Agricultural Drought Indices - US Department of Agriculture

Heim (2002) notes that as recently as 1957, annual rainfall amount was used as a drought index in
a study of drought in Texas. Similar criteria have been employed in other countries:
1) Britain: 15 consecutive days with less than 0.25 mm (0.01 in.);
2) India: rainfall half of normal or less for a week, or actual seasonal rainfall deficient by more than
twice the mean deviation;
3) Russia: 10 days with total rainfall not exceeding 5 mm (0.20 in.);
4) Bali: a period of 6 days without rain;
5) Libya: annual rainfall less than 180 mm (7 in.).
Heim (2002) notes that most of these indices were developed and thus valid only for their specific
application in their specific region and makes the point that indices developed for one region may
not be applicable in other regions because the meteorological conditions that result in drought are
highly variable around the world.
Putting Precipitation-based Indices in Context
Although the practical and functional aspects of the (sole) use of meteorological drought indices
are now well recognized, it is also known that for agricultural application purposes, the quantity and
timing of rain events throughout a growing season largely determines the value of such indices in
agricultural production assessments. Meteorological drought indices can be normalized by using
appropriate seasonal indices. However, indices based solely on rainfall data do not, by definition,
take into account other factors such as ambient temperature, relative or absolute humidity, mean
and extreme wind speed, net radiation, evapotranspiration, deep percolation, runoff, soil type, or
the agricultural enterprise (White and Walcott 2009).
Because the length of a growing season can vary between years depending on when rainfall
occurs, tailoring indices to growing seasons to better assess whether drought conditions are
affecting crops and pastures may remain a difficult task and negate the value of sole use of
meteorological indices in drought assessment. White et al. (1998) and White (2000) note that
other important meteorological factors besides rainfall can greatly influence plant growth in a
country such as Australia in ways not necessarily foreseen, and so a second step is often
recommended in drought assessments besides the sole use of a meteorological drought index.
Modification of drought indices, including just slight modification to indices such as the SPI, can
provide improved practical application in certain regions (Ntale and Gan 2003). In particular, in a
comparison of the PDSI, BMDI, and SPI in different regions of East Africa, the SPI was rated
superior to the other indices tested and greatly superior to the PDSI through utilization of this
modification approach.
Of the seven drought indices assessed in Iran by Morid et al. (2006), the meteorological drought
index (the Deciles Index [DI]) (Gibbs and Maher 1967) was rated as “oversensitive,” leading to
unrealistically high temporal and spatial variations in wet conditions, especially in summer.
However, importantly, the authors noted that this sensitivity could be reduced by using temporal
scales larger than 1 month. Additionally, the importance of using long-term precipitation records
for drought analyses has been highlighted by Morid at al. (2006), who note that despite utilizing
different underlying statistical distributions, the SPI and the China-Z index (CZI) performed similarly
in their ability to detect and monitor drought.
Interestingly, when a whole range of drought indices have been ranked according to robustness,
tractability, transparency, sophistication, extendability, and dimensionality, the overall superior
drought indices often emerge as those being simply based on rainfall data inputs and otherwise
most relevant to meteorological drought assessment (Keyantash and Dracup 2002). In a study for
Oregon (USA), Keyantash and Dracup (2002) found, when making an overall assessment, that the
superior drought indices were rainfall deciles, total water deficit, and computed soil moisture, while
the SPI also emerged as a highly valuable estimator of drought severity.
Simulation studies (e.g., Donnelly et al. 1998, Stafford Smith and McKeon 1998, White et al.1998)
have demonstrated that, indeed, grassland and agricultural droughts often coincide with
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