Journal of Geographical Sciences ›› 2021, Vol. 31 ›› Issue (7): 997-1014.doi: 10.1007/s11442-021-1882-4
• Research Articles • Previous Articles Next Articles
XIA Xingsheng1,2(), PAN Yaozhong1,2, ZHU Xiufang1,3,*(
), ZHANG Jinshui1,3
Received:
2021-02-20
Accepted:
2021-04-28
Online:
2021-07-25
Published:
2021-09-25
Contact:
ZHU Xiufang
E-mail:xiayuan1104@163.com;zhuxiufang@bnu.edu.cn
About author:
Xia Xingsheng, PhD and Instructor, specialized in crop water requirements research. E-mail: xiayuan1104@163.com
Supported by:
XIA Xingsheng, PAN Yaozhong, ZHU Xiufang, ZHANG Jinshui. Monthly calibration and optimization of Ångström-Prescott equation coefficients for comprehensive agricultural divisions in China[J].Journal of Geographical Sciences, 2021, 31(7): 997-1014.
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Figure 1
Comprehensive agricultural divisions and data station locations (A. Northeastern China. A1: Hinggan; A2: Songnen and Sanjiang Plain; A3: Changbai Mountains; A4: Liaoning Plain. B. Inner Mongolia and Regions along the Great Wall. B1: Northern Inner Mongolia; B2: Central and Southern Inner Mongolia; B3: Regions along the Great Wall. C. Huang-Huai-Hai. C1: Piedmont at the foot of the Yanshan and Taihang Mountains; C2: Low-lying plain regions of Hebei, Shandong, and Henan; C3: Huang-huai Plain; C4: Hilly region of Shandong. D. Loess Plateau. D1: Hilly region of Western Henan and Eastern Shanxi; D2: Fenhe and Weihe valleys; D3: Hilly loess region of Shanxi, Shaanxi, and Gansu; D4: Hilly region of Central Gansu and Eastern Qinghai. E. Middle and Lower Reaches of the Yangtze River. E1: Lower Yangtze Plain; E2: Mountainous regions of Henan, Hubei, and Anhui; E3: Plains in the Middle Reaches of the Yangtze River; E4: Hilly regions south of the Yangtze River; E5: Hilly region of Zhejiang and Fujian; E6: Hilly regions of Nanling. F. Southwestern China. F1: Qinling and Daba Mountains; F2: Sichuan Basin; F3: Border between Sichuan, Hubei, Hunan, and Guizhou; F4: Guizhou and Guangxi plateaus; F5: Sichuan and Yunnan plateaus. G. Southern China. G1: Southern Fujian and Central Guangdong; G2: Western Guangdong and Southern Guangxi; G3: Southern Yunnan; G4: Hainan and South China Sea Islands; G5: Taiwan. H. Gansu and Xinjiang. H1: Border between Inner Mongolia, Ningxia, and Gansu; H2: Northern Xinjiang; H3: Southern Xinjiang. I. Tibet. I1: Southern Tibet; I2: Border between Sichuan and Tibet; I3: Border between Qinghai and Gansu; and I4: High cold region of Tibet).
