On the Attribution of Changing Reference Evapotranspiration in a Coastal Area of China

Reference evapotranspiration (ET0) is a crucial parameter for hydrological modeling, land-atmospheric interaction investigations and agricultural irrigation management. This study investigated changes in ET0 and attributed those changes to climate variations in a coastal area (Zhejiang province) of China by a numerical experiment method. The results indicated that annual ET0 increased significantly (p < 0.05) at a rate of 1.58 mm·year−1 from 1973 to 2013, which was mainly caused by an obvious increase in ET0 in spring. Air temperature and water vapor pressure deficits increased significantly (p < 0.05) at rates of 0.04 ◦C·year−1 and 0.005 kPa·year−1, respectively, at an annual time scale during the study period, while wind speed and solar radiation decreased significantly (p < 0.05) at rates of −0.01 m/s·year−1 and −3.94 MJ·m−2·day−1·year−1, respectively. The contributions of changes in air temperature, wind speed, water vapor pressure deficits and solar radiation to increases in ET0 were 0.39, −0.56, 2.62 and −0.61 mm·year−1, respectively. The decrease in wind speed and solar radiation negatively affected the increase in ET0, which was offset by the positive effects of the air temperature and water vapor pressure deficits increase, where the water vapor pressure deficits was the dominant factor in increasing ET0 in the coastal area. Moreover, the impact of topography on ET0 was further discussed. ET0 changes at plain stations were approximately 5.4 times those at hill stations, which may be due to the impact of a large water body and the augment of surface roughness from intense human activities in the well-developed plain area. The results are helpful for investigating spatial and temporal changes in the evaporative demand for well-developed regions under energy-limited conditions.


Introduction
Reference evapotranspiration (ET 0 ) is an important parameter for hydrological process simulations, land surface model investigations and agricultural irrigation management, especially in humid regions, which reflects a potential demand for evapotranspiration under a certain underlying surface [1][2][3][4].Under a changing climate, significant decreases in ET 0 have been reported all over the world, which are associated with increasing air temperature, also known as an "evaporation paradox" [5][6][7].However, recent studies indicated that ET 0 has shown an increasing trend, and the "evaporation paradox" has disappeared since the late 1990s [8][9][10].
Quantifying changes in ET 0 due to climate variations is an important issue in current studies.There are several methods for attributing ET 0 changes to climate variables, such as a regression analysis, sensitivity method, detrended method, differentiation approach and numerical modeling [11][12][13][14].For example, Vicente-Serrano et al. [14] studied the changes in monthly ET 0 in Spain by a sensitivity analysis and found there were spatial gradients in ET 0 sensitivity.Xu et al. [12] used a detrended method to study ET 0 changes in the Yangtze River catchment and concluded that the decrease in total net radiation was the dominant factor for changes in ET 0 .Liu and Sun [15] assessed atmospheric evaporation demands in 12 state-of-the-art global climate models against D20 pan evaporation observations by a differentiation approach.Sun et al. [16] attributed changes in ET 0 to climate variables in southwestern China using numerical experiments.These abundant investigations are beneficial for understanding the dynamic response of evaporative demand changes to complex land-atmospheric interactions [17][18][19].
Up to now, many studies on ET 0 changes are available for small catchments, continents and at the global scale [20][21][22].Changes in ET 0 exhibited different trends, and controlling factors varied under different climate conditions at different time scales [3,23,24].Wang and Dickinson [20] conducted an investigation on global atmospheric evaporative demands over land from 4250 globally distributed stations from 1973 to 2008 and found that the contribution of water vapor pressure deficits to the monthly variability of evaporative demands was much larger than that of solar radiation, wind speed and air temperature at the global scale.In addition, several studies have attempted to investigate the impact of natural factors (i.e., geography, water bodies, and climate conditions) and socio-economic factors on ET 0 (i.e., agriculture and household income) [10,25].For example, Zhang et al. [10] indicated that the amplitude of ET 0 changes near a large freshwater lake was larger than that away from the lake, which was due to a larger sensitivity of ET 0 to climate variables near the lake.Han et al. [26] found that the decrease in ET 0 was accelerated in agricultural stations, with a more significant decrease in the aerodynamic term in arid/semi-arid regions and a more significant decrease in the radiation term in humid regions.Litvak et al. [25] found that evapotranspiration from the total land area was linearly correlated with the median household income in Los Angeles, California.
Zhejiang province is one of the most developed regions in China and is located in the southeastern coastal area of the country [27].As a critical input for hydro-meteorological predictions, changes in ET 0 have been investigated by several researchers [28][29][30].Xu et al. [28] studied future ET 0 changes from 2011 to 2014 by a global sensitivity analysis method that used one regional climate model in Zhejiang province and concluded that intra-and inter-annual changes in ET 0 were mainly due to changes in solar radiation, relative humidity and daily minimum temperature.Pan et al. [29] investigated the sensitivity of ET 0 to climate variables in the Shengsi Islands in Zhejiang province and found that ET 0 was most sensitive to solar radiation in the summer and most sensitive to relative humidity during the remaining seasons.These results are important for the improvement of hydrological modeling, urban flood-drought risk management and the planning of commercial crop irrigation.However, a comprehensive quantification of changes in ET 0 to climate variables in Zhejiang province has not been available until recently.Moreover, the influence of topography on ET 0 changes has not been clear in this coastal area.
The objectives of this study are (1) to analyze the changes in ET 0 and climate variables in Zhejiang province from 1973 to 2013; (2) to quantify the contribution of climate variations to ET 0 changes; and (3) to discuss the influence of topography on ET 0 changes.

