Riprap scoring methodology
Riprap produces a flood-exposure tier (1–4) per NYC address, not a calibrated damage probability. The tier is a deterministic literature-grounded composite of public-data signals; the language model writes the citing prose around it but does not score.
1. Why this design
Closed-methodology scores (First Street, Jupiter, Fathom) are useful products but uncitable in civic work. A NYCEM grant writer can't quote "0.73" in a FEMA BRIC sub-application without a defensible audit trail. At the same time, an LLM-emitted score would be non-reproducible and uncalibrated, with documented LLM-as-judge pathologies (Zheng et al. 2023; Wang et al. 2024). The honest middle: a deterministic rubric a planner can argue with.
The tier is computed in app/score.py and mirrored in web/static/app.js.
Both implementations are kept in sync; the Python side is authoritative
for register builds and CLI exports.
2. Methodology pedigree
The composite construction follows a well-trodden path in the multi- indicator vulnerability/exposure literature:
- Cutter, Boruff & Shirley (2003), Social Science Quarterly 84(2): 242–261. The SoVI hazards-of-place pattern: group indicators thematically; sum factors with equal weights because there is no defensible theoretical basis for differential weighting.
- Tate (2012), Natural Hazards 63: 325–347. Explicit Monte Carlo sensitivity analysis showing that hierarchical equal-weighted composites are the most rank-stable. This is why we use equal weights within sub-indices.
- Balica, Wright & van der Meulen (2012), Natural Hazards 64: 73–105. Coastal City Flood Vulnerability Index, multiplicative (Exposure × Susceptibility / Resilience). We adopt only the override-behavior of multiplicative form, as a "max-empirical floor" (§4 below), because we have no resilience term.
- Kim et al. (2019), Scientific Reports 9:18564. Additive vs geometric aggregation; additive is more transparent and reproducible if sub-indices are pre-grouped thematically. Done.
NPCC4 (2024) Ch. 3 (Rosenzweig et al., Annals of the New York Academy of Sciences 1539) and the NYC Hazard Mitigation Plan 2024 supply the NYC-specific tiering hierarchy that informs which scenarios get higher weights inside the Regulatory sub-index.
3. Sub-index structure
Three thematic sub-indices, each normalized to [0, 1] by dividing the weighted sum by the maximum possible weight in the group. The composite is the simple sum of the three sub-indices (range 0–3).
3.1 Regulatory sub-index
Binary "inside zone" indicators with weights ordered by agency tiering:
| Indicator | Weight | Citation |
|---|---|---|
| FEMA NFHL 1% (SFHA) | 1.00 | FEMA NFHL. Regulatory mandate threshold |
| FEMA NFHL 0.2% | 0.50 | FEMA NFHL. Tail scenario |
| NYC DEP Moderate-2050 + 2.5 ft | 0.75 | NYC DEP Stormwater Maps 2021; NPCC4 Ch.3 |
| NYC DEP Extreme-2080 + SLR | 0.50 | NYC DEP Stormwater Maps 2021. Explicitly tail |
| NYC DEP Tidal-2050 | 0.75 | NPCC4 Ch.3 coastal projection |
Why DEP-2050 outranks DEP-2080: NPCC4 designates the 2080 extreme scenario as a tail projection. Closer-horizon coastal/pluvial maps. Those a current planner can act on. Get the higher weight.
