Baijanath fire, April 2022 Bardiya National Park, Baijanath, Bansagadhi
The fire started on 15 April 2022 in Baijanath, Nepal, and satellites saw it burning for 15 days. Copernicus’s global GWIS system rebuilt a burnt perimeter of 2,968 hectares from heat detections, spread across 3 municipalities.
It is the 23th largest in Lumbini since 2016 (of 47 with a page). Number 5 in Nepal in 2022, of 11.
The power measured by the satellite is low (10.8 MW in the strongest hotspot), more typical of grass or stubble burning, or a slow surface fire, than of a large crown fire.
Compare with…
- Burnt area
- 2,968ha
- GWIS perimeter (Copernicus)
- Duration
- 15days
- 15 Apr 2022 – 29 Apr 2022
- Municipalities hit
- 3
- municipalities
- Started on
- 15 Apr
- 2022
- Heat detections
- 114
- in a single hotspot: 11 MW
- Danger at start
- 42
- Very high · FWI index
- Average daily power
- 32MW
- detected power per day, on average
Where it burned
How it evolved, day by day
Fire radiative power detected each day, in megawatts, and number of hotspots. The magenta bar marks the peak day.
The weather it burned in
It had gone more than two months without rain (1 mm or more) when it started. Rain came after the fire: 13.8 mm on 2 May.
This area had burned before
99% of the perimeter overlaps earlier fires recorded since 2016: 2,041 ha in 2016, 910 ha in 2017, 389 ha in 2018, 3,235 ha in 2019, 2,430 ha in 2021. Part of it burned more than once, so the yearly figures add up to more than the 2,945 ha that had burned before.
- 2,771 ha Mihinpurwa Motipur fire, April 2019 21,844 ha in total; the hectares shown are those it shares with this fire
- 2,430 ha Bardiya National Park fire, March 2021 17,821 ha in total; the hectares shown are those it shares with this fire
- 1,397 ha Mihinpurwa Motipur fire, April 2016 17,983 ha in total; the hectares shown are those it shares with this fire
- 70 ha Rapti Sonari fire, April 2016 6,431 ha in total; the hectares shown are those it shares with this fire
How big is it?
London boundary: geoBoundaries · Office for National Statistics (Open Government Licence v3.0).
Paris boundary: geoBoundaries · Institut national de l'information géographique et forestière (IGN-F) (Etalab Open License 2.0).
Madrid boundary: geoBoundaries · Open Data ESRI, IGN Central Registry of Cartography Area (CC BY 4.0).
Berlin boundary: geoBoundaries · Federal Agency for Cartography and Geodesy (dl-de/by-2-0).
This compares size, not location: both shapes are at the same scale, north up, centred on each other.
What happened to each town
-
1,603 ha reached on 18 Apr1.8 %
-
Baijanath where it started1,369 ha reached on 16 Apr9.6 %
-
5 ha0.0 %
Burnt area inside each municipality, from crossing the GWIS perimeter with administrative boundaries. The distance runs from the point marking the centre of each area to the nearest fire: staying a kilometre away does not mean it reached the houses.
People and buildings inside the perimeter
GHSL 2020Inside the perimeter there was no noticeable built-up land and almost nobody lived there (GHSL 2020, satellite-based estimate).
This is an estimate on 100 m cells, made from satellite imagery and census data: it does not mean that homes burned or that anyone was harmed. The perimeter also contains land that never burned.
Source: Global Human Settlement Layer (GHS-BUILT-S and GHS-POP R2023A), European Commission Joint Research Centre (JRC), © European Union, CC BY 4.0. Sum inside the perimeter computed by WorldFires. human-settlement.emergency.copernicus.eu
The weather day by day
ECMWF ERA5 reanalysis at the fire location, the standard reference for past weather, and the Canadian Fire Weather Index (the same system Copernicus uses), computed by WorldFires from that data. Days after the fire run until the first rain.
