Urban growth modelling and social vulnerability assessment for a hazardous Kathmandu Valley

In our rapidly urbanizing world, many hazard-prone regions face significant challenges regarding risk-informed urban development. This study addresses this issue by investigating evolving spatial interactions between natural hazards, ever-increasing urban areas, and social vulnerability in Kathmandu Valley, Nepal. The methodology considers: (1) the characterization of flood hazard and liquefaction susceptibility using pre-existing global models; (2) the simulation of future urban built-up areas using the cellular-automata SLEUTH model; and (3) the assessment of social vulnerability, using a composite index tailored for the case-study area. Results show that built-up areas in Kathmandu Valley will increase to 352 km2 by 2050, effectively doubling the equivalent 2018 figure. The most socially vulnerable villages will account for 29% of built-up areas in 2050, 11% more than current levels. Built-up areas in the 100-year and 1000-year return period floodplains will respectively increase from 38 km2 and 49 km2 today to 83 km2 and 108 km2 in 2050. Additionally, built-up areas in liquefaction-susceptible zones will expand by 13 km2 to 47 km2. This study illustrates how, where, and to which extent risks from natural hazards can evolve in socially vulnerable regions. Ultimately, it emphasizes an urgent need to implement effective policy measures for reducing tomorrow's natural-hazard risks

A Novel People-Centered Approach to Modeling and Decision Making on Future Earthquake Risk

Numerous approaches to earthquake risk modeling and quantification have already been proposed in the literature and/or are well established in practice. However, most of these procedures are designed to focus on risk in the context of current static exposure and vulnerability, and are therefore limited in their ability to support decisions related to the future, as yet partially unbuilt, urban landscape. This paper outlines an end-to-end risk modeling framework that explicitly addresses this specific challenge. The framework is designed to consider the earthquake risks of tomorrow's urban environment, using a simulationbased approach to rigorously capture the uncertainties inherent in future projections of exposure as well as physical and social vulnerability. The framework also advances the state-of-practice in future disaster risk modeling by additionally: (1) providing a harmonized methodology for integrating physical and social impacts of disasters that facilitates flexible characterization of risk metrics beyond physical damage/asset losses; and (2) incorporating a participatory, people-centered approach to riskinformed decision making. It can be used to support decision making on policies related to future urban planning and design, accounting for various stakeholder perspectives on risk

Modelling and quantifying tomorrow's risks from natural hazards

Understanding and modelling future risks from natural hazards is becoming increasingly crucial as the climate changes, human population grows, asset wealth accumulates, and societies become more urbanised and interconnected. This need is recognised by the 2015-2030 Sendai Framework for Disaster Risk Reduction, which emphasises the importance of preparing for the disasters that our world may face tomorrow through strategies/policies that aim to minimise uncontrolled development in hazardous areas. While the vast majority of natural-hazard risk-assessment frameworks have so far focused on static impacts associated with current conditions and/or are influenced by historical context, some authors have sought to provide decision makers with risk-quantification approaches that can be used to cultivate a sustainable future. This Review documents these latter efforts, explicitly examining work that has modelled and quantified the individual components that comprise tomorrow's risk, i.e., future natural hazards affected by climate change, future exposure (e.g., in terms of population, land use, and the built environment), and the evolving physical vulnerabilities of the world's infrastructure. We end with a discussion on the challenges faced by modellers in determining the risks that tomorrow's world may face from natural hazards, and the constraints these place on the decision-making abilities of relevant stakeholders

Advancements in multi-rupture time-dependent seismic hazard modeling, including fault interaction

Several recent earthquake events (e.g., 2008 moment-magnitude (M_{W}) 8.0 Wenchuan, China; 2016 M_{W} 7.8 Kaikōura earthquake, New Zealand; 2019 M_{W} 6.4–7.1 Ridgecrest sequence, USA) have emphasized the need to explicitly account for fault sources in probabilistic seismic hazard analysis (PSHA). Fault-based PSHA currently involves a number of significant but necessary modeling assumptions that mainly relate to fault segmentation, multi-segment event occurrence, long-term fault interaction, and time-dependent/independent earthquake recurrence. Each of these issues is typically investigated in isolation, neglecting the implications of their dependencies. This study offers a review of the current literature on fault-based PSHA, unifying state-of-the-art advances in the field within a single harmonized framework. The framework specifically incorporates some underlying methodologies of the latest Uniform California Earthquake Rupture Forecast (UCERF3; Field et al., 2014), providing a comprehensive means of relaxing fault segmentation, accounting for multi-segment ruptures in a standardized way, interpreting available fault data (e.g., slip rates and paleoseismic data) consistently, and inferring time-dependent probabilities of mainshock occurrence. The proposed framework also explicitly accounts for fault-interaction triggering between major known faults, using the approach outlined by Mignan et al. (2016) and Toda et al. (1998). A simple case study is established to demonstrate the framework's capabilities and limitations, involving a holistic investigation of the aforementioned modeling assumptions' effect on the seismic hazard estimates. The main findings of this study are (1) the ground-motion amplitude estimates can change significantly (for certain return periods) depending on the segmentation assumptions used (e.g., strict segmentation or relaxed segmentation, excluding multi-segment ruptures); (2) considering an ensemble of faults with a time-dependent occurrence model changes the shape of the hazard curve with respect to the time-independent assumption; (3) faults with the largest contribution to the hazard can differ between the time-dependent and time-independent cases; and (4) accounting for fault interaction may change the hazard estimates with respect to those obtained using classic time-dependent analysis (for which fault interaction is neglected). The framework provides a clear means of leveraging paleoseismic campaigns and slip rate data collections to potentially better constrain hazard estimates

