Personal profile

Biography

I want to know how the Earth works…


I am Mark Naylor, a Reader in Computational Geoscience and Hazard Research at the School of GeoSciences at the University of Edinburgh.

Having graduated with a Master's in Physics from the University of Oxford in 2000, I have worked in Earth sciences for 20 years.

I am currently a Senior Member of the NERC Constructing a Digital Environment Expert Network. I am also the Academic Lead for IT within the School of GeoSciences.

Websites

Research Interests

Inspired by my time in the outdoors, I really want to know about how the Earth works. In my research, I have studied how mountains grow, landscapes evolve and the natural hazards that emerge in these dynamic systems. I particularly like to find new ways of understanding the natural world using computational, statistical and mathematical methods.

The Edinburgh-Seismicity-Hub GitHub repos hosts various seismicity analyses from my group ranging from exploratory data analyses to earthquake forecasts generated using inlabru.

  • Exploratory Seismic Analysis using R Markdown
  • ETAS.inlabru is the public release of our R based package for generating synthetic catalogues and fitting the temporal ETAS model. For technical details see:
    • Serafini, Lindgren and Naylor, (Submitted) Approximation of Bayesian Hawkes processe models with Inlabru, Submitted to Environmetrics (Preprint)
    • Naylor, Serafini, Lindgren, and Main, (Submitted) Bayesian modelling the temporal evolution of seismicity using the ETAS.inlabru package, Submitted to Frontiers in Applied Mathematics and Statistics (Preprint)

Current Research Interests

  • Seismic Monitoring of Bedload Transport in Mountain Rivers
  • Statistical Forecasting of Earthquakes and other Hazards
  • Earthquake Hazard and Statistical Seismology
  • Mountain Belt Growth, Erosion and Foreland Basin Evolution

 

Research students

Current Students

2023-               Eliana Toro-Paz (NERC E4 DTP): Sediment mobility in Himalayan rivers recorded by seismic monitoring with implications for flood risk under a changing climate (2nd Supervisor)

2022-                Wenjin Lu (Co-supervisor with Ian Main as lead)

2021-                Man Ho Suen (2nd Supervisor, Lindgren lead supervisor) Modelling landslides with inlabru

2020-submitted               Bronwyn Matthews (EPSRC): Sounding out the river – Monitoring bedload mobilisation and transport on the River Feshie

  • Matthews, B., Naylor, M., Sinclair, H., Dietze, M., Williams, R., and Cuthill, C.: Isolating bed load transport from river induced seismic signals, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7633, https://doi.org/10.5194/egusphere-egu22-7633, 2022

2020-                Himanshu Agrawal (GCRF Tomorrows City Hub, Edinburgh/UCL): Physics-based ground-motion simulations for seismic risk assessment in rapidly urbanising environments

 

Completed Students

2020-2024                Farnaz Kamranzad (GCRF Tomorrows City Hub): 

  • Kamranzad, Naylor, Lindgren, Bayliss and Main Enhancing the ETAS model: incorporating rate-dependent incompleteness, constructing a representative dataset, and reducing bias in inversions [preprint]
  • Bayliss, Naylor, Kamranzad, and Main, Pseudo-prospective testing of 5-year earthquake forecasts forCalifornia using inlabru, Natural Hazards and Earth System Sciences [EGU]

2019-2023                Francesco Serafini (H2020, RISE): Modelling seismicity as a spatio-temporal point process using inlabru

