Avino, Angelo (2023) Updating annual rainfall maxima statistics in a data-scarce region: the case study of Southern Italy. [Tesi di dottorato]
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| Tipologia del documento: | Tesi di dottorato |
|---|---|
| Lingua: | English |
| Titolo: | Updating annual rainfall maxima statistics in a data-scarce region: the case study of Southern Italy |
| Autori: | Autore Email Avino, Angelo angelo.avino@unina.it |
| Data: | 10 Marzo 2023 |
| Numero di pagine: | 176 |
| Istituzione: | Università degli Studi di Napoli Federico II |
| Dipartimento: | Ingegneria Civile, Edile e Ambientale |
| Dottorato: | Ingegneria dei sistemi civili |
| Ciclo di dottorato: | 35 |
| Coordinatore del Corso di dottorato: | nome email Papola, Andrea papola@unina.it |
| Tutor: | nome email Pianese, Domenico [non definito] Manfreda, Salvatore [non definito] Cimorelli, Luigi [non definito] |
| Data: | 10 Marzo 2023 |
| Numero di pagine: | 176 |
| Parole chiave: | rainfall extremes; sub-daily annual maxima; data-scarce region; spatially-constrained ordinary kriging; non-parametric trend test |
| Settori scientifico-disciplinari del MIUR: | Area 08 - Ingegneria civile e Architettura > ICAR/02 - Costruzioni idrauliche e marittime e idrologia |
| Depositato il: | 28 Mar 2023 13:22 |
| Ultima modifica: | 09 Apr 2025 13:13 |
| URI: | http://www.fedoa.unina.it/id/eprint/15037 |
Abstract
The growing number of extreme hydrological events observed has raised the level of attention toward the impact of climate change on the rainfall process, which is difficult to quantify given its strong spatial and temporal heterogeneity. Therefore, that impact cannot be determined on the individual hydrological series but must be assessed on a regional and/or district scale. With this objective, the present thesis aims at identifying the trends and dynamics of extreme sub-daily rainfall in southern Italy in the period 1970-2020. The database of annual maxima was assembled using all available rainfall data (provided by the National Hydrographic and Mareographic Service - SIMN, and the Regional Civil Protection). However, due to the frequent changes (location, type of sensor, and managing agencies) experienced by the national monitoring network, the time-series were found to be extremely uneven and fragmented. Since the spatio-temporal discontinuity could invalidate any statistical analysis, gap-filling techniques (deterministic and geostatistical) were applied to reconstruct the missing data. In particular, the “Spatially-Constrained Ordinary Kriging” (SC-OK) method was used, namely a mixed procedure that adopts the Ordinary Kriging (OK) approach with the spatial constraints of the Inverse Distance Weighting (IDW) technique. The SC-OK procedure allows to reconstruct only missing data for the stations selected by the IDW method (those with a sufficient number of functioning neighbouring rain gauges). The reconstructed dataset has been used to explore trends and regional patterns in annual maxima, highlighting how rainfall are evolving in the most recent years.
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