地表反照率不同计算方法对干旱区流域蒸散反演结果的影响——以新疆三工河流域为例
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摘要
地表蒸散是维持地球表面水量平衡和热量平衡的重要环节,SEBAL模型作为一种快速且有效的反演地表蒸散的遥感物理模型方法,在地表蒸散研究中得到广泛应用。地表反照率作为影响地表能量平衡的重要因素,同时也是SEBAL模型的重要输入参数,因此不同的地表反照率计算方法对SEBAL模型的反演结果有重要影响。以新疆三工河流域为研究区,利用Landsat8 OLI/TIRS数据,以应用最为广泛的Smith地表反照率计算法和Liang地表反照率计算法两种方法计算地表反照率,并输入SEBAL模型中反演日蒸散量,比较分析两种地表反照率计算方法对蒸散反演结果的影响,得出以下结论:(1)两种地表反照率计算方法下经SEBAL模型得到的日蒸散量与实测值拟合程度均较高,不同年份下线性拟合决定系数大于0.75,但是使用Smith方法计算出的地表反照率结合SEBAL模型得到的日蒸散量与实测值拟合程度更高;(2)通过RMSE等精度指标比较两种地表反照率计算方法下基于SEBAL模型反演的日蒸散量,结果显示,Smith地表反照率计算方法下反演的日蒸散量精度略高;(3)Smith地表反照率计算方法下最终得到的区域日均蒸散量高于使用Liang地表反照率计算方法最终得到的区域日均蒸散量,夏季差异最大,差异为0.64 mm/d,其他季节差异较小,差异约为0.2 mm/d。(4)进一步比较研究日内两种地表反照率计算方法得到的地表反照率,结果显示,Smith地表反照率计算法得到的地表反照率均值均小于同时期Liang地表反照率计算法得到的地表反照率均值。
Surface evapotranspiration is an important link for maintaining the water and heat balance of the earth. The SEBAL model is a remote sensing evapotranspiration estimation model used widely in the evapotranspiration research field. Surface albedo is not only a significant factor for the surface energy balance but is a vital input parameter in the SEBAL model. Different surface albedo computing methods will affect the results of the SEBAL model. In this study, we used two surface albedo computing methods, which were proposed by Smith Ronald and Liang Shunlin, respectively, to calculate the surface albedo for the Sangong River Basin in Xinjiang. Then, the calculated surface albedo was input into the SEBAL model to obtain a diary surface evapotranspiration. By analyzing two kinds of evapotranspiration and surface albedo results, we were able to draw several conclusions. The diary evapotranspiration results calculated from the two kinds of surface albedo methods and the SEBAL model fit well with the measured values. The smallest coefficient of determination was 0.75. The evapotranspiration results calculated using Smith′s surface albedo showed a higher correlation with the measured diary evapotranspiration value than that of Liang′s surface albedo. We compared the two diary evapotranspiration results using RMSE and other indicators, and we found that the evapotranspiration results from Smith′s albedo method was more accurate than Liang′s. The average diary evapotranspiration using Smith′s surface albedo was higher than that of Liang′s albedo; the difference was greater in the summer than in the other seasons tested(0.64 mm/d). The difference in the other seasons was smaller(0.2 mm/d). An additional comparison of the two kinds of average surface albedo revealed that the average surface albedo calculated by Smith′s method was less than that of Liang′s method for 6 periods.
Surface evapotranspiration is an important link for maintaining the water and heat balance of the earth. The SEBAL model is a remote sensing evapotranspiration estimation model used widely in the evapotranspiration research field. Surface albedo is not only a significant factor for the surface energy balance but is a vital input parameter in the SEBAL model. Different surface albedo computing methods will affect the results of the SEBAL model. In this study, we used two surface albedo computing methods, which were proposed by Smith Ronald and Liang Shunlin, respectively, to calculate the surface albedo for the Sangong River Basin in Xinjiang. Then, the calculated surface albedo was input into the SEBAL model to obtain a diary surface evapotranspiration. By analyzing two kinds of evapotranspiration and surface albedo results, we were able to draw several conclusions. The diary evapotranspiration results calculated from the two kinds of surface albedo methods and the SEBAL model fit well with the measured values. The smallest coefficient of determination was 0.75. The evapotranspiration results calculated using Smith′s surface albedo showed a higher correlation with the measured diary evapotranspiration value than that of Liang′s surface albedo. We compared the two diary evapotranspiration results using RMSE and other indicators, and we found that the evapotranspiration results from Smith′s albedo method was more accurate than Liang′s. The average diary evapotranspiration using Smith′s surface albedo was higher than that of Liang′s albedo; the difference was greater in the summer than in the other seasons tested(0.64 mm/d). The difference in the other seasons was smaller(0.2 mm/d). An additional comparison of the two kinds of average surface albedo revealed that the average surface albedo calculated by Smith′s method was less than that of Liang′s method for 6 periods.
