Effects of forest evapotranspiration on soil water budget and energy flux partitioning in a subalpine valley of China

Effects of forest evapotranspiration on soil water budget and energy flux partitioning in a subalpine valley of China

Agricultural and Forest Meteorology 246 (2017) 207–217 Contents lists available at ScienceDirect Agricultural and Forest Meteorology journal homepag...

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Agricultural and Forest Meteorology 246 (2017) 207–217

Contents lists available at ScienceDirect

Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet

Effects of forest evapotranspiration on soil water budget and energy flux partitioning in a subalpine valley of China ⁎

Chunhua Yana, Wenli Zhaoa, Yue Wanga, Qingxia Yangb, Qingtao Zhangc, , Guo Yu Qiua,

MARK



a

Shenzhen Engineering Laboratory for Water Desalination with Renewable Energy, School of Environment and Energy, Peking University, Shenzhen 518055, China Jiuzhaigou Administration Bureau, Jiuzhaigou County 623402, Aba Prefecture, Sichuan Province, China c Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute, Department of Water Resources and Environment, School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China b

A R T I C L E I N F O

A B S T R A C T

Keywords: Evapotranspiration Energy flux Precipitation Runoff Energy-limited Forest rehabilitation

Jiuzhaigou Valley (JZG) has been rated as World Heritage, National Nature Reserves and world-class places of interests, due to its fantastic beauty of water. In recent years, however, JZG is losing its beauty with runoff decreasing and stream drying up. An increase of evapotranspiration (ET) over the rehabilitating forest is assumed to be the main reason for runoff decreasing, however, this assumption remained untested for lack of longterm observing data. To test this assumption, a long-term field experiment was carried out from August 2013 to December 2015 in JZG over a typical secondary forest. Meteorological parameters and energy fluxes were measured by eddy covariance system, soil moisture by time-domain reflectometry probes, and ET by eddy covariance method and soil water budget. Results showed that (1) despite the limitation of high elevation, high atmospheric humidity and low annual air temperature, annual ET was quite large. It was 700 mm and 739 mm, respectively for 2014 and 2015, while the corresponding precipitation (P) was 1003 mm and 782 mm. ET/P was close or over 1, which meant that P was mostly used for forest ET and only a very small proportion of P contributed to runoff. (2) The ratio of latent heat flux (LE) to net radiation (Rn) was 0.69 and 0.75 in the growing season of 2014 and 2015, respectively. These high LE/Rn ratio values were considerably higher in JZG than in other areas of the Tibetan Plateau, which could be attributed to better forest rehabilitation in JZG. Our results also showed that ET at the forest site was limited by available energy. We conclude that ET in JZG was energylimited, whereas forest ET consumed most precipitation. (3) The above assumption is verified to be true. The high ET rate after forest rehabilitation in JZG comes at a cost of decreasing runoff and leads to streams drying up. These results will be useful for sustainable managements of water and forest in JZG.

1. Introduction

northeast Qinghai-Tibet Plateau and the Sichuan Basin. It has been rated as World Heritage, National Nature Reserves and world-class places of interests, due to its fantastic beauty of water. However, longterm observed precipitation showed insignificant changing trends in both center and edge of Qinghai-Tibet Plateau while ET showed increasing trends, resulting in a decreasing trend in discharge (Yang et al., 2011). It has also been found in recent years, JZG is losing its beauty with runoff decreasing and stream drying up and this phenomenon is especially remarkable during spring when the forest began to foliate (Di et al., 2011; Gan and Zheng, 2007; Liu et al., 2011; Wu et al., 2012a, 2012b). Di et al. (2011) demonstrated that the wetland area in Jiuzhaigou Valley decreased from 2.34 km2 in 1983 to 1.61 km2 in 2002. It was also demonstrated by Liu et al. (2011) that the water area decreased by about 30% from 1997 to 2005. Furthermore, JZG has experienced forest harvest between 1964 and 1979 and forest

Evapotranspiration is a major component of the water cycle and energy budget in forest ecosystems that links other hydrological processes such as runoff, deep percolation and so on (Wilson and Baldocchi, 2000; Wever et al., 2002; Zhu et al., 2014). Understanding seasonal variability in ET and the effects of forest evapotranspiration on energy flux and soil water, is important for investigating precipitation redistribution of forests, especially for forests after rehabilitation (Sheng et al., 2008), and is vital for water balance (Jones and Post, 2004). There is an urgent need for further study of ET for water resources management and hydrological processes of forests after rehabilitation. Jiuzhaigou Valley (JZG), located in the upper reach of the Jialing River, is a subalpine river valley in the transition zone between the



Corresponding authors. E-mail addresses: [email protected] (Q. Zhang), [email protected] (G.Y. Qiu).

http://dx.doi.org/10.1016/j.agrformet.2017.07.002 Received 19 October 2016; Received in revised form 28 June 2017; Accepted 2 July 2017 0168-1923/ © 2017 Elsevier B.V. All rights reserved.

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Fig. 1. Location of the study area. The experimental site where the eddy covariance system was installed is located in the red circle. The rivers flows from south to north, with the only outlet lie in the entrance to Jiuzhaigou Valley (black triangle). The green pentagon stands for the Primary Forest in JZG, which locates in the upper of the watershed and was not disturbed by forest harvest from 1966 to 1979. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

hence caused a reduction in runoff. Minjiang Valley, located adjacent to JZG, has similar climate, topography and vegetation distribution as JZG. It also suffered forest harvest in the last century and experienced post-logging forest rehabilitation as JZG during the same period. The forest coverage in Minjiang Valley has only increased from 18.8% to approximately 30% (Zhang et al., 2005; Zhang et al., 2008), while in JZG, it has already increased to around 65% (Bossard et al., 2015). The ET/P ratio in Minjiang Valley was only 30–40% and that in JZG can be supposed to be much higher due to better forest rehabilitation, which remained untested for lack of detailed observing data. For the present study, it is hypothesized that the ET in JZG is limited by water availability as in other places on the Qinghai-Tibet Plateau and high ET following forest rehabilitation is the critical factor to the decline of runoff. To test these hypotheses, we examined the characteristics of annual and rain season soil water content, seasonal patterns of water and energy flux exchange over a secondary forest in JZG. The present study aimed to: (1) investigate the partitioning of precipitation into forest ET, runoff and soil water, (2) elucidate the characteristics of forest ET and the water cost of forest rehabilitation, and (3) reveal the characteristics of energy flux partitioning and the controlling factors of forest ET.

