Statement of Purpose:
The Mekong River Basin is one of the world’s largest contributors in the global rice production market with rice paddies covering more than 10 million hectares of land. The production of these crops contributes significantly to the local economies and workforce within the region. The Mekong River Basin experiences seasonal flooding, as well as periods of drought, which affect rice yield. The majority of rice fields in the Mekong River Basin rely primarily on rainwater rather than groundwater for irrigation, which can be problematic during extended periods of drought. In this region, drought is a frequent natural hazard and extreme event caused by weather patterns that reduce precipitation, affecting agricultural production, water resources, and economic stability within the area. The NASA SERVIR Coordination Office located at the Marshall Space Flight Center (MSFC) has partnered with the Asian Disaster Preparedness Center (ADPC) through the SERVIR Mekong Hub in order to improve climate resilience in the Mekong River Basin. This project applied a Scaled Drought Condition Index (SDCI) throughout Thailand, Myanmar, Laos,Vietnam, and Cambodia – the five countries that compose the lower Mekong River Basin. SDCI is an index used specifically to identify regions of agricultural drought through the integration of MODIS NDVI and LST, as well as TRMM and GPM precipitation data. Each input parameter was used in the following ways: a) NDVI aided in the identification of areas with high and low vegetation; b) LST enhanced analysis of vegetation health, surface conditions, and heat stress; and c) precipitation data provided a survey of monthly rainfall conditions throughout the study area. The SDCI was used in creating a time series and compiling a near real-time monitoring tool that aided in mitigation efforts against prolonged agricultural drought in the Mekong River Basin. Through the use of this index, ADPC will be able to reduce local, regional, and national risks throughout the lower basin by integrating drought monitoring tools into food security and the development planning process.
Description of Data Sets:
This index was created using the following data sets: 1) Normalized Difference Vegetation Index (NDVI), 2) land surface temperature (LST), and 3) precipitation data. NDVI and LST data were produced using the MODIS sensor on both Aqua and Terra satellites, stored through the Land Processes Distributed Active Archive Center (LP DAAC). Both NDVI and LST are monthly global data products with a 5.6 kilometer spatial resolution. Precipitation data were gathered from both the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) instrument and the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) sensor. TRMM PR data were acquired as global monthly 3B42 products, and GPM IMERG data were acquired as global 30-minute products. Input data values were scaled as necessary to produce SDCI values corresponding to areas of high and low drought conditions.