World Bank · Climate
Droughts, floods, extreme temperatures
Droughts, floods and extreme temperatures is the annual average percentage of the population that is affected by natural disasters classified as either droughts, floods, or extreme temperature events. A drought is an extended period of time characterized by a deficiency in a region's water supply that is the result of constantly below average precipitation. A drought can lead to losses to agriculture, affect inland navigation and hydropower plants, and cause a lack of drinking water and famine. A flood is a significant rise of water level in a stream, lake, reservoir or coastal region. Extreme temperature events are either cold waves or heat waves. A cold wave can be both a prolonged period of excessively cold weather and the sudden invasion of very cold air over a large area. Along with frost it can cause damage to agriculture, infrastructure, and property. A heat wave is a prolonged period of excessively hot and sometimes also humid weather relative to normal climate patterns of a certain region. Population affected is the number of people injured, left homeless or requiring immediate assistance during a period of emergency resulting from a natural disaster; it can also include displaced or evacuated people. Average percentage of population affected is calculated by dividing the sum of total affected for the period stated by the sum of the annual population figures for the period stated.
- Coverage
- 168 of 238 countries
- Latest data
- 2009
- Series
- 168
- Unit
- percent
- Licence
- CC BY 4.0
- Retrieved
- 2026-11-05
- Indicator
- droughts-floods-extreme-temperatures
- Interva ID
- worldbank-droughts-floods-extreme-temperatures
Recency
stale
data to 2009; catalog to 2025
Provenance
2 steps
as the publisher declares it
Versions
1
catalog snapshots
Citation
BibTeX + CSL
versioned permalink
Quality profile
This profile describes what Interva can measure in the data. It does not claim the dataset is accurate, complete, or suitable for a particular use.
Recency
0%Latest observation is 2009; the catalog broadly reports to 2025, so this data is 16 year(s) behind (stale).
Method: Compares the dataset's latest non-projected period with the year most datasets in the catalog end in. Up to 2 years behind is current — annual data is routinely published a year or two late — and more than 5 is stale. Measured from the data, not from when Interva last crawled it.
Temporal completeness
100%0 of 168 series skip at least one year inside their own span; the median series reports 100% of its years.
Method: Per series, years present divided by years from its first to its last observation; the median across series is reported. Annual periods are assumed, which holds for every series in the catalog today.
Geographic coverage
MeasuredCovers 168 of the 238 countries in the catalog.
Method: Counts distinct geographies with at least one observation. Not scored: a regional dataset covering its region completely is not deficient for omitting the rest of the world.
History depth
MeasuredThe median series has 1 observations; the earliest begins in 2009.
Method: Counts non-projected observations per series. Not scored: a long history is useful for trend work and irrelevant for a cross-section.
Revisions
MeasuredNo observation has been restated in any vintage Interva has recorded.
Method: Counts values the publisher changed between Interva's publishes. Not scored: revising estimates is ordinary and often a sign of care, and the count is here so a reader citing a figure knows whether it moves.
Schema conformity
Not assessedNo declared schema or validation rules are attached to this dataset yet.
Validity
Not assessedNo field-level validation rules are attached to this dataset yet.
Consistency
Not assessedCross-series consistency rules are not defined yet. The obvious first one — whether two publishers measuring one concept agree within a stated tolerance — is a candidate.
2 scored from the data, 3 described without a score, 3 not assessed. Pipeline integrity: all 5 checks pass. Assessed 2026-11-07.
By country
Droughts, floods, extreme temperatures for each of the 168 countries it covers, with the full history.
- Afghanistan 2009–2009
- Albania 2009–2009
- Algeria 2009–2009
- American Samoa 2009–2009
- Angola 2009–2009
- Argentina 2009–2009
- Armenia 2009–2009
- Australia 2009–2009
- Austria 2009–2009
- Azerbaijan 2009–2009
- Bangladesh 2009–2009
- Belarus 2009–2009
- Belgium 2009–2009
- Belize 2009–2009
- Benin 2009–2009
- Bhutan 2009–2009
- Bolivia, Plurinational State of 2009–2009
- Bosnia and Herzegovina 2009–2009
- Botswana 2009–2009
- Brazil 2009–2009
- Bulgaria 2009–2009
- Burkina Faso 2009–2009
- Burundi 2009–2009
- Cabo Verde 2009–2009
- Cambodia 2009–2009
- Cameroon 2009–2009
- Canada 2009–2009
- Central African Republic 2009–2009
- Chad 2009–2009
- Chile 2009–2009
- China 2009–2009
- Colombia 2009–2009
- Comoros 2009–2009
- Congo 2009–2009
- Congo, The Democratic Republic of the 2009–2009
- Costa Rica 2009–2009
- Côte d'Ivoire 2009–2009
- Croatia 2009–2009
- Cuba 2009–2009
- Cyprus 2009–2009
- Czechia 2009–2009
- Denmark 2009–2009
- Djibouti 2009–2009
- Dominican Republic 2009–2009
- Ecuador 2009–2009
- Egypt 2009–2009
- El Salvador 2009–2009
- Eritrea 2009–2009
- Estonia 2009–2009
- Eswatini 2009–2009
- Ethiopia 2009–2009
- Fiji 2009–2009
- Finland 2009–2009
- France 2009–2009
- Gambia 2009–2009
- Georgia 2009–2009
- Germany 2009–2009
- Ghana 2009–2009
- Greece 2009–2009
- Guatemala 2009–2009
- Guinea 2009–2009
- Guinea-Bissau 2009–2009
- Guyana 2009–2009
- Haiti 2009–2009
- Honduras 2009–2009
- Hong Kong 2009–2009
- Hungary 2009–2009
- India 2009–2009
- Indonesia 2009–2009
- Iran, Islamic Republic of 2009–2009
- Iraq 2009–2009
- Ireland 2009–2009
- Israel 2009–2009
- Italy 2009–2009
- Jamaica 2009–2009
- Japan 2009–2009
- Jordan 2009–2009
- Kazakhstan 2009–2009
- Kenya 2009–2009
- Kiribati 2009–2009
- Korea, Democratic People's Republic of 2009–2009
- Korea, Republic of 2009–2009
- Kuwait 2009–2009
- Kyrgyzstan 2009–2009
- Lao People's Democratic Republic 2009–2009
- Latvia 2009–2009
- Lebanon 2009–2009
- Lesotho 2009–2009
- Liberia 2009–2009
- Libya 2009–2009
- Lithuania 2009–2009
- Luxembourg 2009–2009
- Madagascar 2009–2009
- Malawi 2009–2009
- Malaysia 2009–2009
- Maldives 2009–2009
- Mali 2009–2009
- Marshall Islands 2009–2009
- Mauritania 2009–2009
- Mauritius 2009–2009
- Mexico 2009–2009
- Micronesia, Federated States of 2009–2009
- Moldova, Republic of 2009–2009
- Mongolia 2009–2009
- Montenegro 2009–2009
- Morocco 2009–2009
- Mozambique 2009–2009
- Myanmar 2009–2009
- Namibia 2009–2009
- Nepal 2009–2009
- Netherlands 2009–2009
- New Zealand 2009–2009
- Nicaragua 2009–2009
- Niger 2009–2009
- Nigeria 2009–2009
- North Macedonia 2009–2009
- Norway 2009–2009
- Pakistan 2009–2009
- Panama 2009–2009
- Papua New Guinea 2009–2009
- Paraguay 2009–2009
- Peru 2009–2009
- Philippines 2009–2009
- Poland 2009–2009
- Portugal 2009–2009
- Puerto Rico 2009–2009
- Romania 2009–2009
- Russian Federation 2009–2009
- Rwanda 2009–2009
- Saint Vincent and the Grenadines 2009–2009
- Samoa 2009–2009
- Saudi Arabia 2009–2009
- Senegal 2009–2009
- Serbia 2009–2009
- Seychelles 2009–2009
- Sierra Leone 2009–2009
- Slovakia 2009–2009
- Slovenia 2009–2009
- Solomon Islands 2009–2009
- Somalia 2009–2009
- South Africa 2009–2009
- Spain 2009–2009
- Sri Lanka 2009–2009
- Sudan 2009–2009
- Suriname 2009–2009
- Sweden 2009–2009
- Switzerland 2009–2009
- Syrian Arab Republic 2009–2009
- Tajikistan 2009–2009
- Tanzania, United Republic of 2009–2009
- Thailand 2009–2009
- Timor-Leste 2009–2009
- Togo 2009–2009
- Trinidad and Tobago 2009–2009
- Tunisia 2009–2009
- Türkiye 2009–2009
- Turkmenistan 2009–2009
- Uganda 2009–2009
- Ukraine 2009–2009
- United Kingdom 2009–2009
- United States 2009–2009
- Uruguay 2009–2009
- Uzbekistan 2009–2009
- Vanuatu 2009–2009
- Venezuela, Bolivarian Republic of 2009–2009
- Viet Nam 2009–2009
- Yemen 2009–2009
- Zambia 2009–2009
Latest observations
| Country | Period | Value | Unit |
|---|---|---|---|
| Afghanistan | 2009 | 1.06 | percent |
| Albania | 2009 | 5.27 | percent |
| Algeria | 2009 | 0.04 | percent |
| American Samoa | 2009 | 0.00 | percent |
| Angola | 2009 | 1.01 | percent |
| Argentina | 2009 | 0.17 | percent |
| Armenia | 2009 | 0.48 | percent |
| Australia | 2009 | 3.05 | percent |
| Austria | 2009 | 0.04 | percent |
| Azerbaijan | 2009 | 1.11 | percent |
Provenance
Who produced these figures, as World Bank declares it — not inferred, and each line says which published field it was read from.
Produced by
CRED, Université Catholique de Louvain
EM-DAT The International Disaster Database, Centre for Research on the Epidemiology of Disasters (CRED) - Université Catholique de Louvain, uri: https://www.emdat.be/
declared by worldbank in sourceOrganization
Read from
World Bank
World Development Indicators
declared by worldbank in source
Versions
A vintage is a dated publish of the catalog. The current entry is a catalog snapshot; checksums are not recorded yet and are shown as such.
- CurrentCurrent catalog snapshotchecksum not recorded
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Citation
Version: catalog snapshot 2026-11-05. The record labels this as a catalog snapshot because immutable dataset releases are not stored yet.
World Bank (2026). Droughts, floods, extreme temperatures. Interva. https://interva.co/dataset/worldbank-droughts-floods-extreme-temperatures (accessed 2026-11-07). catalog snapshot 2026-11-05.
@misc{interva-worldbank-droughts-floods-extreme-temperatures,
title = {Droughts, floods, extreme temperatures},
author = {World Bank},
year = {2026},
howpublished = {\url{https://interva.co/dataset/worldbank-droughts-floods-extreme-temperatures}},
note = {Interva dataset worldbank-droughts-floods-extreme-temperatures; catalog snapshot 2026-11-05},
urldate = {2026-11-07}
}DOI: not assigned (not assigned). The permalink is versioned by catalog snapshot; a stable dataset DOI is a later step.
API access
Every fact on this page is available from the API.
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