Study Area
Zhejiang province is located at the eastern coast of China, south of the Yangtze River Delta (Figure 1), which is one of the most rapidly developed regions in China [31].The area of this province is 1.02 × 10 5 km 2 , and the altitude ranges from −74 to 1922 m.Zhejiang province belongs to the typical Asian monsoon region.The average air temperature is 17.2 • C, the extreme maximum air temperatures is 43.2 • C and the extreme minimum air temperatures is −13.5 • C. The average annual rainfall is 1493.3mm.The rainstorm days is 4.1 days and 50% of rainstorm occurs during the Mei-Yu period from June to July, which is caused by a persistent stationary front known as the Mei-Yu front [32].This coastal province is affected by typhoon frequently, which mainly occurred during July to September [33,34].Zhejiang province is a powerful economic province in China, and the per capita net income ranks the first in China for more than 20 years, which has reached the level of moderately developed countries [35].
Atmosphere 2018, 9, 9 3 of 14 period from June to July, which is caused by a persistent stationary front known as the Mei-Yu front [32].This coastal province is affected by typhoon frequently, which mainly occurred during July to September [33,34].Zhejiang province is a powerful economic province in China, and the per capita net income ranks the first in China for more than 20 years, which has reached the level of moderately developed countries [35].

Data
Daily meteorological records from 1973 to 2013 at 46 meteorological stations were collected from Zhejiang Meteorological Bureau and included sunshine duration (hour), wind speeds at 10 m (m/s), relative humidity (%), minimum air temperature (°C), and maximum air temperature (°C).Considering the continuity of meteorological data, missing data from the selected stations were less than 2%.All meteorological data were accumulated into monthly values.If the data missing for a station were more than 9 days in a certain month, then the value of this month was replaced by the average climate value.Climate variables and ET0 for the whole province were averaged from all 46 stations.
The Digital Elevation Model (DEM) data for Zhejiang province was downloaded from the Global Land Cover Facility with a resolution of 90 m × 90 m [36], which was used to analyze the impact of topography on ET0 changes.

Calculation of ET0
The Penman-Monteith formula, recommended by the Food and Agriculture Organization of the United Nations, was used to estimate ET0 (mm), which represents the evaporative capacity of a

Data
Daily meteorological records from 1973 to 2013 at 46 meteorological stations were collected from Zhejiang Meteorological Bureau and included sunshine duration (hour), wind speeds at 10 m (m/s), relative humidity (%), minimum air temperature ( • C), and maximum air temperature ( • C).Considering the continuity of meteorological data, missing data from the selected stations were less than 2%.All meteorological data were accumulated into monthly values.If the data missing for a station were more than 9 days in a certain month, then the value of this month was replaced by the average climate value.Climate variables and ET 0 for the whole province were averaged from all 46 stations.The Digital Elevation Model (DEM) data for Zhejiang province was downloaded from the Global Land Cover Facility with a resolution of 90 m × 90 m [36], which was used to analyze the impact of topography on ET 0 changes.

