{"title":"Modelling and Assessment of Climate Change Impact on Rainfed Rice Cultivation in a Sub-humid Subtropical Region","authors":"Aniket Baishya, Ashok Mishra, Sudip Sengupta","doi":"10.1007/s40003-023-00671-w","DOIUrl":null,"url":null,"abstract":"<div><p>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<sup>−1</sup>) 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 (<i>r</i><sup>2</sup> > 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.</p></div>","PeriodicalId":7553,"journal":{"name":"Agricultural Research","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Research","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s40003-023-00671-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
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.
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.