基于CMIP6模式的塔里木河流域棉花生产评估

doi:10.13866/j.azr.2025.10.15

摘要/Abstract

摘要：

气候变化是影响棉花生产的重要因素。本文分析了DSSAT-CROPGRO-Cotton模型在塔里木河流域棉花生产模拟中的适用性。根据CMIP6气候模式模拟的SSP2-4.5和SSP5-8.5共享社会经济路径下的气候变化数据集，分析了2021—2100年气候变化特征、棉花产量、灌溉量和水分生产率在空间上的变化特征和重心转移规律。结果表明：塔里木河流域2021—2100年棉花生长季气温升高最高可达4.9 ℃，降水平均减少3.4~4.4 mm，辐射平均降低0.6~0.7 MJ∙m^-2。DSSAT-CROPGRO-Cotton+GIS耦合模型能够准确地模拟塔里木河流域棉花产量和灌溉量。未来情景下塔里木河流域棉花产量较历史时期增加12.42%~23.96%，灌溉量增加1.76%~21.82%，水分生产率增加0.95%~20.61%。棉花产量、灌溉量和水分生产率在SSP2-4.5和SSP5-8.5情景下分别表现为“增加-停滞”“持续增加”“增加-下降”和“增加-停滞-下降”“持续增加”“增加-停滞-急剧下降”的变化规律。SSP2-4.5情景下棉花产量重心向东北移动，而SSP5-8.5情景下则表现为“东北-西南”的折返状态。未来情景下灌溉重心向东北移动，水分生产率重心向西南移动。

关键词: 气候变化, 棉花生产, CMIP6, DSSAT-CROPGRO-Cotton+GIS, 塔里木河流域

Abstract:

Climate change significantly affects cotton production. This study assessed the effectiveness of the DSSAT-CROPGRO-Cotton model in simulating cotton production in the Tarim River Basin. Using climate change datasets generated by CMIP6 climate models under the SSP2-4.5 and SSP5-8.5 Shared Socioeconomic Pathways, the study analyzed the spatiotemporal variations and centroid shift patterns of climate characteristics, cotton yield, irrigation water volume, and water productivity from 2021 to 2100. The results indicate that during the cotton-growing season, temperature in the Tarim River Basin is projected to rise by up to 4.9 ℃, whereas precipitation is expected to decrease by an average of 3.4-4.4 mm, and solar radiation is likely to decline by 0.6-0.7 MJ∙m^-2 from 2021 to 2100. The DSSAT-CROPGRO-Cotton+GIS coupled model reliably simulated cotton yield and irrigation water volume in the Tarim River Basin. Under future scenarios, cotton yield is projected to increase by 12.42%-23.96% relative to historical levels, with irrigation water volume rising by 1.76%-21.82% and water productivity by 0.95%-20.61%. The changes in cotton yield, irrigation water volume, and water productivity under the SSP2-4.5 and SSP5-8.5 scenarios exhibit distinct patterns. In the SSP2-4.5 scenario, cotton yield is expected to follow an “increase-stagnation” pattern, whereas irrigation water volume is anticipated to “continuously increase,” and water productivity is likely to follow an “increase-decrease” pattern. In contrast, under the SSP5-8.5 scenario, cotton yield is projected to follow an “increase-stagnation-decrease” pattern, with irrigation water volume still “continuously increasing,” whereas water productivity is expected to follow an “increase-stagnation-sharp decrease” pattern. Centroid analysis shows that under the SSP2-4.5 scenario, the centroid of cotton yield is expected to shift northeastward, whereas under the SSP5-8.5 scenario, it exhibits a “northeast-southwest” oscillation. The centroid of irrigation water volume is projected to shift northeastward, whereas that of water productivity is likely to shift southwestward in future scenarios.

