TR Robinson; NJ Rosser – Dept Geography, Durham University

TR Robinson; NJ Rosser – Dept Geography, Durham University
Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Kate Pedley NZ Defence Force @MarlEmergency Key Messages Modelling landslide hazard post-earthquake can be rapid (hours) and is quicker than manual mapping Allows rapid identification of locations where landslides cause losses to transport infrastructure Critical to informing emergency response activities in terms of gaining access and evacuation needs

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Kate Pedley NZ Defence Force Method @MarlEmergency Results Key Messages Modelling landslide hazard post-earthquake can be rapid (hours) and is quicker than manual mapping Allows rapid identification of locations where landslides cause losses to transport infrastructure Critical to informing emergency response activities in terms of gaining access and evacuation needs Method Results Method Results

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Pacific Plate Australian 37 mm/a 34 mm/a North Island South Wellington Auckland Christchurch Kaikoura Dunedin Seaward Kaikoura Ranges 42 mm/a State Highway 1

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Pacific Plate Australian 37 mm/a 34 mm/a North Island South Wellington Auckland Christchurch Kaikoura Dunedin Seaward Kaikoura Ranges 42 mm/a State Highway 1 Method Results Method Results Method Results

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu 00:02am NZST 14 Nov 2016 Mw 7.8 earthquake in North Canterbury-Marlborough Largest earthquake in a decade Ruptured 21 individual fault segments, jumping fault gaps >10km – ‘most complex ever’ Shaking predominantly affected rural areas resulting in 2 fatalities Kaikoura and Marlborough are popular tourist destinations with several 1000 visiting each day in summer Seabed uplifted several metres and tsunami recorded throughout central NZ

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu 00:02am NZST 14 Nov 2016 Mw 7.8 earthquake in North Canterbury-Marlborough Largest earthquake in a decade Ruptured 21 individual fault segments, jumping fault gaps >10km – ‘most complex ever’ Shaking predominantly affected rural areas resulting in 2 fatalities Kaikoura and Marlborough are popular tourist destinations with several 1000 visiting each day in summer Seabed uplifted several metres and tsunami recorded throughout central NZ Method Results Method Results Method Results

Training Environments
Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Kritikos et al 2015 – JGR-ES DEM Earthquake characteristics Active faults map Multiple Inventories Model derives factors influencing landsliding from multiple past events Assumes relationships are ‘global’ Allows rapid application post earthquake Trained on Northridge & Wenchuan & tested in Chi- Chi Training Environments Test Environment Isoseismals Slope Fuzzy maps Hazard Map Fault proximity Stream proximity Slope position Model showed MMI, Slope Angle, Proximity to Faults & Streams, & Slope Position all strongly correlated in Northridge & Wenchuan Applied to Chi-Chi, model predicts ~90% of landslide from 1% area Same memberships applied to Kaikoura event immediately post-EQ

Training Environments
Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Kritikos et al 2015 – JGR-ES DEM Earthquake characteristics Active faults map Multiple Inventories Model derives factors influencing landsliding from multiple past events Assumes relationships are ‘global’ Allows rapid application post earthquake Trained on Northridge & Wenchuan & tested in Chi- Chi Training Environments Test Environment Isoseismals Slope Fuzzy maps Hazard Map Method Fault proximity Stream proximity Results Method Results Slope position Model showed MMI, Slope Angle, Proximity to Faults & Streams, & Slope Position all strongly correlated in Northridge & Wenchuan Applied to Chi-Chi, model predicts ~90% of landslide from 1% area Same memberships applied to Kaikoura event immediately post-EQ Method Results

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Model  12:30 16 Nov (60.5 hrs) Mapping  21:30 18 Nov (129.5 hrs) UTexas & Earthquake Geology in Greece

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Model  12:30 16 Nov (60.5 hrs) Mapping  21:30 18 Nov (129.5 hrs) Method Results Method Results Method Results UTexas & Earthquake Geology in Greece

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Most dry landslides have almost constant reach angles of ~30° Reach angle to road can be calculated for all cells in study area rapidly: tanθ = H / L Only slopes with θ >30° pose a risk to roads – Danger Cells Risk summarised as ≈ average hazard in cells θ > 30° Identifies locations where landslides could potentially reach the road 30° Danger Cells (red) identified for sample road network

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Most dry landslides have almost constant reach angles of ~30° Reach angle to road can be calculated for all cells in study area rapidly: tanθ = H / L Only slopes with θ >30° pose a risk to roads – Danger Cells Risk summarised as ≈ average hazard in cells θ > 30° Identifies locations where landslides could potentially reach the road Method Results 30° Method Results Danger Cells (red) identified for sample road network Method Results

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Only 2 roads connect Kaikoura to rest of South Island – SH1 (see Location) and Inland Road Both pass through steep landslide prone terrain (see Location) Modelling completed within 36 hours of the earthquake Results suggested that multiple blockages were expected N & S of Kaikoura – no ground access possible Reconnaissance confirmed >30 landslides blocking roads around Kaikoura  cut-off Model identified >80% of blockages Some over-prediction – particularly in the far-field

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Only 2 roads connect Kaikoura to rest of South Island – SH1 (see Location) and Inland Road Both pass through steep landslide prone terrain (see Location) Modelling completed within 36 hours of the earthquake Results suggested that multiple blockages were expected N & S of Kaikoura – no ground access possible Reconnaissance confirmed >30 landslides blocking roads around Kaikoura  cut-off Model identified >80% of blockages Some over-prediction – particularly in the far-field Method Results Method Results Method Results

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Most dry landslides have almost constant reach angles of ~30° Reach angle to river can be calculated for all cells in study area rapidly: tanθ = H / L Only slopes with θ >30° pose a risk to rivers – Danger Cells Risk summarised as ≈ average hazard in cells θ > 30° Identifies locations where landslides could potentially reach the river Sixth Slide 30° Danger Cells (red) identified for sample road network

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu Most dry landslides have almost constant reach angles of ~30° Reach angle to river can be calculated for all cells in study area rapidly: tanθ = H / L Only slopes with θ >30° pose a risk to rivers – Danger Cells Risk summarised as ≈ average hazard in cells θ > 30° Identifies locations where landslides could potentially reach the river Method Results 30° Method Results Danger Cells (red) identified for sample road network Method Results

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu 150 landslide dams identified (from Environment Canterbury)

Rapid landslide risk assessment of transport infrastructure following the 13 November 2016 Kaikoura earthquake TR Robinson; NJ Rosser – Dept Geography, Durham University Navigation Menu 150 landslide dams identified (from Environment Canterbury) Method Results Method Results Method Results

TR Robinson; NJ Rosser – Dept Geography, Durham University

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TR Robinson; NJ Rosser – Dept Geography, Durham University

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