4.7 Article

Predicting the impacts of climate change - A case study of paddy irrigation water requirements in Sri Lanka

Journal

AGRICULTURAL WATER MANAGEMENT
Volume 93, Issue 1-2, Pages 19-29

Publisher

ELSEVIER
DOI: 10.1016/j.agwat.2007.06.003

Keywords

food production; geographical information system; water resources; spatial variability; adaptation

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Nearly 72% of paddy production, the staple food in Sri Lanka, is grown during the wet season in dry areas where water resources are already stressed. Climate change datasets for Sri Lanka were derived using outputs from the UK Hadley Centre for Climate Prediction and Research Model (HadCM3) for selected scenarios for the 2050s, chosen from the Intergovernmental Panel of Climate Change Special Emission Scenarios Report. Water balance modelling and a geographical information system were used to model and map the impacts on irrigation requirements for wet season paddy. We examined two scenarios. The A2 scenario represents a heterogeneous, regionalised, market-led world, with high population growth, leading to a rapid increase in atmospheric carbon dioxide levels. The B2 scenario follows a similar regionalised future but with more moderate population growth and more concern for the environment and local sustainability, and a slower rate of increase in atmospheric carbon dioxide. Results suggests that, during the wet season, average rainfall decreases by 17% (A2) and 9% (B2), with rains ending earlier, and potential evapotranspiration increasing by 3.5% (A2) and 3% (B2). Consequently, the average paddy irrigation water requirement increases by 23% (A2) and 13% (B2). Mapping with GIS highlights the importance of considering spatial variation. Climate change impacts on wet season paddy production are positive in the extreme south, confirming results of a previous study. However, the impacts are negative across most of Sri Lanka. The adaptations needed are different in the two regions. Furthermore, spatial variation points to a further adaptation; the transfer of some paddy production to positively affected areas, which would not have been so clear if only point modelling had been used. (c) 2007 Elsevier B.V. All rights reserved.

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