A Framework for Assessing Landslide Risk in Hilly Terrains

Landslides have occurred in various places in Indonesia. Likewise with West Java, there were many regions that has experienced repeated landslides. Having many experience of occurrences of landslides, we should have had a good landslide risk reduction program. Indeed, the incidence of landslides depends on many variables. Due to that condition, it may that a region would have different variable with another region. So it is impossible to generalize the implementation of a mitigation technology for all areas prone to landslides. Research of the Cililin's landslide is to anticipate the next disasters that may happen in around the area of 2013 Cililin Landslide. Through observation lithological conditions, water condition, land cover and landscape, as well as consideration of wide dimension of the building footing, the distance of building to the slopes and so forth, it has been determined some efforts of disaster risk reduction in the area around the landslide against the occurrence of potential landslide in the future.Bencana tanah longsor telah terjadi di berbagai tempat di Indonesia. Demikian halnya dengan Jawa Barat, tidak sedikit daerahnya telah berulang kali mengalami longsor. Seharusnya dengan telah banyaknya kejadian longsor, kita mampu mengupayakan program penurunan risiko longsor secara baik. Memang kejadian longsor bergantung pada banyak variabel, dimana dari satu daerah dengan daerah yang lain akan sangat memungkinkan mempunyai variabel yang berbeda, sehingga tidak mungkin kita membuat generalisasi penerapan suatu teknologi mitigasinya untuk semua daerah rawan longsor. Penelitian longsor di Cililin dilakukan untuk mengantisipasi terjadinya bencana di sekitar daerah Longsor Cililin 2013 yang lalu. Melalui pengamatan kondisi litologi, keairan, tutupan lahan dan bentang alam yang ada, serta pertimbangan akan dimensi luas pijakan bangunan, jarak batas bangunan dengan lereng dan lain sebagainya, telah ditentukan beberapa upaya penurunan risiko bencana di daerah sekitar longsor terhadap potensi kejadian longsor dimasa mendatang.Keywords: Landslide, risk reduction, footing of building, Cililin

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ANALISIS KONDISI BAWAH PERMUKAAN DAN RISIKO BENCANA TANAH LONGSOR UNTUK ARAHAN PENATAAN KAWASAN DI DESA TENGKLIK KECAMATAN TAWANGMANGU KABUPATEN KARANGANYAR JAWA TENGAH

Jurnal Sains dan Teknologi Indonesia ◽

10.29122/jsti.v13i2.881 ◽

2013 ◽

Vol 13 (2) ◽

Author(s):

Heru Sri Naryanto

Keyword(s):

Information System ◽

Geographic Information System ◽

Regional Planning ◽

Rainy Season ◽

Great Influence ◽

Landslide Risk ◽

Potential Hazard ◽

Volcanic Deposits ◽

Steep Topography ◽

Steep Slopes

Karanganyar District is a hilly area with steep slopes, rock constituent of young volcanic deposits of Lawu Volcano products, thick soil and relatively high rainfall, so it is potential for large landslides in this region. The landuse in the Karanganyar District including the Tengklik Village is generally dominated by rice fields, seasonal gardens and settlements. Plantation made up in areas with steep topography has great influence on erosion and landslides. Similarly, many settlements are built on a slope so that the area is very vulnerable to the threat of landslides. In the rainy season landslides are common. The potential hazard of landslidesoccurred in 14 sub districts in Karanganyar District. Large landslides have occurred in Karanganyar on December 26, 2007 which claimed the lives of 62 people, with the greatest victims were in the Ledoksari Village, Tawangmangu. The Tengklik Village has already experienced creep type landslides, which have destroyed settlements, roads, seasonalgardens and all existing infrastructure in the area. In order to do the proper handling and anticipation of a catastrophic landslide, a variety of technological applications landslides using geographic information system (GIS) was then carried out, to detect the configuration of 2D geoelectrical subsurface prone areas for landslide risk study and regional planning.