Modeling damage accumulation during ground-motion sequences for portfolio seismic loss assessments

Conventional earthquake risk assessments use fragility and vulnerability models that are based on seismic demands from individual (mainshock) ground motions, and implicitly assume that a structure is intact before an earthquake hits. This study develops a suite of more realistic state-dependent seismic fragility and vulnerability models for a wide range of building taxonomies, leveraging state-of-the-art methods to account for dynamic damage accumulation in structures due to multiple earthquake events (i.e., ground-motion sequences). Models are developed for 561 building classes (i.e., structural types) from the Global Earthquake Model's global database of fragility and vulnerability models. Four 2010–2012 Canterbury sequence earthquakes are then used to demonstrate an application of the developed models within a portfolio loss assessment, capturing the time-dependent nature of damage and loss in the vulnerability calculations. The results of this application indicate that accounting for damage accumulation across a series of events can significantly increase expected loss ratios compared to a conventional mainshock-only portfolio risk analysis. This work can help analysts to develop and apply state-dependent fragility and vulnerability models for quantifying the potential impact of damage accumulation in portfolio-scale seismic loss assessments

Impact of time-dependent earthquake recurrence modelling on probabilistic seismic hazard analysis

The (re)insurance industry has traditionally used a memoryless, time-independent (i.e., Poissonian) model for representing earthquake recurrence in seismic loss (risk) calculations. However, time-dependent renewal models, which account for the time elapsed since the last event, are more appropriate for modelling the longterm characteristics of cyclical mainshock occurrences in fault-based seismic hazard assessments. This study first reviews the main features and advantages of some of the most used time-dependent models for mainshock recurrence, and provides a critical discussion on their calibration and possible combination. A simple casestudy fault is used to quantify the changes in seismic hazard estimates resulting from the use of time-dependent Brownian Passage-Time (BPT) models instead of the conventional Poisson process. The considered fault is the Ohariu Fault in New Zealand, which is one of the major sources of earthquake hazard for the city of Wellington. BPT model parameters are calibrated using the maximum likelihood estimation (MLE) method together with paleoseismic data published in the literature. Results from this study show that the use of a timedependent BPT model can lead to a significant over- or under-estimation of the seismic hazard compared to the time-independent Poisson model, depending on the ratio between the time elapsed since the last event and the mean recurrence time of the fault. The simple single-fault case study also highlights the potential need for a combination of time-dependent models in actual earthquake risk models, since the single BPT model produces unrealistically low seismic hazard estimates for time periods in the immediate aftermath of an earthquake occurrence

A simulation‐based framework for earthquake risk‐informed and people‐centred decision making on future urban planning

Numerous approaches to earthquake risk modelling and quantification have already been proposed in the literature and/or are well established in practice. However, most of these procedures are designed to focus on risk in the context of current static exposure and vulnerability, and are therefore limited in their ability to support decisions related to the future, as yet partially unbuilt, urban landscape. We propose an end-to-end risk modelling framework that explicitly addresses this specific challenge. The framework is designed to consider the earthquake (ground-shaking) risks of tomorrow’s urban environment, using a simulation-based approach to rigorously capture the uncertainties inherent in future projections of exposure as well as physical and social vulnerability. The framework also advances the state-of-practice in future disaster risk modelling by additionally: (1) providing a harmonised methodology for integrating physical and social impacts of disasters that facilitates flexible characterisation of risk metrics beyond physical damage/asset losses; and (2) incorporating a participatory, people-centred approach to risk-informed decision making. The framework is showcased using the physical and social environment of an expanding synthetic city. This example application demonstrates how the framework may be used to make policy decisions related to future urban areas, based on multiple, uncertain risk drivers

