Monitoring Drought in the United States: Status and Trends - Monitoring and Predicting Agricultural Drought: A Global Study - page 124

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46

bution with a mean of zero and standard deviation of one so the values of
the SPI are expressed in standard deviations (Edwards and McKee, 1997).
A particular precipitation total for a specified time period is then identified
with a particular SPI value consistent with probability. Positive SPI values
indicate greater than median precipitation, whereas negative values indi-
cate less than median precipitation. The magnitude of departure from zero
represents a probability of occurrence so that decisions can be made based
on this SPI value. An SPI value of less than -1.0 (moderately dry) occurs
16 times in 100 years and an SPI of less than -2.0 (extremely dry) occurs
2-3 times in 100 years.
The fundamental strength of the SPI is that it can be calculated for a
variety of time scales. This versatility allows the SPI to be used to monitor
short-term water supplies such as soil moisture, which is important for agri-
cultural production, and longer-term water resources such as ground water
supplies, streamflow, and lake and reservoir levels, which are important
for agriculture and other water users. Colorado uses the SPI information
as part of a routine climatic assessment completed by the Water Avail-
ability Task Force for Colorado's drought plan. This information is useful
for detecting the potential impacts of drought on agriculture and other
economic sectors. Determining the linkages between SPI values at differ-
ent time scales is the subject of considerable research as those involved in
monitoring drought seek to identify triggers to initiate various mitigation
actions for agriculture and other sectors.
The SPI has a number of advantages over the PDSI. First, it is a sim-
ple index and is based only on precipitation. The PDSI calculations are
complex because 68 terms are defined as part of the calculation procedure
(Soulé, 1992). In spite of the complexity of the PDSI, McKee (personal com-
munication, 1996) believes that the main driving force behind the PDSI is
precipitation. Second, the SPI is versatile. It can be calculated on any time
scale, which gives the SPI the capability to monitor conditions important
for both agricultural and hydrological applications. This versatility is also
critical for monitoring the temporal dynamics of a drought, including its
onset and termination, which has typically been a difficult task for other
indices. Third, because of the normal distribution of SPI values, the fre-
quencies of extreme and severe drought classifications for any location and
any time scale are consistent. McKee et al. (1993) suggest an SPI classifica-
tion scale (table 9.1). Fourth, because it is based only on precipitation and
not on estimated soil moisture conditions as is the case with PDSI, the SPI
is just as effective during the winter months.
Although developed for use in Colorado, the SPI can be applied to any
location with a data set of 30 years or longer. SPI maps for multiple time
scales are routinely available on the NDMC Web site ( http://drought.unl.
edu) in the “drought watch” section and on the Web site of the West-
ern Regional Climate Center (http://www.wrcc.dri.edu/spi/spi.html). The
NDMC has disseminated SPI information and software at workshops and
through direct e-mail contact with foreign governments, international or-

[124

Line
——
0.0
——
Norm
PgEn

[124