Disaster resilience assessment based on the spatial and temporal aggregation effects of earthquake-induced hazards

Structural challenges for seismic stability of buildings in hilly areas

Buildings on hills behave dynamically, very different from buildings on flatlands. Due to irregularity in horizontal and vertical planes, they inhibit non-uniform mass and stiffness distribution and are subjected to torsional forces. Studies in various Indian cities in hilly terrains have highlighted serious concerns about existing construction practices. Lack of adequate planning and design has resulted in haphazard development in hilly regions. This state-of-the-art review investigates the factors that influence the structural performance of buildings on slopes while explaining reasons that have caused enormous damages and even collapse of hill buildings in the recent earthquake events. The work discusses building configurations, comparison of various vital building regulations, the major problems encountered in building stocks and associated structural deficiencies on hill slopes. The significance of intensification of earthquake-related losses due to soil amplification has been well documented in the past. Insights from experimental and numerical studies focusing on impacts of topographical and geological factors on damage amplification of hillside buildings are fetched, the results of which are in good corroboration with the findings of post-earthquake surveys and reviews. This study establishes that a higher slope gradient necessitates more slope cutting than a lower slope gradient to get the same building footprint, and many times, this value exceeds the permissible height of slope cutting given in existing building byelaws. Such excessive slope cutting makes the slope weak and unstable. Recommendations and solutions to help enhance structural resilience, reduce disproportionate damages and mitigate failure of hill buildings have been delineated.

Analysis of the formation mechanism of debris flows after earthquakes – A case study of the Legugou debris flow

By means of the Graphic Method, Gray Correlation Method and Frequency Method, the total amount of loose solid materials, the amount of loose solid materials per unit area in the source area, and the risk degree and critical rainfall of the study area are determined, respectively. On the basis of the calculation results, the total amount of loose solid materials is 57.2 × 104 m3, the amount of loose solid materials per unit area is 0.13 m3/m2 (greater than 0.1 m3/m2), which better meets the initiation conditions for dilute debris flow. The Hazard Evaluation Model of Debris Flow in earthquake areas is established by the gray correlation method and the hazard index H = 0.725 is determined. According to the hazard classification standards for debris flows in earthquake areas, the debris flow in Lecugou was moderate after the earthquake. The critical rainfall value of 1H, calculated by the frequency method, ranged from 17.45 to 22.21 mm (Re = 25 mm) and 8.17 to 13.01 mm (Re = 50 mm). The critical rainfall value at 10 min ranged from 6.23 to 8.44 mm (Re = 25 mm) and 2.92 to 5.13 mm (Re = 50 mm), respectively. The maximum rainfall intensity of 45.5 mm/h was reached between 10:00 and 11:00 on July 29, 2019 and the cumulative rainfall reached 144 mm, far exceeding the critical rainfall of Legugou. Under the influence of earthquakes and human activities, the loose solid source amount and loose solid source amount per unit area increased greatly, and the critical rainfall for debris flow after earthquakes decreased sharply, which induced debris flows under the influence of heavy rainfall. This research will be helpful for the establishment of monitoring and early warning systems based on artificial intelligence methods, and can greatly improve the effectiveness of disaster prevention and mitigation.

The role of infrastructure, socio-economic development, and food security to mitigate the loss of natural disasters

This study shows the impact of risk (hazard, exposure, and vulnerability) and resilience (infrastructure, information and communication technology, institutional quality, food security, women empowerment, economic performance, human capital, emergency workforce, and social capital) indicators on losses due to natural disasters in 24 high-income, 24 upper-middle-income, 30 lower-middle-income, and 12 low-income countries from 1995 to 2019. It develops a new disaster risk index and disaster resilience index using standard index-making procedure (indicators selection, winsorization, normalization, aggregation). The generalized additive modeling was used to explore the non-linear relationship between response and explanatory variables. There exists a positive link between damage due to natural disasters and hazard index (all panels) and exposure index in high-income countries. The decrease in damage due to natural disasters was observed due to an increase in infrastructure (upper-middle-, lower-middle-, and low-income countries), information and communication technology (high-income countries), institutional quality (high-income countries), food security (high- and upper-middle-income countries), women empowerment (lower-middle-income countries), economic performance (high- and low-income countries), human capital (low-income countries), and emergency workforce (upper-middle and lower-middle-income countries). The governments should enhance disaster resilience through Sendai Framework, having seven targets and four priority areas to increase disaster resilience.

Spatiotemporal characteristics and influencing factors of urban resilience efficiency in the Yangtze River Economic Belt, China

Urban resilience efficiency is an important indicator to explore the relationship between resource consumption and urban resilience, shedding new light on the study of urban sustainable development. Based on the panel data of 2008, 2012, and 2017, this paper makes a spatiotemporal assessment on the urban resilience efficiency of 126 cities in the Yangtze River Economic Belt (YREB) in China by applying an entropy weight-TOPSIS method and a slack-based measure (SBM) model. Combined with the analysis of a geographically weighted regression model (GWR), the influencing factors on resilience efficiency are also investigated. The results show that both the resource consumption index (RC, inputs) and the urban resilience index (UR, outputs) presented a steady upward trend, and their spatial distribution characteristics were similar, showing a gradual decrease from the eastern coastal cities to the central and western inland cities. Derived from inputs and outputs, the mean values of resilience efficiency index (RE) in three periods were 0.3149, 0.2906, and 0.1625, respectively, revealing that there had been a noticeable decline. Spatially, its spatial distribution has evolved from a relatively balanced pattern to an unbalanced one, showing a gradual decrease from west to east. The results of the GWR model analysis indicate that the total electricity consumption and area of construction land had a considerable correlation with the overall urban resilience of the YREB. Furthermore, total quantity of water supply and science and technology (S&T) expenditure continued to be the main driving factors on urban resilience of the upstream cities. The midstream regions mainly depended on the scale of construction land, and the influencing factors are relatively single. The influencing factors in the downstream areas have changed from dominance of resources and capital factors to the single dominance of resource factors, and total electricity consumption had a strong explanatory power. Based on these findings, we had put forward the overall and local regional policy implications.