A New Procedure for Evaluating Ground-Motion Models, with Application to Hydraulic-Fracture-Induced Seismicity in the United Kingdom

An essential component of seismic hazard analysis is the prediction of ground shaking (and its uncertainty), using ground-motion models (GMMs). This article proposes a new method to evaluate (i.e., rank) the suitability of GMMs for modeling ground motions in a given region. The method leverages a statistical tool from sensitivity analysis to quantitatively compare predictions of a GMM with underlying observations. We demonstrate the performance of the proposed method relative to several other popular GMM ranking procedures and highlight its advantages, which include its intuitive scoring system and its ability to account for the hierarchical structure of GMMs. We use the proposed method to evaluate the applicability of several GMMs for modeling ground motions from induced earthquakes due to U.K. shale gas development. The data consist of 195 recordings at hypocentral distances (R) less than 10 km for 29 events with local magnitude (ML) greater than 0 that relate to 2018/2019 hydraulic-fracture operations at the Preston New Road shale gas site in Lancashire and 192 R<10  km recordings for 48 ML>0 events induced—within the same geologic formation—by coal mining near New Ollerton, North Nottinghamshire. We examine: (1) the Akkar, Sandikkaya, and Bommer (2014) models for European seismicity; (2) the Douglas et al. (2013) model for geothermal-induced seismicity; and (3) the Atkinson (2015) model for central and eastern North America induced seismicity. We find the Douglas et al. (2013) model to be the most suitable for almost all of the considered ground-motion intensity measures. We modify this model by recomputing its coefficients in line with the observed data, to further improve its accuracy for future analyses of the seismic hazard of interest. This study both advances the state of the art in GMM evaluation and enhances understanding of the seismic hazard related to U.K. shale gas development

A Review of the Technical and Socio-Organizational Components of Earthquake Early Warning Systems

Every year, natural hazards affect millions of people around the world, causing significant economic and life losses. The rapid progress of technology and advances in understanding of the highly complex physical phenomena related to various natural hazards have promoted the development of new disaster-mitigation tools, such as earthquake early warning (EEW) systems. However, there is a general lack of integration between the multi- and cross-disciplinary elements of EEW, limiting its effectiveness and applications for end users. This paper reviews the current state-of-the-art in EEW, exploring both the technical components (i.e., seismological and engineering) as well as the socio-organizational components (i.e., social science, policy, and management) of EEW systems. This includes a discussion of specific evidence from case studies of Italy, United States’ West Coast, Japan, and Mexico, where EEW systems have reached varying levels of maturity. Our aim is to highlight necessary improvements for increasing the effectiveness of the technical aspects of EEW in terms of their implications on operational, political/legal, social, behavioral, and organizational drivers. Our analysis suggests open areas for research, associated with: 1) the information that needs to be included in EEW alerts to implement successful mitigation actions at both individual and organizational levels; 2) the need for response training to the community by official bodies, such as civil protection; 3) existing gaps in the attribution of accountability and development of liability policies involving EEW implementation; 4) the potential for EEW to increase seismic resilience of critical infrastructure and lifelines; 5) the need for strong organizational links with first responders and official EEW bodies; and 6) the lack of engineering-related (i.e., risk and resilience) metrics currently used to support decision making related to the triggering of alerts by various end users

Comparing the Performance of Regional Earthquake Early Warning Algorithms in Europe

Several earthquake early warning (EEW) algorithms have been developed worldwide for rapidly estimating real-time information (i.e., location, magnitude, ground shaking, and/or potential consequences) about ongoing seismic events. This study quantitatively compares the operational performance of two popular regional EEW algorithms for European conditions of seismicity and network configurations. We specifically test PRobabilistic and Evolutionary early warning SysTem (PRESTo) and the implementation of the Virtual Seismologist magnitude component within SeisComP, VS(SC), which we use jointly with the SeisComP scanloc module for locating events. We first evaluate the timeliness and accuracy of the location and magnitude estimates computed by both algorithms in real-time simulation mode, accounting for the continuous streaming of data and effective processing times. Then, we focus on the alert-triggering (decision-making) phase of EEW and investigate both algorithms’ ability to yield accurate ground-motion predictions at the various temporal instances that provide a range of warning times at target sites. We find that the two algorithms show comparable performances in terms of source parameters. In addition, PRESTo produces better rapid estimates of ground motion (i.e., those that facilitate the largest lead times); therefore, we conclude that PRESTo may have a greater risk-mitigation potential than VS(SC) in general. However, VS(SC) is the optimal choice of EEW algorithm if shorter warning times are permissible. The findings of this study can be used to inform current and future implementations of EEW systems in Europe