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The paper presents a new hourly high-resolution (i.e., at 0.02°, ≃2.2 km) precipitation dataset, labelled as ERA5@2km, obtained by dynamically downscaling ERA5 reanalysis at convection permitting scale (CPS) over 20 European cities for the recent past thirty years (1989–2018). The downscaling activity is performed within the framework of the Contract implemented by Fondazione CMCC to support Sectoral Information System about “Disaster Risk Reduction” (see https://climate.copernicus.eu/pluvial-flood-risk-assessment-urban-areas) of Copernicus Climate Change Service (C3S). Specifically, such an additional precipitation dataset is developed to provide precipitation data for estimating expected precipitations at fixed return periods used as input for pluvial flooding risk analysis where hazard (inundated areas, water levels) and risk (estimated damages) are assessed. The ambition is to support the Disaster Risk Reduction (DRR) community involved in pluvial flood risk assessment by providing a basis for impact analysis at city scale, in terms of extreme hourly precipitation, that matches with the expected spatial and temporal requirements. In this work, ERA5@2km precipitation dataset is introduced for the first time and its reliability and coherence are evaluated as for spatial patterns and trends as for extreme values against a set of available high-resolution observational datasets (comparable in terms of spatial and temporal resolution). Such an evaluation provides a clearer understanding about the added value of very high-resolution (VHR) dynamical downscaling reanalysis in terms of localization and magnitude of precipitation events at urban scale, confirming a general and relevant added value of this new configuration for the assessment of extreme atmospheric events (such as heavy precipitations).

Understanding and modelling pluvial flood patterns is pivotal for the estimation of flood impacts in urban areas, especially in a climate change perspective. However, urban flood modelling under climate change conditions poses several challenges. On one hand, the identification and collection of climate change data suitable for flood-related evaluations requires consistent computational and scientific effort. On the other hand, large difficulties can arise in the reproduction of the rainfall-runoff transformation process in cases when only little information about the subsurface processes is known. In this perspective, a simplified approach is proposed to address the challenges regarding the quantitative estimation of climate change effects on urban flooding for real case applications. The approach is defined as “bottom-up” because climate change information is not included in flood modelling, but it is only invoked for the interpretation of results. In other words, the challenge faced in this work is the development of a modelling strategy that is expeditious, because it does not require flood simulations for future rainfall scenarios, but only under current climate conditions, thus reducing the overall computational effort; and it is flexible, because results can be easily updated once new climate change data, scenarios or methods become available, without the need of additional flood simulations. To simulate real case applications, the approach is tested for a scenario analysis, where different return periods and hyetograph shapes are used as input for urban inundation modelling in Naples, Italy. The approach can support public and private stakeholders, such as land administrators and water systems managers; moreover, it represents a valuable and effective basis for climate change risk communication strategies.

Flood hazard mitigation in urban areas crossed by vegetated flows can be achieved through two distinct approaches, based on structural and eco-friendly solutions, referred to as grey and green–blue engineering scenarios, respectively, this one is often based on best management practices (BMP) and low-impact developments (LID). In this study, the hydraulic efficiency of two green–blue scenarios in reducing flood hazards of an urban area crossed by a vegetated river located in Central Tuscany (Italy), named Morra Creek, were evaluated for a return period of 200 years, by analyzing the flooding outcomes of 1D and 2D unsteady hydraulic simulations. In the first scenario, the impact of a diffuse effect of flood peak reduction along Morra Creek was assessed by considering an overall real-scale growth of common reed beds. In the second scenario, riverine vegetation along Morra Creek was preserved, while flood hazard was mitigated using a single vegetated flood control area. This study demonstrates well the benefits of employing green–blue solutions for reducing flood hazards in vegetated rivers intersecting agro-forestry and urban areas while preserving their riverine ecosystems. It emerged that the first scenario is a valuable alternative to the more impacting second scenario, given the presence of flood control areas.

