BAO Lingling,YANG Yonggang,LIU Jianjun,et al.Calculation of Reference Crop Evapotranspiration in Chongqing Based on 5 Artificial Intelligent Models[J].Research of Soil and Water Conservation,2021,28(01):85-92.
基于5种人工智能模型计算重庆地区参考作物蒸散量
- Title:
- Calculation of Reference Crop Evapotranspiration in Chongqing Based on 5 Artificial Intelligent Models
- 文章编号:
- 1005-3409(2021)01-0085-08
- Keywords:
- Chongqing; reference crop evapotranspiration; artificial intelligent models; empirical model; sunshine hours
- 分类号:
- S161.4
- 文献标志码:
- A
- 摘要:
- 为获得计算重庆地区参考作物蒸散量(Reference crop evapotranspiration,ET0)的最优模型,选用支持向量机模型(SVM)、高斯指数模型(GEM)、随机森林模型(RF)、极限学习机模型(ELM)和广义回归神经网络模型(GRNN)5种人工智能模型,以丰都、奉节、沙坪坝、万州、酉阳共5个站点1991—2016年的逐日气象数据为基础,估算ET0日值、月值,并与Penman-Monteith(P-M)计算结果进行了对比,结果表明:不同模型精度存在差异,在相同气象参数输入的情况下,人工智能模型计算精度要高于经验模型,在相同参数输入的情况下,GEM模型误差指标最低而一致性指标最高,日照时数n是影响重庆地区ET0变化和影响模型精度的最关键因素,而GEM模型为重庆地区ET0估算的最优人工智能模型。
- Abstract:
- In order to obtain the optimal model for calculating reference crop evapotranspiration(ET0)in Chongqing, the five artificial intelligent models such as support vector machines(SVM), Gaussian exponential model(GEM), random forest model(RF), extreme learning machine model(ELM)and generalized regression neural network model(GRNN)were used as the calculation models. Based on the daily meteorological data from Fengdu, Fengjie, Shapingba, Wanzhou, and Youyang from 1991 to 2016, the daily and monthly ET0 under different combinations of meteorological parameter inputs were estimated, and compared with the calculation results of the standard model Penman-Monteith(PM). The results show that the accuracies of different models are different; under the input of the same meteorological parameters, the calculation accuracy of the artificial intelligence model is higher than that of the empirical model; the error index of the GEM model is the lowest and the consistency index is the highest. Sunshine duration is the most critical factor impacting the accuracy of modeling and change in ET0 in Chongqing. GEM model is the optimal artificial intelligence model to estimate ET0 in Chongqing.
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备注/Memo
收稿日期:2020-02-03 修回日期:2020-03-23
资助项目:重庆市社会民生类重点研发项目“渝东北小微型水利工程防治洪旱灾害关键技术研究”(cstc2018jscx-mszdX0052)
第一作者:鲍玲玲(1981—),女,江苏省无锡市人,硕士,正高级工程师,主要从事水文与水资源研究。E-mail:27729560@qq.com
通信作者:张卫华(1974—),男,河北省沙河市人,博士,副教授,主要从事水文学及水资源研究。E-mail:swuwater@126.com