Modelling and Assessment of Climate Change Impact on Rainfed Rice Cultivation in a Sub-humid Subtropical Region

IF 1.4 Q3 AGRONOMY Agricultural Research Pub Date : 2023-09-01 DOI:10.1007/s40003-023-00671-w
Aniket Baishya, Ashok Mishra, Sudip Sengupta
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Abstract

Changing climate is one of the main factors affecting to decline food production because crop growth is sensitive to climatic changes. In this study, DSSAT and APSIM models were calibrated and validated at 15 different locations of the Kangsabati river basin and compared based on three output parameters for three famous variety, viz. Swarna, Lalat, and MTU 1010 to identify which one was the most accurate in reproducing rainfed rice yield in the research location. The results suggest that DSSAT model can simulate rice crop growth and yield better than APSIM model in this region. In terms of rice yield, Swarna, a long-duration rice variety, had a greater RMSE (144.63 kg ha−1) than the short-duration rice variety Lalat and MTU 1010. However, the DSSAT model performed better than the APSIM model in modeling rainfed rice crop growth and yield (r2 > 0.86 and greater ME). Bias-corrected RCM (HadGEM3-RA) have been linked to the DSSAT model to analyze yield changes of three popular rice varieties (Swarna, Lalat, and MTU 1010) for future climate scenario (2030s & 2040s). The average decrease in rice yield of Swarna is projected to be around 7% in 2030s and 9% in 2040s, and under RCP 8.5, average decrease in rice yield of Swarna is projected to be 12.8% (2030s) and 15.4% (2040s), which is much higher than production of Lalat and MTU 1010 in both the cases. In conclusion, DSSAT might be a helpful tool for determining the effects of management techniques and climate change on various rice varieties.

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气候变化对亚热带半湿润地区旱作水稻种植影响的模拟与评估
气候变化是影响粮食产量下降的主要因素之一,因为作物生长对气候变化非常敏感。在这项研究中,DSSAT 和 APSIM 模型在 Kangsabati 河流域的 15 个不同地点进行了校准和验证,并根据三个著名品种(即 Swarna、Lalat 和 MTU 1010)的三个输出参数进行了比较,以确定哪个模型在再现研究地点的雨水灌溉水稻产量方面最准确。结果表明,在该地区,DSSAT 模型模拟水稻作物生长和产量的能力优于 APSIM 模型。在水稻产量方面,长生育期水稻品种 Swarna 的均方根误差(144.63 千克/公顷-1)大于短生育期水稻品种 Lalat 和 MTU 1010。然而,DSSAT 模型在雨水灌溉水稻作物生长和产量建模方面的表现优于 APSIM 模型(r2 > 0.86 和更大的 ME)。经过偏差校正的 RCM(HadGEM3-RA)与 DSSAT 模型相连,分析了未来气候情景(2030 年代 & 2040 年代)下三种常用水稻品种(Swarna、Lalat 和 MTU 1010)的产量变化。在 RCP 8.5 条件下,Swarna 的平均减产率预计为 12.8%(2030s)和 15.4%(2040s),远高于 Lalat 和 MTU 1010 的产量。总之,DSSAT 可能是确定管理技术和气候变化对各种水稻品种影响的有用工具。
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来源期刊
CiteScore
3.80
自引率
0.00%
发文量
24
期刊介绍: The main objective of this initiative is to promote agricultural research and development. The journal will publish high quality original research papers and critical reviews on emerging fields and concepts for providing future directions. The publications will include both applied and basic research covering the following disciplines of agricultural sciences: Genetic resources, genetics and breeding, biotechnology, physiology, biochemistry, management of biotic and abiotic stresses, and nutrition of field crops, horticultural crops, livestock and fishes; agricultural meteorology, environmental sciences, forestry and agro forestry, agronomy, soils and soil management, microbiology, water management, agricultural engineering and technology, agricultural policy, agricultural economics, food nutrition, agricultural statistics, and extension research; impact of climate change and the emerging technologies on agriculture, and the role of agricultural research and innovation for development.
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