Influence of wetland reclamation on land-surface energy exchange and evapotranspiration in the Sanjiang plain, Northeast China

Agricultural and Forest Meteorology 296 (2021) 108214

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Influence of wetland reclamation on land-surface energy exchange and evapotranspiration in the Sanjiang plain, Northeast China Yuedong Guo a, Changchun Song a, *, Jiashuang Zhang a, Lili Wang b, Li Sun a, * a b

Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130012, China Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China

A R T I C L E I N F O

A B S T R A C T

Keywords: Wetland reclamation Energy partitioning Evapotranspiration Surface conductance

Sustained, large-scale wetland reclamation of paddy fields has been implemented since the 1960s in the Sanjiang Plain, northeast China. The investigation of the effect of this reclamation on land-surface energy exchange and the local water cycle is important for evaluating the stability of regional water resources for future agriculture development and ecological conservation. This study used the eddy covariance method to measure evapo­ transpiration (ET) and dominant energy transport fluxes for two sites, a typical natural marsh and a paddy field, during the growing seasons of 2017–2018. The two sites showed similar total available energy, whereas the ratio of the latent to net radiative energy (LE/Rn) was substantially lower in the marsh (0.49) compared to the paddy field (0.81), indicating a considerable increase in ET energy consumption after wetland reclamation. The average ET rates of the marsh and paddy field were 2.3 mm d− 1 and 3.6 mm d− 1, respectively, throughout the growing season. Both the high Priestley-Taylor coefficient (αeq, 1.21 ± 0.20) and the decoupling factor (Ω) suggested Rnlimited conditions in the paddy field, whereas the controlling factor in the marsh changed from vapor pressure deficit (VPD) to radiation energy over the season. The greatest difference in ET occurred in spring due to the alteration in the hydrological environment, including a lowered standing water table and elevated water tem­ perature in the paddy site. The differences in physiology and canopy shape between the paddy and marsh plants contributed largely to enhanced ET during the summer months. In total, alterations in the hydrological envi­ ronment, canopy structure and plant physiology contributed to the increase in ET, suggesting a synthetic in­ fluence of marsh reclamation on surface energy and ET processes. Wetland reclamation increased water consumption through ET and altered the seasonal pattern of the energy balance. This process will inevitably result in increased deficits in regional water resources in the Sanjiang Plain.

1. Introduction

Wetland reclamation affects ET by altering natural vegetation cover, modifying soil texture and changing the microclimate and water avail­ ability, which in turn changes the relationship between sensible and latent heat (H and LE) (Hatala, et al., 2012; Muro et al., 2018). There has been an increasing focus on the evaluation of the effect of wetland reclamation on evapotranspiration (ET) and the surface energy balance, particularly for the conversion of wetlands to paddy field in important plant regions (Zhao et al., 2008; Eichelmann et al., 2018). However, large uncertainties in identifying the main drivers and the key processes under different climates and environmental conditions remain (Suzuki et al., 2014; Liu and Hu, 2019). ET has been reported to decrease or increase following the conversion of wetlands to paddy fields, depend­ ing on the canopy characteristics, boundary layer conditions and hy­ drology management (Zhao et al., 2008; Baldocchi et al., 2016;

The wetlands located in the northern temperate regions provide a wide range of importance ecosystem services, including water and plant resource, habitats for migratory birds and biodiversity protection (Tiner et al., 2015; Wells et al., 2017). However, there has been extensive conversion of wetlands to farmland, a form of wetland reclamation, over the last half century to meet the demands of population growth and the agricultural economy in both developed and developing countries (Awala et al., 2009; Suzuki et al., 2014; Yu et al., 2018). This reclama­ tion has resulted in considerable alterations to land cover, which in turn has changed the land-surface energy balance and water cycle, resulting in a reduction of the soil carbon pool and increased greenhouse gas emissions (Song et al., 2011; Olikawa et al., 2016).

* Corresponding author. E-mail addresses: [email protected] (C. Song), [email protected] (L. Sun). https://doi.org/10.1016/j.agrformet.2020.108214 Received 17 February 2020; Received in revised form 9 August 2020; Accepted 7 October 2020 Available online 1 November 2020 0168-1923/© 2020 Elsevier B.V. All rights reserved.

