A NEER public-good project
The first statewide, publicly accessible 1% annual-chance (100-year) flood hazard maps for India — now spanning 27 states and union territories, from the Himalaya to the coast. Free, transparent, and honest about what it can and can't tell you.
Tamil Nadu & Puducherry · 100-yr flood depth 
Why this exists
Hundreds of millions of people in India live with flood risk they can't see. The best flood data is either commercial and closed, or built for other countries. We're changing that — openly.
No paywall, no login. Anyone can explore the full flood map — and read exactly how it was made.
Every step is documented and built on open, well-sourced data. Not a black box.
Modeled on India’s own terrain and monsoon rainfall, state by state — not adapted from another country.
The idea everyone gets wrong
It means a 1% chance every single year — and the risk stacks up the longer you stay. Try it:
…the chance of seeing at least one 100-year flood is about 1 in 4.
“It flooded last year, so we're safe for decades.” The odds reset every January 1st — last year's flood changes nothing about this year's 1%.
Over a 30-year home loan, it's roughly a 1-in-4 chance. Over a lifetime in one place, higher still. That's why a 1% map matters.
The human stakes
building footprints sit where a 100-year flood would reach — about 20% of the 363M buildings mapped across 27 states & union territories — home to ~1.3 billion people.
Each square ≈ 2% of mapped buildings. Modeled estimate — building footprints overlaid on the 100-year flood layer.
Of the 73M exposed footprints, by modeled flood depth:
Mean depth where flooded: 1.1 m. Most exposure is shallow — but even shallow urban flooding shuts a city down.
of the road network — 11,22,126 km — floods in a 100-year event.
of railway track — 39,763 km — floods in a 100-year event.
A transport segment counts as at risk when the modeled flood is ≥ 15 cm (6 in) deep — enough to stall vehicles and trains.
Share of each district's buildings inside the 100-year floodplain. Andhra's Krishna–Godavari delta and the new Polavaram gorge district, the Cauvery delta and Kerala's backwaters stand apart.
The severe (> 3 m) tail concentrates in the incised Godavari gorge (Andhra's Polavaram, Telangana's Bhadradri Kothagudem) and Kerala's hill-edge districts (Idukki, Pathanamthitta, Kannur) — partly genuine steep-valley flooding, partly where the DEM is weakest. We flag it rather than hide it.
How it's built
A fully documented pipeline. Click a stage to see what happens inside.
Stage 1
The NEER DEM is a bare-earth terrain model built for hydrology across India. We derive it from GEDTM30 (CC-BY, OpenGeoHub) and calibrate it against ICESat-2 ATL08 ground photons — NASA laser measurements of the true ground surface. A spatially-blocked, cross-validated bias surface removes systematic error, and a LightGBM residual model corrects what remains. Heights are referenced to the EGM2008 geoid and hydro-flattened (sea → 0, inland water → bank level) so water routes correctly through the model.
Stage 2
Rainfall losses — how much soaks in versus runs off — are set by the SCS Curve Number method, varied across the grid by land cover and soil. These losses are computed inside the 2D model itself, not as a separate step.
Stage 3
Statistical frequency analysis of rainfall records yields the 1% annual-chance design rainfall — the event that defines this flood layer.
Stage 4
We model the flood as a rain-on-grid (direct-rainfall) 2D HEC-RAS simulation: the design rainfall falls directly onto the terrain mesh and runs as unsteady flow over the NEER DEM, with Curve-Number losses applied cell by cell. Hydrology (rainfall → runoff) and hydraulics (how water moves and pools) are solved together in one model — with no separate hydrologic model or gauged inflow hydrographs. That is what lets it run consistently across India’s largely ungauged basins.
Accuracy & limitations
National terrain error (MAE), before → after correction
Systematic bias, driven to near-zero nationwide
In the atlas states the NEER DEM is at its strongest. Tamil Nadu lands at 1.04 m and Kerala at 1.65 m mean absolute error against ICESat-2, at near-zero bias — flat, flood-relevant terrain, which is exactly where terrain accuracy matters most for modeled flood depth. Accuracy is lower in steep, mountainous regions, where even the satellite ground-truth is itself noisy.
Coverage & roadmap
Hover a state to highlight it; click a live state to open its map. The data is published on a schema built to grow — every new state and return period drops straight in.
Only the 100-year (1%) event is free today. The others — and full property-level risk — are available from NEER on request.
Request other return periods ↗We also model the 2100 flood under future-climate rainfall — IDF design storms shifted along SSP warming pathways — to show how the 1% event grows. Available on request.
Puducherry is in every statistic; its enclaves (Karaikal, Puducherry, Mahe) are too small to draw on the map.
Data access · for teams
The map is free for everyone. For organizations, we serve the underlying data for any area of interest — a city, a district, an asset portfolio, or a whole state — through a simple API.
Built for governments, insurers, proptech, infrastructure planners and researchers.
