CERS - 2021

Permanent URI for this collectionhttp://192.248.9.226/handle/123/17780

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Browsing CERS - 2021 by Author "De Silva, PKC"

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    item: Conference-Abstract
    Analysis of multi-day extreme rainfall events in Kelani River basin
    (Department of Civil Engineering, University of Moratuwa, 2021-11) Chathuranga, GK; Fernando, WCDK; De Silva, PKC; Hettiarachchi, P
    Floods, one of the major disasters in Sri Lanka occur not only due to a single daily rainfall but due to multiday rainfall events. Thus, to safeguard the properties, analysis of the multiday rainfall events is more relevant than analysis of one-day rainfall events. The objective of the research is to identify the temporal rainfall pattern in the Kelani River upper catchment (using Canyon, Castlereigh, Laxapana, Norton and Hatton - Meteorological stations) for conducting rainfall frequency analysis using data from the annual maximum (AMAX) series. The preparation of the data series is done by using the Block Maxima tool and the trend pattern is identified with the Mann-Kendall test. Then selected potential candidates for frequency analysis using the L-moment method and selected the best fit distribution by using the goodness of fit test. The final outcome is to identify the Extreme rainfall values for different return periods. According to Manne Kendal test results, all series have increasing trends but they are not significant, except for Norton PX3D which has a significant increasing trend. Hatton Kotagala PX3D has a decreasing trend that is not significant. For all AMAX series skewness is positive, In the kurtosis for all AMAX series except PX2D and PX3D in the Canyon, its tails are longer and wider, and often its central peak is higher and sharper(leptokurtic). For AMAX series PX2D and PX3D in the Canyon, its tails are shorter and narrower, and often its central peak is lower and broader (platykurtic). Gamma (G), Lognormal (LN), and Weibull (EV3) were selected as potential candidates for frequency analysis. From KS test results Gamma distribution fitted to 46% of the series, while Lognormal and Weibull fitted to 27% of the series. The maximum PX1D is 440 mm in 1989 at Laxapana and for the PX2D series, the maximum value is 831 mm in 1989 at Laxapana. It was observed that the maximum PX3D is 924.7 mm in 1989 at Laxapana. The average ratio between 3-day maxima to 1-day maxima is 2.1 and the ratio of 2-day to 1-day becomes 1.9. This finding greatly helps to estimate PX2D or PX3D in the context of engineering design when there is a lack of data. It is seen that there is an increasing trend at all stations except Hatton-Kotagala PX3D. However, a significant increasing trend was detected at Norton PX3D at a 5% level of significance. For all other stations, AMAX shows no significant trends. In general, it can be argued that the Kelani River Upper catchment has an increasing trend but is not significant for annual maximum rainfall series of one day, two days and three days at a 5% level of significance. The Gamma distribution is the best-fit distribution for most of the one-day annual maximum rainfall series. However, for two-day and three-day series all three distributions - Gamma distribution, Lognormal distribution, and Weibull distribution can be considered as equal. In low return periods such as 25 years and 50 years there is no such difference in return levels. However, for larger return periods, the discrepancy is higher. The accuracy and reliability of the results can be further improved by increasing the length of records and the number of gauging stations. If four- or fiveday events are considered in the analysis, a better idea about the extreme events can be obtained and how they combined with the flooding condition. These results can be used for flood mitigation projects, for statistical estimation of probable maximum precipitation, better models of risk and damage can be developed from multi-day extreme rainfall events and flooding.
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    item: Conference-Abstract
    Investigation on wave energy characteristics in South-Western coastline of Sri Lanka
    (Department of Civil Engineering, University of Moratuwa, 2021-11) Thujanan, T; De Silva, PKC; Hettiarachchi, P
    Ocean wave power is an abundant and promising renewable energy source with limited environmental impact and high energy density. The distribution of wave energy varies spatially and temporally, attributed to bathymetric and seasonal effects. Therefore, a proper wave energy resource assessment is required in order to find optimum sites which have higher wave energy potential so that the energy produced from Wave Energy Converters (WECs) can be maximised. The aim of this study was to investigate the wave power potential around the south-western coast of Sri Lanka and its spatio-temporal and directional distribution based on 5 years (1999 to 2003) of wave data simulated using SWAN (Simulating WAves Nearshore). The results of the analysis indicated that the annual mean wave power in the region is exceeding 10 kW/m while the possible monthly mean wave power values are higher than 5 kW/m throughout the year. A significant increase in the monthly mean wave power was observed from May to September months because of the influence of the tropical south-west monsoon. Sixteen study points were selected along the nearshore and offshore around the west coast (from Colombo to Beruwala) and south-west coast (from Beruwala to Matara) for a detailed assessment and numerical modelling was done using DELFT3D for high resolution nearshore bathymetry. The calculated annual and monthly mean wave power values at the selected nearshore points showed that the south-west coast has higher potential than the west coast except near Matara area. The temporal and directional variations were also assessed at selected points using statistical indices and wave power roses, and those revealed that the region has moderately stable wave power with narrow directionality. The annual electric power output that can be extracted from three commercially available wave energy converters; Oyster, Wave Star and Wave Dragon were estimated at all nearshore points using wave scatter diagrams and publicly available power matrices. Accordingly, the nearshore area from Galle to Weligama found to be most suitable for wave energy harvesting. Further, the performance of the selected devices was evaluated based on their capacity factors, and the Oyster and Wave Star converters were found to be most suited to the prevailing wave conditions in the region.