干旱区生态环境知识资源中心(Arid): A Study on Evaporation Calculations of Agricultural Reservoirs in Hyper-Arid Areas

Arid

DOI	10.3390/agriculture12050612
	A Study on Evaporation Calculations of Agricultural Reservoirs in Hyper-Arid Areas
	Yin, Changjun; Liu, Yunfei; Gui, Dongwei; Liu, Yi; Lv, Wengai
通讯作者	Gui, DW
来源期刊	AGRICULTURE-BASEL
EISSN	2077-0472
出版年	2022
卷号	12 期号:5
英文摘要	Free surface evaporation is an important process in regional water cycles and energy balance. The accurate calculation of free surface evaporation is of great significance for evaluating and managing water resources. In order to improve the accuracy of estimating reservoir evaporation in data-scarce arid regions, the applicability of the energy balance method was assessed to calculate water surface evaporation based on the evaporator and reservoir evaporation experiment. A correlation analysis was used to assess the major meteorological factors that affect water surface temperature to obtain the critical parameters of the machine learning models. The water surface temperature was simulated using five machine learning algorithms, and the accuracy of results was evaluated using the root mean square error (RMSE), correlation coefficient (r), mean absolute error (MAE), and Nash efficiency coefficient (NSE) between observed value and calculated value. The results showed that the correlation coefficient between the evaporation capacity of the evaporator, calculated using the energy balance method and the observed evaporation capacity, was 0.946, and the RMSE was 0.279. The r value between the calculated value of the reservoir evaporation capacity and the observed value was 0.889, and the RMSE was 0.241. The meteorological factors related to the change in water surface temperature were air temperature, air pressure, relative humidity, net radiation and wind speed. The correlation coefficients were 0.554, -0.548, -0.315, -0.227, and 0.141, respectively. The RMSE and MAE values of five models were: RF (0.464 and 0.336), LSSVM (0.468 and 0.340), LSTM (1.567 and 1.186), GA-BP (0.709 and 0.558), and CNN (1.113 and 0.962). In summary, the energy balance method could accurately calculate the evaporation of evaporators and reservoirs in hyper-arid areas. As an important calculation parameter, the water surface temperature is most affected by air temperature, and the RF algorithm was superior to the other algorithms in predicting water surface temperature, and it could be used to predict the missing data. The energy balance model and random forest algorithm can be used to accurately calculate and predict the evaporation from reservoirs in hyper-arid areas, so as to make the rational allocation of reservoir water resources.
英文关键词	arid area agricultural reservoir energy balance water surface temperature machine learning
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000802425000001
WOS关键词	SUPPORT VECTOR MACHINE ; CLIMATE-CHANGE ; WATER-USE ; MODELS ; EVAPOTRANSPIRATION ; CALIBRATION
WOS类目	Agronomy
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/391676
推荐引用方式 GB/T 7714	Yin, Changjun,Liu, Yunfei,Gui, Dongwei,et al. A Study on Evaporation Calculations of Agricultural Reservoirs in Hyper-Arid Areas[J],2022,12(5).
APA	Yin, Changjun,Liu, Yunfei,Gui, Dongwei,Liu, Yi,&Lv, Wengai.(2022).A Study on Evaporation Calculations of Agricultural Reservoirs in Hyper-Arid Areas.AGRICULTURE-BASEL,12(5).
MLA	Yin, Changjun,et al."A Study on Evaporation Calculations of Agricultural Reservoirs in Hyper-Arid Areas".AGRICULTURE-BASEL 12.5(2022).