Estimating the main hydrodynamic features of real vegetated water bodies is crucial to assure a balance between their hydraulic conveyance and environmental quality. Riparian vegetation stands have a high impact on vegetated channels. The present work has the aim to integrate riparian vegetation’s reflectance indices and hydrodynamics of real vegetated water flows to assess the impact of riparian vegetation morphometry on bulk drag coefficients distribution along an abandoned vegetated drainage channel fully covered by 9–10 m high Arundo donax (commonly known as giant reed) stands, starting from flow average velocities measurements at 30 cross-sections identified along the channel. A map of riparian vegetation cover was obtained through digital processing of Unnamed Aerial Vehicle (UAV)-acquired multispectral images, which represent a fast way to observe riparian plants’ traits in hardly accessible areas such as vegetated water bodies in natural conditions. In this study, the portion of riparian plants effectively interacting with flow was expressed in terms of ground-based Leaf Area Index measurements (LAI), which easily related to UAV-based Normalized Difference Vegetation Index (NDVI). The comparative analysis between Arundo donax stands NDVI and LAI map enabled the analysis of the impact of UAV-acquired multispectral imagery on bulk drag predictions along the vegetated drainage channel.

The paper considers a methodology to assess rainfall erosivity in Italy for the recent decades (1981–2010), building on datasets and materials freely available, such as those included within the Climate Data Store (CDS) of the Copernicus Climate Change Service (C3S). Twenty-one referenced empirical models to assess rainfall erosivity (R-factor) based on coarse rainfall data are tested and compared; then, a custom model is calibrated, with the support of seasonal rainfall pattern clustering by means of the Self-Organizing Map. Moreover, a large database of sub-hourly rainfall observations, covering the period 2002–2011, is collected and used for validation. Model performances are analysed at the point-scale of the rain gauges and at the spatial scale of different relevant gridded rainfall products: the fifth generation of ECMWF ReAnalysis (ERA5, ERA5-Land), the gridded European observational dataset (E-OBS), all included in the CDS, and SCIA-ISPRA (the Italian standard rainfall gridded dataset). New Hydrological Insights from the Region The proposed methodology provides four alternatives of spatially distributed rainfall erosivity datasets covering Italy with diverse levels of reliability. Analysis of results shows that the best performance is achieved by the combined use of the custom model and the SCIA-ISPRA dataset, followed by ERA5-Land, with the main source of error lying in the use of an empirical model instead of the rigorous model for R-factor estimation, and secondly in the use of gridded rainfall data instead of point-scale rainfall observations.

Flooding is one of the most challenging weather-induced risks in urban areas, due both to the typically high exposures in terms of people, buildings, and infrastructures, and to the uncertainties lying in the modelling of the involved physical processes. The modelling of urban flooding is usually performed by means of different strategies in accordance with the specific purpose of the analysis, ranging from detailed simulations, requiring large modelling and computational efforts, and typically adopted for design purposes, to simplified evaluations, particularly feasible for scenario analyses, when a large number of simulations is required perturbing one or more input parameters.According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, intensity of precipitation events could be greatly impacted by the expected climate change primarily due to the increase in temperature, entailing an increase in the atmospheric moisture retention capability. However, the effect of climate change on the rainfall regime of local areas is not straightforward, but deeply depends on local features such as latitude, topography, distance from the coast. Over Europe, an ensemble of climate simulations coming from the application of different Regional Climate Models (RCMs) (able to perform a dynamical downscaling of General Circulation Models, GCMs, available at the global scale) is freely available within the EURO-CORDEX initiative, which is the current standard for climate change analysis over EU countries. The spatial resolution of EURO-CORDEX simulations (about 12km) is too coarse to be directly used in local impact analyses; in this case, bias corrections are usually performed using local rainfall observations, to adjust climate simulation results to the local rainfall regime. The availability of multiple climate projections coming from different Climate Simulation Chains (in other words, different RCM/GCM couplings) allows to quantify the uncertainty in climate modelling, that should be accounted for in impact analyses.In the present work, an approach is proposed that aims to quantify the uncertainty caused by the use of an ensemble of climate projections on urban flood modelling, taking a limited area within the City of Naples (Italy) as test case. The specific purpose is that of understanding the resilience of the area with respect to any variation in rainfall intensity such as those possibly caused by climate change, building on 19 climate projections available within the EURO-CORDEX initiative and bias-corrected to make them suitable to be used for impact analyses at the local scale. The concept of resilience is expressed by a selection of indicators considered useful both in the framework of classical hazard analysis and for transport network, considered a strategic service for the test case. Urban flood modelling is undertaken by using two different numerical codes characterized by two different levels of complexity. In this way, it will be possible to draw conclusions about the computational costs that are actually needed, in terms of input data and resources, when integrating uncertainties due to climate projections in urban flood modelling for multi-purpose analyses.

