2000-2014年黄河源区ET时空特征及其与气候因子关系
Spatio-temporal characteristics of evapotranspiration and its relationship with climate factors in the source region of the Yellow River from 2000 to 2014
查看参考文献71篇
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文摘
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黄河源区地处青藏高原东缘,具有独特的自然生境和丰富的自然资源,是中国西南区域经济发展的重要生态安全屏障。以MODIS ET产品作为研究黄河源区地表蒸散发(ET)的数据源,结合黄河源区内部及周边18个气象站数据、全国1∶100万植被类型图和黄河源区DEM数据,利用趋势分析、相对年际变化和相关分析法,研究2000-2014年黄河源区ET时空变化特征及不同土地利用类型下ET的变化规律,重点探讨了ET与气候因子的关系。结果表明:①黄河源区多年ET区域分异规律明显,北部ET显著弱于中部和东南部,最强ET位于黄河源区的东南部,多年平均ET值为538.61 mm/a,距平相对变化显著,ET年际变化呈先减小后增加的趋势,平均趋势变化率为0.44 mm/a;②年内ET呈周期性单峰变化趋势,7月达到峰值;2000-2014年黄河源区多年四季ET季节性差异明显,夏季ET最强达到188.14 mm/a,春秋季次之,冬季ET最弱仅97.15 mm/a;③研究时段内不同土地利用类型的ET大小表现为沼泽地>林地>草地>其他>裸地,整体上各土地利用类型的ET呈逐渐增加趋势;④相关分析结果表明,ET与同期气温、降水呈正相关关系,与相对湿度呈负相关关系,其中降水对ET的影响强于气温;驱动分区结果显示黄河源区ET受气候因子驱动的地区主要表现为降水驱动。 |
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其他语种文摘
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Located at the eastern margin of the Tibetan Plateau, the source region of the Yellow River is an important ecological security shelter for economic development in Southwest China, with its unique natural habitats and abundant natural resources. Based on the data of 18 meteorological stations within and around the source region, map of China vegetation types (1: 1000,000) and DEM data, and using the methods of trend analysis, relative inter- annual variation and correlation analysis, we selected MODIS evapotranspiration (ET) as the main data source to research the spatio- temporal characteristics of ET and its variation under different land use types as well as its relationship with climate factors in the study area from 2000 to 2014. The results indicate that: (1) the regional differentiation of mean ET over years is obvious, the northern ET is significantly weaker than that of the central and southeastern parts, and the strongest ET is observed in the southeastern part. The multi-year mean value of ET is 538.61 mm/a, and the anomaly relative variation is obvious. In addition, the trend of interannual variation of ET decreases firstly and then increases, and the trend variation rate is 0.44 mm/a. (2) During the study period, the ET shows a periodic unimodal trend and peaks in July. Moreover, seasonal differences of ET are apparent in the source region of the Yellow River, and the highest value of ET reaches 188.14 mm/a in summer, followed by spring and autumn, yet the lowest is only 97.15 mm/a in winter. (3) From 2000 to 2014, the value of ET in different types of land use has a similar regular pattern, namely: wetland > forest > grassland > other types > bare land. On the whole, the value of ET in each type of land use increases gradually. (4) According to the correlation analysis results, there are positive correlations between ET and air temperature, as well as between ET and precipitation, while ET has a negative correlation with relative humidity. The effect of precipitation on ET is stronger than that of air temperature. Furthermore, the result of ET driven by different factors demonstrates that the climate-driven region of ET is predominantly precipitation-driven in the source region of the Yellow River. |
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来源
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地理学报
,2018,73(11):2117-2134 【核心库】
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DOI
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10.11821/dlxb201811006
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关键词
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地表蒸散发(ET)
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时空特征
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气候因子
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MODIS
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黄河源区
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地址
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1.
