Configuration methodology for a green variety reef system (AR group) based on hydrodynamic criteria - Application to the Ria de Ares-Betanzos

Estuarine, Coastal and Shelf Science 252 (2021) 107301 Available online 2 March 2021 0272-7714/© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Configuration methodology for a green variety reef system (AR group) based on hydrodynamic criteria – Application to the Ría de Ares-Betanzos Luis Carral a , * , María Isabel Lamas–Galdo b , Mª Jesús Rodríguez-Guerreiro a , Andreina Vargas c , Carlos ´ Alvarez-Feal a , Iv´ an L´ opez c , Rodrigo Carballo c a Universidade da Coru˜ na, Mixed Engineering Group, Spain b Universidade da Coru˜ na, Escuela Polit´ ecnica Superior, Spain c Departamento de Enxe˜ naría Agroforestal, Universidade de Santiago de Compostela, EPSE, Rúa Benigno Ledo s/n, 27002, Lugo, Spain ARTICLE INFO Keywords: Artificial reef Hydrodynamics Coastal dynamics Computational fluid dynamics (CFD) ABSTRACT For the evolution and development of artificial reefs to attain the expected results, hydrodynamics is emerging as a key factor that must be taken analyzed in detail. In particular, thanks to the hydrodynamics of a given coastal area, suitable water circulation and velocity in the reef’s interior can increase the yield and the renewal of nutrients favourable for larval settlement, along with reducing the sedimentation. This document proposes a methodology for determining the geometry of an artificial reef group adapted to the specific characteristics of the selected zone of installation, the Ría de Ares-Betanzos (NW Spain), based on hydrodynamic criteria by defining the Artificial Reef Tool (ART). The starting point of the ART tool is the existing reef model or AR unit’s design –a modular construction with productive and protective features. Then a highresolution hydrodynamic circulation model (HCM) is developed allowing the high-resolution site-specific computation of the flow pattern in the selected area. Finally, the results obtained are used as input for a hydrodynamic model for food delivery prediction (HMFDP), allowing the estimation of the food supply to each module. The results obtained lead to the definition of the geometry of the reef group. 1. Introduction The coastal zones of Galicia (North West Iberian Peninsula) are renowned for their uniqueness, as well as their crucial role in supporting the population through economic activities, biological diversity and the supply of resources. In particular its estuaries are ecosystems of significant biological productivity, but in need of protection, owing to the intense human pressure that they undergo through fishing, shellfishgathering, the urbanisation of the surrounding areas and recreational use (Carral et al., 2020). At the same time, Galicia supports a highly productive fishing fleet, which has not been able to increase its productivity levels. Because of these poor results and the community’s excessive dependence on this activity, measures must be taken to promote wealth and biodiversity in zones that stand out for their productive capacity (Carral et al., 2018a). Artificial Reefs (AR) could be a means to this end; they provide systems in which species attached to rocky bottoms or nearby sandy areas find refuge, and where the presence of algae and other colonising organisms make possible a wider availability of food (Ramos – Espl´ a et al., 2000). When installed in intermediate or shallow waters, artificial reefs also provide coastal protection, reducing coastal erosion and accumulating sediment (Hedge, 2010). Besides, if artificial reefs are installed, the pre-existing equilibrium remains completely unaltered (Pratt, 1994; Pickering et al., 1999). The European concept of AR focuses mainly on the protection and potentiation of the fishing resources. Countries such as Portugal and Spain, between others, develop actuations to prepare the coastal area for protection and regeneration of the fishing resources. In Spain, other AR, the oceanic Posidonia, are installed (Daza-Cordero et al., 2008). Whitmarsh et al. (2008) argue that AR must be adapted to the established objectives and the geographical regions in which they are located. Carral et al., (2018b) apply this approach to PROARR, (Spanish acronym of Recycled Artificial Reef PROject), a research project financed by