Erosion processes are caused by a combination of predisposing factors (slope, intrinsic soil properties), accelerating factors (removal of vegetation cover, altered soil properties due e.g. to fires, overgrazing, tillage) and triggering factors (water – from rain and rivers – and wind). While the first components are rather unchanging (or changing slowly) at the human time scale, the last two must deal with the consequences of global changes. Indeed, modifications in land use, land management and climate have strong feedbacks so that, from one side, lands are more and more overexploited, degraded and exposed to erosion and, on the other side, over these lands, the frequency, magnitude, duration and timing of triggering events could deviate from their “normal” conditions.According to the well-known RUSLE soil loss estimation model, the triggering effect of rainfall for sheet and rill erosion is accounted for by means of the so-called rainfall erosivity or “R-factor”. R-factor consists of the annual summation of the erosive power of relevant storm events, averaged over a significant period of observation. For each storm event, computation of R-factors requires high-resolution rainfall information for the evaluation of the maximum rainfall intensity occurring over a time window of 30 min during the rainfall event. Due to the generally limited access to sub-hourly precipitation observations, a number of empirical models relating R-factor to easily accessible climate, physical and geographical covariates, such as rainfall data at coarse aggregation levels, have been developed for different areas of the world.As concerns Italy, a novel empirical model is proposed relating rainfall erosivity to cumulative precipitation, elevation and latitude. Such model, calibrated for a significant selection of relevant rain gauges with available sub-hourly data, showed a good accordance with observations and a large amount of explained variance at the annual scale, with promising results also at the monthly level. The model was effectively extended to cover the whole Italian Country for the period 1981-2010 by means of gridded rainfall datasets retrievable in the Copernicus Climate Change Service (C3S) Climate Data Store (CDS), with limited performance loss, exploring the feasibility of Copernicus products for erosion-related assessments. Although affected by limitations, the proposed model is particularly suitable for applications involving future rainfall projections since it explicitly accounts for monthly cumulative precipitation as the only climate covariate, differently for other proposed methodologies also including rainfall-related variables with higher temporal resolution, whose future trends cannot be robustly evaluated with current climate modelling tools. In the present research an ensemble of twelve future rainfall projections included in the Euro-Cordex initiative, bias-adjusted by means of the ERA5-Land reanalysis dataset, is considered to account for the uncertainties coming from the use of multiple projections. The proposed approach provides a unique example of rainfall erosivity dataset accounting for a wide ensemble of bias-adjusted rainfall projections resulting from different General Circulation Models/Regional Climate Models coupling, for multiple Representative Concentration Pathway scenarios (RCP 2.6, RCP 4.5 and RCP 8.5) and different future horizons (near, 2021-2050, and far, 2051-2080, future).

This research aims at understanding and analyzing the possible effect of climate change on the seasonal rainfall regime over Italy. First, rainfall patterns are identified by applying a clustering procedure based on the Self-Organizing Map, by adopting and comparing the results of different gridded datasets describing current climate (1981-2010). Second, for the identified clusters the impact of climate change in the near (2021-2050) and the far future (2051-2080) is assessed by employing an ensemble of bias-adjusted EUROCORDEX climate projections under the Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5. The results of this study show that, for the considered models’ ensemble, a significant decrease in cumulative rainfall values should be expected in the future, reflecting in a decrease in monthly values across all the seasons.

