Storm Surge Hazard (RP 250)

The storm surge hazard map indicates the mean run-up height on the coast for seven return periods: 10, 25, 50, 100, 250, 500, 1000 years. The map has coastal coverage with points in the countries with storm surge hazard. The data were classified into three hazard categories—low, moderate, and high—based on storm surge run-up heights for a 250-year return period, a widely used standard for coastal hazard zoning and infrastructure risk assessment. Run-up values below 0.1 meters are considered as “Low”; run-up values between 0.1 meters and 2 meters (inclusive) are considered as “Moderate”; run-up values greater than 2 meters are considered as “High”. Storm surge hazard is modeled only along the coastline. The process involves generating a grid along the coastline and 5km inland. In fact, no backwater effects were modeled, this is only due to the continent’s contour map (shapefile) version used to create the grid mentioned on the coastline. The tropical cyclone events used for the elaboration of this map consider climate change based on models representative concentration pathways (RCP) scenarios. Climate change scenario: SSP5 RCP8.5 In this project Mediterranean tropical-like cyclones were not included in the hazard assessment process. We considered only tropical cyclones as storms that develop in areas of low pressure over tropical oceans, and that are associated with several hazards such as strong winds and storm surge. These two hazards were assessed at a global level but given that although tropical cyclones are formed along the North Atlantic Ocean but do not occur in Europe, neither strong wings nor storm surge were modeled for European countries. Background paper: Multi-hazard Disaster Risk Model of Infrastructure and Buildings at the Global Level (2023). Cardona, O.D., Bernal, G.A., Villegas, C.P., Molina, J.F., Herrera, S.A., Marulanda, M.C., Rincón, D.F., Grajales, S., Marulanda, P.M., Gonzalez, D., Maskrey, A. (2023). https://giri.unepgrid.ch/sites/default/files/2023-11/2.4-INGENIAR-CDRI-Background-Report-Risk-model.pdf Release date: Fri Jun 30 2023 The layer was clipped to the geographic boundaries of 1) IDB Borrowing Member Countries, 2) Caribbean Development Bank (CDB) Borrowing Countries, 3) Organization of Eastern Caribbean States (OECS) Member Countries.

The tsunami hazard map indicates the mean wave run-up height on the coast for a return period of 475 years. The map has coastal coverage with points in the countries with tsunami hazard. Run-up values below 0.1 m are considered as “Low”; run-up values between 0.1 m and 2 m (inclusive) are considered as “Moderate”; run-up values greater than 2 m are considered as “High”. Background paper: Multi-hazard Disaster Risk Model of Infrastructure and Buildings at the Global Level (2023). Cardona, O.D., Bernal, G.A., Villegas, C.P., Molina, J.F., Herrera, S.A., Marulanda, M.C., Rincón, D.F., Grajales, S., Marulanda, P.M., Gonzalez, D., Maskrey, A. (2023). https://giri.unepgrid.ch/sites/default/files/2023-11/2.4-INGENIAR-CDRI-Background-Report-Risk-model.pdf Release date: Fri Jun 30 2023 The layer was clipped to the geographic boundaries of 1) IDB Borrowing Member Countries, 2) Caribbean Development Bank (CDB) Borrowing Countries, 3) Organization of Eastern Caribbean States (OECS) Member Countries.

Note: This layer is produced using a different data source and modeling methodology than the climate‑change riverine flooding layer (CDRI-GIRI), which means there are areas identified as hazardous by one model but not the other; using both layers together is good practice to capture all areas that may be potentially affected by riverine flooding across the two modeling frameworks. This layer represents an aggregated riverine flood hazard classification derived from seven original flood‑inundation depth rasters corresponding to return periods (RP) of 10, 20, 50, 75, 100, 200, and 500 years. Each RP layer was classified as either Moderate or High hazard using the matrix shown below, following a hazard‑ranking approach derived from the Nicaragua MET‑ALARN thresholds. This classification was applied independently to the seven RP layers. A combination rule was then applied, assigning to each pixel the highest hazard class observed across all seven RPs. Intensity / Frequency RP ≤ 10 10 H ≥ 1.0 m High High 0.5 m ≤ H High Moderate 0.1 m ≤ H Moderate Moderate The original rasters come from the Global River Flood Hazard (GLOFAS) Maps dataset, a gridded global product representing simulated inundation depths along the global river network. The underlying flow simulations are produced with the open‑source LISFLOOD hydrological model, while inundation extents are simulated using the LISFLOOD‑FP hydrodynamic model. Each cell in the source rasters represents water depth in meters, and the dataset was developed under the Copernicus Emergency Management Service (CEMS) to support disaster‑risk management and infrastructure‑resilience planning. The map has a resolution of 3 arc-sec. (~93 meters at the equator; east–west distance decreases with latitude). The layers were clipped to the geographic boundaries of the IDB borrowing countries. Links to the original layers: 1‑in‑10 yr riverine flooding hazard 1‑in‑20 yr riverine flooding hazard 1‑in‑50 yr riverine flooding hazard 1‑in‑75 yr riverine flooding hazard 1‑in‑100 yr riverine flooding hazard 1‑in‑200 yr riverine flooding hazard 1‑in‑500 yr riverine flooding hazard VECTORIZED VERSION AVAILABLE HERE: Riverine Flooding Hazard. Disclaimer on Coastal Coverage Limitations The spatial dataset does not provide complete coverage in coastal areas. The data were clipped using the World Countries Generalized polygon, which does not fully capture detailed coastal geometries. As a result, certain coastal zones fall outside the clipping boundary and are therefore not represented in the dataset. This limitation should be taken into account when interpreting results for coastal or near‑shore areas. This will be corrected soon.