rehabilitation since 1980 (Yang et al., 1998; Cheng and Mou, 2007; Qiao, 2012). The forest timber volume of JZG was 4 million cubic meters before 1964 and during the forest harvest period, every year more than 0.1 million cubic meters of wood was removed from the forest. Now the primary forest only exists in the upper reach of the watershed with an elevation higher than 3000 m (Fig. 1). After forest rehabilitation for more than 30 years, the landscape in JZG is dominated by forestland, which controls the water and energy exchange of the entire landscape (Liu et al., 2011). To explain the change in the water cycle, it is essential to have a good knowledge of seasonal variability in forest ET. Due to its unique topographical and landscape features, the water and energy fluxes on the Qinghai-Tibet Plateau play an important role in climate, from local to global scales (Gu et al., 2005). And great efforts have been made on the Qinghai-Tibet Plateau in the energy and water cycle over grass or shrub (Tanaka et al., 2001; Gu et al., 2005; Song et al., 2005; Hu et al., 2009; Liu et al., 2009; Yao et al., 2011; Zhang et al., 2014; Gu et al., 2015) and forests (Cheng et al., 2003; Lin et al., 2012; Zhu et al., 2014). Gu et al. (2005) and Yao et al. (2011) found that for the alpine meadow ecosystems sensible heat flux (H) was higher than LE in winter and spring, but was lower than LE in summer and autumn. However, in a subalpine spruce forest ecosystem, even in summertime more available energy is consumed as H than as LE (Zhu et al., 2014). Regardless of the different patterns of energy partitioning, the reported LE/Rn ratio is generally lower than 0.5 even in the growing season and is limited by the low soil water content (Gu et al., 2005; Zhu et al., 2014; Gu et al., 2015). However, there is a lack of research about the water and energy exchange in the transition area between QinghaiTibet Plateau and the Sichuan Basin. The annual ET/P ratio is usually associated with land uses, vegetation types and climate and is widely used to investigate the impacts of climate and landscape changes on regional hydrology (Zhang et al., 2001; Donohue et al., 2006; Yang et al., 2009; Li et al., 2013; Zhang et al., 2015). They found that grassland transferring to forestland, afforestation or vegetation recovery would lead to greater ET/P ratio and

2. Material and methods 2.1. Study site The study site (Jiuzhaigou Valley, JZG) is located in Jiuzhaigou County of the Aba Tibetan and Qiang Autonomous Prefecture, Sichuan Province (32°53′ − 33°20′N, 103°46′ − 104°05′E, Fig. 1). JZG lies in a transition zone between the northern subtropical area and the warm temperate area of the Tibet Plateau and is marked by a highland temperate monsoon climate. Mean annual precipitation determined by the average of measured precipitation from Songpan meteorological station from 1956 to 2014 was 762 mm, most of which occurred in the rainy season from April to October. Daily air temperature ranged from 208

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−3.7 °C (the average in January) to 16.8 °C (the average in July) and the mean daily air temperature was 7.3 °C (Hao, 2009). And annual relatively air humidity is approximately 70%. Because JZG lies in the upper reach of the Jialing River and is the water resource area, precipitation is the only incoming term in the regional water balance (Qiao, 2012). The experimental site is located in a conifer and broadleaf mixed forest (33°9.54′N, 103°52.86′E) at an elevation of 2478 m. This forest experienced harvest during 1964–1979, and after rehabilitation for more than 30 years, it’s now a close-canopy forest dominated by pine (Pinus tabulaeformis), oak (Quercus liaotungensis) as well as some subcanopy species such as Chinese paper birch (Betula albo-sinensis) and maple (Acer ginnala) (Hao, 2009; Dai et al., 2010).

LEeq =

(2)

where Δ is the slope of the relationship between saturation vapor pressure and air temperature (kPa K−1), γ is the psychrometric constant (kPa K−1), Rn is net radiation (W m−2) and G is soil heat transfer (W m−2). The missing or rejected sensible heat flux (H) data were gap-filled using the linear temporally local relationships between H and net radiation (Stoy et al., 2006). After gap-filling, the flux data were finally summed to daily values and annual values. After gap-filling, energy budget closure was used to evaluate the eddy covariance data, which was determined by using the linear regression statistics between (LE + H) and (Rn − G) following Wilson and Baldocchi (2000). The energy budget closure was 0.75 and 0.69 for 2014 and 2015, which was reported to range from 0.55 to 0.99 (Wilson et al., 2002; Shi et al., 2008; Wu et al., 2012a,b). This energy budget closure indicates that data at this site were reasonably satisfactory. Soil water budgets, which could give comparable results through the use of TDR with eddy covariance measurements (Wilson et al., 2001; Schelde et al., 2011), were used to estimate water consumption from the observing soil water layers during bright days. To apply this method, it is assumed that the measured volumetric soil water contents at 3, 10, 20, 30, 40, 50, 60 and 80 cm could apply to soil levels at 0–5, 5–15, 15–25, 25–35, 35–45, 45–55, 55–65 and 65–85 cm, respectively. At our site, above 85 cm the soil type is brown loam and it contains stones below a depth of 85 cm (Qiao, 2012). Therefore, these levels could accurately reveal the vertical movements of soil water in the rooting depth and soil characteristics. It was also assumed that the contribution of soil water below 85 cm to evaporation or transpiration was negligent. Previous studies in forests have demonstrated that evaporation or transpiration showed little response to soil water below 80 cm. Raz-Yaseef et al. (2012) reported soil evaporation was related to soil moisture in the topsoil (5 cm depth) and transpiration was related to soil moisture at a depth of 10–20 cm in a pine forest. It was also demonstrated that in a humid forest ET was controlled by soil water content in the upper 15 cm of soil (Sun et al., 2014). Additionally, deciduous species in JZG have more shallow root distribution than the local conifer species (Bossard et al., 2015). Hence soil water budget is feasible at this pine mixed forest in JZG. To estimate daily values of soil water consumption above 85 cm, the soil water storage for each layer was firstly calculated by the product of the measured volumetric soil water content and the thickness of the relevant soil layer. Then the daily soil water storage change for each layer was obtained from the difference in soil water storage for each layer for two consecutive days. Finally, we obtained the daily values by summing the daily soil water storage changes for all layers. To exclude the effect of rain events on soil water movements, forest ET should be estimated from soil water consumption only for the bright days which were more than 2 days after rain events. In our study, soil water budgets were utilized to monitor soil water movement and investigate the water source for forest ET in 5 typical days of the dry period of growing season in 2014 (July 18–22). Long-term meteorological data were also obtained from the Songpan meteorological station (Location: 32°39′N, 103°33.6′E, 2852 m elevation), which is the nearest meteorological station with the longest data for JZG. Data were derived from the Chinese meteorological association (http://data.cma.cn/). The trends of air temperature and precipitation were analyzed by the slope and the significance was test by Mann-Kendall method (Mann, 1945; Kendall, 1975). To investigate the control of atmospheric demand on forest ET, the measured evapotranspiration from the eddy covariance was compared with potential evapotranspiration (LEp), which is defined as the amount of evaporation under a sufficient water source condition and was given by Monteith and Unsworth (1990) as follows