Calculation of ET 0
The Penman-Monteith formula, recommended by the Food and Agriculture Organization of the United Nations, was used to estimate ET 0 (mm), which represents the evaporative capacity of a hypothetical reference crop with an assumed crop height of 0.12 m, a fixed surface resistance of 70 s•m −1 and an albedo of 0.23 [37]: where R n is the net radiation (MJ•m −2 •day −1 ), G is the soil heat flux density (MJ•m −2 •day −1 ), T is the mean air temperature ( • C), VPD is the water vapor pressure deficits (kPa), U 2 is the wind speed at 2 m (m•s −1 ), ∆ is the slope of the vapor pressure curve versus temperature (kPa• • C −1 ) and γ is the psychrometric constant (kPa Wind speed observed at 10 m was adjusted to 2 m by a logarithmic wind speed profile: G is calculated by: where T i and T i−1 are the air temperature at time i and i − 1. Solar radiation (R s ) is calculated by: where a s and b s are coefficients, n is the sunshine duration and N is the maximum possible duration of sunshine.R a is the extraterrestrial radiation calculated by the Angstrom formula [3].R n is calculated by: where α (=0.23) is the albedo of the reference grassland.σ is Stefan-Boltzmann constant (4.903 ), R so is clear-sky radiation (MJ•m −2 •day −1 ).

Attribution of Changes in ET 0
A numerical experiment method proposed by Sun et al. [16] was employed to quantify the impact of climate variations on changes in ET 0 in this study.For ET 0 , the combined effects of air temperature, solar radiation, wind speed and water vapor pressure deficits were designed in five experiments to attribute the influence of climate variations on ET 0 change, including one control experiment and four sensitivity experiments (Table 1).ET 0 calculated by the control experiment represented the combined influence of the four climate variables, whereas the ET 0 calculated by each sensitivity experiment represented the combined influence of the other three climate variables, excluding the non-changed variable.The impact of each climate variable on changes in ET 0 can then be estimated as: where L(ET 0 _CTR) and L(ET 0 _x i ) are the calculated long-term trends in ET 0 via a linear regression based on the control test and the sensitivity test, respectively.The variable x i represents either air temperature, solar radiation, wind speed or the water vapor pressure deficits, and C(x i ) is the contribution of the corresponding climate variable to ET 0 changes.Errors in the experiment analyses can be calculated as: Then, the relative contribution R(x i ) of each climate variable to changes in ET 0 can be calculated as:

Changes in ET 0
Figure 2 shows the spatial distribution of changes in annual ET 0 at 46 meteorological stations in Zhejiang province from 1973 to 2013.Annual ET 0 at 39 stations increased during the past 40 years and trends at 24 stations were significant at the 95% level.Highly increasing trends in ET 0 were generally located at northern and coastal stations, which are well-developed socio-economic regions.Annual ET 0 at 7 stations showed a decreasing trend, and only one station had a trend significant at the 95% level.Annual ET 0 increased significantly (p < 0.05) at a rate of 1.58 mm•year −1 , which was the provincial average (Table 2).For seasonal distribution, the changes in ET 0 clearly varied (Figure 3).It is worth noting that ET 0 decreased at 35 stations in winter, and the trends at 8 stations were significant at the 95% level.For the provincial average, ET 0 increased at rates of 1.12, 0.23 and 0.34 mm•year −1 during spring, summer and autumn, respectively, whereas ET 0 decreased at a rate of −0.17 mm•year −1 in winter.
Atmosphere 2018, 9, 9 5 of 14 Then, the relative contribution R(xi) of each climate variable to changes in ET0 can be calculated as:

Changes in ET0
Figure 2 shows the spatial distribution of changes in annual ET0 at 46 meteorological stations in Zhejiang province from 1973 to 2013.Annual ET0 at 39 stations increased during the past 40 years and trends at 24 stations were significant at the 95% level.Highly increasing trends in ET0 were generally located at northern and coastal stations, which are well-developed socio-economic regions.Annual ET0 at 7stations showed a decreasing trend, and only one station had a trend significant at the 95% level.Annual ET0 increased significantly (p < 0.05) at a rate of 1.58 mm•year −1 , which was the provincial average (Table 2).For seasonal distribution, the changes in ET0 clearly varied (Figure 3).It is worth noting that ET0 decreased at 35 stations in winter, and the trends at 8 stations were significant at the 95% level.For the provincial average, ET0 increased at rates of 1.12, 0.23 and 0.34 mm•year −1 during spring, summer and autumn, respectively, whereas ET0 decreased at a rate of −0.17 mm•year −1 in winter.