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Eichelmann et al., 2018). The plant canopy is the most important factor influencing ET and radiative energy partitioning (Panferov et al., 2001; Li et al., 2018), and the considerable contribution of transpiration of natural vascular plants to ET of a wetland has been well documented (Mohamed et al., 2012). The conversion of wetland to paddy field would inevitably transform the canopy morphology and stomatal conductance of leaves, and therefore also transpiration potential of the canopy (Zhao et al., 2008; Hirano et al., 2016). Transpiration is generally positively related to surface conductance at the canopy scale, resulting in a strong relationship be­ tween ET and the leaf area index (LAI) or the Normalized Difference Vegetation Index (NDVI) (Gu et al., 2007; Liu et al., 2019a). Paddy fields characterized by larger LAI compared to wetlands generally exhibit higher ET and LE/Rn ratio (Rn, net radiation) (Hatala et al., 2012). The alteration of plant cover can result in changes in surface wind speed, aerodynamic roughness and even the boundary layer condition at a regional scale, thereby resulting in changes in turbulent motion and vapor transportation into the atmosphere (Brümmer et al., 2012; Bal­ docchi et al., 2016). In addition, the management of hydrology within paddy fields is largely different from that within natural wetlands, resulting in changes in water availability for both canopy transpiration and surface water evaporation (Diaz et al., 2019). However, the com­ bined influence of biophysical, physiological and environmental alter­ ations resulting from wetland reclamation on land-surface energy exchange and evapotranspiration remains unresolved. In theory, the balance between water availability and received en­ ergy is the key process controlling ET in both natural and managed ecosystems, which in boreal regions manifests as limitations to both water and energy over different seasons (Brümmer et al., 2012; Runkle et al., 2014; Xu et al., 2020). The classical Penman-Monteith (PM) and Preistley-Taylor (PT) equations, which both consider energy and aero­ dynamics, are important tools for quantifying the balance between water availability and received energy (Monteith, 1965; Priestley and Taylor, 1972). The variables considered in the equations are based on the “big leaf” assumption and include aerodynamic and canopy conductance and the decoupling coefficient, which are useful for the evaluation of the contribution of the energy environment and climate. In essence, these equations reflect the alteration to energy transport and partition within ecosystems in response to changes in ET. Investigations of latent heat according to the theoretical framework of surface-energy cycling would supply more comparable and meaningful information (Saptomo et al., 2009). However, the exact effects on ET remain unan­ swered since previous studies have focused on different ecosystems, climate and soil conditions. Therefore, it is valuable of further research on ET responses to wetland reclamation. While studies on wetland reclamation have been conducted globally, relatively little attention has been focused on the Sanjiang Plain. The plain is the largest wetland reclamation region in China, and also the region that had the highest concentration of wetlands in the 1960s. The region has experienced reclamation of ~75% of its wetlands (~1.95×104 km2) for paddy field over the past half century (Liu et al., 2019b). This extensive reclamation process has resulted in the Sanjiang Plain becoming the largest area of paddy field and the most important commodity grain base in China. Unfortunately, the large-scale recla­ mation has resulted in considerable water resource deficits, in particular a decrease in ground water level by 0.2 m yr− 1–0.3 m yr− 1, and an irrigation deficit of 8 × 109 m3 (Wei et al., 2016). In addition, there has been a continuous increase in regional air temperature with a rate of 0.3 C◦ 10a− 1 during 1970-2015. If this warming trend continues, there will be further increases in the land ecosystem water requirements in the future (Zhang et al., 2019). Sustainable development of the region will require further research on approaches to balance water allocation be­ tween agricultural production and ecological conservation (Wang et al., 2018). Unfortunately, the effects of converting wetland to paddy fields have received relatively little attention. Consequently, the degree to which wetland reclamation can alter the land-surface energy balance

