PDF Download

[1]DENG Xingyao,YAO Junqiang,LIU Zhihui,et al.Spatiotemporal Dynamic Change Characteristics of Evapotranspiration in Tianshan Mountains from 2000 to 2014[J].Research of Soil and Water Conservation,2017,24(04):266-273.

Copy

Spatiotemporal Dynamic Change Characteristics of Evapotranspiration in Tianshan Mountains from 2000 to 2014

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 24 Number of periods: 2017 04 Page number: 266-273 Column: Public date: 2017-08-28

Title:: Spatiotemporal Dynamic Change Characteristics of Evapotranspiration in Tianshan Mountains from 2000 to 2014

Author(s):: DENG Xingyao^1,2,3, YAO Junqiang⁴, LIU Zhihui^2,3, LIU Yang^1,2,3; 1. College of Resources and Environment Science, Xinjiang University, Urumqi 830046, China;
2. Institute of Arid Ecology and Environment, Xinjiang University, Urumqi 830046, China;
3. Key Laboratory of Oasis Ecology of Education Ministry, Xinjiang University, Urumqi 830046, China;
4. Institute of Desert Meteorology, China Meteorlogical Administration, Urumqi 830002, China

Keywords:: evapotranspiration; MODIS; the Tianshan Mountains; precipitation; trend analysis

CLC:: P426.2

DOI:: -

Abstract:: Using MODIS ET data of actual surface evapotranspiration products that were concentrated from 2000 to 2014, we used variable coefficients, the Theil-Sen median trend analysis, Mann-Kendall test, and Hurst index, to investigate the spatial pattern of evapotranspiration, spatial heterogeneity, characteristics of time variation, and future trends considering the Tianshan Mountains. The results showed as the following. (1) Evapotranspiration over the entire region was very high from 2000 to 2014, and the area with evapotranspiration greater than 400 mm accounts for 49.172% of the total area. Affected by precipitation, evapotranspiration is high in the west and north, but low in the east and south. Affected by land cover types, areas with higher value of evapotranspiration (more than 400 mm) mainly included the mountain forestland and grassland, but the area with low value of evapotranspiration (less than 200 mm) concentrated in sparse vegetation region. Evapotranspiration data decreased in the order: cropland > forestland > grassland > sparse vegetation. (2) The degree of variation in evapotranspiration over the past 15 years for the entire region is not obvious, but shows a slight fluctuation. The proportion of areas with slight fluctuations accounts for 45.140% of the total area. Among them, the region of high fluctuation was caused by the change of land cover types. (3) The value of evapotranspiration over the past 15 years for the entire region varied from 305 mm to 387 mm and shows changes in the fluctuations with a weakly decreasing trend with the change rate of -2.911 6 mm/year. An analysis based on the pixel scale also shows a mainly decreasing trend, the area with decrease trend accounts for 83.022% of the total area. This decrease trend of regional evapotranspiration was caused by the decrease of precipitation. (4) The Hurst index average of evapotranspiration for the entire region is 0.747. The area with Hurst index greater than 0.5 accounts for 86.382% of the total area. The change trend of evapotranspiration in the future for the entire region is mainly towards a persistent decrease and this area accounts for 69.888% of the total area. However, the trend of changes for 15.589% of the area cannot be determined.

