Peak runoff contributing area as hydrological signature of the probability distribution of floods

For the analysis of hydrological extremes and particularly in flood prediction, deeper investigation is needed on the relative effects of different hydrological processes acting at the basin scale in different hydroclimatic areas of the world. In this framework, the theoretical derivation of flood distribution shows a great potential for development and knowledge advancement. In addition, another promising path of investigation is represented by the use of distributed hydrological models via simulation modelling (including Monte Carlo, discrete event and continuous simulation). In this paper results of a theoretically derived flood frequency distribution are analyzed and compared with the results of a simulation scheme that uses a distributed hydrological model (DREAM) in cascade with a rainfall generator (IRP). The numerical simulation allows the reproduction of a large number of extreme events and provides insight into the main control for flood generation mechanisms with particular emphasis to the peak runoff contributing areas, highlighting the relevance of soil texture and morphology in different climatic environments. The proposed methodology is applied here to the Agri and the Bradano basin, in Southern Italy.

How to cite: Fiorentino, M., S. Manfreda, V. Iacobellis, Peak Runoff Contributing Area as Hydrological Signature of the Probability Distribution of FloodsAdvances in Water Resources, 30(10), 2123-2134, (doi:10.1016/j.advwatres.2006.11.017), 2007.  [pdf]

Analysis on flood generation processes by means of a continuous simulation model

In the present research, we exploited a continuous hydrological simulation to investigate on key variables responsible of flood peak formation. With this purpose, a distributed hydrological model (DREAM) is used in cascade with a rainfall generator (IRP-Iterated Random Pulse) to simulate a large number of extreme events providing insight into the main controls of flood generation mechanisms. Investigated variables are those used in theoretically derived probability distribution of floods based on the concept of partial contributing area (e.g. Iacobellis and Fiorentino, 2000). The continuous simulation model is used to investigate on the hydrological losses occurring during extreme events, the variability of the source area contributing to the flood peak and its lag-time. Results suggest interesting simplification for the theoretical probability distribution of floods according to the different climatic and geomorfologic environments. The study is applied to two basins located in Southern Italy with different climatic characteristics.

How to cite: Fiorentino, M., A. Gioia, V. Iacobellis, S. Manfreda, Analysis on flood generation processes by means of a continuous simulation modelAdvances in Geosciences, 7, 231-236, (SRef-ID: 1680-7359/adgeo/2006-7-231), 2006. [pdf]

DREAM: a distributed model for runoff, evapotranspiration, and antecedent soil moisture simulation

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.

How to cite: Manfreda, S., M. Fiorentino, V. Iacobellis, DREAM: a Distributed model for Runoff, Evapotranspiration, and Antecedent Soil Moisture SimulationAdvances in Geosciences, 2, 31-39, (SRef-ID: 1680-7359/adgeo/2005-2-31), 2005. [pdf]