Climate Change in the Lower Mekong Basin: An Analysis of Economic Values at Risk
Date
2014Author
United States Agency for International Development (USAID)
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RT Generic T1 Climate Change in the Lower Mekong Basin: An Analysis of Economic Values at Risk A1 United States Agency for International Development (USAID) YR 2014 LK https://wedocs.unep.org/20.500.11822/9371 PB United States Agency for International Development (USAID) AB TY - GEN T1 - Climate Change in the Lower Mekong Basin: An Analysis of Economic Values at Risk AU - United States Agency for International Development (USAID) Y1 - 2014 UR - https://wedocs.unep.org/20.500.11822/9371 PB - United States Agency for International Development (USAID) AB - @misc{20.500.11822_9371 author = {United States Agency for International Development (USAID)}, title = {Climate Change in the Lower Mekong Basin: An Analysis of Economic Values at Risk}, year = {2014}, abstract = {}, url = {https://wedocs.unep.org/20.500.11822/9371} } @misc{20.500.11822_9371 author = {United States Agency for International Development (USAID)}, title = {Climate Change in the Lower Mekong Basin: An Analysis of Economic Values at Risk}, year = {2014}, abstract = {}, url = {https://wedocs.unep.org/20.500.11822/9371} } TY - GEN T1 - Climate Change in the Lower Mekong Basin: An Analysis of Economic Values at Risk AU - United States Agency for International Development (USAID) UR - https://wedocs.unep.org/20.500.11822/9371 PB - United States Agency for International Development (USAID) AB -View/Open
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This report presents preliminary values-at-risk (VAR) estimates for key resources expected to be impacted by climate change in the Lower Mekong Basin (LMB). These include rural and urban infrastructure, worker productivity, crop production, hydroelectric power, and ecosystem services. To generate VAR estimates for each of these resources WRI utilized the climate modeling of USAID Mekong ARCC’s Climate Change Impact and Adaptation Study for the LMB (hereafter referred to as “Climate Study”) used by ICEM to identify the geographic regions likely to be impacted by increases in flooding, drought, temperature extremes and sea level rise then applied existing methods local data sources to generate VAR estimates.
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