In the last few years, some regions of the Mediterranean area have witnessed a progressive increase in extreme events, such as urban and flash floods, as a response to the increasingly frequent and severe extreme rainfall events, which are often exacerbated by the ever-growing urbanization. In such a context, the urban drainage systems may not be sufficient to convey the rainwater, thus increasing the risk deriving from the occurrence of such events. This study focuses on a particularly intense urban flood that occurred in Palermo (Italy) on 15 July 2020; it represents a typical pluvial flood due to extreme rainfall on a complex urban area that many cities have experienced in recent years, especially in the Mediterranean region. A conceptual hydrological model and a 2D hydraulic model, particularly suitable for simulations in a very complex urban context, have been used to simulate the event. Results have been qualitatively validated by means of crowdsourced information and satellite images. The experience of Palermo, which has highlighted the urgent need for a shift in the way stormwater in urban settlements is managed, can be assumed to be a paradigm for modeling pluvial floods in complex urban areas under extreme rainfall conditions. Although the approaches and the related policies cannot be identical for all cities, the modeling framework used here to assess the impacts of the event under study and some conclusive remarks could be easily transferred to other, different urban contexts.

Among the indirect estimation approaches of soil water content in the upper layer of the soil, the “triangle method” is one of the most common that relies on the simple relationship between the optical and thermal features sensed via Earth Observation. These features are controlled by water content at the surface and within the root zone but also by meteorological forcing including air temperature and humidity, as well as solar radiation. Night- and day-time MODIS composites of land-surface temperature (LST) allowed applying a version of the triangle method that takes into account the temporal admittance of the soil. In this study, it has been applied to a long time-series of pair images to analyze the seasonal influence of the meteorological forcing on a triangle method index (or temperature–vegetation index, TVX), as well as to discuss extra challenges of the diachronic approach including seasonality effects and the variability of environmental forcing. The Imera Meridionale basin (Sicily, Italy) has been chosen to analyze the method over a time-series of 12 years. The analysis reveals that, under these specific environmental and climatic conditions (strong seasonality and rainfall out of phase with vegetation growth), Normalized Difference Vegetation Index (NDVI) and LST pairs move circularly in time within the optical vs. thermal feature space. Concordantly, the boundaries of the triangle move during the seasons. Results showed a strong correlation between TVX and rainfall normalized amplitudes of the power spectra (r2 ~0.8) over the range of frequencies of the main harmonics.

Tsunamis are among the most dangerous natural disasters for coastal areas experiencing tsunami hazard. One of the major concerns in the assessment of strategies for the risk mitigation is to estimate vulnerability of structures and infrastructures. However, reliable approaches for the evaluation of the structural capacity under tsunami loads are nowadays not always available for all the types of structures, especially masonry. On this aim, the paper deals with the modeling issues of 3D masonry structures subjected to tsunami loads and the effect on the structural behavior of different modeling approaches. First, a brief state of the art on the available studies is presented regarding the evaluation of tsunami forces on buildings and the studies carried out on the determination of structural capacity. Then, an advanced structural analysis software based on the Finite Element Method (FEM) is used to analyze the influence of parameters such as load type, masonry type and interaction properties type. Finally, an application on a typical two-storey masonry structure subjected to tsunami load according to the actual codes is presented and discussed, providing recommendations on the assumptions to be made for the definition of a reliable numerical model. The findings of the numerical simulations revealed that the structural response is strongly influenced by the modeling approach defined for the masonry walls in terms of interaction properties and the type of connection between orthogonal walls. Moreover, it was observed that, as for the case of seismic analysis, when local behavior governs the failure, lower structural capacity is obtained, while in the case of global behavior governing the failure, higher structural performances are provided.

