Temporal variations of reference evapotranspiration and controlling factors: Implications for climatic drought in karst areas
Abstract: Variations in reference evapotranspiration (ET0) and drought characteristics play a key role in the effect of climate change on water cycle and associated ecohydrological patterns. The accurate estimation of ET0 is still a challenge due to the lack of meteorological data and the heterogeneity of hydrological system. Although there is an increasing trend in extreme drought events with global climate change, the relationship between ET0 and aridity index in karst areas has been poorly studied. In this study, we used the Penman–Monteith method based on a long time series of meteorological data from 1951 to 2015 to calculate ET0 in a typical karst area, Guilin, Southwest China. The temporal variations in climate variables, ET0 and aridity index (AI) were analyzed with the Mann–Kendall trend test and linear regression to determine the climatic characteristics, associated controlling factors of ET0 variations, and further to estimate the relationship between ET0 and AI. We found that the mean, maximum and minimum temperatures had increased significantly during the 65-year study period, while sunshine duration, wind speed and relative humidity exhibited significant decreasing trends. The annual ET0 showed a significant decreasing trend at the rate of −8.02 mm/10a. However, significant increase in air temperature should have contributed to the enhancement of ET0, indicating an “evaporation paradox”. In comparison, AI showed a slightly declining trend of −0.0005/a during 1951–2015. The change in sunshine duration was the major factor causing the decrease in ET0, followed by wind speed. AI had a higher correlation with precipitation amount, indicating that the variations of AI was more dependent on precipitation, but not substantially dependent on the ET0. Although AI was not directly related to ET0, ET0 had a major contribution to seasonal AI changes. The seasonal variations of ET0 played a critical role in dryness/wetness changes to regulate water and energy supply, which can lead to seasonal droughts or water shortages in karst areas. Overall, these findings provide an important reference for the management of agricultural production and water resources, and have an important implication for drought in karst regions of China.
Figure 6. Annual variability trends of meteorological factors during 1951–2015. (a) precipitation, (b) air temperature, (c) wind speed, (d) relative humidity, (e) mean vapor pressure, (f) sunshine duration, (g) minimum temperature, and (h) maximum temperature. Red dotted line represents linear regression of different meteorological variables, and gray dotted line represents 65-year average value.
Table 1. Meteorological station site and mean meteorological variables of Guilin, China
Guilin 110.30 25.32 164.40 19.0 75.1 2.4 1533.1 18.1 1902.6 Note: RH represents relative humidity; Tmean is the mean air temperature; U10 is the wind speed at the height of 10 m.
Table 2. Interdecadal variation in the annual and seasonal reference evapotranspiration (ET0) in Guilin, China
Summer ET0 (mm) Magnitude
Autumn ET0 (mm) Magnitude
1950s 1164.17 − 208.57 − 375.74 − 390.75 − 189.5 − 1960s 1167.32 0.3 207.49 −0.5 386.8 2.9 390.08 −0.2 183.32 −3.3 1970s 1130.66 −3.1 201.95 −2.7 367.04 −5.1 375 −3.9 185.46 1.2 1980s 1117.85 −1.1 201.44 −0.3 371.35 1.2 361.37 −3.6 182.7 −1.5 1990s 1126.85 0.8 205.62 2.1 354.46 −4.5 375.46 3.9 191.49 4.8 2000s 1136.89 0.9 209.48 1.9 362.59 2.3 382.44 1.9 182.99 −4.4 2010–2015 1104.9 −2.8 204.56 −2.3 363.2 0.2 364.44 −4.7 171.9 −6.1 Mean 1135.52 −0.9 205.59 −0.3 368.74 −0.5 377.08 −1.1 183.91 −1.6
Table 3. Mean, maximum and minimum annual and seasonal ET0 (Unit: mm)
Values Annual Spring Summer Autumn Winter Mean 1137.9 205.7 369.2 378.0 184.8 Maxmium 1269.5 243.1 424.7 444.2 225.6 Minimum 1010.4 178.5 325.5 320.3 133.7 Ratio (%) - 18.1 32.4 33.2 16.2
Table 4. Annual, seasonal changing rates of reference evaporation (ET0) and climate factors in Guilin, China
(m s−1 10a−1)
Vapor pressure (hpa 10a−1) Sunshine duration
Maximum temperature (°C 10a−1) Annual −8.02* 9.93 0.17* −0.074* −0.64* −0.02 −62.90* 0.20* 0.08* Spring 0.134 −14.39 0.253* −0.114* −0.58* 0.086 −84.45 0.279* 0.214* Summer −4.231* 28.81 0.102* −0.023 −0.358* 0.016 −14.62* 0.097* 0.043 Autumn −2.871 −11.872 0.153* −0.026 −0.78* −0.065 −18.27* 0.184* 0.046 Winter −1.138 7.715 0.154* −0.143* −0.727* −0.026* −14.695 0.239* 0.017 * indicate significant at the level of 0.05.
