In this study, the El Nino Southern Oscillation (ENSO) phase index is used for water management over the Kotmale reservoir in Sri Lanka. Daily rainfall data of 9 stations over the Kotmale catchment during 1960–2005 June-September (JJAS) season is investigated over the Kotmale catchment. The ENSO phases are identified based on the 0.5°C sea surface temperature (SST) anomaly over Nino 3 region. The study has brought out few stations showing increasing and a few decreasing seasonal rainfall trends for JJAS season, while there is no change in the annual rainfall for the catchment. Monthly and seasonal rainfall of all the selected stations showed negative correlation with the sea surface temperature (SST) over the Nino-3 region index during JJAS season with varying magnitudes. During the warm phase of ENSO, below average rainfall is prominent for JJAS season over many stations. The rainfall especially during early September showed a significant below average rainfall during the warm ENSO phase. The seasonal rainfall during neutral and cold ENSO phases does not experience similar significant changes as seen during warm ENSO phase. Inflow of the Kotmale reservoir shows decreasing trend for the period of 1960–2005 in the observation from all stations collectively.
Climate change and variability have considerable attention from the scientific community in the recent decades and numerous studies on this topic have led to a better understanding of various climate phenomena and their driving mechanisms. The term teleconnection refers to large and persistent ocean-atmospheric anomaly patterns
The ENSO phenomenon is one of the primary modes of seasonal climate variabilities, particularly in the tropics [
The rainfall of Sri Lanka and India becomes weak during El Nino episodes in the boreal summer due to large-scale subsidence over the Central Indian Ocean region and enhanced from October to December [
Here we investigate the viability of using ENSO index for the reservoir water management over the Kotmale reservoir in Sri Lanka as a case study. Kotmale reservoir is one of the multipurpose reservoirs created for irrigation, drinking, and hydropower generation of 445 Giga-watt hour/year [
Location of the Kotmale reservoir in Sri Lanka. Source: Food and Agriculture Organization of the United Nation [
However the original volume of 176.78 million cubic meters (Maximum capacity) has an average annual loss of 0.23% due to the formation of sediments [
Contribution of rainfall during JJAS season to annual rainfall for the stations.
Daily rainfall data of 11 meteorological stations are used in this study (Table
Rainfall stations used for the study and duration of the data.
Duration of available data | Station name |
---|---|
1900–1961 (62 years) | Nuwara Eliya |
1961–1974 (14 years) | Hope–estate |
1961–1989 (29 years) | Oonagalla–estate |
1961–1996 (36 years) | Watawala |
1961–2000 (40 years) | Ambewela, Holmwood–estate |
1961–2005 (45 years) | Annfield, Campion, Helboda–north, Labukele–estate, Sandringham |
Inflow data of Kotmale reservoir for the duration from 1984 to 2012 is also collected from Mahaweli Authority of Sri Lanka (MASL). MASL calculates the inflow to the Kotmale reservoir by applying the following method. Water volume of the reservoir is calculated using the remaining water level of the reservoir from its original capacity, after sustaining the removals for hydropower generation. Using contour gridding of the reservoir, the inflow is back-calculated from the remaining water level.
The sea surface temperature (SST) values are extracted from the Japan Meteorological Agency website. Data are available at
Mean SST values are correlated with the mean monthly rainfall values for each station for JJAS season. Nuwara Eliya station is eliminated from the SST analysis, because only the rest of the 9 stations have data between 1960 and 2005. This analysis is done to find whether there is a relationship between SST and the selected rainfall stations. Pentad daily rainfall data are also created for each ENSO phase. Finally, the rainfall anomalies of each station are examined for different ENSO phases to understand the variability of rainfall over the catchment area.
Among the 11 station datasets, almost all the data contained precipitation anomalies in the range of −0.5 to 0.5 mm/day. All stations show a similar precipitation anomaly and root mean square error (RMSE), except for Ambewela and Nuwara Eliya. Ambewela and Nuwara Eliya stations show significant deviation in anomalies during 1994 and 1924 to 1927. All the stations exhibit a tendency of having low variance and the absence of extreme outliers.
