DEPTH
DURATION
PROPAGATION
SYSTEMIC IMPAIRMENT
Simulation Active
FD-ENGINE v2.1

Physical Risk,
Quantified.

Physics-based flood propagation modeling across infrastructure, portfolios, and capital systems.

Request Technical BriefingExplore the Engine →
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01 / The Problem

Statistical Systems
Fail in Motion.

Flood exposure is not static. It propagates across terrain and infrastructure in time-evolving sequences that static boundary models cannot capture.

Interdependencies between infrastructure nodes amplify impairment across interconnected systems — cascading failure that point-in-time models fundamentally miss.

Only Flood Dynamics models rain, coastal, and riverine floods together — at asset level, in motion.

Traditional Models: 10–15% Capture
Flood Dynamics: 95–99% Capture

Over 80% of flood events are rain-driven — yet virtually every traditional model is built around coastal and riverine boundary zones, leaving the dominant flood mechanism almost entirely unmodeled.


02 / The Engine

A Hydrodynamic
Simulation Engine.

Urban Flood Scenario v1.2
ExportResetScenario
Layers
Depth
Duration
Flow Velocity
Impairment Layer
Asset Overlay
Depth Threshold
3.0 m
Hr 0Hr 4Hr 8Hr 12
01
High-Resolution Terrain Modeling
Sub-feet digital elevation data processed for accurate surface flow computation across complex urban topography.
02
Time-Step Flow Computation
Time-step simulation producing continuous flood propagation — not static snapshots.
03
Threshold-Based Impairment Logic
Depth and duration thresholds trigger systemic impairment flags across infrastructure abstraction layers.
04
Infrastructure Abstraction Layer
Network interdependencies modeled to surface cascading impairment beyond first-order exposure.

03 / Applications

Applied Across
Critical Systems.

Risk Transfer
Insurance &
Reinsurance
Refine asset-level impact and concentration risk across underwriting books. Move beyond aggregate flood zone classification.
  • Asset-level loss modeling
  • Concentration risk mapping
  • Reinsurance exposure analytics
Capital Markets
Credit & Lending
Identify collateral exposure under forward physical scenarios. Quantify asset-level impairment probability across loan books and real estate portfolios before events occur.
  • Collateral exposure quantification
  • Forward scenario stress-testing
  • Loan book concentration risk
  • Regulatory physical risk disclosure

04 / Deployed Pilots

Deployed Pilots

Real-world deployments with cities, institutions, and utilities

PILOT 01
City of Cambridge
Cambridge, MA
Urban flood risk assessment & Grand Junction Bike Path infrastructure design
PILOT 02
MIT
Massachusetts Institute of Technology
Flood exposure modeling preventing loss of insurance coverage; premiums reduced by millions
PILOT 03
City of Cleveland*
Cleveland, OH
$10B+ in unaccounted exposure uncovered; emergency protocols across 20+ underpasses
PILOT 04
NEORSD*
Northeast Ohio Regional Sewer District
Stormwater & drainage risk assessment; improved infrastructure investment & emergency strategy
*Academic Pilot
PILOT 01 — SIMULATION DETAIL / Cambridge, MA
CAM-2025 / Urban Flood Scenario
ACTIVE
Hr 0Hr 6Hr 12Hr 24
Max Depth
15ft
Above 0.5m threshold
Duration Threshold Exceeded
22hrs
Sustained impairment window
High-Exposure Clusters
18
Identified zones
Assets in Impairment Radius
3,218
Flagged for review
AGGREGATE IMPACT
US$5B+
In losses avoided with proactive response based on Flood Dynamics' findings.
AGGREGATE IMPACT
US$20B+
In hidden risks uncovered for cities and insurers.
AGGREGATE IMPACT
US$100M+
In infrastructure funding redirected to where it matters most.

05 / Technical Architecture

System Architecture

Data Inputs
Terrain elevation data
Rainfall intensity models
Drainage network topology
Asset geolocation registry
Hydrodynamic Engine
Time-step flow computation
Surface routing algorithms
Infiltration modeling
Depth-velocity calculation
Impairment Layer
Threshold-based flagging
Infrastructure abstraction
Cascade propagation logic
Cluster identification
Application Outputs
Asset-level exposure scores
Portfolio aggregation
Scenario comparison
API / data export


06 / Press & Recognition

In the News.

AWARD · MARCH 2026
Breakthrough Technology Prize
2026 MIT Energy Conference · Innovators Forum

Flood Dynamics was named the winner of the 2026 MIT Energy Conference Innovators Forum Breakthrough Technology Prize — recognized for advancing physical risk intelligence to secure energy infrastructure and build resilient communities worldwide.

MIT ENERGY CONFERENCE · 2026
AS POSTED ON LINKEDIN

“We’re honored to be named the 2026 MIT Energy Conference Innovators Forum Breakthrough Technology Prize winner. Thank you to the MIT Energy Conference team for recognizing our work. We’re excited to contribute to securing the energy future and building resilient resources for communities worldwide.”

FD
Flood Dynamics
March 2026
View Post
#MITEnergy  ·  #BreakthroughTechnology  ·  #FloodDynamics
FEATURE · APRIL 2026
Selected for TMA BlueTech Trade Mission
Singapore & Indonesia · April 19–29

Flood Dynamics selected to represent U.S. climate innovation in TMA BlueTech’s 2026 Trade Mission — joining leading maritime innovators shaping the future of coastal and port resilience across Southeast Asia, in partnership with the U.S. Department of Commerce.

TMA BLUETECH · U.S. DEPT. OF COMMERCE
LI →
FEATURE · 2025
Featured at Autodesk University
Autodesk · Data-Driven Hydrodynamic Modeling

MIT and NEORSD engineers presented Flood Dynamics’ scalable data-driven pluvial modeling at Autodesk University — demonstrating real flood event prediction across Cleveland and Cambridge using 1D/2D hydrodynamic models.

AUTODESK UNIVERSITY
Watch →
EVENT · 2025
C40 Cities Summit & COP30
Rio de Janeiro · COP30 Local Leaders Forum

Flood Dynamics represented MIT-born innovation in climate resilience at the C40 Cities Summit in Rio de Janeiro, showcasing AI-driven flood modeling and risk intelligence to global city leaders advancing climate action at COP30.

C40 CITIES · COP30 RIO DE JANEIRO
LI →

07 / About Us

Built at MIT.
Deployed at Scale.

ORIGIN

Flood Dynamics was developed at the Massachusetts Institute of Technology (MIT) and is led by MIT engineers with backgrounds in hydrology, infrastructure systems, and computational modeling.

WHAT WE BUILD

We build advanced simulation systems that model how physical risk impacts the built environment and the institutions that depend on it.

OUR MISSION

Our mission is to make forward-looking physical exposure measurable for institutions that rely on infrastructure stability.

FOUNDED
Massachusetts Institute of Technology (MIT)
EXPERTISE
Hydrology · Infrastructure Systems · Computational Modeling
DEPLOYMENTS
Cambridge · MIT · Cleveland · NEORSD
GET IN TOUCH

Understand Your
Physical Exposure.

Capital-grade physical risk intelligence. Engineered for the precision that financial decision-making demands.