Title of the Study:      Impact of Climate Change on Coconut Production in

LCWIR and LCWR Regions of Sri Lanka

 

Investigator(s):          T.S.G. Peiris

 

 

Scientific background and scope/objectives of the study:

 

Coconut is important to Sri Lanka both as a food crop and as an industrial crop. The annual coconut production fluctuated mainly due to climate variability and the type of management. Previous studies on crop-weather interactions confirmed the importance of studying the effect of climate change on coconut (Peiris et. al., 2000; Peiris and Thattil, 1998; Peiris et. al., 1995; Abeywardena, 1983). Further, previous studies have been confined to a given location or the effect of rainfall alone on the coconut production. The effect of climate change on coconut production is immensely useful to study the impact assessment and adaptation of climate change on national coconut production. The objective of this project is to identify the climate change with respect to rainfall, maximum and minimum temperature and relative humidity (a.m. and p.m.) in coconut growing areas of low country wet intermediate region (LCWIR) and low country wet region (LCWR) and their effects on coconut production in each region.

 

Experimental Method:

 

Five climate variables, rainfall (RF) in mm, minimum air temperature (TMIN) in deg. C, maximum air temperature (TMAX) in deg. C, relative humidity in the afternoon (RHPM) during the period 1976-2000 in LCWIR and LCWR are analyzed to study the climate change in the two regions using multivariate approach. Having identified the important variables to explain the climate change in each region, crop-weather models are developed separately for each region.

 

Results Obtained:

 

No long term trend was found in annual rainfall in LCWIR and LCWR. The long term annual means of RHAM and TMAX is higher in LCWIR than in LCWR while that of RHPM and TMIN is lower in LCWIR than in LCWR. There is a significant correlation in maximum daily temperature between LCWR and LCWIR (r=0.77 p<0.001) and in annual rainfall between LCWR and LCWIR (r=0.57, p<0.003). The variability of each climate parameter is higher in LCWR than the corresponding value in LCWIR.

 

Rainfall alone is not sufficient o explain the climate change in each region. The climatic indicators were developed separately for both regions to explain the respective climate variability. The indicator identified using monthly climate values for LCWIR is,

0.4*RF + 0.5*RHPM – 0.4*TMAX (I1LCWIR, say).

The indicators for LCWR are,

0.4*(RF-TMAX) + 0.5*RHAM (I1LCWR, say) and 0.6 * (RHPM-TMIN)  (I2LCWR, say).

 

The correlation between the yield and some monthly values of the indices are significant. The influence of climate on coconut yield is different for the two regions. Therefore, the assessment of impacts and adaptation to climate change in coconut has to be carried out separately for each coconut growing regions. The models developed using climate indices for both regions explain about 75% of the variability of the annual coconut production in the respective regions. These models can be used to estimate the yield in those two regions one year ahead. However, these models have to be further developed to study the impact assessment and adaptation to climate change on coconut production.

 

Conclusions:

 

Inter-annual and inter-month variability of the five selected climate variables (rainfall, maximum temperature, minimum temperature, relative humidity morning, relative humidity afternoon) in LCWIR is higher than that in LCWR. The reason for this have to be investigated. During the decade 1990s the period 1997/98 is the warmest period in LCWIR and LCWR in Sri Lanka as for global instrumental record. The night time daily temperature increases at a rate of 0.02 and 0.09 deg. C per year in LCWR and LCWIR respectively. Rainfall alone is not sufficient to explain the climate change over time. The indices developed separately LCWIR and LCWR can be used as proxy indicators to study the assessment and adaptation to climate change on coconut. As those indices depend on the level of temporal aggregation, it is important to continue this study to identify the correct level of aggregation for climate change studies. The use of daily data is desirable to avoid the aggregation effect on temporal scale. There is strong association between the yield and some of the monthly indices. The models developed using climate indices I1LCWIR for LCWIR and using I1LCWR and I2LCWR for LCWR can be used to estimate the yield for one year ahead. However, the model have to be further developed to study the impact of climate change on coconut production for the next decade.

 

References:

 

Abeywardena, V. 1983. Effect of moisture stress and irrigation on yield of coconut in Sri Lanka. IN Coconut Research and Development. Ed. N.M. Nayar. Willey Eastern, New Delhi. P 98-106.

 

Peiris, T.S.G. and Thattil, R.O. 1998. The study of climate effects on the nut yield of coconut using parsimonious models. Experimental Agriculture. 34. 189-206.

 

Peiris, T.S.G., Thatitil, R.O. and Mahindapala, R. 1995. An analysis of the effect of climate and weather on coconut. Experimental Agriculture. 31. 451-460.

 

Peiris, T.S.G., Peiris, T.S.U. and Rajapksha, S. 2000. Prediction of annual national coconut production – a stochastic approach. Journal of Apld. Statistics in Sri Lanka. 1. 25-32.

 

 

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