Abstract

The impact of climate change on agricultural yield is one amongst the major concerns the world is witnessing. Our study focusses on rice yield prediction for an agricultural research station in Kerala with the help of climate change scenario input from the Meteorological Research Institute (MRI) Global Climate Model (GCM) projection under Representative Concentration Pathway 8.5 (RCP8.5). We have used Cropping System Model (CSM) Crop Estimation through Resource and Environment Synthesis (CERES) Rice within Decision Support System for Agrotechnology Transfer (DSSAT) package for predicting the yield. Our study has the novelty of using very high-resolution climate data from a model which is highly skilful in capturing the present-day climate features and climatic trends over India (in particular, over the Western Ghats), as input for simulating the future crop yield. From this study, we find that the rice yield decreases due to rise in temperature and reduction in rainfall, thereby reducing the crops maturity time in the future. Based on our results, the adaptation measures suggested to achieve better yield under future warming conditions are: (i) to opt for alternative rice varieties which have tolerance to high temperatures and consume less water, and (ii) shifting of planting date to the most appropriate window.

Highlights

1. 1. Impact study of future climate change on rice yield is carried out using CERES Rice Cropping System Model after systematic validation.
2. 2. Highly reliable climate change information from the projection by a 20-km resolution global climate model of MRI which is remarkably skilful in simulating the present-day Indian climate, is used as input for the crop model.
3. 3. Rice yield is found to decrease in future due to rise in temperature and reduction in rainfall, thereby reducing the crops maturity time.
4. 4. Adaptive measures of opting for temperature tolerant, high yielding rice varieties which consume less water and shifting of planting date to an appropriate window, are suggested to achieve better yield.

中文翻译：

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使用高分辨率全球气候模型预测中的气候变化情景，喀拉拉邦水稻产量的未来变化

摘要

气候变化对农业产量的影响是世界正在关注的主要问题之一。我们的研究集中在喀拉拉邦一个农业研究站的水稻产量预测上，该气象站是根据气象研究所（MRI）全球气候模式（GCM）预测在代表浓度路径8.5（RCP8.5）下提供的气候变化情景输入的。我们在农业技术转移决策支持系统（DSSAT）软件包中使用了通过资源和环境综合（CERES）水稻进行的作物系统模型（CSM）作物估计，以预测产量。我们的研究具有新颖性，该模型使用了非常高分辨率的气候数据模型，该模型非常熟练地捕获了印度（尤其是西高止山脉）的当今气候特征和气候趋势，作为模拟未来作物产量的输入。从这项研究中，我们发现由于温度升高和降雨减少，水稻产量下降，从而减少了未来的作物成熟时间。根据我们的结果，为在未来的变暖条件下获得更好的产量而建议采取的适应措施是：（i）选择对高温具有耐受性并消耗较少水的替代水稻品种，以及（ii）将播种日期移至最长时间适当的窗口。

强调

1. 1. 在系统验证后，使用CERES水稻种植系统模型进行了未来气候变化对水稻产量的影响研究。
2. 2. 将20 km分辨率的MRI全球气候模型从投影中获得的高度可靠的气候变化信息用作作物模型的输入，该模型在模拟当今印度气候方面非常熟练。
3. 3. 由于温度升高和降雨减少，发现水稻单产未来将下降，从而缩短了作物的成熟时间。
4. 4.建议 采取适应性措施，选择耐温，高产的水稻品种，该品种耗水量少，并且将播种期移到适当的窗口，以提高产量。