  • Cecilia I. Nievasa, Helen Crowley, Yves Reulanda, Graeme Weatherill, Georgios Baltzopoulosa, Kirsty Bayliss, Eleni Chatzi, Eugenio Chioccarelli, Philippe Guéguen, Iunio Iervolino, Mark Naylor, Mabel Orlacchio, Jelena Pejovica, Francesco Serafini & Nina Serdar (2024) EXPLORATION OF STATE-DEPENDENT RAPID LOSS ASSESSMENT AND EVENT-BASED OPERATIONAL EARTHQUAKE LOSS FORECASTING INCORPORATING STRUCTURAL HEALTH MONITORING: AN OPEN-SOURCE TOOL, Earthquake Engineering and Dynamics for a Sustainable Future, CECED 2023.
  • Serafini, F., Lindgren, F., & Naylor, M. (2023). Approximation of Bayesian Hawkes process with inlabru. Environmetrics, e2798. https://doi.org/10.1002/env.2798 (Journal Paper, Preprint)
  • Naylor, Serafini, Lindgren, and Main, (In Press, 2023) Bayesian modelling the temporal evolution of seismicity using the ETAS.inlabru package, Frontiers in Applied Mathematics and Statistics, doi: 10.3389/fams.2023.1126759 (Journal Link, arvix Preprint)
  • Serafini, Naylor, Lindgren, Werner, and Main, (2022) Ranking earthquake forecasts using proper scoring rules: Binary events in a low probability environment, Geophysical Journal International, ggac124https://doi.org/10.1093/gji/ggac124 [Journal link ; PrePrint Server]
  • Serafini, F., Naylor, M., Lindgren, F., and Werner, M.: Ranking earthquake forecasts: On the use of proper scoring rules to discriminate forecasts, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7418, https://doi.org/10.5194/egusphere-egu21-7418, 2021
  •  

2016-2022       Dr Gina Geffers (NERC E3, 2nd supervisor): Model selection in earthquake recurrence relationships: b-value bias in tectonic, volcanic and induced seismological settings

2015-2020      Dr Thomas Bernard (2nd supervisor): The evolution and geomorphology of mountain landscape

  • T Bernard, H.D. Sinclair, M. Naylor, F. Christophoul, M. Ford (2020) Post‐orogenic sediment drape in the Northern Pyrenees explained using a box model, Basin Research, https://doi.org/10.1111/bre.12457

2014-2019      Dr Kirsty Bayliss (EPSRC): Seismic source zonation using modern statistical methods [currently doing a postdoc on the RISE H2020 project]

  • Bayliss, Naylor, Illian, Main (In Press) Data-driven optimisation of seismicity in models using diverse datasets: generation, evaluation and ranking using inlabru, JGR: Solid Earth
  • K Bayliss, M Naylor, IG Main (2019) Probabilistic identification of earthquake clusters using rescaled nearest neighbour distance networks, Geophysical Journal International 217 (1), 487-503

2012-2016      Dr Rami Eid (EoN, 2nd supervisor): Testing of geophysical monitoring techniques using numerical leakage situations[after a postdoc, went on to work for the Geological Survey of Victoria, Australia]

  • Eid, R., Ziolkowski, A., Naylor, M., Pickup, G. (2015) Seismic monitoring of CO2 plume growth, evolution and migration in a heterogeneous reservoir: Role, impact and importance of patchy saturationInternational Journal of Greenhouse Gas Control, 43, pp. 70-81.
  • Eid, R., Ziolkowski, A., Naylor, M., Pickup, G. (2014) The detectability of free-phase migrating CO2: A rock physics and seismic modelling feasibility study, Energy Procedia, 63, pp. 4449-4458.

2009-2011      Dr Sarah Touati (EPSRC): Complexity, aftershock sequences, and uncertainty in earthquake statistics [after a postdoc, left academia to work in health statistics at the Scottish Government]

  • Touati, S., Naylor, M., Main, I.G. (2014) Statistical modeling of the 1997-1998 Colfiorito earthquake Sequence: Locating a stationary solution within parameter uncertainty, Bulletin of the Seismological Society of America, 104 (2), pp. 885-897.
  • Touati, S., Naylor, M., Main, I.G., Christie, M. (2011) Masking of earthquake triggering behavior by a high background rate and implications for epidemic-type aftershock sequence inversions, Journal of Geophysical Research: Solid Earth, 116 (3), art. no. B03304
  • Touati, S., Naylor, M., Main, I.G. (2009) Origin and nonuniversality of the earthquake interevent time distribution, Physical Review Letters, 102 (16), art. no. 168501