Changes in Climate Variables
Figure 4 shows the changes in climate variables related to ET0 in Zhejiang province during the period of 1973-2013.The annual mean air temperature at the 46 stations presented an upward trend, and all trends passed the 0.05 significance level by the t-test (Table 3).For the provincial average, the annual mean air temperature increased significantly (p < 0.05) at a rate of 0.04 °C•year −1 .Changing rates in air temperature were 0.04, 0.03, 0.03 and 0.03 °C •year −1 during the four seasons, respectively.
Wind speed showed declining trends at 35 stations, and the declining trend was significant (p < 0.05) at 29 stations.Wind speed at the other 11 stations showed rising tendencies, and the increasing trend was significant (p < 0.05) at 4 stations.For the regional average, the decreasing rate of wind speed for the whole province was −0.01 m/s•year −1 (p < 0.05) from 1973 to 2013 at both annual and seasonal time scales.

Changes in Climate Variables
Figure 4 shows the changes in climate variables related to ET 0 in Zhejiang province during the period of 1973-2013.The annual mean air temperature at the 46 stations presented an upward trend, and all trends passed the 0.05 significance level by the t-test (Table 3).For the provincial average, the annual mean air temperature increased significantly (p < 0.05) at a rate of 0.04 • C•year −1 .Changing rates in air temperature were 0.04, 0.03, 0.03 and 0.03 • C•year −1 during the four seasons, respectively.
Wind speed showed declining trends at 35 stations, and the declining trend was significant (p < 0.05) at 29 stations.Wind speed at the other 11 stations showed rising tendencies, and the increasing trend was significant (p < 0.05) at 4 stations.For the regional average, the decreasing rate of wind speed for the whole province was −0.01 m/s•year −1 (p < 0.05) from 1973 to 2013 at both annual and seasonal time scales.
Note: the number in the brackets indicates the number of stations where its trend is significant at the level of 0.05 by t-test.
The water vapor pressure deficits at all 46 stations showed an increasing trend, and the trends were significant at the 0.05 level at 45 stations.Water vapor pressure deficits increased significantly (p < 0.05) by 0.005 kPa•year −1 for the regional average.For the four seasons, the water vapor pressure deficits increased at rates of 0.006, 0.009, 0.005 and 0.001 kPa•year −1 , respectively.
Solar radiation decreased at 34 stations, and trends were significant at 26 stations.Solar radiation at the other 12 stations showed an increasing trend.For the provincial average, solar radiation  Note: the number in the brackets indicates the number of stations where its trend is significant at the level of 0.05 by t-test.
The water vapor pressure deficits at all 46 stations showed an increasing trend, and the trends were significant at the 0.05 level at 45 stations.Water vapor pressure deficits increased significantly (p < 0.05) by 0.005 kPa•year −1 for the regional average.For the four seasons, the water vapor pressure deficits increased at rates of 0.006, 0.009, 0.005 and 0.001 kPa•year −1 , respectively.
Solar radiation decreased at 34 stations, and trends were significant at 26 stations.Solar radiation at the other 12 stations showed an increasing trend.For the provincial average, solar radiation decreased significantly at a rate of −3.94 MJ•m −2 •day −1 •year −1 from 1973 to 2013.It is worth noting that solar radiation increased at a rate of 1.37 MJ•m −2 •day −1 •year −1 in the spring.

Quantification of ET 0 Changes
Figure 5 shows there are significant relationships between trends in ET 0 from the control test and the accumulated trends in ET 0 from the four sensitivity tests at annual and seasonal time scales.The R 2 is 0.98, and the relative error is −16.5% at the annual time scale for the provincial average (Table 4).R 2 ranges from 0.97 to 0.99, and the relative error ranges from −17.2 to 17.6% for the four seasons.This result indicates that the method used in this study is effective for quantifying the impact of climate variations on ET 0 changes.decreased significantly at a rate of −3.94 MJ•m −2 •day −1 •year −1 from 1973 to 2013.It is worth noting that solar radiation increased at a rate of 1.37 MJ•m −2 •day −1 •year −1 in the spring.