Soil erosion by water greatly affects Italy impacted by 24% of total soil loss of Europe, 33% of agricultural lands exposed, and costs, e.g. for crop production, up to about 600Meuro. Furthermore, expected increases in severity and magnitude of extreme precipitation events could exacerbate such an issue.In this regard, rainfall information at very fine spatial and temporal resolution represents a key point; unfortunately, weather stations are not spread uniformly across regions and they uncommonly provide free data at sub-daily scale. Moreover, the reliable projections of how rainfall will change in the coming decades are hard to store and manage for non-experts.In trying to overcome such a gap, Copernicus Climate Change Service (C3S) provides several tools. The C3S is part of the Copernicus Earth Observation Programme and is implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission. In particular, Climate Data Store (CDS) hosts rainfall time series for the historical period and most recent decades from observational (E-OBS) and reanalysis (ERA5, ERA5-Land, UERRA) datasets, at (sub) daily time step and with horizontal resolution ranging from 31 km to 5.5 km. For the future, the simulations’ ensemble within EURO-CORDEX (resolution ~12 km, daily time step) are available for robust evaluations, i.e. to consider the uncertainty due to alternative greenhouse gas concentration scenarios and model chain used.In this context, in the last months, C3S funded the Demo Case SOIL EROSION implemented by the CMCC Foundation and aimed at assessing ongoing and future soil loss by water erosion over Italy. The Demo Case is expected to develop further specific datasets and a web-application by exploiting products and tools also provided by Climate Data Store (CDS) infrastructure.To assess soil losses, the largely adopted Revised Universal Soil Loss Equation (RUSLE) is selected. Such an empirical equation combines rainfall erosivity (R-factor), evaluated in this case by exploiting datasets in CDS, to soil susceptibility to erosion due to soil intrinsic properties but also to land cover, land management, and topography. Gridded datasets related to R-factor and soil losses will be then made available within the CDS catalog. Moreover, the web application will permit visualizing and retrieving trends and results for specific areas (e.g. NUTS) in the way of maps and graphs. In addition to the "Basic" mode, the Application is expected to support "what-if" analysis ("Advanced" mode) permitting to understand how variations in land use (C-factor) or management practice (P-factor) can influence soil losses at large scale under current and future conditions.

In the present paper, a novel method is provided to detect significant daily consumption patterns and to obtain scaling laws to predict consumption patterns for groups of homogeneous users. The first issue relies on the use of Self-Organizing Map to gain insights about the initial assumption of distinct homogeneous consumption groups and to find additional clusters based on calendar dates. Non-dimensional pattern detection is performed on both residential and non-residential connections, with data provided by one-year measurements of a large-size smart water network placed in Naples (Italy). The second issue relies on the use of the variance function to explain the dependence of aggregated variance on the mean and on the number of aggregated users. Equations and related parameters’ values are provided to predict mean dimensional daily patterns and variation bands describing water consumption of a generic set of aggregated users.

Flooding is one of the most challenging weather-induced risks in urban areas. However, in a climate change perspective, significant gaps can still be observed in literature addressing the key role of rainfall input and related variability within urban flood impact models. The present research attempts to bridge this gap by investigating the effect of using a large ensemble of bias-corrected Euro-CORDEX climate projections on flood hazard estimations, with the goal of understanding the propagation of future climate variability in terms of flooding outputs for the urban environment. With this aim, a scenario analysis is performed for two return periods (10 and 200 years) building on nineteen climate projections for future horizon 2071–2100 under RCP 4.5 and 8.5 scenarios by means of CADDIES Caflood inundation model, using a test case in the City of Naples (Italy). Model outcomes are investigated and discussed in terms of relevant metrics and indicators available in literature targeting both general hazards, evaluated in terms of runoff volumes and flooded areas, and sectoral hazards, specified by a number of relevant literature hazard classifications. Modelling outcomes are analysed and normalised with respect to baseline values representing current climate conditions to emphasize potential impacts of climate change. Results show that flood features increase more slowly than rainfall, and the relationship between rainfall and flood increase is linear, with decreasing slope with increasing return period. Furthermore, the spread in rainfall input due to the use of different climate projections does not inflate through the impact modelling stages, albeit a dependence on the indicators used to model flood impacts can be observed. The outcomes of the research can be of aid to managers, designers and policy makers to understand the impacts of climate change in flood-prone urban areas and, in perspective, to adapt urban areas exploring the feasibility and effectiveness of solutions.

