Environmental sensitivity index mapping as a prevention strategy against oil spill pollution: A case study on the coastal area of South Sumatera Province in Indonesia

Rustandi, Yudi; Damar, Ario; Rakasiwi, Galih; Afandy, A; Hamdani, Agus; Mulyana, Dadan

doi:10.1088/1755-1315/414/1/012019

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…Semakin tinggi skor, semakin besar tingkat keterpaparan dan sensitifitas mangrove terhadap minyak (NOAA, 2002). Adapun parameter yang digunakan dalam membentuk IS (Tabel 3) mengacu pada Rakasiwi et al (2020) dan Rustandi et al (2020).…”

Section: Pengumpulan Dataunclassified

“…Nilai dari masing-masing parameter yang membentuk IK, IE dan IS selanjutnya akan membentuk nilai IKL ekosistem mangrove. Perhitungan IK dan IE mengacu pada Ali et al (2008) dan Stjernholm et al (2011), sedangkan perhitungan IS mengacu pada Rustandi et al (2020) dan . Semua parameter yang digunakan diasumsikan memiliki bobot yang sama karena masing-masing parameter saling berkaitan dan memiliki pengaruh serta nilai penting yang sama.…”

Section: Analisis Dataunclassified

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Analisis Metode Indeks Kepekaan Lingkungan Ekosistem Mangrove Terhadap Tumpahan Minyak Di Pesisir Subang, Jawa Barat

Rikardi

Nurjaya

Damar

2021

J. Ilmu dan Teknologi Kelautan Tropis

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Penelitian ini bertujuan untuk mengembangkan metode indeks kepekaan lingkungan ekosistem mangrove terhadap tumpahan minyak dengan studi kasus di daerah pesisir Subang Jawa Barat. Data yang digunakan adalah data primer (data jenis mangrove, tipe substrat dan data sosial ekonomi) dan data sekunder (karakterisitik pantai dan hidrooseanografi). Data tersebut kemudian digunakan sebagai parameter dalam Indeks Kepekaan Lingkungan (IKL). Indeks kepekaan lingkungan terdiri dari tiga indeks yaitu indeks kerentanan (IK), indeks ekologi (IE), dan indeks sosial ekonomi (IS). Parameter IK terdiri dari kemiringan pantai, rentang pasang surut, tinggi gelombang, tipe substrat dan jarak ekosistem mangrove dari pantai. Parameter IE terdiri dari zonasi mangrove, kepadatan mangrove, keragaman mangrove, keberadaan hewan dilindungi dan status perlindungan ekosistem mangrove. Parameter IS terdiri dari dua kompoen yaitu komponen sosial dan komponen ekonomi dari ekosistem mangrove. Formula IKL yang digunakan adalah IKL = IK(0,3) + IE(0,3) + IS(0,4) dan terbagi kedalam 5 tingkatan kepekaan. Kajian IKL di daerah penelitian menunjukkan sebagian besar daerah memiliki tingkat kepekaan yang “sedang” terhadap tumpahan minyak kecuali Tegal Tike, Anggaranu dan Tanjung yang memiliki tingkat kepekaan “peka”.

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Section: Pengumpulan Dataunclassified

Section: Analisis Dataunclassified

Analisis Metode Indeks Kepekaan Lingkungan Ekosistem Mangrove Terhadap Tumpahan Minyak Di Pesisir Subang, Jawa Barat

Rikardi

Nurjaya

Damar

2021

J. Ilmu dan Teknologi Kelautan Tropis

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“…By classifying shoreline types based on a set of criteria that include their pollution sensitivity, biological productivity, and patterns of human activity, the ESI map offers a detailed analysis of the varying degrees of risk across coastal regions, from the least to the most vulnerable to damage from oil spills. The utilization of the ESI map enables the strategic prioritization of areas that are significantly at risk, thereby enhancing the efficacy of oil spill response initiatives, and has achieved global application [20][21][22]. Integrating the ESI with simulations of oil spill trajectories enhances the understanding of potential impacts on fragile environmental resources and facilitates the precise identification of risk-prone areas.…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment of Oil Spills along the Coastline of Jiaozhou Bay Using GIS Techniques and the MEDSLIK-II Model

