<p>Food security is an increasing threat to rice-consuming nations in the face of a changing climate. In this study, we present a framework for analysing&#160; the historical and projecting the future relationship between climate variability and rice yield in the context of weather index insurance. The case study is the Muda rice granary, the largest rice paddy planting area in Malaysia producing approximately 40% of the national output. First, correlation and linear regression are used to explore the response of seasonal rice yield to various average and extreme precipitation, temperature and streamflow-based indices over a 16 year period between 2001 to 2016.&#160; The highest Pearson correlation (r) and coefficient of determination (R<sup>2</sup>) values were obtained with June minimum temperature in the dry season, and December maximum 1 day precipitation and&#160; January mean streamflow in the wet season. The results suggest that rice yield is most at risk from the impact of hydroclimatic variability and change during the flowering and maturity stages of crop growth. Next, findings from the statistical analysis are integrated with hydro-crop simulation of the 4,515 km2 catchment area, using a calibrated Soil Water Assessment Tool (SWAT) and bias-corrected Regional Climate Model output from the Coordinated Regional Downscaling Experiment for South East Asia (CORDEX-SEA). The output is finally used to construct projected future risk profiles for rice production in the area.&#160;</p>
Good index selection is key to minimising basis risk in weather index insurance design. However, interannual, seasonal, and intra-seasonal hydroclimatic variabilities pose challenges in identifying robust proxies for crop losses. In this study, we systematically investigated 574 hydroclimatic indices for their relationships with yield in Malaysia’s irrigated double planting system, using the Muda rice granary as a case study. The responses of seasonal rice yields to seasonal and monthly averages and to extreme rainfall, temperature, and streamflow statistics from 16 years’ observations were examined by using correlation analysis and linear regression. We found that the minimum temperature during the crop flowering to the maturity phase governed yield in the drier off-season (season 1, March to July, Pearson correlation, r = +0.87; coefficient of determination, R2 = 74%). In contrast, the average streamflow during the crop maturity phase regulated yield in the main planting season (season 2, September to January, r = +0.82, R2 = 67%). During the respective periods, these indices were at their lowest in the seasons. Based on these findings, we recommend temperature- and water-supply-based indices as the foundations for developing insurance contracts for the rice system in northern Peninsular Malaysia.
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