Xunta de Galicia (Spain) to develop efficient ARs in the Galician estuaries. This project proposes a management tool to be used for the sustainability of small-scale fishing in Galician estuaries to * Corresponding author. E-mail address: [email protected] (L. Carral). Contents lists available at ScienceDirect Estuarine, Coastal and Shelf Science journal homepage: http://www.elsevier.com/locate/ecss https://doi.org/10.1016/j.ecss.2021.107301 Received 19 August 2020; Received in revised form 13 February 2021; Accepted 19 February 2021 Estuarine, Coastal and Shelf Science 252 (2021) 107301 2 compensate the effects of population depletion, which is of particularly interest where this type of small-scale fishing actively sustains local communities. As a result of the PROARR research project, environmentally friendly AR fish yielding and erosion prevention modules were developed, Fig. 1, adapted to the geomorphology of the Galician estuaries (Carral et al., 2018a). Each reef consists of a concrete slab and an upper prism based on four pre cast concrete surfaces, Fig. 1(a). The slab provides stability, while the upper prism constitutes a surface to for nest cavities to settle different species (Rodríguez-Guerreiro et al., 2020). Protection modules based on steel bars, Fig. 1(b), are installed to avoid damages from fishing gears. The results of the project were patented and subject to hydrodynamic optimisation through Computational Fluid Dynamics (CFD) (Lamas et al., 2020), having designated the Ares-Betanzos estuary as the site for an experimental reef group (Carral et al., 2018a). The Ares-Betanzos estuary, with an area of 72 km 2 , is located between the A Coru˜ na and Ferrol estuaries on the North-West coast of the Iberian Peninsula, Fig. 2. It comprises a dual estuary system (Asensio-Amor and Gracal-Blanco, 1981) with a volume of 0.75 km 3 . It is made up of two branches: Ares, the River Eume estuary, and Betanzos, the River Mandeo estuary, whose rivers show great seasonal variations and an average discharge of 16.5 and 14.1 m 3 /s respectively (Prego et al., 1999; S´ anchezMata et al., 1999). These two sectors converge in a confluence zone that is freely connected to the Atlantic Ocean through a 40 m deep and 4 km wide mouth, Fig. 2. In the case of the Ares-Betanzos estuary, the subtidal circulation is positive even in upwelling and downwelling conditions, thanks to the major role played by river flows. S´ anchez-Mata et al. (1999), Villegas-Ríos et al. (2011), and Carral et al. (2019) determine the magnitude of the surface tidal currents as close to 0.89 ms −1 . These circulation values were modified by Piedracoba et al. (2014) and Carral et al. (2019), who estimated them to be considerably lower, less than 10 cms −1 . All of these characteristics are of great interest in the establishment of an AR, due to the influence of water circulation on aquaculture production of coastal ecosystems (Grant et al., 1998; Grant and Bacher, 2001). A range of studies have attempted to relate a suitable general habitat to the development of fish farming and the establishment of AR. Pastres et al. (2001) used a detailed ecosystem model to identify suitable locations for producing clams in Venice Lagoon. An alternative approach for selecting clam-farming locations in Florida was proposed by Arnold et al. (2000), who used multiple criteria based on water quality and space requirements, as well as limiting the impact of cultivation. For their part, Raillard and M´ enesquen (1994), Dowd (1997), Bacher et al. (1998), and Ferreira et al. (1998) developed other modules to assess load capacity adapted to the ecosystem. Bacher et al. (2003) traced the relationship between bivalve growth and the depletion of food sources in an area of intensive aquaculture, Sungo Bay. However, a smaller number of research projects have linked the circulation, an important aspect of the habitat, to the implantation of AR. Hayley et al., (2019), Tian (2018), and Fujihara et al. (2011) consider important to take into account the distribution and orientation of the various modules that form a reef group. In this sense, Nakamura (1982) and Allemand (2000) indicate that AR modules must be perpendicularly oriented to the predominant currents and to the migratory movements of fish. In particular, this is due to the fact that many sessile