The landslide susceptibility map for current climate conditions highlights regions vulnerable to landslides caused by earthquakes or precipitation. This map was derived by combining the two susceptibility layers described below: for each cell, the highest value between the two was selected. Classes 2 and 3 are categorized as "Moderate", and classes 4 and 5 as "High". Class 1 denotes no susceptibility and is not shown. 1) The earthquake-induced landslide susceptibility map indicates the areas of the world that are more prone to landslides triggered by earthquakes. The landslide susceptibility is based on the model developed by NGI (Nadim et al., 2006, 2013; Jaedicke et al., 2013) but with improvements and refinements. The earthquake-induced landslides susceptibility map classifies the terrain into five susceptibility classes by combining slope, vegetation, lithology, and soil moisture information from global datasets. The weights of different susceptibility factors were calibrated to the information available in landslide inventories and physical processes. 2) The precipitation-induced landslide susceptibility map for the existing climate indicates the areas of the world that are more prone to landslides in the current climate conditions. The landslide susceptibility is based on the model developed by NGI (Nadim et al., 2006, 2013; Jaedicke et al., 2013) but with improvements and refinements. The precipitation-induced landslides susceptibility map for the current climate classifies the terrain into five susceptibility classes by combining slope, vegetation, lithology, and antecedent rainfall information from global datasets. Antecedent rainfall information has been obtained from the W5E5 dataset for the period 1979-2016. The weights of different susceptibility factors were calibrated to the information available in landslide inventories and physical processes. Note: This layer represents landslide susceptibility and not landslide hazard. It does not incorporate triggering factors (e.g., earthquake ground motion or rainfall intensity/return periods). Hazard can only be derived by combining susceptibility with a defined trigger scenario. The map has a resolution of 3 arc-sec. (~93 meters at the equator; east–west distance decreases with latitude). Background paper: A new model for global landslide susceptibility assessment and scenario-based hazard assessment (2003) Rosa M. Palau, Farrokh Nadim, Eivind Paulsen, Erlend Storrøsten https://giri.unepgrid.ch/sites/default/files/2023-06/20230615-NGI_manuscript_GIRI_landlside_hazard_model.pdf Release date: Sun Apr 30 2023 The layer was clipped to the geographic boundaries of 1) IDB Borrowing Member Countries, 2) Caribbean Development Bank (CDB) Borrowing Countries, 3) Organization of Eastern Caribbean States (OECS) Member Countries. VECTORIZED VERSION AVAILABLE HERE: Landslide Susceptibility