Table 1
Monthly optimal values for the coefficients of the AP for each agricultural subregion in China
Region ID | Jan. | Feb. | Mar. | Apr. | May. | Jun. | Jul. | Aug. | Sep. | Oct. | Nov. | Dec. | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
as | bs | as | bs | as | bs | as | bs | as | bs | as | bs | as | bs | as | bs | as | bs | as | bs | as | bs | as | bs | |
A1 | 0.36 | 0.32 | 0.20 | 0.62 | 0.32 | 0.48 | 0.18 | 0.62 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.19 | 0.62 | 0.21 | 0.62 | 0.36 | 0.29 |
A2 | 0.28 | 0.46 | 0.31 | 0.44 | 0.26 | 0.49 | 0.25 | 0.50 | 0.26 | 0.44 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.30 | 0.41 | 0.33 | 0.35 |
A3 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 |
A4 | 0.33 | 0.25 | 0.26 | 0.40 | 0.13 | 0.62 | 0.14 | 0.60 | 0.20 | 0.51 | 0.22 | 0.46 | 0.25 | 0.37 | 0.16 | 0.55 | 0.20 | 0.50 | 0.18 | 0.53 | 0.21 | 0.45 | 0.28 | 0.31 |
B1 | 0.47 | 0.24 | 0.43 | 0.32 | 0.37 | 0.39 | 0.29 | 0.46 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.27 | 0.50 | 0.26 | 0.53 | 0.37 | 0.38 | 0.45 | 0.25 |
B2 | 0.40 | 0.27 | 0.20 | 0.56 | 0.25 | 0.49 | 0.25 | 0.50 | 0.25 | 0.50 | 0.27 | 0.39 | 0.38 | 0.20 | 0.23 | 0.49 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 |
B3 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.23 | 0.49 | 0.25 | 0.48 | 0.25 | 0.50 | 0.32 | 0.38 |
C1 | 0.19 | 0.50 | 0.21 | 0.49 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.21 | 0.46 | 0.16 | 0.54 |
C2 | 0.23 | 0.46 | 0.25 | 0.50 | 0.31 | 0.37 | 0.13 | 0.66 | 0.26 | 0.43 | 0.22 | 0.48 | 0.25 | 0.50 | 0.25 | 0.39 | 0.27 | 0.37 | 0.20 | 0.52 | 0.19 | 0.54 | 0.22 | 0.47 |
C3 | 0.20 | 0.50 | 0.23 | 0.48 | 0.25 | 0.50 | 0.25 | 0.50 | 0.22 | 0.46 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.19 | 0.52 | 0.25 | 0.50 | 0.18 | 0.52 | 0.25 | 0.50 |
C4 | 0.21 | 0.43 | 0.18 | 0.52 | 0.25 | 0.50 | 0.21 | 0.47 | 0.17 | 0.55 | 0.21 | 0.46 | 0.20 | 0.47 | 0.20 | 0.46 | 0.25 | 0.50 | 0.17 | 0.54 | 0.17 | 0.53 | 0.18 | 0.47 |
D2 | 0.22 | 0.46 | 0.25 | 0.38 | 0.25 | 0.36 | 0.28 | 0.30 | 0.26 | 0.37 | 0.21 | 0.48 | 0.22 | 0.47 | 0.20 | 0.50 | 0.18 | 0.52 | 0.20 | 0.47 | 0.21 | 0.46 | 0.22 | 0.47 |
D3 | 0.24 | 0.44 | 0.25 | 0.50 | 0.25 | 0.50 | 0.18 | 0.55 | 0.15 | 0.60 | 0.14 | 0.61 | 0.18 | 0.55 | 0.18 | 0.54 | 0.15 | 0.59 | 0.13 | 0.62 | 0.19 | 0.52 | 0.17 | 0.54 |
D4 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.13 | 0.67 | 0.22 | 0.51 | 0.21 | 0.52 | 0.25 | 0.50 | 0.19 | 0.56 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 |
E1 | 0.16 | 0.55 | 0.12 | 0.64 | 0.10 | 0.69 | 0.14 | 0.60 | 0.18 | 0.53 | 0.17 | 0.52 | 0.16 | 0.55 | 0.15 | 0.56 | 0.16 | 0.55 | 0.17 | 0.55 | 0.15 | 0.57 | 0.14 | 0.58 |
