Quantifying risk to agriculture from volcanic ashfall: a case study from the Bay of Plenty, New Zealand

Quantitatively assessing long-term volcanic risk can be challenging due to the many variables associated with volcanic hazard and vulnerability. This study presents a structured first-order approach for considering variables in hazard and vulnerability analyses, such as eruption style and cyclic fragility, in order to quantitatively estimate risk. Probabilistic volcanic hazard data derived from advection–diffusion–sedimentation tephra fall model TEPHRA2 and probabilistic volcanic hazard analysis tool BET_VH (Bayesian Event Tree for Volcanic Hazards) are combined with fragility functions and seasonal vulnerability coefficients for agricultural production to calculate volcanic risk indices which represent the likelihood of damage or loss to farm production over a given time frame. The resulting dataset allows for approximations of quantitative risk over a continuous range of ash thickness thresholds, at multiple levels of uncertainty, and in the context of fluctuating hazard and vulnerability environments (e.g., seasonal wind patterns and crop phases). We illustrate this approach through a case study which evaluates the risk of incurring 90% damage to agricultural production at dairy and fruit farms in the Bay of Plenty region of New Zealand (BoP) due to ashfall from a Plinian eruption phase at the large local caldera volcano, the Okataina Volcanic Centre (OVC). Consideration of seasonal wind profiles, seasonal fluctuations in fruit and dairy farm vulnerability, multiple possible OVC eruption styles, different possible OVC vent locations, and a continuous distribution of ash thickness and damage thresholds enables a multi-dimensional analysis that aims to reflect the natural complexity and interdependencies associated with volcanic risk. A risk uncertainty matrix is introduced as a conceptual scheme to help guide evaluation and communication of the results of such quantitative risk analyses by showing how different types of uncertainty can yield “maximum”, “average”, or “minimum” estimates of risk. Results of this case study indicate that BoP fruit farms are at higher risk of experiencing damage and production loss from OVC ashfall than dairy farms, and farms to the east of the OVC are typically at higher risk than farms to the north of the OVC. Forecasts based on the annual maximum estimate of risk for fruit farms show a regional average of 2.3% probability (greater than 1 in 50 likelihood) of experiencing 90% damage from a basaltic or rhyolitic Plinian eruption from anywhere within the OVC over a period of 100 years. Seasonal-level analyses revealed that the risk of experiencing losses due to OVC ashfall at fruit farms is cyclic and fluctuates with time of year and harvest season, with the highest risk experienced during peak harvest season (15 October–14 April) when crop vulnerability is high and westerly winds dominate in the BoP.