International Research Symposium on Pure and Applied Sciences (IRSPAS)

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    GIS as a tool to find the suitable place for construction of water tanks in Karuwalabadda, Puttalam District, Sri Lanka
    (4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Vaigunthan, T.; Lansakara, L. M. A. P.; Weerasinghe, V. P. A.
    The United Nations has long been addressing the global water crisis caused by insufficient water supply to satisfy basic human needs and growing demands on the world's water resources to meet human, commercial and agricultural needs. Although there are lots of water bodies in Sri Lanka some parts of the country suffer with a severe water crisis. Karuwalabadda is a Grama Niladari Division (GND) in Puttalam district in Sri Lanka which has 135 houses and more than 245 families and there are no any surface water bodies observed in the area. The most considerable problem in that area is the lack of drinking water due to longer period of drought except 4 -5 months. Many organizations and students from different universities tried to help them as short term solutions by distributing water in bowsers and bottles. There were several drawbacks of these solutions such as water distribution coverage is changing, water distribution does not occur throughout the day, higher fuel waste for water bowsers, there is no specific route for distribution of water and plastic bottles make environmental problem etc. Hence previous solutions are not sustainable, it is proposed to construct tanks permanently in different locations of the area. The suitable locations to construct water tanks were found out using ArcGIS software for the construction of tanks with minimum environmental impacts. From the GND map of Sri Lanka, Karuwalabadda study area was extracted and digitized with houses and main roads. Buffer was done 500m away from houses and 75m away from roads and then reclassified. Land use map of Karuwalabadda was converted from vector to raster. Surface water layer was not considered because there are no any surface water body in Karuwalabadda GND. Criteria for the suitable locations were bare land, 500 m away from houses and 75 m away from main roads. The final suitable area to construct water tanks map was prepared by assigning weightage to different thematic maps as 60% to land use map, 20% to houses and 20% to roads and then they were superimposed by weighted overlay tool. Final map was classified into 03 classes as suitable, moderately suitable and not suitable area. From suitable area 07 locations were selected to construct the water tanks. It was observed that constructing seven tanks of capacity 3000 L in the selected areas the water need of the whole village can be fulfilled. Proposed number of families for one tank can be approximately 22 families. Society based maintenance can be an effective way to maintain these tanks and by handing over these tanks to Preadeshiya Sabha water can be filled once a week. GIS technology is an effective and efficient tool for solving any location based environmental problems in the world and it has more potential to be used further to overcome many environmental challenges.
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    Assessment of spatial variation of ground water quality in Colombo district, Sri Lanka
    (4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Antalyn, B.; Weerasinghe, V. P. A.
    In Sri Lanka, groundwater resources are widely used for domestic, commercial and industrial purposes and the demand for ground water is steadily increasing, particularly for urban & rural domestic water supplies, irrigated agriculture and in the industrial sector. This rapid increase in demand and lack of management is exerting considerable pressure on the available groundwater resources. Therefore, it’s vital to monitor the quality of ground water for sustainable utilization. For ground water quality assessment, Colombo district was selected as the study area since it is urbanized rapidly in last decades. The main aim of the study was assessing spatial variation of ground water quality in Colombo district in year 2018. Some of the physicochemical parameters were selected namely pH, temperature, conductivity, total dissolved solids, salinity, COD, hardness, total phosphate, nitrate-N, DO and BOD5. Sampling was carried out during the south western monsoon from June 2018 to September 2018. With the availability 03 open wells were selected randomly, from each Divisional Secretary Division (DSD) and water samples were collected during the morning hours in between 0-3 m depths as 03 replicates from each well at once. Total 39 open well samples were tested using standard methods. The obtained results are compared with proposed ambient water quality standards for inland waters in Sri Lanka by the Central Environmental Authority (CEA). The results reveal that in most of the sites pH, COD and BOD5 are not meeting the standards. Lower pH levels can occur due to natural acidification as well as anthropogenic causes linked to the industrialization, atmospheric emissions or cultivation. Results of PCA analysis reveal that the sites which are surrounded with agricultural areas such as in Hanwella, Padukka, Homagama, Kaduwela, and Kesbewa showed higher nitrate-N, total phosphate levels and low pH values. In contrast higher pH values as well as low nitrate-N and total phosphate levels were observed in non-agricultural areas. Hence come to a conclusion that long-term agricultural practices may have acidified the ground water and elevated organic matter accumulation due to high urban runoff, sewage seepage from slums and poor maintenance of wells could have caused higher COD, BOD5 levels in urbanized areas such as in Thimbirigasyaya, Moratuwa, Dehiwala, and Kotte. The study of physicochemical characteristics of this ground water samples suggests that the evaluation of water quality parameters as well as water quality management practices should be carried out to protect the water resources. Unless the use of surface area is managed in a sustainable way, it will have adverse repercussions on the environment
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    Identify a potential location for wind power plant in Jaffna district, Sri Lanka using GIS techniques
    (4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Weerasinghe, V. P. A.; Dilshara, R. M. P.; Liyanage, P. M.; Perera, G. L. D. N.
