Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Influences on flood frequency distributions in Irish river catchments

View through CrossRef
Abstract. This study explores influences which result in shifts of flood frequency distributions in Irish rivers. Generalised Extreme Value (GEV) type I distributions are recommended in Ireland for estimating flood quantiles. This paper presents the findings of an investigation that identified the GEV statistical distributions that best fit the annual maximum (AM) data series extracted from 172 gauging stations of 126 rivers in Ireland. Of these 126 rivers, 25 have multiple gauging stations. Analysis of this data was undertaken to explore hydraulic and hydro-geological factors that influence flood frequency distributions and whether shifts in distributions occur in the down-river direction. The methodology involved determining the shape parameter of GEV distributions that were fitted to AM data at each site and to statistically test this shape parameter to determine whether a type I, type II or type III distribution was valid. The classification of these distributions was further supported by moment and L-moment diagrams and probability plots. Results indicated that of the 143 stations with flow records exceeding 25 yr, data for 92 was best represented by GEV type I distributions and that for another 12 and 39 stations followed type II and type III distributions respectively. The spatial, hydraulic and hydro-geological influences on flood frequency distributions were assessed by incorporating results on an Arc-GIS platform with individual layers showing karst features, flood attenuation polygons and lakes. This data reveals that type I distributions are spatially well represented throughout the country. The majority of type III distributions appear in four distinct clusters in well defined geographical areas where attenuation influences from floodplains and lakes appear to be influential. The majority of type II distributions appear to be in a single cluster in a region in the west of the country that is characterised by a karst landscape. The presence of karst in river catchments would be expected to provide additional subsurface storage and in this regard, type III distributions might be expected. The prevalence of type II distributions in this area reflects the finite nature of this storage and the effects, in extreme conditions, when the karst is saturated and further storage is no longer available. Results therefore indicate that in some instances assuming type I distributions is incorrect and may result in erroneous estimates of flood quantiles in these regions. Where actual data follows a type II distribution, flood quantiles may be underestimated and for type III distributions, overestimates may be expected.
Title: Influences on flood frequency distributions in Irish river catchments
Description:
Abstract.
This study explores influences which result in shifts of flood frequency distributions in Irish rivers.
Generalised Extreme Value (GEV) type I distributions are recommended in Ireland for estimating flood quantiles.
This paper presents the findings of an investigation that identified the GEV statistical distributions that best fit the annual maximum (AM) data series extracted from 172 gauging stations of 126 rivers in Ireland.
Of these 126 rivers, 25 have multiple gauging stations.
Analysis of this data was undertaken to explore hydraulic and hydro-geological factors that influence flood frequency distributions and whether shifts in distributions occur in the down-river direction.
The methodology involved determining the shape parameter of GEV distributions that were fitted to AM data at each site and to statistically test this shape parameter to determine whether a type I, type II or type III distribution was valid.
The classification of these distributions was further supported by moment and L-moment diagrams and probability plots.
Results indicated that of the 143 stations with flow records exceeding 25 yr, data for 92 was best represented by GEV type I distributions and that for another 12 and 39 stations followed type II and type III distributions respectively.
The spatial, hydraulic and hydro-geological influences on flood frequency distributions were assessed by incorporating results on an Arc-GIS platform with individual layers showing karst features, flood attenuation polygons and lakes.
This data reveals that type I distributions are spatially well represented throughout the country.
The majority of type III distributions appear in four distinct clusters in well defined geographical areas where attenuation influences from floodplains and lakes appear to be influential.
The majority of type II distributions appear to be in a single cluster in a region in the west of the country that is characterised by a karst landscape.
The presence of karst in river catchments would be expected to provide additional subsurface storage and in this regard, type III distributions might be expected.
The prevalence of type II distributions in this area reflects the finite nature of this storage and the effects, in extreme conditions, when the karst is saturated and further storage is no longer available.
Results therefore indicate that in some instances assuming type I distributions is incorrect and may result in erroneous estimates of flood quantiles in these regions.
Where actual data follows a type II distribution, flood quantiles may be underestimated and for type III distributions, overestimates may be expected.

Related Results

Irish Literature and the Union with Britain, 1801–1921
Irish Literature and the Union with Britain, 1801–1921
Studies of Romantic and Victorian literary culture often sideline Irish writing—not always out of Anglocentric prejudice, but also because Irish literature in those periods was fre...
Assessment of Flood Risk Analysis in Selangor
Assessment of Flood Risk Analysis in Selangor
Flood events occur every year especially during the monsoon season. Although its consequences are not as disastrous as other natural disasters such as earthquakes and tornado storm...
Numerical Simulation of Flood Propagation in the Kelara River Flood Early Warning System
Numerical Simulation of Flood Propagation in the Kelara River Flood Early Warning System
Flood historical data from the Kelara River in the last 10 years shows that the river has often overflowed, and the worst floods happened on January 22, 2019. One of the efforts to...
Study on hazard assessment of mountainous flood in riverside country- a case study in Xinshan, Hubei, China
Study on hazard assessment of mountainous flood in riverside country- a case study in Xinshan, Hubei, China
Abstract Mountainous riverside countries have already become the weaknesses of flood disaster control infrastructure in China, so flood calculation based on hydrauli...
Catchment classification by runoff behaviour with self-organizing maps (SOM)
Catchment classification by runoff behaviour with self-organizing maps (SOM)
Abstract. Catchments show a wide range of response behaviour, even if they are adjacent. For many purposes it is necessary to characterise and classify them, e.g. for regionalisati...
Reconstructing a hydraulic model for historic flood levels in the city of Bath, United Kingdom
Reconstructing a hydraulic model for historic flood levels in the city of Bath, United Kingdom
<p>Assessing the risk of future flood events and the implications for flood risk in cities is an economically and socially costly problem. In this research, we assess...
Flood Frequency Analysis Using Mixture Distributions in Light of Prior Flood Type Classification in Norway
Flood Frequency Analysis Using Mixture Distributions in Light of Prior Flood Type Classification in Norway
The fundamental assumption of flood frequency analysis is that flood samples are generated by the same flood generation mechanism (FGM). However, flood events are usually triggered...

Back to Top