| Impact of future climate change on cotton yield and irrigation amount in Alaer, Xinjiang |
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| DOI：10.7606/j.issn.1000-7601.2025.06.28 |
| Key Words: cotton climate change irrigation amount yield global climate model DSSAT-CROPGRO-cotton model |
| Author Name | Affiliation | | YUE Shengru | College of Hydraulic and Architectural Engineering, Tarim University, Alaer, Xinjiang 843300, China；School of Geography and Information Engineering, China University of Geosciences, Wuhan, Hubei 430074, China | | HU Xuefei | College of Hydraulic and Architectural Engineering, Tarim University, Alaer, Xinjiang 843300, China | | HOU Xiaohua | College of Hydraulic and Architectural Engineering, Tarim University, Alaer, Xinjiang 843300, China | | MENG Fujun | College of Hydraulic and Architectural Engineering, Tarim University, Alaer, Xinjiang 843300, China | | FENG Zhuoya | College of Hydraulic and Architectural Engineering, Tarim University, Alaer, Xinjiang 843300, China |
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| Abstract: |
| Predicting and assessing the potential impacts of future climate variability on cotton yield and irrigation requirements in arid regions is of vital importance. This study employed the DSSAT-CROPGRO-Cotton model (Decision Support System for Agrotechnology Transfer-CROPGRO Cotton), driven by parameters localized from 13 Global Climate Models (GCMs), to simulate the trends in cotton yield and irrigation amount under the Shared Socioeconomic Pathways (SSP) scenarios of SSP2-4.5 and SSP5-8.5. The study also considered the influence of inter\|model differences in climate models on the simulation results. Through correlation analysis, random forest algorithms, and stepwise regression analysis, we qualitatively and quantitatively evaluated the mechanisms by which various climate factors affect yield and irrigation requirements. The results showed that (1) the uncertainty of 13 GCMs for future precipitation simulation in Alar is the highest, followed by radiation, and the uncertainty of temperature simulation is the smallest. (2) Under the SSP2-4.5 and SSP5-8.5 scenarios, cotton yield increased by 23.0% and 22.7% on average, and the contribution of CO2 concentration change was 14.9% and 23.4%, respectively. The impact of CO2 concentration change on irrigation amount was limited. There were significant differences in yield and irrigation amount simulation results across different GCMs. Under the SSP5-8.5 scenario, in the 2090s, the yield simulation results from the INM-CM4.8 and IPSL-CM6A-LR models differed by as much as 102.6%. (3) Under future scenarios, the key factors affecting cotton yield and irrigation amount, as well as their characteristic weights, changed over time. Under the SSP2-4.5 scenario, temperature and CO2 concentration shifted from a positive to a negative correlation with yield over time. Under the SSP5-8.5 scenario, this shift happened earlier and was more pronounced. Maximum temperature, precipitation, and radiation were the main factors influencing irrigation amount. |
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