Techniques to Predict Agricultural Droughts - Monitoring and Predicting Agricultural Drought: A Global Study - page 52

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[52],

Line
——
8.3
——
Norm
PgEn

Fig ure 4.7 Estimation of drought-affected area.

Spatio-temporal drought behaviors were investigated by Sirdas and ¸en
(2 003) for Turkey, where the drought period, magnitude, and standardized
pr ecipitation index (SPI) values were presented to depict the relationships
be tween drought duration and magnitude.

[52],

C onclusions
This chapter has focused on some of techniques that can be used to predict
agricultural drought. Whereas statistical regression, time series, and pat-
tern recognition techniques were directly based on the crop yield variation
to define drought, the probabilistic technique was centered on soil moisture
surplus or deficit concept. It must be noted, however, that an intricate rela-
tionship exists between soil moisture deficit and crop yield or agricultural
drought. Therefore, the probabilistic method described in this chapter can
be indirectly linked to crop yield to predict agricultural drought.

References
Boken, V.K. 2000. Forecasting spring wheat yield using time series analysis: A case
study for the Canadian Prairies. Agron. J. 92:1047-1053.
Boken, V.K., and C.F. Shaykewich. 2002. Improving an operational wheat yield
model for the Canadian Prairies using phenological-stage-based normalized
difference vegetation index. Intl. J. Remote Sensing 23:4157-4170.