    Wind energy is one of the renewable energy sources in the Sri Lanka. Currently, there are some active wind power stations located in Central region, Hambanthota, and Puttalam. National Renewable Energy Laboratory (NREL) estimates that there are nearly 5000 km2 of windy areas with good-to-excellent wind resource potential in Sri Lanka after accounting for excluded lands like national parks, nature reserves, archaeological and cultural sites. The windy land represents about 6 % of the total land area (65,600 km2) of Sri Lanka. Hence the population increment has become a major problem on electricity demand and the hydro power is limited especially in dry season, this study is focused on finding a suitable location to establish a wind power plant in Jaffna District using Geographical Information Systems (GIS). The land was selected considering criteria namely; the distance from obstructions as 150 m, the distance from Coastal area as 100 m, the height from buildings and trees as 9 m and 1.5 acres of land area was considered as providing 2 MW of power. The land use maps were collected from Survey Department, Sri Lanka and the wind data was taken using wind finder software. Under the methodology, the wind speed data of selected points were clipped to Jaffna district map. The wind speed, land use, terrain, building area and nature reserve maps were reclassified and assigned weights using weighted overlay tool in ArcGIS software to derive the suitability map. The weights were given as wind speed (70%), land use (15%), building area (10%), nature reserves (4%) and terrain (1%). According to the results shown in the map, the wind speed was high in Delft Island and Nainatheeve and poor in Chundikulam. When considering all the criteria, Delft island (5000 ha) should be the best place and the land area of 200 ha can be used for the construction of the wind power station
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    Identification of suitable areas to cultivate Aloe vera in Kegalle District, Sri Lanka using GIS
    (4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Dissanayake, C. T. M.; Weerasinghe, V. P. A.
    Aloe vera (Aloe barbadensis Miller) is used in ayurvedic medicine, pharmaceuticals, cosmetic products and also as a food product such as drinks or mixer with yoghurt. It is getting popular with the improvements in technology of harvesting and processing the product. In Sri Lanka, it is popular as a home garden crop, but not as a crop growing in large-scale. Most Sri Lankans are less aware of getting an income from Aloe vera. Therefore, the aim of this study is to make Aloe vera cultivation popular by identifying suitable areas to cultivate Aloe vera in Kegalle district, which was the study area of this research. Data analysis was done by using ArcGIS software tools to select the suitable areas. The criteria to grow Aloe vera successfully were selected using relevant literature. They were namely land uses such as coconut or bare lands, annual rainfall range as 1800 mm-2300 mm and annual temperature range as 25 °C - 26 °C. Those criteria were considered as most favorable factors to grow Aloe vera successfully with demanding leaf thicknesses. Land use data was collected from the Survey Department, Colombo and rainfall and temperature data were collected from the Meteorology Department, Colombo. Rainfall and temperature layers were developed by using Kriging interpolation technique in spatial geostatistics in ArcGIS software. Then land use layer, rainfall layer and temperature layer were overlaid using spatial analysis tools to identify the most suitable area, moderately suitable areas and not suitable areas. Kelegama and Rambukkana DSD areas are the most suitable areas to grow Aloe vera in Kegalle district. The final map generated from this study will be useful for extension/field officers of the Department of Agriculture, to enhance the awareness of people in Kegalle district about suitable places to grow Aloe vera in order to get an extra income as well as to get the maximum utility of the land.
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    Spatio-temporal variation of surface water quality in Kalu Oya and Mudun Ela micro-catchments during rainy season
    (4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Thotagamuwa, H. T. B. N.; Weerasinghe, V. P. A.
