西北地区地表太阳总辐射计算模型适用性评价
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摘要
为有效提高中国西北地区Rs预报精度,选取西北地区11个代表性气象站点1959—2015年逐日气象数据,评价了4种基于日照时数的Rs计算模型(Angstrom-Prescott,Ogelman,Bahel和Louche模型)和2种基于温度的Rs计算模型(Hargreaves和Bristow-Campbell模型)在西北地区4个分区(温带大陆性高温干旱区、温带大陆性干旱区、高原大陆性半干旱区和温带季风半干旱区)的适用性.结果表明:6种模型在西北地区的Rs模拟值与实测值均在P<0.001水平具有统计学意义;基于日照时数的Rs计算模型(R2介于0.901～0.903)精度高于基于温度的模型(R2介于0. 695～0. 719);其中,基于日照时数的模型中Bahel模型的精度最高,其R2,MAE,MRE,RMSE和NSE分别为0.903,1.624 MJ/(m2·d),15.7%,2.298 MJ/(m2·d)和0.902;基于温度的模型中Bristow-Campbell模型精度最高,其值分别为0.719,2.851 MJ/(m2·d),30.7%,3.959 MJ/(m2·d)和0. 713.因此,为有效提高西北地区Rs日值和月值预报精度,在仅有温度资料时推荐使用Bristow-Campbell模型,在仅有日照时数资料时推荐使用Bahel模型.
To effectively improve the prediction accuracy of Rsin 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 models)and two kinds of temperature-based models(Hargreaves and Bristow-Campbell models) were evaluated in four sub-zones,which are 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 Rsresults 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 of0.903,MAE of 1.624 MJ/(m2·d),MRE of 15.7%,RMSE of 2.298 MJ/(m2·d) and NSE of0.902.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 Rswhen only the sunshine duration data are avai-lable in Northwest China and the Bristow-Campbell model is recommended to estimate Rswhen only temperature data are available.
To effectively improve the prediction accuracy of Rsin 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 models)and two kinds of temperature-based models(Hargreaves and Bristow-Campbell models) were evaluated in four sub-zones,which are 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 Rsresults 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 of0.903,MAE of 1.624 MJ/(m2·d),MRE of 15.7%,RMSE of 2.298 MJ/(m2·d) and NSE of0.902.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 Rswhen only the sunshine duration data are avai-lable in Northwest China and the Bristow-Campbell model is recommended to estimate Rswhen only temperature data are available.
引文
[1]TEKE A,YILDIRIM H B,CELIK O.Evaluation and performance comparison of different model for the estimation of solar radiation[J].Renewable and sustainable energy reviews,2015,50:1097-1107.
[2]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.
[3]ZHANG H,XIN X,LI L,et al.Estimating global solar radiation using a hybrid parametric model from MODISdata over the Tibetan Plateau[J].Solar energy,2015,112:373-382.
[4]闫明,刘鹏举,蒋育昊,等.基于DEM与太阳辐射的北京市山地坡向提取方法研究[J].北京林业大学学报,2018,40(1):67-73.YAN Ming,LIU Pengju,JIANG Yuhao,et al.Extraction 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)
[5]GAIRAA K,KHELLAF A,MESSLEM Y,et al.Estimation of the daily global solar radiation based on BoxJenkins and Ann models:a combined approach[J].Renewable and sustainable energy reviews,2016,57:238-249.
[6]张皓杰,崔宁博,徐颖,等.基于ELM的西北旱区参考作物蒸散量预报模型[J].排灌机械工程学报,2018,36(8):779-784.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)
[7]OGELMAN H,ECEVIT A,TASDEMIROGLU E.A new method for estimating solar radiation from bright sunshine data[J].Solar energy,1984,33(6):619-625.
[8]BAHEL V,BAKHSH H,SRINIVASAN R.A correlation for estimation of global solar radiation[J].Energy,1987,12(2):131-135.
[9]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.
[10]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.
[11]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.
[12]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.
[13]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.
[14]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.
[2]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.
[3]ZHANG H,XIN X,LI L,et al.Estimating global solar radiation using a hybrid parametric model from MODISdata over the Tibetan Plateau[J].Solar energy,2015,112:373-382.
[4]闫明,刘鹏举,蒋育昊,等.基于DEM与太阳辐射的北京市山地坡向提取方法研究[J].北京林业大学学报,2018,40(1):67-73.YAN Ming,LIU Pengju,JIANG Yuhao,et al.Extraction 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)
[5]GAIRAA K,KHELLAF A,MESSLEM Y,et al.Estimation of the daily global solar radiation based on BoxJenkins and Ann models:a combined approach[J].Renewable and sustainable energy reviews,2016,57:238-249.
[6]张皓杰,崔宁博,徐颖,等.基于ELM的西北旱区参考作物蒸散量预报模型[J].排灌机械工程学报,2018,36(8):779-784.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)
[7]OGELMAN H,ECEVIT A,TASDEMIROGLU E.A new method for estimating solar radiation from bright sunshine data[J].Solar energy,1984,33(6):619-625.
[8]BAHEL V,BAKHSH H,SRINIVASAN R.A correlation for estimation of global solar radiation[J].Energy,1987,12(2):131-135.
[9]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.
[10]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.
[11]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.
[12]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.
[13]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.
[14]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.