Quantification of ET0 Changes
Figure 5 shows there are significant relationships between trends in ET0 from the control test and the accumulated trends in ET0 from the four sensitivity tests at annual and seasonal time scales.The R 2 is 0.98, and the relative error is −16.5% at the annual time scale for the provincial average (Table 4).R 2 ranges from 0.97 to 0.99, and the relative error ranges from −17.2 to 17.6% for the four seasons.This result indicates that the method used in this study is effective for quantifying the impact of climate variations on ET0 changes.During the period from 1973 to 2013, changes in air temperature, wind speed, water vapor pressure deficits and solar radiation led to changes in ET0 of 0.39, −0.56, 2.62 and −0.61 mm•year −1 , respectively, at the annual time scale.The positive effects of the increase in air temperature and water vapor pressure deficits were offset by the negative effects of the decrease in wind speed and solar radiation.The combined effects of the four climate variables led to an increase in ET0 of 1.84 mm•year −1 .The increase in the water vapor pressure deficits was the dominant factor for the increase in ET0.For the 46 stations, air temperature, wind speed, water vapor pressure deficits and solar radiation were the dominant factors for changes in ET0 at 0, 1, 43, and 2 stations, respectively (Figure 6).During the period from 1973 to 2013, changes in air temperature, wind speed, water vapor pressure deficits and solar radiation led to changes in ET 0 of 0.39, −0.56, 2.62 and −0.61 mm•year −1 , respectively, at the annual time scale.The positive effects of the increase in air temperature and water vapor pressure deficits were offset by the negative effects of the decrease in wind speed and solar radiation.The combined effects of the four climate variables led to an increase in ET 0 of 1.84 mm•year −1 .The increase in the water vapor pressure deficits was the dominant factor for the increase in ET 0 .For the 46 stations, air temperature, wind speed, water vapor pressure deficits and solar radiation were the dominant factors for changes in ET 0 at 0, 1, 43, and 2 stations, respectively (Figure 6).Seasonally, air temperature and water vapor pressure deficits have positive effects on the increase in ET0 in spring, summer and autumn and negative effects on the decrease in ET0 in winter.The decrease in wind speed has a negative effect on the increase in ET0 in spring, summer and autumn and a negative effect on the decrease in ET0 in winter.The decrease in solar radiation has a negative effect on the increase in ET0 in summer and autumn, but it has a positive effect on ET0 changes in spring and winter.The increase in water vapor pressure deficits is the controlling factor for the increase in ET0 in spring, summer and autumn, while a rapid decrease in solar radiation is the controlling factor for the decrease in ET0 in winter (Figure 7).Seasonally, air temperature and water vapor pressure deficits have positive effects on the increase in ET 0 in spring, summer and autumn and negative effects on the decrease in ET 0 in winter.The decrease in wind speed has a negative effect on the increase in ET 0 in spring, summer and autumn and a negative effect on the decrease in ET 0 in winter.The decrease in solar radiation has a negative effect on the increase in ET 0 in summer and autumn, but it has a positive effect on ET 0 changes in spring and winter.The increase in water vapor pressure deficits is the controlling factor for the increase in ET 0 in spring, summer and autumn, while a rapid decrease in solar radiation is the controlling factor for the decrease in ET 0 in winter (Figure 7).Seasonally, air temperature and water vapor pressure deficits have positive effects on the increase in ET0 in spring, summer and autumn and negative effects on the decrease in ET0 in winter.The decrease in wind speed has a negative effect on the increase in ET0 in spring, summer and autumn and a negative effect on the decrease in ET0 in winter.The decrease in solar radiation has a negative effect on the increase in ET0 in summer and autumn, but it has a positive effect on ET0 changes in spring and winter.The increase in water vapor pressure deficits is the controlling factor for the increase in ET0 in spring, summer and autumn, while a rapid decrease in solar radiation is the controlling factor for the decrease in ET0 in winter (Figure 7).