引文
[1] Bastiaanssen W G M,Pelgrum H,Wang J,Ma Y,Moreno J F,Roerink G J,van der Wal T.A remote sensing surface energy balance algorithm for land (SEBAL).:Part 2:validation.Journal of Hydrology,1998,212- 213:213- 229.
[2] Su Z.The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes.Hydrology and Earth System Sciences,2002,6(1):85- 100.
[3] 吴炳方,熊隽,闫娜娜,杨雷东,杜鑫.基于遥感的区域蒸散量监测方法——ETWatch.水科学进展,2008,19(5):671- 678.
[4] Santos C A G,da Silva R M,Silva A M,Neto R M B.Estimation of evapotranspiration for different land covers in a Brazilian semi-arid region:a case study of the Brígida River basin,Brazil.Journal of South American Earth Sciences,2017,74:54- 66.
[5] Rawat K S,Bala A,Singh S K,Pal R K.Quantification of wheat crop evapotranspiration and mapping:a case study from Bhiwani District of Haryana,India.Agricultural Water Management,2017,187:200- 209.
[6] Alemayehu T,van Griensven A,Senay G B,Bauwens W.Evapotranspiration mapping in a heterogeneous landscape using remote sensing and global weather datasets:application to the Mara Basin,East Africa.Remote Sensing,2017,9(4):390.
[7] 曾丽红,宋开山,张柏,杜嘉.基于SEBAL模型的扎龙湿地蒸散量反演.中国农业气象,2008,29(4):420- 426.
[8] 杜嘉,张柏,宋开山,王宗明,曾丽红.基于MODIS产品和SEBAL模型的三江平原日蒸散量估算.中国农业气象,2010,31(1):104- 110,162- 162.
[9] 曾丽红,宋开山,张柏,王宗明,杜嘉.基于SEBAL模型与MODIS产品的松嫩平原蒸散量研究.干旱区资源与环境,2011,25(1):140- 147.
[10] 张殿君,张学霞,武鹏飞.黄土高原典型流域土地利用变化对蒸散发影响研究.干旱区地理,2011,34(3):400- 408.
[11] 张发耀,王福民,周斌,周柳萍.基于SEBAL模型的浙江省区域蒸散发量估算研究.人民长江,2013,44(17):40- 44.
[12] 王秋云.基于SEBAL模型的北京平原造林区蒸散发量研究[D].南昌:东华理工大学,2016.
[13] 周玲,张丽,许君一,刘广.基于SEBAL模型的漓江流域蒸散发量变化分析.水土保持研究,2015,22(4):332- 337.
[14] 杨肖丽,任立良,雍斌.基于SEBAL模型的老哈河流域蒸散发研究.水电能源科学,2010,28(1):9- 11.
[15] 李宝富,陈亚宁,李卫红,曹志超.基于遥感和SEBAL模型的塔里木河干流区蒸散发估算.地理学报,2011,66(9):1230- 1238.
[16] 张楠楠,王文,王胤.基于HJ- 1B数据和SEBAL模型的陆面蒸散发遥感估算.地理空间信息,2013,11(5):69- 73.
[17] 陈强,苟思,严登华,倪广恒.基于SEBAL模型的区域ET计算及气象参数敏感性分析——以天津市为例.资源科学,2009,31(8):1303- 1308.
[18] Charney J G,Stone P H,Quirk W J.Drought in the Sahara:a biogeophysical feedback mechanism.Science,1975,187(4175):434- 435.
[19] 肖登攀,陶福禄,Moiwo J P.全球变化下地表反照率研究进展.地球科学进展,2011,26(11):1217- 1224.
[20] Grace J,Lloyd J,McIntyre J,Miranda A,Meir P,Miranda H,Moncrieff J,Massheder J,Wright I,Gash J.Fluxes of carbon dioxide and water vapour over an undisturbed tropical forest in south-west Amazonia.Global Change Biology,1995,1(1):1- 12.
