Agricultural Drought Indices - US Department of Agriculture

Crop Moisture Index (CMI): CMI is a non-cumulative index based on the difference between the
current ETa and the expected ETa (climatological value) for the same period, as proposed by
Palmer (1968):
CMI = ETa observed – ETa expected (4)
Negative values indicate that deficient evapotranspiration occurred, indicating a drought condition,
whereas positive values show that ETa was more than expected for the period.
Crop Water Development Index (CWDI): CWDI is an agricultural index used to follow the
development conditions of crops in general. This index is based on the relationship between soil
water storage (SWS) and SWHC, called the crop water development fraction (CWDF). SWS is
obtained from the climatological water balance of Thornthwaite and Mather (1955), but can also be
estimated with different WB models. CWDF and CWDI are calculated by the following procedures:
CWDF = SWS / SWHC (5)
CWDI = (CWDF * 0.4) – 1 (6)
Accumulated CWDI (ACWDI) is then obtained for normalized conditions, by
ACWDI = ∑ CWDI / (1.5 n) (7)
where n is the number of periods considered. The classification of the crop development conditions
is presented in Table 5.
Table 5. Classification of ACWDI for crop development conditions. Source: www.infoseca.sp.gov.br.
ACWDI lasses
Crop development conditions
0.8 ≤ ACWDI ≤ 1 Very good
0.6 ≤ ACWDI < 0.8 Good
0.4 ≤ ACWDI < 0.6 Reasonable
0.3 ≤ ACWDI < 0.4 Unfavorable
0.2 ≤ ACWDI < 0.3 Critical
0.1 ≤ ACWDI < 0.2 Severe
ACWDI < 0.1
Extremely severe
Soil Water Storage (SWS) (or relative soil moisture): Another way to identify agricultural droughts
is by soil water storage monitoring. SWS is an output of the water balance (WB). This variable can
be obtained by different WB methods, such as those proposed by Thornthwaite and Mather (1955),
Molinas and Andrade (1993), Allen et al. (1998), and Ritchie (1998). Each kind of WB method will
require specific inputs, but basically they require climate (rainfall and potential evapotranspiration),
soil (physical properties), and plant (crop type, leaf area, crop sensitivity to water stress, crop water
requirement for each phenological phase, and management practices) information, depending on
their complexity. In Brazil, Thornthwaite and Mather’s WB is used by INMET, AGRITEMPO, and
several regional M&HSs. CPTEC/INPE employs Richards’s equation (Hillel 1998, Gevaerd and
Freitas 2006), also known as the hydrological model, using rainfall and temperature data derived
from satellite images as inputs, whereas FUNCEME uses MUSAG WB model (Molinas and
Andrade 1993), which has rainfall, ETP, soil water storage in the previous period, and pedo-transfer
functions for hydraulic soil characterization as inputs. Figures 7, 8, and 9 present examples of the
products provided by INMET, CPTEC, and FUNCEME, where SWS data are spacialized in maps.
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