Global Drought Total Economic Loss Risk Deciles

The Global Drought Total Economic Loss Risk Deciles is a 2.5 minute grid of global drought total economic loss risks. A process of spatially allocating Gross Domestic Product (GDP) based upon the Sachs et al. (2003) methodology is utilized. First the proportional contributions of subnational Units to their respective national GDP are determined using sources of various origins. The contribution rates are then applied to published World Bank Development Indicators to determine a GDP value for the subnational Unit. Once the national GDP is spatially stratified into the smallest administrative Units available, GDP values for grid cells are derived using Gridded Population of the World, Version 3 (GPWv3) data of population distributions. A per capita contribution value is determined within each subnational Unit, and this value is multiplied by the population per grid cell. Once a GDP value has been determined on a per grid cell basis, then the regionally variable loss rate as derived from the historical records of EM-DAT is used to determine the total economic loss risks posed to a grid cell by drought hazards. The final surface does not present absolute values of total economic loss, but rather a relative decile (1-10 with increasing risk) ranking of grid cells based upon the calculated economic loss risks. This data set is the result of collaboration among the Columbia University Center for Hazards and Risk Research (CHRR), International Bank for Reconstruction and Development/The World Bank, and Columbia University Center for International Earth Science Information Network (CIESIN).

全球干旱总经济损失风险十位数数据集以2.5分钟格网形式呈现全球干旱总经济损失风险。本数据集采用Sachs等人（2003年）提出的方法论对国内生产总值（GDP）进行空间分配。首先，通过多种来源确定次国家级单位对其相应国家GDP的比重贡献。随后，将贡献率应用于世界银行发布的开发指标，以确定次国家级单位的GDP值。接着，将国家GDP空间分层至最小的行政单元，并利用世界人口网格化数据（GPWv3）中的人口分布数据推导出网格单元的GDP值。在每个次国家级单位内，确定人均贡献值，并将其与每个网格单元的人口数相乘。在确定每个网格单元的GDP值后，利用源自EM-DAT历史记录的区域性损失率来确定干旱灾害对网格单元造成的总经济损失风险。最终数据表面不呈现总经济损失的绝对值，而是基于计算出的经济损失风险，对网格单元进行相对十位数（1-10，风险递增）排名。本数据集是哥伦比亚大学灾害与风险评估研究中心（CHRR）、世界银行重建与发展国际银行以及哥伦比亚大学国际地球科学信息网络中心（CIESIN）合作的结果。