Environmental and social impact of a mini-hydropower plant based on Sudu Ganga in Sri Lanka

Survey was carried out to identify human attitudes on micro-sleepiness and preventive measures with a view to develop a food product to combat micro-sleepiness. Statistical data pertaining to road accidents were collected from, Sri Lanka Police Traffic Division and were statistically analyzed to identify the social impact. Results revealed that peak level of road accidents is observed at 14.00 -20.00h (38.2%)[1] and intencity of micro-sleepiness falls at the same time period (37.36%) while14.00 to 16.00h is the peak time,16.00 to 18.00h is the least; again 18.00 to 20.00h it reappears slightly. Peak hours of micro-sleepiness occurs at 14.00- 20.00h and it was also validated by the statistics from Sri Lanka police during last ten years. Even though respondents of the survey expressed that peak hours of micro-sleepiness is 14.00-16.00h, according to police reports, peak hours fall in between 18.00-20.00h. Reason for this disparity is due to stressful condition of the drivers, traffic jams, mental stress, rushing to attend urgent matters and bad light. Out of the interviewees, 69.27% strongly wanted to avoide micro-sleepiness and intend to spend LKR 10-20 on a commercial product to combat micro-sleepiness. As age old practices to supress micro-sleepiness are time taken, modern day respondents (51.64%) like to have a quick solution through a drink. Moreover, 46.94% respondents proposed a product developed from plant based materials and 94.5% expressed formulation of a product is of nationally importance. Survey further disclosed that about, 76.84%, 96.39% and 80.93% taking heavy diets for their breakfirst, lunch and dinner respectively. Therefore, food habits of morning and noon may cause for micro-sleepiness while dinner may cause for both, natural and micro-sleepiness due to heavy glicemic load of food[2].According to the study micro-sleepiness can be catogorized in to three zones such as low-risk zone(08.00-10.00h and 18.00-20.00h), managable zone(10.00-12.00h), and high-risk zone(14.00-16.00h).

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Projection of Future Hydropower Generation in Samanalawewa Power Plant, Sri Lanka

Mathematical Problems in Engineering ◽

10.1155/2020/8862067 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Bhabishya Khaniya ◽

Chamaka Karunanayake ◽

Miyuru B. Gunathilake ◽

Upaka Rathnayake

Keyword(s):

Power Generation ◽

Sri Lanka ◽

Climate Models ◽

Regional Climate ◽

Local Area ◽

Hydropower Plant ◽

Ann Model ◽

Hydropower Generation ◽

The Future ◽

The Impact

The projection of future hydropower generation is extremely important for the sustainable development of any country, which utilizes hydropower as one of the major sources of energy to plan the country’s power management system. Hydropower generation, on the other hand, is mostly dependent on the weather and climate dynamics of the local area. In this paper, we aim to study the impact of climate change on the future performance of the Samanalawewa hydropower plant located in Sri Lanka using artificial neural networks (ANNs). ANNs are one of the most effective machine learning tools for examining nonlinear relationships between the variables to understand complex hydrological processes. Validated ANN model is used to project the future power generation from 2020 to 2050 using future projected rainfall data extracted from regional climate models. Results showcased that the forecasted hydropower would increase in significant percentages (7.29% and 10.22%) for the two tested climatic scenarios (RCP4.5 and RCP8.5). Therefore, this analysis showcases the capability of ANN in projecting nonstationary patterns of power generation from hydropower plants. The projected results are of utmost importance to stakeholders to manage reservoir operations while maximizing the productivity of the impounded water and thus, maximizing economic growth as well as social benefits.

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Impacts of streamflow alteration on benthic macroinvertebrates by mini-hydro diversion in Sri Lanka

Scientific Reports ◽

10.1038/s41598-020-79576-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Dinuke S. N. Munasinghe ◽

Mohamed M. M. Najim ◽

Silvia Quadroni ◽

Muneeb M. Musthafa

Keyword(s):

Sri Lanka ◽

Benthic Macroinvertebrates ◽

Volume Flow Rate ◽

Water Diversion ◽

Hydropower Plant ◽

Macroinvertebrate Communities ◽

Hydrologic Alteration ◽

Wet Season ◽

Small Hydropower ◽

Study Sites

AbstractOur study focused on quantifying the alterations of streamflow at a weir site due to the construction of a mini-hydropower plant in the Gurugoda Oya (Sri Lanka), and evaluating the spatial responses of benthic macroinvertebrates to altered flow regime. The HEC–HMS 3.5 model was applied to the Gurugoda Oya sub-catchment to generate streamflows for the time period 1991–2013. Pre-weir flows were compared to post-weir flows with 32 Indicators of Hydrologic Alteration using the range of variability approach (RVA). Concurrently, six study sites were established upstream and downstream of the weir, and benthic macroinvertebrates were sampled monthly from May to November 2013 (during the wet season). The key water physico-chemical parameters were also determined. RVA analysis showed that environmental flow was not maintained below the weir. The mean rate of non-attainment was ~ 45% suggesting a moderate level of hydrologic alteration. Benthic macroinvertebrate communities significantly differed between the study sites located above and below the weir, with a richness reduction due to water diversion. The spatial distribution of zoobenthic fauna was governed by water depth, dissolved oxygen content and volume flow rate. Our work provides first evidence on the effects of small hydropower on river ecosystem in a largely understudied region. Studies like this are important to setting-up adequate e-flows.

