PROCESSI STOCASTICI IN IDROLOGIA

TEMA 1: PROCESSI STOCASTICI IN IDROLOGIA – STOCHASTIC PROCESSES IN HYDROLOGY
L’approccio statistico rappresenta uno dei principali strumenti di analisi per lo studio dei fenomeni naturali. Eventi estremi e processi di base sono stati analizzati e caratterizzati utilizzando diversi metodi statistici quali: teoria dei valori estremi, distribuzioni di probabilità teoricamente derivate, processi di Poisson, e equazioni differenziali stocastiche. Questi metodi sono stati utilizzati per fornire strumenti di calcolo in diversi ambiti delle costruzioni idrauliche, dell’idrologia e dell’ecoidrologia. Tra questi è opportuno menzionare i modelli per la caratterizzazione spazio-temporale del contenuto idrico del suolo, le distribuzioni derivate per la stima delle piene e dell’erosione localizzata, ed i modelli interpretativi sulla organizzazione spaziale della vegetazione.

The Theoretically Derived Probability Distribution of Scour

Based on recent contributions regarding the treatment of unsteady hydraulic conditions in the state-of-the-art scour literature, theoretically derived probability distribution of bridge scour is introduced. The model has been derived assuming a rectangular hydrograph shape with a given duration, and a random flood peak, following a Gumbel distribution. A model extension for a more complex flood event has also been presented, assuming a synthetic exponential hydrograph shape. The mathematical formulation can be extended to any flood-peak probability distribution. The aim of the paper is to move forward the current approaches adopted for the bridge design, by coupling hydrological, hydraulic, and erosional models, in a mathematical closed form. An example of the application of the proposed distribution has been included with the aim to provide a guidance for the parameters estimation.

How to cite: Manfreda S., O. Link, A. Pizarro, The Theoretically Derived Probability Distribution of Scour, Water, 10, 1520, 2018. [pdf]

Comparison of different methods describing the peak runoff contributing areas during floods

In the last few years, the scientific community has developed several hydrological models aimed at the simulation of hydrological processes acting at the basin scale. In this context, the portion of peak runoff contributing areas represents a critical variable for a correct estimate of surface runoff. Such areas are strongly influenced by the saturated portion of a river basin (influenced by antecedent conditions) but may also evolve during a specific rainfall event. In the recent years, we have developed 2 theoretically derived probability distributions that attempt to interpret these 2 processes adopting daily runoff and flood ‐ peak time series. The probability density functions (PDFs) obtained by these 2 schematisations were compared for humid river basins in southern Italy. Results highlighted that the PDFs of the peak runoff contributing areas can be interpreted by a gamma distribution and that the PDF of the relative saturated area provides a good interpretation of such process that can be used for flood prediction.

How to cite: Gioia, A., S. Manfreda, V. Iacobellis, M. Fiorentino, Comparison of different methods describing the peak runoff contributing areas during floodsHydrological Processes, 31(11), 2041-2049 (doi: 10.1002/hyp.11169), 2017.  [pdf]

Performance of a Theoretical Model for the Description of Water Balance and Runoff Dynamics in Southern Italy

In the present paper, an analytical work for the description of the soil water balance and runoff production was adopted over a significant number of river basins belonging to a humid region of Southern Italy. The model is based on a stochastic differential equation, where the spatial heterogeneity of a basin is incorporated by a parabolic function describing the distribution of soil water storage capacity at the basin scale. The model provides an analytical description of the probability density function (PDF) of relative saturation of a basin as well as the PDF of daily runoff production. The proposed model includes five parameters that depend on climatic and soil characteristics. In particular, two parameters describe the rainfall process (α and λ), two characterize the distribution of soil water storage capacity (wmax and b), and the last is the soil water loss coefficient (V). Application of the model allowed the regionalization of model parameters based on physically consistent characteristics of the river basins. In particular, it was found that the soil water loss coefficient is strongly controlled by the fraction of forest cover of the river basin, while the parameter b, controlling the shape of the distribution of soil water storage capacity, is influenced by the basin topography.

How to cite: Gioia, A., S. Manfreda, V. Iacobellis, M. Fiorentino, Performance of a theoretical model for the description of the water balance and runoff dynamics in Southern ItalyJournal of Hydrologic Engineering, 19(6), 1113-1123, (doi: 10.1061/(ASCE)HE.1943-5584.0000879), 2014. [pdf]

Influence of infiltration and soil storage capacity on the skewness of the annual maximum flood peaks in a theoretically derived distribution

Understanding the spatial variability of key parameters of flood probability distributions represents a strategy to provide insights on hydrologic similarity and building probabilistic models able to reduce the uncertainty in flood prediction in ungauged basins. In this work, we exploited the theoretically derived distribution of floods model TCIF (Two Component Iacobellis and Fiorentino model; Gioia et al., 2008), based on two different threshold mechanisms associated to ordinary and extraordinary events. The model is based on the hypotheses that ordinary floods are generally due to rainfall events exceeding a constant infiltration rate in a small source area, while the so-called outlier events responsible for the high skewness of flood distributions are triggered when severe rainfalls exceed a storage threshold over a large portion of the basin. Within this scheme, a sensitivity analysis was performed with respect to climatic and geomorphologic parameters in order to analyze the effects on the skewness coefficient and provide insights in catchment classification and process conceptualization. The analysis was conducted to investigate the influence on flood distribution of physical factors such as rainfall intensity, basin area, and particular focus on soil behavior.

