Preferential hydrodynamic, geomorphological, and vegetation ecology conditions for turtle nesting

Abstract

Sea turtles are a popular tourist attraction that offers travelers a unique nature experience. As a part of Saudi Arabia’s 2030 vision, an unprecedented amount of tourism development is being carried out under the ‘Red Sea Development Project’. The aim is to develop hyper-luxury islands in a sustainable and ecologically friendly way by closely following ‘Building with Nature’ principles. The tourism development site at Al Wajh Bank encompasses an archipelago of more than 90 islands and some of the sandy islands provide nesting grounds for Hawksbill and Green turtles. The thesis is a component of a broad study on investigating the preferential conditions for sea turtle nesting and conservation where TU Delft is collaborating with NIOZ and KAUST. The present study makes a preliminary assessment of the preferential conditions for sea turtle nesting of wave hydrodynamics and geomorphological conditions based on available data and numerical wave model simulations. The study is expected to provide information and guidance for future research for the conservation of sea turtle nesting at Al Wajh Bank.

The coral reefs provide breeding grounds for sea turtles in the gently sloping sandy beaches along the raised islands where the sand has ideal conditions of moisture, temperature, and distribution of sediment size for successful nesting and hatching of eggs at an optimum distance from the highwater line to avoid inundation by wave runup. In general, the foreshore at the turtle nesting site has a fore reef with a steep slope followed by a wide and shallow reef flat having high bottom roughness for dissipation of wave energy. The Al Wajh Bank spread over an area of 2880 km^2 has a very large and complex barrier reef system at the outer edge in the deep sea enclosing a massive lagoon with several islands. These islands have sandy beaches on the up wave (windward) side and mudflats with sand and vegetation in the sheltered zones. The vegetation is dominated by mangroves in the mudflats and seagrass in the shallow lagoon beds.

The study used the Delft3D WAVE stand-alone phase averaging spectral wave model for transforming waves from offshore to nearshore and to examine the energy dissipation characteristics of the reef system. The high-resolution bathymetry data for the Al Wajh Banks was obtained from GCC and relatively coarse resolution data for the offshore from GEBCO. The model simulated offshore wind and wave data validated using satellite altimetry, SAR, and Buoy measurements was obtained from BMT ARGOSS online services website “waveclimate.com”. The normal and extreme wave conditions were derived using this data. The data on GPS coordinates at the location of turtle nesting sites was provided by a survey undertaken by KAUST. A limited data on sediment size distribution at four islands south of Al Wajh Bank was made available by KAUST collected by ALS Arabia. The data on beach slopes, the distance of nests from HWL, geomorphology, vegetation was derived from secondary sources or in an indirect manner using bathymetry data.

The wave model results were analyzed for the nearshore wave heights and distribution of energy density at the fore reef and inside the lagoon. The wave model results revealed that the extensive barrier reef on the seaward side of the Al Wajh Bank is able to completely prevent and dissipate the energy of the offshore waves providing ideal conditions for turtle nesting at seaside islands. Further, the results show that the offshore waves do not have any role in the production and dissipation of wave energy inside the lagoon. The study confirmed that the waves inside the lagoon are exclusively local wind-generated waves. The wave climate inside the lagoon during storm conditions is only influenced by the prevailing strong winds and not dependent on the storm-generated extreme waves from offshore.

Most of the sea turtle nests have been found on the up wave or windward side of beaches with flat and wide reefs or fringing reefs between the reef crest and the high-water line. The wave model demonstrated the large energy dissipation rates under these geo-morphological conditions. In the absence of relevant data on sediments for the nesting and non-nesting beaches, no specific conclusions could be drawn. The beach slopes where sea turtle nests were abundant had slopes in the range of 1:10 and 1:20. The study indicated that the non-nesting sites inside the lagoon are in the sheltered zones of inner reef shelfs and behind the islands where mudflats with mangroves and other vegetation are abundant.

The wave runup is estimated using the HyCReWW metamodel at the nesting and non-nesting sites. The metamodel estimates indicated that the wave runup is of comparable magnitude both for the nesting and non-nesting sites. The comparison of runup distance along the beach indicated that the turtle nesting sites are located sufficiently away from the runup computed for 1 in 100-year wave height

A satellite imagery-based global shoreline data source (Shoreline Monitor, Deltares/TUDelft) was used to examine the erosion and accretion trends at Al Wajh Bank. The data identified two of the islands as having chronic erosion which have a small percentage of nesting sites. The analysis of the data identified that the turtle nesting sites are located on beaches with stable erosion/accretion rates.

The study confirmed the limitations of the Delft3D WAVE (SWAN) model used in simulating IG waves. Due to the very large domain and the course grid adopted in the present study the wave setup aspects have not been covered. The present study was useful in providing a range of information and guidance for further hydrodynamic and geomorphological data inputs at a regional scale and application of models like X-Beach or SWASH for a more comprehensive and detailed analysis on the influence of the surf and swash zone dynamics including IG waves on the sea turtle nesting sites. A systematic data acquisition on geomorphological and sediment characteristics will be useful for logistic regression analysis to study the dominant factors influencing the turtle nesting and non-nesting sites.