For a large part of human history, urbanization was focused on two main objectives: defence and resource harvesting. The first objective was always achieved in a broad sense, i.e., defending the population from other humans and from natural events. Focusing on human activities, this defensive approach was also applied to urban drainage, which resulted in a systematic underestimation of the impacts of urbanization on natural systems. Environmental sustainability was introduced in an attempt to mitigate these impacts, as they had the potential to endanger future developments; thus, the possibility that urban floods may be the lesser evil was accepted. Resilience was then introduced to improve not only defence of urban areas but also their ability to recover from negative events, even though physical resilience is not always accompanied by social resilience. This paper attempts to address the philosophy of urban drainage design, introducing the new concept offloodabilityas an evolution of flood resilience by identifying its requirements and drivers and by using real examples to present the new concept.

Gully erosion is a form of accelerated erosion that may affect soil productivity, restrict land use, and lead to an increase of risk to infrastructure. An accurate mapping of these landforms can be difficult because of the presence of dense canopy and/or the wide spatial extent of some gullies. Even where possible, mapping of gullies through conventional field surveying can be an intensive and expensive activity. The recent widespread availability of very high resolution (VHR) imagery has led to a remarkable growth in the availability of terrain information, thus providing a basis for the development of new methodologies for analyzing Earth's surfaces. This work aims to develop a geographic object-based image analysis to detect and map gullies based on VHR imagery. A 1-meter resolution LIDAR DEM is used to identify gullies. The tool has been calibrated for two relatively large gullies surveyed in the Calhoun Critical Zone Observatory (CCZO) area in the southeastern United States. The developed procedure has been applied and tested on a greater area, corresponding to the Holcombe's Branch watershed within the CCZO. Results have been compared to previous works conducted over the same area, demonstrating the consistency of the developed procedure.

Remote sensing allowed monitoring the reservoir water level by estimating its surface extension. Surface extension has been estimated using different approaches, employing both optical (Landsat 5 TM, Landsat 7 ETM+ SLC-Off, Landsat 8 OLI-TIRS and ASTER images) and Synthetic Aperture Radar (SAR) images (Cosmo SkyMed and TerraSAR-X). Images were characterized by different acquisition modes, geometric and spectral resolutions, allowing the evaluation of alternative and/or complementary techniques. For each kind of image, two techniques have been tested: The first based on an unsupervised classification and suitable to automate the process, the second based on visual matching with contour lines with the aim of fully exploiting the dataset. Their performances were evaluated by comparison with water levels measured in situ (r2 = 0.97 using the unsupervised classification, r2 = 0.95 using visual matching) demonstrating that both techniques are suitable to quantify reservoir surface extension. However ~90% of available images were analyzed using the visual matching method, and just 37 images out of 58 using the other method. The evaluation of the water level from the water surface, using both techniques, could be easily extended to un-gauged reservoirs to manage the variations of the levels during normal operation. In addition, during the period of investigation, the use of Global Navigation Satellite System (GNSS) allowed the estimation of dam displacements. The advantage of using as reference a GNSS permanent station positioned relatively far from the dam, allowed the exclusion of any interaction with the site deformations. By comparing results from both techniques, relationships between the orthogonal displacement component via GNSS, estimated water levels via remote sensing and in situ measurements were investigated. During periods of changing water level (April 2011–September 2011 and October 2011–March 2012), the moving average of displacement time series (middle section on the dam crest) shows a range of variability of ±2 mm. The dam deformation versus reservoir water level behavior differs during the reservoir emptying and filling periods indicating a hysteresis-kind loop.

