IRSPAS 2019
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Item 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 environmentItem Factors associated with valuation of land in Colombo district: a case study(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Mendis, B. J. R. I.; Viswakula, S. D.This study aims to identify the factors associated with the valuation of lands in Colombo District, and to build a model to predict the price of a land in Colombo District. Moreover, this study gives an insight on how land prices vary among the Divisional Secretariats of Colombo District. The data were collected through a telephone survey and stratified sampling technique was used treating the Divisional Secretariats as strata. The preliminary analysis of the data was carried out using appropriate data visualisations and statistical association tests. Water and electricity availability and value of additional resources that belongs to the land showed associations with price per perch according to preliminary analysis. Furthermore, it was concluded that the Colombo Division had the highest average price per perch while land values decreased as the divisions move away from the Colombo Division. Notably, Hanwella and Padukka Divisions reported the lowest price per perch. A generalised linear model with gamma distribution was fitted along with the forward selection method to select the main factors associated with the land price. A multiple linear regression model with ridge and lasso regularisations were also tried out in obtaining a better predictive model. The lasso regression model which selects features through shrinking coefficients to zero, resulted in the lowest mean squared error on the test set, in comparison to rest of the models fitted. Hence, the lasso regression model was selected as the best model for predicting the price of a land in Colombo district. The final model included the variables, Division to which the land belongs, Size of the land (in perches), Distance to nearest town, Distance to nearest bus halt, Water and electricity availability, Number of neighbouring lands to be sold, Level of the land, Type of the additional resource that belongs to the land, Value of the additional resource and the Type of land usage. The coefficient of determination and mean squared error of the proposed predictive model for the test set were 85.3% and 0.52 respectively