    Kalu Oya and Mudun Ela basins are micro-catchments of the Kelani river basin mostly consisting of low-lying urbanized areas. Sri Lanka Land Reclamation and Development Corporation (SLLRDC) requires surface water quality assessment of these micro-catchments in order to prepare a wetland management strategy for the catchment. This study was aimed at assessing the surface water quality at the catchment as a preliminary study. As per the collected data on land use, catchment hydrology and wetland distribution, sampling sites were selected based on random and judgmental sampling techniques. Sampling was carried out from June to October 2018 in South-Western monsoon period. Sampling frequency was once a month. Spatially composite water samples were triplicated from each sampling point. Water samples were preserved and stored in 40C and were transported to the laboratory and analyzed using standard methods for ex-situ water quality parameters namely; Biochemical Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), Oil and grease, Nitrate and dissolved Phosphorous levels. In-situ physico-chemical parameters namely; water temperature, pH, salinity, conductivity, Total Dissolved Solids (TDS) were measured using instruments on-site using standard calibrated instruments. The mean values of data gathered from physico-chemical analysis in each sampling site at each sampling event were compared with the Proposed SLSI (general) surface water quality standards. Nitrate levels in all the sites were below the standard. Site 02 which is situated at the fish market outlet exceeded the standard levels of conductivity, TDS, salinity, phosphate, COD and BOD5 levels. Oil and grease levels in all the sites were extremely higher than the standard limits. This may be due to service stations located at the upper catchment of the area might be discharging oil and grease contaminated water to the surface area. Physico-chemical data were subjected to analysis of variance using two-way ANOVA. When the null hypothesis in the ANOVA was rejected, Tukey’s pairwise comparisons were carried out. All the water quality parameters were significantly different among ten sampling points (p<0.05) and showed spatial variation. Temperature, pH, conductivity, TDS, salinity, DO and COD levels were highly independent among sites. BOD5, oil and grease and phosphate levels showed grouping (95% confidence Interval) in the study area. All the water quality parameters were significantly different among the five months. It is recommended to repeat this study in the dry season for better conclusion.
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    A geo-spatial analysis of dengue patients and rainfall in Sri Lanka -2017
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Pathiraja, K.; Premadasa, S.; Gnanasinghe, S.; Wadasinghe, L. G. Y. J. G.; Weerasinghe, V. P. A.
    Dengue is one of the most prevalent arthropod borne virus affecting human. There are four serotypes that manifest with similar symptoms and two main vectors identified in Sri Lanka named as Aedes aegypti and Aedes albopictus. Dengue disease range from mild to dengue hemorrhagic fever. The distribution of dengue vector is varied mostly according to the rainfall. This study evaluates the relationship between percentage dengue patients in each district of Sri Lanka and monthly average rainfall distribution in 2017. Data was analyzed using ArcGIS 10.2 software. In order to get descriptive results, spatial autocorrelation (Moran’s I) was carried out. Positive Moran’s I shows that the average rainfall data are clustered according to the climatic zones in Sri Lanka and percentage dengue patients’ data for February, March, May, June, July and August months are clustered. Hot Spot Analysis was carried out for the clustered months for dengue patients. According to the Hot Spot Analysis the average rainfall distribution of each month of 2017 in Sri Lanka is restricted to specific districts; Hot spots are, Ampara (February), Rathnapura (May, June, July), Rathnapura and Kaluthara (September), Kaluthara (October) and Badulla (December) (99% confidence). Similarly, percentage dengue patients’ distribution in 2017 is restricted to specific districts; Hot spots are Trincomalee (February) and Colombo (March) (99% confidence). Ordinary Least Squares (OLS) linear regression was carried out to identify the relationship between the percentage dengue patients and monthly average rainfall. The variable distributions and relationships graphs of each month indicate a positive relationship between average rainfall and percentage dengue patients. Adjusted R2 in the diagnostic output of each month range between 0.7785 (June) and 0.1674 (February) and indicates that 16.74% - 77.85% of the variation in percentage dengue patients can be explained by average rainfall in 2017. It shows that only rainfall cannot explain the total percentage of dengue patients and that there are other environmental parameters which may contribute. There is a relationship between the percentage of dengue patients in each district and average rainfall distribution which appears to vary. Therefore, further studies should be carried out to identify other environmental parameters on the distribution of dengue such as atmospheric temperature, humidity, wind velocity, intensive farming, urbanization and solid waste disposal practices etc. Using multiple regression, multicollinearity between independent variables can be estimated using Geo statistics. Using environmental parameters, an environmental dengue index can be developed to further relate it with dengue patients’ percentage for geo-spatial analysis to develop a model for incidence of dengue in each district in Sri Lanka with varying environmental variables.
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    Spatial analysis of population density, birth rate and death rate in Sri Lanka (2015 and 2016)
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Rajapaksha, D.; Jayakody, H.; Wadasinghe, L. G. Y. J. G.; Gnanasinghe, S.; Weerasinghe, V. P. A.
