1.7 Model Sensitivity and Uncertainty Issues
17
parameters are used with consensus within the industry, to obtain comparable results
between analyses. As an example; for sediment substrates, finding as accurate as
possible values of e.g. total organic carbon content (TOC) will improve the result
accuracy. On the other hand, measurements of TOC vary greatly with the local
conditions (e.g. background contamination) and the uncertainty may be high. The
sensitivity of each model step to its parameters was therefore the subject of a separate
study in the project and is the focus of Chap. 4. The input parameters and the proposed
standard values were tested for their relative importance to the outcome of the model
in the sensitivity and validation phase of the project.
As far as possible, results have also been validated against impact estimates from
two historically important oil spills, the Exxon Valdez Oil Spill and the Deepwater
Horizon Oil Spill. Comparing the model against historic spills is a particularly interesting and challenging task described in Chap. 4 “Testing and Validating against
Historic Spills”. Whilst such model validations have many limitations, as impact
assessments from the historic spills in themselves also contain uncertainties as results
of modelling and calculations, we found that the results of ERA Acute calculations
fell within the boundaries of the impact estimates from the spills. We therefore believe
that the model is ready to be used and that further experience and work will refine
and improve it over time.
References—Introduction
Bjørgesæter A, Damsgaard Jensen J (2015). ERA Acute phase 3—surface compartment. Acona
report to Statoil and Total. Report No. 37571. v.04. Oslo, 22.05.2015. (Supplementary Material,
Background Report 3, Surface_compartment_ERA Acute 2015.pdf). https://norskoljeoggass.no/
globalassets/dokumenter/miljo/era-acute/report-3-era-acute-surface_compartment-2015.pdf
Bock M, Robinson H, Wenning R, French-McCay RJ, Walker AH (2018) Comparative risk assessment of oil spill response options for a deepwater oil well blowout: Part II. Relative risk
methodology. Mar Pollut Bull 133(2018):984–1000
Brönner U, Nordtug T, Jonsson H, Ugland KI (2015) Joint report—impact and restoration model—
water column. SINTEF & DNV GL Report. SINTEF F26517/DNV GL 1IL8NGC-13. 81 pp.
(Supplementary Material, Background Report 5. Water_column_ERA_Acute 2015.pdf). https://
norskoljeoggass.no/globalassets/dokumenter/miljo/era-acute/report-5-era-acute-watercolumn_
compartment–2015.pdf
Brönner U, Stefanakos C, Skancke J (2017) ERA Acute calculator—technical specification. ERA
Acute Project Report WP1a, 87 pp. (Supplementary material, ERA Acute Technical Specification
2017.pdf)
Brude OW, Rusten, M, Braathen, M (2015) Development of Shoreline compartment algorithms.
DNV GL Report. 1ILBNGC-9. 43 pp (Supplementary Material, Background Report 4 Shoreline_compartment_ERA Acute 2015.pdf). Figure 6. https://norskoljeoggass.no/globalassets/dok
umenter/miljo/era-acute/report-4-era-acute-shorelinecompartment-2015.pdf
GNOME model webpage (2020). https://response.restoration.noaa.gov/oil-and-chemical-spills/oilspills/response-tools/gnome.html. Accessed December 2020
Guillen G, Rainey G, Morin M (2004) A simple rapid approach using coupled multivariate statistical
methods, GIS and trajectory models to delineate areas of common oil spill risk. J Mar Syst
45(3):221–235
17
parameters are used with consensus within the industry, to obtain comparable results
between analyses. As an example; for sediment substrates, finding as accurate as
possible values of e.g. total organic carbon content (TOC) will improve the result
accuracy. On the other hand, measurements of TOC vary greatly with the local
conditions (e.g. background contamination) and the uncertainty may be high. The
sensitivity of each model step to its parameters was therefore the subject of a separate
study in the project and is the focus of Chap. 4. The input parameters and the proposed
standard values were tested for their relative importance to the outcome of the model
in the sensitivity and validation phase of the project.
As far as possible, results have also been validated against impact estimates from
two historically important oil spills, the Exxon Valdez Oil Spill and the Deepwater
Horizon Oil Spill. Comparing the model against historic spills is a particularly interesting and challenging task described in Chap. 4 “Testing and Validating against
Historic Spills”. Whilst such model validations have many limitations, as impact
assessments from the historic spills in themselves also contain uncertainties as results
of modelling and calculations, we found that the results of ERA Acute calculations
fell within the boundaries of the impact estimates from the spills. We therefore believe
that the model is ready to be used and that further experience and work will refine
and improve it over time.
References—Introduction
Bjørgesæter A, Damsgaard Jensen J (2015). ERA Acute phase 3—surface compartment. Acona
report to Statoil and Total. Report No. 37571. v.04. Oslo, 22.05.2015. (Supplementary Material,
Background Report 3, Surface_compartment_ERA Acute 2015.pdf). https://norskoljeoggass.no/
globalassets/dokumenter/miljo/era-acute/report-3-era-acute-surface_compartment-2015.pdf
Bock M, Robinson H, Wenning R, French-McCay RJ, Walker AH (2018) Comparative risk assessment of oil spill response options for a deepwater oil well blowout: Part II. Relative risk
methodology. Mar Pollut Bull 133(2018):984–1000
Brönner U, Nordtug T, Jonsson H, Ugland KI (2015) Joint report—impact and restoration model—
water column. SINTEF & DNV GL Report. SINTEF F26517/DNV GL 1IL8NGC-13. 81 pp.
(Supplementary Material, Background Report 5. Water_column_ERA_Acute 2015.pdf). https://
norskoljeoggass.no/globalassets/dokumenter/miljo/era-acute/report-5-era-acute-watercolumn_
compartment–2015.pdf
Brönner U, Stefanakos C, Skancke J (2017) ERA Acute calculator—technical specification. ERA
Acute Project Report WP1a, 87 pp. (Supplementary material, ERA Acute Technical Specification
2017.pdf)
Brude OW, Rusten, M, Braathen, M (2015) Development of Shoreline compartment algorithms.
DNV GL Report. 1ILBNGC-9. 43 pp (Supplementary Material, Background Report 4 Shoreline_compartment_ERA Acute 2015.pdf). Figure 6. https://norskoljeoggass.no/globalassets/dok
umenter/miljo/era-acute/report-4-era-acute-shorelinecompartment-2015.pdf
GNOME model webpage (2020). https://response.restoration.noaa.gov/oil-and-chemical-spills/oilspills/response-tools/gnome.html. Accessed December 2020
Guillen G, Rainey G, Morin M (2004) A simple rapid approach using coupled multivariate statistical
methods, GIS and trajectory models to delineate areas of common oil spill risk. J Mar Syst
45(3):221–235