A NEER public-good project

India's flood risk,
finally made open.

The first statewide, publicly accessible 1% annual-chance (100-year) flood hazard maps for India β€” starting with Tamil Nadu and Kerala. Free, transparent, and honest about what it can and can't tell you.

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Buildings in the floodplain
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States mapped
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Grid resolution
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Free & open
Modeled 100-year flood depth across Tamil Nadu Tamil Nadu Β· 100-yr flood depth
Shallow Deep

Why this exists

Good flood maps exist. Just not for the people who need them.

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 β€” openly.

01

Free & open

No paywall, no login. Anyone can explore the full flood map β€” and read exactly how it was made.

02

Transparent

Every step is documented and built on open, well-sourced data. Not a black box.

03

Built for India

Modeled on India’s own terrain and monsoon rainfall, state by state β€” not adapted from another country.

The idea everyone gets wrong

A β€œ100-year flood” is not once every 100 years.

It means a 1% chance every single year β€” and the risk stacks up the longer you stay. Try it:

30 years

…the chance of seeing at least one 100-year flood is about 1 in 4.

26%
The myth

β€œIt flooded last year, so we're safe for decades.” The odds reset every January 1st β€” last year's flood changes nothing about this year's 1%.

The reality

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

Across Tamil Nadu, Puducherry & Kerala, the 1% floodplain isn't empty.

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building footprints sit where a 100-year flood would reach β€” about 16% of the 39M buildings mapped across three regions home to ~114 million people.

Each square β‰ˆ 2% of mapped buildings. Modeled estimate β€” building footprints overlaid on the 100-year flood layer.

How deep, for how many buildings

Of the 6.3M exposed footprints, by modeled flood depth:

  • 0–0.5 m 42% 2.67M
  • 0.5–1 m 22% 1.42M
  • 1–2 m 20% 1.28M
  • 2–3 m 8% 496K
  • 3–6 m 6% 351K
  • > 6 m 2% 98K

Mean depth where flooded: 1.1 m. Most exposure is shallow β€” but even shallow urban flooding shuts a city down.

Where the risk concentrates β€” by district

Share of each district's buildings inside the 100-year floodplain. The Cauvery delta and Kerala's backwaters stand apart.

  1. 0 MayiladuthuraiTN 47% 155K
  2. 0 KaraikalPY 46% 19K
  3. 0 NagapattinamTN 41% 118K
  4. 0 ThiruvarurTN 37% 184K
  5. 0 TiruchirappalliTN 32% 293K
  6. 0 ThanjavurTN 30% 244K
  7. 0 CuddaloreTN 28% 231K
  8. 0 PuducherryPY 26% 59K
  9. 0 AlappuzhaKL 26% 223K
  10. 0 KarurTN 25% 121K
  11. 0 VelloreTN 25% 113K
  12. 0 ChennaiTN 24% 72K
  13. 0 KozhikodeKL 23% 237K
  14. 0 ThiruvallurTN 21% 224K
  15. 0 KannurKL 19% 187K
  16. 0 KottayamKL 19% 149K
  17. 0 ChengalputtuTN 19% 90K
  18. 0 MalappuramKL 18% 288K
  19. 0 ThoothukkudiTN 18% 126K
  20. 0 ErnakulamKL 18% 228K
  21. 0 TirupathurTN 17% 62K
  22. 0 PathanamthittaKL 17% 100K
  23. 0 ThrissurKL 17% 206K
  24. 0 AriyalurTN 17% 49K
  25. 0 NamakkalTN 16% 136K
  26. 0 KasaragodKL 16% 81K
  27. 0 IdukkiKL 16% 65K
  28. 0 KancheepuramTN 16% 143K
  29. 0 PerambalurTN 16% 32K
  30. 0 ErodeTN 15% 165K
  31. 0 RamanathapuramTN 14% 71K
  32. 0 TiruppurTN 14% 171K
  33. 0 MahePY 13% 2K
  34. 0 ViluppuramTN 13% 92K
  35. 0 SalemTN 13% 176K
  36. 0 KollamKL 13% 132K
  37. 0 VirudhunagarTN 13% 86K
  38. 0 ThiruvananthapuramKL 12% 148K
  39. 0 CoimbatoreTN 12% 154K
  40. 0 MaduraiTN 12% 95K
  41. 0 DharmapuriTN 11% 73K
  42. 0 RanipetTN 10% 47K
  43. 0 KallakurichiTN 10% 41K
  44. 0 KrishnagiriTN 10% 69K
  45. 0 PalakkadKL 10% 106K
  46. 0 The NilgirisTN 9% 21K
  47. 0 TirunelveliTN 9% 56K
  48. 0 DindigulTN 9% 78K
  49. 0 WayanadKL 9% 30K
  50. 0 TiruvannamalaiTN 8% 79K
  51. 0 KanniyakumariTN 8% 46K
  52. 0 TheniTN 7% 28K
  53. 0 SivagangaTN 7% 43K
  54. 0 TenkasiTN 7% 38K
  55. 0 PudukkottaiTN 5% 38K