and water consumption remains unclear. The present study aimed to fill some of these knowledge gaps by conducting compared observations of a natural wetland site and a paddy field site within the Sanjiang Plain over two growing seasons in 2017–2018. The objectives of the present study were to determine the seasonal and annual differences in energy partitioning and ET between the two sites and to identify the environ­ mental and biological drivers responsible for controlling ET dynamics. 2. Materials and methods 2.1. Description of the study sites The Sanjiang Plain of the northeast China extends between 45.01◦ –48.32◦ N latitude and 130.21◦ –135.01◦ E longitude. The plain has a low slope grade (1:5,000–1:10,000) due to long-term alluviation by the Heilong, Wusuli, and Songhua rivers. Freshwater sedge marsh has been extensively distributed over the plain since the late Pleistocene. Two observation sites were selected in the center of the plain, with one being a natural marsh and the other a paddy field. This region experi­ ences a temperate continental monsoon climate, characterized by an annual average temperature of 1.9 ℃ and an annual average frost-free period of 125 d. On average, the warmest and coldest months between 1981 and 2015 were July (22 ℃) and January (− 21 ℃), respectively. The land-surface (including marsh) tends to be completely frozen from late October to the following April. The growing season extends from late April to late September and from middle May to early October for marshland and paddy, respectively. Precipitation is concentrated over July–August, accounting for > 60% of total annual precipitation (550–600 mm). The marsh site (47.52◦ N, 133.50◦ E) is situated in the Honghe Wetland Native Reserve, which includes ~218 km2 of natural marsh. An eddy-covariance tower was established in the center of a semi-enclosed depression with a seasonal hydrological connection to the main river in the reserve. The surface of the marsh tends to freeze throughout the winter until late April, and remains inundated during the following growing season with the water table level fluctuating between 20 and 80 cm. The dominant marsh plant in this area is Carex lasiocarpa accom­ panied by the subsidiary species Deyeuxia angustifolia. The paddy field site (47.51◦ N, 133.51◦ E) is situated within the experimental field of the Sanjiang Wetland Experimental Station of the Chinese Academy of Sci­ ence. The experimental field extends over an area of 6.5 hm2 and was reclaimed from marsh 15 years ago. The experimental field forms part of continuous paddy planting area extending for hundreds of miles. Pre­ cipitation constitutes the main water source for the marsh during the growing season, whereas the paddy field receives precipitation as well as groundwater for irrigation. Irrigation of the paddy field continues through most of the growing seasons until late September, shortly before crop maturity. The maximum standing water level in the paddy field is manually controlled and maintained to be within 15 cm during the irrigation period. 2.2. Eddy covariance measurements 2.2.1. Instrument setup An eddy covariance (EC) system with a fast response open-path CO2/ H2O infrared gas analyzer (Li-7500, LiCor Inc., USA) and a tri-axial ul­ trasonic anemometer (CSAT3, Campbell Scientific, USA) was estab­ lished in each site. Latent heat flux (LE), sensible heat flux (H) and the three-dimensional wind speed were measured at a height of 2 m above the canopy at both sites. The anemometers were oriented toward the prevailing wind directions and the distance between the mid-points of the anemometer and the gas analyzer was set to 15 cm. All signals for the sensors were sampled at 10 Hz and 30-min average covariances were calculated and recorded with a datalogger (CR5000, Campbell Scienti­ fic, USA). As H2O fluctuations were measured in situ, flux estimates obtained from the eddy covariance system were corrected for 2

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simultaneous fluctuations in both LE and H flux. The observation periods for both sites over 2017 and 2018 were 183 days (2017/4/22 – 2017/ 10/21) and 175 days (2018/4/22-2018/10/13), respectively.

seasons. To identify the difference in the transpiration potential in the leaf level between the paddy and the natural marsh plants (C. lasiocarpa and D. angustifolia), we measured the stomatal conductance and transpira­ tion rate using a portable photosynthesis analyser having a LED red-blue light leaf chamber (Li-6400, LiCor Inc, USA). The field observations were carried out during 4 sunny days (22 June, 19 July, 8 August, and 3 September 2017), between 9:00 – 12:00 AM. When measuring, healthy leaves in the upper canopy of each plant were selected, with five repeats being set in each site, and the photosynthetically active radiation (PAR) in the leaf chamber were set as 1200 μmol m-2 s-1.

