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国土资源遥感  2020, Vol. 32 Issue (2): 204-212    DOI: 10.6046/gtzyyg.2020.02.26
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基于遥感数据与SEBAL模型的江浙沪地区地表蒸散反演
金楷仑, 郝璐()
南京信息工程大学江苏省农业气象重点实验室,南京 210044
Evapotranspiration estimation in the Jiangsu-Zhejiang-Shanghai Area based on remote sensing data and SEBAL model
Kailun JIN, Lu HAO()
Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
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摘要 

地表蒸散的准确估算对于研究区域尺度上因气候或土地利用变化引起的水量-能量变化有着重要的意义。本研究集成MODIS数据,利用陆面能量平衡模型(surface energy balance algorithm for land,SEBAL),对江苏、浙江和上海市地区(以下简称江浙沪)地区2002—2015年间生长季的蒸散进行了估算,并使用蒸渗仪地表观测数据对模型进行了验证。在总结蒸散时间扩展方法的基础上,对区域蒸散进行了月、季节尺度的扩展,计算得到区域月、季节尺度的蒸散量。并选取特征年2004年与2013年来分析日尺度与生长季尺度的空间蒸散特征。研究表明,SEBAL模型较适用于江浙沪地区的蒸散估算,该地区的年生长季蒸散范围跨度较大,在空间上呈现南高北低的特征,2004年区域生长季蒸散平均值为930 mm; 2013年为758 mm,低于2004年的蒸散值。对特定地物提取的生长季日平均蒸散进行统计发现,江浙沪地区的自然地物蒸散要高于人造地物,而在自然地物中,水体>林地>滩涂滩地>草地>未利用地。而对于人造地物,城镇的蒸散值很低,而水田、旱地以及农村居民点的蒸散值较高。

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金楷仑
郝璐
关键词 MODIS遥感数据江浙沪地区SEBAL模型地表蒸散土地覆被类型    
Abstract

The evapotranspiration in the Jiangsu-Zhejiang-Shanghai Area during the 2004 and 2013 growing seasons was estimated by integrating the MODIS remote sensing data and using the Surface Energy Balance Algorithm for Land (SEBAL) model, and the model was validated using the surface observation data of the lysimeter. On the basis of summarizing the evapotranspiration time-space expansion method, the crop volatility method was used to expand the regional evapotranspiration on the monthly and seasonal scales, and the evapotranspiration of the regional monthly and seasonal scales was calculated. The results show that the SEBAL model is more suitable for evapotranspiration estimation in this region. The evapotranspiration range of the annual growing season in the Jiangsu-Zhejiang-Shanghai Area is wider, and the southern evapotranspiration is higher in the region. The average evapotranspiration in the regional growing season in 2013 was 758 mm. It was lower than the average evapotranspiration of about 930 mm in the growing season in 2004 . According to the statistics of the average daily evapotranspiration of the growing seasons, the authors have found that the natural land use evapotranspiration of the Jiangsu-Zhejiang-Shanghai Area is higher than that of the artificial land use, while in natural land use, the evapotranspiration is in order of water>forest>beach land>grassland>unused land. For artificial land use, the evapotranspiration of urban area is significantly low, while the evapotranspiration values of paddy fields, dry land and rural area are relatively high, and the difference is insignificant.

Key wordsMODIS remote sensing data    Jiangsu-Zhejiang-Shanghai Area    SEBAL algorithm    evapotranspiration    spatial evapotranspiration pattern
收稿日期: 2019-04-09      出版日期: 2020-06-18
:  TP79  
基金资助:国家自然科学基金项目“湿润区生态水文变化影响城市群热岛干化效应的过程和机制”(41877151);“城市化对水稻田流域蒸散发及生态水文过程的影响机制”(41571026)
通讯作者: 郝璐
作者简介: 金楷仑(1994-),男,硕士研究生,主要研究方向为应用气象。Email: jkl_nuist@163.com。
引用本文:   
金楷仑, 郝璐. 基于遥感数据与SEBAL模型的江浙沪地区地表蒸散反演[J]. 国土资源遥感, 2020, 32(2): 204-212.
Kailun JIN, Lu HAO. Evapotranspiration estimation in the Jiangsu-Zhejiang-Shanghai Area based on remote sensing data and SEBAL model. Remote Sensing for Land & Resources, 2020, 32(2): 204-212.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/gtzyyg.2020.02.26      或      https://www.gtzyyg.com/CN/Y2020/V32/I2/204
Fig.1  江浙沪地区高程图
Fig.2  SEBAL模型演算流程
Fig.3  SEBAL估算结果验证
2000年 2010年
林地 草地 水体 未利用地 水田 旱地 农村居民点 滩涂滩地 城镇 总计
林地 66 674.8 285.1 297.4 34.3 495.8 714.4 164.4 11.0 590.8 69 268.0
草地 216.3 2 777.8 306.5 64.8 67.6 86.2 13.5 82.2 155.3 3 770.3
水体 20.7 14.0 14 230.7 0.6 124.2 60.1 35.7 129.1 268.5 14 883.7
未利用地 5.0 2.3 3.0 15.0 0.3 41.3 1.1 0.1 9.6 77.5
水田 450.6 16.4 1 479.8 23.3 62 898.3 194.9 2 706.6 34.0 5427.0 73 230.9
旱地 118.9 4.8 212.4 40.6 1 990.6 25 275.0 596.0 10.4 1195.7 29 444.3
农村居民点 14.6 0.9 60.6 2.6 204.2 51.7 11 296.9 1.5 1 398.0 13 030.9
滩涂滩地 24.9 79.3 601.8 0.2 76.0 28.6 13.2 2879.7 104.9 3 808.5
城镇 12.4 31.5 320.0 34.2 57.1 19.2 239.4 3.9 5 936.2 6 653.8
总计 67 538.3 3 211.9 17 512.0 215.7 65 914.2 26 471.2 15 066.7 3 152.0 15 085.9 21 4167.9
变化量 -1 729.7 -558.4 2 628.3 138.2 -7 316.7 -2 973.1 2 035.8 -656.5 8 432.1
Tab.1  2000—2010年江浙沪地区土地利用转移矩阵
Fig.4  江浙沪地区2000年和2010年的土地利用分类
Fig.5  江浙沪地区2004年和2013年生长季总蒸散空间分布
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