    Lack of open space, shortage of clean water, and pollution are major concerns of higher population densities. In 2015, United Nations (UN) identified 17 Sustainable Development Goals (SDG) expected to fulfill by 2030 with the help of the governments of countries, which many researches reveals to lower the population growth. This study aims to analyze the distribution pattern of population density in Sri Lanka. Population density depends on resource, natural growth of population and migration. In this study, spatial pattern of population density, birth rate and death rates in Sri Lanka were analyzed for 2015 and 2016. The spatial relationships of population density with birth and death rate of 25 districts were also analyzed. The population data were collected from Department of Census and Statistics of Sri Lanka and analyzed using Geo-statistics tools in ArcGIS 10.2. Spatial patterns and relationships among the data sets were identified. Spatial Autocorrelation (Moran’s I) was carried out for population density, birth and death rate for the 25 districts. Spatial pattern of population density is highly clustered (p=0.001, Moran’s I: 0.198) while spatial pattern of birth rates of each district is randomly distributed in 2015 and 2016. High population density restricted areas are Colombo and Gampaha (99% and 90% CI) for both years. Death rates of districts are slightly clustered in 2015 (p=0.035, Moran’s I: 0.198) and 2016 (p=0.022, Moran’s I: 0.218). Hot Spot Analysis tool was used to identify the clustered areas. High death rate prevailing districts are Colombo (95% CI), Kandy and Galle (90% CI) in 2015. Low death rate prevailing district is Killinochchi (90% CI). In 2016, high death rate is observed in Colombo (99% CI) and Jaffna districts (90% CI). Spatial relationship was identified by using Ordinary Least Squares (OLS) tool. 44.25% of the population density variation can be explained by death rate (adjusted R2=0.4425) in 2015 and, 49.96% can be explained by death rate (adjusted R2=0.4996) in 2016. Regression equation can be developed according to the coefficient output (p<0.05) in 2015 and 2016. There is a significant relationship between death rate and population density (p=0.00017) in 2015 and 2016. The overall results of the present study can be used for planning development projects in the country to fulfill the SDG of UN. Colombo and Gampaha districts should have projects leading to decrease the population density. Colombo and Jaffna districts need to decrease death rates by improving their living standards with better health facilities. This study has to continue with emigration and immigration rate data to develop a better model for population density in the country.
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    Estimation of crop management factor and conservation support practice factor of RUSLE model to assess vulnerability to soil erosion in Kalu Oya and Mudun Ela basins using GIS
    (Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Lekamge, M. L. D.; Dayananda, M. D. N. R.; Weerasinghe, V. P. A.
    Soil erosion is a serious environmental problem, which emerges from intense anthropogenic activities, agricultural practices and improper land use management. River basin soil erosion assessment enables to plan, conserve and manage the watershed areas and associated ecosystems. Revised Universal Soil Loss Equation (RUSLE) model is the most widely used model to predict the long term erosion rates in an area using rainfall-runoff erosivity factor, soil erodibility factor, slope length and steepness factor, crop management factor (C factor) and conservation support practice factor (P factor). Present study has been conducted to estimate the C and P factor to assess the vulnerability to soil erosion in Kalu Oya and Mudun Ela basins located in Gampaha district, Western province, Sri Lanka. The total catchment area of Kalu Oya and Mudun Ela basins (7°7'60" N and 79°54'0" E) are about 78 km2. C and P factor of RUSLE model were estimated using land use map and 30m resolution LANDSAT 8 OLI/TIRS satellite images acquired on 17th February, 2018 to determine the vulnerability of erosion and conservation status. The C factor values for barren areas and well protected areas were assigned from 1 - 0 respectively, whereas 0 - 1 range was used for the good conservation (0) and poor conservation (1) status of the prevailing land use patterns using the field observations and literature reviews. Spatial join tool of overlay analysis was used to obtain the combined effect of C and P factors and two separate thematic maps were derived using ArcGIS 10.2.2 version to represent the spatial distribution of both C and P factors according to five classes; low, moderate, high, very high and extremely high which represent the vulnerability to soil erosion. The study identified 9.94% of the total area with 0.00 - 0.01, 80.56% with 0.01 - 0.14, 0.61% with 0.01 - 0.20, 8.03% with 0.20 - 0.63 and 1.86% with 0.63 - 1.00 of C factor and 0.01% with 0.20, 0.61% with 0.20 - 0.40, 82.57% with 0.4 - 0.5, 1.45% with 0.50 - 0.60, 15.35% with 0.60 - 1.00 P factor. Significantly higher amount of erosion vulnerability areas were observed besides the tributaries. The study identified 9.01% of the total area under low erosion (0.00 - 0.02), 79.56% under moderate erosion (0.02 - 0.14), 0.61% under high erosion (0.14 - 0.20), 8.03% under very high erosion (0.20 - 0.63) and 1.86% under extremely high erosion (0.63 - 1.00) for combined effect of C and P factor. Moderate erosion could be reduced using suitable agronomic practices. Appropriate conservation measures have to be implemented for the areas under high, very high and extremely high vulnerability to soil erosion within the Kalu Oya and Mudun Ela basins to reduce sediment transport.