Influence of Topography on ET 0 Changes
It seems plausible that the changes in ET 0 at plain stations are larger than those at hill stations (Figures 2 and 3), which reflects the impacts of topography on ET 0 changes.Therefore, all 46 stations are classified into two categories based on the degree of topographic relief: stations in the plain area, where the degree of topographic relief is lower than 100 m, which reflects the influence of a large water body, and stations in the hill area (25 stations), where the degree of topographic relief is larger than 100 m, which reflects the influence of topography [38][39][40][41].
Figure 8 shows the comparison of ET 0 changes and the contributions of the two categories.The annual trends in ET 0 for the plain category and hill category are 2.67 and 0.50 mm•year −1 , respectively.The former increase is 5.4 times the latter This might be caused by the location of plain stations in well-developed cites, and intense human activities must influence underlying surface characterizations [42,43].For example, the increase in air temperature and water vapor pressure deficits for the coastal plain category is 1.5 and is 1.6 times that of the hill category (Figure 9).It is worth noting that the decreases in solar radiation and wind speed for the plain category are smaller than those for the hill category, which has a negative effect on the increase in ET 0 .The contributions of solar radiation, air temperature, wind speed and water vapor pressure deficits to the increase in ET 0 are −12%, 17.92%, −19.3% and 124.2%, respectively, for the plain category, and the increase in water vapor pressure deficits plays a dominant role in ET 0 increase.For the hill category, the contributions of solar radiation, air temperature, wind speed and water vapor pressure deficits to the increase in ET 0 are −181.1%,59%, −122.5% and 387.5%, respectively.Although the water vapor pressure deficits is still the dominant factor for ET 0 increase, influences from solar radiation and wind speed cannot be ignored either.Moreover, it can be found in Figure 8 that the increase in ET 0 in these two categories is due to the rapid increase in ET 0 in spring.

Influence of Topography on ET0 Changes
It seems plausible that the changes in ET0 at plain stations are larger than those at hill stations (Figures 2 and 3), which reflects the impacts of topography on ET0 changes.Therefore, all 46 stations are classified into two categories based on the degree of topographic relief: stations in the plain area, where the degree of topographic relief is lower than 100 m, which reflects the influence of a large water body, and stations in the hill area (25 stations), where the degree of topographic relief is larger than 100 m, which reflects the influence of topography [38][39][40][41].
Figure 8 shows the comparison of ET0 changes and the contributions of the two categories.The annual trends in ET0 for the plain category and hill category are 2.67 and 0.50 mm•year −1 , respectively.The former increase is 5.4 times the latter one.This might be caused by the location of plain stations in well-developed cites, and intense human activities must influence underlying surface characterizations [42,43].For example, the increase in air temperature and water vapor pressure deficits for the coastal plain category is 1.5 and is 1.6 times that of the hill category (Figure 9).It is worth noting that the decreases in solar radiation and wind speed for the plain category are smaller than those for the hill category, which has a negative effect on the increase in ET0.The contributions of solar radiation, air temperature, wind speed and water vapor pressure deficits to the increase in ET0 are −12%, 17.92%, −19.3% and 124.2%, respectively, for the plain category, and the increase in water vapor pressure deficits plays a dominant role in ET0 increase.For the hill category, the contributions of solar radiation, air temperature, wind speed and water vapor pressure deficits to the increase in ET0 are −181.1%,59%, −122.5% and 387.5%, respectively.Although the water vapor pressure deficits is still the dominant factor for ET0 increase, influences from solar radiation and wind speed cannot be ignored either.Moreover, it can be found in Figure 8 that the increase in ET0 in these two categories is due to the rapid increase in ET0 in spring.Generally, humidity in this coastal province is very high, and the water vapor pressure deficits is the dominant factor affecting changes in ET0.The other two important factors affecting increases in ET0 are wind speed and solar radiation.The coastal Zhejiang province has a strong sea-land breeze due to land-atmosphere interactions [44,45].Therefore, the decrease in wind speed in the plain category is smaller than that of the hill category, although the increase in surface roughness from intense human activities is much more obvious for the plain category.In addition, the plain category also has a smaller decrease in solar radiation than the hill category.Lin et al. [46] indicated that solar radiation considerably decreases with wind stilling for weakened wind, which amplified the impact of aerosol emissions on solar dimming.The contribution of air temperature to the increase in ET0 is Generally, humidity in this coastal province is very high, and the water vapor pressure deficits is the dominant factor affecting changes in ET 0 .The other two important factors affecting increases in ET 0 are wind speed and solar radiation.The coastal Zhejiang province has a strong sea-land breeze due to land-atmosphere interactions [44,45].Therefore, the decrease in wind speed in the plain category is smaller than that of the hill category, although the increase in surface roughness from intense human activities is much more obvious for the plain category.In addition, the plain category also has a smaller decrease in solar radiation than the hill category.Lin et al. [46] indicated that solar radiation considerably decreases with wind stilling for weakened wind, which amplified the impact of aerosol emissions on solar dimming.The contribution of air temperature to the increase in ET 0 is the smallest of the four factors.However, numerous studies have found that air temperature is the dominant factor affecting the increase in ET 0 in past decades [13,20,22].This might be due to the coastal area being characterized by the energy-limited condition, where the impact of air temperature is limited on ET 0 increase.In addition, this study considers the water vapor pressure deficits as an influential factor, rather than water vapor pressure, which leads to a different contribution result from previous studies.
Atmosphere 2018, 9, 9 11 of 14 the smallest of the four factors.However, numerous studies have found that air temperature is the dominant factor affecting the increase in ET0 in past decades [13,20,22].This might be due to the coastal area being characterized by the energy-limited condition, where the impact of air temperature is limited on ET0 increase.In addition, this study considers the water vapor pressure deficits as an influential factor, rather than water vapor pressure, which leads to a different contribution result from previous studies.