invertebrates serving as food for determined species feed on particles in suspension along the water column. Bayes and Szmant (1989) relate speed to orientation, establishing that for weak speeds (0-10 cms −1 ) the axis of the reef group must be perpendicular to the predominant current. Recently, numerical techniques have become a powerful tool in the study of AR behaviour insofar as they provide detailed information about the pressure and velocity field distribution. Unfortunately, few numerical simulations regarding artificial reefs are available. One can refer to Su et al. (2008) and Liu and Su (2013), who developed projects to characterize the flow in and around an artificial reef, and Duzbastilara and Senturkb (2009), who calculated the mobilisation forces and drag coefficients. By means of a wind tunnel and numerical simulation methods, Lin et al., (2009, 2010) established the flow fields around artificial reef models of varying cubic, pyramid and prismatic triangular shapes. Su et al. (2008) used Particle Image Velocimetry (PIV) measurements to study the flow pattern of an artificial reef. The results of the PIV were used to verify the numerical results obtained from Finite Volume Method (FVM) simulations. Recently, Jiao et al. (2017) analyzed reefs composed by tubes and compared their experimental results with PIV measurements. Liu et al. (2012, 2013) and Jiang et al. (2013, 2014) also developed PIV measurements to validate their simulations. Liu and Su (2013) numerically investigated the influence of changes in an artificial reef on its flow. Woo et al., (2014) classified 24 artificial reef models by numerically calculating aerodynamic resistance coefficients. 2. Objectives Carral et al. (2019) provide a methodology suitable for determining the main areas of interest for the installation of an AR, which is implemented to the Ares-Betanzos estuary. This methodology is based on different aspects, grouped in (i) excluding factors, related with the existing uses in the area, (ii) functional factors, including bathymetric, geomorphological and hydrodynamic characteristics, and (iii) economic factors, related to construction and maintenance costs. Based on Fig. 1. PROARR artificial reef modules for production (a) and protection (b). Source: Author’s own. L. Carral et al. Estuarine, Coastal and Shelf Science 252 (2021) 107301 3 the results obtained, the objective of this study is to develop a methodology to establish the configuration of an environmentally friendly PROARR reef group in the Ares-Betanzos estuary (NW Iberian Peninsula). It would shed light on the hydrodynamic factors that influence how the fish stocks being promoted develop. AR units that both yield fish stocks and prevent erosion in accordance with an established geometry will determine the configuration of an AR group. The conglomeration of various reef groups maintaining predetermined distances makes up an AR complex. In this study, the design of modularly built reef modules for fish production and protection prevention (PROARR project) to form a reef group are assumed, Fig. 1. Then, the so-called ART (Artificial Reef Tool) management tool is defined by combining two hydrodynamic models in the Ares-Betanzos estuary. First, a high-resolution hydrodynamic circulation model (HCM) is implemented, allowing the accurate computation of the circulation flow patterns at the location of interest. Then, a CFD hydrodynamic model for food delivery prediction (HMFDP) is developed, which uses as input the values of ad-hoc velocity parameters obtained from HCM, leading to the prediction of the food supply to the different modules, Fig. 3. The results obtained lead to the definition of the AR group configuration. As indicated above, this HMFDP model is applied to the Ares-Betanzos estuary, and the main objectives of this model are: – Adapt the reef model geometry for the adequate circulation of nutrients along the cavities on the basis of the circulation flow pattern. – Establish an appropriate distance between reefs that constitute a group of reefs, i.e., determine the hydrodynamic behaviour between adjacent reefs due to the existing interaction amongst them. 3. Hydrodynamic circulation model (HCM) 3.1. Model characteristics and implementation The appropriate functioning of an AR relies on its correct design which should be