Stationary vs. non-stationary modeling of flood frequency distribution across North West England (UK)

Hesarkazzazi, Sina (2018) Stationary vs. non-stationary modeling of flood frequency distribution across North West England (UK). [Laurea magistrale], Università di Bologna, Corso di Studio in Ingegneria per l'ambiente e il territorio [LM-DM270], Documento full-text non disponibile
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As environmental change is happening at an unprecedented pace, a comprehensive and holistic approach is needed in order to mitigate the increasing negative effect of extreme natural events occurring based on the natural and anthropogenic variations. Of all the geophysical phenomena, flooding is one of the most catastrophic events, leading to quite a few losses and damages across the World. Recent extraordinary flood events happened in north – western England, precisely sequences of the severe floods in the county of Cumbria, Lancashire and Manchester in 2004, 2009 and 2015, have brought many concerns not only for the residents but also for the community of hydrologists in UK. These extreme events in these areas comparing with their typical river discharge values have raised an important question of whether any significant changes in the magnitude of river flows can be detected as a result of natural/human - induced clime change. If so, whether they can be attributed to any meteorological predictors such as rainfall frequency analysis. The results, performed for 39 river gauging stations based on annual maxima (AM) approach, indicate that around 92% of the river gauging stations show non – stationary behaviour; whereas only in 8%, stationarity is dominant. More importantly, annual rainfall is deemed as the best explanatory variable to express the variability of our data much better than other covariates for a vast majority of stations (around 60%).

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Hesarkazzazi, Sina
Relatore della tesi
Correlatore della tesi
Corso di studio
Earth resources engineering
Ordinamento Cds
Parole chiave
Non-stationarity,Statistical Hydrology,Annual Maxima (AM),Flood Frequency,Generalized Logistic distribution (GLO) model,Maximum Likelihood Estimation (MLE),Alkaike Information Criteria (AIC)
Data di discussione della Tesi
5 Ottobre 2018

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