Abstract - Development of a Water Budget Model for Monitoring Agriculture in Africa

Track: Water Resources

Robert Klaver
US Geological Survey
Science and Applications Branch
, SD

Telephone: 605-594-6067
Fax: 605-594-6568
E-mail: bklaver@edcserver1.cr.usgs.gov

John Lewis, James Verdin

Development of a Water Budget Model for Monitoring Agriculture in Africa

The U.S. Agency for International Development's Famine Early Warning System (FEWS) project monitors subSaharan Africa using personal interviews, governmental statistics, and satellites to assess the vulnerability of the population to famine. Useful satellite techniques for agricultural monitoring are the Normalized Difference Vegetation Index (NDVI) from the National Oceanographic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer data and estimates of rainfall from MeteoSat. The staff of the U.S. Geological Survey's EROS Data Center and FEWS proposed the development of a water budget model to assist the crop monitoring effort. This index would complement NDVI imagery by providing similar information developed from different data sources. The development of the water budget model proceeded incrementally. Initially, data from NOAA's NCEP/NCAR forty-year reanalysis CD ROM was used to test the feasibility of the project and develop techniques. The CD ROM contained monthly averages (1982 - 1994_ for pressure, temperature, radiation, and rainfall at 2.5-degree resolution for the world. These data were converted into ARCGrid format, and evapotransirpiation (ET) using the Priestly-Taylor method was calculated. Images of precipitation, ET, moisture, deficit and surplus, and Thornthwaite's Moisture Index were produced showing patterns consistent with the expectations with FEWS analysts. These data served as climatic averages against which moisture deviations over shorter time periods were calculated. The next step in model development was to obtain six-hour data from NOAA's GDAS climatic model These one-degree resolution data were summarized over a ten-day period. From these dekadal data, not only are the proceeding indices calcullated but also the Food and Agriculture Organization (FAO) soil water requitement satisfaction index. this index combines precipiation and ET with soil water holding capacity to calculate the cumulative water stress for crops over a growing season. The FAO soil water satisfaction index provides decision makers with an independent measure of crop growing conditions to be used in addition to NDVI and field reports. The modeling effort thus far has focused on the Sahel.