# exposure for any area of interest
curl https://flood-api.neer.io/exposure \
?region=tamil_nadu &event=100yr
{
"event": "100yr", "unit": "meters",
"buildings": { "total": 25231607, "exposed": 4060006, "pct": 16.1 },
"roads_km": { "total": 419015, "at_risk": 81574, "pct": 19.5 },
"rail_km": { "total": 8335, "at_risk": 2456, "pct": 29.5 },
"depth_cog": "https://.../100yr/tamil_nadu.tif"
}Free to explore. No login. Opens the live interactive map.
Need other return periods (2-yr to 1000-yr) or full property-level risk? Contact NEER →
Questions
It means a flood of this size has a 1% chance of happening in any given year — every year. It is NOT “once every 100 years.” Over a 30-year mortgage, the chance of seeing at least one such flood is about 26%. The name is a probability, not a schedule.
Open the map and type your address into the search bar — it will zoom straight to that spot. If your exact address doesn’t come up, search a nearby landmark or locality instead, then pan and zoom in until you find your building. The blue shading is the modeled 100-year flood; if it covers your rooftop, your building sits inside the floodplain. Click any point to read the modeled flood depth there — how much water that spot would see in a 1% (100-year) event. It’s ~30 m data, so read it as “this building/area could flood,” not an exact figure for one wall.
The colour shows how deep the water gets. Lighter blue is shallower water; deeper, darker blue means deeper — and more dangerous — flooding. Anywhere shaded is expected to take on some water in a 1% (100-year) event; the shade tells you roughly how much. Click a point on the map for the exact modeled depth there.
No. It is an open, independent, modeled flood hazard atlas built by NEER for public awareness and planning context. Always defer to official local authorities for regulatory or emergency decisions.
The underlying NEER DEM reaches sub-meter to ~1.6 m accuracy in the atlas states (Tamil Nadu 1.04 m, Kerala 1.65 m corrected MAE vs ICESat-2), at near-zero bias. The flood layer is modeled on top of that at ~30 m, so treat it as regional hazard screening rather than parcel-level truth.
Three reasons, usually. First, this is the 1% (100-year) event — a rare, severe flood. You can live somewhere for decades and never witness it, and that does not mean the risk is zero. Second, the map shows modeled hazard — where water would go in that extreme event — not a record of floods that have already happened. Third, at ~30 m resolution it cannot see every wall, embankment, or drain that might protect a specific building. Read it as “this area could flood in a severe event,” not “this will flood.”
This layer models one specific thing: the 1% annual-chance river and rainfall flood. It does not capture chronic, local flooding from blocked drains, overwhelmed urban stormwater, very localized low spots, or small channels below the ~30 m grid. Frequent street flooding from poor drainage is real — it is simply a different problem than the large, rare event this map is built to show. That gap is exactly why we publish our limitations alongside the map rather than hide them.
Plan, don’t panic — this is a hazard screen, not a prediction that your home will flood. A few sensible steps: (1) Confirm locally — at ~30 m the map can’t see your exact plot, which may sit higher or lower, so check with local authorities and your own experience. (2) Be ready — know your nearest higher ground and route to it, sign up for any local flood warnings, and keep documents, medicines and an emergency kit handy. (3) Protect the building — where you can, raise electrical points and valuables above likely water levels, keep nearby drains and channels clear, and consider barriers or seals for doors and openings. (4) Building or buying? Factor it in — a higher plinth and good site drainage go a long way. (5) Look into home insurance — India has no standalone flood policy, but standard home cover (like IRDAI’s Bharat Griha Raksha) already includes flood damage under “STFI” perils. Very few households carry any cover, so it’s worth knowing the option exists.
Emergency numbers (India): 112 — all-India emergency · 108 — ambulance · 1077 — district disaster control room.
It spans scales, and it’s mostly about planning ahead. City and regional level: keep new development out of the highest-hazard zones, protect and restore natural drainage (wetlands, floodplains, lakes, urban green space that soak up water), and invest in stormwater drainage, embankments and early-warning systems where they matter most. Building level: elevated plinths, flood-resilient materials, protected utilities. None of it is quick or cheap — chronic urban flooding often needs sustained drainage investment — which is exactly why knowing where the risk concentrates matters: it lets planners aim limited budgets at the places and people most exposed. That prioritization is what this atlas is built to support.
Yes — it is free and public. The methodology and source data are documented and openly licensed (see attributions). Get in touch if you want to collaborate or need the underlying data.
Free today: the 100-year (1% annual chance) flood layer now spans 27 states and union territories — the whole Indo-Gangetic plain (Uttar Pradesh, Bihar, West Bengal, Punjab, Haryana, Delhi), the west (Rajasthan, Gujarat, Madhya Pradesh), the Himalaya (Jammu & Kashmir, Ladakh, Himachal Pradesh, Uttarakhand, Sikkim), the east (Jharkhand, Odisha, Chhattisgarh) and the south (Tamil Nadu, Andhra Pradesh, Telangana, Karnataka, Kerala, Goa) plus Puducherry, Chandigarh and Daman, Diu & DNH. Interactive maps are live for the southern and central states; the newest additions show data and analysis now with maps following. Other return periods — 2, 5, 10, 25, 50, 500 and 1000-year — and full property-level risk are available from NEER on request.