Conclusions
This study investigated the spatial and temporal changes in ET0 along the coast of Zhejiang province during the period of 1973 to 2013, and a numerical experiment method was used to quantify the contribution of climate variations to changes in ET0.The results indicated that the annual ET0 increased significantly (p < 0.05), with a slope of 1.58 mm•year −1 during the past 40 years.At the seasonal time scale, ET0 increased in spring, summer and autumn but decreased in winter.Air temperature, water vapor pressure deficits, wind speed and solar radiation changed significantly (p < 0.05) at rates of 0.04 °C•year −1 , 0.005 kPa•year −1 , −0.01 m/s•year −1 and −3.94 MJ•m −2 •day −1 •year −1 , respectively.
The results of the five numerical experiments manifested that changes in air temperature, wind speed, vapor pressure deficits and solar radiation led to annual changes in ET0 by 24.7%, −35.4%, 165.8% and −38.6%, respectively, and the relative error of the numerical experiment method was −16.5%.An increase in the water vapor pressure deficits was the controlling factor for increasing ET0 along the coastal province.The impacts of topography on ET0 changes were further analyzed.The trend in ET0 for the plain category was approximately 5.4 times that of the hill category.This might be caused by the influence of a large water body, as well as the augment of surface roughness by intense human activities in the well-developed plain area.
This study provides a comprehensive understanding of ET0 changes in a well-developed coastal province and highlights the important role of water vapor pressure deficits to increases in ET0.Further investigation is required to properly quantify the influence of human activities on evaporative demand, such as the urban heat island effect and the augment of surface roughness.Our

Conclusions
This study investigated the spatial and temporal changes in ET 0 along the coast of Zhejiang province during the period of 1973 to 2013, and a numerical experiment method was used to quantify the contribution of climate variations to changes in ET 0 .The results indicated that the annual ET 0 increased significantly (p < 0.05), with a slope of 1.58 mm•year The results of the five numerical experiments manifested that changes in air temperature, wind speed, vapor pressure deficits and solar radiation led to annual changes in ET 0 by 24.7%, −35.4%, 165.8% and −38.6%, respectively, and the relative error of the numerical experiment method was −16.5%.An increase in the water vapor pressure deficits was the controlling factor for increasing ET 0 along the coastal province.The impacts of topography on ET 0 changes were further analyzed.The trend in ET 0 for the plain category was approximately 5.4 times that of the hill category.This might be caused by the influence of a large water body, as well as the augment of surface roughness by intense human activities in the well-developed plain area.
This study provides a comprehensive understanding of ET 0 changes in a well-developed coastal province and highlights the important role of water vapor pressure deficits to increases in ET 0 .Further investigation is required to properly quantify the influence of human activities on evaporative demand, such as the urban heat island effect and the augment of surface roughness.Our results are helpful for hydrological modeling, land-atmospheric interaction simulations and irrigation of eco-agriculture planning.

Figure 1 .
Figure 1.Sketch map of the study area.

Figure 1 .
Figure 1.Sketch map of the study area.

Figure 2 .
Figure 2. (a) Significance of changes in annual ET0 at 46 meteorological stations in Zhejiang Province from 1973 to 2013.S and NS in the figure legend indicate significance and insignificance at p = 0.05, respectively.The numbers given after S or NS indicate the number of stations out of 46 stations that fall these categories; (b) Slopes in annual ET0 at 46 meteorological stations.