E2 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.21 | 0.46 | 0.23 | 0.43 | 0.22 | 0.47 | 0.21 | 0.51 | 0.19 | 0.53 | 0.16 | 0.60 | 0.14 | 0.60 | 0.16 | 0.54 | 0.25 | 0.50 |
E3 | 0.10 | 0.73 | 0.11 | 0.70 | 0.11 | 0.67 | 0.12 | 0.63 | 0.17 | 0.55 | 0.17 | 0.55 | 0.18 | 0.53 | 0.15 | 0.59 | 0.11 | 0.71 | 0.19 | 0.53 | 0.16 | 0.58 | 0.16 | 0.56 |
E4 | 0.10 | 0.68 | 0.10 | 0.71 | 0.11 | 0.65 | 0.16 | 0.46 | 0.15 | 0.58 | 0.20 | 0.45 | 0.23 | 0.44 | 0.21 | 0.48 | 0.19 | 0.52 | 0.18 | 0.52 | 0.15 | 0.58 | 0.12 | 0.65 |
E5 | 0.13 | 0.73 | 0.19 | 0.52 | 0.16 | 0.60 | 0.20 | 0.52 | 0.18 | 0.61 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.21 | 0.53 | 0.18 | 0.59 |
E6 | 0.13 | 0.63 | 0.12 | 0.63 | 0.11 | 0.65 | 0.13 | 0.55 | 0.14 | 0.60 | 0.19 | 0.48 | 0.18 | 0.50 | 0.23 | 0.42 | 0.17 | 0.56 | 0.21 | 0.48 | 0.16 | 0.58 | 0.17 | 0.52 |
F1 | 0.16 | 0.59 | 0.19 | 0.51 | 0.18 | 0.55 | 0.35 | 0.17 | 0.26 | 0.40 | 0.20 | 0.54 | 0.24 | 0.48 | 0.19 | 0.59 | 0.15 | 0.68 | 0.18 | 0.56 | 0.24 | 0.37 | 0.22 | 0.48 |
F2 | 0.15 | 0.53 | 0.15 | 0.64 | 0.16 | 0.59 | 0.17 | 0.52 | 0.19 | 0.49 | 0.17 | 0.55 | 0.19 | 0.49 | 0.18 | 0.50 | 0.16 | 0.53 | 0.17 | 0.52 | 0.16 | 0.57 | 0.14 | 0.62 |
F3 | 0.14 | 0.53 | 0.13 | 0.58 | 0.11 | 0.64 | 0.14 | 0.54 | 0.16 | 0.52 | 0.18 | 0.50 | 0.19 | 0.49 | 0.23 | 0.41 | 0.21 | 0.43 | 0.18 | 0.45 | 0.15 | 0.55 | 0.14 | 0.54 |
F4 | 0.11 | 0.77 | 0.12 | 0.73 | 0.25 | 0.50 | 0.14 | 0.61 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.20 | 0.46 | 0.16 | 0.54 | 0.25 | 0.50 | 0.12 | 0.76 | 0.13 | 0.62 |
F5 | 0.20 | 0.56 | 0.25 | 0.50 | 0.13 | 0.63 | 0.19 | 0.53 | 0.20 | 0.52 | 0.22 | 0.48 | 0.23 | 0.46 | 0.21 | 0.51 | 0.22 | 0.51 | 0.25 | 0.50 | 0.18 | 0.59 | 0.16 | 0.61 |
G1 | 0.15 | 0.59 | 0.14 | 0.62 | 0.13 | 0.65 | 0.15 | 0.58 | 0.16 | 0.55 | 0.19 | 0.43 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 |
G2 | 0.17 | 0.58 | 0.15 | 0.62 | 0.16 | 0.54 | 0.17 | 0.57 | 0.19 | 0.50 | 0.21 | 0.48 | 0.22 | 0.45 | 0.22 | 0.46 | 0.22 | 0.48 | 0.27 | 0.41 | 0.21 | 0.52 | 0.20 | 0.53 |
G3 | 0.25 | 0.50 | 0.25 | 0.50 | 0.23 | 0.45 | 0.30 | 0.33 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.27 | 0.42 |
G4 | 0.19 | 0.54 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.34 | 0.28 | 0.25 | 0.50 | 0.28 | 0.34 | 0.25 | 0.50 | 0.25 | 0.50 | 0.21 | 0.50 |
H1 | 0.25 | 0.50 | 0.25 | 0.50 | 0.41 | 0.29 | 0.35 | 0.38 | 0.25 | 0.50 | 0.25 | 0.50 | 0.27 | 0.47 | 0.23 | 0.53 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 |
H2 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.37 | 0.30 | 0.17 | 0.60 | 0.30 | 0.42 | 0.27 | 0.44 | 0.24 | 0.49 | 0.25 | 0.50 | 0.21 | 0.53 | 0.23 | 0.52 | 0.26 | 0.47 |