adapted to the specific hydrodynamic conditions of the intended installation areas. With this aim, in this work, a high-resolution Fig. 2. Disposition of the Ares-Betanzos estuary, in the NW region of Spain. Source: own. L. Carral et al. Estuarine, Coastal and Shelf Science 252 (2021) 107301 4 numerical model is implemented in the Ares-Betanzos estuary. The DELFT3D FLOW open source code (Deltares, 2010) was used, which solves the Navier-Stokes equations under the shallow water and Boussinesq assumptions coupled to the transport equation: ∂ u ∂ x+ ∂ v ∂ y+ ∂ w ∂ z=Sm(1) Du Dt =fv −g ∂ ζ ∂ x−g ρ 0∫z′= ς z′=z ∂ρ ∂ xdz′+ υ h( ∂ 2u ∂ x2+ ∂ 2u ∂ y2)+ υ v( ∂ 2u ∂ z2)(2) Dv Dt = − fu −g ∂ ζ ∂ y−g ρ 0∫z′= ς z′=z ∂ρ ∂ ydz′+ υ h( ∂ 2v ∂ x2+ ∂ 2v ∂ y2)+ υ v( ∂ 2v ∂ z2)(3) ∂ p ∂ z= − ρ g(4) Dc Dt =Dh( ∂ 2c ∂ x2+ ∂ 2c ∂ y2)+Dv ∂ 2c ∂ z2−λdc+St(5) These equations represent the mass conservation for an incompressible fluid, Eq. (1); the conservation of momentum in xand y-directions, Eqs. (2) and (3), respectively; the conservation of momentum in z-direction, Eq. (4), which is reduced to the hydrostatic pressure distribution according to the shallow water assumption; finally, the transport equation, Eq. (5), is used to solve the spatial thermohaline distribution. In these equations, u, v and w are the components of the velocity in x, y and z directions, respectively; ζ stands for the free surface elevation relative to z =0; ρ and ρ 0 represent the water density and reference density, respectively; S m represents the source term of mass; f is the Coriolis parameter; υ h and υ v represent the horizontal and vertical turbulent eddy viscosity in the horizontal and vertical directions, respectively; c accounts for the salinity or temperature constituents; D h and D v represent the turbulent eddy diffusivity in the horizontal and vertical directions, respectively; λ d express the decay processes (first order); finally, S t is the source term in the transport equation. To determine the hydrodynamic characteristics of the area under study, the model is implemented with a high spatial resolution (50 m) in the estuary, which is adequate to characterize the water depth variations in the area of interest, increasing its size towards the open ocean boundaries, placed at a sufficient distance so as not to affect the area of study (Fig. 4), for which a total number of 212,895 cells are considered, and the time step set to 0.5 s. The model is used to characterize the estuary’s hydrodynamic behaviour for a period representative of average conditions, for which a complete spring-neap tidal cycle is analyzed. When determining the forces acting during this period, previous works establish that the circulation in the Galician estuaries is the result of a complex interaction amongst several forcing agents (Carballo et al., 2009; Iglesias and Carballo, 2011). It has been established that the circulation induced by average winds is of a much less magnitude than the transitory circulation generated by the tide (Piedracoba et al., 2014; Iglesias and Carballo, 2010). In this way, this study considers the following generating forces of currents: i) the tide, ii) freshwater discharges, iii) thermohaline characteristics of sea water masses. The tide is implemented by introducing the major tidal harmonics at the open boundaries. Regarding the sea water open boundary conditions, its average annual characteristics are considered as defined through data supplied by the Villano-Sisargas buoy. Finally, the average annual freshwater inputs are considered, based on previous studies in the survey area (Prego et al., 1999; S´ anchez-Mata et al., 1999). Carral et al. (2019) provide a methodology suitable for determining the main areas of interest in the installation of an AR, in accordance with socioeconomic and environmental aspects, hydrodynamic and geomorphological characteristics, and costs of installation and maintenance. On these bases, the hydrodynamic analysis is focused on three large areas of the mid-estuary (1, 2 and 3) considered as those with the greatest potential. Within these areas, control points deemed to be the most representative of each area, are selected, Fig. 4. 