scholarly journals Modeling the Characteristics of Unhealthy Air Pollution Events: A Copula Approach

2021 ◽  
Vol 18 (16) ◽  
pp. 8751
Author(s):  
Nurulkamal Masseran
Keyword(s):  
Air Pollution ◽  
Return Period ◽  
Copula Model ◽  
Return Periods ◽  
Statistical Tool ◽  
Long Tail ◽  
Kendall’S Τ ◽  
Copula Approach ◽  
Pollution Events

This study proposes the concept of duration (D) and severity (S) measures, which were derived from unhealthy air pollution events. In parallel with that, the application of a copula model is proposed to evaluate unhealthy air pollution events with respect to their duration and severity characteristics. The bivariate criteria represented by duration and severity indicate their structural dependency, long-tail, and non-identically marginal distributions. A copula approach can provide a good statistical tool to deal with these issues and enable the extraction of valuable information from air pollution data. Based on the copula model, several statistical measurements are proposed for describing the characteristics of unhealthy air pollution events, including the Kendall’s τ correlation of the copula, the conditional probability of air pollution severity based on a given duration, the joint OR/AND return period, and the conditional D|S and conditional S|D return periods. A case study based on air pollution data indices was conducted in Klang, Malaysia. The results indicate that a copula approach is beneficial for deriving valuable information for planning and mitigating the risks of unhealthy air pollution events.

scholarly journals Global flood hazard map and exposed GDP comparison: a China case study

2020 ◽  
Author(s):  
Jerom P. M. Aerts ◽  
Steffi Uhlemann-Elmer ◽  
Dirk Eilander ◽  
Philip J. Ward
Keyword(s):  
Return Period ◽  
Flood Hazard ◽  
Regional Scale ◽  
Flood Protection ◽  
Economic Losses ◽  
Return Periods ◽  
Hazard Maps ◽  
High Exposure ◽  
Pluvial Flooding

Abstract. Floods are among the most frequent and damaging natural hazard events in the world. In 2016, economic losses from flooding amounted to $56 bn globally, of which $20 bn occurred in China (Munich Re, 2017). National or regional scale mapping of flood hazard is at present providing an inconsistent and incomplete picture of floods. Over the past decade global flood hazard models have been developed and continuously improved. There is now a significant demand for testing of the global hazard maps generated by these models in order to understand their applicability for international risk reduction strategies and for reinsurance portfolio risk assessments using catastrophe models. We expand on existing methods for comparing global hazard maps and analyse 8 global flood models (GFMs) that represent the current state of the global flood modelling community. We apply our comparison to China as a case study and, for the first time, we include industry models, pluvial flooding, and flood protection standards in the analysis. We find substantial variability between the flood hazard maps in modelled inundated area and exposed GDP across multiple return periods (ranging from 5 to 1500 years) and in expected annual exposed GDP. For example, for the 100 year return period undefended (assuming no flood protection) hazard maps the percentage of total affected GDP of China ranges between 4.4 % and 10.5 % for fluvial floods. For the majority of the GFMs we see only a small increase in inundated area or exposed GDP for high return period undefended hazard maps compared to low return periods, highlighting major limitations in the models’ resolution and their output. The inclusion of industry models which currently model flooding at higher spatial resolution, and which additionally include pluvial flooding, strongly improves the comparison and provides important new benchmarks. Pluvial flooding can increase the expected annual exposed GDP by as much as 1.3 % points. Our study strongly highlights the importance of flood defenses for a realistic risk assessment in countries like China that are characterized by high concentrations of exposure. Even an incomplete (1.74 % of area of China) but locally detailed layer of structural defenses in high exposure areas reduces the expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.

scholarly journals Estimation of return period and its uncertainty for the recent 2013–2015 drought in the Han River watershed in South Korea

2018 ◽  
Vol 49 (5) ◽  
pp. 1313-1329 ◽  
Author(s):  
Jin-Young Kim ◽  
Byung-Jin So ◽  
Hyun-Han Kwon ◽  
Tae-Woong Kim ◽  
Joo-Heon Lee
Keyword(s):  
South Korea ◽  
Return Period ◽  
Drought Severity ◽  
Copula Model ◽  
Return Periods ◽  
Drought Duration ◽  
River Watershed ◽  
Han River ◽  
Joint Return ◽  
Very High

Abstract This study introduces an approach to copula model parameter estimation within a Bayesian framework. The model is applied to estimate the return periods of the 2013–2015 drought in the Han River watershed (South Korea) as observed through a network of 18 rainfall stations in the watershed. For the univariate return periods, some of the 2013–2015 drought durations (i.e., 9–24 months) have return periods of around 30 years while the drought severities (which range from about 400 to 1,400 mm) at certain stations might be regarded as extreme events with return periods in the hundreds of years. The recent drought is extraordinary at many stations in the Han River watershed although the associated uncertainty is quite large (e.g., for the Seoul station, a range of about 180 to 2,250 years). Moreover, it is clearly seen that the unprecedented joint return periods of the 2013–2015 drought at many stations are consistent with the very high drought severity. The joint return period of the drought duration and severity is above 100 years for many of the stations and upwards of 1,000 years for a few stations.

