Abstract
Water risk is increasingly material to households, municipalities, insurers, lenders, property owners, and water-dependent companies. Yet public-facing water intelligence remains split across flood maps, drought indicators, contamination records, infrastructure data, and satellite observations. This report proposes a property-level water intelligence framework built from public data, satellite-backed observation, and transparent scoring methods.
Executive Summary
The core claim is narrow: no current public product appears to combine water quality, PFAS and contamination risk, drought, flood, groundwater, infrastructure age, and property or insurance relevance into one inspectable water-risk view. ALCUB3 should validate this gap before expanding product claims. Water Pulse is the first public interface, with Observatory and BasinKit supporting visual evidence and developer access.
Prior Art and Market Context
Waterplan demonstrates demand for AI-native water risk platforms for water-dependent companies. First Street has established consumer-facing property climate risk and flood data. Floodbase shows the importance of satellite-backed flood intelligence and insurance workflows. Fathom contributes flood maps and commercial water-risk modeling.
The ALCUB3 wedge is broader water intelligence: quality, contamination, drought, flood, groundwater, infrastructure, and public evidence in one mission/product lane.
Public Data Sources
- EPA and state water-quality records for public water systems, contaminant observations, and compliance context.
- USGS and groundwater records for wells, hydrology, and regional water conditions.
- Drought.gov and NOAA context for drought, streamflow, flood forecast, and water-model signals.
- NASA SWOT for surface-water height and storage context where coverage is suitable.
- Landsat and Sentinel-2 for historical optical water-body change detection.
- SAM 2 or SAM 2.1 as the externally defensible segmentation baseline for satellite or image water-body work.
Proposed Scoring Framework
1. Source Confidence
Every feature should carry a source tier: directly observed, public-record derived, modeled, inferred, or unavailable. The score should make confidence visible rather than hiding uncertainty behind one number.
2. Risk Families
The initial model should separate quality and contamination, supply stress, flood exposure, groundwater context, infrastructure age, and property relevance. Each family should be inspectable before any composite score is shown.
3. Product Relevance
Different users need different weighting. Homeowners, insurers, lenders, EHS teams, municipalities, and water-dependent enterprises should see the same evidence with different workflow emphasis.
Limitations
- Public datasets can be stale, incomplete, regionally inconsistent, or difficult to compare across jurisdictions.
- Satellite segmentation can miss narrow waterways, cloud-obscured scenes, seasonal dynamics, and local infrastructure details.
- Property-level relevance is not the same as laboratory testing, engineering inspection, or regulatory determination.
- NVIDIA ecosystem components may be useful for acceleration and serving, but this report treats them as stack options, not partnership claims.
- Unverified models and research tools stay out of public claims until identity, license, and commercial permissibility are verified.
Validation Plan
- Select reference regions with varied water profiles: coastal flood, inland drought, groundwater stress, known contamination concern, and infrastructure age risk.
- Build a reproducible source registry for each region with citation, timestamp, coverage, and caveat metadata.
- Compare Water Pulse outputs against public records, known flood products, local water reports, and partner review where available.
- Publish an evidence brief for each reference region before presenting a generalized product claim.
Product Implications
The initial wedge should be mission plus evidence: Water Pulse and Observatory as public entry points, BasinKit as the developer/API layer, and Research as the validation layer. The commercial path can serve property, insurance, mortgage, EHS, municipal, and water-dependent enterprise risk once the evidence model is strong enough.
Citations and References
- Waterplan - AI-native water risk platform reference.
- First Street Flood Factor methodology - property-level flood risk reference.
- Floodbase - satellite-backed flood intelligence and insurance workflows.
- Fathom - flood maps and water-risk intelligence.
- NASA SWOT - surface-water and ocean topography mission data context.
- NOAA NWPS API - water prediction and streamflow/flood context.
- Landsat water resources - water observation use cases.
- Meta SAM 2 announcement and facebookresearch/sam2 - segmentation baseline references.
- NVIDIA Earth-2 and NVIDIA Inception - ecosystem references, not partnership claims.
Publication Review Status
This technical report is under publication review. Before public launch, it follows ALCUB3-PUBLICATION-POLICY.md: technical review, legal/IP check, founder approval, final citation check, and then publication. arXiv consideration comes later only if the work is strong enough.