Analysis of Dynamic Spatiotemporal Changes in Actual Evapotranspiration and Its Associated Factors in the Pearl River Basin Based on MOD16

Tao Zhang, Yangbo Chen
2017 Water  
Evapotranspiration is an important part of the hydrological cycle, surface energy balance and global climate system. Due to spatial heterogeneity, the trends in actual evapotranspiration (ET) and its associated factors vary in different regions. Because direct measurements of ET are limited over large areas, remote sensing provides an efficient method of ET spatial analysis, and standard data products are available at the global scale. This study uses the monthly MOD16 ET dataset and daily
more » ... aset and daily meteorological data to analyze the dynamic spatiotemporal changes in ET and its associated factors in the Pearl River Basin (PRB) from 2000 to 2014. The results of the study are as follows. (1) Over time and space, annual ET exhibited a slight increasing trend from 2000 to 2014, with an average value of approximately 946.56 mm/a. ET considerably varied at the monthly and seasonal scales, and in July displayed the highest monthly ET of approximately 119.57 mm, accounting for 36.37% of the annual ET. (2) ET displayed obvious spatial heterogeneity. Specifically, the west was a low-ET region, and moderate and high ET values were interspersed in the central and eastern PRB. Moreover, the rate of change of ET ranged from −13.99 mm/a to 12.81 mm/a in space, and 46.25% of the basin exhibited an increasing trend. (3) Dynamic changes in ET were mainly associated with temperature and relative humidity (RH). Additionally, energy-related elements and wind speed were positively correlated with ET, and temperature was the most influential factor of ET in some months (February-March and September-November). RH was the most important factor in other months but negatively correlated with ET in June and July. Affected by the actual environmental condition, qualitative changes were observed in the correlation between RH and ET in different months. The positive and negative spatial correlations between ET and its associated factors changed in different regions and in different months, and the changes mainly occurred from northwest to southwest. important content of water cycle, agricultural irrigation and climate change research under different global change scenarios [8] [9] [10] [11] . Because of the importance of ET, researchers around the world have extensively investigated ET changes [8, [12] [13] [14] [15] [16] . Generally, ET trends should increase in the context of global warming; however, observations have shown that actual ET and pan ET have decreased, and this contrary phenomenon is called the evaporation paradox [17] . Study showed the reference ET decreased in China in all seasons from 1954 to 1993, with increases in the northeast and southwest and decreasing trends in the northwest and southeast [8] . Another study showed annual ET exhibited a decreasing trend in most areas east of 100 • E in China from 1960 to 2002 and an increasing trend in the western and northern parts of northeast China [18] . Cong suggested that pan ET in China decreased from 1956China decreased from to 1985China decreased from and increased from 1986China decreased from to 2005. But reference evapotranspiration also showed increasing trend in some regions such as in southern Iran, Spain, Poland, and the Loess Plateau in China [20] [21] [22] [23] . These results suggest that ET in different regions exhibits different trends. Moreover, the main factors associated with ET will change due to the heterogeneity of different regions [11, 13, [24] [25] [26] [27] . Gong et al. suggested the humidity was the main factor that influenced reference ET in the Yangtze River Basin [28] . Yang et al. postulated that radiation and wind speed were the main factors associated with pan evaporation in China [29] . Another study found that relativity humidity, temperature, shortwave radiation and wind speed were the main factors that affected reference ET in the Hai River Basin [30] . Radiation was the most factor that most influenced the annual reference ET in the West Liao River Basin, while the average temperature, maximum temperature and relative humidity were the main factors in different seasons [26] . The response of ET to climate change varies in different regions and at different time scales; therefore, extensive research is required to investigate the factors related to ET in different regions and at different time scales [13, [31] [32] [33] . Researchers have used many methods to estimate ET in different regions [34] [35] [36] . Traditional methods rely on observation data from pan ET, energy balance Bowen ratio systems, eddy covariance measurements, large aperture scintillators, the crop factor method or ET calculation formulas [2, 12, [37] [38] [39] [40] . Although using the metrological data and interpolation methods can give a long-term ET, affected by the number, spatial distribution, and heterogeneity of observation stations, the regional accuracy of high-resolution spatial ET is difficult to assess [41, 42] . With the development of new technologies, remote sensing can cover extensive regions and provide high-resolution information [43] [44] [45] [46] . Based on the Landsat, Advanced Very High Resolution Radiometer, Moderate Resolution Imaging Spectroradiometer (MODIS) and other types of remote sensing images, the surface energy balance model, temperature plant index, and other estimation methods have been developed [43, 47, 48] , these can give a high-resolution ET spatial change in a large region. Based on the Penman-Monteith model, Mu used MODIS data and meteorological data to produce the official ET product of the National Aeronautics and Space Administration (NASA): MOD16 ET [49, 50] . This dataset provides eight-day, monthly and annual intervals of ET for global vegetated land areas at a 1-km 2 resolution, and reliable data can be conveniently obtained free of charge for ET studies in different region of the world [10,51]. Numerous researchers have used these data for studies in different regions [52, 53] . Notably, the MOD16 ET dataset performs well in forest areas and can estimate ET with reasonable accuracy [54]. Additionally, the MOD16 ET dataset perform best in studies of sites located in temperate and humid climates [10]. Wu et al. used the MOD16 ET to study the characteristics of land surface ET in the Poyang Lake Basin [55]; He et al. investigated surface ET in Shanxi Province based on the MOD16 product [56]; and Li et al. used the MOD16 ET to analyze the drought condition in Hainan Province [57] . Overall, based on the MOD16 product, many ET studies have been completed in the midwestern region of China, but few studies have been conducted in southern China. The Pearl River is the third largest river and with the second highest flow in China. Due to its location in a region of land and sea intersection in Southeast Asia, it is impacted by the South China Sea monsoon and tropical cyclones. Additionally, the basin receives considerable rainfall with an uneven
doi:10.3390/w9110832 fatcat:2tgysyfudrg2jl7odkpmctdvpq