Team Location: Wise County Clerk of Court’s Office, Wise, Virginia; and TecnolÌ_gico de Monterrey Campus Saltillo, Saltillo, Mexico
Normalized Differential Drought Index of Coahuila Mexico (Drought). Image Credit: Coahuila Agriculture Team, NASA DEVELOP National Program.
Authors:
Rohini Swaminathan (Purdue University), Project Lead
Rhiannon Coates (University of Virginia at Wise)
Abednego Mayon (East Tennessee State University)
Pedro Rodriguez Rivera (Mountain Empire Community College)
Carlos Cardenas (TecnolÌ_gico de Monterrey)
Laura Esqueda (TecnolÌ_gico de Monterrey)
Mentors/Advisers:
Kenton Ross, Ph.D. (NASA, DEVELOP National Science Adviser)
DeWayne Cecil, Ph.D. (Global Science and Technology Inc.)
Jack Kennedy (Wise County/City of Norton Circuit Court)
Abstract:
Throughout the course of human history, drought has been one of the most prominent problems affecting the welfare and food security. Coahuila, the third largest state in Mexico, is characterized by semi-arid weather conditions and have been constantly affected by drought. In 2013, roughly 43 percent of Mexico was suffering from drought of some degree, with 2 percent classified as most severely affected. Coahuila was one of the most affected states in the country. With the collaboration of several Mexican agencies, including the National Institute of Statistics and Geography (INEGI), National Water Commission (CONAGUA) and Secretariat of Environment of Coahuila (SEMA), the project aimed to provide a drought severity index of this region utilizing NASA’s Earth observations including Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar. Landsat and MODIS surface reflectance data were utilized to produce vegetation indices of the region at different scales. MODIS Land Surface Temperature (LST) combined with TRMM rainfall data and vegetation indices were used in the Scaled Drought Condition Index (SDCI) to obtain drought severity. Surface Reflectance data from MODIS also was used to calculate Normalized Differential Drought Index (NDDI). The Palmer Drought Severity Index (PDSI) was used to compare the outputs of SDCI model and NDDI. The project also compared the differences in accuracy between TRMM rainfall data and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Socio-economic data were used to estimate the percentage of the most severely affected human and cattle population within the study area. Project results and methodologies provided the ability to enhance Coahuila’s drought assessment capabilities and other decision-making processes.