2.2. Measurements A 30-m-high tower was selected for installing eddy covariance system and meteorological instruments. The fluctuations in CO2 and H2O density were measured using an open path infrared gas analyzer (LI7500A, LI-COR, Lincoln, NE, USA). A three-dimensional ultrasonic anemometer (R3-50, Gill, Hampshire, UK) was used to measure wind speed and direction. Air temperature and humidity (SKH2060, Skye, Inc., Powys, UK), downward and upward solar and longwave radiation (CNR-4, Kipp & Zonen, Delft, Netherlands), and precipitation (7852MAB, Davis, California, USA) were also measured. All data were logged at 10 Hz on a LI-7550 Analyzer Interface Unit (LI-COR, Lincoln, NE, USA) and recorded on a CR3000 datalogger (Campbell Scientific, Logan, UT, USA). The eddy covariance system started to work in August 2013 and stopped in the end of 2015. Soil heat flux, volumetric soil water contents and soil temperature were measured for the successive time of eddy covariance. Two soil heat flux plates (HFP01, Hukseflux, Netherlands) were installed at 5 cm below the ground. The volumetric soil water contents and soil temperature were measured at depths of 3, 10, 20, 30, 40 and 50 cm using five time-domain reflectometry probes (SM300, Delta-T Devices Ltd, Burwell, Cambridge, UK). The volumetric soil water contents at depths of 60 and 80 cm were also measured using another two time-domain reflectometry (TDR) probes (ML-2X, Delta-T Devices Ltd, Burwell, Cambridge, UK). Both the soil heat flux plates and soil moisture sensors were installed in a flat area which was about 2 m away from the surrounding tree. These data were sampled every 1 min and the 10-min averages were stored on a CR1000 datalogger (Campbell Scientific, Logan, UT, USA). 2.3. Data processing and analysis The 10-Hz raw measuring data were initially processed via CR3000 code, as shown in Fig. 2, and the 30-min data fluxes of latent heat, sensible heat, radiation and water vapor were also recorded on CR3000 datalogger. After obtained half-hour values of energy fluxes from the eddy covariance system, we then gap-filled the missing or rejected flux data due to anomalous factors or instrument malfunction. The gap-filling was done through the method described by Wilson and Baldocchi (2000) with the following equation

LE = αLEeq

Δ (Rn − G ) Δ+γ

(1)

where α is the 2-week average Priestly-Talyor coefficient (Priestley and Taylor, 1972) and can be obtained by the ratio of total LE and total LEeq during the 2-week period when LE is available. LEeq is the equilibrium evapotranspiration for the same half hour. Priestley and Taylor (1972) suggested that air moving from an extensive area of uniform wet surface into an air mass should come into equilibrium with the wet surface when VPD equals to 0, and thus gave the equilibrium evapotranspiration as follows 209

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Fig. 2. Flow charts of eddy covariance data processing.

LEp =

Δ(Rn − G ) + ρRCpVPD / ra Δ + γ (1 + rc / ra)

depends on energy availability (Jarvis and Mcnaughton, 1986; Monteith and Unsworth, 1990). In this study, the following exponential function was used to investigate the relationship between the Priestly-Talyor coefficient α and canopy surface conductance gc as previous researchers have done (de Bruin, 1983; Komatsu, 2010; Monteith, 1995)

(3) −3

where ρ is the air density (kg m ), Cp is the specific heat of air at constant pressure (J kg−1 K−1), VPD is the vapor pressure deficit (kPa), ra is the aerodynamic resistance (s m−1), and rc is the canopy surface resistance (s m−1). In this study, canopy surface conductance ( gc , m s−1) was used to assess the relative importance of the environmental and biological controls in evapotranspiration. Canopy surface conductance describes the resistance of mass and heat transfer through the transpiring canopy and evaporating soil surface and plays a major role in determining energy flux partitioning (Monteith, 1995). It is the inverse of canopy surface resistance (Dingman, 1992), and could be calculated by inverting the Penman-Monteith equation through the use of the measured latent heat flux (LE) and sensible heat flux (H) of the calibration data set, as follows (Gu et al., 2005; Shi et al., 2008; Zhu et al., 2014):

ρCpVPD 1 1 Δ H rc = = + ( − 1) gc γLE ga γ LE

α = αm(1 − exp( − gc /g0 ))

where αm and g0 are two fitting parameters. In most of these studies, αm ranges from 1.1 to 1.4, g0 is close to 5 mm s−1 and g0 probably depends on conditions at the top of the convective boundary layer. 3. Results and discussion 3.1. General meteorological characteristics Meteorological observations at the experimental site (Fig. 3a) indicated a higher annual rainfall in 2014 (1003 mm) and a comparable rainfall in 2015 (782 mm) compared with mean annual rainfall from 1956 to 2014 (762 mm), in both year more than 70% of which occurred during the rainy season. The rainy season usually started in April with small rain events (∼5 mm day−1), and there were occasionally larger rain events (∼20 mm day−1 but up to 60 mm day−1) during the main rainy period between June and September. Rain typically ceased during the dry season from November to March. Due to seasonal evolution and changes in weather, the daily net radiation was highly variable, ranging from around 0 W m−2 during winter to more than 200 W m−2 during summer (Fig. 3a). In 2014 and 2015, the annual average Rn and the total net radiation were 94.99 W m−2 and 2.98 GJ m−2, 97.77 W m−2 and 3.08 GJ m−2, respectively. Seasonal variation in air temperature followed a similar pattern as that of Rn (Fig. 3b). The lowest daily mean temperature was −6.17 °C and −4.86 °C, and the highest temperature was 20.08 °C, 21.08 °C, respectively for 2014 and 2015. The mean annual air temperature in these two years was 7.64 °C and 8.10 °C, which were slightly higher than the mean annual air temperature from 1956 to 2014 (Hao, 2009). The mean annual air relative humidity was 71% and 69% in 2014 and 2015. RH > 70% was observed during 208 days of 2014 and during 201 days in 2015(Fig. 3b). on meteorological data from the Songpan meteorological station, despite large variations occurred in mean annual precipitation, ranging from 513 mm to 1003 mm (Fig. 4). Most precipitation in this region occurred in synch with the growing season (Fig. 9b), and thus water availability is not usually a limiting factor in forest growth, as discussed by Yin et al. (2010) and Schwartz et al. (2013). Compared with other

