8 research outputs found
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Epochal Changes in ENSO–Streamflow Relationships in Sri Lanka
In an effort to use climate predictions for streamflow and malaria hazard prediction, the decadal variability of the El Niño–Southern Oscillation (ENSO) influence on streamflow and rainfall in the Kelani River in Sri Lanka was investigated based on records from 1925 to 1995. In the last half century, the warm ENSO phase was associated with decreased annual streamflow and the cold ENSO phase with increased streamflow. The annual streamflow had a negative correlation (warm ENSO associated with low streamflow) with the concurrent ENSO index of Niño-3.4 that was significant at the 5% level. This negative correlation with Niño-3.4 is enhanced to a 1% significance level if the aggregate streamflow from January to September alone is considered. There has been a transition in correlation between January–September streamflow and ENSO between the 1950s and 1970s from near or above zero to negative values that have 95% significance levels reminiscent of an epochal shift. This shift was evident when considering the period when the southwest monsoon dominates (April–September) or when correlations were undertaken between the seasonal streamflow and rainfall and the ENSO index in the month prior to each season. Since the relationship between ENSO and Sri Lankan streamflow has strengthened in recent decades the potential for ENSO-based prediction is retained. The epochal shift may also explain why malaria epidemics ceased to co-occur frequently with El Niño episodes after 1945
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Predictability of stream flow and rainfall based on ENSO for water resources management in Sri Lanka
We investigate the viability of using El Niño–Southern Oscillation (ENSO) and sea surface temperature (SST) data to predict seasonal streamflow for one of the major rivers in Sri Lanka, the Kelani, using correlation analysis, contingency tables, and principal component analysis. The agricultural seasons in Sri Lanka are Yala (April–September) and Maha (October–March). The correlation between the Kelani River streamflow during Yala and ENSO indices (r = −0.41) is significant at 99% level. In addition, the Kelani streamflow during Yala has a correlation with the Central Indian Ocean SST (r = −0.40) that is also significant at the 99% level. The first principal component of the Indo-Pacific Ocean SST is reminiscent of the SST associated with the ENSO mode. A prediction scheme based on this mode for the streamflow during Yala has a skill characterized by a correlation of 0.5 in a cross-validated mode. The prediction of streamflow during Maha is best carried out separately for the two halves of the season. During the El Niño phase, the rainfall during Maha is enhanced during the first half of the season (October–December) and diminished in the second half (January–February). Rainfall rather than streamflow has a better relationship with ENSO from October to December. During the second half of the Maha season, rainfall declines with both warm and cold ENSO phases and any prediction scheme has to take into account this non-linear relationship. Overall, useful skill for seasonal streamflow predictions has been demonstrated for the Yala season and skill for seasonal rainfall predictions for the first and second half of the Maha season has been elucidated
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Predictability of Sri Lankan rainfall based on ENSO
Investigating the year-round rainfall of Sri Lanka provides understanding into the South Asian monsoon system as it compliments studies on the Indian summer monsoon. The El Niño-Southern Oscillation (ENSO) is a primary mode of climate variability of this area. Here, the predictability of Sri Lanka rainfall based on ENSO is quantified based on composite analysis, correlations and contingency tables. The rainfall is modestly predictable based on ENSO during January-March, July-August and October-December. El Niño typically leads to wetter conditions during October to December and drier conditions during January to March and July to August on average. The correlations of ENSO indices with rainfall are statistically significant for October to December, January to March and July to August and an analysis based on contingency tables shows modest predictability. The use of ENSO indices derived from the central Pacific sea surfaces improves the predictability from January to June. The predictability in the mountain regions is diminished when garnering orographic rainfall. The predictability in the east is diminished during the cyclone season. The predictability based on ENSO for October to December rainfall is robust on a decadal scale while the predictability of January to March and July to August rainfall has acquired significance in recent decades. An ENSO-based scheme that is adapted to each season and region, and takes account of decadal variations can thus provide skillful rainfall predictions
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Fine Scale Natural Hazard Risk and Vulnerability Identification Informed by Climate
Although many natural disasters have hydro-meteorological antecedents, little advantage has been taken of the availability of weather and climate data, advanced diagnostics and seasonal predictions for disaster risk management. In this study, methodologies for use of hydro-meteorological data in hazard risk assessment are presented laying the ground work for future dynamic hazard predictions. A high-resolution assessment of natural hazards, vulnerability to hazards and of multihazard disaster risk has been carried out for Sri Lanka. Drought, flood, cyclone and landslide hazards, and vulnerability were identified using data from Sri Lankan government agencies. Drought and flood prone areas were mapped using rainfall data that was gridded at a resolution of 10-km. Cyclone and landslide hazardousness were mapped based on long-term historical incidence data. Indices for regional industrial development, infrastructure development and agricultural production were estimated based on proxies. An assessment of regional food