Fluvial, pluvial and coastal flooding are the most frequent and costly natural hazard. Cities are social hubs and life in cities is reliant on a number of services and functions such as housing, healthcare, education and other key daily facilities. Urban flooding can cause significant disruption to these services and wider impacts on the population. These impacts may be short or long with a variably spatial scale: urban systems are spatially distributed and the nature of this can have significant effects on flood impacts. From an urban-planning perspective, measuring this disruption and its consequences is fundamental in order to develop more resilient cities. Whereas the assessment of physical vulnerabilities and direct damages is commonly addressed, new methodologies for assessing the systemic vulnerability and indirect damages at the urban scale are required. The proposed systemic approach recognizes the city as a collection of sub-systems or functional units (such as neighborhoods and suburbs), interconnected through the road network, providing key daily services to inhabitants (e.g., healthcare facilities, schools, food shops, leisure and cultural services). Each city is part of broader systems—which may or may not match administrative boundaries—and, as such, needs to be connected to its wider surroundings in a multi-scalar perspective. The systemic analysis, herein limited to residential households, is based on network-accessibility measures and evaluates the presence, the distribution among urban units and the redundancy of key daily services. Trying to spatially sketch the existence of systemic interdependences between neighborhoods, suburbs and municipalities, the proposed method highlights how urban systemic vulnerability spreads beyond the flooded areas. The aim is to understand which planning patterns and existing mixed-use developments are more flood resilient, thereby informing future urban development and regeneration projects. The methodology has been developed based on GIS and applied to an Italian municipality (Noale) in the metropolitan area of Venice, NE Italy.

Actual evapotranspiration is assessed via surface energy balance at an hourly rate. However, a robust estimation of daily evapotranspiration from hourly values is required. Outcomes of surface energy balance are frequently determined via measures of eddy covariance latent heat flux. Surface energy balance can be applied on images acquired at different times and spatial resolutions. In addition, hourly actual evapotranspiration needs to be integrated at a daily rate for operational uses. Questions arise whether the validation of surface energy balance models can benefit from complementary in situ measures of latent heat flux and sap flow transpiration. Here, validation was driven by image acquisition time, spatial resolution, and temporal integration. Thermal and optical images were collected with a proximity-sensing platform on an olive orchard at different acquisition times. Actual latent heat fluxes from canopy and sap flux at tree trunks were measured with a flux tower and heat dissipation probes. The latent heat fluxes were then further analyzed. A surface energy balance was applied over proximity sensing images re-sampled at different spatial resolutions with resulting latent heat fluxes compared to in situ ones. A time lag was observed and quantified between actual latent heat fluxes from canopy and sap flux at the tree trunk. Results also indicate that a pixel resolution comparable to the average canopy size was suitable for estimating the actual evapotranspiration via a single source surface energy balance model. Images should not be acquired at the beginning or the end of the diurnal period. Findings imply that sap flow transpiration can be used to measure surface energy balance at a daily rate or when images are found at an hourly rate near noon, and the existing time lag between the latent heat flux at the canopy and the sap flow at the trunk does not need to be taken into account.

The pressure sensors positioning is a crucial step for leakages detection. The optimal positioning of monitoring sensors, or simply sampling design, has been previously addressed with respect to several purposes. The proposed methodology aims to select the pressure monitoring nodes for leakages detection by coupling the water distribution network hydraulic simulation model with the identifiability analysis. The nodes selection is done among those which are more sensitive with respect to different leakages positions and uncorrelated from each other to avoid redundant information. The parameter uncertainty effect on the results is also investigated. The method is applied to the benchmark network Apulian.

Recently, it has been demonstrated that it is possible to relate water levels of a reservoir with its dam displacements. Water levels were determined via remote sensing, while dam displacements were measured via Global Navigation Satellite System (GNSS). Results have shown that displacements and water levels are correlated.Water levels at the Magazzolo reservoir in southern Italy were firstly retrieved using two remote sensing approaches: by visual matching between the reservoir shoreline and contour lines, and by evaluating the surface extent via unsupervised classification to estimate the water levels with an area/depth relation. Dam displacements were measured using GPS receivers on the dam and a permanent station from a GNSS Continuously Operating Reference Stations (CORS) network, about 30 kilometers away.Subsequently, two other remote sensing approaches were tested to detect reservoir levels; the first based on shape similarity indices, while the second on the evaluation of the average distance between a reservoir shoreline and contour levels. First results were extracted from a Landsat 8 optical image acquired during a clear sky day. Within this work, algorithms for water level retrieval have been tested and validated under different conditions over a more consistent satellite dataset including Sentinel-1A Synthetic Aperture Radar (SAR) images acquired from October 2014 to September 2015. The dataset is also used to analyses dam displacements via Interferometric SAR (InSAR), to be compared with the effects of water level fluctuations on the dam. First results suggest that it is possible to correlate dam displacements and water levels derived by the same dataset. However, it is shown that displacements also depend on meteorological forcing.