2.2.2. Data processing and gap filling The half-hourly H2O and CO2 flux data for the two sites were calculated using with the software EddyPro 6.2.1 (Version 6.2.1, www. licor.com/eddypro) and quality control flags of 2 according to Foken et al. (2004) were removed from the data series. Advanced settings implemented in EddyPro included double rotation of the coordinate, time lag detection, block average detrending, Webb-Pearman-Leuning correction and spectral corrections. Data falling outside the physical or biological ranges and data measured during rainfall events, water vapor condensation, instrument maintenance and power failures were regarded as anomalous. Datum values characterized by abnormal "automatic gain control" (AGC) < 90% and friction velocity (u*) < 0.1 m s− 1 were then rejected. In total, ~31% of data obtained from the EC systems at the two sites over the two years was discarded, consistent with average data gaps reported for other EC sites (Gong et al., 2017; Liu et al., 2019a).To calculate daily and annual sums of the H2O fluxes, data gaps were filled according to the following methods: (1) linear interpolation was used to fill the daytime (total radiation ≥ 100W m-2) gaps less than five continuous half-hours between the nearest normal data points; (2) Short (< 5 hours) daytime gaps were filled by daily linear regression relationship between half-hourly LE and net radiation (Rn). (3) For daytime gaps longer than 5 continuous hours, the linear relationships between Rn and the fluxes using the data five days prior to and following the gap were used. (4) Nighttime gaps were filled with the average value derived from compiling the 30 min ensemble average trend of five days prior to and following the gap. In the analysis below, daily fluxes were used only when the daily data include more than 36 half hours. For other analyses in monthly and annually period, a com­ plete data set after gap-filling was used. Missing CO2 flux data were gap-filled according to the methods of Song et al. (2011). The net ecosystem exchange (NEE) was calculated from the final CO2 flux data, which was subsequently divided into two categories, namely gross primary productivity (GPP) and ecosystem respiration (Reco), where NEE = GPP − Reco. A regression between nighttime NEE and soil temperature was used to quantify the relationship between Reco and soil temperature, thereby allowing daily rates of Reco to be evaluated. Finally, GPP was estimated to be the difference between NEE and Reco.

2.4. Main calculations 2.4.1. Energy balance The surface energy balance can be expressed by the formula below, which includes net radiation (Rn), latent heat flux (LE), sensible heat flux (H), change in heat storage in the surface water column (ΔW) and ground heat flux (G): Rn = LE + H + ΔW + G

(1)

The sign of Rn is positive in the downward direction, whereas those of H and LE are positive in the upward direction over the entire moni­ toring period. The sign of G switches depending on seasons: positive sign occurs during most of the growing season indicating a downward heat transfer from surface water to soil, while this tendency may reverse during late autumn indicating an opposite transfer direction. ET = LE/ λρw, where λ is the latent heat of vaporization (J kg− 1) and ρw is the density of water (1.0 × 103 kg m− 3). 2.4.2. Change in energy storage of surface water Since the ice cover had almost completely thawed before the initia­ tion of field observations, the present study simply focused on surface water energy storage. The change in heat storage of surface water was evaluated as follows: ΔW = ΔTw dw ρw Cw /Δt

(2) − 2

In Eq. (2), ΔW is the change in heat storage of surface water (W m ), dw is the standing water level (m), ρw is water density (1.0 × 103 kg m− 3), Cw is the heat capacity of water (4,184 J kg− 1 ℃− 1), ΔT is the change in average temperature during the selected time interval (℃) and t is the time interval (s). The average water temperatures at the beginning and end of each time interval were recorded automatically using temperature probes (UTBT001, Onset Computer Corporation, USA). The temperature probes were fixed both at the water surface beneath a float plank (10 cm × 10 cm) and at the bottom of the water column, with three replicates set randomly in both sites. Average water temperature was calculated as the average value registered by the two probes at the surface and bottom The time interval for water tempera­ ture measurement was set to 2 h to capture variations within the mea­ surement precision of the probes (± 0.1 ℃). In fact, the selection of a shorter time interval (e.g. 30 min) as adopted by Wu and Shukla (2014) would have introduced further errors associated with a higher number of computations. The data for ΔW presented in Fig. 2 represent diurnal values to facilitate a comparison with other results.

2.3. Meteorological and ancillary measurements A meteorological tower was established in each site for the collection of data on air temperature and relative humidity (083D, Campbell Sci­ entific Ltd., UK), air pressure (CS106, Vaisala, Finland) and fourcomponent radiation (CNR01, Kipp and Zonen, Netherlands) at a 2 m height above the canopy. CS-107 temperature probes (Campbell Scien­ tific Ltd., UK) were used to measure soil temperature at a depth of 0 – 100 cm at intervals of 10 cm; Soil heat flux (G) was measured using heat flux plates (HFP01, Hukseflux, NL) at a depth of 5 cm below the soil surface and 2 m away from the meteorological towers. Water level loggers were used to automatically record standing water at the two sites every 30 min (U20, Onset Computer Corporation, USA). Leaf area index (LAI) values of the marsh and the paddy canopies were measured using a LAI meter (LAI-2000, LiCor Inc, USA) with five rep­ licates within a radius of 200 m around the flux tower every 5 –10 d. Thaw depth of the soil layer was manually surveyed with a 1.0 m stainless steel ruler (accuracy = 0.1 cm) with seven replicates at the same sites. Irrigation water for the paddy field was pumped from ~40 m below ground with the volume measured using an electromagnetic flow meter (YK-LDG, Yoke Corporation, China) fixed on the outlet of the well, whereas precipitation was manually measured using a rain gauge (SCYL05, Istrong Corporation, China). All the measurements were executed parallelly to the flux observation during the two growing

