Hebei vs Punjab: River flooding exposure — Cropland share exposed to river flooding

Hebei
15.82 Percentage of agricultural land area
in 2022
Punjab
15.66 Percentage of agricultural land area
in 2022
Hebei rank
264th
Punjab rank
265th

River flooding exposure — Cropland share exposed to river flooding over time

  • Hebei
  • Punjab
051015200020112022

How they compare

Hebei currently reports 15.82 Percentage of agricultural land area against 15.66 Percentage of agricultural land area in Punjab, a difference of 0.16 Percentage of agricultural land area.

Across all 23 years both countries report, Hebei has been ahead every year.

Hebei ranks 264th and Punjab ranks 265th of 3163 regions.

Hebei has averaged higher in every one of the 3 decades both report.

Head to head by decade

Decade Hebei Punjab Difference Ahead
2000s 15.7 Percentage of agricultural land area 15.47 Percentage of agricultural land area 0.2313 Percentage of agricultural land area Hebei
2010s 15.67 Percentage of agricultural land area 15.59 Percentage of agricultural land area 0.0848 Percentage of agricultural land area Hebei
2020s 15.8 Percentage of agricultural land area 15.63 Percentage of agricultural land area 0.1611 Percentage of agricultural land area Hebei

Averages of every year both report within each decade.

Frequently asked questions

Which has higher river flooding exposure — cropland share exposed to river flooding, Hebei or Punjab?
Hebei, at 15.82 Percentage of agricultural land area against 15.66 Percentage of agricultural land area in Punjab as of 2022.
What is the difference in river flooding exposure — cropland share exposed to river flooding between Hebei and Punjab?
0.16 Percentage of agricultural land area, with Hebei ahead.
How many years of comparable data are there for Hebei and Punjab?
23 years are reported by both, from 2000 to 2022.
How do Hebei and Punjab rank globally for river flooding exposure — cropland share exposed to river flooding?
Hebei ranks 264th and Punjab ranks 265th of 3163 regions.
Where does this data come from?
Organisation for Economic Co-operation and Development, published as River flooding exposure — Cropland share exposed to river flooding. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Hebei vs Punjab: River flooding exposure — Cropland share exposed to river flooding. Statizoid, drawing on Organisation for Economic Co-operation and Development. Retrieved 20 August 2026, from https://environment.statizoid.com/compare/river-flooding-exposure-cropland-share-exposed-to-river-flooding/hebei/punjab/

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About this data

Indicator
River flooding exposure — Cropland share exposed to river flooding
Unit
Percentage of agricultural land area
Source
Organisation for Economic Co-operation and Development
Licence
OECD Terms and Conditions (attribution required)
Coverage
3,425 places, 78,723 data points, 2000–2022
Last refreshed

The dataset provides a global assessment of land, population, built-up area and cropland exposure to river flooding for different return periods. Exposure indicators to river flooding have been prepared by the Organisation for Economic Co-operation and Development (OECD). Please see the working paper for a more complete description of the methods. The datasets span the period 2000-2020 depending on data availability and is based on river flood hazard maps with a 10-, 20-, 50- and 100-year return period. A return period is the average or estimated time that a specific hazard is likely to recur. The dataset has a global coverage on a national level; on the sub-national TL2 level (i.e. large subnational regions) results are reported for all OECD countries as well as for Argentina, Brazil, China, India, Indonesia and South Africa. A number of aggregates are included: Euro area, European Union, Advanced economies, Emerging market economies, G7, G20, OECD, OECD Europe, OECD Asia Oceania, OECD Americas and the LAC region. Data source(s): JRC River flood hazard map data, Copernicus Climate Change Initiative land cover data and Global Human Settlement Layer population grid data. Contact: ENV.Stat@oecd.org