Open-Meteo.com (CC BY 4.0) · Copernicus Climate Change Service (ERA5)
| Day | High | Min. humidity | Peak gust | Rain | Danger (FWI) |
|---|---|---|---|---|---|
| 14 Apr | 37.4 °C | 22 % | 46 km/h | 0.1 mm | Very high 42 |
| 15 Apr | 36.9 °C | 17 % | 48 km/h | 0.0 mm | Very high 48 |
| 16 Apr | 37.8 °C | 18 % | 48 km/h | 0.0 mm | Very high 49 |
| 17 Apr | 37.5 °C | 19 % | 48 km/h | 0.0 mm | Very high 50 |
| 18 Apr | 38.8 °C | 21 % | 45 km/h | 0.0 mm | Very high 48 |
| 19 Apr | 36.7 °C | 37 % | 39 km/h | 0.0 mm | High 36 |
| 20 Apr | 36.9 °C | 36 % | 36 km/h | 0.0 mm | High 36 |
| 21 Apr | 35.4 °C | 42 % | 37 km/h | 0.5 mm | High 34 |
| 22 Apr | 36.6 °C | 25 % | 46 km/h | 0.1 mm | Very high 42 |
| 23 Apr | 37.0 °C | 21 % | 52 km/h | 0.0 mm | Very high 49 |
| 24 Apr | 37.5 °C | 16 % | 52 km/h | 0.0 mm | Extreme 53 |
| 25 Apr | 37.5 °C | 22 % | 38 km/h | 0.0 mm | Very high 48 |
| 26 Apr | 38.5 °C | 22 % | 46 km/h | 0.0 mm | Very high 50 |
| 27 Apr | 37.8 °C | 22 % | 42 km/h | 0.0 mm | Very high 49 |
| 28 Apr | 37.5 °C | 31 % | 34 km/h | 0.0 mm | Very high 41 |
| 29 Apr | 38.0 °C | 37 % | 39 km/h | 0.9 mm | High 32 |
| 30 Apr after | 36.0 °C | 41 % | 37 km/h | 0.3 mm | High 31 |
| 1 May after | 34.8 °C | 42 % | 30 km/h | 0.8 mm | High 24 |
| 2 May after | 33.8 °C | 51 % | 32 km/h | 13.8 mm | Very low 4 |
Before and after, from space
Drag the line to compare the same ground before the fire and after it.
If the day is cloudy, change the date: each satellite passes once a day. In false colour the burnt ground looks brown or red.
Detections table · 114Every satellite heat detection, one by one, with time, satellite, power and coordinates.
| Date and time | Satellite | FRP (MW) | Lat | Lon |
|---|
Other fires nearby
- 17,821 haBardiya National ParkMarch 2021 · 23 days · 3 km away
- 21,844 haMihinpurwa MotipurApril 2019 · 14 days · 9 km away
- 17,983 haMihinpurwa Motipur4 April 2016 · 28 days · 13 km away
- 26,185 haRapti SonariApril 2022 · 21 days · 20 km away
- 26,744 haRapti Sonari16 April 2019 · 28 days · 22 km away
- 19,256 haBabaiMarch 2021 · 31 days · 36 km away
Frequently asked questions
- How long did the Baijanath fire last?
- According to the heat detections seen by satellite inside the perimeter, it burned from 15 April 2022 to 29 April 2022 (15 days). The perimeter dates it from 22 April 2022 to 27 April 2022.
- How much area did it burn?
- The perimeter GWIS (Copernicus) rebuilt from heat detections is 2,968 hectares (29.7 km²). It is an estimate: official national figures may differ.
- Which municipalities burned?
- The fire entered 3 municipalities: Bardiya National Park (1,603 ha, 1.8 %); Baijanath (1,369 ha, 9.6 %); Bansagadhi (5 ha, 0.0 %).
- What was the weather like?
- During the fire the temperature reached 38.8 °C, humidity dropped to 16 % and gusts hit 52 km/h. The fire danger index (FWI) reached 53, class Extreme.
- Where does this data come from?
- From the GWIS (Copernicus) burnt perimeter, NASA FIRMS VIIRS hotspots and the administrative boundaries of Nepal (geoBoundaries). It is not an official report.
Where to verify it
A satellite detection is not an official report. Final figures and the fire’s status are published by each country’s emergency service.
Emergency number: 101 · Emergency number and official warnings ›
Satellite cross-check
History of this page · 2 Changes in area, dates, name, official record or merged pages, compared every night since 24 October 2026.
- Last day with fire: 27 April 2022 → 29 April 2022.
- Start date: 22 April 2022 → 15 April 2022.
Does something look wrong on this page?
This page is built from satellite data and official records, and it sometimes gets things wrong: the wrong dates, the wrong town, two fires merged into one, or something that was not a wildfire at all. If you know this fire first-hand (you live nearby, saw it, fought it or reported on it), tell us what really happened and we will check it.
Report an error
How we know this
- Perimeter: GWIS (Copernicus), rebuilt from heat detections rather than mapped on imagery.
- Dates adjusted with the VIIRS detections inside the perimeter, which said 22 April 2022 to 27 April 2022. 114 Suomi-NPP VIIRS detections on those dates.
- We have not matched this page with any official record.
- Weather: Copernicus ERA5 reanalysis at the fire location, in cells of about 25 km.
- Built-up area and population come from the JRC Global Human Settlement Layer (epoch 2020, 100 m cells), summed inside the perimeter: an estimate of what was there, not a damage count.
Where this data comes from
The perimeter comes from the Copernicus Global Wildfire Information System (GWIS), which rebuilds it from MODIS and VIIRS heat detections and publishes it under CC BY 4.0. It is not measured on imagery as in Europe, so it is an estimate. Heat detections come from the VIIRS sensors aboard Suomi-NPP and NOAA-20, distributed by NASA FIRMS at 375 m resolution. Municipal boundaries come from geoBoundaries ADM3 (Creative Commons Attribution-ShareAlike 4.0 International License). The area per municipality is computed by WorldFires by crossing the perimeter with those boundaries, so it may differ from each country’s official figure.