基于MOD16的洞庭湖流域2000-2014年地表蒸散时空变化分析
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摘要
地表蒸散是决定土壤-植被-大气之间水循环与能量转换的关键因素,研究流域蒸散量的时空变化对水文、气象和农业等领域的治理和管理具有重要意义。该文基于时间序列MOD16数据集,分析了2000-2014年洞庭湖流域地表蒸散量时空变化,并利用多年降水量及气温数据,采用回归模型探讨了蒸散量与气候因子之间的相关性,以期为洞庭湖流域热量平衡和气候干湿状况评价提供数据支持。结果表明:1)MOD16地表蒸散量产品数据的精度满足洞庭湖流域蒸散量时空分布研究的需求;2)洞庭湖流域年蒸散量值具有较高的空间分异性,呈现出东北部低、西部和南部高的趋势。洞庭湖流域各年蒸散量多年年平均蒸散量值为636.83mm/a,多年年均蒸散量整体呈波动下降趋势;3)蒸散量的季节性变化明显,一年中夏季地表蒸散量平均值最高4)洞庭湖流域地表蒸散量年内分布显现为先增大后减小的单峰型分布趋势,蒸散量的高值区主要集中在5-9月,最高值出现在7月,最小值出现在12月;5)地表蒸散量值与降水量和气温的平均相关系数分别是0.67和0.41,表明地表蒸散量与降水量的相关性较高。基于已有的研究表明,总体而言,MOD16产品为全球变化研究提供了较为可靠的、长时间序列蒸散发产品,并可以用于全球范围地表蒸散研究。
As an important part of ecological environment and water resources assessment, timely and accurate analysis of spatio-temporal characteristics of regional evapotranspiration and its relationship with climate factors, is of great significance to the regional weather, hydrology, water conservancy and agricultural fields. In this article, we analyzed the inter-annual variation and annual variation of surface evapotranspiration in the Dongting Lake Basin during 2000-2014 based on the time series MOD16 dataset. And the correlation between evapotranspiration and climate factors was discussed by using regression model based on the annual precipitation and temperature data of study area. The results show that: 1) Based on the measured evapotranspiration of Taoyuan station, we validated the MOD16 dataset. The correlation coefficient between the measured evapotranspiration and surface evapotranspiration from MOD16 was 0.88, which met the needs of accuracy of the study on the spatial and temporal distribution of evapotranspiration in Dongting Lake Basin; 2) The annual evapotranspiration value of Dongting Lake Basin has a strong spatial differentiation pattern, showing a trend of being low in the northeast area, and high in western and southern areas of the study area. During the study period, the average annual evapotranspiration in Dongting Lake Basin was 636.83 mm/a, which showed a downward trend with irregular fluctuations. The highest evapotranspiration value appeared in 2001, which was 669.19 mm/a, and the lowest evapotranspiration value was 613.62 mm/a, which appeared in 2011. The change rate of annual surface evapotranspiration(θ) was-2.98%, which indicated that the evapotranspiration value showed a downward trend of Dongting Lake Basin. The spatial distribution of evapotranspiration was related to land cover types, which had effect on the evapotranspiration distribution in the Dongting Lake Basin, and the order of evapotranspiration intensity of different land cover types was forest > grassland > bare land > cultivated land > town. 3) The seasonal variation of evapotranspiration value was obvious, and the evapotranspiration in summer was the highest. The order of evapotranspiration value of different seasons was Summer > Spring > Autumn > Winter. 4) Furthermore, the annual variation of evapotranspiration in Dongting Lake Basin showed a unimodal pattern that increased first and then decreased. The high value area of monthly evapotranspiration was mainly concentrated between May and September, the minimum value appeared in December, and the peak value occurred in July. 5) The correlation coefficients between surface evapotranspiration and precipitation and temperature were 0.67 and 0.41, respectively. Most of the regional precipitation and temperature have a positive correlation with surface evapotranspiration in Dongting Lake Basin. Comparatively, the correlation between surface evapotranspiration and precipitation was stronger than that between surface evapotranspiration and temperature. The humid climatic condition is beneficial to the growth and development of vegetation. With the increase of vegetation coverage, the value of surface evapotranspiration also increases. However, a higher temperature and less precipitation, being not conducive to the growth of vegetation, results in low surface evapotranspiration. According to the above analysis of this article, it can be further explained that the coupling effect of temperature and precipitation is an important factor affecting the surface evapotranspiration in Dongting Lake Basin.