However, Hope Estate station exhibits a significant lower value of correlation with other 10 stations. Furthermore, Hope station does not show significant correlation between the JJAS seasonal rainfall of the Annfiled and Oonagalla stations,
According to the data, results show that the rainfall during JJAS season is responsible for 30 to 55% of annual rainfall of the study region (stations put together) or the catchment area (i.e., Campion station, 30.9% and Watawala station, 55.3%). Figure
We identified four distinct rainfall trends (i.e., significant increasing rainfall trend, insignificant increasing rainfall trend, significant decreasing rainfall trend, and insignificant decreasing rainfall trend) (Figure
Holmwood and Labukelle–estate stations show decreasing rainfall trends (a) and Watawala and Helboda–north stations show increasing rainfall trends (b).
Furthermore Chandrasekara and Prasanna [
For each station, the JJAS seasonal rainfall shows negative correlation with mean SST over Nino–3 region (Figure
Correlation between mean SST (Nino–3 region) and JJAS mean rainfall for 9 stations.
Table
List of years for different ENSO phases during JJAS season from 1960 to 2005.
Description | Years | Total number of years |
---|---|---|
Warm ENSO phase | 1963, 1965, 1972, 1976, 1982, 1983, 1987, 1991, 1997 and 2002 | 10 years |
|
||
Cold ENSO phase | 1961, 1964, 1967, 1970, 1971, 1973, 1975, 1978, 1984, 1985, 1988 and 1999 | 12 years |
|
||
Neutral ENSO phase | 1960, 1962, 1966, 1968, 1969, 1974, 1977, 1979, 1980, 1981, 1986, 1989, 1990, 1992, 1993, 1994, 1995, 1996, 1998, 2000, 2001, 2003, 2004 and 2005 | 24 years |
SST anomalies over Nino–3 region for JJAS season from 1960 to 2010.
For all the stations, average pentad rainfall for JJAS season during neutral ENSO phase showed similar pattern as average daily rainfall. Furthermore, all the stations showed significant above average pentad rainfall during mid-June (39th pentad). However, Ambewela station showed significant above average pentad rainfall not only during mid-June (39th pentad), but also at the end of July (48th pentad) and beginning of September (55th pentad) compared to average pentad rainfall for JJAS season (Figure
Pentad (five-day mean) rainfall changes in Ambewela station for JJAS season.
Labukelle–estate, Holmwood–estate, Campion, Annfield, and Watawala stations observed above average seasonal rainfall during JJAS season for neutral ENSO phase. Sandringham and Helboda–north stations showed more frequent below average seasonal rainfall events than the above average seasonal rainfall during neutral ENSO phase for JJAS season. Ambewela and Oonagalla–estate showed equal chance of having above average seasonal rainfall and below average seasonal rainfall for neutral ENSO phase.
For all the stations, average pentad from daily rainfall for JJAS season during warm ENSO phase showed similar pattern, but with lower rainfall than average pentad rainfall. However, during mid-June (33rd pentad), early July (37th pentad), and early September (43rd pentad) was shown significant below average pentad rainfall compared to the mean pentad rainfall for the JJAS season (Figure
Pentad (from daily data) rainfall changes in Helboda–north station for JJAS season.
Sumathipala [
Ambewela, Helboda–north, Labukelle–estate, and Oonagalla–estate stations showed below average rainfall on every warm ENSO phase (Table
Furthermore, Principal Component Analysis (PCA) showed that during warm ENSO phase more or less than 96% of variance is explained from first principal component of the rainfall (Figure
Principal components and their explained variances for the ENSO phases.
Zubair [
The averaged pentad data from daily rainfall of JJAS season during cold ENSO phase depicts a similar pattern, as averaged pentad data from the daily rainfall shows a significant above average pentad rainfall during end of June (41st pentad) and mid-August (51st pentad) (Figure
Pentad (from daily data) rainfall changes in Watawala station for JJAS season.