insecurity from the World Food Programme was used in the analysis. Records of emergency relief were used in estimating a spatial proxy for disaster risk. A multi-hazardousness map was developed for Sri Lanka. The hazardousness estimates for drought, floods, cyclones, landslides were weighted for their associated disaster risk with proxies for economic losses to provide a risk map or a hotspots map. Our principal findings are summarized below. Useful hazard and vulnerability analysis can be carried out with the type of data that is available in-country. The hazardousness estimates for droughts, floods, cyclones and landslides show marked spatial variability. Vulnerability shows marked spatial variability as well. Thus, the resolution of analysis needs to match the resolution of spatial variations in relief, climate and other features. The higher resolution information is needed in planning and action for disaster management. Multi-hazard analysis brought out regions of high risk in Sri Lanka such as the Kegalle and Ratnapura Districts in the South West and Ampara, Batticaloa, Trincomalee, Mullaitivu and Killinochchi districts in the North-East and the districts of Nuwara Eliya, Badulla, Ampara and Matale that contain some of the sharpest hill slopes of the central mountain massifs. There is a distinct seasonality to risks posed by drought, floods, landslides and cyclones. Whereas the Eastern slopes regions have hotspots during the boreal fall and early winter, the Western slopes regions is risk prone in the summer and the early fall. Thus attention is warranted not only on Hot-Spots but also on "Hot-Seasons." Climate data was useful in estimating hazardousness in the case of droughts, floods and cyclones and for estimating flood and landslide risk. The methodologies presented here for hazard analysis of floods and droughts present an explicit link between climate and hazard. The results from this study coupled with the high-resolution seasonal climate prediction techniques developed in a related study point the way to using historical, current and predictive climate information to inform disaster management policy, and early warning systems. Climate, environmental and social change such as deforestation, urbanization and war affect the hazardousness and vulnerability. It is more difficult to quantify such changes rather than the baseline conditions. Our analysis was carried out for a period since 1960 that included a period of civil war after 1983. This war affected the North-East of the island in particular. To put things in context, while natural disasters accounted for 1,483 fatalities in this period, the civil wars accounted for over 65,000. Wars and conflict poses complications for hazard and vulnerability analysis. Yet, the vulnerabilities created by the war make such efforts to reduce disaster risks all the more important. Technical details of our work have been included in a case study published by the World Bank and in journals listed in the outputs
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Climate Influences on Human-Elephant Conflict in Sri Lanka
Contemporary ecological research supports focus on the preservation of habitats and the preservation of keystone species that are critical to the ecological character of the habitats. Conservation of endangered species works best with attention not only to the species but also to the needs of the people who may be adjacent to or bordering habitats. Southern Sri Lanka fall into the category of globally important biodiversity hotspots. The biggest land animal, the elephant is the keystone species in Sri Lanka outside the highlands. The population of elephants in Sri Lanka is estimated to be between 3000 and 4,000; yet there has been an alarming loss of 1000 elephants during from 1990-2003. Given its island setting and rich hydro-climatic data, Sri Lanka provides a unique opportunity to study the dynamics leading to species loss. Our work in this project was initially motivated by the practical concerns of our project partners in the Mahaweli River Basin in Sri Lanka where the human-elephant conflict was a major problem. The question that arose was: "Are the climate, water availability and river basin management practices contributing to conflict between elephants and people?" If this was indeed the case, then, could one adaptively manage the river basin, organize agricultural practices, and prioritize conflict mitigation options such as separate habitat enrichment programs? Moreover, could we propose various adaptive measures in changes if one could monitor the climate and environmental conditions and take advantage of seasonal climate predictions
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Impact assessment and adaptation to climate change of plantations in Sri Lanka
This report documents the work undertaken by the IRI, FECT, NRMS and University of
Peradeniya as part of the overall project. Separate reports were prepared by the Tea
Research Institute, Coconut Research Institute and the Department of Meteorology in Sri
Lanka. The work at IRI, FECT and NRMS has proceeded satisfactorily. The work was in
the domain of climate and climate change, crop-climate impact analysis and contributions
to synthesis. We have contributed significantly in terms of research output and in
capacity building, which were the goals of the AIACC project
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Analysis of impacts of climate variability on malaria transmission in Sri Lanka and the development of an early warning system
This project set goals of bringing together a multi-disciplinary, multi-national and multi-institutional team to address the relationship between climate and malaria in aggregate terms for Sri Lanka, and in detail for the Uva Province to help develop early warning systems. The project was undertaken in partnership with Sri Lanka’s Anti-Malaria Campaign (AMC) and the Foundation for Environment, Climate and Technology, Sri Lanka (FECT). Overall, we have accomplished the projected outcomes in spite of several setbacks
Epochal changes in the association between malaria epidemics and El Niño in Sri Lanka
This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens