We examined the stratigraphy of alluvial fans formed at the steep range front of the Southern Alps at Te Taho, on the north bank of the Whataroa River in central West Coast, South Island, New Zealand. The range front coincides with the Alpine Fault, an Australian-Pacific plate boundary fault, which produces regular earthquakes. Our study of range front fans revealed aggradation at 100- to 300-year intervals. Radiocarbon ages and soil residence times (SRTs) estimated by a quantitative profile development index allowed us to elucidate the characteristics of four episodes of aggradation since 1000 CE. We postulate a repeating mode of fan behaviour (fan response cycle [FRC]) linked to earthquake cycles via earthquake-triggered landslides. FRCs are characterised by short response time (aggradation followed by incision) and a long phase when channels are entrenched and fan surfaces are stable (persistence time). Currently, the Te Taho and Whataroa River fans are in the latter phase. The four episodes of fan building we determined from an OxCal sequence model correlate to Alpine Fault earthquakes (or other subsidiary events) and support prior landscape evolution studies indicating ≥M7.5 earthquakes as the main driver of episodic sedimentation. Our findings are consistent with other historic non-earthquake events on the West Coast but indicate faster responses than other earthquake sites in New Zealand and elsewhere where rainfall and stream gradients (the basis for stream power) are lower. Judging from the thickness of fan deposits and the short response times, we conclude that pastoral farming (current land-use) on the fans and probably across much of the Whataroa River fan would be impossible for several decades after a major earthquake. The sustainability of regional tourism and agriculture is at risk, more so because of the vulnerability of the single through road in the region (State Highway 6).
Geospatial liquefaction models aim to predict liquefaction using data that is free and readily-available. This data includes (i) common ground-motion intensity measures; and (ii) geospatial parameters (e.g., among many, distance to rivers, distance to coast, and Vs30 estimated from topography) which are used to infer characteristics of the subsurface without in-situ testing. Since their recent inception, such models have been used to predict geohazard impacts throughout New Zealand (e.g., in conjunction with regional ground-motion simulations). While past studies have demonstrated that geospatial liquefaction-models show great promise, the resolution and accuracy of the geospatial data underlying these models is notably poor. As an example, mapped rivers and coastlines often plot hundreds of meters from their actual locations. This stems from the fact that geospatial models aim to rapidly predict liquefaction anywhere in the world and thus utilize the lowest common denominator of available geospatial data, even though higher quality data is often available (e.g., in New Zealand). Accordingly, this study investigates whether the performance of geospatial models can be improved using higher-quality input data. This analysis is performed using (i) 15,101 liquefaction case studies compiled from the 2010-2016 Canterbury Earthquakes; and (ii) geospatial data readily available in New Zealand. In particular, we utilize alternative, higher-quality data to estimate: locations of rivers and streams; location of coastline; depth to ground water; Vs30; and PGV. Most notably, a region-specific Vs30 model improves performance (Figs. 3-4), while other data variants generally have little-to-no effect, even when the “standard” and “high-quality” values differ significantly (Fig. 2). This finding is consistent with the greater sensitivity of geospatial models to Vs30, relative to any other input (Fig. 5), and has implications for modeling in locales worldwide where high quality geospatial data is available.
Orientation: Large-scale events such as disasters, wars and pandemics disrupt the economy by diverging resource allocation, which could alter employment growth within the economy during recovery.
Research purpose: The literature on the disaster–economic nexus predominantly considers the aggregate performance of the economy, including the stimulus injection. This research assesses the employment transition following a disaster by removing this stimulus injection and evaluating the economy’s performance during recovery.
Motivation for the study: The underlying economy’s performance without the stimulus’ benefit remains primarily unanswered. A single disaster event is used to assess the employment transition to guide future stimulus response for disasters.
Research approach/design and method: Canterbury, New Zealand, was affected by a series of earthquakes in 2010–2011 and is used as a single case study. Applying the historical construction–economic relationship, a counterfactual level of economic activity is quantified and compared with official results. Using an input–output model to remove the economy-wide impact from the elevated activity reveals the performance of the underlying economy and employment transition during recovery.
Main findings: The results indicate a return to a demand-driven level of building activity 10 years after the disaster. Employment transition is characterised by two distinct periods. The first 5 years are stimulus-driven, while the 5 years that follow are demand-driven from the underlying economy. After the initial period of elevated building activity, construction repositioned to its long-term level near 5% of value add. Practical/managerial implications: The level of building activity could be used to confidently assess the performance of regional economies following a destructive disaster. The study results argue for an incentive to redevelop the affected area as quickly as possible to mitigate the negative effect of the destruction and provide a stimulus for the economy. Contribution/value-add: This study contributes to a growing stream of regional disaster economics research that assesses the economic effect using a single case study.
