Natural hazards in Nordic Countries

Nadim, Farrokh; Pedersen, Stig Asbjorn Schack; Schmidt-Thomé, Philipp; Sigmundsson, Freysteinn; Engdahl, Mats

doi:10.18814/epiiugs/2008/v31i1/024

Cited by 37 publications

(16 citation statements)

References 19 publications

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“…S‐wave seismic data are generally acquired for two purposes: obtaining higher‐resolution images than P‐waves and to provide information about the S‐wave velocity (or shear‐modulus) of the normally consolidated sediments (Inazaki ; Polom et al ; Pugin et al ; Martinez et al ; Vangkilde‐Pedersen et al ). However, the success of S‐wave studies is restricted to hard surfaces (e.g., paved or asphalted roads), with little success over soft sediments.…”

Section: Geophysical Surveysmentioning

confidence: 99%

“…Examples of quick‐clay landslides in Nordic countries include (according to the regional name and year of occurrence): Trögstad 1967 (1 million‐m 3 , 4 casualties), Rissa 1978 (33 hectares, 1 casualty) and Verdal 1893 (55 million‐m 3 , 116 casualties) in Norway and Surte 1950 (22 hectares, 1 casualty), Göta 1957 (15 hectares, 3 casualties), Tuve 1977 (27 hectares, 9 casualties) and Småröd 2006 (10 hectares, no casualties; Fig. ) in Sweden (Solberg ; Nadim et al ; Lundström et al ). It is, therefore, important to detect the presence of quick‐clays and the risk of failure; geophysical methods may have the potential to do this but few studies have been carried out.…”

Section: Introductionmentioning

confidence: 99%

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Geophysical assessment and geotechnical investigation of quick‐clay landslides – a Swedish case study

Malehmir

Bastani

Krawczyk

et al. 2013

Near Surface Geophysics

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We present a preliminary assessment of the potential utility of various geophysical measurements carried out over a quick-clay landslide site in south-west Sweden. The multidisciplinary approach includes active P-and S-wave seismic investigations, including 2D and 3D reflection and refraction surveys, passive single and 3C seismic surveys, electrical resistivity tomography and electromagnetic surveys including controlled-source and radio-magnetotellurics, ground-penetrating radar and potential field studies. The P-wave and particularly S-wave reflection seismic data show a highresolution image of bedrock topography and the stratigraphy of a 100 m thick sequence of sediments that lies on top, which include lightly consolidated quick-clays. Of particular interest is the identification of a layer of relatively coarse-grained material between 10-20 m below the ground surface. Geotechnical investigations indicate that most but not all quick-clays at the site are located above this layer. Further studies are required to determine the importance of their relationship and whether the coarse-grained layer may have had a role in triggering quick-clay landslides in the region. Geoelectrical and electromagnetic methods provide high-resolution images of the unconsolidated subsurface and particularly the normal and leached clays. Radio-magnetotelluric methods proved valuable near the river where traditional geoelectrical methods failed to provide sufficient depth coverage. The study shows that geophysical data are able to image major subsurface structures associated with quick-clay landslides.

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Section: Geophysical Surveysmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Geophysical assessment and geotechnical investigation of quick‐clay landslides – a Swedish case study

Malehmir

Bastani

Krawczyk

et al. 2013

Near Surface Geophysics

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“…Rockslides, landslides, and avalanche are the natural hazards that cause the most deaths, and they represent major threats to transportation infrastructure. During a period of 150 years, more than 2,000 persons died in such events (Nadim et al 2008) and roads have been impacted 1,500-2,000 times per year (Jaedicke et al 2009). Large-scale storm and flooding occur less often, but the impacts on lifeline infrastructure may be severe.…”

Section: Norwegian Contextmentioning

confidence: 99%

“…The area is subject to many types of rapid mass movement, especially in the rugged southwest. Rock slides are the most severe natural hazards because of their tsunamigenic potential (Nadim et al 2008). Table 3.…”

Section: Norwegian Contextmentioning

confidence: 99%

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Lifeline Issue in Social Vulnerability Indexing: A Review of Indicators and Discussion of Indicator Application

Holand

2015

Nat. Hazards Rev.

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The article reviews ways to improve measurements of lifeline vulnerability, defining lifeline vulnerability as aspects of social vulnerability to natural hazards influenced by lifeline failure. First, a literature review of indicators commonly used to address lifeline vulnerability within social vulnerability indexing is presented, in order to provide a theoretical basis for the study. Then, nine lifeline vulnerability indicators for central Norway are mapped to provide a practical basis. Thereafter, the author uses the theoretical and practical basis to discuss some problematic issues with respect to indicator selection. The review shows that to date assessments have addressed narrow segments of the broad range of factors influencing lifeline vulnerability. The map examples underscore that an indicator must be validated for each context, and that minor variations on the definition of a lifeline indicator is a critical process. Lifeline indicators represent life situations that conceptually stand apart from indicators representing social categories or exposure. Due to interdependencies among lifeline systems and because of the spatial irregularity of people's dependence on lifelines, it is difficult to determine both the spatial extent of outage and the social consequences. Further, because of lifeline vulnerability's distinct conceptual and spatial characteristics, the author suggests that it should be indexed separately from social factors, exposure, and risk.

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A machine learning–based approach to regional‐scale mapping of sensitive glaciomarine clay combining airborne electromagnetics and geotechnical data

Christensen¹,

Harrison²,

Pfaffhuber³

et al. 2021

Near Surface Geophysics

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Sensitive glaciomarine clays, often referred to as ‘quick clay’, commonly occur in many countries at high, northerly latitudes, causing frequent and occasionally devastating landslides. The salt content of quick clay is strongly correlated to both its shear strength and electrical resistivity. Hence, it can be mapped using electromagnetic methods more efficiently than traditional intrusive methods, the latter of which can often be slow and costly. However, the resistivity signature of quick clay is non‐unique, leading to ambiguous, imprecise interpretations of geophysical models. In this study, we present an improved method for predicting the probability of quick clay using airborne electromagnetics. Using machine learning algorithms, we combine geophysical models with geotechnical data to address the issue of their non‐unique resistivity signature. Beyond resistivity values, the machine learning algorithms use spatial derivatives of resistivity and spatial attributes. We evaluate the performance of this method using data collected from a road construction project in central Norway. Results show that this method is able to make plausible and accurate predictions of quick clay occurrence using as few as 10 boreholes across an area of 14.8 km2, and that it outperforms a simple interpretation based on resistivity intervals alone. In addition to a ‘best guess’ categorical classification, these algorithms output probability estimates, and we demonstrate that they are a reliable indication of uncertainty. The accuracy of these predictions also tends to increase as more geotechnical data are included as training data, helping compensate for the limited resolution of the airborne electromagnetics data. Given that the petrophysics of the clays at this test site are consistent with observations in other regions, we expect this method has the potential to make quick clay hazard mapping more efficient by offering valuable early‐phase insights, leading to large time and cost savings for both infrastructure planning and regional hazard mapping.

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Natural hazards in Nordic Countries

Cited by 37 publications

References 19 publications

Geophysical assessment and geotechnical investigation of quick‐clay landslides – a Swedish case study

Geophysical assessment and geotechnical investigation of quick‐clay landslides – a Swedish case study

Lifeline Issue in Social Vulnerability Indexing: A Review of Indicators and Discussion of Indicator Application

A machine learning–based approach to regional‐scale mapping of sensitive glaciomarine clay combining airborne electromagnetics and geotechnical data

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