Research Publications Authored by SLIIT Staff
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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Open Access Satellite Rainfall Products for analysis of Rainfall trends for Mahaweli River Basin(SLIIT, 2022-02-11) Perera, H; Gunathilake, M. B; Rathnayakea, UThe presence of accurate and spatiotemporal data is of utmost importance in hydrological studies for river basins. However, limited ground-measured rainfall data restrict the accuracy of these analyses. Data scarcities can often be seen not only in many developing countries but also in the developed world. Therefore, much attention is given to alternative techniques to accomplish the data requirement. Precipitation data extraction from satellite precipitation products is one of the frequently used techniques in the absence of ground-measured rainfall data. The Mahaweli River Basin (MRB) is the largest river basin in Sri Lanka and it covers 1/6th of the total land area of the country. Mahaweli River is the heart of the country and the water of it is being used for many activities, including hydropower development, water supply, irrigation, etc. Therefore, analyzing rainfall trends of MRB is interesting and worthwhile for many stakeholders of the river basin. Therefore, this research investigates the suitability of Satellite Rainfall Products (SRP’s) as an alternative for Rain Gauge measured data in the MRB by performing trend analysis between the two datasets. Six precipitation products, namely PERSIANN, PERSIANNCCS, PERSIANN-CDR, GPM IMERG V06, TRMM-3B42 V7, TRMM-3B42RT V7 were extracted for 10-35 years for 14 locations of the MRB spatially distributed in the three climatic zones of the catchment. Non-parametric tests, including the Mann-Kendall test and Sen’s slope estimator tests, were used to detect the possible rainfall trends in precipitation products. Significant increasing trends were observed for both ground-measured and SRP’s in the annual scale while mixed results were observed in monthly and seasonal scales. The trends from ground-measured rainfall and SRP’s were compared and the suitability of SRP’s as an alternative technique was stated.Publication Open Access Analyzing relationships between rainfall and paddy harvest using artificial neural network (ANN) approach: case studies from North-western and North-central provinces, Sri Lanka(The Faculty of Agricultural Sciences of the Sabaragamuwa University of Sri Lanka, 2022-01-04) Ranasinghe, T; Rathnayake, U. S; Gunawardena, G; Wimalasiri, E. MPurpose: Food and agriculture are frequently affected from on-going climate change. A significant percentage of annual harvest is lost due to extreme climatic conditions in different parts of the world. Sri Lanka is considered as a country which is vulnerable to climate change. Therefore, this research presents a detailed analysis to find out the non-linear relationships between the rainfall and paddy harvest in two major provinces of Sri Lanka. Research Method: North-central and North-western provinces as two major agricultural areas were selected for the study. Rainfall trends were identified using non-parametric Mann-Kendall and Sen’s slope estimator tests. The artificial neural network (ANN) approach was used to establish non-linear relationships between rainfall and paddy yield. Findings: There was no significant (p > 0.05) linear correlation between rainfall amount and the rainfed paddy yield in tested locations. However, no clear relationship between the rainfall and rain fed yield were found in the 14 predefined functions (polynomial, logarithmic, exponential and trigonometric) derived using ANN where the calculated coefficients of determination were less than 0.3. Research Limitations: Due to lack of other climate variables such as temperatures, a significant relationship was not observed in this study. Originality/value: We have shown that non-linear artificial neural network approach can be used to study the impact of climate on agricultural production in Sri Lanka.Publication Embargo Impact of climate variability on hydropower generation: A case study from Sri Lanka(Taylor & Francis Group, 2018-06-18) Khaniya, B.; Priyantha, H. G; Baduge, N; Azamathulla, H. M; Rathnayake, U. SHydropower accounts for 16.4% of world’s electricity demand. The key element in hydropower generation is the runoff and this runoff totally depends on the precipitation. However, the future climate is predicted to be debatable and can severely affect the water resources around the world. Therefore, a critical question to answer by the research community is, what would be the impact of climate change/variability on hydropower development? Hence, this paper aims to study the impingement of climate change on hydropower generation for Denawaka Ganga mini-hydropower located in Ratnapura district, Sri Lanka. Multi-year rainfall trend analysis for 30 years along with power generation trend study for 6 years have been carried out to evaluate the performance of the hydropower station under possible shifting precipitation pattern. Mann–Kendall test and Sen’s slope estimator tests were used to culminate the trend analysis. Seasonal and monthly trend analysis did not render negative trends (except one rain gauge) in rainfall. However, positive rainfall trends were found in several rain gauging stations for several months. Power generation trend study showcased a decreasing trend in electricity generation for January and November. Nevertheless, the results elucidate that the catchment area is not under an intense threat due to the climate variability.