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SAFE is widely used by researchers across different fields (some statistics of the SAFE download requests between 2016 and 2022 are given here). The full list of scientific papers referencing SAFE can be found on Google Scholar or Scopus.

This page provides a list of some of the scientific applications of SAFE developed by our research group, along with the associated workflows and data.

For information about industry applications of SAFE, see:

  • Knowledge Transfer project on using SAFE in the (re)insurance industry: safe-insurance.uk
  • Talk on why we need to better handle uncertainty in mathematical models
  • AXA XL White paper on using SAFE for Catastrophe models evaluation

Scientific applications from our group

Bozzolan, E., Holcombe, E. A., Pianosi, F. & Wagener, T., (2020), Including informal housing in slope stability analysis – an application to a data-scarce location in the humid tropics, Natural Hazards and Earth System Sciences, 20(11).
Keywords: parameter vs climate uncertainty; scenario-discovery; CART
Summary of key findings: blog post for the Cabot Institute

Wang, A., Pianosi, F., Wagener, T. (2020), A Diagnostic Approach to Analyze the Direction of Change in Model Outputs Based on Global Variations in the Model Inputs, Water Resources Research, 56(8).
Keywords: model calibration, testing and validation; time-varying GSA
Code: workflow script (and data) to reproduce the paper findings: SAFEtoolbox | Miscellaneous | matlab_code_WRR2020

Sarrazin, F., Hartmann, A., Pianosi, F., Rosolem, R. Wagener, T. (2018), V2Karst V1.1: a parsimonious large-scale integrated vegetation–recharge model to simulate the impact of climate and land cover change in karst regions, Geosci. Model Dev., 11, 4933-4964.
Keywords: model calibration; testing and validation; CART
Code: https://github.com/fannysarrazin/V2Karst_model

Almeida, S., Holcombe, E. A., Pianosi, F., and Wagener, T. (2017), Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change, Nat. Hazards Earth Syst. Sci., 17, 225-241.
Keywords: parameter vs climate uncertainty; scenario-discovery; CART

Pianosi, F., Wagener, T. (2016), Understanding the time-varying importance of different uncertainty sources in hydrological modelling using global sensitivity analysis. Hydrol. Process.
Keywords: parameter vs data uncertainty; time-varying GSA; sensitivity & identifiability; PAWN method
Code: workflow script (and data) to reproduce the paper findings: SAFEtoolbox | Miscellaneous | matlab_codeHP2016

Savage, J.T.S., Pianosi, F., Bates, P., Freer, J., Wagener, T. (2016), Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model, Water Resources Research, 52(11), 9146-9163.
Keywords: parameter vs data uncertainty; discrete modelling choices