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slm is Dead, Long Live Sri Lanka Malay

Journal of Language Contact ◽

10.1163/19552629-00702006 ◽

2014 ◽

Vol 7 (2) ◽

pp. 381-391 ◽

Cited By ~ 1

Author(s):

Umberto Ansaldo

Keyword(s):

Sri Lanka ◽

Social Impact ◽

Genetic Evidence ◽

Theory Method ◽

Speech Community ◽

Scientific Interest ◽

Scientific Curiosity

This paper discusses the results of scholarship on Sri Lanka Malay based on the studies presented in Nordhoff 2013 in terms of theory, method, and social impact. It touches on a variety of topics including the significance of recent genetic evidence for old theories of language genesis, as well as the efforts for revitalization sparked by the scientific interest in the speech community. In evaluating this collection of variable significance, the author reflects on the transition of ownership of Sri Lanka Malay: from object of scientific curiosity to ancestral language of communal value.

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Regression-Based Prediction of Power Generation at Samanalawewa Hydropower Plant in Sri Lanka Using Machine Learning

Mathematical Problems in Engineering ◽

10.1155/2021/4913824 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Piyal Ekanayake ◽

Lasini Wickramasinghe ◽

J. M. Jeevani W. Jayasinghe ◽

Upaka Rathnayake

Keyword(s):

Machine Learning ◽

Power Generation ◽

Sri Lanka ◽

Correlation Coefficient ◽

Prediction Models ◽

Accurate Prediction ◽

Hydropower Plant ◽

Maximum Temperature ◽

Support Vector ◽

Major Power

This paper presents the development of models for the prediction of power generation at the Samanalawewa hydropower plant, which is one of the major power stations in Sri Lanka. Four regression-based machine learning and statistical techniques were applied to develop the prediction models. Rainfall data at six locations in the catchment area of the Samanalawewa reservoir from 1993 to 2019 were used as the main input variables. The minimum and maximum temperature and evaporation at the reservoir site were also incorporated. The collinearities between the variables were investigated in terms of Pearson’s and Spearman’s correlation coefficients. It was found that rainfall at one location is less impactful on power generation, while that at other locations are highly correlated with each other. Prediction models based on monthly and quarterly data were developed, and their performance was evaluated in terms of the correlation coefficient (R), mean absolute percentage error (MAPE), ratio of the root mean square error (RMSE) to the standard deviation of measured data (RSR), BIAS, and the Nash number. Of the Gaussian process regression (GPR), support vector regression (SVR), multiple linear regression (MLR), and power regression (PR), the machine learning techniques (GPR and SVR) produced the comparably accurate prediction models. Being the most accurate prediction model, the GPR produced the best correlation coefficient closer to 1 with a very less error. This model could be used in predicting the hydropower generation at the Samanalawewa power station using the rainfall forecast.

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Social Impact of SMS in Sri Lanka

2008 4th International Conference on Information and Automation for Sustainability ◽

10.1109/iciafs.2008.4783951 ◽

2008 ◽

Author(s):

Sumudu Wijetunge ◽

Pushpika Wijesinghe ◽

Upul Gunawardana

Keyword(s):

Sri Lanka ◽

Social Impact

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First record of cyanobacteria species: Cephalothrix komarekiana, from tropical Asia

Environmental Engineering Research ◽

10.4491/eer.2020.040 ◽

2020 ◽

Vol 26 (2) ◽

pp. 200040-0

Author(s):

Md. Fuad Hossain ◽

R.W.T.M.R.T.K Bowange ◽

K.L.W. Kumara ◽

D.N. Magana-Arachchi ◽

R.R. Ratnayake

Keyword(s):

Sri Lanka ◽

Social Impact ◽

Value Added ◽

First Record ◽

South American ◽

Tropical Asia ◽

Freshwater Bodies ◽

Westiellopsis Prolifica ◽

The Tropics ◽

First Time

Cyanobacteria play an important ecological role in every ecosystem with hidden economic and social impact. Among tropical countries, Sri Lanka holds a rich biodiversity with remarkable cyanobacterial diversity. The major objective of this study was to investigate the diversity of culturable cyanobacteria from freshwater bodies of Sri Lanka, with a phylogenetic perspective. Molecular characterization followed by phylogenetic evaluations allowed identification of new species with value added potential and revealed deeper taxonomic resolutions. A total of 74 monocultures were obtained. Rare isolates; Alkalinema pantanalense (U4), Geitlerinema sp. (U36) and Westiellopsis prolifica (U58) were also among them. Novel species Cephalothrix komarekiana was identified for the first time in Sri Lanka. This species was first reported from South American continent (Brazil and Amazonian rivers in 2015 and 2017 respectively) and Korea in 2018. The present study is next in line reporting the species first time from the tropical Asia. Higher value added potential and easy culturing of C. komarekiana suggest its economical applicability in many industries. Overall, this study provides insight on diversity, ecological distribution and industrial applicability of culturable cyanobacteria from the tropics with special reference to C. komarekiana reported from Sri Lanka.

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