Same Model, Different Environments
We applied the same RAM PE model at three active or planned offshore wind sites. Each has different water depth, bottom composition, and distance from the NARW migration corridor. If the sensitivity ranking changes across sites, site-specific surveys are essential. If the ranking is stable, the same survey strategy works everywhere.
| Site | Location | Water Depth | Bottom Type | Baseline Zone (160 dB) |
|---|---|---|---|---|
| Vineyard Wind (VW) | S. Massachusetts | 37 m | Sand / glacial till | 5.2 km |
| CVOW | Virginia Beach | 25 m | Sand / clay | 6.8 km |
| Revolution Wind (RevWind) | Rhode Island | 37 m | Sand / gravel | 4.9 km |
The shallower site (CVOW, 25 m) produces the largest baseline shutdown zone. In shallow water, sound interacts more strongly with the bottom, and the lower absorption means energy propagates farther. This is consistent with Investigation 01’s finding that bottom interaction dominates.
Sound speed from WOA2023 monthly T/S via Mackenzie (1981). January (winter, well-mixed) vs July (summer, stratified thermocline). All three sites show 40–50 m/s seasonal variation at the surface but converge below 30 m.
The Tornado Chart
For each input, we varied it across its plausible range while holding all other inputs at their baseline values. The result is the spread in the 160 dB shutdown zone distance attributable to each input alone.
Bottom attenuation dominates with 11 km of zone spread — more than all other inputs combined. The physical explanation is straightforward: in shallow water (<40 m), sound bounces off the bottom many times per kilometer. Small changes in how much energy each bounce absorbs compound rapidly with range.
Bottom type (sand vs. clay vs. gravel) contributes 4 km of spread, primarily through changes in the sound speed ratio at the water-sediment interface, which controls the critical angle for total internal reflection.
Seasonal sound speed profile contributes only 0.5 km. The summer thermocline creates a slight downward-refracting profile that increases bottom interaction, but the effect is small compared to the bottom properties themselves.
Bathymetry resolution (31 m CUDEM vs. 1 km interpolated) contributes only 0.2 km. The continental shelf is relatively flat in these lease areas; higher-resolution bathymetry doesn’t change the answer meaningfully.
One-at-a-time (OAT) sensitivity: each input varied across its plausible range while others held at baseline. OAT cannot capture interactions between inputs. Bottom attenuation and bottom type are physically correlated (both derive from sediment grain size via Hamilton’s regressions); their individual spreads cannot simply be summed. Combined across 3 sites (envelope of max minus min zone distance).
What OAT Cannot See
OAT analysis identified bottom sediment properties as the dominant driver of shutdown zone size. Sobol analysis reveals that source level (S₁ = 0.74) and active mitigation (S₁ = 0.61) together explain most of the variance in marine mammal take — sediment properties explain roughly 5%.
These two analyses lead to opposite survey recommendations:
- OAT-informed strategy: Commission a geotechnical survey to characterize bottom sediment. Addresses ~5% of take variance. Cost: $200K–$500K.
- Sobol-informed strategy: Instrument the first few installation piles carefully to measure source levels and validate mitigation effectiveness. Addresses ~74% of take variance. Cost: comparable or lower.
OAT doesn't just give an incomplete picture — it points regulators at the wrong survey to commission.
OAT varies one input at a time, holding everything else fixed. That means it structurally cannot detect interactions — cases where the combination of two inputs matters more than either alone. We ran a Sobol variance decomposition (Saltelli sampling, 28,672 evaluations) across 6 inputs simultaneously to quantify both direct effects and interactions.
| Input | Range | S1 (Direct) | ST (Total) | Interaction |
|---|
Source level (ST = 74%) and mitigation performance (ST = 61%) dominate the take estimate — not bottom properties (ST < 5%). But their first-order effects are only 23% and 15%. The gap is interaction: the S2 interaction between source level and mitigation alone accounts for ~25–30% of total variance. Physically, this makes sense: take scales with zone area (πr²), and the zone is the product of source-level range and mitigation reduction — a multiplicative interaction that OAT cannot detect.
The OAT tornado is not wrong — it’s incomplete. Within environmental inputs only, bottom properties do dominate. But the OAT held source level and mitigation at fixed assumed values (221.7 dB and 6 dB). When those assumptions are uncertain too, they dominate everything else. Sum(S1) = 0.44 means 56% of variance comes from interactions. The sensitivity ranking changes depending on what you hold fixed — and on the assumed prior ranges. If the pile design constrains source level to a narrow band (e.g., 218–224 dB for a known monopile), bottom properties would re-emerge as the leading driver. The Sobol analysis shows what matters when all inputs are uncertain; the OAT shows what matters once the engineering decisions are fixed.
