water

Article Flood Modeling and Groundwater Flooding in Urbanized Reclamation Areas: The Case of ()

Corrado P. Mancini, Stefano Lollai, Elena Volpi and Aldo Fiori *

Department of Engineering, Roma Tre University, 00154 Roma, Italy; [email protected] (C.P.M.); [email protected] (S.L.); [email protected] (E.V.) * Correspondence: aldo.fi[email protected]

 Received: 20 June 2020; Accepted: 15 July 2020; Published: 17 July 2020 

Abstract: Coastal regions below the sea level, subject to reclamation, are becoming more and more exposed to flooding following increasing urbanization and hydrological changes. In these areas, groundwater and water table dynamics during intense rainfall events can be an important component of flooding and inundation, leading to groundwater flooding. Thus, the commonly employed hydrological models based on only the surface component of flow may result in a poor estimation of the extension and persistence of inundation events. We introduce here a simple and parsimonious approach for handling the groundwater contribution to flooding in such areas, which can be easily implemented and introduced into surface hydraulic models for flood management and the delineation of inundation maps. The approach involves few relevant parameters, requiring a minimum of information regarding the hydrogeological setup. The method is exemplified through the flood analysis of a wide reclamation area located in the southern part of Rome, Italy. The introduction of the groundwater component could explain the large water volumes pumped by the stations, which are much larger than excess rainfall. The application confirmed the validity of the proposed approach, emphasizing the important role played by groundwater to flooding in areas similar to the one considered here.

Keywords: floods; inundation map; groundwater flooding; reclamation areas; 2D flood models; Rome (Italy);

1. Introduction Low-elevation coastal areas are home to more than 600 million people, that is, roughly one in 10 people in the world live in such territories [1]. It turns out that two thirds of world’s largest cities, i.e., those with more than five million people, are located (at least partially) in these low areas. According to the United Nations [2], nine of the ten largest urban agglomerations in the world are located in deltas or floodplain areas. Floodplains usually offer favorable conditions for urban and economic development, and they have therefore attracted human settlements over the years. Small urban settlements evolve into dense cities, and are then vulnerable to high-consequence and low-probability events [3,4]. In such cases, structural and/or non-structural measures are required to control floods and reduce flood losses. Flooding is estimated to affect more people globally than any other natural hazard, with an average of 250 million people affected annually [5]. Overland flooding, e.g., caused by insufficient river capacity, has long been recognized as a risk, and is commonly included in land-use policies and insurance risk considerations [6,7]. Hazard maps and policies, generally based on flood recurrence intervals for design river discharges, are typically based on overland flooding, which is mainly studied using the

Water 2020, 12, 2030; doi:10.3390/w12072030 www.mdpi.com/journal/water Water 2020, 12, 2030 2 of 16 tools available in surface hydrology, leading to either pluvial (i.e., direct runoff from rainfall) and/or river flooding (due to overflow from rivers and channels). Of particular interest are the coastal regions below sea level that were originally wetlands and have been reclaimed by lowering the groundwater level by pumping. Such coastal areas are widespread and have been the subject of intensive urbanization over the years, and are becoming more and more exposed to flooding. In those areas, groundwater and the water table dynamics during intense rainfall events can be an important component of flooding and inundation. Such behavior is called groundwater flooding, which is defined as the “emergence of groundwater at the ground surface away from perennial river channels or the rising of groundwater into man-made ground, under conditions where the ‘normal’ ranges of groundwater level and groundwater flow are exceeded” [8–10]. Flood damage can occur before the rise of the water table to the ground surface, e.g., in the case of inundation of subsurface structures (i.e., basements) by groundwater [7], or the rise of the water table due to riverbank filtration [11]. When compared to overland flooding, groundwater flooding is inadequately recognized and poorly understood worldwide [12], with the possible exception of the EU Flood Directive in 2007 [13]. In comparison to fluvial and pluvial flooding, flooding from groundwater has only recently been given adequate consideration following groundwater floods in Northern and Central Europe in the past two decades [14–17]. The available studies on groundwater flooding are rather scattered, with many dealing with different groundwater processes and case studies (e.g., References [18–22]). In this work, we dealt with groundwater flooding determined by the sudden rise of the water table due to intense direct precipitation, as is characteristic in low areas, and particularly in coastal zones subject to reclamation. The latter are areas below sea level and are typically characterized by a network of natural and artificial channels, usually connected to the groundwater table, that drain water to a pumping station or a network of stations. Such systems keep the groundwater levels below the ground, and the drained water is further delivered to the sea by a system of channels. The pumps usually operate automatically as a function of the water levels in the pump chambers. The water level in the channels displays a sudden increase after rainfall due to runoff, which in turn recharges the aquifer by infiltration. Thus, when rainfall is intense and the water table is high, the dewatering stations receive both surface water and groundwater feeding the channels. As a consequence, the volume pumped is potentially larger than the total rain that has fallen on the surface catchment, being also impacted by the size of the hydrogeological (groundwater) basin. The correct assessment of the flooding risk conditions in such areas, and the subsequent design of any mitigation measures, therefore requires the implementation of suitable hydrological and hydraulic models capable of representing in a robust, possibly parsimonious way (i) the joint surface–subsurface hydrological processes and (ii) the specific role played by the drainage network and the pumping stations, of which the (often limited) capacity determines the effective drainage of rainwater and the extension of the inundated areas. This is in contrast with the common practice of employing modeling approaches for flooding based on surface hydrological/hydraulic dynamics, typically neglecting the groundwater component [23]. In the present work, we introduce a simple approach for handling the groundwater contribution to flood in reclaimed areas, which can be easily implemented and introduced into surface hydraulic models for flood management and the delineation of inundation maps. The approach aims at integrating the groundwater contribution to flooding in a parsimonious manner, with few relevant parameters, requiring a minimum of information regarding the hydrogeological setup. The approach differs from other approaches involving direct groundwater simulations (e.g., References [7,15]) or from combined, fully numerical surface/groundwater modeling (e.g., Reference [18]); such approaches are more complex than the one employed here, requiring significant information, data, and computational resources. The proposed method was exemplified through the flood analysis and delineation of the inundation maps of a wide reclamation area located in the southern part of Rome, Italy, emphasizing the important role played by groundwater in flooding. Water 2020, 12, x FOR PEER REVIEW 3 of 16

2. Site Description The study area is located in southern Rome, Italy (Figure 1), along the Tyrrenian coast. The region includes a wide catchment that drains water to zones with elevations below the sea level; in the past, it was a wetland, with groundwater levels partially above the ground. The land was reclaimed in the previous century via the realization of a network of channels connected to a series Water 2020of pumping, 12, 2030 stations. The area has seen a very intense urbanization in recent years, with an 3increasing of 16 population during the past century, and it is now incorporated into the municipality of Rome. The site has experienced several floods due to the insufficient transport capacity of the drainage 2. Site Description channels and the pumping stations, and it is frequently inundated, with a relatively small return Theperiod study of the area events. is located The inoverall southern area Rome, was divided Italy (Figure for simplicity1), along theinto Tyrrenian two major coast. zones, The as region depicted in includesFigure a wide 1c (the catchment elevation that map drains is provided water to zonesin Figure with 1d, elevations where the below areas the below sea level; sea level in the are past, evident): it was a(i) wetland, the areas with at higher groundwater altitudes levels (hereinafter partially high above areas, the or ground. HA), draining The land water was by reclaimed gravity directly in the into previousthe century Tyrrhenian via the Sea realization through ofa system a network of of natural channels and connected artificial to channels a series; ofand pumping (ii) the stations. part of the The areacatchment has seen draining a very intense water urbanizationinto areas below in recent the years,sea level with (low anincreasing areas, or populationLA), for which during relies the on a past century,system of and pumps it is now that incorporateddeliver the excess into the water municipality collected by of the Rome. channel network to the sea.

