## 4 Soil water and drought monitoring for early-warning applications
### Sample Product Descriptions  
Figures 10 to 13 show sample graphics that highlight the main products from the water-balance model outputs using the Southern Africa region as an example. Similar products are available for western and eastern Africa, central America, Haiti and Dominican Republic and Afghanistan. Figure 10 shows an onset of rains map for southern Africa for the 2006/2007 growing seasons as of the 2\({}^{\mathrm{nd}}\) dekad of March, 2007. Normally, the region's crop growing season spans from September through April. The exact growing season depends on the geographic location. For example, for much of Zimbabwe, the growing season is from November to April. Onset of rains map is a surrogate for the start of season (SOS) of the crop growing period. The SOS is defined with a simple rainfall accounting criteria: a total of 25 mm rainfall received in one dekad followed by a total of 20 mm in the following two consecutive dekads. The SOS map by itself provides critical information on the performance of the season, especially if there is a significant delay in its establishment. In addition, the SOS map is used to initialize the crop water balance model, i.e., the crop water balance model simulates crop water use between the date of the SOS and the end of season for each grid cell at 10 km resolution. The end of the growing season (EOS) is dependent on the location and it varies from a minimum of 9 dekads (3 months) in arid and semi-arid regions to 18 dekads (6 months) in mountainous and wetter regions. Figure 11 shows the soil water index (SWI) which shows the level of soil water in the root zone as defined by the soil water holding capacity (WHC) of the top 1 m of soil. The SWI is a percentage of the WHC. The SWI image shows 4 broad classes for qualitative interpretations. Areas with less than or equal to 10% are labeled as wilting. This is generally a trigger level for drought early warning. The image is interpreted along with a weekly forecast rainfall. If the 7-day forecast rainfall is not promising, the areas with lowest SWI category are expected to go into the crop wilting phase. This is considered critical and becomes a potential candidate for highlighting it as a drought polygon if the data is corroborated with field information. In this regard, a large area of southern Africa falls in this region by the 2\({}^{\mathrm{nd}}\) dekad of March, 2007 because of a dry spell in February and March. Figure 12 shows the spatial distribution of maize crop water requirement satisfaction index (WRSI) for southern Africa as of the 2\({}^{\mathrm{nd}}\) dekad of March 2007. The extended WRSI is composed of two data sources: 1) observed demand and supply from the SOS till the 2\({}^{\mathrm{nd}}\) dekad March, and 2) extended demand and supply from the 2\({}^{\mathrm{nd}}\) dekad of March till the end of the growing season. The extended demand and supply is based on climatological rainfall and potential evapotranspiration data. The WRSI values are expressed as index from 0 to 100. Generally, areas receiving less than 50% of the water demand are considered to have failed while area with values greater than 94% are considered to have received adequate rainfall for yield and biomass production. In the 94+ category, crop yield is more likely to be limited by other management factors (such as fertilizer use, seed variety etc) than water. Figure 10: Onset of rains map for southern Africa for the 2006/2007 growing seasons as of the 2\({}^{\mathrm{nd}}\) dekad of March, 2007. Regions showing WRSI values between the 50 and 95 are at different stages of yield reduction due to water shortage. The exact yield reduction is determined by the prevailing management practices in the region. Thus, using historical data from an administrative district, it is possible to formulate a mathematical relationship between WRSI and yield, which would allow the possibility of using WRSI to forecast yield beginning the mid crop growing season.