Abstract

To achieve accurate evaluation of evapotranspiration of reference crops (ET0) in Jiangxi, China, in the absence of systematic climatological data, with reference to the FAO-56 Penman–Monteith (P-M) equation, the Priestley-Taylor (P–T) method, the Makkink method, the Hargreaves-Samani (H–S) method, the Irmak-Allen (I-A) method, the Penman1948 (48PM) method, the Penman-Van Bavel (PVB) method, the Baier-Robertson (B-R) method, the improved Baier-Robertson (M-B-R) method, the Schendel (Sch) method, the Turc method, the Jensen-Haise (J-H) method, and the Brutsaert-Stricker (B-S) method were used to evaluate the daily climatological data collected by 26 weather stations in Jiangxi, China, and 17 weather stations in adjacent provinces. The results were compared with each other and parameter rate determination was conducted. The results indicated that the Turc method exhibited optimized applicability before parameter rate determination and the average root mean square error (RMSE) and the average normalized root mean square error (NRMSE) by this method were 0.39 mm/d and 0.157 mm, respectively. However, parameter rate determination led to negligible improvement in accuracy for this method. The Turc method could be directly applied in Jiangxi (except Nanchang). For special distribution of error after parameter rate determination, all methods exhibited significant errors in Northern Jiangxi. Herein, the 48PM method and the B-S method showed good applicability after parameter rate determination and RMSE and NRMSE of data by these methods ranged in 0.06 ~ 0.34 mm/d and 0.08 ~ 0.27, 8 ~ 27%, respectively, and their d-indices were close to 1. The annual over-estimations in weather stations in Jiangxi were below 30 mm. In the absence of data about relative humidity and wind speed, the P–T method was an appropriate simplified method for Jiangxi. In this case, α was slightly lower than the default value (1.05 ~ 1.18), RMSE was within 0.21 ~ 0.66 mm/d, and NRMSE was within 0.08 ~ 0.308 ~ 30%. Accuracy of RMSE, d-index, and NRMSE of data by the P–T method, the I-A method, and the PVB method was consistent with all stations, while that by the Mak method was slightly lower, which could be attributed to severe over-estimation in July and August. RMSE of the H–S method, the B-R method, the M-B-R method, the J-H method, and the Sch method were above 0.75 mm/d and these methods were not suitable for accurate evaluation of ET0 in Jiangxi, China. The annual ET0 was calculated by various methods (except the 48PM method and the B-S method) exhibited significant variation around 2003. This may be attributed to significant changes in certain meteorological factors over recent years.

Highlights

  • As basic data for determination of water demands of crops, the reference crop evapotranspiration is a key factor affecting the estimation accuracy of water demands of crops (Liu, Li, & Wang, 2006), as well as one of the key factors in irrigation system planning and hydrological model establishment (Allen, Pereira, Raes, & Smith, 1998; Wang, Peng, Yang, Shao, & Xing, 2011)

  • The results indicated that the Turc method exhibited optimized applicability before parameter rate determination and the average root mean square error (RMSE) and the average normalized root mean square error (NRMSE) by this method were 0.39 mm/d and 0.157 mm, respectively

  • Accuracy of RMSE, d-index, and NRMSE of data by the P-T method, the I-A method, and the Penman-Van Bavel (PVB) method were consistent with all stations, while that by the Mak method was slightly lower, which could be attributed to severe overestimation in July and August

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Summary

Introduction

As basic data for determination of water demands of crops, the reference crop evapotranspiration is a key factor affecting the estimation accuracy of water demands of crops (Liu, Li, & Wang, 2006), as well as one of the key factors in irrigation system planning and hydrological model establishment (Allen, Pereira, Raes, & Smith, 1998; Wang, Peng, Yang, Shao, & Xing, 2011). The FAO 24 Penman radiation method (Zhang, Duan, Gao, Shen, & Cai, 2015) and the Penman-Van Bavel (PVB) method (Yuan, Yang, Chen, & Wu, 2014) have attracted great attentions. Applications of these methods are limited by local climate and geographic conditions and many models cannot be directly applied. Wu et al ( 2016) evaluated the applicability of various methods (including the H-S method) in Northwestern China and proposed alternative methods in the absence of climatological data. Reference evapotranspiration estimation is valuable when it is used in calculating actual evapotranspiration

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