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Modelling Flood Risk

Committed To Securing Livelihoods

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Modelling Risk of High-Resolution Inundation

Flood damage accounts for an increasing amount of catastrophe losses as a result of our changing climate. As more and more of the global population and wealth are accumulated in regions that will have some measure of probability of inundation occurrence of a 1-in-100-year event, a serious task arises for (re)insurers who face growing concentrations and severity of risk. Furthermore, flood hazard maps will have to be updated more frequently as they will quickly become outdated and more sophisticated methods will be necessary to assess, quantify and manage the risk.

By considering the range complex numerical or other measurable factors that are associated with damaging floods, governments, institutions,  

agencies, etc. will be able to make better informed decisions, develop policy, guidelines and effective risk management strategies. (Re-)insurers and other industries will be able to recognise more profitable business opportunities.

Infinite Observations ZineQx Flood Models capture all aspects of flood risk, including fluvial (riverine) and pluvial (surface water)  flooding, at very high spatial resolutions. By combining our Hur Cat Models with our Flood Models we obtain comprehensive view of tropical cyclone-induced flooding, which is in addition to other sources of flooding, an important flood risk and are able to offer our expertise in regions with coastal and inland flood risk.

Global Flood Catastrophe Models

Modelled Regions :

Click a region to see countries or islands where courage is available. 

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North America

Europe

Middle East

Central America & Caribbean

Asia & Pacific

Latin America

Africa

Australia

North America

Canada

United States

Mexico

Central America

Belize

Costa Rica

El Salvador

Honduras

Nicaragua

Panama

Caribbean

The Greater Antilles

Cuba

Puerto Rico

Jamaica

Cayman Islands

Hispaniola:

Haiti

Dominican Republic

Lucayan Archipelago

Bahamas

Turks and Caicos Islands

Lesser Antilles (Leeward Islands)

Anguilla (UK)

Saint Martin (Fr.)

Sint Maarten (Neth.)

Saint-Barthélemy (Fr.)

Saba (Neth.)

Sint Eustatius (Neth.)

Saint Kitts

Nevis

Antigua

Barbuda

Redonda

Bermuda

Montserrat (UK)

Guadeloupe (Fr.)

La Désirade (Fr.)

Marie-Galante (Fr.)

Les Saintes archipelago (Fr.)

St. Thomas (US VI)

St. John (US VI)

St. Croix (US VI)

Water Island (US VI)

Tortola (UK VI)

Virgin Gorda (UK VI)

Anegada (UK VI)

Jost Van Dyke (UK VI)

Aruba (Neth.)

Curaçao (Neth.)

Bonaire (Neth.)

La Orchila

La Tortuga

La Blanquilla

Margarita Island

Coche

Cubagua

Los Roques Archipelago

Lesser Antilles (Windward Islands)

Dominica

Martinique (Fr.)

Saint Lucia

Barbados

Saint Vincent

Grenadines

Carriacou

Petite Martinique

Grenada

Trinidad

Tobago

South America

Argentina

Bolivia

Chile

Cayman Islands

Colombia

Ecuador

Guyana

Guiana (Fr.)

Paraguay

Peru

Suriname

Uruguay

Venezuela

Europe

Andorra

Austria

Belgium

Bulgaria

Czech Republic

Denmark

Estonia

Finland

France

Germany

Greece

Hungary

Iceland

Ireland

Italy

Latvia

Liechtenstein

Lithuania

Luxembourg

Malta

Monaco

Netherlands 

Norway

Poland

Russia

Spain

Sweden

Switzerland

Turkey

United Kingdom

Vatican City

Asia & Pacific

East Asia

China

Hong Kong (China)

Macau (China)

Japan

North Korea

South Korea

Taiwan

South Asia

Bangladesh

India

Maldives

Sri Lanka

South Asia

Brunei

Cambodia

Indonesia

Laos

Malaysia

Myanmar

Philippines

Singapore

Thailand

Timor-Leste

Vietnam

Australasia

Australia

New Zealand

Melanesia

Fiji

New Caledonia (Fr)

Papua New Guinea

Solomon Islands

Vanuatu

Micronesia

Guam (US)

Kiribati

Marshall Islands

Nauru

Northern Mariana Islands (US)

Wake Island (US)

Polynesia

American Samoa (US)

Cook Islands (NZ)

Easter Island (Ch)

French Polynesia (Fr)

Niue (NZ)

Norfolk Island (A)

Tonga

Tuvalu

Samoa

Wallis and Futuna (Fr)

Understanding Flood Risk Exposure Models

Data Driven Flood Modelling

Infinite Observations estimates that by 2040, over a third of the current agricultural area will be subject to increase inundation, thus having negative implications for human health and economies worldwide. Over half of the population in the most exposed small island developing nations are exposed to some form of flooding exacerbated by sea level rise. In large countries trillions of worth in GDP is exposed to hurricanes. Increasingly severe climate conditions impose growing economic pressure, which impacts sovereign credit risk. Infinite Observations uses global granular data along with detailed analytics for sovereign climate risk data that focuses on key risk drivers such as the amount of agricultural area, population, and GDP (PPP) are/will be exposed to climate hazard of flood risk. This cutting-edge methodology helps to expand the understanding of climate risk that sovereign countries are facing and aid decision and policymakers, investors and credit institutions. 

Quantifying Flood Hazard Losses

To capture flood risk Infinite Observations takes into account: (1) Potential flooding that affects several river basins are caused by large-scale frontal systems of storms and small-scale torrential downpours that frequently cause localized inundations, such as convective summer storms. To be able to capture both (large- and small scale) types of storms a Global Circulation Model (GCM) is coupled with a high-resolution Numerical Weather Prediction (NWP) model. (2) High-resolution precipitation data, snow build-up and snowmelt is considered to be able to take local soil-water balance into account. (3) A flood routing scheme is employed where surface run-off is routed downstream along the river network. (4) The inundation depth is determined using a physically based hydraulic model that converts river flow into water level, or elevation. (5) Average Annual Losses estimates (AAL) are derived for each flood event based on an exposure database that contains flood defence systems, population, building data that are grouped into different structural classes and structural characteristics.

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ZineQx - Infinite Observations

Realistically Quantify & Manage Global Flooding Scenario's Using Our Solutions