2.4.3. Aerodynamic and canopy conductance The canopy conductance theory is based on the assumption that all the energy for water evaporation accepted by the canopy is consumed through two kinds of conductance processes: (1) the canopy conduc­ tance (gc) process, when the water diffuses through the leaves, (2) the aerodynamic conductance (ga) process, when the water diffuses into the atmosphere (Shuttleworth, 1992). The value of ga can be calculated through quality-controlled estimates of friction velocity (u*) which can be measured with a sonic anemometer (Monteith and Unsworth, 1990): 3

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ga =

(w

s

u∗2

+ 6.2u−

Agricultural and Forest Meteorology 296 (2021) 108214 2/3

)−

1

3. Results

(3)

3.1. Meteorological conditions and plant growth

Where u* is friction velocity estimated by the EC system (m s− 1), and ws is wind speed at a height of 2 m (m s− 1). Therefore, gc, can be esti­ mated by applying the inverted Penman-Monteith equation based on the measured LE and the estimated ga: gc =

γLEga sA + cp ρa VPDga − LE(s + γ)

Meteorological data typical of the geographic location of the study area, i.e., the northern boundary of the northern temperature zone, were observed over the study period. A co-occurrence of peak temperature and heavy rain during summer was noted (Fig. 1a–b). Average tem­ peratures and precipitation over the growing seasons in 2017 and 2018 were 14.1℃ and 539.2 mm and 14.4 ℃ and 462 mm, respectively, consistent with historical averages of the study area. The average surface water temperature of the paddy site was 6.4 ℃ higher compared to that of the marsh site throughout spring and summer from late April to late August (Fig. 1c). The marsh site exhibited a significantly higher average water level (41 ± 5 cm VS 7 ± 1 cm; n = 351; P<0.05) and a greater maximum depth of frozen soil (114 ± 3 cm VS 92 ± 4 cm; n = 5; P < 0.05) compared to the paddy field site during the growing season (Fig. 1d–e). The water volume and frequency of irrigation were manually adjusted to facilitate full utilization of precipitation water, and the water table in the paddy site demonstrated higher stability compared to the marshland site. Thawing of the frozen soil layer in the paddy field was usually complete by mid-June, one-month earlier than that in the marsh site. The seasonal variation in the LAI curves of the two sites were different, with the LAI of the marsh reaching a peak (2.92 ± 0.06) at the beginning of August, 15 days earlier than that in the paddy site where the peak was of 5.07 ± 0.08 (Fig. 1f). Both sites presented similar variation in VPD, with the peak occurring during the spring months (Fig. 1g).

(4)

Where A is the energy for turbulent motion calculated as the sum of H and LE. Traditionally, A has been calculated as Rn – G – ΔW. However, the present study rejected this approach because of the potential mismatch between the footprints of G and ΔW combined with the dif­ ficulty in obtaining a good spatial estimate. VPD represents the vapor pressure deficit (kPa), s is the slope of the saturation vapor pressure against temperature (kPa ℃− 1), γ is the psychrometric constant (kPa − 1 ), cp is air heat capacity (J kg− 1 ℃− 1) and ρa is the density of dry air (kg m− 3). While the two conductance terms were calculated based on the half-hourly dataset, they were presented as diurnal average values. Notably, data measured during rainy days were not included in the figures to limit excessively variations and to facilitate a comparison between the marsh and paddy sites. The decoupling coefficient (Ω) was introduced to characterize the degree of the interaction between the evaporating surface and the at­ mosphere outside the leaf boundary layer. An Ω value close to 0 in­ dicates a perfect coupling condition between the vegetation canopy and the atmosphere, which provides all the energy required for ET, whereas an Ω value equal to 1 indicates a completely decoupled system in which radiation is the only contributor to the ET process. Ω=

s+γ sγ(1 + ga /gc)

3.2. Energy exchange in the two ecosystems

(5)

