Research on the Water Demand of Rice and Its Influencing Factors
Received date: 2025-05-20
Online published: 2025-07-08
ET0 Calculator and single crop coefficient method were used to calculate the water demand of rice. The effects of rice planting regions, rice types and planting period on water demand of rice in recent 41 years in China were analyzed, and the relative importance of climatic factors affecting water demand was compared to clarify the water demand of rice and its influencing factors in China, and to provide a theoretical basis for the efficient utilization of water in rice. The water demand of rice increases gradually with the growth process. The minimum value of total water demand in the whole growth period is 4 057.0 t/hm2, the maximum value is 9 788.0 t/hm2, and the average value is 6 621.0 t/hm2. The average daily water demand increases first and then decreases. The daily average water demand of the green-returning stage, tillering stage, jointing-booting stage, heading and filling stage and yellow-ripen stage is 50.0, 63.0, 75.0, 64.0 and 37.0 t/hm2·d, respectively. Factors such as rice planting regions, rice types, and planting period have a certain impact on water demand. The water demand of rice in Northeast China, Northeast China, the middle and lower reaches of the Yangtze River, Southern China and Southwest China is 5 161.0~6 111.0, 8 845.0-9 788.0, 5 211.0-9 591.0, 4 057.0-5 676.0 and 7 658.0-8 347.0 t/hm2, respectively. The water demand of early rice, late rice and single rice is 5 211.0-5 891.0, 6 074.0-6 990.0 and 8 428.0-9 545.0 t/hm2, respectively. With the passage of planting period, the water demand of rice shows an increasing trend. Among the climatic factors affecting rice water demand, the relative importance of average temperature, maximum temperature, sunshine hours, minimum temperature, relative humidity, precipitation and wind speed account for 25.5%, 22.9%, 22.6%, 20.9%, 4.9%, 1.7% and 1.5%, respectively.
Key words： rice; water demand; climate; ET0 Calculator
WANG Bin, YANG Cheng, WU Penghao, LI Xiaokun . Research on the Water Demand of Rice and Its Influencing Factors[J]. China Rice, 2025 , 31(4) : 79 -85 . DOI: 10.3969/j.issn.1006-8082.2025.04.014
| [1] | HA M, SCHLEIGER R. Fresh water supply and the water cycle[J]. ASCCC Open Educational Resources Initiative, 2022, 13: 1. |
| [2] | ZHANG L, MA Q M, ZHAO Y B, et al. China’s strictest water policy: Reversing water use trends and alleviating water stress[J]. Journal of Environmental Management, 2023, 345(1): 118 867. |
| [3] | 孙景生, 康绍忠. 我国水资源利用现状与节水灌溉发展对策[J]. 农业工程学报, 2000, 16(2): 1-5. |
| [4] | FAROOQ M, SIDDIQUE K H M, REHMAN H, et al. Rice direct seeding: Experiences, challenges and opportunities[J]. Soil and Tillage Research, 2011, 111(2): 87-98. |
| [5] | 王鹏涛, 延军平, 蒋冲, 等. 华北平原参考作物蒸散量时空变化及其影响因素分析[J]. 生态学报, 2014, 34(19):5589-5 599. |
| [6] | ALLEN R G, PEREIRA L S, RAES D, et al. Crop evapotranspiration-guidelines for computing crop water demands-FAO irrigation and drainage paper 56[R]. Rome, Italy: Food and Agriculture Organization of the United Nations, 1998: 152-223. |
| [7] | JENSEN M E, WRIGHT J L, PRATT B J. Estimating soil moisture depletion from climate, crop and soil data[J]. Transactions of Asabe, 1971, 14(5): 954-959. |
| [8] | ANNANDALE J, JOVANOVIC N, BENADÉ N, et al. Software for missing data error analysis of Penman-Monteith reference evapotranspiration[J]. Irrigation Science, 2001, 21(2): 57-67. |
| [9] | 刘钰, 汪林, 倪广恒, 等. 中国主要作物灌溉需水量空间分布特征[J]. 农业工程学报, 2009, 25(12): 6-12. |
| [10] | MACLEAN J L, DAWE D C, HARDY B, et al. Rice Almanac: Source book for the most important economic activity on earth[J]. The Journal of Agricultural Science, 2005, 143(1): 110. |
| [11] | 李勇, 杨晓光, 叶清, 等. 1961—2007年长江中下游地区水稻需水量的变化特征[J]. 农业工程学报, 2011, 27(9): 175-183. |
| [12] | 何旭刚, 买买提·沙吾提, 夏梓洋, 等. 1960—2020年新疆主要作物需水量时空特征分析[J]. 作物学报, 2023, 49(12): 3 352-3 363. |
| [13] | 孙博凯, 王卫光, 刘国帅. 大气CO2浓度升高对长江中下游地区水稻灌溉需水量的影响[J]. 水利水电科技进展, 2023, 43(3): 22-27. |
| [14] | MEHMET Y, KALELI A, CORAPSIZ M F. Machine learning based dynamic super twisting sliding mode controller for increase speed and accuracy of MPPT using real-time data under PSCs[J]. Renewable Energy, 2023, 219(1): 119 470. |
| [15] | 于靖. 寒区水稻需水规律及水分胁迫影响研究[D]. 哈尔滨: 东北农业大学, 2013. |
| [16] | 罗万琦, 吕辛未, 吴从林, 等. 中国主要稻区水稻灌溉需求变化及其规律分析[J]. 节水灌溉, 2021(12): 1-7. |
| [17] | 熊剑英, 刘方平. 江西水利普查灌区水稻灌溉用水定额计算方法浅析[J]. 中国水利, 2012(12): 55-56. |
| [18] | 罗玉峰, 彭世彰, 王卫光, 等. 气候变化对水稻灌溉需水量的影响——以高邮灌区为例[J]. 武汉大学学报, 2009, 42(5): 609-613. |
| [19] | 田富强, 胡和平, 杨诗秀. 水稻灌溉制度的计算机模拟[J]. 农业工程学报, 1999, 15(4): 100-103. |
| [20] | 曹言, 王杰, 王树鹏, 等. 气候变化下滇中地区水稻需水量与灌溉需水指数时空变化研究[J]. 干旱地区农业研究, 2020, 38(5): 226-235. |
| [21] | TANG C, LIU D, WEI Y, et al. Spatial-temporal mode analysis and prediction of outgoing longwave radiation over China in 2002—2021 based on atmospheric infrared sounder data[J]. Atmosphere, 2022, 13(3): 400. |
| [22] | PEARSON K. Notes on the history of correlation[J]. Biometrika, 1920, 13: 25-45. |
| [23] | GROEMPING U. Relative importance for linear regression in R: The package relaimpo[J]. Journal of Statistical Software, 2006, 17(1): 1-27. |
| [24] | FRICH P, ALEXANDER L V, DELLA M P, et al. Peterson observed coherent changes in climatic extremes during the second half of the twentieth century[J]. Climate Research, 2002, 19(3): 193-212. |
| [25] | 邢贞相, 喻熠, 李凤昱, 等. 建三江主要作物需水量变化趋势与关键影响因子识别[J]. 农业机械学报, 2022, 53(7): 308-315. |
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