3.2 Hydrological sub-index
Continuous terrain measures, banded into 4 levels (1.0 / 0.66 / 0.33 / 0):
| Indicator | Weight | Bands | Citation |
|---|---|---|---|
| HAND (m) | 1.00 | <1, 1–3, 3–10, ≥10 | Nobre et al., 2011, J. Hydrology 404: 13–29 |
| TWI quartile | 0.50 | ≥12, 10–12, 8–10, <8 | Beven & Kirkby, 1979; Sørensen et al., 2006, HESS 10 |
| Elev pct (200 m, inv) | 0.50 | <10, 10–25, 25–50, ≥50 | Standard geomorphometric proxy |
| Elev pct (750 m, inv) | 0.50 | <10, 10–25, 25–50, ≥50 | Standard geomorphometric proxy |
| Basin relief (m) | 0.25 | ≥8, 4–8, 2–4, <2 | Supporting variable, Nobre 2011 |
TWI is half-weighted relative to HAND because TWI is documented as noisier in flat urban DEMs (Sørensen 2006 explicitly states TWI is site-specific and best percentile-binned). HAND remains the canonical hydrology indicator (Aristizabal et al. 2023, WRR 59, NOAA NWM).
3.3 Empirical sub-index
Mix of binary observed-extent flags and banded count signals:
| Indicator | Weight | Citation |
|---|---|---|
| Sandy 2012 inundation | 1.00 + floor | NYC OD 5xsi-dfpx; NYC HMP 2024 |
| USGS Ida HWM within 100 m | 1.00 + floor | USGS STN Event 312 |
| USGS Ida HWM within 800 m | 0.50 | USGS STN Event 312 |
| Prithvi-EO 2.0 Ida polygon | 0.75 | Jakubik et al., 2025 (NASA/IBM Prithvi-EO 2.0); semi-empirical |
| 311 complaint count band | 0.75 | NYC OD erm2-nwe9; NYC 311-as-flood-proxy literature |
| FloodNet trigger (3 yr) | 0.75 | FloodNet NYC; NPCC4 Ch.3 references |
The 311 and FloodNet weights are capped at 0.75 because both signals have documented coverage and reporting bias. 311 reflects civic engagement as well as flooding, FloodNet has uneven spatial coverage. Sandy and HWMs are 1.0 because they're engineered ground-truth observations.
Bands for 311 count (200 m buffer, 5-year window):
| Count | Value |
|---|---|
| ≥10 | 1.00 |
| 3–9 | 0.66 |
| 1–2 | 0.33 |
| 0 | 0 |
4. Max-empirical floor
If Sandy 2012 inundation OR a USGS Ida HWM within 100 m fired, the tier is capped at 2 (Elevated). It cannot be worse, regardless of the additive composite.
This recovers the important multiplicative behaviour Balica 2012
argues for: empirical, ground-truth observations should not be
cancelled out by terrain or modeled scenarios. We implement it as a
floor (a min(tier, 2) after composition) rather than a full
multiplicative form so the composite remains additive and auditable.
The 100 m radius is chosen because USGS HWM positional uncertainty is typically 5–30 m horizontal. 100 m gives ~3σ headroom for a confident "this address was inundated" signal.
5. Composite → tier mapping
The composite is the sum of the three normalized sub-indices (range 0–3):
| Composite | Tier | Label |
|---|---|---|
| ≥ 1.50 | 1 | High exposure |
| ≥ 1.00 | 2 | Elevated exposure |
| ≥ 0.50 | 3 | Moderate exposure |
| > 0 | 4 | Limited exposure |
| 0 | 0 | No flagged exposure |
Then floor: Sandy or HWM<100m → tier ≤ 2.
6. Live signals are NOT in the score
NWS active alerts, NOAA tide residual (surge), and NWS hourly precip are not part of the static tier. Per IPCC AR6 WG II glossary and NPCC4 Ch. 3, exposure is a quasi-stationary property of place; event occurrence is time-varying. Mixing the two would produce a tier that flickers every six minutes and that residents could interpret as neither "is my building exposed?" nor "is it flooding right now?".
Live signals are surfaced separately in the UI as a "Current conditions" badge, with their own provenance (NOAA station ID, NWS alert URL, ASOS station code), and they expire on their own cadence. Static tier is unaffected.
This mirrors how First Street separates Flood Factor (static, 30-yr horizon) from event-day Flood Lab products, and how Fathom separates Global Flood Map from real-time intelligence.
7. Honest scope
Riprap's tier is not:
- A flood-damage probability or expected loss.