FigureFigure 1. The 1. study The study area (areac), with (c), itswith location its location within within the Italian the Italian territory territory (a) and (a) the and the Lazio region region (b); (b); the highthe andhigh low and areas low a andreas their and drainagetheir drainage networks networks are represented are represented by solid by lines;solid lines; the dots the displaydots display the dewateringthe dewatering pumping pumping stations. stations. The shadedThe shaded high areashigh a werereas were studied studied and modeled and modeled in a previous in a previous work [work24]. The [24]. topography The topography of the studyof the area study (d) area clearly (d) shows clearly the shows zones the with zones elevation with belowelevation sea level.below sea The redlevel. star The in panel red star (d) in is thepanel center (d) is position the center of theposition sub-area of the represented sub-area represented in Figure 6. in Figure 6.

The siteThe has area experienced under consideration several floods covers due an to are thea insu of approximatelyfficient transport 36 capacitykm2, of which of the drainageabout 13 km2 channelsflows and towards the pumping the sea or stations, is moved and by it isgravity frequently (HA) inundated,and the remain withing a relatively 23 km2 requires small return pumping, periodwhich of the is events.performed The overallby four areamain was pumping divided stations: for simplicity Ostiense into (catchment two major of zones, about as 9 depictedkm2), Stagni in (10 Figurekm1c2), (the Bagnolo elevation (2 km map2), isand provided Tor San in Michele Figure1 (aboutd, where 2 km the2). areas The belowwater seadynamics level are in evident):the HA of (i) higher the areaselevation at higher (shaded altitudes area (hereinafter in Figure 1 high), with areas, an area or HA), 57 km draining2, were water studied by gravityand modeled directly in into a previous the Tyrrhenianwork [24]. Sea through a system of natural and artificial channels; and (ii) the part of the catchment draining waterThe hydrological into areas below and thehydraulic sea level models (low areas, employed or LA), in for the which present relies study on arequired system ofa pumpspreliminary that delivercampaign the excessto acquire water the collected data needed by the for channel an accurate network description to the sea. of the transport capacity of the 2 2 Theexisting area drainage under consideration network and covers the hydraulic an area characterization of approximately of 36the km area, of. Such which information about 13 kmincluded 2 flowsthe towards characteristics the sea or is of moved the urbanization,by gravity (HA) the and structure the remaining of the 23 km drainagerequires networks, pumping, the which various 2 2 is performedinterconnections, by four main the hydraulic pumping cross stations:-sections Ostiense, and (catchment the state of of conservation about 9 km of), Stagnithe canalizations, (10 km ), as Bagnolo (2 km2), and Tor San Michele (about 2 km2). The water dynamics in the HA of higher elevation 2 (shaded area in Figure1), with an area 57 km , were studied and modeled in a previous work [24]. The hydrological and hydraulic models employed in the present study required a preliminary campaign to acquire the data needed for an accurate description of the transport capacity of the existing drainage network and the hydraulic characterization of the area. Such information included the characteristics of the urbanization, the structure of the drainage networks, the various interconnections, the hydraulic cross-sections, and the state of conservation of the canalizations, as Water 2020, 12, 2030 4 of 16 well as the characteristics of the intersections with the other civil infrastructures together with the hydraulic characteristics of the draining systems. This intense campaign covered the entire network of the reclamation channels, a total of 100 channels, and overall involved the survey of

more than 95 km of drainage channels (riverbed and bank profiles), • more than 1250 sections of the remediation channels, • more than 500 structures (bridges, manholes, weirs, etc.), including more than 300 bridges. • The network of the main and secondary channels previously illustrated has a total extension of 97.56 km and is in several cases interconnected. As previously stated, the study area has been subject to several floods, mainly due to the absence of rain sewers and the insufficient capacity of the reclamation channels and the four major pumping stations. In particular, frequent floods have been reported in the past fifteen years, including the most relevant ones of 1 November 2002, 20 October 2011, 31 January 2014, and the more recent event of 10 September 2017. For all of these intense events, the recording of rainfall intensity (from four stations: Ostia, Acilia, Ponte Galeria, and Isola Sacra, time resolution of 10 min) and the operation data of some or all of the pumping stations (in terms of discharge and water levels in the system) were available; such information was necessary for the calibration and verification of the hydraulic simulations of the events and, for some of them, the detailed description of the hydraulic effects on the territory. Unfortunately, no quantitative information on the piezometry during the flood events was available as no monitoring is routinely performed in the area.

3. River Flooding and Groundwater Flooding The joint analysis of rainfall and the water discharge at the pumping stations, which is described and discussed in the next sections, revealed that in most of the events, the runoff component of rainfall alone could not justify the high water volumes that are pumped during and after the rain events. As shown below, the volume of water pumped was often larger than the total average rainfall in the catchment. The reason for this is simple and understandable in view of the nature of the reclamation area, and it relates to the interaction between the drainage channels and the aquifer, such that the hydrological behaviors of the high and low areas are different. The high areas are poorly connected to the aquifer, and the flow discharge in the channels is determined by the surface hydrological component alone (river flooding), which in turn derives from the excess rainfall. In contrast, the low areas are mostly connected to the aquifer, and the channels are fed by both surface (river flooding) and subsurface (groundwater flooding) waters. Thus, groundwater flooding derives from the increase of the water table in the area, which in turn is due to infiltration. Such increase of the water table is relatively fast because the aquifer is shallow and highly permeable (mostly alluvial sands). The mechanism is described in Figure2. The hydrological conditions in absence of rain (Figure2a), which are determined by the water table as lowered by the pumps, change after rainfall as a function of its intensity, which is usually measured in terms of the return period T (Figure2b). Rainfall determines an increase of the water table which in turn increases the contributing areas near the channels (Figure2c), leading to a groundwater flooding component that adds to the surface one. This mechanism is in fact very similar to that of the contributing areas in the runoff generation mechanism originally envisioned by Dunne and extensively studied in the literature [25]; because of the low elevation and shallow water table, it represents a fundamental contribution to floods in the region under examination and in similar coastal regions. Water 2020, 12, x FOR PEER REVIEW 5 of 16 quantitativelyWater 2020, 12, 2030 similar to or greater than that determined by surface runoff via the standard Hortonian5 of 16 mechanism.

