Detention dams are one of the most effective practices for flood mitigation. Therefore, the impact of these structures on the basin hydrological response is critical for flood management and the design of flood control structures. With the aim of providing a mathematical framework to interpret the effect of flow control systems on river basin dynamics, the functional relationship between inflows and outflows is investigated and derived in a closed form. This allowed the definition of a theoretically derived probability distribution of the peak outflows from in-line detention basins. The model has been derived assuming a rectangular hydrograph shape with a fixed duration and a random flood peak. In the present study, the undisturbed flood peaks are assumed to be Gumbel distributed, but the proposed mathematical formulation can be extended to any other flood-peak probability distribution. A sensitivity analysis of parameters highlighted the influence of detention basin capacity and rainfall event duration on flood mitigation on the probability distribution of the peak outflows. The mathematical framework has been tested using for comparison a Monte Carlo simulation where most of the simplified assumptions used to describe the dam behaviours are removed. This allowed demonstrating that the proposed formulation is reliable for small river basins characterized by an impulsive response. The new approach for the quantification of flood peaks in river basins characterized by the presence of artificial detention basins can be used to improve existing flood mitigation practices and support the design of flood control systems and flood risk analyses.
How to cite: Manfreda, S., D. Miglino, and C. Albertini, Impact of detention dams on the probability distribution of floods, Hydrol. Earth Syst. Sci., 25, 4231–4242, https://doi.org/10.5194/hess-25-4231-2021, 2021 [pdf]
In recent years, the acquisition of data from multiple sources, together with improvements in computational capabilities, has allowed to improve our understanding on natural hazard through new approaches based on machine learning and Big Data analytics. This has given new potential to flood risk mapping, allowing the automatic extraction of flood prone areas using digital elevation model (DEM) based geomorphic approaches. Most of the proposed geomorphic approaches are conceived mainly for the identification of flood extent. In this article, the DEM‐based method based on a geomorphic descriptor—the geomorphic flood index (GFI)—has been further exploited to predict inundation depth, which is useful for quantifying flood induced damages. The new procedure is applied on a case study located in southern Italy, obtaining satisfactory performances. In particular, the inundation depths are very similar to the ones obtained by hydraulic simulations, with a root‐mean‐square error (RMSE) = 0.335 m, in the domain where 2D dynamics prevail. The reduced computational effort and the general availability of the required data make the method suitable for applications over large and data‐sparse areas, opening new horizons for flood risk assessment at national/continental/global scale.
How to cite: Manfreda, S., C. Samela, A DEM-based method for a rapid estimation of flood inundation depth, Journal of Flood Risk Management, 12 (Suppl. 1):e12541, (doi: 10.1111/jfr3.12541) 2019. [pdf]
The last decades have seen a massive advance in technologies for Earth Observation (EO) and environmental monitoring, which provided scientists and engineers with valuable spatial information for studying hydrologic processes. At the same time, the power of computers and newly developed algorithms have grown sharply. Such advances have extended the range of possibilities for hydrologists, who are trying to exploit these potentials the most, updating and re-inventing the way hydrologic and hydraulic analyses are carried out. A variety of research fields have progressed significantly, ranging from the evaluation of water features, to the classification of land-cover, the identification of river morphology, and the monitoring of extreme flood events. The description of flood processes may particularly benefit from the integrated use of recent algorithms and monitoring techniques. In fact, flood exposure and risk over large areas and in scarce data environments have always been challenging topics due to the limited information available on river basin hydrology, basin morphology, land cover, and the resulting model uncertainty. The ability of new tools to carry out intensive analyses over huge datasets allows us to produce flood studies over large extents and with a growing level of detail. The present Special Issue aims to describe the state-of-the-art on flood assessment, monitoring, and management using new algorithms, new measurement systems and EO data. More specifically, we collected a number of contributions dealing with: (1) the impact of climate change on floods; (2) real time flood forecasting systems; (3) applications of EO data for hazard, vulnerability, risk mapping, and post-disaster recovery phase; and (4) development of tools and platforms for assessment and validation of hazard/risk models.
How to cite: Manfreda S., C. Samela, A. Refice, V. Tramutoli, F. Nardi, Advances in Large Scale Flood Monitoring and Detection, Hydrology, 5, 49, (doi: 10.3390/hydrology5030049) 2018. [pdf]
High and low ﬂows and associated ﬂoods and droughts are extreme hydrological phenomena mainly caused by meteorological anomalies and modiﬁed by catchment processes and human activities. They exert increasing on human, economic, and natural environmental systems around the world. In this context, global climate change along with local ﬂuctuations may eventually trigger a disproportionate response in hydrological extremes. This special issue focuses on observed extreme events in the recent past, how these extremes are linked to a changing global/regional climate, and the manner in which they may shift in the coming years.