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LANDSLIDE RISK MANAGEMENT IN THE COASTAL ZONE OF THE KUIBYSHEV RESERVOIR DUE THE DESIGN OF HIGH-SPEED LINE "MOSCOW-KAZAN"

Proceedings of International Conference "Managinag risks to coastal regions and communities in a changinag world" (EMECS'11 - SeaCoasts XXVI) ◽

10.31519/conferencearticle_5b1b9403c99983.72529271 ◽

2017 ◽

Author(s):

Nikolai Petrov ◽

Inna Nikonorova ◽

Vladimir Mashin ◽

...

Keyword(s):

High Speed ◽

Computational Models ◽

Stable State ◽

Landslide Risk ◽

Kuibyshev Reservoir ◽

Stepped Surface ◽

The Stability ◽

Landslide Slope ◽

The Village

High-speed railway "Moscow-Kazan" by the draft crosses the Volga (Kuibyshev reservoir) in Chuvashia region 500 m below the village of New Kushnikovo. The crossing plot is a right-bank landslide slope with a stepped surface. Its height is 80 m; the slope steepness -15-16o. The authors should assess the risk of landslides and recommend anti-landslide measures to ensure the safety of the future bridge. For this landslide factors have been analyzed, slope stability assessment has been performed and recommendations have been suggested. The role of the following factors have been analyzed: 1) hydrologic - erosion and abrasion reservoir and runoff role; 2) lithologyc (the presence of Urzhum and Northern Dvina horizons of plastically deformable rocks, displacement areas); 3) hydrogeological (the role of perched, ground and interstratal water); 4) geomorphological (presence of the elemental composition of sliding systems and their structure in the relief); 5) exogeodynamic (cycles and stages of landslide systems development, mechanisms and relationship between landslide tiers of different generations and blocks contained in tiers). As a result 6-7 computational models at each of the three engineering-geological sections were made. The stability was evaluated by the method “of the leaning slope”. It is proved that the slope is in a very stable state and requires the following measures: 1) unloading (truncation) of active heads blocks of landslide tiers) and the edge of the plateau, 2) regulation of the surface and groundwater flow, 3) concrete dam, if necessary.

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LANDSLIDE RISK REDUCTION IN PUERTO RICO: SCIENCE AND RISK COMMUNICATION

10.1130/abs/2019am-340150 ◽

2019 ◽

Author(s):

Lindsay A. Davis ◽

◽

Jonathan W. Godt ◽

Lori A. Peek

Keyword(s):

Puerto Rico ◽

Risk Communication ◽

Risk Reduction ◽

Landslide Risk ◽

Science And Risk ◽

Landslide Risk Reduction

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InSAR Monitoring of Landslide Activity in Dominica

Remote Sensing ◽

10.3390/rs13040815 ◽

2021 ◽

Vol 13 (4) ◽

pp. 815

Author(s):

Mary-Anne Fobert ◽

Vern Singhroy ◽

John G. Spray

Keyword(s):