A pretreatment with H2O2 was conducted to improve the performance of the anaerobic digestion (AD) process for a partial treatment of tannery wastewater (TWW). Four different H2O2 dosages (0.5, 1, 2, and 4 g/L) were tested by adding to TWW different volumes of a 30% (m/v) H2O2 solution in order to improve the biodegradability of TWW organic load and decrease the total Cr concentration. Indeed, a less total Cr concentration was detected in pretreated samples that showed a minimum removal efficiency of 11% and a maximum removal efficiency of 41%. Moreover, several Biomethane Potential tests (BMP) were conducted to assess the enhanced biodegradability of pretreated TWW. Methane yields resulted in 594, 1151, 1090, 767, and 525 mL CH4/g TVS for the unpretrated TWW and for those pretreated with 0.5, 1, 2, and 4 g/L of H2O2, respectively. BMP tests proved that the best pretreatment condition for TWW, in terms of methane production and consequently total COD reduction, was achieved with a low dosage of H2O2 (0.5 g H2O2/L), corresponding to 1.0·10−4 g H2O2/g TVS and 3.2·10−5 g H2O2/g COD, whereas the highest dosage (4 g H2O2/L) was not related to the highest methane yield. Such contradictory results highlights the relevance of an appropriate dosage of H2O2, Finally, a kinetic study was also conducted.

Remote monitoring and collection of water consumption has gained pivotal importance in the field of demand understanding, modelling and prediction. However, most of the analyses that can be performed on such databases could be jeopardized by inconsistencies due to technological or behavioural issues causing significant amounts of missing or anomalous values. In the present paper, a nonparametric, unsupervised approach is presented to investigate the reliability of a consumption database, applied to the dataset of a district metering area in Naples (Italy) and focused on the detection of suspicious amounts of zero or outlying data. Results showed that the methodology is effective in identifying criticalities both in terms of unreliable time series, namely time series having huge amounts of invalid data, and in terms of unreliable data, namely data values suspiciously different from some suitable central parameters, irrespective of the source causing the anomaly. As such, the proposed approach is suitable for large databases when no prior information is known about the underlying probability distribution of data, and it can also be coupled with other nonparametric, pattern-based methods in order to guarantee that the database to be analysed is homogeneous in terms of water uses.

A methodological framework for the estimation of the expected value of hourly peak water demand factor and its dependence on the spatial aggregation level is presented. The proposed methodology is based on the analysis of volumetric water meter measurements with a 1-h time aggregation, preferred by water companies for monitoring purposes. Using a peculiar sampling design, both a theoretical and an empirical estimation of the expected value of the peak factor and of the related standard error (confidence bands) are obtained as a function of the number of aggregated households (or equivalently of the number of users). The proposed methodology accounts for the cross-correlation among consumption time series describing local water demand behaviours. The effects of considering a finite population is also discussed. The framework is tested on a pilot District Metering Area with more than 1000 households equipped with a telemetry system with 1-h time aggregation. Results show that the peak factor can be expressed as a power function tending to an asymptotic value greater than one for the increasing number of aggregated households. The obtained peak values, compared with several literature studies, provide useful indications for the design and management of secondary branched pipes of water distribution systems.

The runoff coefficient φ is a crucial parameter for flood peak discharge estimate in ungauged drainage basins. Tables and graphs generally allow the determination of φ in a somewhat empirical way that can lead to inconsistency in application; therefore, it is important to identify other parameters that can be utilized to assess φ more directly. In the present paper, focusing on Southern Continental Italy, a simple analytical expression between runoff coefficient φ and soil potential maximum retention S is proposed; moreover, an improvement of this expression is provided by considering the pre-event moisture condition of the watershed through the use of a climatic factor. At this aim, the US Soil Conservation Service classification for soil permeability has been adopted, that allows the evaluation of S, according to its relationship with the runoff curve number CN, as a function of soil type, land use and antecedent soil moisture condition (AMC).

This paper describes and discusses the available experimental investigations concerning vertical pipe flow in order to understand possible differences caused by different intake types and inflow conditions. Specific attention is given to the difference between drain pipes and overflow pipes and to the influence of the inflow conditions on the head-discharge relation. Data from the available literature are systematized and treated in a unified manner to provide a comprehensive view of possible flow regimes, among which four main types are selected, namely Borda free and full flow, governed by pipe cross section; weirlike flow, governed by pipe diameter; and full pipe flow, governed by pipe cross section and length. For each, both data from the literature and novel data are used to calibrate both dimensional and nondimensional head-discharge equations, along with prediction equations for the discharge coefficients. The equations describing the critical head, marking the passage to full pipe flow, and the vortex critical head, marking the passage to a vortex-free full pipe flow, are provided. © 2018 American Society of Civil Engineers.