The marsh and paddy field sites showed obvious differences in sea­ sonal variation of the five measured energy components. While the two sites showed roughly similar seasonal patterns in Rn, clear differences between the sites were observed during the spring and autumn months of 2017 and 2018 (Fig. 2a, Table 1). LE and H were the factors contributing the most to Rn, collectively represented 75% and 89% of Rn in the marsh and in the paddy sites, respectively. The ratio of H to LE in the marsh site was much more balanced compared to that for the paddy site, with ratio values of ~1:2 and ~1:12, respectively. The LE obtained for the paddy field was much higher than that for the marsh, indicating a considerable increase in the energy consumption by ET subsequent to marsh being reclaimed for paddy field (Fig. 2b, Table 1). Noticeably, the largest difference in LE between the two sites occurred in May during the initial growing season of the paddy field (Table 1). LE peaks in the marsh site were generally registered during mid-summer coinciding with the peak in LAI, whereas those of the paddy site extended over a relatively longer period of May–July. In addition, peaks in H were registered in the marsh site mainly during spring, whereas the paddy site did not show any clear seasonal trend in H. The values of H were occasionally nega­ tive, indicating a gain in sensible heat. Changes in surface water energy storage (ΔW) contributed to a limited extent to available energy. ΔW oscillated between − 40 m− 2 and 40 W m− 2 in the marsh site with no detectable seasonal trend or peri­ odicity or any consistency with the water table (Fig. 2d). This result was predominantly due to fluctuations in surface water temperature, with the maximum difference in daily average temperatures of the marsh reaching 2.2 ℃. The fluctuation period of ΔW for the paddy site was identical to that of the marsh site, although that of the paddy site showed a much lower magnitude due to a sustained low standing water level during the growing seasons. There was a gradual decline in ground heat flux (G) during the growing season at both sites (Fig. 2e). Downward heat fluxes to the deep soil, indicated by positive sign, were evident during the spring and summer months, whereas upward heat fluxes with negative sign mostly occurred during autumn (Table 1). Although much larger fluctuations in ΔW were evident, G was significantly related to

2.4.4. Priestley-Taylor coefficient The Priestley-Taylor coefficient (αeq) is defined as the ratio of ET to equilibrium evaporation (ETeq). ETeq represents the vapor flux released from an extremely moist surface when actual vapor pressure of the at­ mosphere approaches the saturation vapor pressure. ETeq =

sA s+ γ

(6)

αeq =

ET ETeq

(7)

ETeq was derived from the Penman-Monteith equation under condi­ tions of no advective influence since the u, VPD and conductance terms are missing in Eq. (6). In Eq. (7), αeq is a dimensionless parameter ranging between 0.34 – 1.74 under different conditions (Shuttleworth, 1992; Gavin and Agnew, 2004), and is taken to be equal to 1.26 over ocean and saturated land surfaces (Priestley-Taylor, 1972). 2.5. Statistical analyses The average and the standard deviation of ET, energy components and environmental factors for the two sites were analyzed using the Statistical Program for Social Sciences (SPSS) version 16.0 software. One-way analyses of variance (ANOVA) were performed to determine the differences between gauged and calculated data between the two sites at a significance level P of 0.05. Two-tailed Pearson correlation and regression analyses were also conducted to test the relationship between ET and environmental parameters, and between calculated coefficients, as well as between energy components.

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Fig. 1. Changes in meteorological factors, water level, thaw depth and LAI during the growing seasons of 2017 and 2018. “Water T” indicates the temperature in water surface; “Air T” is the air temperature at a height of 2m.

ΔW over the two years (paddy: n =277, P<0.01; marsh: n = 349, P<0.01). The calculated energy balance closure demonstrated a good reli­ ability of the EC systems, particularly in the case of the paddy field

(Table 1). The two sites showed similar monthly averaged shortwave albedo, exceeding 60% before late August and subsequently declining to 31%–48%. The Bowen ratio which was calculated considering both night and day values generally showed a decline over the seasons in the 5

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Fig. 2. Comparison between the available radiative energy and each of its components at the two sites. Table 1 Average monthly cumulative surface energy balance (MJ m− 2) for each term. Month April May June July August September October Total