Sobol analysis via SALib (Saltelli 2002). Uniform distributions on all 6 inputs. Nbase = 2,048, second-order indices computed. The model is a fast parametric surrogate: shutdown zone from Q2 RAM PE lookup (9 grain sizes, 4 freq, 4 azimuths) with analytical scaling for attenuation (zone × α−0.3) and source level (zone × 10ΔSL/17.5). Validated against 50 full RAM PE runs (400 propagation solves): R² = 0.925, median error 8.2%, positive bias +1.5 km (conservative — surrogate overpredicts zones). The surrogate degrades above SL > 225 dB where the analytical scaling overestimates range; the Sobol ranking is robust but exact index values carry ±10–15% uncertainty from surrogate error. Sobol indices are conditional on assumed prior ranges — narrowing the source level range (e.g., to a known pile design) would increase the relative importance of bottom properties.
Different Decisions, Different Drivers
The Sobol ranking changes depending on which output matters. The shutdown zone (regulatory metric) is driven by source level (ST = 67%) and mitigation (ST = 46%), with moderate interactions. The masking zone (ecological metric) is almost entirely source level (ST = 97%) because bubble curtains are irrelevant at 50–80 km range. And NARW density only matters for the take estimate, not the zone distance.
All three outputs computed from the same 28,672 surrogate evaluations (validated against 50 full RAM PE runs, R² = 0.925). ST confidence intervals < 0.07 for zone metrics; wider for annual take (up to 0.21) due to multiplicative scaling through area and density. Second-order indices confirm source level × mitigation interaction (S2 ≈ 0.15–0.31 for take and shutdown, ≈ 0 for masking zone; S2 has wider confidence bands than S1/ST at this sample size). Masking zone uses the same surrogate with range-scaled RAM PE propagation curve; uncertainty is higher at extreme ranges (>80 km).
Where to Spend the Survey Budget
The sensitivity ranking translates directly into survey prioritization. If an input drives most of the uncertainty, the survey that resolves it has the highest value. If an input barely matters, the survey that measures it is wasted money.
| Survey | Resolves | Est. Cost | Zone Uncertainty Reduced | Priority |
|---|---|---|---|---|
| Geotechnical (cores + CPT) | Bottom attenuation + type | ~$200K | 15 km (bottom atten + type) | HIGH |
| CTD / Glider Campaign | Seasonal SSP | ~$100K | 0.5 km | LOW |
| Multibeam Bathymetry | Bathymetry resolution | ~$50K | 0.2 km | LOW |
Survey cost estimates are order-of-magnitude ranges based on published BOEM and IHA cost data for Atlantic OCS projects. Actual costs vary significantly with scope, vessel availability, and number of sites.
The Sobol analysis adds a new priority: characterize actual source level and mitigation performance through in-situ monitoring during initial piles. These two inputs explain 74% and 61% of take variance (total-order). A $200K geotech survey resolves both bottom parameters (ST < 5% each, partially overlapping) — important but far less than the 74% from source level. The most cost-effective “survey” may be careful measurement of the first few piles.
Shallower Sites Show More Seasonal Sensitivity
While bottom properties dominate everywhere, the relative importance of seasonal sound speed varies with depth. At CVOW (25 m), the seasonal SSP spread is 3.2 km. At Vineyard Wind (37 m), it is only 0.5 km. The physics: shallower water has fewer propagating modes, and the thermocline occupies a larger fraction of the water column, so seasonal changes have a proportionally larger effect on the mode structure.
| Site | Depth | Bottom Spread (km) | Seasonal SSP Spread (km) | SSP / Bottom Ratio |
|---|---|---|---|---|
| CVOW | 25 m | 14.2 | 3.2 | 23% |
| Vineyard Wind | 37 m | 10.8 | 0.5 | 5% |
| Revolution Wind | 37 m | 9.6 | 0.7 | 7% |
This means CTD surveys may have value at shallower sites even though they are low priority at deeper ones. The survey recommendation is not universal — it depends on the site’s depth. But the geotech survey is high priority everywhere.
OAT screening (3 sites, 4 environmental inputs) + Sobol global analysis (6 inputs, 28,672 evaluations, Saltelli sampling). 160 dB re 1 μPa SPL threshold. Ranges from literature and IHA applications.