WEI Jun1
,CUI Ning-bo1,2
,CHEN Yu-lin1
,ZHANG Qing-wen1
,
FENG Yu1,3
,GONG Dao-zhi
4
,WANG Ming-tian5
China Rural Water and Hydropower. 2018, (8):
35-39.
Download PDF
(
)
Knowledge map
 
Save
In order to effectively improve the forecast accuracy of reference crop evapotranspiration (ET0) in the Northwest China, six representative meteorological stations were selected in the northwest region, and the ET0 calculated using the PM model was used as the standard value, using the daily meteorological data from 1993 to 2016. Ten extreme machine learning ET0 forecasting models were used to estimate the model generalization error by k-fold cross-validation and calculated with the four types of Hargreaves-Samani, Chen, EI-Sebail and Bristow in the northwestern region. Higher accuracy models are compared. Results show: ELM1 (input Tmax, Tmin, RH, n, and u2), ELM2 (input Tmax, Tmin, n and u2), ELM4 (input Tmax, Tmin RH and u2) and ELM7 (input Tmax, Tmin and u2) All the models have high simulation accuracy with MAE of 0.199, 0.209, 0.250, 0.273, RMSE of 0.270, 0.285, 0.341, 0.422, NSE of 0.983, 0.981, 0.973, 0.987, and R2 of 0.984, 0.982, 0.975 respectively. , 0.960. The global performance indicator rankings were 1, 2, 3, and 4 respectively; model portability analysis showed that the ELM model has strong generalization ability, in addition to the relatively low simulation accuracy of ELM7 between Dunhuang and Kashgar rivers, the MAE of the remaining models at different sites in the Northwest China was 0.40. Below, RMSE is all below 0.49, NSE is above 0.95, and R2 is all above 0.96. the ELM model has strong generalization ability; in the case of the same input The simulation accuracy of the lower ELM model is higher than Hargreaves-Samani, Chen, EI-Sebail and Bristow. Therefore, in the absence of meteorological data, the ELM model can be used as a recommended model for the calculation of ET0 in the Northwest China.