For the design of hydraulic structures for flood conveyance and discharge, or protection of territory against flood is fundamental the knowledge of the ``extreme rainfall regime'' in the area where the hydraulic structures must be set up. Indeed the design flood is commonly evaluated as output of rainfall-runoff models that receive as input the quantitative description of a rainfall extreme event with a given exceedance probability. This dissertation assesses the performance of different statistical approaches in characterizing extreme rainfall in the island of Sardinia (Italy). After a detailed review of the theoretical bases of existing methodologies, we compare the results obtained from the use of: a) a Generalized Extreme value (GEV) distribution model, and a Two component Extreme Value (TCEV) distribution model, both applied to yearly maxima of daily rainfall, and b) a Generalized Pareto (GP) distribution model applied to rainfall excesses above a properly specified threshold. For the latter purpose, we use the Multiple Threshold Method (MTM) developed by Deidda(2010), which demonstrate good performance also in the case of quantized records. In order to describe the spatial variation of TCEV, GEV and GP model parameters a regional approach based on homogeneous regions, and two versions of Kriging (a commonly used geostatistical approach) i.e. ordinary Kriging (OK), and Kriging for uncertain Data (KUD), are compared. The obtained results are very promising, pointing towards the use of: a)a GEV distribution model for yearly rainfall maxima, and a KUD model to describe the spatial variation of model parameters, and b)a GP model for rainfall excesses and either an OK or a KUD model for the spatial variation of model parameters. The reason why the OK and KUD approaches lead to the same results in the GP case, is attributed to the robustness of the MTM method.

Extreme rainfall regime characterization in Sardinia using daily rainfall data

HELLIES, MATTEO
2016-02-09

Abstract

For the design of hydraulic structures for flood conveyance and discharge, or protection of territory against flood is fundamental the knowledge of the ``extreme rainfall regime'' in the area where the hydraulic structures must be set up. Indeed the design flood is commonly evaluated as output of rainfall-runoff models that receive as input the quantitative description of a rainfall extreme event with a given exceedance probability. This dissertation assesses the performance of different statistical approaches in characterizing extreme rainfall in the island of Sardinia (Italy). After a detailed review of the theoretical bases of existing methodologies, we compare the results obtained from the use of: a) a Generalized Extreme value (GEV) distribution model, and a Two component Extreme Value (TCEV) distribution model, both applied to yearly maxima of daily rainfall, and b) a Generalized Pareto (GP) distribution model applied to rainfall excesses above a properly specified threshold. For the latter purpose, we use the Multiple Threshold Method (MTM) developed by Deidda(2010), which demonstrate good performance also in the case of quantized records. In order to describe the spatial variation of TCEV, GEV and GP model parameters a regional approach based on homogeneous regions, and two versions of Kriging (a commonly used geostatistical approach) i.e. ordinary Kriging (OK), and Kriging for uncertain Data (KUD), are compared. The obtained results are very promising, pointing towards the use of: a)a GEV distribution model for yearly rainfall maxima, and a KUD model to describe the spatial variation of model parameters, and b)a GP model for rainfall excesses and either an OK or a KUD model for the spatial variation of model parameters. The reason why the OK and KUD approaches lead to the same results in the GP case, is attributed to the robustness of the MTM method.
9-feb-2016
BM
GEV
GP
Kriging
POT
eventi estremi
extreme events
regional analysis
regionalizzazione
soglia ottimale
File in questo prodotto:
File Dimensione Formato  
Phd_Thesis_Matteo_Hellies.pdf

accesso aperto

Tipologia: Tesi di dottorato
Dimensione 20.62 MB
Formato Adobe PDF
20.62 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/266863
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact