Aligning Sowing Dates with the Onset of Rains to Improve Rice Yields and Water Productivity: Modelling Rice (Oryza sativa L.) Yield of the Maha Season in the Dry Zone of Sri Lanka | Zendy

R.P.R.K. Amarasingha | Zendy; Lakshman Galagedara | Zendy; B. Marambe | Zendy; G.L.L.P. Silva | Zendy; Ranjith Punyawardena | Zendy; Uday Nidumolu | Zendy; Mark Howden | Zendy; L. D. B. Suriyagoda | Zendy

Open Access

Aligning Sowing Dates with the Onset of Rains to Improve Rice Yields and Water Productivity: Modelling Rice (Oryza sativa L.) Yield of the Maha Season in the Dry Zone of Sri Lanka

Author(s) -

R.P.R.K. Amarasingha,

Lakshman Galagedara,

B. Marambe,

G.L.L.P. Silva,

Ranjith Punyawardena,

Uday Nidumolu,

Mark Howden,

L. D. B. Suriyagoda

Publication year - 2015

Publication title -

tropical agricultural research

Language(s) - English

Resource type - Journals

ISSN - 1016-1422

DOI - 10.4038/tar.v25i3.8038

Subject(s) - agriculture , productivity , oryza sativa , sowing , tropical agriculture , crop , agronomy , sri lanka , yield (engineering) , agroforestry , crop productivity , agricultural productivity , crop yield , geography , biology , ecology , biochemistry , materials science , tanzania , macroeconomics , environmental planning , metallurgy , economics , gene

Rice (Oryza sativa L. ) cultivation in Sri Lanka is restricted by limited water availability. Increased variability of seasonal rainfall as a result of climate change will further exacerbate risk in rice cultivation. Knowing the onset of rainfall through forecasts, adjusting planting date based on the predicted rainfall onset, and efficient irrigation management are important determinants to reduce the risk in rice farming. In this study, a modelling approach was used to assess the yield advantage of changing planting dates according to the onset of seasonal rainfall compared to a fixed planting date in the major rainy season (Maha), and evaluated the efficiency of irrigation management. The model, Agricultural Production Systems Simulator (APSIM), was parameterized using data from the literature, and the model could simulate the observed yield of rice varieties Bg300 and Bg359 with a good fit (CV Tropical Agricultural Research Vol. 25 (3): 277-286 (2014)

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