The Socioeconomic Vulnerability of Coastal Communities to Abrasion In Samas, Bantul Regency, Indonesia

Climate change is a global issue that significantly affects archipelagic countries (Hereher 2016, Schmutter et al. 2017, Senapati, Gupta 2017,). This issue also applies to the biggest archipelago in the world, Indonesia. It consists of 13,466 islands with 81,000 km long shoreline and seas as wide as 3.1 million km² or 62% of its territorial area (UNCLOS 1982). According to the Climate Conference in Warsaw, the coastal regions in Indonesia are inhabited by 42 million people and predicted to experience the negative impact of climate change (Duckers et al. 2015, Neale, Weir 2015, Taylor, Peace 2015, Ullah et al. 2015). The impact is felt particularly in Java Island because 65% of its population lives in coastal regions and grows by 2.2% per year, which is higher than the national average growth rate (Miladan 2009). Setiyono (1996) states that erosion is the process of coastal material removal by the destructive force of sea waves and currents. Similar phenomena are also explained by Mahapatra (2015), Fitton et al. (2016), Merlotto et al. (2016), Ghosh (2017), Yankson et al. (2017), Bevacqua et al. (2018), Chang et al. (2018), and Onat et al. (2018). Breaking waves are also able to transport or move loose materials on the shoreline into the sea, generating an abrasion process (Sutikno 1999, Marfai et al. 2008, Wesli et al. 2013, Widianto, Damen 2014). From strategic point of view, the impact of abrasion is a decline in land surface; while from environmental point of view, it is the loss of habitats in an ecosystem (Ongkosongo 2011). Marfai (2011) explains that coastal erosion has serious negative impact, such as damaged public facilities and settlements as well as deforestation, which are argued to be the triggers for the widespread negative impact of coastal erosion.

Coastal erosion is a significant implication of sea level rise on sandy or muddy beach that induces shoreline change as a form of equilibrium beach profile (Marfai, King 2008, Numberi 2009). According to the Regional Disaster Management Agency of Bantul Regency, the coastal regions in the southern area experience large waves and coastal erosions every year. Coastal erosion wears away most of the land along the beach and causes harm to the society (BNBD Kabupaten Bantul, 2016). Among the other coasts in South Bantul, Samas Coast suffers from the severest erosion. This condition is due to sands blocking the mouth of Opak River, which cause a lagoon to form and prevent the river water from flowing into the sea. The Office of Marine Affairs and Fisheries of Bantul Regency states that the lagoon has potentials for marine tourism and that it can improve regional economy and local welfare (DKP Kabupaten Bantul 2016). Therefore, physical infrastructures and facilities become necessary to support it as a tourist attraction (Sidik 2013). However, intensive erosion will remain a threat to the sustainability of its development if the problems induced by coastal erosion are not solved immediately.

The extent of coastal erosion impact is strongly influenced by the capacity or the vulnerability of at-risk elements. Van Westen and Soeters (2006) defines at-risk elements as all objects, humans, animals, and activities or processes, including buildings, public facilities, population, economic activities, and environments, that are affected by a disaster event in an area either directly or indirectly. Meanwhile, capacity is depicted as ability, i.e. the combination of all of the strengths of a society, a social community, or an organization that can reduce the impact of risks or hazards. It is formed through various economic, social, or institutional ways, individual or communal skills, as well as organizations or leaderships that result in the reduction of risk or hazard level. In terms of disaster risk reduction, capacity is influenced by, for example, the functions of available resources in an area (UNISDR 2004).

Vulnerability is the exposure level of at-risk elements (humans and things) to threats (Maarif et al. 2014, Islam et al. 2016, Nur, Shrestha 2017, Raufirad et al. 2017, Yadav, Barve 2017, Jurjonas, Seekamp 2018). It represents the condition of a society or a community that shapes their inability to deal with and minimize the impact of hazards, which will lead to damages and disruptions if disaster attacks (Sutikno 2002, UNDP 2004, Bakornas PB 2007, Sakijege 2013, Rijanta et al. 2014, Zorn, Shamseldin 2015, Figerio, Amicis 2016, Fatemi et al. 2017, De Silva et al. 2018). In disaster management context, this condition is determined by physical, social, economic, and environmental factors or processes (UNISDR 2009) that control the ability to prevent, mitigate, prepare, and respond to the impact of hazards.

