Filters: partyWithName: Lei Zou (X) > partyWithName: Volodymyr V. Mihunov (X)

Folders: ROOT > ScienceBase Catalog > National and Regional Climate Adaptation Science Centers > South Central CASC > FY 2014 Projects ( Show direct descendants )

Location Folder Show Tree ROOT _ScienceBase Catalog __National and Regional Climate Adaptation Science Centers ___South Central CASC ____FY 2014 Projects Community Resilience to Drought Hazard: An Analysis of Drought Exposure, Impacts, and Adaptation in the South Central U.S. Developing Effective Drought Monitoring Tools for Farmers and Ranchers in the South Central U.S. Examining Soil and Drought Dynamics to Improve Fire Forecasting in the Southern Great Plains Identifying Tribal Vulnerabilities and Supporting Planning for Extreme Weather Events Science to Assess Future Conservation Practices for the Mississippi River Basin More... Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Extensions Citation (2) Types Citation (3) Contacts Nina S. N. Lam Jennifer E. Argote Margaret A. Reams Nazla Bushra Nina Lam More... Categories Publication (2) Data (1) Tag Types Place (1) Label (3) Theme (1) Drought, Fire and Extreme Weather (3) Science Themes (3) Other (1) Categories (1) More... Tag Schemes Geographic Names Information System (1) None (1) https://www.sciencebase.gov/vocab/category/NCCWSC/DroughtFireandExtremeWeather (3) https://www.sciencebase.gov/vocab/category/NCCWSC/Project/OrganizationName (3) https://www.sciencebase.gov/vocab/category/NCCWSC/ScienceThemes (3) View Results as: JSON ATOM CSV Browse Folder

Combined county-level drought incidence, damage, and census data The threat of droughts and their associated impacts on the landscape and human communities have long been recognized in the United States, especially in high risk areas such as the southcentral region. This project examines whether existing drought indices can predict the occurrence of drought events and their actual damages, how the adaptive capacity (i.e., resilience) varies across space, and what public outreach and engagement effort would be most effective for mitigation of risk and impacts. The study region includes all 503 counties in Arkansas, Louisiana, New Mexico, Oklahoma, and Texas. This data set was created to assess the community resilience to the drought hazards using the Resilience Inference Measurement... Categories: Data; Types: Citation; Tags: Arkansas, Climatological hazard, Drought, Drought, Fire and Extreme Weather, Louisiana, All tags... New Mexico, Oklahoma, Resilience Inference Measurement (RIM) model, South Central CASC, Texas, community resilience, drought, Fewer tags Emerging disparities in community resilience to drought hazard in south-central United States Volodymyr V. Mihunov, Nina S.N. Lam, Robert V. Rohli, Lei Zou, 2019, Emerging disparities in community resilience to drought hazard in south-central United States, International Journal of Disaster Risk Reduction. Categories: Publication; Types: Citation; Tags: Drought, Drought, Fire and Extreme Weather, South Central CASC Community Resilience to Drought Hazard in the South-Central United States Abstract (from http://www.tandfonline.com/eprint/EBxQ7emIEP3P6pzxz74H/full) Drought is a hazard that inflicts costly damage to agricultural, hydrologic, and ecological systems and affects human health and prosperity. A comprehensive assessment of resilience to the drought hazard in various communities and an identification of the main variables that affect resilience is crucial to coping with the hazard and promoting resilience. This study assessed the community resilience to drought hazards of all 503 counties of Arkansas, Louisiana, New Mexico, Oklahoma, and Texas using the resilience inference measurement (RIM) model for the period of 2000 to 2015. Through k-means cluster analysis, stepwise discriminant analysis... Categories: Publication; Types: Citation; Tags: Citation, Drought, Drought, Drought, Fire and Extreme Weather, Publication, All tags... South Central CASC, South Central CASC, Statistical Downscaling, Fewer tags