As an important part of ecological environment and water resources assessment, timely and accurate analysis of spatio-temporal characteristics of regional evapotranspiration and its relationship with climate factors, is of great significance to the regional weather, hydrology, water conservancy and agricultural fields. In this article, we analyzed the inter-annual variation and annual variation of surface evapotranspiration in the Dongting Lake Basin during 2000-2014 based on the time series MOD16 dataset. And the correlation between evapotranspiration and climate factors was discussed by using regression model based on the annual precipitation and temperature data of study area. The results show that: 1) Based on the measured evapotranspiration of Taoyuan station, we validated the MOD16 dataset. The correlation coefficient between the measured evapotranspiration and surface evapotranspiration from MOD16 was 0.88, which met the needs of accuracy of the study on the spatial and temporal distribution of evapotranspiration in Dongting Lake Basin; 2) The annual evapotranspiration value of Dongting Lake Basin has a strong spatial differentiation pattern, showing a trend of being low in the northeast area, and high in western and southern areas of the study area. During the study period, the average annual evapotranspiration in Dongting Lake Basin was 636.83 mm/a, which showed a downward trend with irregular fluctuations. The highest evapotranspiration value appeared in 2001, which was 669.19 mm/a, and the lowest evapotranspiration value was 613.62 mm/a, which appeared in 2011. The change rate of annual surface evapotranspiration(θ) was-2.98%, which indicated that the evapotranspiration value showed a downward trend of Dongting Lake Basin. The spatial distribution of evapotranspiration was related to land cover types, which had effect on the evapotranspiration distribution in the Dongting Lake Basin, and the order of evapotranspiration intensity of different land cover types was forest > grassland > bare land > cultivated land > town. 3) The seasonal variation of evapotranspiration value was obvious, and the evapotranspiration in summer was the highest. The order of evapotranspiration value of different seasons was Summer > Spring > Autumn > Winter. 4) Furthermore, the annual variation of evapotranspiration in Dongting Lake Basin showed a unimodal pattern that increased first and then decreased. The high value area of monthly evapotranspiration was mainly concentrated between May and September, the minimum value appeared in December, and the peak value occurred in July. 5) The correlation coefficients between surface evapotranspiration and precipitation and temperature were 0.67 and 0.41, respectively. Most of the regional precipitation and temperature have a positive correlation with surface evapotranspiration in Dongting Lake Basin. Comparatively, the correlation between surface evapotranspiration and precipitation was stronger than that between surface evapotranspiration and temperature. The humid climatic condition is beneficial to the growth and development of vegetation. With the increase of vegetation coverage, the value of surface evapotranspiration also increases. However, a higher temperature and less precipitation, being not conducive to the growth of vegetation, results in low surface evapotranspiration. According to the above analysis of this article, it can be further explained that the coupling effect of temperature and precipitation is an important factor affecting the surface evapotranspiration in Dongting Lake Basin.
引文
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[3]莫兴国,林忠辉,李宏轩,等.基于过程模型的河北平原冬小麦产量和蒸散量模拟[J].地理研究,2004,23(5):623-631.Mo Xingguo,Lin Zhonghui,Li Hongxuan,et al.Simulation of winter wheat yield and evapotranspiration with process-based model and remote[J].Geographical Research,2004,23(5):623-631.(in Chinese with English abstract)
[4]He R,Jin,Y,Kandelous M M,et al.Evapotranspiration estimate over an almond orchard using landsat satellite observations[J].Remote Sensing,2017,9(5):436-448.
