Controlling variables
The nine variables used in this study can be classified into three categories: 1. Five structural variables of (a) geology, (b) geomorphology, (c) topography, (d) shoreline change, and (e) shoreline exposure; 2. Three physical process variables of (f) relative sea-level rise, (g) significant wave height, and (h) mean tide range; and 3. A socioeconomic factor (i) land-use. The data were obtained from various sources (fieldwork, maps, aerial photographs, satellite image, and bibliography; Table 1) and described in subsections below. Direct field surveys for collecting coastal geomorphology and land-use data were conducted along the entire coastline of Ngazidja. During low tide, we walked from 3 to 5 h to take measurements and geo-referencing (For example, cliffs) using a decametre and GPS. The classification of these variables was made while on the spot based on previous studies (For example, Mclaughlin and Cooper 2010; Nurhuda et al. 2019). The collected data was subsequently integrated into ArcGIS software and combined with high-resolution (1 dpi) aerial photographs.
(a) Geology
This variable relates to the erodibility risk of bedrock that is subject daily to waves. Accordingly, unconsolidated rock is assigned to a high vulnerability (Shaw et al. 1998). Ngazidja Island volcanic rocks include aphyric, olivine, plagioclase-phyric, and alkali olivine basalts, basanites, ankaramites, oceanites, and hawaiites derived from Karthala and La Grille volcanoes lava flows (Fig. 2.a). The weathering degree allows distinguishing the older from the recent lava (Bachèlery and Coudray 1993; Bachèlery et al. 2016). For example, , recent lava flows of Karthala and La Grille indicate a high degree of weathering resistance compared to the older lava flows of Karthala and La Grille volcanoes which are more prone to weathering. The most indurated lava flows are recent, about 19th and 20th centuries, with little to no alteration in surface features. They indicate no habitation and a total absence of vegetation. The indurated lava flow has a conserved upper unit and a smoothed lower unit. The moderately indurated lava flow exhibits a preserved upper unit, or a little smoothed, while the lower unit is smoothed without significant weathering. The advanced weathered lava shows smoothed without obvious limits upper flows and erased flow limits of lower flows. The most weathered lava flow is smooth with ferralitic weathering. Their spatial distributions along the coastline are 34.8%, 38.8%, 16.3%, 15.5%, and 2.9%, respectively (Fig. 3a).
(b) Geomorphology
Most of the Ngazidja Island coastline comprises resistant basaltic rocks, beaches and unlithified rock cliffs (with an average of 2 to 3 m in height) which are the most vulnerable to wave actions. Although the unlithified rock cliff is active, it revealed no sign of a landslide. The most stable coastal landform is a high hard cliff (exceeding 10 m) and is assigned to a rank value of 1. A medium-hard sea cliff (5 - 10 m) can mitigate erosion effects, but it is sensitive to sea-level rise caused by cyclone and tsunami waves. Compared to the preceding one, the low rocky cliff is subject to inundation in the context of sea-level rise. Figure 3b displays the coastal subdivision in terms of geomorphology. The high hard cliff occupies only 3.4% of the coastline. Medium-hard sea-cliff and low rocky cliffs are the most represented with 26.8% and 66% of the coastline, respectively. Unlithified rock cliff and beaches spatial distributions are 1% and 2.8% of the coastline, respectively.
(c) Topography
Coastal hazard assessment considers relief as a determining factor. A high risk is commonly associated with low-lying coastal areas (Hereher et al. 2020). The contour line of 100 m located 650 m from the shore is outside the sea influence. It is considered in this study as a reference to classify this variable (Table 1). The coastal topography is extracted from a Shuttle Radar Topography Mission (SRTM) on https://glovis.usgs.gov. The scene has a resolution of 30 m, absolute horizontal and vertical accuracies of 20 m and 16 m, respectively. The SRTM indicates that about 13% of the coastline is under the contour line of 10 m. 73% and 11% of the coastline are located between 11 and 30 m and 31 and 50 m, respectively (Fig. 3c). Only 2% of the coastline is above the contour line of 50 m.
(d) Shoreline change
The shoreline change study is performed over three decades. Shorelines (high-water mark) are extracted from Landsat TM1989 and OLI2019 scenes with 30 m resolutions in Idrisi SELVA software by the band-ratioing method (Zhou et al. 2019). Shoreline change rates are computed using the End Point Rate method through the Digital Shoreline Analysis System tool of ArcGis. The results are accurate with a margin of error of +/-0.1 m/yr over the three decades. Most of the coastline (about 97.4% of the coastline) shows a retreat varying between 0 and -1 m/yr. Some sedimentary accumulations (2.1% of the coastline) display shoreline change rates between 0 and +1 m/yr. The maximum advance is due to fillings made to extend the port of Moroni, which led to a shoreline change of +1 to +4 m/yr on a section presenting 0.5% of the shoreline (Fig. 4a).
