Davide Luciano De Luca

Prof. Davide Luciano De Luca

Civil, Building & Environmental Engineering, Sapienza University of Rome, Rome, Lazio, Italy
orcid
Department of Civil, Building and Environmental Engineering,...

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 April 2022 in Journal of Hydrology
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Journal Article
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SGSalvatore Grimaldi
Salvatore Grimaldi
EVElena Volpi
Elena Volpi
ALAndreas Langousis
Andreas Langousis
SPSimon Michael Papalexiou
Simon Michael Papalexiou
Davide Luciano De LucaDavide Luciano De Luca
Davide Luciano De Luca
APAndrea Petroselli
Andrea Petroselli

1 February 2013 in Journal of Hydrology
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Journal Article
Closed access
Daniela BiondiDaniela Biondi
Daniela Biondi
Davide Luciano De LucaDavide Luciano De Luca
Davide Luciano De Luca

3 May 2021 in Hydrology
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Davide Luciano De LucaDavide Luciano De Luca
Davide Luciano De Luca
Andrea PetroselliAndrea Petroselli
Andrea Petroselli
The MS Excel file with VBA (Visual Basic for Application) macros named STORAGE (STOchastic RAinfall GEnerator) is introduced herein. STORAGE is a temporal stochastic simulator aiming at generating long and high-resolution rainfall time series, and it is based on the implementation of a Neymann–Scott Rectangular Pulse (NSRP) model. STORAGE is characterized by two innovative aspects. First, its calibration (i.e., the parametric estimation, on the basis of available sample data, in order to better reproduce some rainfall features of interest) is carried out by using data series (annual maxima rainfall, annual and monthly cumulative rainfall, annual number of wet days) which are usually longer than observed high-resolution series (that are mainly adopted in literature for the calibration of other stochastic simulators but are usually very short or absent for many rain gauges). Second, the seasonality is modelled using series of goniometric functions. This approach makes STORAGE strongly parsimonious with respect to the use of monthly or seasonal sets for parameters. Applications for the rain gauge network in the Calabria region (southern Italy) are presented and discussed herein. The results show a good reproduction of the rainfall features which are mainly considered for usual hydrological purposes.

1 April 2021 in Journal of Hydrology
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Journal Article
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DBDaniela Biondi
Daniela Biondi
AGAldo Greco
Aldo Greco
Davide Luciano De LucaDavide Luciano De Luca
Davide Luciano De Luca

30 November 2020 in Atmosphere
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Davide Luciano De LucaDavide Luciano De Luca
Davide Luciano De Luca
Andrea PetroselliAndrea Petroselli
Andrea Petroselli
LGLuciano Galasso
Luciano Galasso
In this work, a comprehensive methodology for trend investigation in rainfall time series, in a climate-change context, is proposed. The crucial role played by a Stochastic Rainfall Generator (SRG) is highlighted. Indeed, SRG application is particularly suitable to obtain rainfall series that are representative of future rainfall series at hydrological scales. Moreover, the methodology investigates the climate change effects on several timescales, considering the well-known Mann–Kendall test and analyzing the variation of probability distributions of extremes and hazard. The hypothesis is that the effects of climate changes could be more evident only for specific time resolutions, and only for some considered aspects. Applications regarded the rainfall time series of the Viterbo rain gauge in Central Italy.

28 February 2024 in Journal of Hydrology
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Journal Article
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Davide Luciano De LucaDavide Luciano De Luca
Davide Luciano De Luca
Elena RidolfiElena Ridolfi
Elena Ridolfi
Fabio RussoFabio Russo
Fabio Russo
BMBenedetta Moccia
Benedetta Moccia
FNFrancesco Napolitano
Francesco Napolitano