H3 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 | 0.29 | 0.42 | 0.34 | 0.35 | 0.35 | 0.34 | 0.30 | 0.40 | 0.32 | 0.37 | 0.34 | 0.36 | 0.31 | 0.42 | 0.25 | 0.50 | 0.27 | 0.43 |
I1 | 0.16 | 0.73 | 0.34 | 0.49 | 0.39 | 0.39 | 0.25 | 0.50 | 0.40 | 0.36 | 0.43 | 0.32 | 0.35 | 0.45 | 0.35 | 0.45 | 0.38 | 0.39 | 0.25 | 0.50 | 0.25 | 0.50 | 0.25 | 0.50 |
I2 | 0.24 | 0.60 | 0.27 | 0.52 | 0.25 | 0.50 | 0.30 | 0.42 | 0.28 | 0.45 | 0.28 | 0.46 | 0.23 | 0.60 | 0.21 | 0.64 | 0.22 | 0.60 | 0.17 | 0.69 | 0.30 | 0.52 | 0.31 | 0.50 |
I3 | 0.33 | 0.47 | 0.48 | 0.29 | 0.49 | 0.24 | 0.27 | 0.55 | 0.27 | 0.53 | 0.26 | 0.53 | 0.26 | 0.54 | 0.30 | 0.47 | 0.29 | 0.50 | 0.29 | 0.53 | 0.28 | 0.56 | 0.25 | 0.50 |
I4 | 0.39 | 0.39 | 0.32 | 0.48 | 0.22 | 0.59 | 0.34 | 0.39 | 0.28 | 0.47 | 0.30 | 0.45 | 0.24 | 0.54 | 0.34 | 0.38 | 0.30 | 0.46 | 0.43 | 0.35 | 0.22 | 0.61 | 0.23 | 0.60 |
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[4] | SONG Tao, SUN Man, LIANG Yutian, Soavapa NGAMPRAMUAN, WUZHATI Yeerken, ZHOU Keyang. Variegated transnational partnerships: Multi-scalar actor networks in China’s overseas industrial parks [J]. Journal of Geographical Sciences, 2021, 31(5): 664-680. |
[5] | LIU Hui, GU Weinan, LIU Weidong, WANG Jiaoe. The influence of China-Europe Railway Express on the production system of enterprises: A case study of TCL Poland Plant [J]. Journal of Geographical Sciences, 2021, 31(5): 699-711. |
[6] | LIANG Yutian, ZENG Jiaqi, KUIK Cheng-Chwee, ZHOU Zhengke, ZHOU Keyang. Policy transfer and scale reconstruction of China’s overseas industrial parks: A case study of the Malaysia-China Kuantan Industrial Park [J]. Journal of Geographical Sciences, 2021, 31(5): 733-746. |
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[8] | FAN Zemeng. Spatial identification and scenario simulation of the ecological transition zones under the climate change in China [J]. Journal of Geographical Sciences, 2021, 31(4): 497-517. |
[9] | HUANG Lin, NING Jia, ZHU Ping, ZHENG Yuhan, ZHAI Jun. The conservation patterns of grassland ecosystem in response to the forage-livestock balance in North China [J]. Journal of Geographical Sciences, 2021, 31(4): 518-534. |
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[13] | WEI Wei, GUO Zecheng, SHI Peiji, ZHOU Liang, WANG Xufeng, LI Zhenya, PANG Sufei, XIE Binbin. Spatiotemporal changes of land desertification sensitivity in northwest China from 2000 to 2017 [J]. Journal of Geographical Sciences, 2021, 31(1): 46-68. |
[14] | MA Bin, ZHANG Bo, JIA Lige. Spatio-temporal variation in China’s climatic seasons from 1951 to 2017 [J]. Journal of Geographical Sciences, 2020, 30(9): 1387-1400. |
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