Abstract:
This study deals with statistical characteristics of climatic
drought which is defined as the difference between potential
evapotranspiration and rainfall. Droughts have been a matter of
serious concern to man since ancient times and even today it is
an outstanding example of man I s helplessness before nature I s
large-scale and formidable phenomena. To the meteorologist,
rought is a rainless situation for an extended period of time
uring which some precipitation should have been normally
received depending upon the geographical location of the region
and season of the year. To the agriculturist, climatic or
agricultural drought is a shortage of moisture availability for
crops.
Analysis begins with calculation of daily drought values. Then
10-day yearly drought maxima is calculated for the period of
_eeard obtained for five meteorological stations in the Teesta
Barrage Project area. The reason for choosing lO-day interval is
that irrigation requirement is usually calculated on lO-day
basis. Extreme Value Type 1 (EVl) distribution is to fitted to
IO-day drought maxima for each station and goodness-of-fit is
judge by visual inspection of probability of plots on extreme
value paper. Overall, EVI distribution seems to fit the drought
data reasonably well. Frequency relationships have also been
presented and using these relationships the magnitude of IO-day
d}:ough can be calculated for a given return period. Method of
calculating irrigation requirement using these drought values has
so been illustrated. The analysis of drought was performed both
i
for growing season of T.Aman (July 15 to November 15) and for the
cri.tical growing period of the same crop (October 15 to November
15) .
Another important parameter in the description of climatic
drought is the dry spells or sequences of dry or non-rainy day
and wet or rainy days. So the next part of the analysis deals
wi th frequency of wet- and dry-day sequences having rainfall
greater than or equal to and less than specified threshold
rainfall val ues, respectively. Threshold rainfall values for this
study were chosen as 6.0 mm, 3.0 mm and 1.0 mm for each station.
For each year the consecutive dry- and wet-day sequences having
maximum length(days) was selected. This yielded one dry-day and
one wet-day sequence in each year. Results obtained show that the
yearly maximum length of consecutive wet-day and dry-day
sequences can be approximated by normal distribution.
-
Finally seasonal distribution of dry-day sequences has been
studied. First average length of consecutive dry-day sequences
for each month over the entire period of record was calculated
for each threshold and plotted against respective months as a
line graph. The largest dry-day sequences occur in January,
February and March and again in october, November and December.
The frequency of dry-day sequences having length greater than or
equal t.O 25 days was also calculated for each month for the
peri,d record for each threshold. Largest frequency of such
sequences was found to occur in January through March and again
in October through December.
