern part of the UAE as the most hazard-prone zone. Therefore, this study develops an integrated analytical hierarchical process (AHP) and machine learning (ML) for risk mapping considering eight geospatial parameters—distance from shoreline, schools, hospitals, roads, residences, streams, confined area, and confined area slope. Experts’ opinions and literature reviews were the basis of the AHP ranking and weighting system. To validate the AHP system, support vector machine (SVM), decision tree (DT), and random forest (RF) classifiers were applied to the datasets. The datasets were split into 60 : 40 ratio for training and testing. Results show that SVM has the highest accuracy of 79.6% compared to DT and RF with a “predicted high” precision of 87.5% attained from the model. Risk maps from both AHP and ML approaches were developed and compared. Risk analysis was categorised into 5 classes “very high,” “high,” “moderate,” “low,” and “very low.” Both approaches modelled relatable spatial patterns as risk-prone zones. AHP approach concluded 3.6% as “very high” risk zone, whereas only 0.3% of total area was identified from ML. The total area for the “very high” (20 km2) and “high” (114 km2) risk was estimated from ML approach.

A River Flood and Earthquake Risk Assessment of Railway Assets along the Belt and Road

Mitigating the disaster risk of transportation infrastructure networks along the Belt and Road is crucial to realizing the area’s high trade potential in the future. This study assessed the exposure and risk of existing and planned railway assets to river flooding and earthquakes. We found that about 9.3% of these railway assets are exposed to a one in 100 year flood event, and 22.3% are exposed to a one in 475 year earthquake event. The combined flood and earthquake risk of physical damage to railway assets, expressed by expected annual damage (EAD), is estimated at USD 1438 (between 966 and 2026) million. Floods contribute the majority of the risk (96%). China has the highest EAD for both floods and earthquakes (between USD 240 and 525 million in total). Laos and Cambodia are the countries with the highest EAD per km from flooding (USD 66,125–112,154 and USD 31,954–56,844 per km, respectively), while Italy and Myanmar have the highest EAD per km from earthquakes (USD 1000–3057 and USD 893–3019 per km, respectively). For the newly built and planned projects along the Belt and Road, the EAD is estimated at USD 271 (between 205 and 357) million. The China–Indochina Peninsula Economic Corridor and China–Pakistan Economic Corridor have the highest absolute EAD and EAD per km, with EADs reaching USD 95 and USD 67 million, and USD 18 and USD 17 thousand per km, on average, respectively. For railway segments with high risks, we found that if the required adaptation cost within 20 years to realize a 10% increase of the railway quality is below 8.4% of the replacement cost, the benefits are positive.

Earthquake Risk Assessment from Insurance Perspective

The assessment of earthquake and risk to a portfolio, in urban or regional scale, constitutes an important element in the mitigation of economic and social losses due to earthquakes, planning of immediate post-earthquake actions as well as for the development of earthquake insurance schemes. Earthquake loss and risk assessment methodologies consider and combine three main elements: earthquake hazard, fragility/vulnerability of assets and the inventory of assets exposed to hazard. Challenges exist in the characterization of the earthquake hazard as well as in the determination of the fragilities/vulnerabilities of the physical and social elements exposed to the hazard. The simulation of the spatially correlated fields of ground motion using empirical models of correlation between intensity measures is an important tool for hazard characterization. The uncertainties involved in these elements and especially the correlation in these uncertainties, are important to obtain the bounds of the expected risks and losses. This paper looks at the current practices in regional and urban earthquake risk assessment, discusses current issues and provides illustrative applications from Istanbul and Turkey.