(4)

where ga (m s−1) is aerodynamic conductance of the boundary layer between the effective water vapor source within the vegetation and a reference height within the surface vegetation layer, and depends on the aerodynamic characteristics of the surface and wind speed (Monteith, 1995). It is the inverse of resistance ra (Dingman, 1992), and could be estimated as follows (Monteith and Unsworth, 1990)

ra =

u 1 = 2 + 6.2u∗−0.67 ga u∗

(5)

where u is the mean wind velocity, and u is the friction velocity esti* mated from the eddy covariance system. The decoupling coefficient (Ω ) was also calculated to determine the relative importance of surface conductance and net radiation to changes in seasonal and yearly evapotranspiration. It describes the degree of decoupling or coupling between vegetation and the atmosphere, and could be obtained from the equation proposed by Jarvis and Mcnaughton (1986):

Ω=

Δ+γ Δ + γ (1 + ga / gc )

(7)

(6)

Generally, the value of Ω ranges from 0 to 1. As Ω approaches 0, vegetation is strongly coupling with the atmosphere and thus the control of surface conductance on evapotranspiration increases, while as Ω is close to 1, vegetation decouples with the atmosphere and in this context, ET is poorly controlled by surface conductance and primarily 210

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Fig. 3. Daily values of (a) precipitation (P) and net radiation (Rn), and (b) air temperature (T) and relative humidity (RH) over the forest in JZG during the study period. Bars stand for the daily sum values for precipitation. Each dot represents daily average values for net radiation, air temperature and relative humidity.

showed gradual thawing of snow and frozen soil beginning in February. All soil water layers were initially wettest after the recharge by the thawing of snow and frozen soil when soil temperature exceeded 0 °C. Subsequently soil water of all measured soil layers gradually dried (Fig. 5b). As showed in Fig. 4b, soil water content near the surface fluctuated more than that at deeper depths, corresponding to the rain events. Similar results were also found in the summer monsoon season (Kurc and Small, 2004). Shallow (10 cm beneath the surface) soil water content varied from 0.39 m3 water m−3 soil in the rainy season to 0.12 m3 water m−3 soil in the dry season, while deep (60 cm beneath the surface) soil moisture was comparatively constant year-round, merely changing from 0.42 m3 water m−3 soil to 0.34 m3 water m−3 soil. Overall, both the shallow and deep soil water contents gradually declined from April despite the start of the rainy season in both 2013 and 2014 (data for 2013 not shown), with an unusual increase observed in September of 2014, which is possibly due to particularly high rainfall. Rainfall in September of 2014 was 283 mm in 2014, which is more than twice of rainfall in September of 2013 (134 mm) and annual mean rainfall in September from 1956 to 2014 (110 mm) (Schwartz et al., 2013). The increase of soil water in early spring and the declining trend throughout rainy season indicates that at our site, soil water was mainly recharged by the thawing of snow and frozen soil. Even during the rainy season precipitation contributed little to deep (60–80 cm beneath the surface) soil water infiltration. To further investigate the movement of soil water in soil layers, soil

forest sites with similar precipitation (Lei et al., 1994; Liu et al., 2000), JZG was characterized by high elevation, high atmospheric humidity and low annual air temperature. The vapor pressure deficit was generally low, which can suppress vapor transfer powers and consequently lead to low ET (Yu et al., 2009; Yang et al., 2011). Even for the Faber fir forest ecosystem in the eastern Tibetan Plateau, which received much higher precipitation of 1932 mm, the annual ET was quite low (366 mm) and was attributed to high elevation, high atmospheric humidity and low annual temperature (Yin et al., 2010). Accordingly, the rate of ET as well as the ET/P ratio in JZG was also supposed to be quite low. This is conflictive with our hypothesis that high ET following forest rehabilitation is the critical factor to the decline of runoff, which needed further investigation. The trends of air temperature and precipitation were analyzed by the slope and the significance was test by Mann-Kendall method (Mann, 1945; Kendall, 1975). As shown in Fig. 4, annual air temperature showed a significant increasing trend from 1956 to 1993 (+0.0090 °C year−1, p < 0.001), while in recent years since 1993, the increasing trend has become larger (+0.0220 °C year−1, p < 0.001). It was also found that there was a nonsignificant increase in annual precipitation (+0.2 mm year−1, p = 0.83). 3.2. Characteristics of annual and rain season soil water content Variationin air temperature (Fig. 3b) and soil temperature (Fig. 5a)

Fig. 4. Trends in annual mean air temperature (T, orange solid line, left axis) and annual precipitation (P, red dash line, right axis) from 1956 to 2014 in JZG. The air temperature and precipitation data are from the Songpan meteorological station (Location: 32°39′N, 103°33.6′E, 2852 m elevation), which is the longest-running station near JZG. Data are derived from the Chinese meteorological association (http://data.cma.cn/). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

211

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Fig. 5. Seasonal variations in (a) soil temperature for six measured depth (3, 10, 20, 30, 40 and 50 cm) and (b) soil water content for eight measured depth (3, 10, 20, 30, 40, 50, 60 and 80 cm) during the study period. Note that the vertical black dot lines represent the start of soil thawing in 2014 and 2015, respectively.

4

3

2

1

Soil water budget

Eddy covariance

0

Fig. 7. Daily evapotranspiration (ET), calculated by a soil water budget that was based on the withdrawal of water in the upper 80 cm of the soil and daily ET, measured by eddy covariance. Comparison were made during a rain-free period in the dry period of growing season of 2014 (18–22 July).

no significant soil water stress and that trees maintained access to soil water throughout the growing season. These results suggest that in the days of wet period or other days of dry period with rainfall events, soil water storage in the top 80 cm would be also sufficient for forest ET. It is then concluded that this forest in JZG could access to enough soil water throughout the growing season and forest ET was not limited by water availability.

Fig. 6. Diurnal patterns of (a) soil water content (30-min means) for 3, 10, 20, 30, 40, 50, 60 and 80 cm beneath the soil surface, and (b) the rate of evapotranspiration (ET) measured by eddy covariance. The measurements were made during a rain-free period in the dry period of growing season of 2014 (18–22 July).