Marsh Rn

H

LE

ΔW

G

c

Paddy Rn

H

LE

ΔW

G

c

49 ± 15 436 ± 39 378 ± 18 432 ± 60 360 ± 33 265 ± 2 84 ± 1 2006 ± 49

16 ± 7 127 ± 25 121 ± 30 103 ± 20 57 ± 23 62 ± 45 22 ± 28 507 ± 179

14 ± 1 147 ± 14 180 ± 41 252 ± 16 193 ± 49 153 ± 47 52 ± 10 990 ± 129

1±1 6±2 14 ± 4 14 ± 2 1±2 − 17 ± 1 − 11 ± 4 7±7

1±1 14 ± 2 11 ± 0 10 ± 0 4±2 − 1±1 − 3±2 37 ± 6

0.65 0.67 0.86 0.88 0.71 0.74 0.71 0.77

102 ± 20 431 ± 21 381 ± 4 409 ± 54 337 ± 3 219 ± 3 65 ± 1 1945 ± 16

11 ± 3 27 ± 11 32 ± 6 20 ± 11 15 ± 8 14 ± 12 9 ± 14 128 ± 25

77 ± 20 351 ± 17 293 ± 4 327 ± 60 283 ± 39 187 ± 26 55 ± 20 1573 ± 146

1±1 2±1 1±1 − 2±1 0±1 2±1

6±1 16 ± 2 10 ± 2 10 ± 0 4±0 − 2±1 − 5±3 39 ± 3

0.92 0.92 0.88 0.88 0.89 0.91 0.91 0.90

Note: c indicates the energy balance closure [= (H+LE+ΔW+G) / Rn].

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marsh reaching a maximum daily value of 2.1 on 28 April, 2017. In contrast, much lower values and no clear seasonal trend in the Bowen ratio was observed for the paddy site. The data collected during midday periods, during which data for rainy days were excluded, showed similar trends, highlighting the impact of marsh reclamation on energy parti­ tioning (Table 2).

represented a non-equilibrium process for the majority of time in the marsh site. The average αeq of the paddy site was 1.21 ± 0.26 with a relatively stable trend, with a slight decline evident across the seasons and characterized by large fluctuations in autumn.

3.3. ET in the two ecosystems

4.1. Effects of wetland reclamation on the surface energy balance

Peak ET rates generally occurred during mid-summer and spring for the marsh site and paddy field site, respectively (Fig. 2b). The average ET rate of the marshland site was 2.3 mm d− 1 over the two growing seasons (maximum value = 4.6 mm d− 1), whereas that of the paddy field site was 3.6 mm d− 1(maximum value = 6.6 mm d− 1). The total differ­ ence in ET between the two sites was 233.9 mm on average, with the largest differences during spring. Total ET consumed 84% of precipita­ tion during the growing seasons for the marsh site, whereas ET consumed only 56% of the total water supply (rainfall + irrigation) available to the paddy field. Notably, ET exceeded precipitation in the marsh site during spring and autumn, with no substantial concurrent drawdown in the water table level (Table 3, Fig. 1d), indicating an additional net inflow of water from surrounding landforms. Both Rn and VPD played an important role in controlling ET at the two sites, with both variables showing significant relationships with ET during both 2017 and 2018 (Fig. 3) The aggregation of the data points clearly suggested a stronger control of Rn on ET in the paddy site compared to in the marsh site. Both sites presented a phased response to VPD (when it was < 0.7 kPa; Fig. 3), which is consistent with a study by Zhao et al. (2008) who identified a similar threshold (0.8 kPa) when studying a soybean field located in the same study area. Excessively high VPD usually triggers a self-protection mechanism in plants, which in this case would shut down leaf stomata, resulting in a clear decline in ET (Ronzhina et al., 2019).