The severe (> 3 m) tail concentrates in Kerala's hill-edge districts (Idukki, Pathanamthitta, Kannur) β€” partly genuine steep-valley flooding, partly where the DEM is weakest. We flag it rather than hide it.

How it's built

From raw satellite terrain to a modeled flood β€” in four stages.

A fully documented pipeline. Click a stage to see what happens inside.

Stage 1

A high-accuracy bare-earth terrain model

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 β€” 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 β†’ 0, inland water β†’ bank level) so water routes correctly through the model.

⇆
Raw GEDTM30 (runs high) NEER DEM Β· matches ground truth ●

Stage 2

Rainfall β†’ runoff (SCS-CN)

The SCS Curve Number method translates design rainfall into surface runoff based on land cover and soil, setting how much water reaches the channels and floodplain.

Stage 3

The 1% (100-year) design storm

Statistical frequency analysis of rainfall records yields the 1% annual-chance design rainfall β€” the event that defines this flood layer.

Stage 4

2D hydraulic modeling

We route the design event through a 2D HEC-RAS hydraulic model over the NEER DEM to produce modeled flood depth in meters across the floodplain.

Modeled flood depth Β· HEC-RAS 2D

Accuracy & limitations

We measured it against the ground. Here's the honest result.

1.68 m β†’ 1.47 m

National terrain error (MAE), before β†’ after correction

β‰ˆ 0.01 m

Systematic bias, driven to near-zero nationwide

Terrain accuracy by state (MAE vs ICESat-2)

  • Delhi 0.59 m
  • Haryana 0.61 m
  • Punjab 0.65 m
  • Rajasthan 0.69 m
  • Bihar 0.72 m
  • Tamil Nadu 1.04 m
  • Kerala 1.65 m

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 β€” 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.

What this map can't tell you

  • These are modeled flood depths, not observed flood records. They show where a 1% annual-chance event would likely produce flooding β€” not a forecast or a guarantee.
  • ~30 m resolution. This is regional hazard screening, not parcel-level or street-level certainty.
  • Terrain accuracy is lower in steep and mountainous areas; some locations are still rough. The atlas leads with flat, flood-relevant terrain where the DEM is strongest.
  • Hydraulic models can produce artifacts. We null physically implausible depths (we removed modeled depths over 100 m), but residual local errors can remain.

Coverage & roadmap

Live today. Growing across India.

Live

Tamil Nadu

  • 1.37 mmean modeled depth
  • 1.04 mterrain accuracy

Hover a state to highlight it; click a live state to open its map. The data is published on a schema built to grow β€” every new state and return period drops straight in.

Return periods

2-yr 50% / yr On request
5-yr 20% / yr On request
10-yr 10% / yr On request
25-yr 4% / yr On request
50-yr 2% / yr On request
100-yr 1% / yr Free Β· Live
500-yr 0.2% / yr On request
1000-yr 0.1% / yr On request

Only the 100-year (1%) event is free today. The others β€” and full property-level risk β€” are available from NEER on request.

Request other return periods β†—
More states coming
KarnatakaAndhra PradeshMaharashtra…and the rest of India

See the flood map for your state.

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 β†’

Questions

Frequently asked

What does β€œ1% annual-chance” or β€œ100-year flood” actually mean?

It means a flood of this size has a 1% chance of happening in any given year β€” every year. It is NOT β€œonce 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.

Is this an official government flood map?

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.

How accurate is it?

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.

Is it free? Can I use it?

Yes β€” 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.

Which states and return periods are available?

Free today: Tamil Nadu and Kerala, 100-year (1% annual chance) only. Other return periods β€” 2, 5, 10, 25, 50, 500 and 1000-year β€” and full property-level risk are available from NEER on request. More states are being added on the same open schema.