Radio-Optical Galaxy Shape and Shear Correlations in the COSMOS Field using 3 GHz VLA Observations

We present a weak lensing analysis of the 3 GHz VLA radio survey of the COSMOS field, which we correlate with overlapping HST-ACS optical observations using both intrinsic galaxy shape and cosmic shear correlation statistics. After cross-matching sources between the two catalogues, we measure the correlations of galaxy position angles and find a Pearson correlation coefficient of $0.14 \pm 0.03$. This is a marked improvement from previous studies which found very weak, or non-existent correlations, and gives insight into the emission processes of radio and optical galaxies. We also extract power spectra of averaged galaxy ellipticities (the primary observable for cosmic shear) from the two catalogues, and produce optical-optical, radio-optical and radio-radio spectra. The optical-optical auto-power spectrum was measured to a detection significance of 9.80$\sigma$ and is consistent with previous observations of the same field. For radio spectra (which we do not calibrate, given the unknown nature of their systematics), although we do not detect significant radio-optical (1.50$\sigma$) or radio-radio (1.45$\sigma$) $E$-mode power spectra, we do find the $E$-mode spectra to be more consistent with the shear signal expected from previous studies than with a null signal, and vice versa for $B$-mode and $EB$ cross-correlation spectra. Our results give promise that future radio weak lensing surveys with larger source number densities over larger areas will have the capability to measure significant weak lensing signals.Comment: 19 pages, 17 figures, accepted for publication in MNRA

Extending natural hazard impacts: an assessment of landslide disruptions on a national road transportation network

Disruptions to transportation networks by natural hazard events cause direct losses (e.g. by physical damage) and indirect socio-economic losses via travel delays and decreased transportation efficiency. The severity and spatial distribution of these losses varies according to user travel demands and which links, nodes or infrastructure assets are physically disrupted. Increasing transport network resilience, for example by targeted mitigation strategies, requires the identification of the critical network segments which if disrupted would incur undesirable or unacceptable socio-economic impacts. Here, these impacts are assessed on a national road transportation network by coupling hazard data with a transport network model. This process is illustrated using a case study of landslide hazards on the road network of Scotland. A set of possible landslide-prone road segments is generated using landslide susceptibility data. The results indicate that at least 152 road segments are susceptible to landslides, which could cause indirect economic losses exceeding £35 k for each day of closure. In addition, previous estimates for historic landslide events might be significant underestimates. For example, the estimated losses for the 2007 A83 'Rest and Be Thankful' landslide are £80 k day−1, totalling £1.2 million over a 15 day closure, and are ~60% greater than previous estimates. The spatial distribution of impact to road users is communicated in terms of 'extended hazard impact footprints'. These footprints reveal previously unknown exposed communities and unanticipated spatial patterns of severe disruption. Beyond cost-benefit analyses for landslide mitigation efforts, the approach implemented is applicable to other natural hazards (e.g. flooding), combinations of hazards, or even other network disruption events

Comparing threshold definition techniques for rainfall induced landslides: a national assessment using radar rainfall

Translational landslides and debris flows are often initiated during intense or prolonged rainfall. Empirical thresholds aim to classify the rain conditions that are commonly associated to landslide occurrence and therefore improve understating of these hazards and predictive ability. Objective techniques which are used to determine these thresholds are likely to be affected by the length of the rain record used, yet this is not routinely considered. Moreover, remotely sensed spatially continuous rainfall observations are under-exploited. This study compares and evaluates the effect of rain record length on two objective threshold selection techniques in a national assessment of Scotland using weather radar data. Thresholds selected by ‘Threat Score’ are sensitive to rain record length whereas, in a first application to landslides, ‘Optimal Point’ (OP) thresholds prove relatively consistent. OP thresholds increase landslide detection and may therefore be applicable in early warning systems. Thresholds combining 1 and 12-day antecedence variables best distinguish landslide initiation conditions and indicate that Scottish landslides may be initiated by lower rain accumulation and intensities than previously thought

Quantification of road network vulnerability and traffic impacts to regional landslide hazards [abstract]

Slope instability represents a prevalent hazard to transport networks. In the UK regional road networks are frequently disrupted by multiple slope failures triggered during intense precipitation events; primarily due to a degree of regional homogeneity of slope materials, geomorphology and weather conditions. It is of interest to examine how different locations and combinations of slope failure impact road networks, particularly in the context of projected climate change and a 40% increase in UK road demand by 2040. In this study an extensive number (>50 000) of multiple failure event scenarios are simulated within a dynamic micro simulation to assess traffic impacts during peak flow (7 – 10 AM). Possible failure locations are selected within the county of Gloucestershire (3150 km2) using historic failure sites and British Geological Survey GeoSure data. Initial investigations employ a multiple linear regression analyses to consider the severity of traffic impacts, as measured by time, in respect of spatial and topographical network characteristics including connectivity, density and capacity in proximity to failure sites; the network distance between disruptions in multiple failure scenarios is used to consider the effects of spatial clustering. The UK Department of Transport road travel demand and UKCP09 weather projection data to 2080 provide a suitable basis for traffic simulations and probabilistic slope stability assessments. Future work will thus focus on the development of a catastrophe risk model to simulate traffic impacts under various narratives of future travel demand and slope instability under climatic change. The results of this investigation shall contribute to the understanding of road network vulnerabilities and traffic impacts from climate driven slope hazards