- A flood-insurance rating. For that, see FEMA Risk Rating 2.0 (FEMA 2021), which uses claims-driven GLMs over decades of labeled outcome data we do not have.
- A vulnerability assessment. Engineering fragility (foundation type, electrical hardening, drainage), social capacity, and financial absorption are out of scope.
- A prediction. Future-scenario layers (DEP 2050/2080, FEMA 0.2%) are bounding scenarios, not forecasts.
It is:
- An exposure prior. A literature-grounded, deterministic, reproducible index of how many publicly-documented flood signals overlap this address.
- Auditable end-to-end: every term has a published source; every weight has a rationale; the floor rule has a stated motivation; the tier breakpoints are documented above.
- Forkable: a researcher who disagrees with any weight can edit
app/score.pyand rerun. The UI methodology panel makes this invitation explicit.
8. Caveats foregrounded in UI copy
These appear next to the tier badge and in the methodology disclosure:
Riprap tiers are not flood-damage probabilities. They reflect publicly-documented exposure indicators only.
311 counts are influenced by neighborhood reporting habits and may under-represent flooding in lower-engagement areas (Agonafir et al. and the broader 311-as-civic-engagement literature).
DEP 2050/2080 and FEMA 0.2% are bounding scenarios, not forecasts. The tier reads them as "if this scenario materialized, this address would be inside its footprint". Not "this is the expected future."
Compound flooding is not separately modeled. Concurrence of rain
- tide + groundwater is the residual research frontier (NPCC4 Ch. 3).
9. Sensitivity / future work
- Tate-style Monte Carlo perturbation of weights to characterize how sensitive each tier assignment is to weight choice. Not yet implemented; would be a natural next research output.
- Calibration exercise if a labeled dataset emerges (FEMA assistance records, building-level damage from Sandy/Ida insurance claims). Until then, "calibrated" is a word we do not use.
- Block- or NTA-level aggregation for neighborhood-grade scoring, with each indicator computed as an areal aggregate rather than a point sample.
References
Aristizabal, F. et al. (2023). "Improving Continental Hydrologic Modeling Using Height Above Nearest Drainage." Water Resources Research 59.
Balica, S., Wright, N., & van der Meulen, F. (2012). "A Flood Vulnerability Index for Coastal Cities and Its Use in Assessing Climate Change Impacts." Natural Hazards 64: 73–105.
Beven, K. J., & Kirkby, M. J. (1979). "A Physically Based, Variable Contributing Area Model of Basin Hydrology." Hydrological Sciences Bulletin 24(1): 43–69.
Cutter, S. L., Boruff, B. J., & Shirley, W. L. (2003). "Social Vulnerability to Environmental Hazards." Social Science Quarterly 84(2): 242–261.
FEMA (2021). NFIP Risk Rating 2.0 Methodology and Data Sources.
Jakubik, J. et al. (2025). "Prithvi-EO 2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications." NASA/IBM.
Kim, S. et al. (2019). "Assessment of Aggregation Frameworks for Composite Indicators in Measuring Flood Vulnerability to Climate Change." Scientific Reports 9:18564.
Nobre, A. D. et al. (2011). "Height Above the Nearest Drainage. A Hydrologically Relevant New Terrain Model." Journal of Hydrology 404(1–2): 13–29.
NYC HMP (2024). NYC Hazard Mitigation Plan 2024. NYC Emergency Management.
NYC NPCC4 (2024). 4th NYC Climate Assessment. New York City Panel on Climate Change. Including Rosenzweig et al., Ch. 3, Annals NYAS 1539.
Sørensen, R., Zinko, U., & Seibert, J. (2006). "On the Calculation of the Topographic Wetness Index." Hydrology and Earth System Sciences 10: 101–112.
Tate, E. (2012). "Social Vulnerability Indices: A Comparative Assessment Using Uncertainty and Sensitivity Analysis." Natural Hazards 63: 325–347.