References:: [1] Xiong Y J, Zhao S H, Tian F, et al. An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing[J]. Journal of Hydrology, 2015,530:392-404.
[2] Zhang K, Pan S, Zhang W, et al. Influence of climate change on reference evapotranspiration and aridity index and their temporal-spatial variations in the Yellow River Basin, China, from 1961 to 2012[J]. Quaternary International, 2015,380:75-82.
[3] Jung M, Reichstein M, Ciais P, et al. Recent decline in the global land evapotranspiration trend due to limited moisture supply[J]. Nature, 2010,467(7318):951-954.
[4] Ghilain N, Arboleda A, Gellens-Meulenberghs F. Evapotranspiration modelling at large scale using near-real time MSG SEVIRI derived data[J]. Hydrology and Earth System Sciences, 2011,15(3):771-786.
[5] Mu Q, Heinsch F A, Zhao M, et al. Development of a global evapotranspiration algorithm based on MODIS and global meteorology data[J]. Remote Sensing of Environment, 2007,111(4):519-536.
[6] 贺添,邵全琴.基于MOD16产品的我国2001-2010年蒸散发时空格局变化分析[J].地球信息科学学报,2014,16(6):979-988.
[7] Kim H W, Hwang K, Mu Q, et al. Validation of MODIS16global terrestrial evapotranspiration products in various climates and land cover types in Asia[J]. KSCE Journal of Civil Engineering, 2012,16(2):229-238.
[8] Liu S M, Xu Z W, Zhu Z L, et al. Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China[J]. Journal of Hydrology, 2013,487:24-38.
[9] Jang K, Kang S, Lim Y J, et al. Monitoring daily evapotranspiration in Northeast Asia using MODIS and a regional Land Data Assimilation System[J]. Journal of Geophysical Research:Atmospheres, 2013,118(23):12927-12940.
[10] 胡汝骥.中国天山自然地理[M].北京:中国环境科学出版社,2004.
[11] 周德成,罗格平,韩其飞,等.天山北坡不同海拔梯度山地草原生态系统地上净初级生产力对气候变化及放牧的响应[J].生态学报,2012,32(1):81-92.
[12] Zhang Y, Ohata T, Ersi K, et al. Observation and estimation of evaporation from the ground surface of the cryosphere in eastern Asia[J]. Hydrological Processes, 2003,17(6):1135-1147.
[13] 郭淑海,杨国靖,李清峰,等.新疆阿克苏河上游高寒草甸蒸散发观测与估算[J].冰川冻土,2015,37(1):241-248.
[14] 张明军,李瑞雪,贾文雄,等.中国天山山区潜在蒸发量的时空变化[J].地理学报,2009,64(7):798-806.
[15] Penman H L. Natural evaporation from open water, bare soil and grass[J]. Proceedings of the Royal Society of London. Series A:Mathematical and Physical Sciences, 1948,193(1032):120-145.
[16] Bouchet R J. Evapotranspiration réelle et potentielle, signification climatique[J]. General Assembly of Berkeley, Red Book, 1963,62:134-142.
[17] 耿雷华,黄永基,郦建强,等.西北内陆河流域水资源特点初析[J].水科学进展,2002,13(4):496-501.
[18] Mu Q, Zhao M, Running S W. Improvements to a MODIS global terrestrial evapotranspiration algorithm[J]. Remote Sensing of Environment, 2011,115(8):1781-1800.
[19] 闻新宇,王绍武,朱锦红,等.英国CRU高分辨率格点资料揭示的20世纪中国气候变化[J].大气科学,2006,30(5):894-904.
[20] 马柱国,符淙斌.中国干旱和半干旱带的10年际演变特征[J].地球物理学报,2005,48(3):519-525.
[21] Milich L, Weiss E. GAC NDVI interannual coefficient of variation(CoV)images:ground truth sampling of the Sahel along north-south transects[J]. International Journal of Remote Sensing, 2000,21(2):235-260.
[22] Yue S, Pilon P, Cavadias G. Power of the Mann-Kendall and Spearman’s rho tests for detecting monotonic trends in hydrological series[J]. Journal of Hydrology, 2002,259(1/4):254-271.
[23] Fensholt R, Langanke T, Rasmussen K, et al. Greenness in semi-arid areas across the globe 1981-2007 an Earth Observing Satellite based analysis of trends and drivers[J]. Remote Sensing of Environment, 2012,121:144-158.
[24] Jiang W, Yuan L, Wang W, et al. Spatio-temporal analysis of vegetation variation in the Yellow River Basin[J]. Ecological Indicators, 2015,51:117-126.
[25] Liang S, Yi Q, Liu J. Vegetation dynamics and responses to recent climate change in Xinjiang using leaf area index as an indicator[J]. Ecological Indicators, 2015,58:64-76.
[26] Roderick M L, Hobbins M T, Farquhar G D. Pan evaporation trends and the terrestrial water balance.Ⅱ:Energy balance and interpretation[J]. Geography Compass, 2009,3(2):761-780.
[27] 何延波, Su Z, Jia L,等.遥感数据支持下不同地表覆盖的区域蒸散[J].应用生态学报,2007,18(2):288-296.
[28] 郭铌,朱燕君,王介民,等.近22年来西北不同类型植被NDVI变化与气候因子的关系[J].植物生态学报,2008,32(2):319-327.
[29] 陈忠升,陈亚宁,李卫红,等.基于生态服务价值的伊犁河谷土地利用变化环境影响评价[J].中国沙漠,2010,30(4):870-877.
[30] 刘宪锋,朱秀芳,潘耀忠,等.1982-2012年中国植被覆盖时空变化特征[J].生态学报,2015,35(16):5331-5342.
[31] 许玉凤,杨井,陈亚宁,等.近32年来新疆地区植被覆盖的时空变化[J].草业科学,2015,32(5):702-709.
[32] 王海波,马明国.基于遥感和Penman-Monteith模型的内陆河流域不同生态系统蒸散发估算[J].生态学报,2014,34(19):5617-5626.
[33] 田静,苏红波,陈少辉,等.近20年来中国内陆地表蒸散的时空变化[J].资源科学,2012,34(7):1277-1286.
[34] 刘朝顺,高志强,高炜.基于遥感的蒸散发及地表温度对LUCC响应的研究[J].农业工程学报,2007,23(8):1-8.
[35] 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[J].干旱区地理,2011(3):400-408.

Similar References:

Memo

Last Update: 1900-01-01