An analysis of spatio-temporal characteristics and influencing factors of surface evapotranspiration in the Yinchuan Plain based on MOD16 data

WANG Zhuoyue; KONG Jinling; LI Ying; ZHANG Zaiyong; LIU Huihui; JIANG Yizhu; ZHONG Yanling; ZHANG Jingya

doi:10.16030/j.cnki.issn.1000-3665.202012041

2021 Vol. 48, No. 3

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WANG Zhuoyue, KONG Jinling, LI Ying, ZHANG Zaiyong, LIU Huihui, JIANG Yizhu, ZHONG Yanling, ZHANG Jingya. An analysis of spatio-temporal characteristics and influencing factors of surface evapotranspiration in the Yinchuan Plain based on MOD16 data[J]. Hydrogeology & Engineering Geology, 2021, 48(3): 53-61. doi: 10.16030/j.cnki.issn.1000-3665.202012041

Citation:

WANG Zhuoyue, KONG Jinling, LI Ying, ZHANG Zaiyong, LIU Huihui, JIANG Yizhu, ZHONG Yanling, ZHANG Jingya. An analysis of spatio-temporal characteristics and influencing factors of surface evapotranspiration in the Yinchuan Plain based on MOD16 data[J]. Hydrogeology & Engineering Geology, 2021, 48(3): 53-61. doi: 10.16030/j.cnki.issn.1000-3665.202012041

An analysis of spatio-temporal characteristics and influencing factors of surface evapotranspiration in the Yinchuan Plain based on MOD16 data

1.
College of Earth Sciences and resources, Chang’an University, Xi’an, Shaanxi　710054, China
2.
College of Geological Engineering and Geomatics, Chang’an University, Xi’an, Shaanxi　710054, China
3.
Institute of Hydrology and Environmental Geology Survey of Ningxia, Yinchuan, Ningxia　750011, China
4.
College of Water Conservancy and Environment, Chang’an University, Xi’an, Shaanxi　710054, China
5.
Institute of Natural Resources Survey of Ningxia, Yinchuan, Ningxia　750002, China

More Information

Corresponding author: KONG Jinling, jlkong@163.com

Received Date: 10 December 2020

Revised Date: 01 March 2021

Publish Date: 15 May 2021

Abstract

Abstract

Surface evapotranspiration is an important part of terrestrial hydrological cycle, and the analysis of spatio-temporal variation characteristics of evapotranspiration is the basis of in-depth understanding of hydrological processes in arid areas. Due to the lack of long-term observations of actual regional evapotranspiration in the Yinchuan Plain, it is difficult to obtain the spatio-temporal variation characteristics of long-term series evapotranspiration. Based on the MOD16A3 surface evapotranspiration data and the measured data of meteorological stations in the study area, this paper analyzes the variation characteristics and influencing factors of surface evapotranspiration in the Yinchuan Plain from the perspective of time and space by using the methods of Theil Sen median trend analysis, MK mutation test and CA-Markov model, and predicts the development trend of surface evapotranspiration in the next five years. The results show that from 2004 to 2019, the interannual variation trend of evapotranspiration in the Yinchuan Plain is increasing, and the MK mutation test results show that the year of 2010 is the mutation point of evapotranspiration time series data. There are obvious differences in spatial distribution pattern and change trend between the actual evapotranspiration (ET) and potential evapotranspiration (PET) in the Yinchuan Plain. Actual evapotranspiration shows an increasing trend in recent 16 years, and potential evapotranspiration shows a decreasing trend, which conforms to the theory of complementary evapotranspiration in arid areas. The future development trend of surface evapotranspiration in the Yinchuan Plain in 2024 is predicted with the CA-Markov model. The simulation results show that the evapotranspiration will still increase in the next five years. The spatio-temporal variation of evapotranspiration is affected by climate and human activities. Evapotranspiration is positively correlated with temperature, precipitation and sunshine hours, and is negatively correlated with relative humidity. Land use structure affects annual evapotranspiration. The results also show the rule: Evapotranspiration of paddy field > dry land > woodland > grassland > desert.
- MOD16 /
- evapotranspiration /
- Theil Sen median trend /
- CA-Markov model /
- Yinchuan Plain