Changes in climate and urban growth are the most influential factors affecting hydrological characteristics in urban and extra-urban contexts. The assessment of the impacts of these changes on the extreme rainfall-runoff events may have important implications on urban and extra-urban management policies against severe events, such as floods, and on the design of hydraulic infrastructures. Understanding the effects of the interaction between climate change and urban growth on the generation of runoff extremes is the main aim of this paper. We carried out a synthetic experiment on a river catchment of 64km(2) to generate hourly runoff time series under different hypothetical scenarios. We imposed a growth of the percentage of urban coverage within the basin (from 1.5% to 25%), a rise in mean temperature of 2.6 degrees C, and an alternatively increase/decrease in mean annual precipitation of 25%; changes in mean annual precipitation were imposed following different schemes, either changing rainstorm frequency or rainstorm intensity. The modelling framework consists of a physically based distributed hydrological model, which simulates fast and slow mechanisms of runoff generation directly connected with the impervious areas, a land-use change model, and a weather generator. The results indicate that the peaks over threshold and the hourly annual peaks, used as hydrological indicators, are very sensitive to the rainstorm intensity. Moreover, the effects of climate changes dominate on those of urban growth determining an exacerbation of the fast runoff component in extreme events and a reduction of the slow and deep runoff component, thus limiting changes in the overall runoff.

To obtain the flooding frequency distribution for an urban watershed, different methods based on simulations of synthetic rainfall events were compared with an empirical analysis of the flooding data and with the results of long‐term simulations. A copula‐based multivariate statistical analysis of the main hydrological variables was proposed to generate synthetic hyetographs. Two different approaches were adopted to assess a temporal pattern to the synthetic rainfall: one analyses all available historical rainfall patterns, and another adopts the cluster analysis in three different variants to reduce the computational effort of the analysis.To test the methodology reliability, the analysis was carried out for a real urban watershed. To carry out the flooding frequency analysis, all generated synthetic hyetographs were used as input of a dual drainage mathematical model of the analysed drainage system. Results showed that the method based on the analysis of all historical rainfall patterns was efficient in the estimation of flooding frequency, especially for higher return periods and approximately halved the computational costs of ordinary long‐term analysis. Regarding clustering approaches, although attractive for their computational efficiency, their adoption must be carefully evaluated because it could neglect relevant information and result in a less accurate flood frequency analysis.

Monitoring dam displacements using different techniques allows an evaluation of their structural behaviour over time. In this study, dam displacements (for the Castello dam, Agrigento, Italy) have been investigated using different Interferometric Synthetic Aperture Radar (InSAR) techniques exploiting a freely available dataset from the EU Copernicus Sentinel-1 SAR built by the European Space Agency (ESA). The dataset includes Sentinel 1A (S1A) images acquired in dual-polarization and Interferometric Wide (IW) swath using the Terrain Observation with Progressive Scans SAR (TOPSAR) mode. Three main Multi-Baseline Construction methods based on the identification of Persistent Scatterers (PS) have been tested, within a scene including an extra-urban area surrounding the dam. The evaluation of the best strategy is carried out over few images (7) with a constant acquisition time-span of 12 days, except for the first image, acquired 24 days before the next one. Three different multi-baseline construction methods have been investigated in this preliminary research to test the capability of these InSAR techniques in finding a time series of displacements with high accuracy in extra-urban areas also. The star graph results in displacement appear to be more in agreement with GNSS measurements than other techniques.

