Abstract:
Variations in climatic patterns are known to influence the availability and sustainability of
water resources in Sri Lanka, thereby influencing the agriculture based livelihoods and
economy. Hence, due attention is required to be paid on the variations of climate patterns,
while focusing on the changes in rainfall patterns that directly denote the changes in climate.
Standardized Precipitation Index (SPI) remains as one of the widely used approaches in
evaluation and prediction of variations in rainfall patterns, due to its simplicity and
effectiveness. Periodic variations of such climate extremes in Batticaloa (DL2b agroecological
zone) were studied, to evaluate the trends and severity of climate extremes using
the Standardized Precipitation Index (SPI). Monthly cumulative rainfall data from January,
1900 to December, 2014 of the Batticaloa rain gauging station were used in this study. The
collected monthly accumulated rainfalls were arranged into two major time periods, ranging
from 1900-1956 (past years) and 1957-2014 (recent years) to be used as the input to the SPI
calculation in Mat Lab R2007b (version 7.5). The identified events (both wet and dry) were
ranked into five classes based on the magnitude (severity) of each event as normal, mild,
moderate, severe and extreme. The variations in rainfall patterns (with respect to SPI) were
evaluated by using the Paired Chi-Square test. The dry events of Batticaloa in the recent
years (1957-2014) indicate a significant reduction of the severity of drought events (p<0.05
at 95% level of confidence), as the occurrence frequency of extreme and severe droughts
decrease with increments in mild and moderate drought events. On the other hand wet
events indicate notable increments in mild, moderate, severe and extreme wet events within
the recent years, which is not significant in terms of Paired Chi-square statistics (p>0.05).
Hence, a significant reduction of the dryness along with a notable increment in wetness, in
terms of severity and frequency of occurrence, could be predicted for Batticaloa, in
accordance with results of SPI.