Figure 2 .
Figure 2. (a) Significance of changes in annual ET 0 at 46 meteorological stations in Zhejiang Province from 1973 to 2013.S and NS in the figure legend indicate significance and insignificance at p = 0.05, respectively.The numbers given after S or NS indicate the number of stations out of 46 stations that fall these categories; (b) Slopes in annual ET 0 at 46 meteorological stations.

Figure 3 .
Figure 3. Trends in ET0 at 46 meteorological stations in Zhejiang Province from 1973 to 2013 in (a) spring; (b) summer; (c) autumn and (d) winter.

Figure 3 .
Figure 3. Trends in ET 0 at 46 meteorological stations in Zhejiang Province from 1973 to 2013 in (a) spring; (b) summer; (c) autumn and (d) winter.

Figure 5 .
Figure 5. Relationships between trends in ET0 by the control test, as well as accumulated trends in ET0 by the four sensitivity tests.

Figure 5 .
Figure 5. Relationships between trends in ET 0 by the control test, as well as accumulated trends in ET 0 by the four sensitivity tests.

Figure 6 .
Figure 6.Contribution of climatic variations to changes in annual ET0 at 46 stations in Zhejiang province.

Figure 6 .
Figure 6.Contribution of climatic variations to changes in annual ET 0 at 46 stations in Zhejiang province.

Figure 6 .
Figure 6.Contribution of climatic variations to changes in annual ET0 at 46 stations in Zhejiang province.

Figure 7 .
Figure 7.The same as Figure 6, but for (a) spring; (b) summer; (c) autumn and (d) winter.Figure 7. The same as Figure 6, but for (a) spring; (b) summer; (c) autumn and (d) winter.

Figure 7 .
Figure 7.The same as Figure 6, but for (a) spring; (b) summer; (c) autumn and (d) winter.Figure 7. The same as Figure 6, but for (a) spring; (b) summer; (c) autumn and (d) winter.

Figure 8 .
Figure 8. Comparisons of ET0 and its contributions for the (a) plain category and (b) hill category.

Figure 8 .
Figure 8. Comparisons of ET 0 and its contributions for the (a) plain category and (b) hill category.

Figure 9 .
Figure 9. Comparisons of (a) solar radiation, (b) air temperature, (c) wind speed and (d) water vapor pressure deficits variations for the plain category (orange bar) and the hill category (gray bar).

Figure 9 .
Figure 9. Comparisons of (a) solar radiation, (b) air temperature, (c) wind speed and (d) water vapor pressure deficits variations for the plain category (orange bar) and the hill category (gray bar).

Table 1 .
Numerical experiment design for ET 0 contribution.ET 0_ CTR air temperature, solar radiation, wind speed, actual vapor pressure from 1973-2013 Temperature Test: ET 0 _T air temperature maintained in 1973, the others same as the control test Solar radiation Test: ET 0_ R s solar radiation maintained in 1973, the others same as the control test Wind speed Test: ET 0 _U 2 wind speed maintained in 1973, the others same as the control test Actual vapor pressure Test: ET 0 _VPD water vapor pressure deficits maintained in 1973, the others same as the control test

Table 1 .
Numerical experiment design for ET0 contribution.ET0_CTR air temperature, solar radiation, wind speed, actual vapor pressure from 1973-2013 Temperature Test: ET0_T air temperature maintained in 1973, the others same as the control test Solar radiation Test: ET0_Rs solar radiation maintained in 1973, the others same as the control test Wind speed Test: ET0_U2 wind speed maintained in 1973, the others same as the control test Actual vapor pressure Test: ET0_VPD water vapor pressure deficits maintained in 1973, the others same as the control test

Table 2 .
Trends in ET0 and climate variables in the study area during the period of 1973-2013.
Note: * means the slope is significant at the level of 0.05 by t-test.

Table 2 .
Trends in ET 0 and climate variables in the study area during the period of 1973-2013.

Table 3 .
Number of stations (out of 46 stations) with ET0 and climate variables changes at annual and seasonal time scales.

Table 3 .
Number of stations (out of 46 stations) with ET 0 and climate variables changes at annual and seasonal time scales.

Table 4 .
Contributions of climate variations to ET0 changes in Zhejiang province during the period from 1973 to 2013.

Table 4 .
Contributions of climate variations to ET 0 changes in Zhejiang province during the period from 1973 to 2013.