(e) Shoreline exposure
This variable was used in the Illawarra Coast to express the orientation of the shore relative to the wave direction (Abuodha and Woodroffe 2010). Shoreline exposure involves the main direction of the wave and the presence of promontory (e.g., coral reefs). This variable highlights the coral reef contribution to wave energy dissipation. Madagascar Island shelters the Comoros archipelago against severe waves from the East Indian Ocean. The southeast of Ngazidja Island also protected by the other three Comoros islands (Figs. 1a and 1b). Fringing coral reef edges about 60% of the coastline and it is being between 500 and 1500 metres in width. The important coral reef is situated in the northern part from Fassi to Ndroude and the southern part from Chindini to Male (Fig. 2a). Rigorous waves are associated with the dominant winds, in Kashkazi from the north and in Kusi from the south. According to these criteria, 28.2% of the coastline is sheltered. About 16.1%, 34.2%, and 21.5% of the coastline is semi-exposed, exposed, and fully exposed, respectively (Fig. 4e).
(f) Relative sea-level rise
Previous studies indicate the significant contributions of sea-level rise to coastal ecosystem degradation and loss of material assets. Sea level data adopted here are from satellite altimetry measures in the period 1992 - 2013 (Cazenave et al. 2015). The mean rate of sea-level rise was 4 mm/yr in the archipelago level. In this study, all the shoreline sections are assigned to a range of 4 – 5 mm/yr (Fig. 4f).
(g) Mean significant wave height
Ngazidja Island includes an entirely open wave-dominated coast. Wave height is related to the wind regime and tropical low-pressure system (Legoff 2011). In this study, wave height data was derived from measures realized offshore regions for austral summer and winter (Figs. 5a and 5b). Most frequent waves (70% - 80%) with heights between 2 and 3 m are from the south-southwest. During the austral summer, other rigorous waves are from the north-western part with frequencies below 10%. Wave heights less than 2 m occur with low frequencies (< 5%) in the East and West. Accordingly, about 42.2% of the coastline registers wave heights between 2 and 3 m. Waves of 1 to 2 m and less than 1 m in height reach 38.7% and 19.1% of the coastline, respectively (Fig. 6g).
(h) Mean tide range
This variable is widely discussed and shows different opinions according to the tidal regime. In a microtidal coastline (< 2 m), shores with smaller tidal range are assumed sensitive (Thieler and Hammar-Klose 1999). In a macrotidal coastline (> 4 m), coastal hazards are specifically significant in the highest tidal levels (Khan and Chatterjee 2018). Ngazidja Island coastline is mesotidal (2-4 m) and semidiurnal. The tide is constant throughout the year and the same on the whole of the coast. Several witnesses assert that spring tides can contribute to coastal floods on some shores of the island. Figure 5c shows the mean water levels at low and high tide noted at the Moroni Port station between 1970 and 2019. Accordingly, the whole coastline is assigned to the tidal range of 3.1 to 4.9 m in this study (Table 1 and Fig. 6h).
(i) Land-use
Coastal vulnerability depends on both the intensity of the hazard and the hinterland nature. Land-use variable is ranked into five classes: bare rocks, grassy and shrubby formations, farm field, village, and city (Yin et al. 2012). The youngest lava flows include bare rocks that are uninhabited. Accordingly, this class is attributed to the rank value of 1. Grassy and shrubby formations constitute the advanced stage with less weathered lava flows compared to the previous ones. The vulnerability increases with the farm fields’ class. Agriculture is the principal sector of occupation for most of the population. Villages and cities are the most vulnerable due to human life and infrastructure. Figure 6i depicts the Ngazidja coastline in terms of the land-use variable displaying 11.4% as bare rocks (very low vulnerable), 52.4% as grassy and shrubby formations (low vulnerability), 21.4% for farm fields (moderate vulnerability), 7.3% for villages (high vulnerability), and 7.5% for cities (very high vulnerability).
Data ranking and Coastal Vulnerability Index
The coastline is subdivided into 270 sections by the superimposition of all variable maps. Juxtaposed sections are different by least one class, and the shortest and longest ones measure 30 m and 6 km, respectively. The ranking of variables is based on local structural and hydrodynamic conditions. As in previous studies, degrees of vulnerability are ranked on a scale from 1 (very low) to 5 (very high; Table 1). The description of variables above indicates that all contribute equally to coastal vulnerability. Thus, the CVI is computed in this preliminary vulnerability assessment using the square root of the product of the ranked variables divided by the total number of variables (equation 1). This CVI formulation has the advantage of expanding the range of values (Shaw et al. 1998; Thieler and Hammar-Klose 2000; Hereher et al. 2020). Therefore, this formulation enables identifying the most determinant variables in coastal vulnerability.
A vulnerability ranking of CVI scores is established according to statistical parameters. Low, moderate, high, and very high vulnerability are assigned to four statistical ranks: [Minimum-1st quartile], ]1st quartile-Average], ]Average-3rd quartile], and ]3rd quartile-Maximum], respectively.