Risk Mitigation ◽

Disaster Mitigation ◽

Aerial Images ◽

Landslide Inventory ◽

Landslide Risk ◽

Susceptibility Map ◽

Interferometric Synthetic Aperture Radar ◽

Rainfall Events ◽

Susceptibility Maps ◽

Digital Elevation

Dominica is a geologically young, volcanic island in the eastern Caribbean. Due to its rugged terrain, substantial rainfall, and distinct soil characteristics, it is highly vulnerable to landslides. The dominant triggers of these landslides are hurricanes, tropical storms, and heavy prolonged rainfall events. These events frequently lead to loss of life and the need for a growing portion of the island’s annual budget to cover the considerable cost of reconstruction and recovery. For disaster risk mitigation and landslide risk assessment, landslide inventory and susceptibility maps are essential. Landslide inventory maps record existing landslides and include details on their type, location, spatial extent, and time of occurrence. These data are integrated (when possible) with the landslide trigger and pre-failure slope conditions to generate or validate a susceptibility map. The susceptibility map is used to identify the level of potential landslide risk (low, moderate, or high). In Dominica, these maps are produced using optical satellite and aerial images, digital elevation models, and historic landslide inventory data. This study illustrates the benefits of using satellite Interferometric Synthetic Aperture Radar (InSAR) to refine these maps. Our study shows that when using continuous high-resolution InSAR data, active slopes can be identified and monitored. This information can be used to highlight areas most at risk (for use in validating and updating the susceptibility map), and can constrain the time of occurrence of when the landslide was initiated (for use in landslide inventory mapping). Our study shows that InSAR can be used to assist in the investigation of pre-failure slope conditions. For instance, our initial findings suggest there is more land motion prior to failure on clay soils with gentler slopes than on those with steeper slopes. A greater understanding of pre-failure slope conditions will support the generation of a more dependable susceptibility map. Our study also discusses the integration of InSAR deformation-rate maps and time-series analysis with rainfall data in support of the development of rainfall thresholds for different terrains. The information provided by InSAR can enhance inventory and susceptibility mapping, which will better assist with the island’s current disaster mitigation and resiliency efforts.

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Landslide risk management in Hong Kong

Landslides ◽

10.1007/s10346-020-01587-0 ◽

2021 ◽

Author(s):

Raymond W. M. Cheung

Keyword(s):

Risk Management ◽

Hong Kong ◽

Landslide Risk

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The Geo-Social Model: A Transdisciplinary Approach to Flow-Type Landslide Analysis and Prevention

Sustainability ◽

10.3390/su13052501 ◽

2021 ◽

Vol 13 (5) ◽

pp. 2501

Author(s):

Valentina Acuña ◽

Francisca Roldán ◽

Manuel Tironi ◽

Leila Juzam

Keyword(s):

Urban Areas ◽

Risk Perceptions ◽

Risk Prevention ◽

Social Model ◽

Experimental Methodology ◽

Landslide Risk ◽

Sociocultural Environment ◽

Flow Type ◽

Complex Interactions ◽

Municipal Level

Landslide disaster risks increase worldwide, particularly in urban areas. To design and implement more effective and democratic risk reduction programs, calls for transdisciplinary approaches have recently increased. However, little attention has been paid to the actual articulation of transdisciplinary methods and their associated challenges. To fill this gap, we draw on the case of the 1993 Quebrada de Macul disaster, Chile, to propose what we label as the Geo-Social Model. This experimental methodology aims at integrating recursive interactions between geological and social factors configuring landslide for more robust and inclusive analyses and interventions. It builds upon three analytical blocks or site-specific environments in constant co-determination: (1) The geology and geomorphology of the study area; (2) the built environment, encompassing infrastructural, urban, and planning conditions; and (3) the sociocultural environment, which includes community memory, risk perceptions, and territorial organizing. Our results are summarized in a geo-social map that systematizes the complex interactions between the three environments that facilitated the Quebrada de Macul flow-type landslide. While our results are specific to this event, we argue that the Geo-Social Model can be applied to other territories. In our conclusions, we suggest, first, that landslides in urban contexts are often the result of anthropogenic disruptions of natural balances and systems, often related to the lack of place-sensitive urban planning. Second, that transdisciplinary approaches are critical for sustaining robust and politically effective landslide risk prevention plans. Finally, that inter- and trans-disciplinary approaches to landslide risk prevention need to be integrated into municipal-level planning for a better understanding of—and prevention of—socio-natural hazards.

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A hybrid model using data mining and multi-criteria decision-making methods for landslide risk mapping at Golestan Province, Iran

Environmental Earth Sciences ◽

10.1007/s12665-021-09788-z ◽

2021 ◽

Vol 80 (15) ◽

Author(s):

Elham Rafiei Sardooi ◽

Ali Azareh ◽

Tayyebeh Mesbahzadeh ◽

Farshad Soleimani Sardoo ◽

Eric J. R. Parteli ◽

...

Keyword(s):

Data Mining ◽

Decision Making ◽

Hybrid Model ◽

Risk Mapping ◽

Landslide Risk ◽

Multi Criteria Decision Making ◽

Golestan Province ◽

Using Data

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