Research on the Optimal Water Allocation of Rice Under Insufficient Irrigation Conditions
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Rice is the representative of hydrophilic and humid crops, which consumes a large amount of water in the field. Southern China is the main rice-producing area. Relatively, weak water-saving awareness under the condition of abundant rainfall, climate change, and seasonal drought results in water shortage increasingly prominent. Based on the comprehensive consideration of rice water demand, water production function, water sensitivity index, and so on, an optimal allocation model of irrigation water under insufficient irrigation conditions is constructed to maximize the total yield of rice crops. The multi-constraint model is solved by the target approximation algorithm and the genetic algorithm. The results show that the genetic algorithm can effectively allocate the limited irrigation water.
KeywordsInsufficient irrigation Rice crops Optimal water allocation
Based on rice water requirement, water production function, and water sensitivity index, this paper adopts an optimal allocation model under the condition of inadequate irrigation that is established by taking maximum the total yield of field crops as the objective function, solves the multi-constraint model by means of target approximation algorithm and genetic algorithm, compares and analyzes the results. The results show that the genetic algorithm can effectively solve the optimal allocation of irrigation water and strictly meet the equality constraints compared with the target approximation algorithm; the optimal allocation model of irrigation water can reasonably distribute the limited irrigation water, so as to maximize the water production function and maximize the irrigation benefits.
- 1.Wang H, Guo P, Zhang F. Research on dual-interval programming for optimal irrigation model of three crops in Minqin County, Wuwei City. J China Agric Univ. 2018;23(02):72–8.Google Scholar
- 2.Jiang X, Chen W. Comparison between BP neural network and GA-BP crop water demand forecasting model. J Drainage Irrig Mach Eng. 2018;8:762–6.Google Scholar
- 3.Xu W, Su X, Shi Y, Nan C, Yang X. The optimization of agricultural planting structure and irrigation system based on the efficient use of water resources—a case study of minqin. 2011;18(01):205–209.Google Scholar
- 4.Ou D, Xia J, Zhang L, Zhao Z. Optimized model and algorithm for multi-crop planting structures and irrigation amount. 2013;21(12):1515–1525.Google Scholar
- 5.Zhang B, Yuan S, Li H, Cong X, Zhao B. Optimized irrigation-yield model for winter wheat based on genetic algorithm. Trans Chin Soc Agric Eng. 2006;08:12–15.Google Scholar
- 6.Yang X, Chai Q, Xie J. Irrigation optimization model and algorithm based on maximum total gains of multiple crops. China Rural Water Hydropower. 2015;05:11–13 + 22.Google Scholar
- 7.Qu H, Lu W, Bao X, Yang W. Dynamic planning model of water saving irrigation in North water deficit zone. Water Resour Hydropower Northeast China. 2006;12:53–55 + 72.Google Scholar
- 8.Pan L, Xiao X, Lei Y. Application of the SAGA optimization method in optimum distribution of irrigation water. Water Saving Irrig. 2006;06:45–47.Google Scholar
- 9.Yang L, Qiu YM, Zhang HY, Wang F. The Study of decision support system on water resources optimal allocation in irrigation area based on unsufficient irrigation. Water Saving Irrig. 2012;02:53–6.Google Scholar
- 10.Cui Y. Optimal allocation of water and land in rice irrigation area under limited irrigation water supply. Eng J Wuhan Univ Eng Ed. 2002;04:18–21 + 26.Google Scholar