David discusses the latest news in North Canterbury including updates on the earthquake damaged Glen Alton bridge funding, calls for a local driving licence test route in Kaikoura, reactions from local mayors on the government's bid to get young people off a jobseekers benefit, and there have been reports of dog attacks on little penguins along Kaikoura's coastline. David Hill is a Local Democracy Reporter with North Canterbury News, based in Rangiora.
The rapid classification of building damage states or placards after an earthquake is vital for enabling an efficient emergency response and informed decision-making for rehabilitation and recovery purposes. Traditional methods rely heavily on inspector-led on-site surveys, which are often time-consuming, resource-intensive, and susceptible to human error. This study introduces a machine learning-supported surrogate model designed to streamline the assessment of building damage, focusing on the automated assignment of damage placards within the context of New Zealand's post-earthquake evaluation frameworks. The study evaluates two key safety evaluation protocols—Rapid Building Assessment (RBA) and Detailed Damage Evaluation (DDE)—and integrates corresponding databases derived from the 2010–2011 Canterbury Earthquake Sequence (CES) in Christchurch. Six ML classifiers—Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Gradient Boosting Classifier (GBC), and Gradient Bagging (GBag)—were rigorously tested across both databases. The results indicate that the RF-based surrogate model outperforms the other classifiers across both RBA and DDE protocols. Two distinct sets of critical predictors have been further identified for each protocol, allowing for the rapid retrieval of essential data for future on-site surveys, while retaining the RF model's predictive accuracy. The developed surrogate model provides a pragmatic tool for practising engineers to rapidly assign placards to damaged structures and for policymakers and building owners to make informed recovery decisions for earthquake-affected buildings
The North Canterbury and Marlborough regions of Aotearoa | New Zealand were severely impacted by almost 30,000 landslides triggered during the 2016 Kaikōura Earthquake. Of these landslides approximately 200 dammed rivers. In the study area near Waiau, rupture of The Humps and Leader faults (and associated ground motions) initiated at least 42 co-seismic landslides. The Leader Landslide is the largest of these landslides, with an area of approximately 600,000 m2 and a volume of 6-8 million m3. The landslide buried approximately 980 m of active Leader River bed length and dammed the river. The dam produced four lakes, with two remaining today and two having been breached by partial landslide collapse and knickpoint migration in the year following the earthquake. As of 2025, the landslide dam has not been completely breached and Lake Rebekah remains. The Leader Landslide dam presents a unique opportunity to chart the evolution of the active riverbed pre- and post-earthquake, for up to 2 km downstream of Lake Rebekah. The river’s evolutionary timeline was observed using LiDAR, satellite aerial imagery, and drone surveys from 2001 to 2024 to develop maps and topographic difference models. Key timeframes for riverbed change events were also constrained with information and dated photography gathered from previous communications with the landowners at Woodchester Station, where the landslide is located. Finally, Schmidt Hammer testing of the Pliocene-Miocene Greta Siltstone Formation was conducted to investigate the role of bedrock strength on the rate of riverbed erosion. I present the history of evolution of the Leader River, pre- and post-earthquake, and consider factors impacting riverbed morphology changes. Despite the stability of Lake Rebekah, these data show that the position and morphology of the Leader River has changed significantly in response to the landslide, with the formation of two knickpoint waterfalls up to 14 m-high, four waterbodies, and diversion of the river around the landslide toe. Evolution of the river is characterised by longer periods of stasis (e.g., months to years) punctuated by rapid changes in riverbed morphology (e.g., hours to weeks) associated with incision and aggradation. In particular, the knickpoints migrated upstream at variable spatial and temporal rates. Factors controlling the rates of processes include; rain-storm events, partial lake outburst flooding, spatial changes in Pliocene-Miocene siltstone bed induration and landowner intervention to stabilise the landslide dam. An overarching conclusion of this thesis is that landforms can develop rapidly (i.e., hours to weeks) and in the absence of historical accounts, could be interpreted to have formed over hundreds to thousands of years.