Figure 2. Sketch of the groundwater flooding mechanism. (a), Flow in the absence of rain where the Figure 2. Sketch of the groundwater flooding mechanism. (a), Flow in the absence of rain where the water table is lowered by pumps, is altered by rainfall; (b) the latter determines an increase of the water water table is lowered by pumps, is altered by rainfall; (b) the latter determines an increase of the table and (c) consequent increase of contributing areas near the channels. water table and (c) consequent increase of contributing areas near the channels. The rapidity of groundwater flooding is usually explained by the celerity of water waves in groundwater,The combined which effectdepend of onflooding transmissivity due to andexcess storativity runoff [ and26], which groundwater justifies the can rapid in principle streamflow be studiedgeneration using from a coupled groundwater hydrological [27–29 ].surface In the–subsurface case of reclaimed modeling areas, approach, the rapidity e.g., as of was streamflow done in Referencegeneration [18]. also However, depends such on thean approach density of may the easily channel require network significant that is modeling connected effort, to the especially aquifer. ifThe a two combination-dimensional of these approach effects is may pursued; be such the that latter it generates is necessary streamflow in view that of isthe quantitatively complexity similarof the hydraulicto or greater infrastructures, than that determined which includes by surface the runo networkff via the of channels, standard Hortonian the various mechanism. structures present (weirs,The manholes, combined small effect and of large flooding bridges due, etc.) to that excess have runo a paramountff and groundwater impact on the can dynamics in principle of the be floodsstudied, and using the aresulting coupled inundated hydrological areas. surface–subsurface Additionally, a combined modeling surface approach,–subsurface e.g., as model was done would in requiReferencere adequate [18]. However, characterization, such an approach especially may concern easily requireing the significant groundwater modeling component effort, especially and the aquifer,if a two-dimensional which are typically approach difficult is pursued; to monitor the and latter characterize. is necessary in view of the complexity of the hydraulicThe objective infrastructures, of the proposed which includes method theis to network integrate of th channels,e groundwater the various contribution structures to flood presenting in(weirs, a parsimonious manholes, small manner, and large with bridges, few relevant etc.) that parameters, have a paramount requiring impact a minimum on the dynamics of information of the regardingfloods, and the the hydrogeological resulting inundated setup. areas. The approach Additionally, is able a combined to be easily surface–subsurface implemented and model introduced would intorequire fully adequate-fledged characterization,two-dimensional especially hydraulic concerning models, where the groundwater the flood dynam componentics are modeled and the aquifer, along thewhich channel are typically network, di ffitogethercult to monitorwith the andpumping characterize. sequences of the pumping stations. The approach envisionedThe objective here is ofto themodel proposed groundwater method flooding is to integrate by a simple the groundwater groundwater contribution component, to flooding along the in ianstantaneous parsimonious unit manner, hydrograph with few (IUH) relevant approach, parameters, which requiring is distributed a minimum along each of information reach of the regarding channel network.the hydrogeological The method setup.requires The the approachdetermination is able of the to begroundwater easily implemented catchment and area introduced drained by intothe channels,fully-fledged which two-dimensional can be much larger hydraulic than the models, surface where drainage the floodarea and dynamics makes areuse modeledof the same along runoff the coefficchannelients network, employed together in the withexcess the runoff pumping hydrological sequences component. of the pumping The method stations. involves The approachonly one parameterenvisioned which here isis todetermined model groundwater after calibration. flooding by a simple groundwater component, along the instantaneousIn the next unit section, hydrograph we detail (IUH) the approach, methodological which is distributed aspects of alongthe proposed each reach approach, of the channel with applicationnetwork. The to the method case study requires under the determinationexamination. of the groundwater catchment area drained by the channels, which can be much larger than the surface drainage area and makes use of the same runoff 4. Materials and Methods coefficients employed in the excess runoff hydrological component. The method involves only one parameterWe describe which in is the determined following after the calibration.hydrological components providing the inflow to each channel of theIn network the next and section, the 2D we hydraulic detail the methodologicalmodel of the area; aspects the model of the proposedincludes approach,the pumping with stations application and theirto the operation case study as undera function examination. of the water levels in the pump chambers. The hydrological component represents the channel contributions coming both from surface runoff4. Materials and from and the Methods aquifer; it is usually the most critical and uncertain component in the modeling chainWe [30 describe]. The two in thecontributions following,the surface hydrological and subsurface, components reach providing the drainage the inflow channels to each at different channel times,of the quickly network in and the thecase 2D of hydraulicthe surface model component of the area;and more the model slowly includes for the groundwater the pumping component; stations and their operation as a function of the water levels in the pump chambers.

Water 2020, 12, 2030 6 of 16

The hydrological component represents the channel contributions coming both from surface runoff and from the aquifer; it is usually the most critical and uncertain component in the modeling chain [30]. The two contributions, surface and subsurface, reach the drainage channels at different times, quickly in the case of the surface component and more slowly for the groundwater component; therefore, the two contributions are identified below as the “fast” and “slow” components of the system response, respectively. The fast component was represented by a standard kinematic IUH model; instead, the slow component was modeled using a linear reservoir model, properly adapted to the channel network. While the first component (surface runoff) is rather standard, the second one (groundwater) was novel, at least in the current implementation of flooding in reclaimed areas, in combination with a surface hydraulic model, and represents the major contribution of this paper. The total flow feeding each channel was obtained by adding the slow and fast components. For channels that are not connected to the aquifer (high areas) only the runoff surface component was considered. Both models, fast and slow, fall into the category of linear rainfall–runoff models, based on IUH theory, which represents the system response (i.e., the flood hydrograph) consequent to an instantaneous unit excess rainfall. Following the IUH approach, the relationship between effective rainfall and flow rate at the closure of the catchment is given by the well-known convolution

Z t q(t) = A p(θ)u(t θ)dθ (1) 0 − where q is the discharge at the outlet, A is the area of the (surface) catchment pertaining to each channel, p is the excess rainfall (total rainfall minus the hydrological losses), and u is the IUH. The IUH corresponds to the probability density function of the travel time of water particles from a random location within the catchment to the outlet.

4.1. Surface Hydrological Component The surface (fast) component of flooding, which is determined by the excess water runoff, was calculated using the standard linear kinematic model, such that the IUH u in Equation (1) was univocally determined by the catchment travel time τb, as follows.

