. Compound events (CEs) are multivariate extreme events in which the individual contributing variables may not be extreme themselves, but their joint – dependent – occurrence causes an extreme impact. Conventional univariate statistical analysis cannot give accurate information regarding the multivariate nature of these events. We develop a conceptual model, implemented via pair-copula constructions, which allows for the quantification of the risk associated with compound events in present-day and future climate, as well as the uncertainty estimates around such risk. The model includes predictors, which could represent for instance meteorological processes that provide insight into both the involved physical mechanisms and the temporal variability of compound events. Moreover, this model enables multivariate statistical downscaling of compound events. Downscaling is required to extend the compound events' risk assessment to the past or future climate, where climate models either do not simulate realistic values of the local variables driving the events or do not simulate them at all. Based on the developed model, we study compound floods, i.e. joint storm surge and high river runoff, in Ravenna (Italy). To explicitly quantify the risk, we define the impact of compound floods as a function of sea and river levels. We use meteorological predictors to extend the analysis to the past, and get a more robust risk analysis. We quantify the uncertainties of the risk analysis, observing that they are very large due to the shortness of the available data, though this may also be the case in other studies where they have not been estimated. Ignoring the dependence between sea and river levels would result in an underestimation of risk; in particular, the expected return period of the highest compound flood observed increases from about 20 to 32 years when switching from the dependent to the independent case.

/pdf/multivariate-statistical-modelling-of-compound-events-via-58bha10huw.pdf

Multivariate statistical modelling of compound events via pair-copula constructions: analysis of floods in Ravenna (Italy)

Copula based drought frequency analysis considering the spatio-temporal variability in Southwest China

This paper is of methodological nature, and deals with the foundations of Risk Assessment. Several international guidelines have recently recommended to select appropriate/relevant Hazard Scenarios in order to tame the consequences of (extreme) natural phenomena. In particular, the scenarios should be multivariate, i.e., they should take into account the fact that several variables, generally not independent, may be of interest. In this work, it is shown how a Hazard Scenario can be identified in terms of (i) a specific geometry and (ii) a suitable probability level. Several scenarios, as well as a Structural approach, are presented, and due comparisons are carried out. In addition, it is shown how the Hazard Scenario approach illustrated here is well suited to cope with the notion of Failure Probability, a tool traditionally used for design and risk assessment in engineering practice. All the results outlined throughout the work are based on the Copula Theory, which turns out to be a fundamental theoretical apparatus for doing multivariate risk assessment: formulas for the calculation of the probability of Hazard Scenarios in the general multidimensional case ( d≥2) are derived, and worthy analytical relationships among the probabilities of occurrence of Hazard Scenarios are presented. In addition, the Extreme Value and Archimedean special cases are dealt with, relationships between dependence ordering and scenario levels are studied, and a counter-example concerning Tail Dependence is shown. Suitable indications for the practical application of the techniques outlined in the work are given, and two case studies illustrate the procedures discussed in the paper.

/pdf/a-multivariate-copula-based-framework-for-dealing-with-15oh88alzn.pdf

A multivariate copula-based framework for dealing with hazard scenarios and failure probabilities

Propagation thresholds of meteorological drought for triggering hydrological drought at various levels

Spatial comparability of drought characteristics and related return periods in mainland China over 1961–2013

[1] Droughts, like floods, are extreme expressions of the river flow dynamics. Here, droughts are intended as episodes during which the streamflow is below a given threshold, and are described as multivariate events characterized by two variables: average intensity and duration. In this work, we introduce the new concept of Dynamic Return Period, formulated using the theory of Copulas, and calculated via a Survival Kendall's approach. We show how it can be used (i) to monitor the temporal evolution of a drought event, and (ii) to perform real time assessment. In addition, a randomization strategy is introduced, in order to get rid of repeated measurements, which may adversely affect the statistical analysis of the available data, as well as the calculation of the return periods of interest: a practical example is shown, involving the fit of the drought duration distribution. The case study of the Po river basin (Northern Italy) is used as an illustration.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/wrcr.20551

Multivariate assessment of droughts: Frequency analysis and dynamic return period

Analytical derivation of rain intensity–duration–area–frequency relationships from event maxima

Sul tempo di risposta dei bacini idrografici italiani

Maximum annual flood peaks distribution in non-stationary conditions

ABSTRACT Global Change challenges are now systematically recognized and tackled in a growingly coordinated manner by intergovernmental organizations such as the United Nations. Heterogeneous observing networks provide the founded data sources to assess the Earth environmental status and take sound decisions to achieve a sustainable development. WMO Hydrological Observing System (WHOS) allows to discover and access historical and near real time hydrological observations. WHOS represents the hydrological contribution to the wider WIGOS-WIS system of WMO. It is a digital ecosystems framework contributed by a set of data providers and technical support centers. In this framework, three regional pilots were successfully completed. The WHOS architecture applies the services brokering style, implemented through the Discovery and Access Broker technology. A brokering approach makes a global system of systems possible and sustainable, where the different enterprise systems are enabled to interoperate, despite they implement heterogeneous communication interfaces and data models. In this manuscript, the WHOS brokering solution is detailed by recurring to the definition of a set of transversal viewpoints to describe the important aspects of the complex ecosystem –namely: enterprise, information, computational, engineering, and technological views. Finally, the three regional pilot ecosystems are described as successful cases of WHOS implementation.

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2022.2099591?needAccess=true

Multi-scale hydrological system-of-systems realized through WHOS: the brokering framework

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