All the stations experienced below average seasonal rainfall during 1970 cold ENSO phase. Except for Labukelle–estate and Ambewela stations, the rest of the study stations showed above average seasonal rainfall during 1988 cold ENSO phase.
However, all the study stations have shown more or less equal chances of having both the above average and below average seasonal rainfall for cold ENSO phase in JJAS season (i.e., 50%:50% chance). Holmwood–estate, Oonagalla–estate, Annfield, and Helboda–north stations showed frequent above average seasonal rainfall during cold ENSO phase in JJAS season. However, Zubair [
During June to November inflow from Kotmale reservoir is higher than the remaining months of the year (Figure
Daily mean inflow (MCM) (a) and annual change of the inflow (b) for Kotmale reservoir, Sri Lanka.
September is the month when the main cultivation season (i.e., Maha season) starts in Sri Lanka. During Maha season almost up to 100% of rice cultivation is recommended by the relevant institutions. Therefore, one of the peak demands for stored water from the JJAS season arises during September. According to our results, there is a more likelihood to observe below average seasonal rainfall for JJAS season for the Kotmale catchment during warm ENSO phase than the other ENSO phases. Besides during warm ENSO phase, significant below average rainfall is also observed in the early September (Figure
Water demand for the hydropower generation is also impacted adversely during warm ENSO phase, due to the presence of below average rainfall. Therefore, mutually generating power with other sources is recommended to minimize the power failures during early September.
Domestic water requirement during warm ENSO phases can be mitigated by adopting scheduled water supply procedure. Water conservation methods and awareness should be spread to conserve the water.
Catchment protection is another long term drought mitigation procedure which can be applied for the Kotmale reservoir. Deforestation is also one of the reasons for the reduction of rainfall for some of the stations in the catchment area; therefore relevant institutions, that is, Department of Forest Conservation, Sri Lanka, need to implement suitable remedies to minimize deforestation. Furthermore, it is advantageous to practice soil conservation methods for upper Kotmale catchment, because large tea plantations cover the upper Kotmale catchment and are neglected and the poorly managed estates have impact on the reservoir by siltation and eutrophication. These actions have led to reduction of quality and quantity of the stored volume of the reservoir [
Rainfall in Kotmale catchment showed both increasing in some stations and decreasing pattern in some other stations for JJAS season during 1960–2005 which is noticed. However, the increase in rainfall in the JJAS season has low influence on the annual rainfall of the selected stations because annual rainfall for the stations showed decreasing trend during the selected time period.
Kotmale catchment has a high likelihood of having below average rainfall for warm ENSO phase during JJAS season and rainfall during early September has a significant below average rainfall in the warm ENSO phase. However, during cold and neutral ENSO phases, Kotmale catchment did not show significant changes in the rainfall as it did in warm ENSO phase.
Although the Kotmale reservoir experiences high rainfall during JJAS, the annual rainfall showed decreasing trend. Therefore, it is vital to incorporate knowledge of teleconnection of ENSO phases over rainfall of the Kotmale catchment to implement effective water management strategy for the reservoir. There are other large persistent atmospheric oscillations, which can also influence the rainfall over Sri Lanka (i.e., Indian Ocean Dipole and Madden Julian Oscillation). Therefore we suggest that further studies are necessary to assess the impact of mentioned oscillations on the rainfall over the Kotmale reservoir in Sri Lanka.
The authors declare that they have no conflicts of interest.
The authors would like to thank APEC Climate Center, Busan, for providing the necessary facilities to pursue this study. The work was done during the YSSP program by the first author under the supervision of second author at APEC Climate Center, Busan. The station datasets provided by the Sri Lanka Meteorological Department and Mahaweli Authority of Sri Lanka are duly acknowledged. This research was also supported by a Grant (16RDRP-B076564-03) from regional development research program funded by Ministry of Land, Infrastructure and Transport of Korean government.