1 u(t) = (0 < t τb) (2) τb ≤

u(t) = 0 (t > τb) The rainfall input p in Equation (1) is given by either

the rainfall intensity measured during the past flood events for the calibration and verification of • the model, or a synthetic design rainfall, with given return period T, for the assessment of the inundation maps • and the flooding scenarios; the design rainfall adopted was the Chicago one [31], which was built on the intensity–duration–frequency (IDF) curves derived from the VAPI project Valutazione delle Piene in Italia, [32] and which provides the IDF for the Italian territory for any choice of T. The return periods adopted in this study were 10, 30, 50, 200, and 500 years.

The excess rainfall was calculated using the simple runoff coefficient φ, such that the excess rainfall p was equal to the product of the total rainfall by φ < 1. The values of the runoff coefficients were those generally employed in the area of interest [24] and are represented in Table1. The averaged values were inferred and delimited on the basis of recent aerial photos of the study area, and the runoff coefficient for each contributing basin was therefore calculated as the weighted average based on the fractions of the area occupied by the different types of soil cover. Water 2020, 12, 2030 7 of 16

Table 1. Runoff coefficients as function land cover and land use.

Land Cover and Use φ High-density consolidated urban areas 0.64 Medium density consolidated urban areas 0.38 Medium density urban areas with expanding urbanization 0.33 Low-density urban areas with expanding urbanization 0.26 Vegetation and agricultural areas 0.15 Forests 0.05

The catchment travel time τb is the sum of an average travel time to reach the channel under consideration by surface runoff and the travel time through the channel itself. The former is determined based on the size of the drained catchment and a velocity parameter that varies with land cover and use and with the average slope of the catchment, in between 0.25 and 0.5 m/s for HA and 0.01 and 0.035 for LA; the latter is equal to the ratio between the channel length and a travel velocity, which is inferred from the hydraulic model (illustrated later). The hydrological input, in terms of discharge q(t), is introduced in each of the channels of the network represented in the hydraulic model. The total number of sub-basins considered in the simulations is 265, with an average size of 13 hectars.

4.2. Subsurface Hydrological Component The groundwater (slow) component of channel flow was analyzed using a simple and parsimonious model, as emphasized in the previous sections. Adopting the same linear approach as Equation (1), we modeled the groundwater discharge to the channels using a linear reservoir IUH, leading to the exponential model 1 u(t) = e t/K (t > 0) (3) K − where K is the storage coefficient. Since the above model reflects the dynamics of the aquifer, the precipitation p that feeds the basin in Equation (1) is that falling over the whole groundwater basin, which generally differs from the surface catchment [33]. For the case under consideration, the extension of the groundwater basin was derived from Reference [34], and it was approximately four times larger the catchment basin of the LA (Figure3). Thus, the rainfall p was that recharging the aquifer over the groundwater catchment. Consistent with the analysis of runoff, the recharge to the aquifer was obtained by multiplying the total rainfall by the complement to unity of the runoff coefficient, with the same values adopted for the surface component (Table1). We implicitly neglected the storage in the shallow unsaturated area and evapotranspiration, which are both reasonable assumptions when analyzing intense flood events with high return periods. The storage coefficient K represents the average response time of the slow component in the system; its value was calculated for each sub-basin as the ratio between the half-length of the path (already used to calculate the travel time of the surface, fast response) and the underground flow celerity, not to be confused with velocity, as previously discussed. In the conceptual scheme adopted here, celerity in the subsoil is a parameter that represents the complex physical processes occurring in the subsurface, which was, for many reasons (model complexity, lack of information, etc.), not represented in detail. The groundwater celerity depends on the aquifer characteristics, mainly transmissivity, which in turn is affected by the hydraulic conductivity of the formation and the aquifer thickness and the derived piezometric gradients. The latter two quantities are highly variable during the year and during intense rainfall events. As a consequence, water celerity is bound to vary among events. In order to ensure the robustness of the model, the value of the subsurface celerity was reasonably set as equal for all the basins identified in the study area. Such a constant value was meant to be an average, “effective” value along each rainfall event. In fact, the derived storage coefficient K is bound to change between sub-basins as the average length is different. Water 2020, 12, x FOR PEER REVIEW 8 of 16

The value of the groundwater celerity, and consequently the values of the storage coefficients of the sub-basins, were determined during the calibration of the hydrological and hydraulic model, after reproducing the behavior of the pumping stations during the observed events in terms of volumes pumped and, where available, of recorded levels. In particular, the celerity calibrated for the 2014 event was used for the simulation of the synthetic events, which among all the simulated real events was the one characterized by a higher return period (around 30 years) and occurred at a time of the year (late January) preceded by significant rainfall that contributed to an increase of the aquifer levels; −4 theWater resulting2020, 12, calibrated 2030 celerity was 6.5 × 10 m/s. Adopting such a value for the high 푇 scenarios8 of 16 allowed a more precautionary and safe estimation of the inundated areas.

FigureFigure 3. 3. HydrogeologicalHydrogeological map map of of the the area area (derived (derived from from Reference Reference [3 [434]),]), which which shows shows the the (surface) (surface) catchmentcatchment size size of of the the l lowow a areasreas (colored(colored areas)areas) for for the the di differentfferent pumping pumping stations stations (circles) (circles) together together with withthe boundarythe boundary (red (red line) line) of the of groundwaterthe groundwater basin, basin, as inferred as inferred from from the iso-piezometricthe iso-piezometric lines. lines.