Collaborative Activity

Postdoc Research Associates

2020-21           Calum Cuthill: Sounding out the river – Low cost seismic sensor development

2019-21           Dr Kirsty Bayliss: (i) RISE, (ii) NERC-NSF

2017-19           Dr Zhang: PUREC

2017                  Dr Cartwright-Taylor: REAR

2015 – 2017   Dr Emily Kawabata: (i) RACER, (ii) PUREC

2012 – 2015   Dr Sarah Touati: PURE

2013                 Dr Jen Roberts: QUIC2 Scoping

2010 – 2013   Dr Neil Burnside: (i) QICS, (ii) QICS2 Scoping, (iii) ScotPower Actuarial Risk

Teaching

I teach on a broad range of courses and try to build innovative teaching in throughout. I teach coding, traditional geophysics, have created our professional placement scheme for geophysics, manage student projects on the GeoScience outreach course and teach basic field skills on our earth science degree programs.

Teaching of coding

I have specific expertise and experience in the use of Jupyter notebooks and nbgrader for teaching and assessment of Python coding. This includes its use for group projects and automated assessment and grading. The system has several advantages for online and in class learning including the ease for releasing assignments to a class because of its integration with learn, having a single notebook which includes the solutions that are removed automatically when the student version is compiled, the ability to auto and manually grade assignments, and a toolkit for providing and distributing feedback on submissions.

If you are interested, I have written a blog post on how I have adapted my teaching to meet the hybrid delivery necessitated by COVID.

  • Earth Science Data Analysis 1 (1st year Earth Science Degree programs): In this new course we are introducing numeracy through a lens of data analysis and coding using Python. The teaching of Python is supported using DataCamp which is a great online resource for teaching data science in Python or R.
  • Geophysical Data Science (2nd year Geophysics): Here I teach an introduction to scientific computing and programming using Python to our geophysics cohort. The focus is on data analysis and takes students with no previous experience through aspects of statistical and geospatial modelling. We use many real-world datasets to explore how coding is used in practise and conclude by recreating many of the classic graphics used to communicate Climate Change.
  • Mathematical and Computational Methods in Geophysics (3rd year Geophysics): I previouelty taught the computational part of this course which moves beyond data analysis and into the modelling of physical processes. We look at how to solve differential equations using Python, computational implementation of Fourier Transform and introduce Monte Carlo methods.

Geophysics Professional Placement

I have developed the professional placement route for our geophysics degrees which provides students with the option of taking a year long professional placement sandwiched in-between the 3rd and 4th years of the standard Geophysics degree as a route to obtaining an MEarthPhys with Professional Placement. Despite the impact of COVID, 2020 sees the first student undertake a placement with the Met Office as part of their Industrial Placement scheme.

Geophysics, Hazard and Risk

  • Physics of the Earth (2nd year Geophysics): I teach the seismological component of this introductory course which also covers geomagnetism and gravity.
  • Natural hazards and risk (4th year Geophysics): Here I teach a component of earthquake risk assessment.
  • 4th year geophysics projects

GeoSciences Outreach Course

Our Geoscience Outreach Course provides students to undertake a year long 20 credit outreach project during their 4th year. This unique course provides students to take real ownership of their learning by creating their own outreach ideas, finding a client to realise their project with, delivering their outreach activity and hopefully leaving a legacy that can be taken up by others. Clients have been varied including schools, prisons, local conservation groups, refugee supporting organisations… This allows students the opportunity to develop real world skills that are not available on a traditional academic course.

Field Teaching

  • Lake District Field Trip (1st year Geology and 2nd year Geophysics with Geology):

Education/Academic qualification

Doctor of Philosophy (PhD), A Discrete Element Model of Orogenesis, University of Edinburgh

Award Date: 1 Jan 2004

Master of Physics, University of Oxford

Award Date: 1 Jan 2000

Keywords

  • QE Geology
  • natural hazards
  • earthquake hazard
  • sediment transport
  • computational geoscience
  • uncertainty
  • foreland basins
  • mountain building
  • QC Physics
  • complexity

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