Evaluation on applicability of global solar radiation calculation model in Northwest China
ZHANG Yixuan1, CUI Ningbo1,2*, FENG Yu1,3, YUE Jinhua4, WANG Jun4, LIU Shuangmei5
1. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, Sichuan 610065, China; 2. Provincial Key Laboratory of Water-Saving Agriculture in Hill Area of Southern China, Chengdu, Sichuan 610066, China; 3. State Engineering Laboratory for Efficient Water Use and Disaster Loss Reduction of Crops, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agriculture Sciences, Beijing 100081, China; 4. Beijing Zhongnong Xingwang Planning and Design Consultion Co.Ltd., Beijing 100102, China; 5. Sichuan Institute of Water Resources Science, Chengdu, Sichuan 610065, China
Abstract To effectively improve the prediction accuracy of Rs in Northwest China, the daily climate data collected from 11 representive meteorological stations during 1959—2015 were used to estimate Rs. Four kinds of sunshine-based models(Angstrom-Prescott, Ogelman, Bahel and Louche model)and two kinds of temperature-based models(Hargreaves and Bristow-Campbell model)were evaluated in four sub-zones: the temperate continental high temperature-arid zone, the temperate continental arid zone, the plateau continental semiarid zone and the temperate monsoon semiarid zone. The results show that the estimate Rs results of each model has a significant correlation with the measured value at the 0.001 level. Generally, the applicability of sunshine-based model(with R2 ranging from 0.901 to 0.903)is better than that of temperature-based model(with R2 ranging from 0.695 to 0.719). Among the 4 sunshine-based models, Bahel model shows the best performance, with R2 of 0.903, MAE of 1.624 MJ/(m2·d), MRE of 15.7%, RMSE of 2.298 MJ/(m2·d)and NSE of 0.902. The most accurate temperature-based model is Bristow-Campbell model, with R2 of 0.719, MAE of 2.851 MJ/(m2·d), MRE of 30.7%, RMSE of 3.959 MJ/(m2·d)and NSE of 0.713. Overall, the Bahel model is recommended to estimate daily and monthly Rs when only the sunshine duration data are avai-lable in Northwest China and the Bristow-Campbell model is recommended to estimate Rs when only temperature data are available.
ZHANG Yi-Xuan-,CUI Ning-Bo-,* et al. Evaluation on applicability of global solar radiation calculation model in Northwest China[J]. Journal of Drainage and Irrigation Machinery Engin, 2019, 37(6): 545-552.
TEKE A, YILDIRIM H B, CELIK O. Evaluation and performance comparison of different model for the estimation of solar radiation[J]. Renewable and sustaina-ble energy reviews, 2015, 50: 1097-1107.
BESHARAT F, DEHGHAN A A, FAGHIH A R. Empirical models for estimating global solar radiation: a review and case study[J]. Renewable and sustainable energy reviews, 2013, 21(21): 798-821.
ZHANG H, XIN X, LI L, et al. Estimating global solar radiation using a hybrid parametric model from MODIS data over the Tibetan Plateau[J]. Solar energy, 2015, 112: 373-382.
YAN Ming, LIU Pengju, JIANG Yuhao, et al. Extra-ction method of slope aspect based on DEM and solar radiation in mountain area of Beijing[J]. Journal of Beijing Forestry University, 2018, 40(1): 67-73.(in Chinese)
GAIRAA K, KHELLAF A, MESSLEM Y, CHELLALI F. Estimation of the daily global solar radiation based on Box-Jenkins and Ann models: a combined approach[J]. Renewable and sustainable energy reviews, 2016,57:238-249.
ZHANG Haojie,CUI Ningbo,XU Ying, et al. Prediction for reference crop evapotranspiration in arid northwest China based on ELM[J]. Journal of drainage and irrigation machinery engineering, 2018, 36(8): 779-784.(in Chinese)
OGELMAN H, ECEVIT A, TASDEMIROGLU E. A new method for estimating solar radiation from bright sun-shine data[J]. Solar energy, 1984, 33(6): 619-625.
BAHEL V, BAKHSH H, SRINIVASAN R. A correla-tion for estimation of global solar radiation[J]. Energy, 1987, 12(2): 131-135.
CITAKOGLU H. Comparison of artificial intelligence techniques via empirical equations for prediction of solar radiation[J]. Computers and electronics in agriculture, 2015, 118: 28-37.
MUHAMMED A H, KHALIL A, KASEB S, et al. Potential of four different machine-learning algorithms in modeling daily global solar radiation[J]. Renewable energy, 2017, 111:52-62.
CHEN R S, KANG E, YANG J P, et al. Validation of five global radiation models with measured daily data in China[J]. Energy conversion and management, 2004, 45(11/12): 1759-1769.
LIU Y F, ZHOU Y, WANG D J, et al. Classification of solar radiation zones and general models for estimating the daily global solar radiation on horizontal surfaces in china[J]. Energy conversion and management, 2017, 154:168-179.
JAHANI B, DINPASHOH Y, NAFCHI A R. Evaluation and development of empirical models for estimating daily solar radiation[J]. Renewable and sustainable energy reviews, 2017, 73: 878-891.
ALLEN R G, PEREIRA L S, RAES D, et al. Crop evapotranspiration-guidelines for computing crop water requirements-FAO irrigation and drainage paper 56[M]. Rome:Food and Agriculture Organization of the United Nations, 1998.