3.3. Characteristics of forest evapotranspiration Seasonal variation in daily evapotranspiration and potential evapotranspiration (ETp) in 2014 are shown in Fig. 8. Daily ET varied with the seasons for the whole year. Daily rates of ET were less than 0.4 mm day−1 in January and later linearly increased to up to 6 mm day−1 during the early spring from April to May, which was in congruence with the growing season for the forest. The average ET at our study site was 1.9 mm day−1, higher than the results from subalpine forests in a mountainous area of southwestern China (∼1.6 mm day−1, Cheng et al., 2003; 0.11–2.56 mm day−1 average for each season, Zhu et al., 2014). In spite of the decrease in soil water from May to August (Fig. 5b), there was no significant reduction in daily ET (In 2014, slope was +0.009 mm day−1, p < 0.001; in 2015, slope was +0.001 mm day−1, p = 0.6) and daily ET in JZG still maintained a high level (∼3.5 mm day−1). ET varied closely with ETp throughout the year. A good relationships was found between ETp and measured ET on both a daily and monthly basis (For daily scales, Pearson correlation coefficient = 0.94, p < 0.001, Fig. 8; and for monthly scales, Pearson

water conditions were analyzed for five bright days of dry period during the growing season of 2014 which were more than 2 days after heavy rain events. Despite smaller variation in deep soil water content, soil water contents for all layers decreased during daytime and remained relatively constant at night, coincident with the daily variation in instantaneous ET rate from eddy covariance (Fig. 6). This diurnal pattern of soil moisture variation with depth indicated that most active roots distributed above a depth of 80 cm. During the rain-free days of dry period, the daily total soil water consumption in the top 85 cm soil layer was 2.3–3.7 mm day−1, which was in excellent agreement with the daily evapotranspiration measured by eddy covariance (Fig. 7), indicating that most soil water storage in the upper 80 cm of the soil was used to maintain the same or higher ET (Rocha et al., 2004; Tanaka et al., 2004). In addition, during the driest period of growing season, the soil at a depth of 80 cm remained moist (more than 0.34 m3 water m−3 soil) (Fig. 5b), implying thatthere was 212

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Fig. 8. Variation in (a) daily evapotranspiration and (b) daily potential evapotranspiration (ETp) over the forest in JZG in the study period.

Fig. 9. Variation in (a) monthly evapotranspiration (ET), monthly potential evapotranspiration (ETp), monthly precipitation (P) in the study period and (b) mean monthly precipitation.

2006; Kosugi et al., 2007; Oishi et al., 2010). Therefore, the fairly constant and high annual ET in 2014 and 2015 was representative for the annual ET of this forest site in other years, and it was approximately equal to mean annual precipitation (762 mm). This high ET/P ratio indicated that in JZG forest area, most of precipitation was consumed by forest ET and only a small proportion contributed to runoff. The ET/P ratio is usually associated with land use, vegetation type and climate. It was much higher in JZG than in the nearby subalpine forests with similar climate conditions and topographic features (Lei

correlation coefficient = 0.99, p < 0.001, Fig. 9). The annual evapotranspiration in 2014 and 2015 was 700 mm and 739 mm, respectively, and was slightly less than the annual potential evapotranspiration (731 mm and 787 mm respectively for 2014 and 2015). Despite large fluctuations in precipitation in 2014 and 2015 (1003 mm and 782 mm), inter-annual fluctuations in evapotranspiration were very small, which is also reported in the previous studies that forest evapotranspiration showed only modest inter-annual variability with annual precipitation (Wilson and Baldocchi, 2000; Stoy et al., 213

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an annual scale. Therefore, we can conclude that the maximum increase in ET/P ratio occurred following forest rehabilitation in JZG with similarannual evapotranspiration and mean annual precipitation.

Table 1 Summaries of energy partitioning for the growing season and whole year of 2014 and 2015. Year

2014

2015

Rn/W m−2

LE/W m−2

H/W m−2

G/W m−2

LE/Rn

H/Rn

Whole year Growing season

95 125

54 86

20 23

0 2

0.57 0.69

0.21 0.18

Whole year Growing season

98 121

59 91

19 23

−2 −1

0.60 0.75

0.20 0.19

3.4. Characteristics of energy flux partitioning Seasonal variations in daily total values of Rn, H, LE and G are shown in Fig. 9. There was a seasonal trend in soil heat flux (G), following the variation of Rn (Fig. 9a). The soil changed to an energy sink (G > 0) from mid-March through most of the summer. The maximum 24-h average soil heat flux (less than 8 W m−2) generally occurred between April and June. During this period, the mean midday G was 10–15 W m−2 and the whole daily ratio of G to Rn was less than 5%. By late September, soil heat flux changed direction and reached minimum daily values (approximately 6 W m−2). During winter, G was often a considerable part of energy partitioning, occupying approximately 10% of net radiation. However, on a yearly scale, the magnitude of the soil heat flux was less than 1% of the total annual net radiation (Table 1). These results are consistent with previous research in temperate forests (Baldocchi, 1997; Wilson and Baldocchi, 2000; Saigusa et al., 2002; Wu et al., 2007). Fig. 10b shows the seasonal variations in sensible and latent heat flux in 2014 and 2015. The daily mean sensible heat flux varied between −8 and 100 W m−2 on a yearly scale. A large part of the net radiation was consumed by H in winter (Fig. 10b) and H reached a maximum before leaf emergence. As the forest began to foliate in spring, there was a dramatic drop in sensible heat, while latent heat increased meanwhile, as net radiation did. After leaf expansion, daily H was quite constant (∼23 W m−2) and LE represented the dominant consumption of available energy throughout the growing season, with a daily mean value of 86 W m−2. Seasonal variations in LE and H were consistent with other results on the Tibetan Plateau, showing that sensible heat flux is the major energy partition in the pre-monsoon and post-monsoon period (spring and winter), whereas latent heat flux become greater than sensible heat flux and is the dominant component of available energy during the monsoon season (summer and autumn) (Gu et al., 2005; Gu et al., 2015; Yao et al., 2011). As shown in Table 1, The LE/Rn ratio in JZG was 0.69 and 0.75 in the growth period of 2014 and 2015, respectively. However, previous studies found that the LE/Rn no more than 0.5 (Gu et al., 2005, 2015; Zhu et al., 2014), indicating that more energy was consumed by forest ET in JZG. A lower LE/Rn ratio in other highland-monsoon areas was attributed to the limitation of available water for forest ET. At our site,

et al., 1994; Liu et al., 2000; Zhang et al., 2008). For example, ET was much lower (only 30–40% of total precipitation) in the Minjiang Valley, which features similar vegetation, climate and topography as JZG. The forests at both sites suffered timber harvesting in the last century and experienced post-logging forest rehabilitation. The forest coverage in Minjiang Valley has increased from 18.8% to approximately 30% (Zhang et al., 2005; Zhang et al., 2008), while in JZG, forest coverage has already increased more than 60%. Hence the higher ET/P ratio in JZG can be attributed to better forest rehabilitation at our site, despite the limitation of high elevation, high atmospheric humidity and low annual air temperature. In addition, according to the relationship between annual forest ET and precipitation proposed by Zhang et al. (2001) from the Budyko framework, P is mostly partitioned into ET when P is no more than 800 mm. And the maximum difference occurred in the ratio of ET to P for forests with different structure, stand composition and coverage when annual precipitation equals to atmospheric demand (762 mm vs 731–787 mm for this site). Forests with higher canopy coverage generally have higher ET and lower runoff as actual ET could be enhanced following forest rehabilitation (Dore et al., 2012; Beck et al., 2013; Benyon et al., 2015). Donohue et al. (2006) also demonstrated that 3–9 years after deforestation, forests start to have higher ET than undisturbed forest, and approximately 5–27 years after deforestation, ET would be 25%-50% higher than in undisturbed forest. For most hydrological applications, precipitation is appropriately assumed to be independent of vegetation types (Calder, 1998), and no significant increase in precipitation was observed at our site (Fig. 4). Yang et al. (2011) verified that the Budyko framework is still applicable to study the effects of energy availability and water availability on regional ET under such special climate conditions in the Tibetan Plateau region at

Fig. 10. Seasonal variations in (a) net radiation and soil heat flux, and (b) latent heat flux (LE) and sensible heat flux (H) for the study period. Each dot represents the daily mean.