4.4. HydraulicThe value Modeling of the groundwater celerity, and consequently the values of the storage coefficients of the sub-basins, were determined during the calibration of the hydrological and hydraulic model, after The hydrological loads calculated via the above procedure were introduced in all channels of reproducing the behavior of the pumping stations during the observed events in terms of volumes the hydraulic model. The contribution of local drainage networks (sewage), when present, was also pumped and, where available, of recorded levels. In particular, the celerity calibrated for the 2014 considered. The hydraulic model employed was HEC-RAS [35], which is an integrated, 1D–2D model event was used for the simulation of the synthetic events, which among all the simulated real events used to solve shallow water equations in an interconnected channel network–floodplain was the one characterized by a higher return period (around 30 years) and occurred at a time of the environment. year (late January) preceded by significant rainfall that contributed to an increase of the aquifer levels; The 1D calculation domain included the channel network and it covered the channel sections the resulting calibrated celerity was 6.5 10 4 m/s. Adopting such a value for the high T scenarios from the bottom to the top of the embankment.× − As is well known, HEC-RAS is able to model head allowed a more precautionary and safe estimation of the inundated areas. losses due to the presence of obstructions (bridges, manholes, etc.) or sudden changes in the riverbed sections4.3. Hydraulic (weirs, Modelingobstructions, etc.), which was a necessary requirement in view of the complexity of the hydraulic system under consideration. The model also included the pump operation, such that the dischargeThe hydrological was automatically loads calculated set as a function via the of above the calculated procedure water were levels introduced in the pump in all chambers, channels of whichthe hydraulic in turn depend model.ed The on contributionthe water discharge of local from drainage the channel networks networks. (sewage), when present, was also considered.The 2D Thesolver hydraulic employ modeled a parabolic employed approximation was HEC-RAS [of35 ], the which two- isdimensional an integrated, shallow 1D–2D water model equations,used to solve thus shallow neglecting water the equations inertial in terms. an interconnected The hydraulic channel connections network–floodplain between the environment.1D and 2D domainsThe were 1D calculation carried out domain via bidirectional included the side channel spillways. network About and it 3600 covered lateral the spillways channel sections were introducedfrom the bottom and adapted to the top to ofthe the bank embankment. profiles inferred As is well from known, the topographic HEC-RAS is surveys able to specifically model head createdlosses duefor to this the study presence and of verifiedobstructions against (bridges, the d manholes,igital elevation etc.) or m suddenap of changes the Ministry in the riverbed of the Environmentsections (weirs, (Lidar obstructions, 1k). Altogether, etc.), which the was following a necessary elements requirement were introduced in view of the and complexity modeled: of100 the hydraulic system under consideration. The model also included the pump operation, such that the discharge was automatically set as a function of the calculated water levels in the pump chambers, which in turn depended on the water discharge from the channel networks. The 2D solver employed a parabolic approximation of the two-dimensional shallow water equations, thus neglecting the inertial terms. The hydraulic connections between the 1D and 2D domains were carried out via bidirectional side spillways. About 3600 lateral spillways were introduced and adapted to the bank profiles inferred from the topographic surveys specifically created for this study and verified against the digital elevation map of the Ministry of the Environment (Lidar 1k). Altogether, Water 2020, 12, 2030 9 of 16 Water 2020, 12, x FOR PEER REVIEW 9 of 16 remediationthe following channels, elements 5800 were hydraulic introduced sections, and modeled:and 500 local 100 structures remediation (bridges, channels, manholes, 5800 hydraulic weirs, etc.),sections, for a total and 500of about local structures98 km. (bridges, manholes, weirs, etc.), for a total of about 98 km. TheThe 2D 2D integration integration domain domain consist consisteded of of mixed mixed-type-type meshes, meshes, both both structured structured (square) (square) of of 55 × 5 5m m × mesh,mesh, and and unstructured unstructured (triangles (triangles or or polygon polygonss up up to to eight eight faces), faces), depending depending on on the the topographical topographical cocondition.ndition. Overall, Overall, more more than than 35 35 km km2 of2 ofland land was was modeled modeled,, made made up up of of approximately approximately 55 55 2D 2D interconnectedinterconnected areas, areas, or orconnected connected to the to the1D 1Ddomain domain,, for a for total a totalof approximately of approximately 1,870,000 1,870,000 cells (see cells Figure(see Figure 4). The4). pumping The pumping stations stations were also were modeled, also modeled, using the using dedicated the dedicated module available module availablein HEC- RASin HEC-RAS..

FigureFigure 4. 4.DomainDomain discretization discretization of ofthe the HEC HEC-RAS-RAS 2D 2D numerical numerical model model and and specification specification of of the the number number ofof elements elements adopted. adopted.

ManningManning roughness roughness coefficients coefficients in in the the channels channels were were assessed assessed based based on on the the morphological morphological characteristicscharacteristics of ofthe the canals, canals, inferred inferred from from the photographs the photographs taken takenalong the along canals the during canals the during survey the 1/3 campaignsurvey campaign.. Manning coefficient Manning coes rangingfficients from ranging 0.020 from to 0.03 0.0205 m to−1/3 0.035s were m adopted− s were for adopted the concrete for the- coveredconcrete-covered canals, depending canals, dependingon the amount on the and amount state of and the statevegetation of the vegetationpresent, while present, for the while uncoated for the riverbedsuncoated they riverbeds were theyassumed, were assumed,always based always on basedthe vegetation on the vegetation present, present, to vary tobetween vary between 0.035 and 0.035 1/3 0.050and m 0.050−1/3s. mTh−e boundarys. The boundary conditions conditions downstream downstream were selected were as selected supercritical as supercritical for the LA, for such the as LA, tosuch avoid as any to avoid backwater any backwater effect, and e fftheect, maximum and the maximum storm surge storm of the surge sea oflevel the in sea the level case in of the HA case was of equalHA wasto 0.75 equal m a.s.l to 0.75 (impact m a.s.l of (impactsea level of rise, sea as level considered rise, as considered for instance for in instance Reference in Reference[22], was not [22 ], 1/3 consideredwas not considered here). A here). constant A constant Manning Manning coefficien coetffi cient푛 = 0n.060= 0.060 m−1/3ms, −wass, was employed employed in in the the 2D 2D subsubdomainsdomains of of the the model. model. The The Manning Manning coefficients coefficients and and the the runoff runo ffcoefficientscoefficients were were calibrated calibrated and and verifiedverified in in the the aforementioned aforementioned previous previous study study focused focused on on the the higher higher areas areas,, after after comparison comparison of of the the modelmodel results results with with the the flood flood areas areas that that actually actually occurred occurred during during the the major major flood flood events events in in the the period period fromfrom 2002 2002 to to 2014 2014 [24] [24.]. Such Such values values have have been been adopted adopted by by the the local local reclamation reclamation authority. authority. TheThe input input of of the the model model were were the dischargesthe discharges calculated calculated with the wi previouslyth the previously illustrated hydrological illustrated hydrologicalanalysis. The analysis. initial conditionThe initial wascondition a minimum was a minimum flow rate inflow all rate channels, in all channels similar to, similar what isto usually what isfound usually in found normal in conditions normal conditions (a few tens (a few of liters tens perof l second).iters per second).

5. Results and Discussion

5.1. Model Verification against Observed Events The hydrological–hydraulic model was verified against the available data (mainly rainfall and discharge data from the pumping stations, including levels in the pump chambers) for some of the