3.2. Site-specific flow pattern results The resulting circulation at mid-flood and mid-ebb during a spring and neap tide is provided in Fig. 5 (general view) and Fig. 6 (detailed view of the selected areas). It can be observed how the magnitude of the currents differs to a great extent, not only during flood and ebb tide, but also during spring and neap tides. In the selected areas, it can be observed that the maximum average speed is around 0.3 ms −1 in spring tides, while in neap tides the maximum magnitudes do not exceed 0.2 ms −1 . Similarly, a high asymmetry in the circulation is apparent. Flow magnitudes during the ebb tide are considerably greater than during flood tide, which in this case is not solely the result of tides interacting with the contours, but also generated by the existing freshwater discharge. On the other hand, noteworthy spatial variations in the current velocities can be observed throughout the estuary, and more specifically amongst the selected areas, with noticeably greater speed magnitudes in areas 1 and 2 than in area3. Regarding the direction of the flow, it tends to align itself with the axis of the main estuary channel; with an approximate direction of SE-NW in the mid-estuary (areas 1 and 2) and NE-SW in the mid-inner estuary (area 3). In an attempt to analyze the existing hydrodynamic behaviour in the selected areas more accurately, Fig. 7 shows the current magnitude distribution at the three control points (1, 2 and 3) throughout the complete spring-neap tidal cycle selected. Based on the results obtained, the following statistical parameters are determined for each of the points during this period: maximum velocity– V max , average velocity-V m , velocity exceeded during 50% of the time -V 50% , and average velocity during the period with speeds exceeding V 50% - V m50% . (Table 1). It can be observed that the location with the greatest current speed is point 2, with 0.227 ms −1 , followed by point 1 with 0.201 ms −1 , and finally with a considerably lower speed, point 3 with 0.103 ms −1 . However, while it is interesting to know the maximum current speeds, they only occur at specific time points during the tide cycle, and as such Fig. 3. PROARR –AR group development tool (ART) by combining two models. Source: author’s own. L. Carral et al. Estuarine, Coastal and Shelf Science 252 (2021) 107301 5 do not represent a characteristic magnitude for which the AR design must be optimised. On the contrary, other parameters such as the average velocity must be drawn upon, or, where applicable, the existing velocity (threshold or average) during a significant period of time, e. g., 50% of the time. For these parameters, a similar pattern to that depicted for the maximum velocity is obtained, but with a significantly lower magnitude. The values obtained for V m , V 50% and V m50% are respectively 0.083 ms −1 , 0.797 ms −1 and 0.124 ms −1 at point 1, 0.096 ms −1 , 0.093 ms −1 and 0.141 ms −1 at point 2, and finally 0.049 ms −1 and 0.048 ms −1 and 0.069 ms −1 at point 3. In this way, it can be observed that the average velocity shows very similar values to the established threshold of speed exceeded during 50% of the time, and slightly lower than those obtained for the average speed during that period of time. In the present work, the average speed, V m , and threshold speed, V 50% , are considered as those most representative, which in turn present similar values, in a way that the largest and lowest magnitudes of the flow located near high and low tides are also considered in the reef design. Thus, based on results obtained, the following values of current magnitude are defined for their analysis through CFD: 0.05 ms −1 , 0.08 ms −1 and 0.1 ms −1 . Table 2 summarizes the input and output variables in this HCM model. 4. Cfd hydrodynamic model for food delivery prediction (HMFDP) A CFD model was carried out to analyze the food supply to the ARs. First of all, this model was validated using experimental results. Once validated, it was applied to the object of this work, PROARR – ARs. 4.1. Validation of the model The experimental results obtained by Jiao et al. (2017) were employed to validate the CFD model. The research carried out by Jiao et al. used PIV to analyze the flow around the tube artificial reefs shown in Fig. 8. The CFD model developed in the present work is based on the RANS equations (Reynolds-averaged Navier-Stokes) of conservation of mass and momentum. A steady 3D simulation based on the