成都理工大学地球科学学院, 成都, 610059
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成都理工大学工程技术学院, 四川, 乐山, 614000
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国土资源部地学空间信息技术重点实验室, 国土资源部地学空间信息技术重点实验室, 成都, 610059
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成都理工大学管理科学学院, 成都, 610059
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成都理工大学环境与土木工程学院, 成都, 610059
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成都理工大学生态资源与景观研究所, 成都, 610059
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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0375-5444 |
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学科
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大气科学(气象学) |
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基金
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国家自然科学基金项目
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国土资源部中国地质调查局项目
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文献收藏号
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CSCD:6364806
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参考文献 共
71
共4页
|
|
1.
Monteith J L. Evaporation and environment.
Symposia of the Society for Experimental Biology,1965,19(19):205
|
被引
70
次
|
|
|
|
|
2.
吴桂平. 基于MOD16产品的鄱阳湖流域地表蒸散量时空分布特征.
地理研究,2013,32(4):617-627
|
被引
68
次
|
|
|
|
|
3.
冯飞. 基于MOD16产品的三江平原蒸散量时空分布特征分析.
生态环境学报,2015,24(11):1858-1864
|
被引
14
次
|
|
|
|
|
4.
包姗宁. 同化叶面积指数和蒸散发双变量的冬小麦产量估测方法.
地球信息科学学报,2015,17(7):871-882
|
被引
10
次
|
|
|
|
|
5.
刘蓉. 黄河源区蒸散发量时空变化趋势及突变分析.
气候与环境研究,2016,21(5):503-511
|
被引
23
次
|
|
|
|
|
6.
Nishida K. Development of an evapotranspiration index from Aqua/MODIS for monitoring surface moisture status.
IEEE Transactions on Geoscience & Remote Sensing,2003,41(2):493-501
|
被引
18
次
|
|
|
|
|
7.
Ruhoff A L. A MODIS-based energy balance to estimate evapotranspiration for clear-sky days in Brazilian tropical savannas.
Remote Sensing,2012,4(3):703-725
|
被引
2
次
|
|
|
|
|
8.
Dong Q. A review on evapotranspiration data assimilation based on hydrological models.
Journal of Geographical Sciences,2016,26(2):230-242
|
被引
7
次
|
|
|
|
|
9.
权晨. 长江源区高寒退化湿地地表蒸散特征研究.
冰川冻土,2016,38(5):1249-1257
|
被引
5
次
|
|
|
|
|
10.
周倜. 非均匀地表蒸散遥感研究综述.
遥感学报,2016,20(2):257-277
|
被引
19
次
|
|
|
|
|
11.
Batra N. Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains.
Remote Sensing of Environment,2006,103(1):1-15
|
被引
20
次
|
|
|
|
|
12.
Zhan C S. Quantitative estimation of land surface evapotranspiration in Taiwan based on MODIS data.
Water Science and Engineering,2011,4(3):237-245
|
被引
2
次
|
|
|
|
|
13.
Chen X. Contributions of climate change and human activities to ET and GPP trends over North China Plain from 2000 to 2014.
Journal of Geographical Sciences,2017,27(6):661-680
|
被引
5
次
|
|
|
|
|
14.
曾丽红. 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
|
被引
14
次
|
|
|
|
|
15.
何慧娟. 基于MOD16监测陕西省地表蒸散变化.
干旱区地理,2015,38(5):960-967
|
被引
15
次
|
|
|
|
|
16.
王万同.
基于遥感技术的区域地表蒸散估算研究:以伊洛河流域为例,2012
|
被引
3
次
|
|
|
|
|
17.
田静. 近20年来中国内陆地表蒸散的时空变化.
资源科学,2012,34(7):1277-1286
|
被引
16
次
|
|
|
|
|
18.
尹云鹤. 过去30年气候变化对黄河源区水源涵养量的影响.
地理研究,2016,35(1):49-57
|
被引
32
次
|
|
|
|
|
19.
张颖. 三江源1982-2012年草地植被覆盖度动态及其对气候变化的响应.
草业科学,2017,34(10):1977-1990
|
被引
26
次
|
|
|
|
|
20.
Xu J. Complex response of runoff-precipitation ratio to the rising air temperature: The source area of the Yellow River, China.
Regional Environmental Change,2015,15(1):35-43
|
被引
2
次
|
|
|
|
|
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