Abstract: The Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3 data set contains land areas with urban, quasi-urban, rural, and total populations (counts) within the LECZ for 234 countries and other recognized territories for the years 1990, 2000, and 2015. This data set updates initial estimates for the LECZ population by drawing on a newer collection of input data, and provides a range of estimates for at-risk population and land area. Constructing accurate estimates requires high-quality and methodologically consistent input data, and the LECZv3 evaluates multiple data sources for population totals, digital elevation model, and spatially-delimited urban classifications. Users can find the paper "Estimating Population and Urban Areas at Risk of Coastal Hazards, 1990-2015: How data choices matter" (MacManus, et al. 2021) in order to evaluate selected inputs for modeling Low Elevation Coastal Zones. According to the paper, the following are considered core data sets for the purposes of LECZv3 estimates: Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT-DEM), Global Human Settlement (GHSL) Population Grid R2019 and Degree of Urbanization Settlement Model Grid R2019a v2, and the Gridded Population of the World, Version 4 (GPWv4), Revision 11. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) and the City University of New York (CUNY) Institute for Demographic Research (CIDR). Purpose: To provide estimates of urban and rural populations and land areas for the years 1990, 2000, 2015 for 234 countries and statistical areas with contiguous coastal elevations of less than or equal to 5m above sea level, 5-10m above sea level, and national totals using multiple updated data sources for comparative analysis. Citation: Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. (2021). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4TM782G Legend: Color Service Pixel Value Legend Label Description: 5 0 - 5m LECZ LECZs are derived from Multi-Error-Removed Improved Terrain Digital Elevation Model (MERIT-DEM) are provided as a spatial layer in a 9 arc second resolution raster (GeoTIFF). This data categorically demarcates the two low elevation coastal zones (0-5m and 5-10m LECZs) and a third category representing the non-coastal areas at any elevation (outside of LECZs) coded as 31. This raster data is also provided as a web map and image service. It is in the WGS84 coordinate system. 10 >5 - 10m LECZ 31 >10m - Outside of LECZ Resolution: nine arc-seconds (~300m) Publication References: Low Elevation Coastal Zone (LECZ) Urban-Rural Population Estimates, Global Rural-Urban Mapping Project (GRUMP), Alpha Version. McGranahan, G., D. Balk, and B. Anderson. (2007). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4TM782G Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 2. Center for International Earth Science Information Network - CIESIN - Columbia University. (2013). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4MW2F2J Sea Level Rise Impacts on Ramsar Wetlands of International Importance. Center for International Earth Science Information Network - CIESIN - Columbia University. (2013). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4CC0XMD Documentation for the Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Center For International Earth Science Information Network - CIESIN - Columbia University. (2021). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/z0r0-gc08

Abstract and Limitations of Use: The Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3 data set contains land areas with urban, quasi-urban, rural, and total populations (counts) within the LECZ for 234 countries and other recognized territories for the years 1990, 2000, and 2015. This data set updates initial estimates for the LECZ population by drawing on a newer collection of input data, and provides a range of estimates for at-risk population and land area. Constructing accurate estimates requires high-quality and methodologically consistent input data, and the LECZv3 evaluates multiple data sources for population totals, digital elevation model, and spatially-delimited urban classifications. Users can find the paper "Estimating Population and Urban Areas at Risk of Coastal Hazards, 1990-2015: How data choices matter" (MacManus, et al. 2021) in order to evaluate selected inputs for modeling Low Elevation Coastal Zones. According to the paper, the following are considered core data sets for the purposes of LECZv3 estimates: Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT-DEM), Global Human Settlement (GHSL) Population Grid R2019 and Degree of Urbanization Settlement Model Grid R2019a v2, and the Gridded Population of the World, Version 4 (GPWv4), Revision 11. This data set is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) and the City University of New York (CUNY) Institute for Demographic Research (CIDR). Because this is a historical dataset, this item does not follow a routine update frequency.   Intended Use: To provide estimates of urban and rural populations and land areas for the years 1990, 2000, 2015 for 234 countries and statistical areas with contiguous coastal elevations of less than or equal to 5m above sea level, 5-10m above sea level, and national totals using multiple updated data sources for comparative analysis.  Citation: Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Center for International Earth Science Information Network - CIESIN - Columbia University, and CUNY Institute for Demographic Research - CIDR - City University of New York. (2021). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4TM782G Legend:ColorService Pixel ValueLegend LabelDescription: 50 - 5m LECZLECZs are derived from Multi-Error-Removed Improved Terrain Digital Elevation Model (MERIT-DEM) are provided as a spatial layer in a 9 arc second resolution raster (GeoTIFF). This data categorically demarcates the two low elevation coastal zones (0-5m and 5-10m LECZs) and a third category representing the non-coastal areas at any elevation (outside of LECZs) coded as 31. This raster data is also provided as a web map and image service. It is in the WGS84 coordinate system. 10>5 - 10m LECZ 31>10m - Outside of LECZResolution: nine arc-seconds (~300m)  Publication References:Low Elevation Coastal Zone (LECZ) Urban-Rural Population Estimates, Global Rural-Urban Mapping Project (GRUMP), Alpha Version. McGranahan, G., D. Balk, and B. Anderson. (2007). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4TM782G Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 2. Center for International Earth Science Information Network - CIESIN - Columbia University. (2013). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4MW2F2J Sea Level Rise Impacts on Ramsar Wetlands of International Importance. Center for International Earth Science Information Network - CIESIN - Columbia University. (2013). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/H4CC0XMD Documentation for the Low Elevation Coastal Zone (LECZ) Urban-Rural Population and Land Area Estimates, Version 3. Center For International Earth Science Information Network - CIESIN - Columbia University. (2021). NASA Socioeconomic Data and Applications Center (SEDAC). DOI: https://doi.org/10.7927/z0r0-gc08