How to cite: Salvatore Manfreda, Vito Iacobellis, Andrea Gioia, Mauro Fiorentino and Krzysztof Kochanek, The Impact of Climate on Hydrological Extremes, Water 2018, 10, 802 (doi:10.3390/w10060802),2018. [pdf]
The pier scour caused by flood waves is analyzed, introducing the dimensionless effective work by the flow on the sediment bed around the pier, W*. The three-parameter exponential function is adopted to relate the normalized scour depth Z* with W*. A novel experimental installation able to reproduce any hydrograph with high precision in the laboratory flume is described and used to carry out four series of scour experiments in order to calibrate and validate the proposed relation. The first series consists of experiments with constant discharge until advanced stages of scour. The second and third series of experiments use single flood waves of different shapes and durations, respectively. The fourth series consists of scour experiments caused by more realistic flow hydrographs with multiple peaks. Results show that the relation between W* and Z* is unique and thus W* represents a reliable concept for the prediction of the flood wave scour because it appropriately integrates the effects of the hydrograph properties, duration, peak discharge, and shape, on scour. The proposed relation allows a straightforward prediction of maximum scour depth after a flood wave with high precision. A good agreement between measured and computed scour was observed in all cases.
How to cite: Pizarro, A., B. Ettmer, S. Manfreda, A. Rojas, and O. Link, Effective Flow Work for Estimation of Pier Scour under Flood Waves, Journal of Hydraulic Engineering, 06017006-1-7, (doi: 10.1061/(ASCE)HY.1943-7900.0001295), 2017. [pdf]
Basilicata is known for the highest frequency of extreme hydrological and geological events. Several landslides and floods have extensively affected the region because of its geological characteristics and dynamics of precipitation producing extensive damage to regional urban areas and infrastructures. In this work, an analysis of extreme events occurred from 1925 to 2015 in Basilicata region is carried out in order to characterize their spatial and temporal evolution. This allowed us to identify the most critical periods and the areas most frequently affected by events that have caused damage on territory.
How to cite: Dal Sasso, S.F., S. Manfreda, G. Capparelli, P. Versace, C. Samela, G. Spilotro, M. Fiorentino, La pericolosità idraulica e geologica della regione Basilicata, L’Acqua, n.3, 77-85, 2017. [pdf]
In the present work, we describe an extended flood risk analysis carried out in the Adige River basin in Italy. The methodologies adopted were used in a comparative approach that highlighted the limits and potentiality of some methods with respect to others. Principles presented may be considered of interest for general problems of flood risk management. The work carried out shows interesting results along with a broad number of specificities that may constitute a useful support for those who will apply hydrological analyses on large-size basins. The study basin covers a wide area of about 12,000 km2. In such a case, a satisfactory analysis becomes complex because of the large number of phenomena involved in flood generation that need to be taken into account.
How to cite: .Manfreda, S. and M. Fiorentino, Flood Volume Estimation and Flood Mitigation: Adige river basin, in “Mountains: Sources of Water, Sources of Knowledge”, Series: Advances in Global Change Research, Vol. 31 Ed. by Ellen Wiegandt, pp. 243-264, (ISBN:978-1-4020-6747-1) 2008. [Link]
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 Floods, Advances in Water Resources, 30(10), 2123-2134, (doi:10.1016/j.advwatres.2006.11.017), 2007. [pdf]
The flood frequency estimation in ungauged basins requires the development of innovative statistical tools aimed to improve the available techniques for risk assessment. This research is aimed to better understand and classify the hydrological processes underlying the flood generation exploiting the theoretical model of Iacobellis and Fiorentino . The effects of climatic and physiographic basin features on the main variables of the cited theoretical flood probability distribution are analyzed focusing on 33 gauged basins in a wide area of Southern Italy. Results provide interesting information for the research of an analytical derivation of a flood frequency distribution whose parameters are directly related to climatic and physiographic basin characteristics.
How to cite: Gioia, A., V. Iacobellis, S. Manfreda, M. Fiorentino, Influence of Climatic and Soil Factors on Flood Frequency Distributions in Southern Italy, WSEAS transactions on Environment and Development, 3(1), 14-23, (ISSN 1790-5079), 2007.