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Fig. 11. Seasonal variations in (a) Priestley–Taylor coefficient (α), (b) surface conductance (gc) and (c) decoupling coefficient (Ω) in the research period. All values are daily means.

Fig. 12. The relationship between daily Priestley–Taylor coefficient α and the canopy surface conductance gc. According to Monteith (1995), the asymptotic value of α typically ranges between 1.1 and 1.4 (1.22 and 1.26 at our site), and another constant in the fitted equation is typically ∼5 mm s−1 (7.11 mm s−1 and 7.77 mm s−1 at our site).

(> 15 mm s−1) in the growing season suggested a low sensitivity of ET to physiological control and thus a significant effect of environmental controls (Rn or VPD) on ET. The decoupling coefficient (Ω, Fig. 11c) during the growing season was also mostly greater than 0.5 and can be up to 0.8, indicating that Rn contributed more to the ET (Vourlitis et al., 2002; Wever et al., 2002; Gu et al., 2005; Khatun et al., 2011; Wilson et al., 2000). Therefore, forest ET in JZG was mainly limited by available energy. And the higher LE/Rn ratio in this energy-limited area could be attributed to higher forest ET that occurred following the process of forest rehabilitation.

however, annual ETp (759 mm averaged for 2014 and 2015) was slightly less than mean annual precipitation (762 mm), and it has been generally recognized that annual ET relates to potential evapotranspiration when ETp ≤ P, while ET relates to P when ETp > P (Budyko, 1958; Zhang et al., 2001; Komatsu et al., 2008). Therefore, ET in JZG is controlled by energy availability, rather than by precipitation (plant available water). The higher LE/Rn ratio in this energy-limited area could be attributed to higher forest ET that occurred following the process of forest rehabilitation. To access the relative importance of the environmental (Rn and VPD) and biological (gc) controls in evapotranspiration, seasonal behaviors of Priestley–Taylor coefficient (α), surface conductance (gc) and decoupling coefficient (Ω) were also investigated for the forest (Fig. 11). At our site, the mean daily α during the growing season of 2014 and 2015 was 1.06 and 1.12, respectively (Fig. 11a), indicating available energy rather than water supply controls on forest ET (Priestley and Taylor, 1972; Zhu et al., 2014). The seasonal variations in gc was similar to those of α (Fig. 11b). When gc was larger than 15 mm s−1, α was insensitive to gc (Fig. 12). The larger gc

4. Conclusions JZG is characterized by high elevation, high atmospheric humidity and low annual air temperature. ET under such special conditions is generally supposed to be low. However, the annual measured ET was 700 mm and 739 mm, respectively for 2014 and 2015, while the corresponding precipitation (P) was 1003 mm and 782 mm. The ET/P ratio was much higher than that of the nearby subalpine forests with similar 215

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Dingman, S.L., 1992. Physical Hydrology. Prentice Hall. Donohue, R.J., Roderick, M.L., Mcvicar, T.R., 2006. On the importance of including vegetation dynamics in Budyko's hydrological model. Hydrol. Earth Syst. Sci. 11 (2), 983–995. Dore, S., Montes-Helu, M., Hart, S.C., et al., 2012. Recovery of ponderosa pine ecosystem carbon and water fluxes from thinning and stand-replacing fire. Glob. Change Biol. 18 (10), 3171–3185. Gan, J.J., Zheng, L.M., 2007. A study of landscape geological environment and water cyclic system in the central scenic spot in the Jiuzhai valley-Huanglong scenic spots. Acta Geol. Sichuan 27 (1), 53–55. Gu, L., Yao, J., Hu, Z., Zhao, L., 2015. Comparison of the surface energy budget between regions of seasonally frozen ground and permafrost on the Tibetan Plateau. Atmos. Res. 153, 553–564. Hao, Y., 2009. The dynamics of land cover change pattern and landscape fragmentation in Jiuzhaigou Nature Reserve, China. Proceedings of SPIE − The International Society for Optical Engineering 7498. Hu, Z., Yu, G., Zhou, Y., et al., 2009. Partitioning of evapotranspiration and its controls in four grassland ecosystems: application of a two-source model. Agric. For. Meteorol. 149 (9), 1410–1420. Jarvis, P.G., Mcnaughton, K.G., 1986. Stomatal control of transpiration: scaling up from leaf to region. Adv. Ecol. Res. 15 (15), 1–49. Jones, J.A., Post, D.A., 2004. Seasonal and successional streamflow response to forest cutting and regrowth in the northwest and eastern United States. Water Resour. Res. 40 (5), 191–201. Kendall, M.G., 1975. Rank Correlation Methods. Griffin, London. Khatun, R., Ohta, T., Kotani, A., et al., 2011. Spatial variations in evapotranspiration over East Asian forest sites: I. Evapotranspiration and decoupling coefficient. Hydrol. Res. Lett. 5, 83–87. Komatsu, H., Maita, E., Otsuki, K., 2008. A model to estimate annual forest evapotranspiration in Japan from mean annual temperature. J. Hydrol. 348 (3–4), 330–340. Komatsu, H., 2010. Forest categorization according to dry-canopy evaporation rates in the growing season: comparison of the priestley–taylor coefficient values from various observation sites. Hydrol. Processes 19 (19), 3873–3896. Kosugi, Y., Takanashi, S., Tanaka, H., et al., 2007. Evapotranspiration over a Japanese cypress forest. I. Eddy covariance fluxes and surface conductance characteristics for 3 years. J. Hydrol. 337 (3–4), 269–283. Kurc, S.A., Small, E.E., 2004. Dynamics of evapotranspiration in semiarid grassland and shrubland ecosystems during the summer monsoon season, central New Mexico. Water Resour. Res. 40 (9), W09305. Lei, R., Shang, L., Tang, Z., 1994. The Influence of Human Activities on Hydrological Functions of a Quercus Aliena Forest. Studies on forest ecosystems, Northeast Forestry University Press, Harbin, pp. 235–244. Li, D., Pan, M., Cong, Z., Zhang, L., Wood, E., 2013. Vegetation control on water and energy balance within the Budyko framework. Water Resour. Res. 49 (2), 969–976. Lin, Y., Wang, G.X., Guo, J.Y., Sun, X.Y., 2012. Quantifying evapotranspiration and its components in a coniferous subalpine forest in Southwest China. Hydrol. Processes 26 (20), 3032–3040. Liu, S., Sun, P., Wang, J., Chen, L., 2000. Hydrological functions of forest vegetation in upper reaches of the Yangtze River. J. Nat. Res. 16 (5), 451–456. Liu, S., Li, S.G., Yu, G.R., Sun, X.M., 2009. Surface energy exchanges above two grassland ecosystems on the Qinghai-Tibetan Plateau. Biogeosci. Dis. 6 (5), 9161–9192. Liu, Y., Wang, Q., Wang, J., 2011. Landscape pattern and stability analysis of Jiuzhaigou Nature Reserve in Sichuan China. Geoinformatics, 2011 19th International Conference on 1–4. Mann, H.B., 1945. Nonparametric tests against trend. Econometrica 13, 245–259. Monteith, J.L., Unsworth, M.H., 1990. Principles of Environmental Physics, 2nd ed. Chapman and Hall, New York, USA. Monteith, J.L., 1995. Accommodation between transpiring vegetation and the convective boundary layer. J. Hydrol. 166 (3), 251–263. Oishi, A.C., Oren, R., Novick, K.A., Palmroth, S., Katul, G.G., 2010. Interannual invariability of forest evapotranspiration and its consequence to water flow downstream. Ecosystems 13 (3), 421–436. Priestley, C.H.B., Taylor, R.J., 1972. On the assessment of surface heat flux and evaporation using large-scale parameters. Mon. Weather Rev. 100 (2), 81–92. Qiao, X., 2012. The Impacts of Regional Air Pollution on the World Natural Heritage Site, Jiuzhaigou National Nature Reserve, Southwestern China. College of Architecture and Environment, Sichuan University, China (Doctor Degree dissertation). Raz-Yaseef, N., Dan, Y., Schiller, G., Cohen, S., 2012. Dynamics of evapotranspiration partitioning in a semi-arid forest as affected by temporal rainfall patterns. Agric. For. Meteorol. 157 (2), 77–85. Rocha, H.R.D., Goulden, M.L., Miller, S.D., et al., 2004. Seasonality of water and heat fluxes over a tropical forest in Eastern Amazonia. Ecol. Appl. 14 (4), 22–32. Saigusa, N., Yamamoto, S., Murayama, S., Kondo, H., Nishimura, N., 2002. Gross primary production and net ecosystem exchange of a cool-temperate deciduous forest estimated by the eddy covariance method. Agric. For. Meteorol. 112 (3–4), 203–215. Schelde, K., Ringgaard, R., Herbst, M., et al., 2011. Comparing evapotranspiration rates estimated from atmospheric flux and TDR soil moisture measurements. Vadose Zone J 10 (1), 78–83. Schwartz, M.W., Dolanc, C.R., Gao, H., et al., 2013. Forest structure, stand composition, and climate-growth response in montane forests of Jiuzhaigou National Nature Reserve, China. PLoS One 8 (8), 23473–23487. Sheng, H., Cai, T., Cui, X., 2008. Rainfall redistribution of a virgin forest and secondary forest in Northeast China. Front. For. China 3 (2), 189–193. Shi, T., Guan, D., Wang, A., et al., 2008. Comparison of three models to estimate evapotranspiration for a temperate mixed forest. Hydrol. Processes 22 (17), 3431–3443.

