| dc.description.abstract | Probable Maximum Precipitation (PMP)
estimates are essential when designing hydraulic
structures, especially since the risk of the failure of such
structures is high. The impact on climate change with PMP
has been crucial at present although the concept does not
incorporate climate change. Although there are two widely
used methods to estimate PMP, this research focused on the
statistical method, covering 16 stations of the Kelani River
catchment. The daily precipitation records for 57 years
were collected, and the annual maximum daily rainfall
series was prepared for all 16 stations. The study was
conducted using five scenarios (S1- S5). The results from
Hershfield PMP (S1) emphasize that the Hershfield
enveloping curve has a very high value of frequency factor
(K) in low annual average maximum daily precipitation.
Thus, the need to modify the curve has arisen as a major
objective of this research. As a result, Modified Hershfield
PMP (S2) and Modified PMP in the context of Sri Lanka
(S3) are considered. Outlier detection (S4) manifests that,
there may be one or more or devoid of outliers deviating
from the original concepts of Hershfield. Split sampling
(S5) concludes that Standard Deviation (SD) is the most
influential factor for PMP, which shows the effect of climate
change. PMP maps are developed to observe the spatial temporal variation of PMP, which is the first version in the
context of Sri Lanka. | en_US |
