干旱区生态环境知识资源中心(Arid): Short-term forecasting of daily reference evapotranspiration using the reduced-set Penman-Monteith model and public weather forecasts

Arid

DOI	10.1016/j.agwat.2018.09.036
	Short-term forecasting of daily reference evapotranspiration using the reduced-set Penman-Monteith model and public weather forecasts
	Yang, Yang 1,2; Cui, Yuanlai 1; Bai, Kaihua 3,4; Luo, Tongyuan 4; Dai, Junfeng 3; Wang, Weiguang 4; Luo, Yufeng 1
通讯作者	Luo, Yufeng
来源期刊	AGRICULTURAL WATER MANAGEMENT
ISSN	0378-3774
EISSN	1873-2283
出版年	2019
卷号	211 页码:70-80
英文摘要	Farm irrigation management and real-time irrigation decisions are based on a series of parameters including irrigation water demand predictions which estimated by the short-term daily reference evapotranspiration (ETo). Based on the temperature data, a simplest empirical model called the temperature-based method, was developed to forecast near-future ETo. Although temperature is one of the most influential weather variables in ETo forecasting, wind velocity also has non-ignorable impact on the forecast performance of ETo. Therefore, we employed the Reduced-set Penman-Monteith (RPM) model for short-term ETo forecasting using temperature data derived from public weather forecasts and wind speed data. Four different types of wind speed data were adopted as model inputs, including wind speed assumed as a default value, i.e., u(2) = 2.0 m s(-1) (W1), forecasted wind speed (W2), long-term daily average wind speed (W3) and annual average wind speed (W4). Based on the above-mentioned wind speed inputs, we presented four types of RPM models (RC, RF, RD and RM models respectively corresponding to W1, W2, W3 and W4) to forecast daily ETo for lead times up to 7 days for eight weather stations in China. The results confirmed that the highest precision wind speed input was W3, followed by W4, W1 and W2, and the most accurate ETo forecasts of four RPM models was provided by RC, followed with RD, RM and RF. By comparing with one of the most common used temperature-based models, the Hargreaves-Samani (HS), it was found that the performance of RPM approaches were better than that of HS model for arid and sub-arid regions whereas opposite results were found in sub-tropical area, suggesting inclusion of wind speed parameter makes positive impact on ETo forecast for arid and semi-arid regions. Further, it was found that the greatest type of RPM model, the RC model, was superior to HS method for most climate regions, including arid, humid, sub-arid and sub-humid areas, thus, the W1 wind speed type could be highly recommended for ETo forecasting for most climate regions.
英文关键词	Reference evapotranspiration forecast Reduced-set Penman-Monteith model Wind speed Public weather forecast Crop water requirement
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000449139500008
WOS关键词	ARTIFICIAL NEURAL-NETWORK ; SUPPORT VECTOR MACHINE ; TEMPERATURE ; PREDICTION ; EQUATIONS ; RADIATION
WOS类目	Agronomy ; Water Resources
WOS研究方向	Agriculture ; Water Resources
来源机构	河海大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/213973
作者单位	1.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Hubei, Peoples R China; 2.Changjiang Survey Planning Design & Res Co Ltd, Wuhan 430010, Hubei, Peoples R China; 3.Guilin Univ Technol, Coll Environm Sci & Engn, Guilin 541004, Guangxi, Peoples R China; 4.Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210098, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Yang, Yang,Cui, Yuanlai,Bai, Kaihua,et al. Short-term forecasting of daily reference evapotranspiration using the reduced-set Penman-Monteith model and public weather forecasts[J]. 河海大学,2019,211:70-80.
APA	Yang, Yang.,Cui, Yuanlai.,Bai, Kaihua.,Luo, Tongyuan.,Dai, Junfeng.,...&Luo, Yufeng.(2019).Short-term forecasting of daily reference evapotranspiration using the reduced-set Penman-Monteith model and public weather forecasts.AGRICULTURAL WATER MANAGEMENT,211,70-80.
MLA	Yang, Yang,et al."Short-term forecasting of daily reference evapotranspiration using the reduced-set Penman-Monteith model and public weather forecasts".AGRICULTURAL WATER MANAGEMENT 211(2019):70-80.