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Abstract Mikunthan, T. 2007.
Modeling of rainfall: a measurable tool in sustainable agriculture. JEMREST
3:83-90. DOI: 10.4029/2007jemrest3no19 Precise prediction of rainfall
has a significant role in productive agriculture especially in dry zone of
Sri Lanka with conservation of natural groundwater. A comprehensive analysis
of rainfall data is equally important to predict, demonstrate and substantiate
agronomic results. It makes a significant contribution in planning in
agriculture at present and in future especially those areas receive lesser
rainfall. Early prediction of rainfall will definitely help to plan out the
cultivation and other related processes towards the efficient use of the
rainfall accordingly. The probability density function of gamma distribution
is used to explain the quantity of rainfall associated with each event and
the risk of long dry spills of every month and of the respective year. A two
parameter gamma distribution model was fitted to the annual rainfall pattern
of Pelwatta sugar catchment with a mean amount of 2.3 mm rainfall per rainy
day and 0.5914 of shape parameter with significant correlation (r2= 98.93)
using 15 years daily rainfall. The result of occurrence of drought incidence
for every month and year showed the ability of the model to predict incidence
of drought with high correlation of observed and predicted values. The
correlations of probability distributions were more than 99% for annual and
monthly distributions except in the month of May which had the value of
96.7%. Occurrence of drought incidence of 75% probability was less than 3
consecutive days in all months except June, July and August which have the values
of 15 days, 4 days and 4 days respectively. The results of 75% fiducial
probability model for Email info@jemrest.org for full text |
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