mass, Eq. (1), and momentum conservation equations was carried out using the open software OpenFOAM. Contrary to the DELFT3D FLOW model treated in the previous section, the shallow water assumption was not assumed since there is no large difference in vertical and horizontal length scales around the AR. According to this, Eq. (6), was used as momentum equation. Water was considered as a single-phase and incompressible fluid. ρ∂ ∂ xj(uiuj)= − ∂ p ∂ xi + ∂τ ij ∂ xj + ∂ ∂ xj(− ρ u′ iu′ j)(6) In the equation above, τ ij represents the viscous stress tensor and u i and u j are the velocity components for x, y, and z. As the fluid was treated as Newtonian, the stress tensor components were computed as: τ ij = μ ( ∂ ui ∂ xj + ∂ uj ∂ xi −2 3δij ∂ uk ∂ xk)(7) The Reynolds stresses, − ρ u′ iu′ j, were calculated according to the following equation: − ρ u′ iu′ j= μ t( ∂ ui ∂ xj + ∂ uj ∂ xi)−2 3( ρ k+ μ t ∂ uk ∂ xk)δij (8) where δij is the Kronecker delta (δij =1 if i =j and δij =0 if i ∕= j), and μ t the eddy viscosity, given by Eq. (9). The turbulence was treated through the kε model. According to this, two transport equations are added, one for the turbulence kinetic energy, k, and a further one for its dissipation rate, ε . μ t= ρ C μ k2 ε (9) Fig. 4. Bathymetry of the study area as interpolated to the numerical grid, showing the areas of interest for the installation of an AR. Source: author’s own. L. Carral et al. Estuarine, Coastal and Shelf Science 252 (2021) 107301 6 A 1 ˣ 0.45 ˣ 0.5 m computational domain was employed, Fig. 9. The boundary conditions are also included in this figure. The left side of the domain was modelled as an inlet, with constant flow velocity. The downstream right-hand side was established as an exit. The sides of the reef and the seabed were established as non-slip. Finally, the remaining sides were set as a zero gradient, with the velocity corresponding to that of the fluid. Fig. 10 illustrates the length of the affected back region against the free-stream velocity obtained numerically and experimentally. In this case, the affected region was determined as the region in which the vertical component of the velocity is equal to or greater than 10% inlet velocity. As can be seen, coherent results are provided by the CFD model developed in the present work, which indicates its adequacy. Other validations of CFD models using experimental measurements of artificial reefs can be consulted in the literature (Liu et al., 2012; Liu et al., 2013; Jiang et al., 2013; Jiang et al., 2014). These studies and the present one confirm the adequacy of CFD to analyze artificial reefs. 4.2. Artificial reef model Once validated, the CFD model was applied to analyze the artificial reef proposed in the present work, Fig. 1. This is cubic, honeycomb-like structure 2 m in maximum length, with a wide surface area for organisms to settle (Carral et al., 2018a). Its walls are provided with orifices of varying size. It has a central hollow which leads to a wide central cavity, while the secondary orifices (20 cm and 15 cm each side) lead to hidden sections with vertical and horizontal walls so that individuals are protected and can develop, Fig. 11. The function of the central holes is to make circulation possible on the inside, while the small sized secondary holes provide nests for crustaceans. The size of these central hollows is configured according to the information provided by this CFD study. Two central hole sizes were analyzed, 200 mm and 400 mm, shown in Fig. 11 (a) and (b), respectively. Fig. 11 (c) shows the AR section for the 400 mm hole size. As indicated previously, the smaller sized secondary holes which supply nests for the crustaceans are located in the free space on each side. The 200 mm size allows an important surface for nest cavities, while the 400 mm size allows less surface for nest cavities. A central hole size lower than 200 mm would lead to extremely low interior velocities and thus would not guarantee the renewal of nutrients on the inside. On the other hand, a central hole size higher than 400 mm would lead to little space to allocate nest cavities. For these reasons, central hole sizes lower than 200 mm and higher than 400 mm were not analyzed in the present work. The computational mesh for the reef with 400 mm central hole size is shown in Fig. 12. It consists