Water 2020, 12, 2030 10 of 16

5. Results and Discussion

5.1. Model Verification against Observed Events

WaterThe 2020,hydrological–hydraulic 12, x FOR PEER REVIEW model was verified against the available data (mainly rainfall10 andof 16 discharge data from the pumping stations, including levels in the pump chambers) for some of the most intensemost intense rainfall rainfall events events that occurred that occurred in the study in the area study in the area last in twenty the last years. twenty The years. events The included events thoseinclude ofd 1 those November of 1 November 2002, 20 2002, October 20 October 2011, and 2011, 31 Januaryand 31 January 2014, and 2014 the, and more the recentmore recent event event of 10 Septemberof 10 September 2017; unfortunately, 2017; unfortunately, a complete a complete dataset wasdata notset availablewas not foravailable all the events.for all the The events. calibration The involvedcalibration only involved the groundwater only the groundwater celerity, while celerity, the other while relevant the parameters other relevant were parameters adopted from were a previousadopted from study a focused previous on study the higher focused areas, on the as previouslyhigher areas, discussed. as previously discussed. TheThe eventevent ofof 3131 January,January, 20142014 (return(return periodperiod T푇== 30 years)years) waswas thethe mostmost intenseintense andand criticalcritical eventevent inin thisthis areaarea amongamong thosethose examined.examined. Figure5 5aa depictsdepicts thethe water water volumes volumes pumpedpumped byby eacheachof of thethe fourfour stationsstations (Stagni,(Stagni, Ostiense,Ostiense, Bagnolo,Bagnolo, and Tor SanSan Michele);Michele); volumesvolumes areare expressedexpressed perper unitunit catchmentcatchment areaarea toto facilitatefacilitate comparisoncomparison withwith totaltotal rainfallrainfall (blue(blue line).line). The figuresfigures show how, inin aa timetime intervalinterval ofof 5454 hh (about(about 3030 hh afterafter thethe endend ofof thethe event),event), thethe volumesvolumes pumpedpumped byby thethe stationsstations werewere inin mostmost casescases largerlarger thanthan thethe totaltotal rainfallrainfall inin thethe samesame areas.areas. ThisThis behaviorbehavior emphasizesemphasizes the crucial role playedplayed byby thethe groundwatergroundwater componentcomponent ofof floodingflooding whichwhich cannotcannot bebe ignored,ignored, motivatingmotivating thethe presentpresent contribution.contribution. To thisthis end,end, thethe dasheddashed lineslines inin FigureFigure5 5 represent represent the the results results obtained obtained by by considering considering onlyonly thethe surfacesurface componentcomponent (for clarity,clarity, onlyonly thethe StagniStagni componentcomponent isis represented);represented); itit isis evidentevident thatthat runorunoffff byby directdirect precipitationprecipitation explainsexplains onlyonly aa relativelyrelatively smallsmall partpart ofof thethe volumesvolumes pumped,pumped, andand hencehence thethe inundationinundation volumes.volumes.

Figure 5. Event of 31 January 2014, comparison between observations (dot-dashed lines) and simulations Figure 5. Event of 31 January 2014, comparison between observations (dot-dashed lines) and (solid lines) at the pumping stations. (a) Water volumes (per unit catchment area) pumped and the simulations (solid lines) at the pumping stations. (a) Water volumes (per unit catchment area) total rainfall; (b) water levels and flow rates at the pumping stations at the Stagni pumping station. pumped and the total rainfall; (b) water levels and flow rates at the pumping stations at the Stagni The simulated results for the Stagni station pertaining to the sole surface component are represented by pumping station. The simulated results for the Stagni station pertaining to the sole surface component dashed lines. are represented by dashed lines. Figure5b shows the temporal behavior of the water levels in the pumping chamber together with Figure 5b shows the temporal behavior of the water levels in the pumping chamber together the flow rates pumped by the Stagni plant. In all cases, good behavior of the model was observed, with the flow rates pumped by the Stagni plant. In all cases, good behavior of the model was with an overall agreement between observations and simulations. The persistence of high levels in the observed, with an overall agreement between observations and simulations. The persistence of high pump chambers, higher than the bank levels of the channels, was due to the limited lifting capacity of levels in the pump chambers, higher than the bank levels of the channels, was due to the limited the system; this caused significant flooding in the upstream areas, consistent with the photographic lifting capacity of the system; this caused significant flooding in the upstream areas, consistent with documentation of the event, as discussed in the following section. the photographic documentation of the event, as discussed in the following section. On the basis of the information available for the 2014 event, it was possible to further check and On the basis of the information available for the 2014 event, it was possible to further check and verify the model capabilities and accuracy for reproducing the dynamics and extension of the inundated verify the model capabilities and accuracy for reproducing the dynamics and extension of the areas at the local scale. This was done for several check-points within the drainage network. As an inundated areas at the local scale. This was done for several check-points within the drainage example, Figure6 display a series of photos taken near the Stagni area during the event, compared network. As an example, Figure 6 display a series of photos taken near the Stagni area during the with the flood dynamics simulated at the same times as the shots were taken; the comparisons show event, compared with the flood dynamics simulated at the same times as the shots were taken; the comparisons show that the flood advancement and levels compared favorably with what was documented in the field while the event was taking place. The good accuracy of the model in reproducing the propagation dynamics was also confirmed by comparison between simulations and photos along a few relevant channels and in proximity of the Stagni pumping plant (not shown in figure).

Water 2020, 12, 2030 11 of 16 that the flood advancement and levels compared favorably with what was documented in the field while the event was taking place. The good accuracy of the model in reproducing the propagation dynamicsWater 2020, 1 was2, x FOR also PEER confirmed REVIEW by comparison between simulations and photos along a few relevant11 of 16 channelsWater 2020, and12, x inFOR proximity PEER REVIEW of the Stagni pumping plant (not shown in figure). 11 of 16

Figure 6. Event of 31 January 2014. Pictures taken during the event at times 14:23 and 14:24 compared with recent photos (from Google Street View, 2016) and the simulated flooding areas at 14:30. The Figure 6. Event of 31 January 2014. Pictures Pictures taken during the event at time timess 14:23 and 14:24 compared position of the area is represented by the red star symbol in Figure 1d. with recent photos (from Google Street View, 2016)2016) andand thethe simulatedsimulated floodingflooding areasareas atat 14:30.14:30. The position of the area isis representedrepresented byby thethe redred starstar symbolsymbol inin FigureFigure1 d.1d. The numerical model was further verified for the event that occurred in 1 November 2002. The eventThe was numerical less intense model than was the further others, verifiedverified being the for theone eventcharacterized thatthat occurredoccurred by the inin smallest 11 NovemberNovember return 2002.2002. period. The eventNevertheless, was less the intense event than caused the severalothers, floods,b beingeing the mainly one characterized in the most depressed by the smallest areas. Unfortunatelyreturn return period. period., Nevertheless,data for this event thethe eventevent were caused caused available several several only floods, floods,for the mainly mainlyStagni in station. thein the most most It depressedwas depressed seen areas.(Figure areas. Unfortunately, 7) Unfortunatelythat the mode data,l fordatabehave this ford event this quite event were well availablewere in terms available only of pumped for only the for Stagni volumes the station.Stagni and station.water It was level seenIt was (Figureat seenthe pumps.7 ()Figure that the The 7) model that large the behavedvolumes model quitebehavepumped welld quitecompared in terms well of into pumped termsthe total of volumespumpedrainfall confirm andvolumes watered andthe level importancewater at the level pumps. ofat the The groundwaterpumps. large The volumes large component pumpedvolumes to comparedpumpedthis flood. compared to the total to rainfallthe total confirmed rainfall confirm the importanceed the importance of the groundwater of the groundwater component component to this flood. to this flood.

