The Auckland Volcanic Field (AVF) is a young basaltic field that lies beneath the urban area of Auckland, New Zealand’s largest city. Over the past 250,000 years the AVF has produced at least 49 basaltic centers; the last eruption was only 600 years ago. In recognition of the high risk associated with a possible future eruption in Auckland, the New Zealand government ran Exercise Ruaumoko in March 2008, a test of New Zealand’s nation-wide preparedness for responding to a major disaster resulting from a volcanic eruption in Auckland City. The exercise scenario was developed in secret, and covered the period of precursory activity up until the eruption. During Exercise Ruaumoko we adapted a recently developed statistical code for eruption forecasting, namely BET_EF (Bayesian Event Tree for Eruption Forecasting), to independently track the unrest evolution and to forecast the most likely onset time, location and style of the initial phase of the simulated eruption. The code was set up before the start of the exercise by entering reliable information on the past history of the AVF as well as the monitoring signals expected in the event of magmatic unrest and an impending eruption. The average probabilities calculated by BET_EF during Exercise Ruaumoko corresponded well to the probabilities subjectively (and independently) estimated by the advising scientists (differences of few percentage units), and provided a sound forecast of the timing (before the event, the eruption probability reached 90%) and location of the eruption. This application of BET_EF to a volcanic field that has experienced no historical activity and for which otherwise limited prior information is available shows its versatility and potential usefulness as a tool to aid decision-making for a wide range of volcano types. Our near real-time application of BET_EF during Exercise Ruaumoko highlighted its potential to clarify and possibly optimize decision-making procedures in a future AVF eruption crisis, and as a rational starting point for discussions in a scientific advisory group. It also stimulated valuable scientific discussion around how a future AVF eruption might progress, and highlighted areas of future volcanological research that would reduce epistemic uncertainties through the development of better input models.

Eruption forecasting in the Auckland Volcanic Field: application of BET_EF during the New Zealand National Disaster Exercise "Ruaumoko"

Method selection in short-term eruption forecasting

Shrimp farming with a non-partial harvest system is a cultivation concept to obtain optimal production harvest. The purpose of this study was to determine the business feasibility status of vaname shrimp ( L. vannamei ) cultivation with a non-partial harvesting system in terms of the ecological and financial aspects from aquaculture. The research method used in this study is a survey research method with data collection techniques based on purposive sampling . The results showed, this non-partial system is ecologically very feasible, because the conditions of the average daily water quality parameter values (DO, pH, temperature, salinity) during the aquaculture period are still above the water quality standard threshold for intensive aquaculture. The business financial feasibility analysis resulted in a profit of IDR 441,307,102,-, BEP Unit 2,062 Kg, BEP Sales IDR 119,995,253,-, R/C of 1.71, Return on Investment of 47.69%, and Payback Period of 2.7 years. Meanwhile based on investment analysis, the Net Present Value of IDR 34,136,139,245,-, Net B/C 11.61, and Internal Rate of Return 37.23%. So, it can be denied, that based on ecological aspects and economic multiplication of aquaculture systems like this can be categorized as very feasible and profitable to be globally developed.

https://ecsofim.ub.ac.id/index.php/ecsofim/article/download/249/pdf

Business Feasibility of Intensive Vaname Shrimp (Litopenaeus vannamei) with Non-Partial System

Modelling spatial population exposure and evacuation clearance time for the Auckland Volcanic Field, New Zealand

Fault-Tree Compiler (FTC) program, is software tool used to calculate probability of top event in fault tree. Gates of five different types allowed in fault tree: AND, OR, EXCLUSIVE OR, INVERT, and M OF N. High-level input language easy to understand and use. In addition, program supports hierarchical fault-tree definition feature, which simplifies tree-description process and reduces execution time. Set of programs created forming basis for reliability-analysis workstation: SURE, ASSIST, PAWS/STEM, and FTC fault-tree tool (LAR-14586). Written in PASCAL, ANSI-compliant C language, and FORTRAN 77. Other versions available upon request.

Fault-Tree Compiler

Probabilistic volcanic impact assessment and cost-benefit analysis on network infrastructure for secondary evacuation of farm livestock: A case study from the dairy industry, Taranaki, New Zealand


 This paper presents the architecture and features of RiskScape software. RiskScape is an open-source software with a flexible modelling engine for multi-hazard risk analysis. The RiskScape engine implements modeller-defined risk quantification workflows as ‘model pipelines’. Model pipeline steps and functions analyse hazard, exposure, and vulnerability data across different spatio-temporal domains using geoprocessing and spatial sampling operations. The RiskScape engine supports deterministic and probabilistic risk quantification, with several probabilistic-based modes described in this paper. RiskScape advances modelling software for multi-hazard risk analysis through several implementation features. The RiskScape engine operates model pipelines independent of system prescribed model input data classifications or standards. Multiple hazard types, metric intensities, and temporal occurrence information is geometry processed and sampled to create coverage data of simultaneous or sequenced multi-hazard events at object-exposure locations. Escalating multi-hazard event impacts are then determined for object-exposures using scripted conditional or nested statements that apply vulnerability functions in a logical sequence of temporal hazard and impact occurrence. These model features, supported by open geospatial consortium standard geospatial data files and operations, expedite RiskScape for modelling multi-hazard risk at any geographical location or scale.

RiskScape: A flexible multi-hazard risk modelling engine

Flood damage assessments provide critical insights on processes controlling building damage and loss. Here, we present a novel damage assessment approach to develop an empirical residential building damage database from five flood events in New Zealand. Object‐level damage data was collected for flood hazard and building characteristics, along with relative building component and sub‐components damage ratios. A Random Forest Model and Spearman's Rank correlation test were applied to analyse damage data variable importance and monotonic relationships. Model and test results reveal flood inundation depth above first finished floor level is highly important and strongly correlated with total building damage ratios while flow velocity is important for structure component damage. Internal finishes components contribute highly to total building damage ratios as higher value sub‐component materials are susceptible to direct damage from water contact and indirect damage during repair. The empirical damage data has several implications for damage model development due to the limited heterogeneity of flood hazard intensities and building attributes observed. Extending empirical damage data with synthetic damage data in future would support development of more representative object‐specific damage models to evaluate direct tangible damages for local contexts.

Residential building flood damage: Insights on processes and implications for risk assessments

/pdf/auckland-volcanic-field-eruption-crisis-management-decision-53jvdjibb4.pdf

Alec Wild

Papers

Probabilistic volcanic impact assessment and cost-benefit analysis on network infrastructure for secondary evacuation of farm livestock: A case study from the dairy industry, Taranaki, New Zealand

Modelling spatial population exposure and evacuation clearance time for the Auckland Volcanic Field, New Zealand

RiskScape: A flexible multi-hazard risk modelling engine

Residential building flood damage: Insights on processes and implications for risk assessments

Auckland Volcanic Field eruption crisis management decision-making pilot workshop