Analysis of extreme hydrological Events on THE danube using the Peak Over Threshold method

Bačová-Mitková, Veronika; Onderka, Milan

doi:10.2478/v10098-010-0009-x

Cited by 51 publications

(38 citation statements)

References 24 publications

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“…While some studies only provide a qualitative description of resulting parameter estimates and estimated return levels for both methods (Jarušková and Hanek, 2006), more formal assessment approaches are based on the asymptotic variance of the T -year event estimator (Cunnane, 1973) or on various goodness-of-fit tests and model performance metrics (Madsen et al, 1997a, b;Bezak et al, 2014). Controversial conclusions have been drawn.…”

Section: Introductionmentioning

confidence: 99%

“…Regarding the threshold excess method, threshold exceedances on consecutive days will likely violate the assumption of independence. Dependent values in the threshold excess series are eliminated by a declustering procedure that consists in removing threshold exceedances within the autocorrelation length on both sides of the local maxima (Jarušková and Hanek, 2006). Based on sensitivity analysis an autocorrelation window of 5 days was chosen for the three temperature indicators, while a window of 3 days was chosen for accumulated daily precipitation.…”

Section: Dealing With Non-stationarity and Dependencymentioning

confidence: 99%

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Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Schlögl

Laaha

2017

Nat. Hazards Earth Syst. Sci.

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Abstract. The assessment of road infrastructure exposure to extreme weather events is of major importance for scientists and practitioners alike. In this study, we compare the different extreme value approaches and fitting methods with respect to their value for assessing the exposure of transport networks to extreme precipitation and temperature impacts. Based on an Austrian data set from 25 meteorological stations representing diverse meteorological conditions, we assess the added value of partial duration series (PDS) over the standardly used annual maxima series (AMS) in order to give recommendations for performing extreme value statistics of meteorological hazards. Results show the merits of the robust L-moment estimation, which yielded better results than maximum likelihood estimation in 62 % of all cases. At the same time, results question the general assumption of the threshold excess approach (employing PDS) being superior to the block maxima approach (employing AMS) due to information gain. For low return periods (non-extreme events) the PDS approach tends to overestimate return levels as compared to the AMS approach, whereas an opposite behavior was found for high return levels (extreme events). In extreme cases, an inappropriate threshold was shown to lead to considerable biases that may outperform the possible gain of information from including additional extreme events by far. This effect was visible from neither the square-root criterion nor standardly used graphical diagnosis (mean residual life plot) but rather from a direct comparison of AMS and PDS in combined quantile plots. We therefore recommend performing AMS and PDS approaches simultaneously in order to select the best-suited approach. This will make the analyses more robust, not only in cases where threshold selection and dependency introduces biases to the PDS approach but also in cases where the AMS contains non-extreme events that may introduce similar biases. For assessing the performance of extreme events we recommend the use of conditional performance measures that focus on rare events only in addition to standardly used unconditional indicators. The findings of the study directly address road and traffic management but can be transferred to a range of other environmental variables including meteorological and hydrological quantities.

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Section: Introductionmentioning

confidence: 99%

Section: Dealing With Non-stationarity and Dependencymentioning

confidence: 99%

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Schlögl

Laaha

2017

Nat. Hazards Earth Syst. Sci.

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“…However, there are numerous applications of the POT approach which do not consider timedependent parameters (e.g. Madsen et al, 1997;Claps and Laio, 2003;Bacova-Mitkova and Onderka, 2010;Fruh et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Effects of disregarding seasonality on the distribution of hydrological extremes

Allamano

Laio

Claps

2011

Hydrol. Earth Syst. Sci.

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Abstract. This paper deals with the seasonality of hydroclimatic extremes and with the problem of accounting for their non-homogeneous character in determining the design value. To this aim we devise a simple stochastic experiment in which extremes are produced by a non-homogeneous extreme value generation process. The design values are estimated in closed analytical form both in a peak over threshold framework and by using the standard annual maxima approach. In this completely controlled world of generated hydrological extremes, a statistical measure of the error associated to the adoption of a homogeneous model is introduced. The sensitivity of this measure, named return period ratio, to the typology and strength of seasonality is investigated. We find that neglecting seasonality induces a downward bias in design value estimators. The magnitude of the bias may be large when the peak over threshold approach is adopted, while the return period distortion is limited when the annual maxima are considered. An application to rainfall data from a 30 000 km 2 region located in North-Western Italy is presented to better clarify the effects of disregarding seasonality in a real case.

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“…Research into event definitions has primarily focused on single site analysis (Bacova-Mitkova and Onderka, 2010;Villarini, 2015, 2016;Kahana et al, 2002). However, as flood events are spatially complex, they often impact many locations, limiting the use of single-site definitions for reinsurance contract definitions.…”

Section: Introductionmentioning

confidence: 99%

“…Many authors have shifted toward a data-driven approach using the peak-over-threshold (POT) analysis to examine changes in flood event frequency (Mallakpour and Villarini, 2016;Bacova-Mitkova and Onderka, 2010), as well seasonality (Black and Werritty, 1997). A data-driven approach allows for the definition of an event to encompass a variety of basin characteristics.…”

Section: Introductionmentioning

confidence: 99%

Defining and analyzing the frequency and severity of flood events to improve risk management from a reinsurance standpoint

Morrill

Becker²

2018

Hydrol. Earth Syst. Sci.

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Abstract. The National Flood Insurance Program (NFIP) debt has accelerated research into private flood insurance options. Offering this coverage begins with the ability to transfer the risk to the reinsurance market. Within the industry, perils such as hurricanes and earthquakes have standard definitions, but no such definition exists for floods. An event definition must examine the spatial and temporal aspects of the flood as well as the complexities of individual events. In this paper we were able to apply a data-driven methodology to capture and aggregate flood peaks into independent events. To aggregate flood peaks into independent events we needed to define what constituted a basin as our area of aggregation. The USGS utilizes the hydrological unit code (HUC) a 2-to 12-digit code that follows the Pfafsetter Coding System. The HUC code is used to identify varying levels of basin sizes ranging from region (2 digits) to subwatershed (12 digits). We chose to analyze both the HUC8 and HUC6, and a total of 7932 HUC8 events and 8444 HUC6 events were recorded during the 15 water years used in our study. Each event was characterized by duration, magnitude and severity. Focusing on the HUC8, events were unevenly distributed nationally while severity was relatively evenly distributed. The goal for our study was to take a method and be able to apply it to basins of varying characteristics. This framework relied on the ability to analyze the individual processes related to each individual basin.

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Analysis of extreme hydrological Events on THE danube using the Peak Over Threshold method

Cited by 51 publications

References 24 publications

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Extreme weather exposure identification for road networks – a comparative assessment of statistical methods

Effects of disregarding seasonality on the distribution of hydrological extremes

Defining and analyzing the frequency and severity of flood events to improve risk management from a reinsurance standpoint

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