Table 5. Correlation coefficients between annual and seasonal climate factors and potential evapotranspiration in Guilin, China during 1951–2015
Precipitation Mean temperature Wind speed Relative humidity Vapor pressure Sunshine duration Maximum temperature Minimum temperature Annual −0.517** 0.129 0.414** −0.584** −0.525** 0.784** 0.489** −0.187 Spring −0.300* 0.555** −0.01 −0.658** 0.194 0.767** 0.728** 0.349** Summer −0.571** 0.451** 0.24 −0.569** −0.146 0.833** 0.690** 0.046 Autumn −0.693** 0.510** 0.366** −0.730** −0.508** 0.812** 0.718** 0.191 Winter −0.664** 0.275* 0.470** −0.836** −0.640** 0.761** 0.638** −0.13 ** significant correlation at the 99% confidence level (two−tailed); * significant correlation at the 95% confidence level (two−tailed). Noting that the maximum correlation coefficients in each season are shown in bold.
Table 6. Summary of previously estimated ET0 or pan evaporation (ETp) trends in China, and the primary causes of the trend
Location ET0 or ETp trend
Study period Cause Source China −3.0, ↓ 1955−2000 Solar irradiance Liu et al. 2004b China −8.56, ↓ 1961−2008 Wind speed
Yin et al. 2010 China −6.02, ↓ 1960−2007 − Liu et al. 2012 China −3.45, ↓ 1956−2015 Wind speed Fan et al. 2016 China −6.84, ↓ 1961−2013 Wind speed
Wang et al. 2017 China < −6.0, ↓ 1960−2012 Wind speed Chai et al. 2018 Yangtze River basin −12.4, ↓ 1960−2000 Net radiation
Xu et al. 2006 Yangtze River basin −3.26, ↓
ETp: −2.98, ↓
1961−2000 Wind speed
Wang et al. 2007 Yangtze River Delta (Eastern China) 22.51, ↑ 1957−2014 Relative humidity
Xu et al. 2017 Yellow River Basin 0.02, ↑ 1961−2006 Air temperature
Liu et al. 2010 Yellow River Basin −12.9, ↓ 1961−2012 Sunshine hours Zhang et al. 2015 Yellow River Basin −4.689, ↓ 1960−2012 Wind speed
She et al. 2017 Heihe River Basin 2.01, ↑ 1961−2014 Relative humidity Du et al. 2016 Songhua River Basin 4.90, ↑ 1961−2010 Mean air temperature Wen et al. 2014 Wei River Basin − 1959−2008 Relative humidity
Zuo et al. 2012 The North China Plain ETp: −7.09, ↓ 1981−2013 Radiation
Mo et al. 2017 Loess Plateau Region −10.30, ↓ 1961−2012 Wind speed Zhao et al. 2014 Tibetan Plateau −9.6, ↓ 1960−2012 − Wang et al. 2014 Qinghai−Tibetan Plateau −24.0, ↓ 1970−2011 Net radiation
Zhang et al. 2018b Northwest China −30.0, ↓ 1955−2008 Wind speed Huo et al. 2013 Shenzhen City − 1954−2012 Sunshine hours
Vapor pressure deficit
Liu et al. 2015 Yunnan province −6.50, ↓ 1961−2004 Sunshine duration Fan and Thomas 2013 Guizhou province −4.476, ↓ 1959−2011 Sunshine duration Gao et al. 2016 Southwest China −4.34, ↓ 1960−2013 Sunshine duration
Zhao et al. 2018 Southwest China −5.13, ↓ 1961−2012 Net radiation Sun et al. 2016 Note: The symbol “↑” and “↓” represent increasing and decreasing trends, respectively. The symbol “−” indicates that ET0 trend was not estimated. Noting that ETp specified in the table refers to pan evaporation, and the others represent ET0 estimated by the FAO56 Penman–Monteith method.
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