Dimensionamento di invasi per il controllo dei deflussi nei bacini urbanizzati

Urbanization is a continuing phenomenon in all the world. Grasslands, forests, etc. are being continually changed to residential, commercial and industrial complexes, roads and streets, and so on. One of the side effects of urbanization with which engineers and planners must deal with, is the increase of peak flows and volumes of runoff from rainfall events. As a result, the urban drainage and flood control systems must be designed to accommodate the peak flows from a variety of storms that may occur. Usually the peak flow, after development, is required not to exceed what would have occurred from the same storm under conditions existing prior to development. In order to do this it is necessary to design detention storage to hold back runoff and to release it downstream at controlled rates. In the first part of the work have been developed various simplified formulations that can be adopted for the design of stormwater detention facilities. In order to obtain a simplified hydrograph were adopted two approaches: the kinematic routing technique and the linear reservoir schematization. For the two approaches have been also obtained other two formulations depending if the IDF (intensity-duration-frequency) curve is described with two or three parameters. Other formulations have been developed taking into account if the outlet have a constant discharge or it depends on the water level in the pond. All these formulations can be easily applied when are known the characteristics of the drainage system and maximum discharge that these is in the outlet and has been defined a Return Period which characterize the IDF curve. In this way the volume of the detention pond can be calculated. In the second part of the work have been analyzed the design of detention ponds adopting continuous simulation models. The drainage systems adopted for the simulations, performed with SWMM5, are fictitious systems characterized by different sizes, and different shapes of the catchments and with a rainfall historical time series of 16 years recorded in Bologna. This approach suffers from the fact that continuous record of rainfall is often not available and when it is, the cost of such modelling can be very expensive, and that the majority of design practitioners are not prepared to use continuous long term modelling in the design of stormwater detention facilities. In the third part of the work have been analyzed statistical and stochastic methodologies in order to define the volume of the detention pond. In particular have been adopted the results of the long term simulation, performed with SWMM, to obtain the data to apply statistic and stochastic formulation. All these methodologies have been compared and correction coefficient have been proposed on the basis of the statistic and stochastic form. In this way engineers which have to design a detention pond can apply a simplified procedure appropriately corrected with the proposed coefficient.

Rainfall spatial predictions: a two-part model and its assessment

Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.

SPHERA, a new Italian convection-permitting regional reanalysis: improving heavy-rainfall representation and describing hail-prone environments

Extreme weather events related to deep convection are high-impact critical phenomena whose reliable numerical simulation is still challenging. High-resolution (convection-permitting) modeling setups allow to switch off physical parameterizations accountable for substantial errors in convection representation. A new convection-permitting reanalysis over Italy (SPHERA) has been produced at ARPAE to enhance the representation and understanding of extreme weather situations. SPHERA is obtained through a dynamical downscaling of the global reanalysis ERA5 using the non-hydrostatic model COSMO at 2.2 km grid spacing over 1995-2020. This thesis aims to verify the expectations placed on SPHERA by analyzing two weather phenomena that are particularly challenging to simulate: heavy rainfall and hail. A quantitative statistical analysis over Italy during 2003-2017 for daily and hourly precipitation is presented to compare the performance of SPHERA with its driver ERA5 considering the national network of rain gauges as reference. Furthermore, two extreme precipitation events are deeply investigated. SPHERA shows a quantitative added skill over ERA5 for moderate to severe and rapid accumulations in terms of adherence to the observations, higher detailing of the spatial fields, and more precise temporal matching. These results prompted the use of SPHERA for the investigation of hailstorms, for which the combination of multiple information is crucial to reduce the substantial uncertainties permeating their understanding. A proxy for hail is developed by combining hail-favoring environmental numerical predictors with observations of ESWD hail reports and satellite overshooting top detections. The procedure is applied to the extended summer season (April-October) of 2016-2018 over the whole SPHERA spatial domain. The results indicate maximum hail likelihood over pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, in agreement with recent European hail climatologies. The method demonstrates enhanced performance in case of severe hail occurrences and the ability to separate between ambient signatures depending on hail severity.