Elsevier

Ocean & Coastal Management

Volume 120, February 2016, Pages 135-147
Ocean & Coastal Management

Estimation of effective usable and burial volumes of artificial reefs and the prediction of cost-effective management

https://doi.org/10.1016/j.ocecoaman.2015.12.007Get rights and content

Highlights

  • Effective usable and burial volumes of artificial reefs were proposed.

  • Five parameters were redefined to clarify their use.

  • Volume coefficients were proposed from geometric hypotheses.

  • We demonstrated how to realize the volume coefficients for a prediction.

  • We discussed the prediction method for cost-effective management.

Abstract

In this study, effective usable and burial volumes were used to estimate the current state of nine cube-type artificial reefs (AR) constructed between 1987 and 2002. Three volume coefficients (k1, k2, and k3) were proposed for estimation of the total loss, effective usable volume, and burial volume of ARs, based on the recorded facility standard volume and seabed condition at the time of construction. Five parameters were redefined to clarify their use; two measures and three statistically obtainable coefficients were proposed from geometric hypotheses. Field data obtained from coastal waters near Busan in South Korea were used to demonstrate the estimation and prediction of these parameters. We determined that the burial volume of an AR can be predicted with less than 20% error using the mean values of k1 = 1.33, k2 = 1.36, and k3 = 1.37 for a rigid seabed and k1 = 1.32, k2 = 1.72, and k3 = 1.83 for a soft seabed. The effective usable volume can be predicted with less than 11% error using the mean values, seabed condition, and facility standard volume determined at the design stage. We found that it is unnecessary to use multi-beam echo, side scan sonar, and divers' investigation for prediction; hence, a cost-effective method was developed for the future management of ARs.

Introduction

The United Nations Environment Program (2009) categorised artificial reefs (ARs) into environmental (biodiversity or ecosystem management, restoration, water quality management, etc.), living marine resource (attraction, enhancement, production and protection), promotion of tourism and leisure activities (angling, SCUBA diving, surfing, boating, etc.), scientific research and education, and multi-purpose structures. This description shows the escalating use of ARs in coastal areas. Considering environmental and living marine resource structures, there is a debate regarding the issues of attraction and production that must be resolved (Ambrose and Swarbrick, 1989, Bohnsack, 1989, Bohnsack et al., 1994, Bombace et al., 1994, Frazer and Lindberg, 1994, Grossman et al., 1997, Charbonnel et al., 2002, Bortone, 2011, Dafforn et al., 2012, Flopp et al., 2013). Several solutions have been suggested, such as commercial ranching substrates for key target species (Pickering and Whitmarsh, 1997), no-take zones, protected manmade reefs (Pitcher and Seaman, 2000), and marine protected areas (Claudet and Pelletier, 2004). There has also been extensive work with the other AR functions, such as managing recreational diving (Kirkbride-Smith et al., 2013), coral settlement (Blakeway et al., 2013), rigs-to-reefs programs (Ajemian et al., 2015), ARs used for scour protection in offshore renewable energy sites (Langhamer, 2012), artificial surf reef (Cáceres et al., 2010, Ranasinghe et al., 2006), and multi-purpose structures (Moschella et al., 2005). Most of these works have focused on the ecological effects of manmade reefs on the surrounding environments and the interaction with marine species.

Engineering-related works for the design, installation, and management of ARs have been carried out for wake estimation (Nakamura, 1985, Sawaragi, 1995, Sheng, 2000, Oh et al., 2011, Kim et al., 2014a, Kim et al., 2014b), general AR drag coefficient calculation (Woo et al., 2014), calculation of the hydraulic characteristics of selected AR modules (Al-Bourae et al., 2013, Liu and Su, 2013, Liu et al., 2013), estimation of the hydrodynamic forces on ARs (Takeuchi, 1991, Düzbastilar and Şentürk, 2009), and the chemical and physical degradation of concrete ARs (Kim et al., 2008a, Kim et al., 2008b). There are also intensive works that review the practices and guidelines for ARs that are almost impossible to pinpoint. Representative works include a summary of AR monitoring in Floridian coastal counties (Seaman, 2004), guidelines and management practices for ARs in Southeast Florida (Lindberg and Seaman, 2011), a perspective on the future of ARs of Europe (Jensen, 2002), the use of ARs for aquatic habitats in Japan (Grove et al., 1994), AR designs for Korean coastal waters (Kim et al., 1994), the present status of ARs in Thailand (Kheawwongjan and Kim, 2012), a review of ARs in Taiwan (Chang, 1985), marine artificial reef materials (Lukens and Selberg, 2004), and a review of AR design, application, management, and performance (Baine, 2001).

In terms of management, these manmade structures have been classified into scales by module, set, group, and complex (Grove and Sonu, 1985), as shown in Fig. 1, which describes the hierarchies among the scales. These scales are usually established or realised through AR placement models, such as the intensively stacked placement model (ISPM), flatly concentrated placement model (FCPM), and flatly distributed placement model (FDPM). Fig. 2 shows the three placement models, captured by multi-beam echo sound (MBES) and recorded in coastal waters near Busan, the second largest city in South Korea (National Fisheries Research and Development Institute, 2008). ISPM and FDPM are usually implemented for smaller ARs to attract fish, whereas FDPM is implemented for larger ARs to attract fish or to establish marine forests (seaweeds) in smaller ARs. The construction of these AR placement models has been achieved by free fall (downward movement by gravitational force) for smaller artificial reefs and guided movement through wires, chains, and divers for larger artificial reefs.