How to cite: Gioia, A., V. Iacobellis, S. Manfreda, and M. Fiorentino, Influence of infiltration and soil storage capacity on the skewness of the annual maximum flood peaks in a theoretically derived distributionHydrology and Earth System Sciences, 16, 937-951, (doi:10.5194/hess-16-937-2012), 2012. [pdf]

Influence of soil parameters on the skewness coe ffi cient of the annual maximum flood peaks

Understanding the spatial variability of key parameters of flood probability distributions represents a strategy to provide insights on hydrologic similarity and building probabilistic models able to reduce the uncertainty in flood prediction in ungauged basins. In this work, we exploited the theoretically derived distribution of floods TCIF (Gioia et al., 2008), based on two different threshold mechanisms associated respectively to ordinary and extraordinary events. The model is based on the hypotheses that ordinary floods are generally due to rainfall events exceeding a threshold infiltration rate in a small source area, while the so-called outlier events, responsible of the high skewness of flood distributions, are triggered when severe rainfalls exceed a storage threshold over a large portion of the basin. Within this scheme, a sensitivity analysis was performed in order to analyze the effects of climatic and geomorphologic parameters on the skewness coefficient. In particular, the analysis was conducted investigating the influence on flood distribution of physical factors such as rainfall intensity, soil infiltration capacity, and basin area, in order to provide insights in catchment classification and process conceptualization.

How to cite: Gioia, A., V. Iacobellis, S. Manfreda, and M. Fiorentino, Influence of soil parameters on the skewness coefficient of the annual maximum flood peaks, Hydrology and Earth System Sciences Discussions, 8, Pages 5559–5604 (doi: 10.5194/hessd-8-5559-2011), 2011. [pdf]

Flood quantiles estimation based on theoretically derived distributions: regional analysis in Southern Italy

A regional probabilistic model for the estimation of medium-high return period flood quantiles is presented. The model is based on the use of theoretically derived probability distributions of annual maximum flood peaks (DDF). The general model is called TCIF (Two-Component IF model) and encompasses two different threshold mechanisms associated with ordinary and extraordinary events, respectively. Based on at-site calibration of this model for 33 gauged sites in Southern Italy, a regional analysis is performed obtaining satisfactory results for the estimation of flood quantiles for return periods of technical interest, thus suggesting the use of the proposed methodology for the application to ungauged basins. The model is validated by using a jack-knife cross-validation technique taking all river basins into consideration.

How to cite: Iacobellis, V., A. Gioia, S. Manfreda, M. Fiorentino, Flood quantiles estimation based on theoretically derived distributions: regional analysis in Southern ItalyNatural Hazards and Earth System Sciences, 11, 673-695, (doi:10.5194/nhess-11-673-2011), 2011. [pdf]

Regional analysis of runoff thresholds behaviour in Southern Italy based on theoretically derived distributions

The analysis of runoff thresholds and, more in general, the identification of main mechanisms of runoff generation controlling the flood frequency distribution is investigated, by means of theoretically derived flood frequency distributions, in the framework of regional analysis. Two nested theoretically-derived distributions are fitted to annual maximum flood series recorded in several basins of Southern Italy. Results are exploited in order to investigate heterogeneities and homogeneities and to obtain useful information for improving the available methods for regional analysis of flood frequency.

How to cite: Fiorentino, M., A. Gioia, V. Iacobellis, and S. Manfreda, Regional analysis of runoff thresholds behaviour in Southern Italy based on theoretically derived distributionsAdvances in Geosciences, 26, 139-144, (doi:10.5194/adgeo-26-139-2011), 2011. [pdf]

Confronto fra i tempi di ritorno di piogge e portate di rilevante entità

Nel presente lavoro, viene analizzato il comportamento dei bacini idrografici durante eventi di piena per approfondire le dinamiche afflussi/deflussi. Le analisi sono condotte mediante simulazione idrologica in continuo utilizzando il modello DREAM accoppiato al modello IRP per la generazione di serie sintetiche di precipitazione. Tale approccio consente di portare in debita considerazione l’eterogeneità spaziale delle caratteristiche geomorfologiche, tessiturali dei suoli e della vegetazione, permettendo di estendere lo studio delle piene a periodi di ritorno alti prescindendo dall’estrapolazione di relazioni basate su brevi periodi di osservazione. Le caratteristiche delle distribuzioni di probabilità delle piene ed alcuni dei principali fenomeni che le influenzano sono analizzate sfruttando centinaia di eventi sintetici generati mediante il DREAM in due casi di studio con condizioni climatiche differenti.

How to cite: Fiorentino, M., A. Gioia, S. Manfreda, V. Iacobellis, Confronto di differenti metodologie per la determinazione dell’area contribuente al picco di piena, Tecniche per la Difesa dall’Inquinamento, Editoriale Bios, 2018. 

Best Fit and Selection of Theoretical Flood Frequency Distributions Based on Different Runoff Generation Mechanisms

Theoretically derived distributions allow the detection of dominant runoff generation mechanisms as key signatures of hydrologic similarity. We used two theoretically derived distributions of flood peak annual maxima: the first is the “IF” distribution, which exploits the variable source area concept, coupled with a runoff threshold having scaling properties; the second is the Two Component-IF (TCIF) distribution, which generalizes the IF distribution, and is based on two different threshold mechanisms, associated with ordinary and extraordinary events, respectively. By focusing on the application of both models to two river basins, of sub-humid and semi-arid climate in Southern Italy, we present an ad hoc procedure for the estimation of parameters and we discuss the use of appropriate techniques for model selection, in the case of nested distributions.

How to cite: Iacobellis, V., M. Fiorentino, A. Gioia, S. Manfreda, Best Fit and Selection of Theoretical Flood Frequency Distributions Based on Different Runoff Generation MechanismsWater, 2(2), 239-256, (doi:10.3390/w2020239), 2010. [pdf]