Journal of Geographical Sciences

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“Bundling regions” based optimization of planting structure for water conservation in the Yellow River Basin

SHEN Yilin, MA Qingtao, GUO Ying, CHEN Xiaolu, LIU Mengzhu, DENG Lu, ZHU Yiding, SHEN Yanjun

Journal of Geographical Sciences, 2026, 36(3): 669-689. DOI: 10.1007/s11442-026-2465-1

Figure S1 Changes in yield and sown area of different crops in the Yellow River Basin

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Figure 1 Location of the study area (Yellow River Basin)
Figure 2 Flow chart
Table 1 Definition and explanation of driving factors for changes in irrigation water demand
Figure 3 Determining the number of clusters using the elbow method
Figure 4 Spatiotemporal variations of irrigation water demand in the Yellow River Basin (The trends of irrigation water demand changes were obtained from data from the years 2000, 2005, 2010, 2015 and 2019.)
Figure 5 Contributions of agricultural water use efficiency changes, yield per unit area, cropping patterns, and planting scale to irrigation water demand
Figure 6 Spatiotemporal variation characteristics of irrigation water demand driving zones in the Yellow River Basin: (a) Irrigation water demand driving characteristics of each zone; (b) spatial distribution of each zone during the periods 2000-2010 and 2010-2019; (c) change trajectories of city zones within the two periods
Figure 7 Annual average sown area (a), annual average irrigation water demand for wheat and maize (b), annual average sown area after optimization (c), annual average irrigation water demand for wheat and maize after optimization (d) in key agricultural water-saving zone (prefecture-level cities of the upper Yellow River Basin transition from B2 to B5 and persistent B5 classification)
Table 2 Annual average sown area, yield, and irrigation water demand of wheat and maize in key regions before and after optimization
Table S1 Crop coefficient of spring wheat
Table S2 Crop coefficient of winter wheat
Table S3 Crop coefficient of spring maize
Table S4 Crop coefficient of summer maize
Table S5 Crop coefficient of cotton
Table S6 Crop coefficient of peanut
Table S7 Crop coefficient of soybean
Table S8 Crop coefficient of tubers (Using the sweet potatoes to represent the tubers)
Figure S2 Spatial distribution of driving factors (values scaled to the 90th percentile to highlight spatial gradients; extreme values beyond this threshold are uniformly represented within the upper and lower color.)
Table S9 The naming and interpretation of each bundle

模态框（Modal）标题

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