Preprints
https://doi.org/10.5194/egusphere-2024-442
https://doi.org/10.5194/egusphere-2024-442
21 Feb 2024
 | 21 Feb 2024
Status: this preprint is open for discussion.

Novel extensions to the Fisher copula to model flood spatial dependence over North America

Duy Anh Alexandre, Chiranjib Chaudhuri, and Jasmin Gill-Fortin

Abstract. Taking into account the spatial dependence of floods is essential for an accurate assessment of fluvial flood risk. We propose novel extensions to the Fisher copula to statistically model the spatial structure of observed historical flood record data across North America. These include a machine-learning based XGBoost model, exploiting the information contained in 130 catchment specific covariates to predict discharge Kendall's τ coefficients between pairs of gauged-ungauged catchments. A novel conditional simulation strategy is utilized to simulate coherent flooding at all catchments efficiently. After subdividing North America into 14 hydrological regions and 1.8 million catchments, applying our methodology allows to obtain synthetic flood event sets with spatial dependence, magnitudes and frequency resembling those of the historical events. The different components of the model are validated using several measures of dependence and extremal dependence to compare the observed and simulated events. The obtained event set is further analyzed and supports the conclusions from a reference paper in flood spatial modeling. We find a non-trivial relationship between the spatial extent of a flood event and its peak magnitude.

Duy Anh Alexandre, Chiranjib Chaudhuri, and Jasmin Gill-Fortin

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-442', Anonymous Referee #1, 24 Mar 2024 reply
    • AC1: 'Reply on RC1', Duy Anh Alexandre, 15 Apr 2024 reply
Duy Anh Alexandre, Chiranjib Chaudhuri, and Jasmin Gill-Fortin
Duy Anh Alexandre, Chiranjib Chaudhuri, and Jasmin Gill-Fortin

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Short summary
Estimating extreme river discharges at single stations is relatively simple. However, flooding is a spatial phenomenon as rivers are connected. We develop a statistical method to estimate extreme flows with global coverage, accounting for spatial dependence. Using our model, synthetic flood events are simulated with more information than the limited historical events. This event catalogue can be used to produce spatially coherent flood depth maps, for flood risk assessment.