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References

[1]	TIAN F, QIU G Y, YANG Y H, et al. Estimation of evapotranspiration and its partition based on an extended three-temperature model and MODIS products[J]. Journal of Hydrology,2013,498:210 − 220. doi: 10.1016/j.jhydrol.2013.06.038 CrossRef Google Scholar
[2]	CHEN Y, XIA J Z, LIANG S L, et al. Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China[J]. Remote Sensing of Environment,2014,140(1):279 − 293. Google Scholar
[3]	王军, 李和平, 鹿海员. 基于遥感技术的区域蒸散发计算方法综述[J]. 节水灌溉,2016(8):195 − 199. [WANG Jun, LI Heping, LU Haiyuan. Review of regional evapotranspiration estimation models basing on the remote sensing[J]. Water Saving Irrigation,2016(8):195 − 199. (in Chinese with English abstract) Google Scholar
[4]	RODELL M, HOUSER P R, JAMBOR U, et al. The global land data assimilation system[J]. Bulletin of the American Meteorological Society,2004,85(3):381 − 394. doi: 10.1175/BAMS-85-3-381 CrossRef Google Scholar
[5]	MIRALLES D, HOLMES T, DE JEU R, et al.Global land-surface evaporation estimated from satellite-based observations[M].Geneva: World Meteorological Orgnization, 2008. Google Scholar
[6]	SENAY G B, BOHMS S, SINGH R K, et al. Operational evapotranspiration mapping using remote sensing and weather datasets: a new parameterization for the SSEB approach[J]. JAWRA Journal of the American Water Resources Association,2013,49(3):577 − 591. doi: 10.1111/jawr.12057 CrossRef Google Scholar
[7]	MU Q Z, ZHAO M S, RUNNING S W. Improvements to a MODIS global terrestrial evapotranspiration algorithm[J]. Remote Sensing of Environment,2011,115(8):1781 − 1800. doi: 10.1016/j.rse.2011.02.019 CrossRef Google Scholar
[8]	DZIKITI S, JOVANOVIC N Z, BUGAN R D, et al. Comparison of two remote sensing models for estimating evapotranspiration: algorithm evaluation and application in seasonally arid ecosystems in South Africa[J]. Journal of Arid Land,2019,11(4):495 − 512. doi: 10.1007/s40333-019-0098-2 CrossRef Google Scholar
[9]	HASSAN A, ISMAIL S S, ELMOUSTAFA A, et al. Evaluating evaporation rate from high Aswan Dam Reservoir using RS and GIS techniques[J]. The Egyptian Journal of Remote Sensing and Space Science,2018,21(3):285 − 293. doi: 10.1016/j.ejrs.2017.10.001 CrossRef Google Scholar
[10]	何慧娟, 卓静, 董金芳, 等. 基于MOD16监测陕西省地表蒸散变化[J]. 干旱区地理,2015,38(5):960 − 967. [HE Huijuan, ZHUO Jing, DONG Jinfang, et al. Surveying variations of evapotranspiration in Shaanxi Province Using MOD16 products[J]. Arid Land Geography,2015,38(5):960 − 967. (in Chinese with English abstract) Google Scholar
[11]	WOOD E F, SU H B, MCCABE M, et al. Estimating evaporation from satellite remote sensing[C]//2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477). Toulouse, France. IEEE, 2003: 1163-1165. Google Scholar
[12]	孙玉芳. 基于遥感监测指数模型的银川平原土壤盐渍化动态研究[J]. 地下水,2019,41(5):80 − 82. [SUN Yufang. Study on soil salinization dynamics in Yinchuan plain based on remote sensing monitoring index model[J]. Ground Water,2019,41(5):80 − 82. (in Chinese with English abstract) Google Scholar
[13]	袁丽华, 蒋卫国, 申文明, 等. 2000—2010年黄河流域植被覆盖的时空变化[J]. 生态学报,2013,33(24):7798 − 7806. [YUAN Lihua, JIANG Weiguo, SHEN Wenming, et al. The spatio-temporal variations of vegetation cover in the Yellow River Basin from 2000 to 2010[J]. Acta Ecologica Sinica,2013,33(24):7798 − 7806. (in Chinese with English abstract) Google Scholar
[14]	THEIL H. A rank-invariant method of linear and polynomial regression analysis[C]//Advanced Studies in Theoretical and Applied Econometrics. Dordrecht: Springer Netherlands, 1992: 345-381. Google Scholar
[15]	TIAN Q, WANG Q, ZHAN C, et al. Analysis of climate change in the coastal zone of Eastern China, against the background of global climate change over the last fifty years: case study of Shandong peninsula, China[J]. International Journal of Geosciences,2012,3(2):379 − 390. doi: 10.4236/ijg.2012.32042 CrossRef Google Scholar
[16]	张明明. 2000—2015年中国干旱半干旱区蒸散发时空变化及其影响因素分析[D]. 西安: 长安大学, 2019. Google Scholar ZHANG Mingming. Analysis of the temporal and spatial variation of evapotranspiration and its driving factors in arid and semi-arid region of China from 2000 to 2015[D]. Xi’an: Chang’an University, 2019. (in Chinese with English abstract) Google Scholar
[17]	温媛媛, 赵军, 王炎强, 等. 基于MOD16的山西省地表蒸散发时空变化特征分析[J]. 地理科学进展,2020,39(2):255 − 264. [WEN Yuanyuan, ZHAO Jun, WANG Yanqiang, et al. Spatiotemporal variation characteristics of surface evapotranspiration in Shanxi Province based on MOD16[J]. Progress in Geography,2020,39(2):255 − 264. (in Chinese with English abstract) doi: 10.18306/dlkxjz.2020.02.007 CrossRef Google Scholar
[18]	王丽霞, 张珈玮, 张双成, 等. 基于CA-Markov模型的陕西省植被覆盖模拟及预测[J]. 安徽农业科学,2020,48(4):53 − 56. [WANG Lixia, ZHANG Jiawei, ZHANG Shuangcheng, et al. Simulation and prediction of vegetation coverage in Shaanxi Province based on CA-Markov model[J]. Journal of Anhui Agricultural Sciences,2020,48(4):53 − 56. (in Chinese with English abstract) Google Scholar
[19]	BOUCHET R J. Évapotranspiration potentielle et évaporation sous abri[C]//Biometeorology. Amsterdam: Elsevier, 1962: 540-545. Google Scholar
[20]	邵小路, 姚凤梅, 张佳华, 等. 基于蒸散干旱指数的华北地区干旱研究[J]. 气象,2013,39(9):1154 − 1162. [SHAO Xiaolu, YAO Fengmei, ZHANG Jiahua, et al. Analysis of drought in North China based on evapotranspiration drought index[J]. Meteorological Monthly,2013,39(9):1154 − 1162. (in Chinese with English abstract) Google Scholar
[21]	薛阳, 金晓媚, 朱晓倩. 宁夏沿黄经济区蒸散量变化特征及水均衡方法验证[J]. 水文地质工程地质,2017,44(3):27 − 32. [Xue Yang, Jin Xiaomei, Zhu Xiaoqian. Variation of evapotranspiration of Ningxia Yellow River economic zone and the validation using water budget method[J]. Hydrogeology & Engineering Geology,2017,44(3):27 − 32. (in Chinese with English abstract) Google Scholar