| Rational distribution of irrigation water is the premise to improve crop yield,also an important measure to solve the problem of regional water shortage and the sustainable development of agriculture.In order to ensure the sustainable development of agriculture,increase food production and solve the problem that the development of sugarcane planting industry in Guangxi is vulnerable to the uneven spatial distribution of water resources,finding suitable irrigation measures is the key to solve the problem of regional water shortage.Although traditional deficit irrigation saves regional water resources allocation,it has high economic cost and long time period.Therefore,the crop model provides an effective solution to the problem of traditional deficit irrigation.However,the optimal allocation of agricultural irrigation is complex.There are various methods to solve the optimization problem by crop model.Temperature and rainfall will affect the optimal allocation result.Therefore,it is urgent to describe the potential relationship between irrigation and main influencing factors,establish efficient and scientific optimization model,improve solving efficiency and determine the optimal irrigation allocation scheme.The experimental data of this study are from the sugarcane watersaving irrigation project base in Jiangzhou District,Chongzuo City,Guangxi Zhuang Autonomous Region.The study combined with the law of regional irrigation water use,the optimization model of field irrigation amount was constructed based on DSSAT model and genetic algorithm.It provides solutions to optimize deficit irrigation in Guangxi.The main contents and results of the study are as follows:(1)The soil and meteorological database of Guangxi regional test station was established by DSSAT model,and the sugarcane parameters were standardization.The crop was irrigated at seedling,tillering,elongation,and mature stage with 10 mm(T1),20 mm(T2),30 mm(T3)and 40 mm(T4)of water respectively,with irrigation of 50 mm taken as the control(CK).Overall,there were 17 treatments and they randomly arranged in the field.Crop growth and development in each treatment was simulated using the DSSAT model,from which we calculated the change in water productivity(WUE),irrigation water use efficiency(IWUE)and the ultimate crop yield.The theoretical basis of optimization was established,analysis and determination of growth stage conditions and optimum irrigation period for optimal irrigation allocation.(2)The optimization model of field irrigation quantity was established.The optimization model aimed at maximum yield and sets the constraint conditions for the maximum irrigation quota and irrigation quota in the field.DSSAT model was used to simulate different deficit irrigation treatments,and crop water production function and soil water balance equation were selected to determine the decision variables and objective function of the optimization model.Five irrigation treatments(40,80,120,160 and 200 mm)were optimized by genetic algorithm and particle swarm optimization.Firstly,the feasibility of the optimization algorithm is determined by comparing the yield and water productivity that are not optimized by the two optimization algorithms,Then,the optimization effect between the other optimization algorithms is compared to determine the optimization ability and applicability of the genetic algorithm.The scheme of algorithm optimization shows that genetic algorithm is superior to unoptimized results in improving yield and WUE.Under the 120 mm treatment and 160 mm treatment,the yield of the algorithm optimized under field deficit irrigation increased by 2.5% and 8.7%,respectively,the optimized WUE was superior to the non-optimized deficit irrigation except for the 40 mm treatment.The results show that the genetic algorithm can solve the optimization problem of sugarcane deficit irrigation in Guangxi,and achieve the goal of stabilizing regional yield and maximizing water productivity. |
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