Peng,

Wang,

et al. 2024

Water

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With the increasing global reliance on maritime oil transportation, oil spills pose significant environmental hazards to coastal ecosystems. This study presents a comprehensive quantitative framework for assessing oil spill risks along the Jiaozhou Bay coastline in China. The research begins with an analysis of historical spill data to construct representative oil spill simulation scenarios. The advanced MEDSLIK-II oil spill prediction model is then employed to simulate oil spill trajectories under these scenarios, focusing on key parameters such as oil thickness and mass to evaluate the hazard levels associated with each scenario. Subsequently, the Environmental Sensitivity Index (ESI) is utilized to assess the vulnerability of coastal zones, while Geographic Information System (GIS) techniques are employed for a spatial analysis and visualization of the results. The case study, covering a 26.87 km stretch of the Jiaozhou Bay coastline, reveals 10 high-risk zones with a total length of 8561.2 m. These areas are predominantly characterized by saltwater marshes, brackish water marshes, and inundated low-lying areas, with ESI rankings of 9 and 10, accounting for 24% of the 339 analyzed segments. The modeling results indicate that in the simulated scenarios, oil spills originating from the Huangdao Oil Port and Qianwan Port pose the greatest risks, with potential impacts extending up to 12 km and 15 km along the coastline, respectively. The study highlights the importance of considering multiple factors, including oil spill trajectories, coastal geomorphology, and ecological sensitivity, in comprehensive risk assessments. The proposed framework demonstrates potential for adaptation and application to other coastal regions facing similar oil spill risks, contributing to the advancement of coastal management practices worldwide.

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“…A plethora of studies on environmental sensitivity index mapping (mapping of shoreline environments) has been carried out all over the world (Souza-Filho et al, (2004;Oyedepo & Adeofun, 2011;Lawal & Oyegun, 2017;Mamde da Silva et al, 2018;Rustandi et al, 2020). However, scant attention was ab-initio paid to other types of environments (especially terrestrial environments) that might be polluted by oil spill.…”

Section: Introductionmentioning

confidence: 99%

Terrestrial Environmental Sensitivity Index Mapping (TESIM) of the Coastal Areas of the Niger Delta Region of Nigeria

Wekpe

2023

Preprint

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It can be argued that despite years of research, the true impacts of oil spill pollution on the environment and human sources of livelihoods are yet to be completely understood. Tools such as environmental sensitivity index (ESI) mapping can provide useful information that can significantly mitigate or help eliminate the known impacts of crude oil pollution, by proactively identifying environmentally sensitive areas. This study adapted the analytical hierarchy process (AHP) and geographic information systems (GIS) based multiple criteria analysis (MCA) approach in the objective determination of sensitive sections of the NDR coastal areas, by combining several competing and or related evaluation criteria. The AHP was used to determine and assign relative weights to the data layers through a pairwise comparison evaluation matrix of mutually exclusive evaluation criteria using the Delphi technique, while the MCA was used to aggregate the evaluation criteria into a single map. The results of the MCA analysis show that over 57% of the study area is sensitive to oil spill pollution in one form or the other. 68% of the identified sensitive areas are classified as extremely environmentally sensitive with 11,752.14km2, while 7.1% are classified as less sensitive. This relative classification of environmental sensitivity in the study area is termed the Niger Delta Relative Environmental Sensitivity Index (NDRESI). The implication of these results is that more has to be done if the very sensitive environment of the NDR is to be conserved by tougher environmental legislations, environmental monitoring and environmental education.

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Environmental sensitivity index mapping as a prevention strategy against oil spill pollution: A case study on the coastal area of South Sumatera Province in Indonesia

Cited by 9 publications

References 7 publications

Analisis Metode Indeks Kepekaan Lingkungan Ekosistem Mangrove Terhadap Tumpahan Minyak Di Pesisir Subang, Jawa Barat

Analisis Metode Indeks Kepekaan Lingkungan Ekosistem Mangrove Terhadap Tumpahan Minyak Di Pesisir Subang, Jawa Barat

Risk Assessment of Oil Spills along the Coastline of Jiaozhou Bay Using GIS Techniques and the MEDSLIK-II Model

Terrestrial Environmental Sensitivity Index Mapping (TESIM) of the Coastal Areas of the Niger Delta Region of Nigeria

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