The spatial presentation of disaster information is essential for risk reduction particularly in providing data that can be utilized directly by the society to familiarize themselves with the condition of their environment (Setyaningrum, Giyarsih 2012, Rachmawati, Budiarti 2016). Therefore, the extent of coastal erosion impact can be minimized by initially providing disaster information. Based on the authors’ knowledge, no research has specifically documented the socioeconomic vulnerability of the population to coastal erosion and the community capacity in Samas Coast to deal with coastal erosion. Referring to this background, this research becomes necessary. This research applied this mitigation measure by aiming to (1) analyse the physical, social, and economic vulnerability level in Samas Coast and (2) analyse the capacity of the local communities to deal with coastal erosion in the study area.

This research was conducted in Srigading and Gadingsari Villages, Samas District, Bantul Regency with survey method. In order to achieve the first objective, i.e. to analyse the physical, social, and economic vulnerability, this research applied the Spatial Multi Criteria Evaluation (SMCE) method. In this case, the SMCE employed a weighting method using pairwise comparison. Meanwhile, in order to achieve the second objective, i.e., to analyse the capacity level of the local population, it used scoring technique and statistical data analysis on the result of the structured interview. SMCE is a vulnerability assessment method that uses both spatial and statistical data as an input to produce a map with composite index. In this research, the spatial variable (i.e. physical parameter) was combined with the quantitative data (i.e. socioeconomic parameter) producing a composite map with spatial information and statistical attributes. The output of this method can assist in planning and decision making for development policy more specifically compared to statistic data presentation like graph, table, picture, chart, and calculation (Rahmat 2015).

The analysis unit was village, especially the villages located in highly vulnerable areas to coastal erosion. The variables of vulnerability in this research are presented in Table 1. The SMCE method for vulnerability assessment consisted of four steps, namely structuring the problem into criteria tree, standardization, weighting, and selecting scenario. The output of this method is a vulnerability map with spatial information and statistical attributes.

In order to assess the capacity level of the communities, the households were selected using multistage random sampling technique. Based on the Harry King’s Nomogram (Fig. 1), a 90% confidence level requires a sample size of 5% of the total population. Gadingsari and Srigading Village have 395 and 713 households, respectively. Therefore, a 90% confidence level over a total population of 1,108 households requires the following sample size:

Fig. 1

Meanwhile, the capacity level was obtained using Likert (1932) scaling on the information provided by the respondents. It was divided into three classes, namely low, medium, and high (Table 2).

Based on the results of the physical, social, and economic vulnerability assessments using the SMCE method, this research decided to compare three scenarios of total vulnerability, namely physical scenario, socioeconomic scenario, and equal scenario. The physical and socioeconomic scenarios show that Srigading has a high vulnerability level, whereas Gadingsari has a low vulnerability level. In addition, the spatial distribution of the total vulnerability produced from equal scenario is the same as that of physical and socioeconomic scenarios. As a conclusion, both physical and socioeconomic scenarios produce relevant outputs because they give the same result and distribution as the equal scenario.

Furthermore, in terms of physical parameter, Srigading is more vulnerable than Gadingsari because its settlement is located close to the shoreline that receives direct impact from coastal erosion. Meanwhile, based on the social and economic parameters, Gadingsari is more vulnerable than Srigading because it has higher population number as well as a higher share of demographically disadvantaged people (i.e. women, toddlers, children, elderly, and disabled people). Because many social variables are vulnerable or exposed to coastal erosion risk, Gadingsari has a high social vulnerability. Moreover, a large number of poor households, unemployed people, as well as people whose jobs are affected by coastal erosion lead to the more presence of at-risk economic elements in this village.

The paucity of economic facilities shows that both Srigading and Gadingsari have low economic condition, which influences the community capacity in terms of disaster mitigation and post-disaster recovery. Based on the knowledge of coastal erosion and its risk reductions, the capacities of the people in both villages are categorized as medium. This level of capacity is influenced by first-hand experiences on coastal erosion that increase the awareness of the local communities, particularly those who live close to shoreline.