Abstract Indonesia lied among the three of world major plates so that several districts along the southern coast of Java Island were vulnerabled to the tsunami including Lumajang. South coast of Lumajang had high population density and settlements and high levels of government and economic activity. Therefore, it is necessary to know the level of insecurity and vulnerability to the tsunami in order to be utilized as input of mitigation data for the preparation of regional spatial plans (RTRW) based on tsunami risk level. The objective of this research is to arrange the regional risk map for tsunami in Lumajang Regency using Geographic Information System (GIS) through approach of insecurity and vulnerability analysis of tsunami. The insecurity rate is analyzed based on seismicity map and run-up data of tsunami event in Lumajang District. Vulnerability approach used multicriteria such as land elevation, slope, coastal morphometry, land use, distance from the coast and distance from the river. The methodology that was used included data collections of both primary and secondary data such as satellite imagery of earth map, Lumajang statistical data. Each vulnerability data variable was processed to result a weighting and scores that its become the parameters for making a regional tsunami vulnerability map. The results showed three level of risks in five subdistricts that directly adjacent to the Southern Coast such as Yosowilangun, Kunir, Tempeh, Pasirian, and Tempursari. The high tsunami risk which covered almost along the coast, the ramps morphology, without any protective vegetation and human activities at the site while the medium of tsunami risk which were in areas with elevation more higher than the coastal and the low of tsunami risk had variations of topography, quite far from the coast and less human activities.

Very low-frequency electromagnetic (VLF-EM) method can be used for imaging the subsurface resistivity, where this image can be used directly to determine subsurface condition. VLF-EM data are generally contaminated with unwanted noise which often leads to a mistake in the resistivity imaging result. In this study, noise-assisted multivariate empirical mode decomposition (NA-MEMD) was applied to reject the unwanted noise contained within the VLF-EM data which produced NA-MEMD-filtered VLF-EM data. The resistivity imaging resulted by filtered VLF-EM data has been used for determining the position of underground rivers over the karst area of Gunung Kidul district, Central Java province, Indonesia. The results show that the NA-MEMD-filtered VLF-EM data were more accurate in determining underground river tracks of the Suci cave areas. The overall result was supported by qualitative analyses (Fraser and K–Hjelt filters) of observed VLF-EM data as well as the NA-MEMD-filtered VLF-EM data.

Kabupaten Lumajang merupakan wilayah yang rentan terhadap tsunami karena berbatasan langsung dengan Pantai Selatan yang menjadi pusat gempa bumi serta keadaan pesisir pantai selatan Lumajang yang memiliki tingkat kepadatan penduduk dan pemukiman, aktivitas pemerintahan dan perekonomian yang tinggi. Pemetaan tingkat kerentanan tsunami perlu dilakukan sebagai informasi mitigasi dan rencana tata ruang wilayah. Lokasi penelitian adalah 5 (lima) kecamatan di pesisir Pantai Selatan Lumajang yaitu Yosowilangun, Kunir, Tempeh, Pasirian, dan Tempursari. Tujuan penelitian ini adalah membuat peta kerentanan tsunami Kabupaten Lumajang menggunakan Sistem Informasi Geografis (SIG). Pendekatan variabel kerentanan meliputi elevasi daratan, kemiringan, morfometri pantai, penggunaan lahan, jarak dari pantai dan jarak dari sungai. Metodologi penelitian antara lain pengumpulan data primer dan sekunder, pengolahan data parameter yang mewakili tiap variabel kerentanan serta pemberian bobot dan skor. Hasil kajian ini menghasilkan peta-peta variabel kerentanan wilayah penelitian yang selanjutnya dapat digunakan untuk kebijakan pemerintah daerah dan tindakan mitigasi seperti pemetaan tingkat risiko tsunami.

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Groundwater flow in the limestone areas through gaps, fractures, and dissolving channels whose dimensions and directions are erratic. If the dimensions and direction of the river flow are known, it will be easier to exploit water to meet the needs of the community. The dimensions and direction of the underground river flow can be mapped using the VLF-EM method. VLF-EM measurements were carried out on 18 trajectories spread across two study areas. Each VLF-EM track has a length of 200 meters, taking data at intervals of 2 meters. Processing of VLF-EM data on each path produces a distribution of resistivity values along the measurement path. Resistivity values around Bleri Cave range between 53 Ωm - 685 Ωm, underground river flow is located at a depth of ± 40 meters and the direction of flow is from northeast to southwest. The distribution of underground river flow around the Bleri Cave with resistivity values around the Lowo Cave ranges from 61 Ωm - 550 Ωm, in the area around the Lowo cave there are no underground anomaly caves that are not drained by water. If you want to exploit underground river water it should be done in the area around Bleri Cave.