Globally and yearly, individual hazards and hazard interrelations have the potential to result in socio-economic losses. Here, in this critical review, we use grey- and peer-review literature to ...identify and compare current research available for the quantification of hazard interrelations, focussing on 14 different natural hazards. We first provide a historical context for quantitative single hazard and multi-hazard assessment. We then construct a literature database with 146 references related to multi-hazard interrelations. We use our literature database to identify trends for hazard interrelation and multi-hazard and from these group hazard interrelations into five types: triggering, change condition, compound, independence and mutually exclusive. Our critical review identifies 19 different modelling methods to quantify natural hazard interrelationships which we cluster into three broad modelling approaches: stochastic, empirical, and mechanistic. We then synthesize results of our classification of quantification methods for hazard interrelationships and using two matrices illustrate this in practice for 24 different interrelations between 14 natural hazards, one for cascading hazards (temporal order in the multi-hazard event) and one for compound hazards (two or more hazards acting together). Finally, we provide examples of applications for each the three quantitative modelling approaches defined. We believe that this review will lead to a better understanding of quantification methodologies for hazard interrelations between different sub-disciplines that focus on natural hazards, thus aiding cross-disciplinary approaches for better understanding potential risk related to multi-hazard events.
Modelling multiple hazard interrelations remains a challenge for practitioners. This article primarily focuses on the interrelations between pairs of hazards. The efficacy of six distinct bivariate ...extreme models is evaluated through their fitting capabilities to 60 synthetic datasets. The properties of the synthetic datasets (marginal distributions, tail dependence structure) are chosen to match bivariate time series of environmental variables. The six models are copulas (one non-parametric, one semi-parametric, four parametric). We build 60 distinct synthetic datasets based on different parameters of log-normal margins and two different copulas. The systematic framework developed contrasts the model strengths (model flexibility) and weaknesses (poorer fits to the data). We find that no one model fits our synthetic data for all parameters but rather a range of models depending on the characteristics of the data. To highlight the benefits of the systematic modelling framework developed, we consider the following environmental data: (i) daily precipitation and maximum wind gusts for 1971 to 2018 in London, UK, and (ii) daily mean temperature and wildfire numbers for 1980 to 2005 in Porto District, Portugal. In both cases there is good agreement in the estimation of bivariate return periods between models selected from the systematic framework developed in this study. Within this framework, we have explored a way to model multi-hazard events and identify the most efficient models for a given set of synthetic data and hazard sets.
In low-lying coastal regions, flooding arises from oceanographic (storm
surges plus tides and/or waves), fluvial (increased river discharge), and/or
pluvial (direct surface run-off) sources. The ...adverse consequences of a flood
can be disproportionately large when these different sources occur
concurrently or in close succession, a phenomenon that is known as
“compound flooding”. In this paper, we assess the potential for compound
flooding arising from the joint occurrence of high storm surge and high
river discharge around the coast of the UK. We hypothesise that there will be
spatial variation in compound flood frequency, with some coastal regions
experiencing a greater dependency between the two flooding sources than
others. We map the dependence between high skew surges and high river
discharge, considering 326 river stations linked to 33 tide gauge sites. We
find that the joint occurrence of high skew surges and high river discharge
occurs more frequently during the study period (15–50 years) at sites on the
south-western and western coasts of the UK (between three and six joint events per
decade) compared to sites along the eastern coast (between zero and one joint
events per decade). Second, we investigate the meteorological conditions
that drive compound and non-compound events across the UK. We show, for the
first time, that spatial variability in the dependence and number of joint
occurrences of high skew surges and high river discharge is driven by
meteorological differences in storm characteristics. On the western coast of
the UK, the storms that generate high skew surges and high river discharge
are typically similar in characteristics and track across the UK on
comparable pathways. In contrast, on the eastern coast, the storms that
typically generate high skew surges are mostly distinct from the types of
storms that tend to generate high river discharge. Third, we briefly examine
how the phase and strength of dependence between high skew surge and high
river discharge is influenced by the characteristics (i.e. flashiness, size,
and elevation gradient) of the corresponding river catchments. We find that high
skew surges tend to occur more frequently with high river discharge at
catchments with a lower base flow index, smaller catchment area, and steeper
elevation gradient. In catchments with a high base flow index, large
catchment area, and shallow elevation gradient, the peak river flow tends to
occur several days after the high skew surge. The previous lack of
consideration of compound flooding means that flood risk has likely been
underestimated around UK coasts, particularly along the south-western and western
coasts. It is crucial that this be addressed in future assessments of flood
risk and flood management approaches.
Compound hazards refer to two or more different natural hazards occurring over the same time period and spatial area. Compound hazards can operate on different spatial and temporal scales than their ...component single hazards. This article proposes a definition of compound hazards in space and time, presents a methodology for the spatiotemporal identification of compound hazards (SI–CH), and compiles two compound-hazard-related open-access databases for extreme precipitation and wind in Great Britain over a 40-year period. The SI–CH methodology is applied to hourly precipitation and wind gust values for 1979–2019 from climate reanalysis (ERA5) within a region including Great Britain and the British Channel. Extreme values (above the 99 % quantile) of precipitation and wind gust are clustered with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, creating clusters for precipitation and wind
gusts. Compound hazard clusters that correspond to the spatial overlap of
single hazard clusters during the aggregated duration of the two hazards are then identified. We compile these clusters into a detailed and comprehensive ERA5 Hazard Clusters Database 1979–2019 (given in the Supplement), which consists of 18 086 precipitation clusters, 6190 wind clusters, and 4555 compound hazard clusters for 1979–2019 in Great Britain. The methodology's ability to identify extreme precipitation and wind events is assessed with a catalogue of 157 significant events (96 extreme precipitation and 61 extreme wind events) in Great Britain over the period 1979–2019 (also given in the Supplement). We find good agreement between the SI–CH outputs and the catalogue with an overall hit rate (ratio between the number of joint events and the total number of events) of 93.7 %. The spatial variation of hazard intensity within wind, precipitation, and compound hazard clusters is then visualised and analysed. The study finds that the SI–CH approach (given as R code in the Supplement) can accurately identify single and compound hazard events and represent spatial and temporal properties of these events. We find that compound wind and precipitation extremes, despite occurring on smaller scales than single extremes, can occur on large scales in Great Britain with a decreasing spatial scale when the combined intensity of the hazards increases.
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