4.6 Article

Performance Measures for Validation of Oil Spill Dispersion Models Based on Satellite and Coastal Data

Journal

IEEE JOURNAL OF OCEANIC ENGINEERING
Volume 47, Issue 1, Pages 126-140

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JOE.2021.3099562

Keywords

Oils; Sea measurements; Predictive models; Biological system modeling; Data models; Atmospheric modeling; Satellites; Model checking; numerical simulation; oil pollution

Funding

  1. Innovate U.K. through A4I Project [37003]
  2. Science and Technology Facilities Council (STFC) Hartree Centre and Riskaware Ltd.
  3. STFC
  4. Innovate U.K.
  5. U.K. Research and Innovation

Ask authors/readers for more resources

This article introduces a set of performance metrics for assessing the ability of oil spill dispersion models. The metrics are applied to real-world case studies and validated using satellite imagery and coastal impact reports. The study proposes ways to assist in cleanup operations of actual oil spills by evaluating model performance and sensitivity to input parameters.
This article presents a set of performance metrics, whose purpose is to provide a quantitative measure of the ability of oil spill dispersion models to simulate real-world oil spills. The metrics are described in detail and are applied to the output from an existing oil spill model for two specific case studies. The metrics in question make use of both satellite imagery and coastal impact reports as the basis of the validation. Specifically, we recommend the 2-D measure of effectiveness as a means of quantifying model performance based on the extent of overlap between the observations and the model output. Additionally, we show that it is advantageous to supplement the 2-D measure of effectiveness with a newly proposed set of skill scores, based on the geometric area and centroid of a given oil spill. We also demonstrate how the metrics can be used to assess the sensitivity of a model to its input parameters and the impact this has on the accuracy of the resultant forecast. Finally, we offer a real-world interpretation for each metric introduced and suggest ways that they can be used to assist in cleanup operations of actual oil spills.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available