基于修正遗传算法的夏玉米作物系数及蒸散发估算

农田蒸散量是作物蒸腾量和土壤蒸发量的总和,准确估算农田蒸散量对制定合理的灌溉计划至关重要,进而对农作物的增产保收具有重要的意义。研究作物系数及蒸散量估算模型已成为一个热点科学问题。淮河流域是中国主要的农业生产基地,而夏玉米是淮河流域最主要的粮食作物之一。为研究夏玉米全生育期蒸散估算模型,反映夏玉米逐日作物系数及蒸散量的变化,为当地的农业生产活动提供指导,采用五道沟水文实验站称重式蒸渗仪及气象要素实测数据,应用遗传算法,构建夏玉米全生育期单作物系数蒸散模型,得到其4个生长阶段的作物系数估算值。其中,参考作物蒸散量采用FAO PenmanMonteith公式计算;对估算误差较大的发育期,利用叶面积指数和发育期天数构建调整模型,对发育期作物系数进行数值修正,取得了较好的效果,并进一步估算蒸散量,最终得到遗传算法与多项式回归相结合的夏玉米蒸散估算模型。结果表明:全生育期内,修正后作物系数计算值与实际值的平均绝对误差为0.09,均方根误差为0.12,准确率(绝对误差<0.3)为96.2%;蒸散量计算值与实际值的平均绝对误差为0.89 mm·d^-1,均方根误差为1.28 mm·d^-1,准确率(绝对误差<4 mm·d^-1)为100%;相比FAO推荐的作物系数模型,修正遗传算法模型作物系数和蒸散量的拟合准确率均明显提高,达到精度要求,该文修正遗传算法模型可用于夏玉米的蒸散估算。

Estimation of Summer Maize Crop Coefficient and Evapotranspiration Based on Modified Genetic Algorithm

Evapotranspiration is the sum of soil evaporation and crop evapotranspiration. It plays an important role in the energy cycle and water cycle on the earth’s surface. Accurate estimation of farmland evapotranspiration is also crucial to formulating a reasonable irrigation plan. In this paper, we use the data recorded by the weighing lysimeter and the measured data of various meteorological factors in the same period, and choose summer maize in Shajiang black soil with a groundwater depth of 1 m as the research object, the research stage is the entire growth period of maize. In this paper, genetic algorithm is used to establish a single crop coefficient evapotranspiration model during the whole growth period of summer maize. Considering the error of the calculation results of the algorithm, we use the leaf area index to construct an adjustment model, and the crop coefficients during the growth period are numerically corrected. Finally, we obtain a summer maize evapotranspiration estimation model combining genetic algorithm and polynomial regression. This model can be used to calculate the evapotranspiration during the whole growth period of summer maize within a small error. In order to further verify the applicability of the model, we compare this model with the crop coefficient model recommended by FAO, and compare the difference in the accuracy of the two in calculating crop coefficient and evapotranspiration. The research results show that during the whole growth period, the average absolute error between the corrected crop coefficient calculated value and the actual value is 0.09, the root mean square error is 0.12, and the accuracy rate(absolute error<0.3) is 96.2%;the average absolute error between the calculated evapotranspiration value and the actual value is 0.89 mm·d^-1;the root mean square error is 1.28 mm·d^-1, and the accuracy rate(absolute error<4 mm·d^-1) is 100%;compared with the crop coefficient model recommended by FAO, the fitting accuracy of crop coefficient and evapotranspiration of the adjusted genetic algorithm model is significantly improved, and meets the accuracy requirements. The adjusted genetic algorithm model proposed in this paper can be used to estimate summer maize evapotranspiration within a certain error tolerance range.