of a block with dimensions of 8 ˣ 16 ˣ 32 m. The reef module is situated in the interior, as shown in Fig. 12 (b). Various simulations were made to model so as to verify that these dimensions are adequate to avoid boundary effects on the flow. Moreover, various mesh sizes were simulated to verify its quality. Finally, the mesh is made up of 1.6∙10 6 tetrahedral elements of 0.01–0.67 m size, being more refined near the module to better characterize the fluid around the reef. The mesh for the reef with 200 mm central hole size is too similar, so it is not shown. The governing equations and numerical details were those employed Fig. 5. Magnitude and direction of current velocity in the Ares-Betanzos estuary at mid-flood (left) and mid-ebb (right) of a mean spring tide (above) and neap tide (below). Source: author’s own. L. Carral et al. Estuarine, Coastal and Shelf Science 252 (2021) 107301 7 in the validation process, Section 4.1. As indicated in this section, the left side of the domain was modelled as an inlet, Fig. 9. The upstream flow velocities were set as 0.05, 0.08 and 0.1 ms −1 according to Section 3. Regarding computational time, each simulation needed about 80 min using an Intel Core i-5 processor with 8 Gb RAM running on a 64-bits Fig. 6. Detailed view of the circulation patterns in the selected areas. Source: author’s own. Fig. 7. Magnitude of the current velocity at points 1, 2 and 3 over a complete spring-neap tidal cycle. Table 1 Values of V max , V m , V 50% and V m50% at points 1, 2 and 3. VELOCITY (MS −1 ) POINT 1 POINT 2 POINT 3 V max 0.201 0.227 0.103 V m 0.083 0.096 0.049 V 50% 0.0797 0.093 0.048 V m50% 0.124 0.141 0.069 Table 2 Input and output variables in the HCM Model. Source: author’s own. INPUT TYPE OF MODEL OUTPUT - Geographic location HCM-Hydrodynamic Circulation Model - Statistical Parameter - Control points (Carral et al., 2019) Threshold speedV m y V 50% - Complete spring-neap tidal cycle - Existing forces (tide, freshwater discharges, characteristics of sea water masses) - Seasonal current distribution L. Carral et al. Estuarine, Coastal and Shelf Science 252 (2021) 107301 8 Linux operating system. 5. Results and discussion - definition of the group of reefs and configuration possibilities (ART) This section shows the results corresponding to the CFD model applied to 200 and 400 mm hole sizes and current velocities 0.05, 0.08 and 0.1 ms −1 . Table 3 summarizes the input and output variables in this HMDPF model. Both the central hole size and the distance between artificial reefs will be analyzed in this section. 5.1. Hydrodynamic improvement of the module Fig. 13 shows the velocity field in the median plane in the case of a 400 mm central hollow and 0.05 ms −1 of current speed. As can be seen, the flow velocity is disrupted due to the presence of the reef module. The module induces an increase in the velocity in its central part, while it diminishes at the boundaries and downstream. This reduction of velocity in the central zone is extremely negative in the transportation of nutrients. Low velocities do not guarantee the necessary supply of nutrients on the inside. In this way, it is necessary to avoid the circulation from reaching a standstill in the points where the nest cavities are situated. Thus, the hydrodynamic improvement of the module must be based on adapting the geometry of the central hole to maintain the circulation in the interior and exterior side zones in which the secondary nest cavities are situated. Fig. 14 presents the contour plots of the velocity field for all the cases analyzed, i.e., 200 and 400 mm central hole sizes and water current velocities of 0.05, 0.08, and 0.1 ms −1 . As can be seen, current velocities of 0.05 ms −1 lead to extremely low velocities inside the artificial reef, especially in the case of 200 mm central hole size. According to this, this hole size is not recommended for 0.05 ms −1 since the supply of nutrients to the interior is not guaranteed. Under 0.05 ms −1 current velocity, the 400 mm central hole size is recommended since it leads to a more appropriate interior circulation. On the other hand, 0.08 and 0.1 ms −1 current velocities provide higher velocities inside the reef and thus the supply of nutrients to the interior is higher on the basis of the circulation flow pattern. Since a reef with 200 mm