Production and preservation of the smallest drumlins

Few very small drumlins are typically mapped in previously glaciated landscapes, which might be an important signature of subglacial processes or an observational artefact. 143 newly emergent drumlins, recently sculpted by the Mulajokull glacier, have been mapped using high resolution LiDAR and aerial photographs in addition to field surveying. In this paper, these are used as evidence that few small drumlins (e.g. height H ≲ 4 m, width W ≲ 40 m, length L ≲ 100 m) are produced; at least, few survive to pass outside the ice margin in this actively forming drumlin field. Specifically, the lack of a multitude of small features seen in other landforms (e.g. volcanoes) is argued not to be due to i) Digital Elevation Model (DEM) resolution or quality, ii) mapper ability in complex (i.e. anthropogenically cluttered or vegetated) landscapes, or iii) post-glacial degradation at this site. So, whilst detection ability must still be at least acknowledged in drumlin mapping, and ideally corrected for in quantitative analyses, this observation can now be firmly taken as a constraint upon drumlin formation models (i.e. statistical, conceptual, or numerical ice flow). Our preferred explanation for the scarcity of small drumlins, at least at sites similar to Mulajokull (i.e. ice lobes with near-margin drumlin genesis), is that they form stochastically during multiple surge cycles, evolving from wide and gentle pre-existing undulations by increasing rapidly in amplitude before significant streamlining occurs

Characterising regional landslide initiation thresholds in Scotland, UK using NIMROD c-band precipitation radar and the BGS National Landslide Database

Characterising regional landslide initiation thresholds in Scotland, UK using NIMROD c-band precipitation radar and the BGS National Landslide Databas

Indirect economic impact of landslide hazards by disruption to national road transportation networks; Scotland, United Kingdom

Indirect economic impact of landslide hazards by disruption to national road transportation networks; Scotland, United Kingdo

Debris-flow release processes investigated through the analysis of multi-temporal LiDAR datasets in north-western Iceland

Debris flows are fast‐moving gravity flows of poorly sorted rock and soil, mixed and saturated with water. Debris‐flow initiation has been studied using empirical and experimental modelling, but the geomorphic changes, indicative of different triggering processes, are difficult to constrain with field observations only. We identify signatures to distinguish two different debris‐flow release styles by integrating high‐resolution multi‐temporal remote sensing datasets and morphometric analysis. We analyse debris flows sourced above the town of Ísafjörður (Iceland). Two debris‐flow triggering processes were previously hypothesized for this site: (i) slope failure, characterised by landslides evolving into debris flows, and (ii) the fire‐hose effect, in which debris accumulated in pre‐existing, steep‐sided bedrock passages is transported by a surge of water. It is unknown which process dominates and determines the local risk. To investigate this question, we compare airborne LiDAR elevation models and aerial photographs collected in 2007 with similar data from 2013. We find that two new debris‐flow tracks were created by slope failures. These are characterised by steep sliding surfaces and lateral leveed channels. Slope failure also occurred in two large, recently active tracks, creating the preparatory conditions for the fire‐hose effect to mobilise existing debris. These tracks show alternating zones of fill and scour along their length, and debris stored below the source‐area at rest angles >35°. Our approach allows us to identify and quantify the morphological changes produced by slope failure release process, which generated the preparatory conditions for the fire‐hose effect. As debris flows are rarely observed in action and morphological changes induced by them are difficult to detect and monitor, the same approach could be applied to other landscapes to understand debris‐flow initiation in absence of other monitoring information, and can improve the identification of zones at risk in inhabited areas near hillslopes with potential for debris flows

Multi-hazard dependencies can increase or decrease risk

In risk analysis, it is recognized that hazards can often combine to worsen their joint impact, but impact data for a rail network show that hazards can also tend to be mutually exclusive at seasonal timescales. Ignoring this overestimates worst-case risk, so we therefore champion a broader view of risk from compound hazard

Molards as an indicator of permafrost degradation and landslide processes

Molards have been defined in the past as conical mounds of debris that can form part of a landslide's deposits. We present the first conclusive evidence that molards in permafrost terrains are cones of loose debris that result from thawing of frozen blocks of ice-rich sediments mobilised by a landslide, and hence propose a rigorous definition of this landform in permafrost environments. We show that molards can be used as an indicator of permafrost degradation, and that their morphometry and spatial distribution give valuable insights into landslide dynamics in permafrost environments. We demonstrate that molards are readily recognisable not only in the field, but also in remote sensing data; surveys of historic aerial imagery allow the recognition of relict molards, which can be used as an indicator of current and past permafrost conditions. The triggering of landslides as a result of permafrost degradation will arguably occur more often as global atmospheric temperatures increase, so molards should be added to our armoury for tracking climate change, as well as helping us to understand landslide-related hazards. Finally, we have also identified candidate molards on Mars, so molards can inform about landscape evolution on Earth and other planetary bodies