Figure 7. Event of 1 November 2002, comparison between observation and simulation at the Stagni Figure 7. Event of 1 November 2002, comparison between observation and simulation at the Stagni pumping station: (a) water volumes (per unit catchment area) pumped and the total rainfall, (b) water pumping station: (a) water volumes (per unit catchment area) pumped and the total rainfall, (b) water levelsFigure and 7. Event flow ratesof 1 November at the pumping 2002, station. comparison between observation and simulation at the Stagni levels and flow rates at the pumping station. pumping station: (a) water volumes (per unit catchment area) pumped and the total rainfall, (b) water Aslevels the and total flow rainfall rates at wasthe pumping smaller station. than during 2014 event (about 100 mm in 12 h compared to As the total rainfall was smaller than during 2014 event (about 100 mm in 12 h compared to about 150 mm in 24 h), the 2002 event was characterized by a lower level and discharge at the Stagni about 150 mm in 24 h), the 2002 event was characterized by a lower level and discharge at the Stagni pumpingAs the station; total thisrainfall notwithstanding, was smaller thethan pumped during volume2014 event at Stagni (about was 100 greater mm in than 12 theh compared total rainfall, to pumping station; this notwithstanding, the pumped volume at Stagni was greater than the total highlightingabout 150 mm again in 24 the h), criticalthe 2002 role event of groundwater was characterized flooding. by a Thelower observed level and and discharge simulated at the behaviors Stagni rainfall, highlighting again the critical role of groundwater flooding. The observed and simulated alsopumping depend station; on the this antecedent notwithstanding, conditions (numberthe pumped of rainy volume antecedent at Stagni days was and greater the alternation than the of total wet behaviors also depend on the antecedent conditions (number of rainy antecedent days and the andrainfall, dry periods).highlighting again the critical role of groundwater flooding. The observed and simulated behavioralternations also of wet depend and dry on periods the antecedent). conditions (number of rainy antecedent days and the alternationThe importance of wet and ofdry the periods groundwater). component in pluvial flooding was further tested by analyzingThe importance the event of that the occurred groundwater on 10 component September in 2017 pluvial, after flooding a prolonged was further summer tested period by analyzingcharacterized the by event an absence that occurred of rainfall, on such 10 thatSeptember the groundwater 2017, after levels a prolongedin the area were summer presumably period characterizedvery low. In Figure by an absence8, we show of rainfall, that, about such that24 h theafter groundwater the end of the levels rainfall, in the the area volume were presumably pumped at verythe Stagni, low. In Ostiense Figure ,8 and, we Bagnoloshow that, pumping about 24stations h after tend theed end to ofremain the rainfall, constant the and volume much pumped lower than at thethe Stagni,total, in Ostiense contrast, toand what Bagnolo happened pumping during stations the previously tended to examined remain constant events. andThis much can be lower explained than the total, in contrast to what happened during the previously examined events. This can be explained

Water 2020, 12, x FOR PEER REVIEW 12 of 16

by the low groundwater levels at the beginning and during the events, confirming again the importance of this component in the flooding dynamics and the water volume pumped. While the modeling of the groundwater component via a lumped approach approximated the water volumes delivered in the channels and the pumps well, it is worth noting that it cannot capture local aquifer features like piezometric surge or groundwater discharge at all locations within the catchment. If such quantities are also of interest, a more integrated approach is needed, including a detailed and distributed analysis of groundwater flow (e.g., References [7,15,18]).

Water5.2. Application2020, 12, 2030 of the Model to Synthetic Rainfall Events for Inundated Area Delineation 12 of 16 Thus, the groundwater component is a very important component in the determination of inundatedThe importance areas in recla of theim groundwatered zones, like component the one under in pluvial examination flooding here, was after further intense tested rainfall by analyzing events. theNeglecting event that this occurred component on 10 may September lead to a 2017, severe after underestimation a prolonged summer of water period volumes characterized and the extension by an absenceof inundate of rainfall,d areas, such and that an theunderestimation groundwater levelsof the inpumping the area plants were presumably that are necessary very low. to Inde Figureliver the8, weexcess show water that, to about the final 24 h recipient. after the end We ofbriefly the rainfall, discuss the in the volume following pumped the main at the results Stagni, of Ostiense, the pumped and Bagnolowater volumes pumping and stations inundation tended areas to remainafter the constant considered and synthetic much lower rainfall than events, the total, as a in function contrast of to a whatfew happened return periods. during Thethe previously calibrated examined and verified events. 2D This numerical can be explained model bywas the employed low groundwater for the levelssimulations, at the beginning and we applied and during the groundwater the events, confirming celerity pertaining again the importanceto the 2014 ofevent this, componentas previously in thediscussed. flooding dynamics and the water volume pumped.

Figure 8. Event of 10 September 2017: comparison between observed and simulated water volumes Figure 8. Event of 10 September 2017: comparison between observed and simulated water volumes (per unit catchment area) and comparison with the total rainfall. (per unit catchment area) and comparison with the total rainfall. While the modeling of the groundwater component via a lumped approach approximated the Figure 9 shows the rainfall volume (solid lines) and the pumped volumes at the Bagnolo station water volumes delivered in the channels and the pumps well, it is worth noting that it cannot capture (dashed lines) as a function of time and the five return periods considered. The great impact of the local aquifer features like piezometric surge or groundwater discharge at all locations within the groundwater component, with volumes always larger than those related to rainwater within the catchment. If such quantities are also of interest, a more integrated approach is needed, including a catchment, was clearly visible and consistent with previous results. The differences between solid detailed and distributed analysis of groundwater flow (e.g., References [7,15,18]). and dashed lines increased with the return period T, i.e., with the intensity and rarity of the event; in 5.2.fact, Application more intense of the rainfall Model events to Synthetic lead to Rainfall a more Events significant for Inundated saturation Area of Delineationthe surface and groundwater components, leading to a larger runoff and water volumes to be pumped. Thus, the groundwater component is a very important component in the determination of inundated areas in reclaimed zones, like the one under examination here, after intense rainfall events. Neglecting this component may lead to a severe underestimation of water volumes and the extension of inundated areas, and an underestimation of the pumping plants that are necessary to deliver the excess water to the final recipient. We briefly discuss in the following the main results of the pumped water volumes and inundation areas after the considered synthetic rainfall events, as a function of a few return periods. The calibrated and verified 2D numerical model was employed for the simulations, and we applied the groundwater celerity pertaining to the 2014 event, as previously discussed. Figure9 shows the rainfall volume (solid lines) and the pumped volumes at the Bagnolo station (dashed lines) as a function of time and the five return periods considered. The great impact of the groundwater component, with volumes always larger than those related to rainwater within the catchment, was clearly visible and consistent with previous results. The differences between solid and dashed lines increased with the return period T, i.e., with the intensity and rarity of the event; in fact, more intense rainfall events lead to a more significant saturation of the surface and groundwater components, leading to a larger runoff and water volumes to be pumped. Water 2020, 12, x FOR PEER REVIEW 13 of 16 Water 2020, 12, 2030 13 of 16 Water 2020, 12, x FOR PEER REVIEW 13 of 16

