Abstract. A new rationale for deriving the probability distribution of floods and help in understanding the physical processes underlying the distribution itself is presented. On the basis of this a model that presents a number of new assumptions is developed. The basic ideas are as follows: (1) The peak direct streamflow Q can always be expressed as the product of two random variates, namely, the average runoff per unit area u• and the peak contributing area a; (2) the distribution of u• conditional on a can be related to that of the rainfall depth occurring in a duration equal to a characteristic response time •'• of the contributing part of the basin; and (3) •'• is assumed to vary with a according to a power law. Consequently, the probability density function of Q can be found as the integral, over the total basin area A, of that of a times the density function of u• given a. It is suggested that u• can be expressed as a fraction of the excess rainfall and that the annual flood distribution can be related to that of Q by the hypothesis that the flood occurrence process is Poissonian. In the proposed model it is assumed, as an exploratory attempt, that a and u a are gamma and Weibull distributed, respectively. The model was applied to the annual flood series of eight gauged basins in Basilicata (southern italy) with catchment areas ranging from 40 to 1600 km 2. The results showed strong physical consistence as the parameters tended to assume values in good agreement with well-consolidated geomorphologic knowledge and suggested a new key to understanding the climatic control of the probability distribution of floods.

No abstract

No abstract

The COVID-19 pandemic affected the lives of millions of people, radically changing their habits in just a few days. In many countries, containment measures prescribed by national governments restricted the movements of entire communities, with the impossibility of attending schools, universities, workplaces, and no longer allowing for traveling or leading a normal social life. People were then compelled to revise their habits and lifestyles. In such a situation, the availability of drinking water plays a crucial role in ensuring adequate health conditions for people and tackling the spread of the pandemic. Lifestyle of the population, climate, water scarcity and water price are influent factors on water drinking demand and its daily pattern. To analyze the effect of restriction measures on water demand, the instantaneous flow data of five Apulian towns (Italy) during the lockdown have been analyzed highlighting the important role of users’ habits and the not negligible effect of commuters on the water demand pattern besides daily volume requested.

[1] We develop a pulse-based representation of temporal rainfall with multifractal properties in the small-scale limit. The representation combines a traditional model for the exterior process at the synoptic scale with a novel hierarchical pulse model for the event interiors. For validation we apply the model to a temporal rainfall record from Florence, Italy. Although the model has only six parameters (four for the exterior process and two for the event interiors), it accurately reproduces a wide range of empirical statistics, including the distribution of dry and wet periods, the distribution of rainfall intensity up to extreme fractiles, the spectral density, the moment scaling function K(q), and the distribution of the partition coefficients for rainfall disaggregation. The model also reproduces observed deviations of physical rainfall from perfect scaling/multiscaling behavior.

Abstract. An application of the theoretically based distribution of floods recently derived by Iacobellis and Fiorentino [2000] was carried out with the aim of analyzing the climatic and geologic control on the distribution itself. In particular, 20 basins in a wide area of southern Italy were considered. These basins were classified by the use of a climatic index I depending on the average annual rainfall and on the potential evapotranspiration. This index takes positive values in humid climates and negative values in dry zones. With regard to the geology, attention was paid to the watershed permeability during intense storms; in each basin the pervious area was estimated after identification of three permeability classes. The analyses demonstrated that the sign of the climatic index strongly discriminates the behavior of both the parameters fA and E[a], the former representing, for each basin, the characteristic total abstraction rate and the latter being the expected value of the basin area contributing to the flood peak. In dry zones, f• was found to decrease'with increasing A, and the ratio r = E[a]/A tended to decline linearly, as the percentage of pervious areas increased. On the contrary, in humid zones the basin area did not seem to have any effect on fA, which was instead particularly sensitive to the climatic index. Moreover, in these zones the parameter r was steadily low without showing any significant dependence on climate, geology, and morphology of the basin. In this paper, an interpretation of these results is indeed provided. !. IntroductionThe characterization of peculiar features of the flood process finds a significant interpretative context within the g½o-morphoclimatic derivation of a flood probability distribution. The probability function of peak streamflow can be derived, either in an analytical or synthetic way, from the probability density function of rainfall, by using the functional relationships provided by the basin's hydrologic response.

Abstract. The paper introduces a semi-distributed hydrological model, suitable for continuous simulations, based upon the use of daily and hourly time steps. The model is called Distributed model for Runoff, Evapotranspiration, and Antecedent soil Moisture simulation (DREAM). It includes a daily water budget and an "event scale" hourly rainfall-runoff module. The two modules may be used separately or in cascade for continuous simulation. The main advantages of this approach lay in the robust and physically based parameterization, which allows use of prior information and measurable data for parameter estimation. The proposed model was applied over four medium-sized basins in southern Italy, exhibiting considerable differences in climate and other physical characteristics. The capabilities of the two modules (daily and hourly) and of the combined runs were tested against measured data.

Abstract.In general, different mechanisms may be identified as responsible of runoff generation during ordinary events or extraordinary events at the basin scale. In a simplified scheme these mechanisms may be represented by different runoff thresholds. In this context, the derived flood frequency model, based on the effect of partial contributing areas on peak flow, proposed by Iacobellis and Fiorentino (2000), was generalized by providing a new formulation of the derived distribution where two runoff components are explicitly considered. The model was tested on a group of basins in Southern Italy characterized by annual maximum flood distributions highly skewed. The application of the proposed model provided good results in terms of descriptive ability. Model parameters were also found to be well correlated with geomorphological basin descriptors. Two different threshold mechanisms, associated respectively to ordinary and extraordinary events, were identified. In fact, we found that ordinary floods are mostly 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 threshold storage in a large portion of the basin.