The knowledge of spatial and temporal variability of soil water content and others soil-vegetation variables (leaf area index, fractional cover) assumes high importance in crop management. Where and when the cloudiness limits the use of optical and thermal remote sensing techniques, synthetic aperture radar (SAR) imagery has proven to have several advantages (cloud penetration, day/night acquisitions and high spatial resolution). However, measured backscattering is controlled by several factors including SAR configuration (acquisition geometry, frequency and polarization), and target dielectric and geometric properties. Thus, uncertainties arise about the more suitable configuration to be used. With the launch of the ALOS Palsar, Cosmo-Skymed and Sentinel 1 sensors, a dataset of multi-frequency (X, C, L) and multi-polarization (co- and cross-polarizations) images are now available from a virtual constellation; thus, significant issues concerning the retrieval of soil-vegetation variables using SAR are: (i) identifying the more suitable SAR configuration; (ii) understanding the affordability of a multi-frequency approach. In 2006, a vast dataset of both remotely sensed images (SAR and optical/thermal) and in situ data was collected in the framework of the AgriSAR 2006 project funded by ESA and DLR. Flights and sampling have taken place weekly from April to August. In situ data included soil water content, soil roughness, fractional coverage and Leaf Area Index (LAI). SAR airborne data consisted of multi-frequency and multi-polarized SAR images (X, C and L frequencies and HH, HV, VH and VV polarizations). By exploiting this very wide dataset, this paper, explores the capabilities of SAR in describing four of the main soil-vegetation variables (SVV). As a first attempt, backscattering and SVV temporal behaviors are compared (dynamic analysis) and single-channel regressions between backscattering and SVV are analyzed. Remarkably, no significant correlations were found between backscattering and soil roughness (over both bare and vegetated plots), whereas it has been noticed that the contributions of water content of soil underlying the vegetation often did not influence the backscattering (depending on canopy structure and SAR configuration). Most significant regressions were found between backscattering and SVV characterizing the vegetation biomass (fractional cover and LAI). Secondly, the effect of SVV changes on the spatial correlation among SAR channels (accounting for different polarization and/or frequencies) was explored. An inter-channel spatial/temporal correlation analysis is proposed by temporally correlating two-channel spatial correlation and SVV. This novel approach allowed a widening in the number of significant correlations and their strengths by also encompassing the use of SAR data acquired at two different frequencies.

The matching between reservoirs’ water edge and digital elevation model’s (DEM) contour lines allowed determining the water level at the acquisition date of satellite images. A preliminary study was conducted on the Castello dam (Magazzolo Lake), between Alessandria della Rocca and Bivona (Agrigento, south-Italy). The accuracy assessment of the technique was than evaluated from the comparison between classified and reference objects using similarity metrics about the shape, theme, edge and position, through the plugin STEP of open source software GIS. Moreover, an independent GIS technique was implemented to evaluate the water level, based on a distances’ array between existing contour lines and nodes extracted from vectorised classification images. Results have shown the potentiality of the techniques when applied on an ideal case; advantages and disadvantages when the images are characterized by clear sky, and limits when images are acquired during not ideal atmospheric conditions.

The optimization and management of an integrated urban wastewater system is a complex problem involving many processes and variables. The possible control options are defined by several management strategies that may differently impact the economic, operational or environmental performance of the system. The present paper aims to contribute to the environmental and energy sustainability of urban wastewater systems by means of a multicriteria performance analysis. The paper begins with a complete analysis of the system performance in several fields of interest (energy, environment, quality of service, operation, economy and financial resources), and it highlights the management strengths and weaknesses in each subsystem. The analysis was carried out by means of a prototype, developed during the ALADIN project, which enables understanding the system, planning effective improvement actions and assessing their possible effects in each part of the urban water cycle. To demonstrate the potential of such an approach, it was tested on an actual integrated urban wastewater system in Sicily.