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Research papers, The University of Auckland Library

A number of field testing techniques, such as standard penetration test (SPT), cone penetration test (CPT), and Swedish weight sounding (SWS), are popularly used for in-situ characterisation. The screw driving sounding (SDS) method, which has been recently developed in Japan, is an improved version of the SWS technique and measures more parameters, including the required torque, load, speed of penetration and rod friction; these provide more robust way of characterising soil stratigraphy. It is a cost-efficient technique which uses a machine-driven and portable device, making it ideal for testing in small-scale and confined areas. Moreover, with a testing depth of up to 10-15m, it is suitable for liquefaction assessment. Thus, the SDS method has great potential as an in-situ testing method for geotechnical site characterisation, especially for residential house construction. In this paper, the results of SDS tests performed at a variety of sites in New Zealand are presented. The soil database was employed to develop a soil classification chart based on SDS-derived parameters. Moreover, using the data obtained following the 2010-2011 Christchurch Earthquake Se-quence, a methodology was established for liquefaction potential evaluation using SDS data. http://www.isc5.com.au/wp-content/uploads/2016/09/1345-2-ORENSE.pdf

Research papers, Lincoln University

This report reviews the literature on regeneration requirements of main canopy tree species in Westland. Forests managed for production purposes have to be harvested in an ecologically sustainable way; to maintain their natural character, harvesting should facilitate regeneration of target species and ensure that their recruitment is in proportion to the extent of extraction. The reasons for species establishing at any point in time are unclear; however, they are probably related to the availability of suitable microsites for establishment, the size of the canopy openings formed by disturbance, and whether or not seeds are available at or around the time of the disturbance. Age structures from throughout Westland show that extensive, similar-aged, post-earthquake cohorts of trees are a feature of the region. This suggests that infrequent, massive earthquakes are the dominant coarse-scale disturbance agent, triggering episodes of major erosion and sedimentation and leaving a strong imprint in the forest structure. In other forests, flooding and catastrophic windthrow are major forms of disturbance. The findings suggest that, in general, large disturbances are required for conifer regeneration. This has implications for any sustained yield management of these forests if conifers are to remain an important component. Any harvesting should recognise the importance for tree establishment of: forest floor microsites, such as fallen logs and tree tip-up mounds; and the variable way in which canopy gaps are formed. Harvesting should maintain the 'patchy' nature of the natural forest—large patches of dense conifers interspersed with more heterogeneous patches of mixed species.This is a client report commissioned by West Coast Conservancy and funded from the Unprogrammed Science Advice fund.

Research papers, Lincoln University

Artificial Neural Networks (ANN) as a tool offers opportunities for modeling the inherent complexity and uncertainty associated with socio-environmental systems. This study draws on New Zealand ski fields (multiple locations) as socio- environmental systems while considering their perceived resilience to low probability but potential high consequences catastrophic natural events (specifically earthquakes). We gathered data at several ski fields using a mixed methodology including: geomorphic assessment, qualitative interviews, and an adaptation of Ozesmi and Ozesmi’s (2003) multi-step fuzzy cognitive mapping (FCM) approach. The data gathered from FCM are qualitatively condensed, and aggregated to three different participant social groups. The social groups include ski fields users, ski industry workers, and ski field managers. Both quantitative and qualitative indices are used to analyze social cognitive maps to identify critical nodes for ANN simulations. The simulations experiment with auto-associative neural networks for developing adaptive preparation, response and recovery strategies. Moreover, simulations attempt to identify key priorities for preparation, response, and recovery for improving resilience to earthquakes in these complex and dynamic environments. The novel mixed methodology is presented as a means of linking physical and social sciences in high complexity, high uncertainty socio-environmental systems. Simulation results indicate that participants perceived that increases in Social Preparation Action, Social Preparation Resources, Social Response Action and Social Response Resources have a positive benefit in improving the resilience to earthquakes of ski fields’ stakeholders.