The Role of the Corbara Reservoir on the Tiber River in the Flood Protection of the Town of Rome, Italy

Calenda, Guido; Mancini, C. P.

doi:10.1061/40440(1999)3

Cited by 6 publications

(5 citation statements)

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“…The index 𝐴𝐴  clearly indicates that the only reservoir that significantly influences the flood quantiles at the Ripetstation is Corbara, for which we have 𝐴𝐴  = 0.884 . Such result can be checked by computing the average ratio between the naturalized (i.e., corrected from the influence of Corbara reservoir) flood peak annual maxima at Ripetta and the corresponding observed ones, that was performed by Calenda and Mancini (1999) for the period 1965-1989. The calculation leads to 𝐴𝐴 0.889 , that is very close to the 𝐴𝐴  value obtained by the simplified proposed approach.…”

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confidence: 99%

A New Physically Based Index to Quantify the Impact of Multiple Reservoirs on Flood Frequency at the Catchment Scale Based on the Concept of Equivalent Reservoir

Cipollini

Fiori

Volpi

2022

Water Resources Research

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The presence of multiple reservoirs in a catchment generally induces the attenuation of flood events, thus mitigating their impact in downstream flood‐prone areas. Such mitigation results from the superposition of several contributions, coming from the regulated (i.e., altered by reservoir) or unregulated subcatchments as determined by the reservoirs spatial distribution within the catchment. Understanding how multiple reservoirs affect the probability distribution of flood peak at the catchment scale is a difficult task, requiring a detailed and generally costly hydrologic/hydraulic simulation. We provide here a simple yet physically based mathematical framework to account for the effect of multiple reservoirs, located in series along the main channel, on peak flood quantile at the catchment scale. The framework allows to disentangle the role of the main relevant parameters controlling the system behavior, such as the number of reservoirs, their relative location and relative storage coefficient within the catchment, and a climatic parameter governing rainfall variability in time. The combined effect of the reservoirs in reducing the peak flow is represented by a global index scriptR $\mathcal{R}$, which is bounded between zero and unit and it is independent of the return period. The index is based on the concept of equivalent reservoir and is easily calculated by the analytical formulas provided in this study, as function of the above parameters.

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confidence: 99%

A New Physically Based Index to Quantify the Impact of Multiple Reservoirs on Flood Frequency at the Catchment Scale Based on the Concept of Equivalent Reservoir

Cipollini

Fiori

Volpi

2022

Water Resources Research

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“…According to the Pettitt test, a change-point in mean is detected in 1965 (significant at the 5% level), but no statistically-significant change-point in variance. This year matches the year of the first filling of the reservoir (Calenda and Mancini 1999), and is very close to the year in which the construction of the Corbara Reservoir was completed (1963). Given the presence of a change-point in mean, we split the time series into two sub-series (before and after the change-point) and performed monotonic trend analysis of each sub-series separately.…”

Section: Analyses Of the Flood Frequency Distribution Of The Tiber Rimentioning

confidence: 66%

“…Another significant alteration of the discharge of the Tiber River is associated with the construction of the Corbara Reservoir, completed in 1963 (e.g. Calenda and Mancini 1999). For more information about the history of the flooding of the Tiber River in Rome and the resulting changes, the reader is referred to Calenda and Mancini (1999), Bersani and Bencivenga (2001), Calenda et al (2003), Calenda et al (2005), Aldrete (2007), Natale and Savi (2007), Calenda et al (2009), among others.…”

Section: Introductionmentioning

confidence: 98%

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Hydrometeorological analysis of the December 2008 flood in Rome

Villarini

Smith

Napolitano

et al. 2011

Hydrological Sciences Journal

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Rome has been plagued by flooding since its foundation, and, in December 2008, the largest flood event over the past 20 years caused a fatality and more than (sic)150 million in economic damage. Meteorological conditions associated with the December 2008 flooding are shown to be typical of flooding in the Tiber. The long record of discharge measurements of the Tiber River at the Ripetta station in downtown Rome was used to examine flood frequency for the Tiber, including assessment of the return interval of the December 2008 flood. Particular attention is given to examination of the stationarity assumption for flood peaks through change-point and trend analyses, quantile regression, and statistical modelling of the flood-peak distribution. Once anthropogenic changes linked to reservoir regulation of the Tiber River have been accounted for, the stationarity assumption holds and can be used for flood frequency analysis. We highlight the difficulties in detecting departures from the stationarity assumption due to climate change. In the current regime, the December 2008 flood event has a return period of the order of 10 20 years

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“…The dynamic of the forecasting system will be able to cope with the event frequency and triggered alert to the authority when the situation is at the severe level. Flood forecasting is significant to cope with the great floods [16].…”

Section: Fig 1 Conceptual Model Of Reservoir Systemmentioning

confidence: 99%

Intelligent Decision Support Model Based on Neural Network to Support Reservoir Water Release Decision

Ishak

Ku-Mahamud

Norwawi

2011

Software Engineering and Computer Systems

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Abstract.Reservoir is one of the emergency environments that required fast an accurate decision to reduce flood risk during heavy rainfall and contain water during less rainfall. Typically, during heavy rainfall, the water level increase very fast, thus decision of the water release is timely and crucial task. In this paper, intelligent decision support model based on neural network (NN) is proposed. The proposed model consists of situation assessment, forecasting and decision models. Situation assessment utilized temporal data mining technique to extract relevant data and attribute from the reservoir operation record. The forecasting model utilize NN to perform forecasting of the reservoir water level, while in the decision model, NN is applied to perform classification of the current and changes of reservoir water level. The simulations have shown that the performances of NN for both forecasting and decision models are acceptably good.

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The Role of the Corbara Reservoir on the Tiber River in the Flood Protection of the Town of Rome, Italy

Cited by 6 publications

References 0 publications

A New Physically Based Index to Quantify the Impact of Multiple Reservoirs on Flood Frequency at the Catchment Scale Based on the Concept of Equivalent Reservoir

A New Physically Based Index to Quantify the Impact of Multiple Reservoirs on Flood Frequency at the Catchment Scale Based on the Concept of Equivalent Reservoir

Hydrometeorological analysis of the December 2008 flood in Rome

Intelligent Decision Support Model Based on Neural Network to Support Reservoir Water Release Decision

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