基于SEBAL模型的北京市日蒸散发区域分布规律
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摘要
为了对北京市地表水转换过程中的分量-蒸散发进行定量研究,基于Landsat7 ETM+遥感影像信息并结合气象数据,通过ERDAS构建了SEBAL模型,并通过模型计算得到北京市2014年7月26日的平均蒸散发为2.49 mm,同时利用彭曼公式和MOD16产品数据对SEBAL反演结果的可靠性进行验证。结果表明,通过SEBAL模型计算得到的蒸散发与彭曼公式法和MOD16数据产品的误差分别为3.2%和3.3%,其结果具有一定的可靠性,且通过Landsat7数据反演具有数据获取便捷、空间分辨率高的优点。通过对比各区域蒸散发分布,得出北京市蒸散发整体呈现西北山区高、东南平原低的趋势,西北山区林草植被覆盖率较高是导致这一趋势的主要原因。通过统计分析,水域的蒸散发最高,硬化面积及建筑物的蒸散发接近于0,在除去水体及硬化面积后,蒸散发的大小与NDVI呈现极显著的正相关关系,两者的决定系数达到0.9233,故下垫面类型是影响某一时刻区域蒸散发大小的主要因素之一。
To quantitatively study the component-evapotranspiration in the process of surface water conversion in Beijing, we built the SEBAL model through ERDAS based on Landsat7 ETM + remote sensing image information combined with meteorological data, calculated that the average evapotranspiration on July 26,2014 in Beijing was 2.49 mm, and verified the reliability of the SEBAL inversion results by using the Penman formula and MOD16 product data. The results showed that: the error of evapotranspiration calculated by SEBAL model and Penman's formula method and MOD16 data product was 3.2% and 3.3%, respectively,which had certain reliability, and the data inversion by Landsat7 had the advantages of convenient data acquisition and high spatial resolution; by comparing the evapotranspiration distribution of each region, it was concluded that the overall evapotranspiration in Beijing was high in the northwest mountainous area and low in the southeast plain which resulted from the high coverage of forest vegetation in the northwest mountainous area; through statistical analysis, the evapotranspiration of the water area was the highest, and that of the hardening area and the building were close to zero; after removing the water body and the hardening area, the size of the evapotranspiration was significantly and positively correlated with NDVI, and the decision coefficient of both reached 0.9233, so the type of underlying surface was one of the main factors affecting the evapotranspiration in a certain time.
To quantitatively study the component-evapotranspiration in the process of surface water conversion in Beijing, we built the SEBAL model through ERDAS based on Landsat7 ETM + remote sensing image information combined with meteorological data, calculated that the average evapotranspiration on July 26,2014 in Beijing was 2.49 mm, and verified the reliability of the SEBAL inversion results by using the Penman formula and MOD16 product data. The results showed that: the error of evapotranspiration calculated by SEBAL model and Penman's formula method and MOD16 data product was 3.2% and 3.3%, respectively,which had certain reliability, and the data inversion by Landsat7 had the advantages of convenient data acquisition and high spatial resolution; by comparing the evapotranspiration distribution of each region, it was concluded that the overall evapotranspiration in Beijing was high in the northwest mountainous area and low in the southeast plain which resulted from the high coverage of forest vegetation in the northwest mountainous area; through statistical analysis, the evapotranspiration of the water area was the highest, and that of the hardening area and the building were close to zero; after removing the water body and the hardening area, the size of the evapotranspiration was significantly and positively correlated with NDVI, and the decision coefficient of both reached 0.9233, so the type of underlying surface was one of the main factors affecting the evapotranspiration in a certain time.
引文
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[23]吴桂平,刘元波,赵晓松.基于MOD16产品的鄱阳湖流域地表蒸散量时空分布特征[J].地理研究,2013,32(4):617-627.
[24]王志慧,李世明,刘良云.基于MODIS NDVI时间序列的土地覆盖分层分类方法研究[J].遥感技术与应用,2013,28(5):910-919.