In the present paper, different clustering techniques were applied to detect significant patterns describing single-household water consumption in a residential neighborhood of the City of Naples, basing on hourly time series aggregated at the monthly scale. Comparisons among results were performed by means of a selection of Clustering Validity Indices, that were adjusted to overcome a bias caused by sparsely populated clusters. The most performant cluster solution proved to be the one resulting from the application of a mixed strategy, namely a Self-Organized Map followed by K-means performed on first level cluster centroids.

The paper is focused on the optimal scheduling of a drainage pumping station, complying with variations in the pump rotational speed and a recurrent pattern for the inflow discharge. The paper is structured in several consecutive steps. In the first step, the experimental set-up is described and results of calibration tests on different pumping machines are presented to obtain equations linking significant variables (discharge, head, power, efficiency). Then, those equations are utilized to build a mixed-integer optimization model able to find the scheduling solution that minimizes required pumping energy. The model is solved with respect to a case study referred to a urban drainage system in Naples (Italy) and optimization results are analysed to provide insights on the algorithm computational performance and on the influence of pumping machine characteristics on the overall efficiency savings. With reference to the simulated scenarios, an average value of 32% energy can be saved with an optimized control. Its actual value depends on the hydraulic characteristics of the system.

In the present paper a procedure is introduced to detect water consumption patterns within water distribution systems. The analysis is based on hourly consumption data referred to single-household flow meters, connected to the Smart Water Network of Soccavo (Naples, Italy). The procedure is structured in two consecutive phases, namely clustering and classification. Clustering is performed on a selection of standardized monthly time series, randomly chosen within the database; different clustering models are tested, basing on K-means, dendrogram and Self-Organizing Map, and the most performant is identified comparing a selection of Clustering Validity Indices. Supervised classification is performed on the remaining time series to associate unlabeled patterns to the previously defined clusters. Final results show that the proposed procedure is able to detect annual patterns describing significant customers behaviors, along with patterns related to instrumental errors and to abnormal consumptions.

The runoff coefficient φ is a crucial parameter for the estimation of the mean value of annual maximum flood peak discharges in ungauged watersheds, where no direct measures are available. If the rational method is applied as a rainfall–runoff transformation model, the runoff coefficient accounts for all the hydrological losses, and it can be conceptually defined as the fraction of the total rainfall contributing to the flood peak response. In the present paper, focusing on Southern Peninsular Italy, a regression model is proposed to improve the prediction of the above defined runoff coefficient as a function of several parameters describing both morphological and mean annual climatic watershed characteristics. Morphological features are described by using the Soil Conservation Service permeability classification and the related variable S, referred to an average antecedent moisture condition. Different climatic indices enable a subsequent enhancement of S in order to account for the specific mean annual moisture condition of each watershed.

The present paper deals with a United States Bureau of Reclamation (USBR) Type II stilling basin, which is characterized by blocks at the end of the chute and a dentated sill at the end of the basin. For this basin, USBR only gives overall design criteria concerning basin length and block dimensions on the basis of the assumption that the hydraulic jump remains confined within the sill. No considerations are provided concerning possible different jump types, pressure regimes, and forces acting on the sill. To comply with such a lack, an experimental campaign was undertaken that focuses on the differences among hydraulic jump types that can occur in a USBR Type II stilling basin. Jump types can range between submerged and spray jump types; accordingly, dimensionless relations are provided to predict jump type and position for assigned boundary conditions, with particular concern about the submerged/nonsubmerged distinction. Considerations about the drag force and drag coefficients are provided, along with estimates of pressure extreme fluctuations. Finally, an evaluation of the dissipation efficiency is presented for both submerged and nonsubmerged jumps, enabling comparisons among different jump types and with classical hydraulic jump. - See more at: http://ascelibrary.org/doi/abs/10.1061/(ASCE)IR.1943-4774.0001150#sthash.ajmk3TuB.dpuf