Figure 9. Synthetic design events: comparison between the pumped water volumes (per unit Figurecatchment 9. 9. SyntheticSynthetic area) and design design the events: total events: design comparison comparison rainfall between at thebetween theBagnolo pumped the pumping pumped water volumes station water volumesfor (per different unit catchment (per return unit catchmentarea)periods and T the. area) total and design the totalrainfall design at the rainfall Bagnolo at pumping the Bagnolo station pumping for diff erent station return for different periods T return. periods T. Unfortunately,Unfortunately, the the capacity capacity of the of existing the existing pumping pumping stations stations is not adequate is not adequate to drain the to significant drain the water volumes coming from the surface and groundwater hydrological components, resulting in large significantUnfortunately, water volumes the capacity coming of from the existing the surface pumping and groundwater stations is not hydrological adequate to components, drain the inundated areas, as a function of the return period. The overlap of the flooding maps for the different significantresulting in water large volumesinundated coming areas, fromas a function the surface of the and return groundwater period. The hydrological overlap of components, the flooding return period is displayed in Figure 10. It was observed that the area is prone to flooding even for resultingmaps for inthe large different inundated return areas,period as is adisplayed function inof Figurethe return 10. Itperiod. was observed The overlap that theof thearea flooding is prone low to moderate return periods, e.g., T = 10 years. This is indeed what usually happens in this area, mapsto flooding for the even different for low return to moderate period is return displayed periods in Figure, e.g., 푇10.= It10 was years. observed This is that indeed the areawhat is u pronesually as explained in Section2. The di fferences in the inundated areas reflect the wide range of synthetic tohappens flooding in eventhis area, for low as explained to moderate in Sectionreturn periods2. The differences, e.g., 푇 = 10in theyears. inundated This is indeedareas reflect what the usually wide rainfall as a function of the return periods considered, ranging from 10 to 500 years. Additionally, the happensrange of insynthetic this area, rainfall as explained as a function in Section of the 2 .return The differences periods considered, in the inundated ranging areas from reflect 10 to 500the years.wide flatter zones generally led to larger inundated areas for the same water volumes. Regarding the latter rangeAdditionally of synthetic, the rainfallflatter zones as a function genera llyof theled return to larger periods inundated considered, areas rangingfor the same from water10 to 500 volumes. years. observation, we remark again that neglecting groundwater contributions severely underestimates AdditionallyRegarding the, the latter flatter observation zones genera, welly remarkled to larger again inundated that neglect areasing for groundwater the same water contribution volumes.s these Interestingly, for the larger values of T, the inundated area reproduced in the Ostiense/Stagni Regardingseverely underestimates the latter observation these Interestingly,, we remark for again the that larger neglect valuesing groundwater of 푇 , the inundated contribution areas region almost exactly the Levante lake that was present in the area before the reclamation works started, severelyreproduce underestimatesd in the Ostiense/Stagni these Interestingly, region almost for exactly the largerthe Levante values lake of that 푇 ,was the present inundated in the areaarea until the end of the 19th century. reproducebefore thed reclamation in the Ostiense/Stagni works started, region until almost the end exactly of the the 19 Levanteth century. lake that was present in the area before the reclamation works started, until the end of the 19th century.

FigureFigure 10.10. InundatedInundated areasareas asas functionfunction ofof thethe returnreturn periodperiod TT.. TheThe mapmap includesincludes thethe inundatedinundated areasareas Figureevaluatedevaluated 10. inInundatedin aa previousprevious areas studystudy as function [[24]24] (shaded(shaded of the areaarea return ofof FigureFigure period1 ).1 ).T . The map includes the inundated areas evaluated in a previous study [24] (shaded area of Figure 1).

Water 2020, 12, 2030 14 of 16

6. Summary and Conclusions We analyzed flood and inundation areas in a reclaimed coastal zone, i.e., a low-elevation area where the groundwater level is kept low by a system of reclamation channels and pumping stations. An important component of flooding in such areas is groundwater flooding, complementary to surface runoff, which is determined by the sudden rise of the water table due to intense direct precipitation. When rainfall is intense and the water table is high, the channel network drains both the surface (runoff) water and groundwater components, resulting in a greater pumping effort by the stations. As a consequence, the volume pumped is potentially larger than the total volume of rain that has fallen on the surface catchment, being impacted by the size of the groundwater basin. Given that most flood models are based on surface hydrological/hydraulic methods and tools, e.g., HEC-RAS, we introduced in this work a simple lumped approach for handling the groundwater contribution to flood in reclaimed areas. The approach is parsimonious (only one calibration parameter), requiring little information on the groundwater setup, and it is easy to implement with existing surface hydraulic models for flood management and the delineation of inundation maps. The method was applied to the analysis of inundation maps of a wide reclamation area located in the southern part of Rome, Italy. The results obtained confirmed that the simple modeling scheme adopted, although simplified and parsimonious, was able to represent the complex dynamics of the surface water drained by the system of channels with enough accuracy for the scopes at hand. Hence, groundwater can be an important component in the delineation of flood-prone areas, especially for high return periods. Neglecting this component may lead to a severe underestimation of water volumes and the extension of inundated areas, and an underestimation of the pumping plants that are necessary to deliver the excess water to the final recipient. The proposed approach represents an approximation of the complex groundwater dynamics that occur during and after an intense rainfall event, and it clearly cannot capture local aquifer features like piezometric surge or groundwater discharge at all locations within a catchment. Nevertheless, it may provide a simple and useful procedure to be implemented with existing surface flood models applied to reclaimed areas similar to the one examined in this study.

Author Contributions: Conceptualization, A.F.; Data curation, C.P.M., S.L. and E.V.; Formal analysis, C.P.M. and E.V.; Investigation, S.L.; Methodology, E.V. and A.F.; Project administration, C.P.M.; Resources, S.L.; Software, C.P.M. and S.L.; Supervision, C.P.M. and A.F.; Visualization, C.P.M. and S.L.; Writing—original draft, A.F.; Writing—review & editing, E.V. All authors have read and agreed to the published version of the manuscript. Funding: This research received funding by the Municipality of Rome through the project: “Study for the hydraulic remediation of the basins of medium and low waters in the area of southern Rome and identification of interventions for the mitigation of hydraulic risk in the area under study”. Funding from the Italian Ministry of Education, University and Research (MIUR), in the frame of the Departments of Excellence Initiative 2018–2022, attributed to the Department of Engineering of Roma Tre University, and from the Italian Ministry of Environment, Land and Sea Protection (MATTM) for SimPRO project (2020–2021), are also acknowledged. Acknowledgments: The authors thank Roberto Botta, Municipality of Rome, and Severino Marasco, Consorzio di Bonifica Litorale Nord, for they continuous support. Support from the “Call for Ideas” project, Roma Tre University, is also acknowledged. Conflicts of Interest: The authors declare no conflict of interest.

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