[2]张宝忠,许迪,刘钰.多尺度蒸散发估测与时空尺度拓展方法研究进展[J].农业工程学报,2015,31(6):8-16.
[3]Bowen I S.The ratio of heat losses by conductions and byevaporation from any water surface[J].Physical Reviews,1926,27(6):779-787.
[4]Si J H,Feng Q,Zhang X Y.Research progress on surveying and calculation of evapotranspiration of plants and its prospects[J].Advances in Water Science,2005,16(3):450-459.
[5]Thornthwaite C W.An approach toward a rational classification of climate:Geographical Review[M].New York:American Geographical Society,1948.
[6]Penman H L.Natural evaporation from open water,bare soil and grass[J].Proceedings of the Royal Society of London.Series A 193,Mathematical and Physical Sciences,1948,193(1032):120-145.
[7]Monteith J L.Evaporation and environment:19th Symposia of the Society for Experimental Biology,Cambridge,1965[C].University Press,Cambridge.
[8]Bastiaanssen W GM.SEBAL2 based sensible and latent heat fluxes in the irrigated Gediz Basin,Turkey[J]Journal of Hydrology,2000,229:87-100.
[9]杜嘉,张柏,宋开山.基于MODIS产品和SEBAL模型的三江平原日蒸散量估算[J].中国农业气象,2010,31(1):104-110,162.
[10]刘朝顺,高炜,高志强.应用MODIS数据推估区域地表蒸散[J].水科学进展,2009,20(6):782-788.
[11]夏婷,王忠静.SEBAL模型参量敏感性再分析[J].清华大学学报:自然科学版,2013,53(9):1241-1248.
[12]苏伟,刘睿,孙中平,等.基于SEBAL模型的农作物NPP反演[J].农业机械学报,2014,45(11):272-279.
[13]魏强,张吴平,吴亚楠,等.基于SEBAL模型的小麦水分生产率研究[J].灌溉排水学报,2017,36(7):38-46.
[14]Zwart S J,Bastiaanssen W G M,de Fraiture C,et al.WATPRO:a remote sensing based model for mapping water productivity of wheat[J].Agricultural Water Management,2010,97(10):1628-1636.
[15]刘朝顺,施润和,高炜,等.利用区域遥感ET分析山东省地表水分盈亏的研究[J].自然资源学报,2010,25(11):1938-1948.
[16]邸苏闯,吴文勇,刘洪禄,等.基于遥感技术的绿地耗水估算与蒸散发反演[J].农业工程学报,2012,28(10):98-104.
[17]高海东.黄土高原丘陵沟壑区沟道治理工程的生态水文效应研究[D].中国科学院研究生院(教育部水土保持与生态环境研究中心),2013.
[18]张仁华.对于定量热红外遥感的一些思考[J].国土资源遥感,1999(1):5-10.
[19]Smith M,Allen R G,Monteith J L,et al.Report on the Expert Consultation on Procedures for Revision of FAO Guide-lines for Prediction of Crop Water Requirements[R].Land and Water Development Division,United Nations Food and Agriculture Service,Rome,Italy,1992.
[20]高彦春,龙笛.遥感蒸散发模型研究进展[J].遥感学报,2008(3):515-528.
[21]DeBruin H A R.From Penman to M akkink[C].Proceedings and Information:TNOC om mittee on Hyd rological Research,Gravenhage,the Netherlands,1987,39:5-31
[22]Mu Q Z,Zhao M S,Running S W.Improvements to a MODISglobal terrestrial evapotranspiration algorith[J].Remote sensing of Environment,2011,115:1781-1800.
[23]吴桂平,刘元波,赵晓松.基于MOD16产品的鄱阳湖流域地表蒸散量时空分布特征[J].地理研究,2013,32(4):617-627.
[24]王志慧,李世明,刘良云.基于MODIS NDVI时间序列的土地覆盖分层分类方法研究[J].遥感技术与应用,2013,28(5):910-919.