scholarly journals Assessment and comparison of extreme sea levels and waves during the 2013/2014 storm season in two UK coastal regions

2015 ◽  
Vol 3 (4) ◽  
pp. 2665-2708 ◽  
Author(s):  
M. P. Wadey ◽  
J. M. Brown ◽  
I. D. Haigh ◽  
T. Dolphin ◽  
P. Wisse
Keyword(s):  
Sea Level ◽  
Return Period ◽  
Data Sets ◽  
Return Periods ◽  
National Scale ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Study Sites

Abstract. The extreme sea levels and waves experienced around the UK's coast during the 2013/2014 winter caused extensive coastal flooding and damage. In such circumstances, coastal managers seek to place such extremes in relation to the anticipated standards of flood protection, and the long-term recovery of the natural system. In this context, return periods are often used as a form of guidance. We therefore provide these levels for the winter storms, as well as discussing their application to the given data sets and case studies (two UK case study sites: Sefton, northwest England; and Suffolk, east England). We use tide gauge records and wave buoy data to compare the 2013/2014 storms with return periods from a national dataset, and also generate joint probabilities of sea level and waves, incorporating the recent events. The UK was hit at a national scale by the 2013/2014 storms, although the return periods differ with location. We also note that the 2013/2014 high water and waves were extreme due to the number of events, as well as the extremity of the 5 December 2013 "Xaver" storm, which had a very high return period at both case study sites. Our return period analysis shows that the national scale impact of this event is due to its coincidence with spring high tide at multiple locations as the tide and storm propagated across the continental shelf. Given that this event is such an outlier in the joint probability analyses of these observed data sets, and that the season saw several events in close succession, coastal defences appear to have provided a good level of protection. This type of assessment should be recorded alongside details of defence performance and upgrade, with other variables (e.g. river levels at estuarine locations) included and appropriate offsetting for linear trends (e.g. mean sea level rise) so that the storm-driven component of coastal flood events can be determined. Local offsetting of the mean trends in sea level allows long-term comparison of storm severity and also enables an assessment of how sea level rise is influencing return levels over time, which is important when considering long-term coastal resilience in strategic management plans.

scholarly journals Multivariate return periods of sea storms for coastal erosion risk assessment

2012 ◽  
Vol 12 (8) ◽  
pp. 2699-2708 ◽  
Author(s):  
S. Corbella ◽  
D. D. Stretch
Keyword(s):  
Return Period ◽  
Coastal Erosion ◽  
Design Method ◽  
Return Periods ◽  
Current Form ◽  
Erosion Risk ◽  
Storm Characteristics ◽  
Relationship Of ◽  
The Relationship

Abstract. The erosion of a beach depends on various storm characteristics. Ideally, the risk associated with a storm would be described by a single multivariate return period that is also representative of the erosion risk, i.e. a 100 yr multivariate storm return period would cause a 100 yr erosion return period. Unfortunately, a specific probability level may be associated with numerous combinations of storm characteristics. These combinations, despite having the same multivariate probability, may cause very different erosion outcomes. This paper explores this ambiguity problem in the context of copula based multivariate return periods and using a case study at Durban on the east coast of South Africa. Simulations were used to correlate multivariate return periods of historical events to return periods of estimated storm induced erosion volumes. In addition, the relationship of the most-likely design event (Salvadori et al., 2011) to coastal erosion was investigated. It was found that the multivariate return periods for wave height and duration had the highest correlation to erosion return periods. The most-likely design event was found to be an inadequate design method in its current form. We explore the inclusion of conditions based on the physical realizability of wave events and the use of multivariate linear regression to relate storm parameters to erosion computed from a process based model. Establishing a link between storm statistics and erosion consequences can resolve the ambiguity between multivariate storm return periods and associated erosion return periods.

scholarly journals Drivers of severe air pollution events in a deep valley during wintertime: A case study from the Arve river valley, France

2021 ◽  
Vol 247 ◽  
pp. 118030
Author(s):  
Julian Quimbayo-Duarte ◽  
Charles Chemel ◽  
Chantal Staquet ◽  
Florence Troude ◽  
Gabriele Arduini
Keyword(s):  
Air Pollution ◽  
River Valley ◽  
Pollution Events

scholarly journals Statistical Estimates of PMP Values

1994 ◽  
Vol 25 (4) ◽  
pp. 301-312 ◽  
Author(s):  
Jónas Elíasson
Keyword(s):  
Statistical Methods ◽  
Return Period ◽  
The Other ◽  
Statistical Distributions ◽  
Return Periods ◽  
Statistical Estimates ◽  
High Return ◽  
Bounded Data ◽  
Limiting Value

