Disaster Risk Analysis of Merapi Volcano Eruption in Cangkringan District Sleman Regency

Abstrak Cangkringan is located in the Merapi Volcano Disaster Prone Areas which has the potential to be affected by eruption. The eruption of Merapi Volcano is a consequence that must be faced by the local resident, so that the need for disaster risk analysis in the region through research is a must. This disaster risk analysis research aims to (1) Analyze the risk level of Merapi Volcano eruption in Cangkringan. (2) Analyze the risk distribution of Merapi Volcano eruption in Cangkringan.This research is a descriptive research with a quantitative approach conducted in Cangkringan District, Sleman Regency, Special Region of Yogyakarta. The population in this study is the entire village in Cangkringan. The entire area is the subject of this research. The variables of this reseach are hazard, vulnerability and capacity. This study used primary data and secondary data. Data collection techniques used are observation, interviews, and documentation. Data analysis techniques used are scoring, overlay and descriptive.The results of this study indicate: (1) The level of risk of Merapi Volcano Eruption in Cangkringan is divided into four levels which are high, medium, low and very low. The area of Cangkringan has a high level of risk covering an area of 19,00% of the total area, the medium-risk level is 38,38% of the total area, the low-risk level is 16,61% of the total area, the very low-risk level is 20,23% of the total area of Cangkringan District. The higher the level of disaster risk, the greater the potential loss due to the eruption of Merapi Volcano. (2) The distribution of disaster risk of Merapi Volcano Eruption in Cangkringan is in the entire village. The distribution of high-risk level is in part of Umbulharjo Village, part of Glagaharjo Village and part of Argomulyo Village. The distribution of medium-risk level is in part of Umbulharjo Village, part of Kepuharjo Village and part of Glagaharjo Village. The distribution of low-risk level is in part of Kepuharjo Village, part of Wukirsari Village and part of Argomulyo Village. The distribution of very low-risk level is in part of Wukirsari Village and part of Argomulyo Village.

A Review of the Possibility of Assessment Indicators for Natural Disaster Risk Analysis through Expert Survey

In recent years, the frequent occurrence of extreme weather due to climate change has increased the possibility of potential danger across the world. Additionally, South Korea has been consistently exposed to disaster risk. Studies on the prediction of damage from natural disasters are critical for the government and local governments to formulate disaster recovery policies. However, the scope of risk analysis evaluation indicators currently utilized by the relevant organizations comprises limitations, as there are no consistent standards for indicator selection. From this viewpoint, this study selected 118 surrogate indicators, including indicators frequently used in previous studies, and conducted a survey with 52 experts in the disaster field to examine the possibility of use of these indicators. As a result of the expert survey, 37 indicators were analyzed as “very appropriate” and 54 indicators were analyzed as “appropriate” regarding their possibility of use. Finally, we suggested four natural disaster risk assessment methods, which can be used in policymaking by the government and local governments in the future.

Analisis Risiko Bencana Kebakaran di Kecamatan Tambora Kota Administrasi Jakarta Barat

Tambora sub-district is a sub-district that has the smallest area in West Jakarta with the largest population, causing Tambora sub-district to be a densely populated area. Population density which is not matched by the carrying capacity of the environment causes a region to become slum and prone to fire disasters. This study aims to analyze the level of risk of fire disasters in Tambora Subdistrict, West Jakarta. The methodology used in this study were the Multi Criteria Evaluation (MCE) analysis and fire disaster risk analysis by considering the relationship between the hazard and vulnerability variables. The results of the fire disaster risk analysis showed that the most dominant level of fire risk was a moderate risk level of 65.7%, a high risk level of 27.8% and the smallest was a low risk level of 6.5%. Viewed from the size of the area included in the medium and high risk of fire, indicating that Tambora Subdistrict is a subdistrict prone to fire and has a large potential loss of both property and life.