climate conditions and topographic features but much lower degree of forest rehabilitation, indicating the higher ET/P ratio was caused by forest rehabilitation. This high ratio also indicated that most precipitation was used by ET of the rehabilitated forest and only a very small proportion of P was partitioned as runoff. All soil water layers were initially wettest after the recharge by the thawing of snow and frozen soil and subsequently soil water of all measured gradually dried regardless of rainfall events. But during the driest period of growing season, the soil at a depth of 80 cm remained moist (more than 0.34 m3 water m−3 soil), forest ET could still be access to soil water to maintain a relatively high rate. Hence, forest ET was not limited by water availability. Sensible heat flux was the major energy partition in the spring and winter season, whereas latent heat flux was the dominant component of available energy in the summer and autumn season. The LE/Rn ratio in JZG was 0.69 and 0.75 in the growth period, considerably higher than ratios reported in other areas on the Tibetan Plateau. And this LE/Rn ratio also maintained at a high level in the study period as soil water content declined. The high values of α and Ω in the growing season suggest that forest ET in JZG was limited by available energy. We then conclude that ET in JZG was energy-limited, whereas forest ET consumed most precipitation. The high ET rate after forest rehabilitation in JZG comes at a cost of decreasing runoff and leads to streams drying up. These results will be useful for sustainable managements of water and forest in JZG. Acknowledgments We acknowledge, with gratitude, the financial support from Shenzhen Science and Technology Project (JCYJ20130331145022339, JCYJ20140417144423187 and JCYJ20150331160617771), the Special Fund for Forestry Research in the Public Interest (201304305), and the National Natural Science Foundation of China (31470707). The authors would like to express their great thanks to Mr. Jiao Xiang, Yongqiang Wang and Zhenhua Wang for their assistance in this study. Great thanks also to Science office of Jiuzhaigou Administrative Bureau and College of Architecture and Environment, Sichuan University for their great helps and cooperation in the field experiments. The authors would like to express their great thanks to Jianhua Wang, Yang Zhang, Tong Li and for Elsevier Language Editing for their efforts to improve the grammar of this paper. References Baldocchi, D., 1997. Measuring and modelling carbon dioxide and water vapour exchange over a temperate broad-leaved forest during the 1995 summer drought. Plant Cell Environ. 20 (9), 1108–1122. Beck, H.E., Bruijnzeel, L.A., Dijk, A.I.J.M., Mcvicar, T.R., 2013. The impact of forest regeneration on streamflow in 12 meso-scale humid tropical catchments. Hydrol. Earth Syst. Sci. Dis. 10 (7), 3045–3102. Benyon, R.G., Lane, P.N.J., Jaskierniak, D., Kuczera, G., Haydon, S.R., 2015. Use of a forest sapwood area index to explain long-term variability in mean annual evapotranspiration and streamflow in moist eucalypt forests. Water Resour. Res. 51 (7). Bossard, C.C., Cao, Y.T., Wang, J.Y., Rose, A., Tang, Y., 2015. New patterns of establishment and growth of Picea, Abies and Betula tree species in subalpine forest gaps of Jiuzhaigou National Nature Reserve, Sichuan, southwestern China in a changing environment. Forest Ecol. Manage. 356, 84–92. Budyko, M.I., 1958. The Heat Balance of the Earth’s Surface, Translated from Russian by N. A Stepanova. US Department of Commerce, Washington, D.C. Calder, I.R., 1998. Water-Resource and Land-Use Issues. International Water Management Institute. Cheng, C., Mou, R.F., 2007. Calculation analysis of Jiuzhaigou forest ecosystem headwaters conservation. J. Henan Univ. Sci. Technol.: Nat. Sci. 28 (3), 69–72. Cheng, G.W., Yu, X.X., Zhao, Y.T., Zhou, Y.M., Luo, J., 2003. Evapotranspiration simulation of subalpine forest area in Gongga Mountainr. J. Beijing For. Univ. 25 (1), 23–27. Dai, X.A., Yang, W.N., Tang, C., 2010. Analysis of landscape spatial pattern changes using remote sensing in Jiuzhaigou valley, northwestern sichuan province, China. Multimedia Technology (ICMT), 2010 International Conference on 1–4. Di, B.F., Zhang, K.S., Luo, H., 2011. Analysis on the dynamic changes of wetland monitoring based on remote sensing in jiuzhaigou. Proceedings of Environmental Scientific Society of Sichuan Province 2011 Meeting 138–145.