The article discusses two statistical methods to estimate PMP values, the Hershfield and the NERC methods. Neither method offers any explanation why the PMP values can be calculated by the use of unbounded statistical distributions, but both methods include the use of envelope curves that are not independent of the region. Bounded data that fits an unbounded distribution must deviate from the distribution for high return periods and tend to a limiting value, and then there exists, a limiting reduced variate that can be used to find the PMP value. When the distribution is EV1, the limiting reduced variate can be defined by a mapping transformation, or by cutting off the distribution. It is shown that when Hershfield or NERC methods are used, the limiting reduced variate is included in the PMP values and can be separated from regional parameters. It is suggested that the limiting reduced variate, that depends solely on return period, may more easily be transferred between regions than the other parameters. This may be a great help in finding PMP values in regions where observations are not extensive enough to define limiting return periods with necessary certainty. A case study with data from Iceland demonstrates, that using the limiting reduced variate, similarities emerge in the Icelandic data and the NERC PMP that justify the acceptance of the NERC method.

scholarly journals On the return period and design in a multivariate framework

2011 ◽  
Vol 15 (11) ◽  
pp. 3293-3305 ◽  
Author(s):  
G. Salvadori ◽  
C. De Michele ◽  
F. Durante
Keyword(s):  
Return Period ◽  
Theoretical Framework ◽  
Difficult Problem ◽  
Return Periods ◽  
Practical Applications ◽  
New Concepts

Abstract. Calculating return periods and design quantiles in a multivariate environment is a difficult problem: this paper tries to make the issue clear. First, we outline a possible way to introduce a consistent theoretical framework for the calculation of the return period in a multi-dimensional environment, based on Copulas and the Kendall's measure. Secondly, we introduce several approaches for the identification of suitable design events: these latter quantities are of utmost importance in practical applications, but their calculation is yet limited, due to the lack of an adequate theoretical environment where to embed the problem. Throughout the paper, a case study involving the behavior of a dam is used to illustrate the new concepts outlined in this work.

scholarly journals Multivariate design via Copulas

2011 ◽  
Vol 8 (3) ◽  
pp. 5523-5558 ◽  
Author(s):  
G. Salvadori ◽  
C. De Michele ◽  
F. Durante
Keyword(s):  
Return Period ◽  
Difficult Problem ◽  
Total Order ◽  
Return Periods ◽  
Euclidean Spaces ◽  
Practical Applications ◽  
Critical Design ◽  
New Concepts ◽  
Multivariate Quantile

Abstract. Calculating return periods and design quantiles in a multivariate framework is a difficult problem: essentially, this is due to the lack of a natural total order in multi-dimensional Euclidean spaces. This paper tries to make the issue clear. First, we outline a possible way to introduce a coherent notion of multivariate total order, and discuss its consequences on the calculation of multivariate return period: in particular, the latter is based on Copulas and the Kendall's measure, which provides a consistent notion of multivariate quantile. Secondly, we introduce several approaches for the identification of critical design events: these latter quantities are of utmost importance in practical applications, but their calculation is yet limited, due to the lack of a suitable theoretical setting where to embed the problem. Throughout the paper, a case study involving the behavior of a dam is used to illustrate the new concepts outlined in this work.

scholarly journals Mixed POT-BM Approach for Modeling Unhealthy Air Pollution Events

2021 ◽  
Vol 18 (13) ◽  
pp. 6754
Author(s):  
Nurulkamal Masseran ◽  
Muhammad Aslam Mohd Safari
Keyword(s):  
Air Pollution ◽  
Extreme Event ◽  
Data Selection ◽  
Peak Over Threshold ◽  
Data Points ◽  
Block Maxima ◽  
Event Based ◽  
Pollution Events ◽  
Pot Technique

This article proposes a novel data selection technique called the mixed peak-over-threshold–block-maxima (POT-BM) approach for modeling unhealthy air pollution events. The POT technique is employed to obtain a group of blocks containing data points satisfying extreme-event criteria that are greater than a particular threshold u. The selected groups are defined as POT blocks. In parallel with that, a declustering technique is used to overcome the problem of dependency behaviors that occurs among adjacent POT blocks. Finally, the BM concept is integrated to determine the maximum data points for each POT block. Results show that the extreme data points determined by the mixed POT-BM approach satisfy the independent properties of extreme events, with satisfactory fitted model precision results. Overall, this study concludes that the mixed POT-BM approach provides a balanced tradeoff between bias and variance in the statistical modeling of extreme-value events. A case study was conducted by modeling an extreme event based on unhealthy air pollution events with a threshold u > 100 in Klang, Malaysia.

Sign in / Sign up

Export Citation Format

Share Document