DISASTER RISK ANALYSIS OF FOREST AND LAND FIRES IN SERANG REGENCY

Forest and land fires (Karhutla) is one of the disasters that frequently hit Indonesia every year. Assessment for Karhutla's hazard, vulnerability and risk is an important early instrument for determining future disaster mitigation measures. The purpose of this study was to perform disaster risk assessment for Karhutla based on forest and land fires hazard and social vulnerability in the Regency of Serang. This particular hazard, vulnerability and risk analysis was based on the guidance outlined in the Head of BNPB Regulation No. 2 of 2012. The analysis results show that 46.87% of the total settlement area in the Regency of Serang falls into the low risk class of Karhutla. Meanwhile, medium and high risk class of Karhutla accounted for approximately 37.78% and 0.90% of the total settlement area in the Regency of Serang, respectively. Future detailing is needed to obtain more detailed results in the future.

Disaster Risk Analysis Part 2: The Systemic Underestimation of Risk

How risk is defined, the nature of methodologies used to assess risk, and the degree to which rare events should be included in a disaster risk analysis, are important considerations when developing policies, programs and priorities to manage risk. Each of these factors can significantly affect risk estimation. In Part 1 of this paper [Etkin, D. A., A. A. Mamuji, and L. Clarke. 2018. “Disaster Risk Analysis Part 1: The Importance of Including Rare Events.” Journal of Homeland Security and Emergency Management.] we concluded that excluding rare events has the potential to seriously underestimate the cumulative risk from all possible events,For example, of the 100 most expensive weather disasters in the US, the single most expensive event accounts for 16% of total economic impacts. Similarly, the worst explosion disaster accounts for 17% of the fatalities of the total 100 worst events. though including them can be very challenging both from a methodological and data availability perspective. Underestimating risk can result in flawed disaster risk reduction policies, resulting in insufficient attention being devoted to mitigation and/or prevention. In Part 2, we survey various governmental emergency management policies and methodologies in order to evaluate varying equations used to define risk, and to assess potential biases within disaster risk analyses that do comparative risk ranking. We find (1) that the equations used to define risk used by emergency management organizations are frequently less robust than they should or are able to be, and (2) that methodologies used to assess risk are often inadequate to properly account for the potential contribution of rare events. We conclude that there is a systemic bias within many emergency management organizations that results in underestimation of risk.

A Tool for Comparative Disaster Risk Analysis and Evaluation in Urban Areas (Draes)

The issue of examining the earthquake safety for existing constructions, which form the basis of urban mitigation strategies, requires new methods and tools according to each city’s and society's specific conditions. The common goal in all methods is to yield correct results in a timely manner. However, due to the multiplicity and complexity of the parameters used in the examination, auxiliary tools are needed. This is not only because of difficulties in collecting data, but also in order to obtain reliable results. Thus, collected data must be analyzed in computerized environment. In this study, an evaluation tool (software) called "Disaster Risk Analysis and Evaluation System (DRAES)" is developed. This software has been implemented and tested in Antalya; one of the metropolitan cities of Turkey within an area of 8800 hectares at 26610 buildings. The obtained results were evaluated comparatively which determined, consequently, the priority areas for planning as an important input for the city of Antalya. In this study, the general structure and working principle of the developed software are given. The source codes and data base of the program have been registered in accordance with the regulation on Registration of the Intellectual and Artistic Works of the Ministry of Culture and Tourism.

Disaster Risk Analysis Part 1: The Importance of Including Rare Events

Rare events or worst-case scenarios are often excluded from disaster risk analysis. Their inclusion can be very challenging, both from methodological and data availability perspectives. We argue that despite these challenges, not including worst-case scenarios in disaster risk analysis seriously underestimates total risk. It is well known that disaster data sets generally have fat tails. In this paper we analyze data for a number of disaster types in order to empirically examine the relative importance of the few most damaging events. The data show consistent fat-tail trends, which suggests that rare events are important to include in a disaster risk analysis given their percentage contributions to cumulative damage. An example of biased risk estimation is demonstrated by a case study of risk analysis of tanker spills off the western coast of Canada. Incorporating worst-case scenarios into disaster risk analysis both reduces the likelihood of developing fantasy planning documents, and has numerous benefits as evidenced by applications of foresight analysis in the public sector. A separate paper "Disaster Risk Analysis Part 2" explores how disaster risk analyses are operationalized in governmental emergency management organizations, and finds evidence of a systemic underestimation of risk.