Drought Monitoring Techniques for Famine Early Warning Systems in Africa - Monitoring and Predicting Agricultural Drought: A Global Study - page 258

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remain the same as the season progresses depending on the water supply
and deficit. The FAO and FEWS NET WRSI products are mathematically
equivalent when the EOS dekad becomes the current dekad.
Figures 19.2 and 19.3 demonstrate the monitoring capability of WRSI
during the 2001-02 growing season in southern Africa. Figure 19.2 shows
early signs of drought at the middle of the growing season (end of January
2002) in Zimbabwe and surrounding countries. Figure 19.3 shows an in-
tensified and expanded drought by the end of the growing season (end of
April 2002). The depictions in these maps were corroborated by field re-
ports, in which 14 million people were reported to require relief assistance.
The extended WRSI map is an estimate (or forecast) of WRSI for the
EOS. Long-term average rainfall and PET are used to calculate WRSI for
the period between the current dekad and EOS. The calculation principles
are the same as for current WRSI.

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R ainfall and NDVI Combined-Departures Method
The quality of rain-fed crop production in Sahel West Africa is largely a
function of the temporal and spatial distribution of seasonal rainfall. A
method based on departures of NDVI and RFE data from their respective
averages has been devised to monitor the annual growing season in the
Sahel and to make qualitative assessments of harvest prospects up to 4-6
dekads in advance.
Food security and vulnerability analysis and mapping are often based on
administrative subdivisions. This facilitates assistance to vulnerable pop-
ulations in areas affected by either severe production shortfalls or other
shocks to the population's livelihood. As previously mentioned, sparse data
observation networks, poor quality data, and untimely accessibility are
the main problems associated with ground/station data. However, neither
NDVI nor RFE is problem free. Combining these measures helps decrease
the uncertainty in the result. The rainfall and NDVI combined departures
(RNCD) is a method based on a combination of NDVI and RFE data into
an index that reflects the quality of growing season conditions, extracted
for given administrative units. The growing season is divided into three dis-
tinct periods and diagnosed separately for each period. The results of the
three periods are combined in a final step to diagnose the whole growing
season.

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Identification of Growing Season Periods The RNCD method uses three
distinct growing season periods whose lengths are agroclimatological-zone
dependent: (1) the sowing period, from the dekad when generalized sowing
is observed to the dekad when sowing would be considered too late; (2) the
vegetative growth period, from the end of the sowing period to the max-
imum vegetative growth indicated by the dekad of maximum NDVI; and
(3) the maturation period, from the end of the second period to complete
maturation of the vegetation (pastures as well as crops). As an example,
for the Sahelian zones, these periods translate to the following dates: first