[21] Cellier P,Brunet Y.Flux-gradient relationships above tall plant canopies.Agricultural and Forest Meteorology,1992,58(1/2):93- 117.
[22] 颜廷武,尤文忠,张慧东,魏文俊,王睿照,赵刚.辽东山区天然次生林能量平衡和蒸散.生态学报,2015,35(1):172- 179.
[23] Bastiaanssen W G M,Menenti M,Feddes R A,Holtslag A A M.A remote sensing surface energy balance algorithm for land (SEBAL).1.Formulation.Journal of Hydrology,1998,212- 213:198- 212.
[24] 曾丽红,宋开山,张柏,杜嘉.应用Landsat数据和SEBAL模型反演区域蒸散发及其参数估算.遥感技术与应用,2008,23(3):255- 263.
[25] 李根.基于SEBAL和SEBS模型的鹰潭小流域蒸散发估算研究[D].南京:南京信息工程大学,2014.
[26] Liang S L.Narrowband to broadband conversions of land surface albedo I:algorithms.Remote Sensing of Environment,2001,76(2):213- 238.
[27] Morse A T,Tasumi G,Richard A,Willam J K.Application of the Sebal Methodology for Estimating Consumptive Use of Water and Streamflow Depletion in the Bear River Basin of Idaho Through Remote Sensing.Waltham,MA:The Raytheon Systems Company-Earth Observation System Data and Information System Project,2000.
[28] Smith R.Understanding Landsat 8:two methods of computing Albedo.[2017- 12- 13].http://surfaceheat.sites.yale.edu/sites/default/files/files/Albedo.pdf.
[29] Willmott C J.Some comments on the evaluation of model performance.Bulletin of the American Meteorological Society,1982,63(11):1309- 1313.
[30] He T,Liang S L,Wang D D,Gao Y F,Gao F,Yu Y Y,Feng M.Evaluating land surface albedo estimation from Landsat MSS,TM,ETM +,and OLI data based on the unified direct estimation approach.Remote Sensing of Environment,2018,204:181- 196.
[31] 张璐,施润和,徐永明,李龙,高炜.国产遥感传感器大气层外波段平均太阳光谱辐照度计算.地球信息科学学报,2014,16(4):621- 627.
[32] 胡顺石,张立福,张霞,王倩,韩冰,张楠.卫星传感器波段平均太阳辐照度计算及可靠性分析.国土资源遥感,2012,(3):97- 102.
[33] 刘三超,张万昌,蒋建军,赵登忠.用TM影像和DEM获取黑河流域地表反射率和反照率.地理科学,2003,23(5):585- 591.
[2] Su Z.The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes.Hydrology and Earth System Sciences,2002,6(1):85- 100.
[3] 吴炳方,熊隽,闫娜娜,杨雷东,杜鑫.基于遥感的区域蒸散量监测方法——ETWatch.水科学进展,2008,19(5):671- 678.
[4] Santos C A G,da Silva R M,Silva A M,Neto R M B.Estimation of evapotranspiration for different land covers in a Brazilian semi-arid region:a case study of the Brígida River basin,Brazil.Journal of South American Earth Sciences,2017,74:54- 66.
[5] Rawat K S,Bala A,Singh S K,Pal R K.Quantification of wheat crop evapotranspiration and mapping:a case study from Bhiwani District of Haryana,India.Agricultural Water Management,2017,187:200- 209.
[6] Alemayehu T,van Griensven A,Senay G B,Bauwens W.Evapotranspiration mapping in a heterogeneous landscape using remote sensing and global weather datasets:application to the Mara Basin,East Africa.Remote Sensing,2017,9(4):390.
[7] 曾丽红,宋开山,张柏,杜嘉.基于SEBAL模型的扎龙湿地蒸散量反演.中国农业气象,2008,29(4):420- 426.
[8] 杜嘉,张柏,宋开山,王宗明,曾丽红.基于MODIS产品和SEBAL模型的三江平原日蒸散量估算.中国农业气象,2010,31(1):104- 110,162- 162.
[9] 曾丽红,宋开山,张柏,王宗明,杜嘉.基于SEBAL模型与MODIS产品的松嫩平原蒸散量研究.干旱区资源与环境,2011,25(1):140- 147.
[10] 张殿君,张学霞,武鹏飞.黄土高原典型流域土地利用变化对蒸散发影响研究.干旱区地理,2011,34(3):400- 408.
