Learning from past earthquake disasters: The need for knowledge management system to enhance infrastructure resilience in Indonesia

Pribadi, Krishna S.; Abduh, Muhamad; Wirahadikusumah, Reini D.; Hanifa, Nuraini Rahma; Irsyam, Masyhur; Kusumaningrum, Patria; Puri, Eliza

doi:10.1016/j.ijdrr.2021.102424

Cited by 49 publications

(38 citation statements)

References 38 publications

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“…From the results of the map of earthquake-prone areas obtained from BPBD Ambon City will be covered with land cover map of Ambon City in 2021 and the results of the prediction of land cover in 2031, it can be seen the land built / settlements that are prone to earthquakes. So, it is in these areas that mitigation efforts both structural and non-structural must be optimally empowered [39]. Historically earthquake events will have a very large impact on the social, economic, and spatial conditions of an area prone to earthquakes.…”

Section: 4mentioning

confidence: 99%

Spatial Dynamics Model of Earthquake Prone Area in Ambon City

Rakuasa

Supriatna

Karsidi

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Ambon City has limitations in the development of residential areas because it is in an area prone to earthquake disasters, This is because Ambon City is in a very active tectonic area and 65% of settlement land / land built in Ambon City is in an active and weak fault zone and if there is a plate movement there will be an earthquake along the weak zone. One of the first steps to the effort to stigmatize disasters is to estimate how large the area of settlements that have been analyzed using cellular automata markov-chain located in earthquake-prone areas. This study aims to analyze changes in Ambon city land cover in 2012, 2017, 2021 and predict land cover in 2031 and synthesize spatial dynamics of settlement land availability with earthquake-prone areas in Ambon City in 2021 and 2031. This study uses Cellular Automata modeling to predict ambon city land cover in 2031 which will be covered with a map of earthquake-prone areas obtained from BPBD Ambon City to see residential areas that are in earthquake prone areas in Ambon City in 2021 and 2031. The results showed that the area of built land affected in earthquake-prone areas has a straight proportional relationship with the year of land development built. So that the more years then the area of land is built in areas prone to earthquakes and increasing. This research is expected to be used as a reference in the management of sustainable settlement area development and for efforts to organize space based on disaster mitigation in order to minimize losses and casualties due to earthquake disasters that will occur in Ambon City in this future.

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Section: 4mentioning

confidence: 99%

Spatial Dynamics Model of Earthquake Prone Area in Ambon City

Rakuasa

Supriatna

Karsidi

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…Mostafavi et al conducted a qualitative study based on the Nepal earthquake in 2015 to investigate the comprehensive factors affecting the seismic resilience of WSSs in developing countries from the perspective of economic, technology, organizational, and environmental factors ( 35 ). Pribadi et al analyzed five destructive earthquake disasters and summarized the technical and environmental factors affecting the seismic resilience of infrastructures, such as WSSs in Indonesia ( 36 ).…”

Section: Current Understanding Of the Resilience Of Wssmentioning

confidence: 99%

Seismic Resilience of Rural Water Supply Systems; Factor Analysis of Cases Set in Sichuan Province, China

Zhou

Kalonji

Chen

et al. 2022

Front. Public Health

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The seismic resilience of water supply systems can be impacted by numerous factors, but what these factors are in the rural context of China is unknown. In this study, 41 potential influencing factors of seismic-resilience for rural water supply system (RWSS) were obtained through a literature review and semi-structured expert interview, comprising 26 general influencing factors (GFs) and 15 water supply safety influencing factors (SFs). This study verified and ranked these factors through a questionnaire survey delivered to RWSS stakeholders in Sichuan Province, China. Based on 123 valid, returned questionnaires, these factors are divided into 9 factor groups through factor analysis performed on GFs and SFs, respectively, of which “economic resilience” and “organizational resilience in disaster prevention stage” are shown to be the most important factor groups. Additionally, it found that the experience of earthquake events significantly affects the perceptions of stakeholders on the importance of certain factors. Specifically, stakeholders who have experienced an earthquake prioritize the post-earthquake resilience of the system, while those who have not experienced an earthquake prioritize the absorption capacity of the system in the disaster prevention stage. Thus, it is not appropriate to use fixed weights to evaluate the seismic resilience of RWSSs. Significantly, this outcome differs from existing findings on the resilience of Urban Water Supply Systems (UWSSs), where “technical resilience” is the key dimension. These findings can help decision-makers fully understand the factors affecting the seismic resilience of RWSSs in China, and in doing so, augment the strengthening of rural water supply.

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“…Floods, landslides, erosions, earthquakes, volcanic eruptions, tsunamis, and forest fires are a series of disasters that occur almost every year in Indonesia. Indonesia's geological condition, as it is located in the plate confluence zone, causes geological disasters (Arifin, 2016;Pribadi et al, 2021). The potential for disasters is exacerbated by global climate change, which has become an international issue recently (Haggag, Yosri, El-Dakhakhni, & Hassini, 2022;Hansen, 2022).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of land resilience against natural disasters using ecosystem services approach in Kendari City, Southeast Sulawesi, Indonesia

Restele

Saleh

Iradat

et al. 2022

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Kendari City has multiple disasters hazard, especially floods and landslides. Consequently, the city requires systematic preventive efforts to minimize the potential disaster risk. This study aims to create a spatial model to determine the resilience of the land against floods and landslides with an ecosystem services approach. We used Sentinel-2 and DEMNAS (National Digital Elevation Model of Indonesia) as our primary data collection tools. Sentinel-2 was used to compile land use maps, and DEMNAS was the basis for compiling landform maps. The integration of the two was carried out by the analytic hierarchy process (AHP). The results showed that 8,259.98 acres (30.01 percent) of land in Kendari had low resilience to disasters. Those areas are located in a residential area on the TWH (Rocky hill over mixed sedimentary rocks) and KHY (Coalescent estuarine/riverine plain) landforms. The dominant disaster hazard in the area is inundation flooding that occurs almost every year in Kendari. Poor soil infiltration capacity is one factor affecting the area become vulnerable to flooding.

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Learning from past earthquake disasters: The need for knowledge management system to enhance infrastructure resilience in Indonesia

Cited by 49 publications

References 38 publications

Spatial Dynamics Model of Earthquake Prone Area in Ambon City

Spatial Dynamics Model of Earthquake Prone Area in Ambon City

Seismic Resilience of Rural Water Supply Systems; Factor Analysis of Cases Set in Sichuan Province, China

Evaluation of land resilience against natural disasters using ecosystem services approach in Kendari City, Southeast Sulawesi, Indonesia

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