216

Agricultural and Forest Meteorology 246 (2017) 207–217

C. Yan et al.

775–782. Wu, N., Bao, W.K., Wu, Y., et al., 2012b. The Ecological Environment and Sustainable Development of the World Natural Heritage Sites-Jiuzhaigou and Huanglong. Science Press Beijing, China. Yang, Y., Liu, Y., Fang, R., 1998. Numerical classification of the forest vegetation in the Jiuzhaigou nature reserve. Chin. J. Ecol. 17 (3), 7–10. Yang, D., Shao, W., Yeh, J.F., et al., 2009. Impact of vegetation coverage on regional water balance in the nonhumid regions of China. Water Resour. Res. 45 (7), 450–455. Yang, K., Ye, B., Zhou, D., et al., 2011. Response of hydrological cycle to recent climate changes in the Tibetan Plateau. Clim. Change 109 (3), 517–534. Yao, J., Zhao, L., Gu, L., Qiao, Y., Jiao, K., 2011. The surface energy budget in the permafrost region of the Tibetan Plateau. Atmos. Res. 102 (4), 394–407. Yin, Z.F., Hua, O., Xu, X.L., et al., 2010. Estimation of evapotranspiration from faber fir forest ecosystem in the Eastern Tibetan Plateau of China using SHAW model. J. Water Resour. Prot. 2 (2), 143–153. Yu, J.J., Zhang, Y.Q., Liu, C.M., 2009. Validity of the Bouchet's complementary relationship at 102 observatories across China. Sci. China 52 (5), 708–713. Zhang, L., Dawes, W.R., Walker, G.R., 2001. Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour. Res. 37 (3), 701–708. Zhang, Y., Yunling, H.E., Zhong, S., Liu, Y., Dou, J., 2005. A study on ecoclimatic effects of montane forest in the upper reaches of minjiang river. J. Mt. Res. 23 (3), 300–307. Zhang, L., Jiang, H., Wei, X., et al., 2008. Evapotranspiration in the meso-scale forested watersheds in Minjiang valley, West China 1. J. Am. Water Resour. As. 44 (44), 1154–1163. Zhang, S.Y., Li, X.Y., Ma, Y.J., et al., 2014. Interannual and seasonal variability in evapotranspiration and energy partitioning over the alpine riparian shrub Myricaria squamosa Desv. on Qinghai-Tibet Plateau. Cold Reg. Sci. Technol. 102 (6), 8–20. Zhang, S., Yang, H., Yang, D., Jayawardena, A.W., 2015. Quantifying the effect of vegetation change on the regional water balance within the Budyko Framework. Geophys. Res. Lett. 43 (12), 1019. Zhu, G., Lu, L., Su, Y., et al., 2014. Energy flux partitioning and evapotranspiration in a sub-alpine spruce forest ecosystem. Hydrol. Processes 28 (19), 5093–5104. de Bruin, H.A.R., 1983. A model for the Priestley-Taylor parameter. J. Appl. Meteorol. 22 (4), 572–578.

Song, G., Tang, Y., Cui, X., et al., 2005. Energy exchange between the atmosphere and a meadow ecosystem on the Qinghai–Tibetan Plateau. Agric. For. Meteorol. 129 (3–4), 175–185. Stoy, P.C., Katul, G.G., Siqueira, M.B.S., et al., 2006. Separating the effects of climate and vegetation on evapotranspiration along a successional chronosequence in the southeastern US. Global Change Biol. 12 (11), 2115–2135. Sun, X., Onda, Y., Kato, H., Otsuki, K., Gomi, T., 2014. Partitioning of the total evapotranspiration in a Japanese cypress plantation during the growing season. Ecohydrology 7 (3), 1042–1053. Tanaka, K., Ishikawa, H., Hayashi, T., Tamagawa, L., Ma, Y., 2001. Surface energy budget at Amdo on the Tibetan Plateau using GAME/Tibet IOP98 data. Chem. Biol. Chem. A Eur. J. Chem. Biol. 17 (2), 181–189. Vourlitis, G.L., Filho, N.P., Hayashi, M.M.S., et al., 2002. Seasonal variations in the evapotranspiration of a transitional tropical forest of Mato Grosso, Brazil. Water Resour. Res. 38 (6) (30-1-30-11). Wever, L.A., Flanagan, L.B., Carlson, P.J., 2002. Seasonal and interannual variation in evapotranspiration, energy balance and surface conductance in a northern temperate grassland. Agric. For. Meteorol. 112 (1), 31–49. Wilson, K.B., Baldocchi, D.D., 2000. Seasonal and interannual variability of energy fluxes over a broadleaved temperate deciduous forest in North America. Agric. For. Meteorol. 100 (1), 1–18. Wilson, K.B., Hanson, P.J., Baldocchi, D.D., 2000. Factors controlling evaporation and energy partitioning beneath a deciduous forest over an annual cycle. Agric. For. Meteorol. 102 (2), 83–103. Wilson, K.B., Hanson, P.J., Mulholland, P.J., Baldocchi, D.D., Wullschleger, S.D., 2001. A comparison of methods for determining forest evapotranspiration and its components: sap-flow, soil water budget, eddy covariance and catchment water balance. Agric. For. Meteorol. 106 (2), 153–168. Wilson, K., Goldstein, A., Falge, E., et al., 2002. Energy balance closure at FLUXNET sites. Agric. For. Meteorol. 113 (1–4), 223–243. Wu, J., Guan, D., Han, S., et al., 2007. Energy budget above a temperate mixed forest in northeastern China. Hydrol. Processes 21 (18), 2425–2434. Wu, J., Jing, Y., Guan, D., et al., 2012a. Controls of evapotranspiration during the short dry season in a temperate mixed forest in Northeast China. Ecohydrology 6 (5),

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