RESEARCH POSTER PRESENTATION DESIGN © 2015 www.PosterPresentations.com ‘Ceylon tea’ industry plays a vital role in relation to the economic sustainability in Sri Lanka. Low productivity of tea growing areas in the country has been attributed to climatic changes, ageing of tea fields, low replanting rate, land degradation, worker shortage and high input cost. Climatic variability has direct and indirect impacts on tea production in Sri Lanka. Tea crop is highly sensitive for water adequacy and affect for plant growth and development. Optimum rainfall required for tea varied from 350 ± 20 mm/month in Up Country Wet Zone.(Amarathunga et al,2007) Photosynthesis rate is decreased by 50%, when water is reduced by 10%. Lack of sunshine at high rainfall is affected for the low yield. High rainfall is reduced the shoot growth of the tea plant due to water logging condition of the soil. Tea plants are very sensitive for monthly rainfall variations. Amount of rainfall in previous month was affected to productivity of crop on next month. Climatic variations is a critical factor for yield variability of upcountry tea industry. Kelani Valley Plantations PLC(KVPL) is one of leading plantation company in Sri Lanka. KVPL Upcountry tea saturated 8 estates in Hatton Region and 6 estates in Nuwaraeliya Region. Introduction To identify impact of rainfall variation on productivity of upcountry tea lands managed by Kelani Valley Plantations PLC in Sri Lanka Objective Results and Discussion Conclusion Vagaries in climate is a critical factor for yield variability of the upcountry tea industry. Maintaining good agricultural practices (GAP) and choosing tea cultivars more adaptable to varying climatic condition will mitigate the effects of climatic variation on productivity of tea lands. References Liu, C. L., Zhang, Q., Singh, V.P and Cui, Y.(2011). Copula-based evaluations of drought variations in Guangdong, South China. Natural Hazards, 59, 1533-1546 Poudel, S., and Shaw, R., (2016) Relationships between Climate Variability and Crop Yield in a Mountainous Environment : A Case study in Lamjung District, Nepal. Climate. 4,13 Preprah, K., (2014) Rainfall and Temperature Correlation with Crop Yield: The Case of Asunafo Forest, Ghana. International Journal of Science and Research (IJSR), 3, 784-789 Wijeratne, M.A., Anandacoomaraswamy, a., Amarathunga, M.KS.L.D., Rathnasiri, J., Basnayake B.R.S.B., Kalva, N.,(2017) Assessement of impact of climatic change on productivity of tea(Camelia Sinenssis L.) plantations in Sri Lanka. Journal National Science foundation Sri Lanka. 35(2), 119-126 Acknowledgement I wish to offer my deepest gratitude to Dr. Prasad Dharmasena, Director of NIPM, Mr. Roshan Rajadurai, Managing Director of Kelani Valley Plantations PLC, Mr. Maruday Kandasamy, Chief Clerk of General Manger Office, Mrs. Niluka Amerasena and Ms. B.N Gayathri, Staff Members of General Mangers’office. Manawasinghe, K.S. 1 , Abeysinghe, D.C. 1 , Weerakoon, A. 2 , Thennakoon, T.M.N.S. 3 Department of Plantation Management, Faculty of Agriculture and Plantation Management, Wayamba University of Sri Lanka, Makandura, Gonawila (NWP), 60170, Sri Lanka 1 Kelani Valley Plantations PLC, Dickoya, Hatton 2 Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka 3 Effects of Climatic Variation on Yield of Upcountry Tea: A Case Study based on Upcountry Tea Estates of Kelani Valley Plantations PLC in Sri Lanka Methodology Study Site The Study was conducted in upcountry tea estates in Kelani Valley Plantations PLC. Tea estates data of rainfall and yield from 2004 to 2015 was used. Selected Indicators for the Study Pearsons’ Correlation Coefficient Pearson’s Correlation Coefficient was used to determine the correlation between the rainfall and the tea yield. (Poudel et al, 2016) Where, n = Number of Pairs of Scores Ʃxy = Sum of the products of paired scores Ʃx = Sum of x scores Ʃy = Sum of y scores Ʃx = Sum of squared x scores Ʃy = Sum of squared y scores Methodology Cont. Standard Precipitation Index Standard Precipitation index was used to identify Climatic condition within a year in the regions(Table 1) (Liu et al.2011). Where, X 1 – rainfall X - mean value S - Standard deviation Table 1 :- SPI values and Climatic events Precipitation Trend Total annual rainfall was recorded the mean of 3044 mm in Hatton Region and 2606 mm in Nuwaraeliya Region, Standard deviation of 455mm in Hatton Region and 322mm in Nuwaraeliya Region. It reveals an ascending trend lines of annual rainfall from 2004 to 2015 in both regions, However the trend line in Nuwraeliya region indicates slightly increasing.(Figure 1) Figure 1:- Annual Precipitation trends in KVPL upcountry estates in Hatton and Nuwaraeliya regions from 2004 to 2015 The maximum rainfall was recorded in month of June and the minimum rainfall was recorded in month of January (Figure 2). Standard deviation 121mm in Nuwaraeliya region and 129mm in Hatton region. Standardized Precipitation Index Table 2 :- Variations of Climatic conditions across tea growing areas in Upcountry KVPL estates FOE – Frequency of events, POC – Percentage of Occurrence Monthly rainfall was highly fluctuated within the year. There were not any extremely dry or severely dry months both Hatton and Nuwaeaeliya tea growing regions. extremely wet month was recorded in Hatton region and Severely wet month was recorded in Nuwaraeliya region (Table 2). Rainfall- Crop Yield Relationship Pearsons’ Correlation Coefficient There was weak Positive correlation between annual rainfall and yield, in Hatton Region (r = +0.12 ) and Nuwaraeliya Region ( r = +0.15). Strong positive correlation is shown between previous month rainfall and following month yield, in Hatton Region ( r= +0.62) and Nuwaraeliya Region(+0.70). Tea plants are very sensitive for monthly rainfall variation. Climatic events Hatton Region Nuwaraeliya Region FOE POC (%) FOE POC (%) Extremely Wet 1 8.33 - - Severely Wet - - 1 8.33 Moderately Wet - - 1 8.33 Mild Wet 1 8.33 4 33.33 Normal Wet 3 24.99 - - Normal Dry 4 33.33 2 16.66 Mild Dry 1 8.33 1 8.33 Moderately Dry 2 16.66 3 24.99 Severely Dry - - - - Extremely Dry - - - - y = 15.655x + 2504.1 R² = 0.0307 y = 82.461x + 2508.7 R² = 0.4258 0 500 1000 1500 2000 2500 3000 3500 4000 4500 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Nuwaraeliya Hatton Linear (Nuwaraeliya) Linear (Hatton) 0.00 100.00 200.00 300.00 400.00 500.00 600.00 700.00 Nuwaraeliya Hatton Figure 2 :- Monthly Precipitation trends in KVPL upcountry estates in Hatton and Nuwaraeliya regions from 2013 to 2015 SPI Value Category 2.0+ Extremely Wet 1.5 to 1.99 Severely Wet 1.0 to 1.49 Moderately Wet 0.5 to 0.99 Mild Wet 0 to 0.49 Normal wet -0.1 to -0.49 Normal dry -0.5 to -0.99 Mild dry -1.0 to -1.49 Moderately dry -1.5 to -1.99 Severely dry -2.0+ Extremely dry SPI = X 1 –X S