[11] 张发耀,王福民,周斌,周柳萍.基于SEBAL模型的浙江省区域蒸散发量估算研究.人民长江,2013,44(17):40- 44.
[12] 王秋云.基于SEBAL模型的北京平原造林区蒸散发量研究[D].南昌:东华理工大学,2016.
[13] 周玲,张丽,许君一,刘广.基于SEBAL模型的漓江流域蒸散发量变化分析.水土保持研究,2015,22(4):332- 337.
[14] 杨肖丽,任立良,雍斌.基于SEBAL模型的老哈河流域蒸散发研究.水电能源科学,2010,28(1):9- 11.
[15] 李宝富,陈亚宁,李卫红,曹志超.基于遥感和SEBAL模型的塔里木河干流区蒸散发估算.地理学报,2011,66(9):1230- 1238.
[16] 张楠楠,王文,王胤.基于HJ- 1B数据和SEBAL模型的陆面蒸散发遥感估算.地理空间信息,2013,11(5):69- 73.
[17] 陈强,苟思,严登华,倪广恒.基于SEBAL模型的区域ET计算及气象参数敏感性分析——以天津市为例.资源科学,2009,31(8):1303- 1308.
[18] Charney J G,Stone P H,Quirk W J.Drought in the Sahara:a biogeophysical feedback mechanism.Science,1975,187(4175):434- 435.
[19] 肖登攀,陶福禄,Moiwo J P.全球变化下地表反照率研究进展.地球科学进展,2011,26(11):1217- 1224.
[20] Grace J,Lloyd J,McIntyre J,Miranda A,Meir P,Miranda H,Moncrieff J,Massheder J,Wright I,Gash J.Fluxes of carbon dioxide and water vapour over an undisturbed tropical forest in south-west Amazonia.Global Change Biology,1995,1(1):1- 12.
[21] Cellier P,Brunet Y.Flux-gradient relationships above tall plant canopies.Agricultural and Forest Meteorology,1992,58(1/2):93- 117.
[22] 颜廷武,尤文忠,张慧东,魏文俊,王睿照,赵刚.辽东山区天然次生林能量平衡和蒸散.生态学报,2015,35(1):172- 179.
[23] Bastiaanssen W G M,Menenti M,Feddes R A,Holtslag A A M.A remote sensing surface energy balance algorithm for land (SEBAL).1.Formulation.Journal of Hydrology,1998,212- 213:198- 212.
[24] 曾丽红,宋开山,张柏,杜嘉.应用Landsat数据和SEBAL模型反演区域蒸散发及其参数估算.遥感技术与应用,2008,23(3):255- 263.
[25] 李根.基于SEBAL和SEBS模型的鹰潭小流域蒸散发估算研究[D].南京:南京信息工程大学,2014.
[26] Liang S L.Narrowband to broadband conversions of land surface albedo I:algorithms.Remote Sensing of Environment,2001,76(2):213- 238.
[27] Morse A T,Tasumi G,Richard A,Willam J K.Application of the Sebal Methodology for Estimating Consumptive Use of Water and Streamflow Depletion in the Bear River Basin of Idaho Through Remote Sensing.Waltham,MA:The Raytheon Systems Company-Earth Observation System Data and Information System Project,2000.
[28] Smith R.Understanding Landsat 8:two methods of computing Albedo.[2017- 12- 13].http://surfaceheat.sites.yale.edu/sites/default/files/files/Albedo.pdf.
[29] Willmott C J.Some comments on the evaluation of model performance.Bulletin of the American Meteorological Society,1982,63(11):1309- 1313.
[30] He T,Liang S L,Wang D D,Gao Y F,Gao F,Yu Y Y,Feng M.Evaluating land surface albedo estimation from Landsat MSS,TM,ETM +,and OLI data based on the unified direct estimation approach.Remote Sensing of Environment,2018,204:181- 196.
[31] 张璐,施润和,徐永明,李龙,高炜.国产遥感传感器大气层外波段平均太阳光谱辐照度计算.地球信息科学学报,2014,16(4):621- 627.
[32] 胡顺石,张立福,张霞,王倩,韩冰,张楠.卫星传感器波段平均太阳辐照度计算及可靠性分析.国土资源遥感,2012,(3):97- 102.
[33] 刘三超,张万昌,蒋建军,赵登忠.用TM影像和DEM获取黑河流域地表反射率和反照率.地理科学,2003,23(5):585- 591.
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