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[6]段春锋,缪启龙,曹雯.西北地区参考作物蒸散变化特征及其主要影响因素[J].农业工程学报,2011,27(8):77-83.Duan Chunfeng,Lao Qilong,Cao Wen.Changing characteristics of reference crop evapotranspiration and main causes in the Northwest China[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2011,27(8):77-83.(in Chinese with English abstract)
[7]连晋姣,黄明斌,李杏鲜,等.夏季黑河中游绿洲样带蒸散量遥感估算[J].农业工程学报,2014,30(15):120-129.Lian Jinjiao,Huang Mingbin,Li Xingxian,et al.Evapotranspiration estimation for oasis transect in middle reach of Heihe River Basin based on remote sensing[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2014,30(15):120-129.(in Chinese with English abstract)
[8]王潇潇,潘学标,顾生浩,等.内蒙古地区参考作物蒸散变化特征及其气象影响因子[J].农业工程学报,2015,31(增刊1):142-152.Wang Xiaoxiao,Pan Xuebiao,Gu Shenghao,et al.Trend in reference crop evapotranspiration and meteorological factors affecting trends in Inner Mongolia[J].Transactions of the Chinese Society of Agricultural Engineering(Transactions of the CSAE),2015,31(Supp.1):142-152.(in Chinese with English abstract)
[9]Guo S,Zhu A X,Meng L,et al.Unification of soil feedback patterns under different evaporation conditions to improve soil differentiation over flat area[J].International Journal of Applied Earth Observations&Geoinformation,2016,49(49):126-137.
[10]Martens B,Miralles D,Lievens H,et al.Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture[J].International Journal of Applied Earth Observation&Geoinformation,2015,48:146-162.
[11]张静,任志远.基于MOD16的汉江流域地表蒸散发时空特征[J].地理科学,2017,37(2):274-282.Zhang Jing,Ren Zhiyuan.Spatiotemporal characteristics of evapotranspiration based on MOD16 in the Hanjiang River Basin[J].Scientia Geographica Sinica,2017,37(2):274-282.(in Chinese with English abstract)
[12]张猛,曾永年,朱永森.面向对象方法的时间序列MODIS数据湿地信息提取:以洞庭湖流域为例[J].遥感学报,2017,21(3):479-492.Zhang Meng,Zeng Yongnian,Zhu Yongsen.Wetland mapping of Dongting Lake Basin based on time-series MODIS data and object-oriented method[J].Journal of Remote Sensing,2017,21(3):479-492.(in Chinese with English abstract)
[13]龙岳红,秦建新,贺新光,等.洞庭湖流域植被动态变化的小波多分辨率分析[J].地理学报,2015,70(9):1491-1502.Long Yuehong,Qin Jianxin,He Xinguang,et al.Wavelet multi-resolution analysis of vegetation dynamic change in Dongting Lake Basin[J].Acta Geographica Sinica,2015,70(9):1491-1502.(in Chinese with English abstract)
[14]王婷,章新平,黎祖贤,等.近52年来洞庭湖流域气象干旱的时空分布特征[J].长江流域资源与环境,2016(3):514-522.Wang Ting,Zhang Xinping,Li Zuxian,et al.Temporal and spatial distribution characteristics of meteorological drought for recent 52 years in Dongting Lake Basin[J].Resources and Environment in the Yangtze Basin,2016(3):514-522.(in Chinese with English abstract)
[15]孙葭,章新平,黄一民,等.基于多源降水数据的洞庭湖流域夏季降水与西太平洋副热带高压的关系[J].地理科学,2016,36(7):1115-1124.Sun Jia,Zhang Xinping,Huang Yimin,et al.Relationship between summer precipitation of different data in Dongting Lake and Western Pacific Subtropical High[J].Scientia Geographica Sinica,2016,36(7):1115-1124.(in Chinese with English abstract)
[16]孙占东,黄群,姜加虎,等.洞庭湖近年干旱与三峡蓄水影响分析[J].长江流域资源与环境,2015,24(2):251-256.Sun Zhandong,Huang Qun,Jiang Jiahu,et al.Recent hydrological droughts in Dongting Lake and its association with the operation of Three Gorges Reservoir[J].Resource and Environment in Yangtze Basin,2015,24(2):251-256.(in Chinese with English abstract)
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