Fig. 3 shows the area and facility volume of cube-type artificial reefs (hereafter, AR1) as a fraction of all ARs installed in Korean coastal waters from 1971 to 2013 (Ministry of Oceans and Fisheries, 2013). As shown, AR1s account for 64.5% of the total area and 67.4% of the total facility volume. These statistics illustrate the popularity of cube-type ARs in South Korea, primarily due to their simple shape, good workability, and low cost. AR1s are made from concrete and reinforcing bars, and typically measure 2 m × 2 m × 2 m, for an apparent facility volume of 8 m3, and a weight of 33.34 kN (3.4 tons). It is known that AR1s are suitable for fisheries and the protection of migratory fish, due to the relatively large void at each surface (Kim et al., 2014b).

According to the Korean regulations, an AR should have a facility volume greater than 800 m3 (Kim et al., 2009a, Kim et al., 2009b). Based on a standard volume of 8 m3, at least one hundred AR1s should be installed to create an AR set. After installation, it is necessary to investigate the condition of an AR for further management of concrete reefs. Reinforced concrete reefs immersed in seawater for 18–25 years were investigated (Kim et al., 2008a, Kim et al., 2008b), and their physical and chemical degradation characteristics were identified through destructive and non-destructive tests. The AR1s were physically and chemically robust, and the originally estimated service life was sufficient for a further service period in water depths between 28 m and 32 m. In addition to material degradation, the settlement and scour of ARs are important in design and management, as they cause loss of facility and usable volumes, and stability of ARs. Therefore, settlement and scour have been investigated for single AR modules and sets (Kim, 2001, Yoon and Kim, 2001, Manoukian et al., 2011), by measuring stability. For the estimation of facility and usable volumes as a result of settlement, Kim et al., 2009a, Kim et al., 2009b introduced an effective usable volume. However, this measure was not properly defined, and so their applications were limited to a facility volume rather than usable volume. For effective management of ARs installed as a set, it is necessary to not only clearly define but also reasonably estimate the required measures (e.g. facility and usable volumes) of an AR set. To reduce the cost of measurements, usually performed by divers, MBES, and side scan sonar (SSS), it is preferable to develop a low-cost prediction method. It should be noted here that the usable and facility volumes of an AR set do not include wake and upwelling regions, which are mostly constructed outside the usable volume by the interactions between ARs and prevailing water flows. It is known that the wake region can facilitate the deposition of sediments and nutrients in the space behind an AR set (Kim et al., 2014a, Kim et al., 2014b), whereas the upwelling regions facilitate transport sediments and nutrients from the bottom of the water column to the surface water (Yanagi and Nakajima, 1991, Kim and Shimasaki, 2013).

This study proposes two major measures – effective usable and burial volumes – to estimate the current states of nine cube-type AR sets, constructed between 1987 and 2002. Three volume coefficients (k1, k2, and k3) were proposed to estimate the total effective usable volume loss and burial volume of ARs, using recorded facility standard volumes and seabed conditions at the time of installation. Five parameters (usable volume, facility standard volume, rate of facility volume, rate of usable volume, and rate of effective facility volume) were re-defined to clearly describe their physical meaning; two measures (rate of effective usable volume and associated burial volume) were proposed to estimate seabed settlement; and three statistically obtainable coefficients were proposed to predict the total loss of ARs, effective usable volume, and burial volume. Nine AR sets, installed in coastal waters near Busan in South Korea, were investigated through field measurements recorded by divers, MBES, and SSS. Intermediate analysis was carried out to apply the re-defined or newly proposed measures to the field data, and these measures were compared to estimate the current physical states of the nine AR sets. Finally, a method for the prediction of AR total loss, effective usable volume, and burial volume was demonstrated using volume coefficients. This study identifies physical measures associated with facility and usable volumes, proposed volume coefficients to predict the total loss of ARs, and effective usable and burial volumes for cost-effective management.

Section snippets

Propositions

To quantify the current state of installed ARs, six measures were introduced. Some of these measures were initially proposed by the National Fisheries Research and Development Institute (hereafter NFRDI), and consequently modified by Kim et al., 2008a, Kim et al., 2008b. However, their works had some errors owing to misconception in definitions, improper explanations for the formulae, and inaccurate results from the field. Therefore, attempts were made to correct these definitions with

Field sites and surveys

Table 1 lists the nine AR sites constructed by ISPM, and located near Busan in South Korea (Fig. 9). These AR sets were constructed using the cube-type AR modules installed since 1987 to enhance marine habitats for fish. Depending on the installed years (1987–2002), the ages of AR sets were quite different, ranging 5 to 20 with respect to the surveyed year of 2007. However, we assumed that the nine AR sites have been stabilized in the form of the spherical cap at the investigation moment. In

Conclusions

This study proposes the use of two parameters – effective usable volume and burial volume – to estimate the current state of nine cube-type AR sets constructed between 1987 and 2002. Three volume coefficients (k1, k2, and k3) were proposed to estimate the total AR loss, the effective usable volume, and the burial volume using the facility standard volume and seabed condition recorded at the time of installation. Five parameters were re-defined to clarify their use and limits, two measures and

Acknowledgement

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2015R1D1A3A01019657).

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