An experimental analysis of a vertical drop shaft with a sharp-edged horizontal intake section and a coaxial venting pipe is undertaken to obtain design criteria given the limited attention provided by literature. Three different flow regimes are observed, namely weir flow and pressurized flow for extreme discharges and transitional flow for intermediate discharges. Particular attention is paid to transitional flow, which is a periodical regime consisting of an alternate switch from weir to pressurized flow, with water heads ranging between a maximum and a minimum. For transitional flow a detailed characterization of water surface oscillations is provided, and nondimensional equations are given describing mean water head, oscillation amplitude and frequency as functions of pipe Froude number and dimensionless plunged length of the coaxial pipe. Also, a region of existence is provided in terms of pipe Froude number and different wave types are identified. For weir flow, a nondimensional head-discharge relation is provided by analogy with overfalls.

The lack of geometrical and hydraulic information about sewer networks often excludes the adoption of in-deep modeling tools to obtain prioritization strategies for funds management. The present paper describes a novel statistical procedure for defining the prioritization scheme for preventive maintenance strategies based on a small sample of failure data collected by the Sewer Office of the Municipality of Naples (IT). Novelty issues involve, among others, considering sewer parameters as continuous statistical variables and accounting for their interdependences. After a statistical analysis of maintenance interventions, the most important available factors affecting the process are selected and their mutual correlations identified. Then, after a Box-Cox transformation of the original variables, a methodology is provided for the evaluation of a vulnerability map of the sewer network by adopting a joint multivariate normal distribution with different parameter sets. The goodness-of-fit is eventually tested for each distribution by means of a multivariate plotting position. The developed methodology is expected to assist municipal engineers in identifying critical sewers, prioritizing sewer inspections in order to fulfill rehabilitation requirements.

Water scarcity and the poor quality of water resources are leading to a wider diffusion of desalination plants using the Reverse Osmosis (RO) process. Unfortunately, the cost of a cubic meter of fresh water produced by an RO plants is still high and many efforts are in progress to increase the efficiency of the membranes used in osmotic plants and to limit the energy required by the process. A further reduction of the energy cost could be obtained by an optimal operation of the desalination plant so reducing the hourly energy cost, or by coupling the RO plant with an energy production plant based on direct osmosis (Pressure Retarded Osmosis PRO). The economic viability of the desalination process has been analyzed until now without accounting for the integration of the RO plant with the existing water network. This analysis is developed in the present paper with reference to a hypothetical change of water supply in a real network, where a desalination plant is used to satisfy the fresh water demand. Several scenarios will be analyzed to assess the minimum cost of fresh water production and water supply to the network, including the use of energy recovery systems, such as an integrated use of RO and PRO processes, or the regulation of pressure at the network intake by a micro hydro power plant.

An integrated Visual Basic Application interface is described that allows for sensitivity analysis, calibration and routing of hydraulichydrological models. The routine consists in the combination of three freeware tools performing hydrological modelling, hydraulic modelling and calibration. With such an approach, calibration is made possible even if information about sewers geometrical features is incomplete. Model parameters involve storage coefficient, time of concentration, runoff coefficient, initial abstraction and Manning coefficient; literature formulas are considered and manipulated to obtain novel expressions and variation ranges. A sensitivity analysis with a local method is performed to obtain information about collinearity among parameters and a ranking of influence. The least important parameters are given a fixed value, and for the remaining ones calibration is performed by means of a genetic algorithm implemented in GANetXL. Single-event calibration is performed with a selection of six rainfall events, which are chosen so to avoid non-uniform rainfall distribution; results are then successfully validated with a sequence of four events.

The results of an experimental analysis are provided concerning the hydraulic behaviour of a vertical drop shaft with a sharp-edged circular intake, also taking into account a peculiar venting system consisting of a coaxial vertical pipe, projecting within the drop shaft with different plunging lengths. Three different flow regimes are experienced: a “weir flow” for low head values, where an air–water mixture at the atmospheric pressure can be observed; a “pressurized flow” for high head values, where water flows in a pressurized regime along the shaft; a “transitional flow” for intermediate water head values, consisting of a continuous, spontaneous switch between weir flow and pressurized flow with consequent water head variation for a fixed discharge. Pressurized flow regime is analytically explained, so that a head–discharge relation can be provided both for the non-vented and for the vented configurations, with specific assumptions about intake losses.