Key words: climate change, cotton production, CMIP6, DSSAT-CROPGRO-Cotton+GIS, Tarim River Basin

岳胜如, 胡雪菲, 侯晓华, 孟福军. 基于CMIP6模式的塔里木河流域棉花生产评估[J]. 干旱区研究, 2025, 42(10): 1925-1938.

YUE Shengru, HU Xuefei, HOU Xiaohua, MENG Fujun. Cotton production assessment in the Tarim River Basin based on CMIP6 models[J]. Arid Zone Research, 2025, 42(10): 1925-1938.

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编号	名称	国家	发布年份	空间分辨率（经向×纬向）
1	ACCESS-ESM1-5	澳大利亚	2019年	1.875°×1.241°
2	BCC-CSM2-MR	中国	2017年	1.125°×1.125°
3	CMCC-ESM2	意大利	2017年	1.25°×0.9375°
4	ESM2-0	中国	2022年	1.875°×1.875°
5	INM-CM4-8	俄罗斯	2016年	2.00°×1.50°
6	INM-CM5-0	俄罗斯	2016年	2.00°×1.50°
7	IPSL-CM6A-LR	法国	2017年	2.50°×1.26°
8	MPI-ESM1-2-HR	德国	2017年	0.9375°×0.9375°
9	MPI-ESM1-2-LR	德国	2017年	1.875°×1.875°
10	MRI-ESM2-0	日本	2017年	1.125°×1.125°
11	NESM3	中国	2016年	1.875°×1.875°
12	NorESM2-MM	挪威	2017年	2.50°×2.50°
13	TaiESM1	中国	2018年	1.25°×0.9375°

区站号	站点名称	纬度	经度	海拔/m	区站号	站点名称	纬度	经度	海拔/m
51559	和静	42.32°N	86.40°E	1100.90	51720	柯坪	40.50°N	79.05°E	1161.80
51567	焉耆	42.08°N	86.57°E	1055.30	51722	阿瓦提	40.65°N	80.40°E	1044.30
51568	和硕	42.25°N	86.80°E	1085.40	51730	阿拉尔	40.55°N	81.27°E	1012.20
51627	乌什	41.22°N	79.23°E	1395.80	51765	铁干里克	40.63°N	87.70°E	846.00
51628	阿克苏	41.12°N	80.38°E	1107.10	51777	若羌	39.03°N	88.17°E	887.70
51629	温宿	41.27°N	80.23°E	1133.10	51802	英吉沙	38.93°N	76.17°E	1297.50
51633	拜城	41.78°N	81.90°E	1229.20	51810	麦盖提	38.92°N	77.63°E	1178.20
51636	新和	41.55°N	82.65°E	1009.80	51811	莎车	38.43°N	77.27°E	1231.20
51639	沙雅	41.23°N	82.78°E	980.40	51814	叶城	37.92°N	77.40°E	1360.40
51642	轮台	41.82°N	84.27°E	982.00	51815	泽普	38.20°N	77.27°E	1274.70
51644	库车	41.72°N	82.97°E	1081.90	51818	皮山	37.62°N	78.28°E	1375.40
51655	尉犁	41.35°N	86.27°E	884.90	51826	策勒	37.02°N	80.80°E	1336.50
51656	库尔勒	41.73°N	85.82°E	899.80	51827	墨玉	37.17°N	79.63°E	1348.90
51704	阿图什	39.72°N	76.17°E	1298.70	51828	和田	37.13°N	79.93°E	1375.00
51707	伽师	39.50°N	76.78°E	1204.70	51829	洛浦	37.08°N	80.17°E	1347.90
51708	阿克陶	39.15°N	75.95°E	1325.10	51839	民丰	37.07°N	82.72°E	1409.50
51709	喀什	39.48°N	75.75°E	1385.60	51855	且末	38.15°N	85.55°E	1247.20
51716	巴楚	39.80°N	78.57°E	1116.50	51931	于田	36.85°N	81.65°E	1422.00
51717	岳普湖	39.25°N	76.78°E	1206.30