Hindu Kush Himalayan (HKH) Food Security: Utilizing NASA's EOS data in the DSSAT Crop Model to Research the Potential Effects of Climate Change on Food Security in HKH Region

摘要

Nepal's food supply is under threat from climate change and population pressure. The reduction in supply and increase in demand have combined to raise food prices and increase cost of production. The goal of this research is to improve environmental management and climate change preparedness by strengthening the relationship between scientists and governments using geospatial technologies in order to improve the food security in the country of Nepal in the Hindu Kush Himalayan (HKH) region. Using real time satellite derived data Nepalese food security forecasts can be generated and famine threat (food security threats) predicted using a gridded form of the Decision Support System for Agrotechnology (DSSAT), GriDSSAT. DSSAT a point data system that can be used to determine crop health, growth, and yield. DSSAT is a computer software system designed to predict growth and yield for more than 25 crops, to assist in producing successful crop management techniques, and to provide alternate options for decision making (Tsuji et al. 1998; Hoogenboom et al. 2004). The gridded form of DSSAT, GriDSSAT, provides spatial and temporal estimates of crop stress and yield. Using real time NASA satellite data, TRMM precipitation and GLDAS solar insolation and temperatures, Nepalese food security forecasts can be generated and famine threat (food security threats) predicted. Current practices in Nepal include timely first hand observations and collections from meteorological stations throughout the country. Management practices harness in situ data collection for flood preparation, not to study agricultural growth, timing or yield; all of which are necessary in order to more accurately predict regions susceptible to famine. The remotely sensed products currently available, such as the Famine Early Warning System Network (FEWSnet) uses the Normalized Differential Vegetation Index (NDVI) and remotely sensed soil moisture readings to predict famine threat. DHM and ICIMOD have a partnership where real time meteorological station data is uploaded into an online mapper. No remotely sensed data is used to understand the effect of daily fluctuations of solar insolation, precipitation, and temperature on crop health, and hence food availability for the country. The DSSAT can be run using NASA's remotely sensed data, making famine prediction more efficient and effective, and relief efforts more targeted. This data from the GriDSSAT output can be displayed as a tool in an online mapper for dissemination of daily crop stresses and seasonal yields.