central hole size provides more surface to allocate nest cavities, a 200 mm central hole size is recommended for current velocities of 0.08 and 0.1 ms −1 . Table 4 summarizes the options recommended, i.e., 400 mm hole size for current speeds less than 0.08 ms −1 , and 200 mm for speeds above this value. Another reason is that greater velocities interfere more in the reef’s downstream currents. As will be indicated in Section 5.2, this parameter influences in the distance between artificial reefs that constitute an artificial reef group. The downstream current must remain as less altered as possible in order to avoid interferences in the reef/s placed downstream. This effect can be attenuated by diminishing the size of the central hole. On the contrary, reduced speeds interfere less in the reef’s downstream currents, which permits larger hole sizes. 5.2. Constitution of a reef group via modules: hydrodynamic criteria for separation between modules As mentioned above, the other parameter to be defined is the distance between reefs. The hydrodynamic criteria will determine the minimum distance between the modules or units of the reef group (DBU) in a way that all are subject to the same velocity fields and subsequently the same supply of nutrients brought by the sea currents. This criterion will determine the configuration of each reef group and the most adequate separation between them for the sustainable development of the ecosystem, Fig. 15. The separation between modules was determined based on assuming the re-establishment of the velocity field. For this, the speed deviation relative to the corresponding value of the free stream velocity was calculated. Under this condition, Fig. 16 shows the deviation with respect to the current velocity in the undisturbed zone (free stream velocity), as a function to the downstream distance of each module. Three cases were analyzed: 400 mm -central hole size with a current speed of 0.05 ms −1 , 200 mm central hole size with a current speed of 0.08 ms −1 , and 200 mm central hole size with a current speed of 0.1 ms −1 , establishing in each case the proposed minimum distances. Fig. 16 shows that an appropriate separation distance is around 3.5 m for 200 mm central Fig. 8. Geometry of the tube employed to constitute artificial reefs, Jiao et al. (2017). Fig. 9. Boundary conditions. Source: author’s own. Fig. 10. Length of affected back region obtained numerically and experimentally. Source: author’s own. L. Carral et al. Estuarine, Coastal and Shelf Science 252 (2021) 107301 9 hole size, while artificial reefs with 400 mm central hole size need around 4.5 m between units in order to guarantee the same velocity field and thus the same supply of nutrients. On the other hand, regarding the distribution and spacing of AR modules indicated by biology criteria, distinct alternatives are provided, spaces from a few meters to 30 m between AR modules (Bombace et al., 2000; Relini, 2000; Tian, 2018), and 300–500 m between AR groups (Costa and Neves, 2000; Leewis and Hallie, 2000). These are guideline distances to avoid the pressure of some species on others or on themselves to cause incompatibility with an adequate development – Distance between units - (DBU). Also, the reef groups are prevented from overlapping with fishing zones around the artificial reef where fish are captured. 6. Conclusions A methodology for determining the geometry of an artificial reef group adapted to the zone of implantation and based on hydrodynamic criteria is done in the present piece of research by defining the tool ART and implemented to the Ares-Betanzos estuary. The starting point of the ART tool is the existing reef model or AR unit’s design –a modular construction with productive and protective features– so that it can be adapted to the flow patterns where it is intended to be located. The ART Fig. 11. Design of the artificial reef. (a) 3D 200 mm hole size; (b) 3D 400 mm hole size; (c) A-A section 400 mm hole size. Source: author’s own. Fig. 12. (a) Computational mesh; (b) B–B section. Source: author’s own. Table 3 Input and output variables in HMFDP model. Source: Author’s own. INPUT TYPE OF MODEL OUTPUT - Threshold speedV m, and V 50% HMFDP-Hydrodynamic Model for Food Delivery Prediction CHScentral hollow size - PROARR AR unit DBU-distance between units L. Carral et al.