A simple analytical method is proposed that allows a preliminary evaluation of the overall efficiency of a detention basin system for flood risk reduction in a specific target section. Solutions are provided both for parallel and series systems, under some simplifying assumptions concerning the linearity of detention basin, river network and watershed responses. Further, for the series configuration a regressive model is proposed for the computation of the overall efficiency, because of the complexity of analytical solution. A case study is also presented, where the overall efficiency of a system of nine detention basins is computed by means of both the analytical and the regressive model. Results are discussed to assess the different influence of detention basins in parallel or in a series system.

Roberta Padulano *, Giuseppe Del Giudice and Armando CarravettaDepartment of Civil, Architectural and Environmental Engineering, Universita di Napoli Federico II,Via Claudio 21, 80125 Naples, Italy; E-Mails: delgiudi@unina.it (G.D.G.);armando.carravetta@unina.it (A.C.)* Author to whom correspondence should be addressed; E-Mail: roberta.padulano@unina.it;Tel.: +39-081-768-3462; Fax: +39-081-593-8936.Received: 11 July 2013; in revised form: 16 August 2013 / Accepted: 3 September 2013 /Published: 12 September 2013Abstract: An experimental campaign is undertaken in order to investigate the hydraulicfeatures of a vertical drop shaft, also considering the influence of a venting system consistingof a coaxial vertical pipe, projecting within the drop shaft with different plunging rates. Threedifferent flow regimes are observed: a “weir flow” for very low head values, where the flowprofile is subject to the atmospheric pressure; a “full flow” for high head values, wherewater flows in a pressurized regime along the whole shaft; and a “transitional flow” forintermediate water head values. Weir flow and full flow can be experimentally investigatedunder steady-state conditions, whereas transitional flow is a pulsating condition, alternatelyswitching from full flow to weir flow. Considering some significant geometric parameters, ahead-discharge relation is sought both for the non-vented and for the vented configurations,by means of an energy balance equation, with specific assumptions about intake losses.Keywords: drop shaft; friction losses; intake losses; pipe Froude number; full flow;weir flow; transitional flow; cavitation1. IntroductionThe evolution of urban texture, along with urban growth, usually leads to the improving and upgradingof existing infrastructures, such as sewer systems. In particular, the increase in the impervious percentageof urban catchment areas implies an increase in surface runoff, which can cause malfunctioning in urbandrainage systems, such as basement or street flooding, manhole cover blow-off, up to structural problems.

In urban drainage systems, it is usually necessary to split the stormwater discharge among different sewer branches because of limited flow capacity of either hydraulic structures or sewer lines. For this purpose sewer sideweirs and leaping weirs are generally used as diversion overflow structures. For supercritical approach flow the former is not recommended because of the occurrence of hydraulic jumps, while the latter requires an outlet located below the approach flow sewer bottom. To overcome these constraints a novel compact hydraulic structure is proposed. It consists of a frontal rectangular intake, representing the diversion sewer inlet, located in the approach flow sewer and parallel to its bottom. A 6.67:1 scale model was tested over a range of hydraulic and geometrical parameters to determine its head-discharge relationship, developing a dimensionless equation relating the diversion discharge to the geometrical properties of the intake under supercritical flow conditions. The limited hydraulic structure size provides cost-effectiveness as well as ease of installation and maintenance.

The present paper describes the experimental campaign carried on the physical model of the spillway of Lower Diamphwe Dam (Malawi), which is provided with a USBR type II stilling basin. Stilling basins are used in order to reduce the excessive kinetic energy of flowing water downstream of spillways. Specifically, a USBR type II basin is provided with blocks at the end of the chute and with a confining dentated sill; these appurtenances allow to dissipate excess energy with high efficiency. The study focuses on the hydraulic behavior of the stilling basin; tests were carried on for different values of incoming discharge and downstream water depth. Results show the dissipation efficiency of the stilling basin in terms of pressure fluctuation and the variability of the jump type with the hydraulic characteristics of the incoming and the downstream flow depths.