The land-surface energy balance depends substantially on land use/ cover, which has seen considerable changed at regional and global scales during the last century, mostly due to the conversion of natural eco­ systems to agricultural land (Riebsame et al., 1994; Van Asselen and Verburg, 2013). Reclamation of natural land results in changes in both energy balance components and the relationship between the energy and water balance in a landscape (Persson 1997; Czarnecka et al., 2009). Therefore, the process of reclamation should consider meteorological conditions such as radiation, wind and humidity, as well as several environmental factors such as plant characteristics and hydrological conditions. The present study found the dominant changes resulting from marshland reclamation to paddy field to be the partitioning of radiation energy between H and LE. Reclamation resulted in an increase in LE/Rn from 0.49 for the marsh site to 0.81 for the paddy field site, indicating considerable increases in energy expended as LE. In partic­ ular, the average LE/Rn value of 0.81 indicated ET in the paddy ecosystem to be an intensive energy expense, and LE/Rn values > 0.8 have seldom been reported in previous studies since most previous studies were verified in warm regions characterized by high water availability from precipitation or floods (Alberto et al., 2011; Diaz et al., 2019). In addition, manually irrigated paddy fields in temperate regions generally show values of LE/Rn of 0.58–0.75, implying that water availability is an important factor controlling LE/Rn at the continental scale (Hossen et al., 2012; Timm, 2014; Liu et al., 2019a). Notably, the total Rn registered in study area of ~2,000 MJ m− 2 during the growing season was much lower than those registered in other rice planting re­ gions at lower latitudes. The allocating of more energy to the ET process might make it possible to gain sufficient power for mass accumulation in the paddy plants over a short growing season. Marsh plants generally adopt a living strategy to balance mass accumulation and reproduction as an adaptation to a varied water condition (Luo et al., 2010; Shi et al., 2015). The high LE/Rn value observed in the present study can therefore be explained as a product of the combination of climate, water avail­ ability and plant physiology. Substantial changes in heat storage and flux in the surface water/soil layers were observed following reclamation (Fig. 2). While both the marsh and paddy site presented the same ΔW oscillation pattern, the paddy site showed much lower values of ΔW, suggesting that reclama­ tion largely weakened the role of surface water as an energy storage vessel, although there was no alteration in the seasonal trend of energy exchange between the land surface and the atmosphere. In fact, the total contribution of ΔW to Rn was limited over the growing season, with

4. Discussion

3.4. Surface conductance and other two parameters The average surface conductance (gc) at the marsh site (13.9 ± 10.1 mm s− 1) was slightly lower than that at the paddy field (17.8 ± 9.7 mm s− 1). The maximum and minimum values at both sites were generally > 30 mm s− 1 and ~5 mm s− 1 and occurred during summer and early spring/late autumn, respectively (Fig. 4). The two sites showed different seasonal patterns of decoupling coefficient (Ω). Ω of the marsh site showed a roughly symmetrical variation during the growing seasons, with a maximum value of 0.8 in July and August. In the paddy site, however, Ω exceeded 0.5 from the beginning of the growing season, following an unsymmetrical seasonal curve, with a maximum of 0.7 in late June, persisting until late August (Fig. 5). The two sites similarly showed different trends in αeq indices. The marsh site showed gradually increasing αeq from spring to late summer, but becoming unstable in autumn (Fig. 5), with an average αeq of 1.04 ± 0.20 and all values ranging between 0.61–1.49. These data suggest that vapor transport Table 2 Average monthly ratios of the key energy balance terms. Month

Marsh LE/Rn

H/Rn

H/LE

(ΔW+G)/Rn

Rn/SWin

Br,mid-day

Paddy LE/Rn

H/Rn

H/LE

(ΔW+G)/Rn

Rn/SWin

Br,mid-day

April May June July August September October Mean

0.28 0.34 0.48 0.58 0.54 0.58 0.61 0.49

0.33 0.29 0.32 0.24 0.16 0.23 0.26 0.26

1.15 0.87 0.67 0.41 0.29 0.41 0.42 0.60

0.02 0.05 0.06 0.06 0.01 - 0.06 - 0.16 0.02

0.58 0.60 0.66 0.68 0.69 0.61 0.42 0.61

1.23 ± 1.58 0.93 ± 0.57 0.75 ± 0.34 0.61 ± 0.31 0.57 ± 0.35 0.60 ± 0.21 0.68 ± 0.29 0.76 ± 0.52

0.76 0.81 0.77 0.80 0.84 0.85 0.84 0.81

0.10 0.06 0.08 0.05 0.04 0.07 0.14 0.08

0.14 0.08 0.11 0.06 0.05 0.08 0.16 0.10

0.06 0.04 0.03 0.03 0.01 - 0.01 - 0.01 0.06

0.57 0.62 0.67 0.63 0.62 0.48 0.31 0.57

0.34 ± 0.23 ± 0.25 ± 0.21 ± 0.27 ± 0.20 ± 0.28 ± 0.25 ±

0.18 0.07 0.14 0.09 0.09 0.07 0.12 0.12

Note: SWin indicates the receiving shortwave radiation, while Br,mid-day refers to the average half-hourly Bowen ratio (H/LE) for the mid-day period (10:00–14:00) on sunny days. 7

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Table 3 Average monthly surface water balance (in mm) obtained for the two sites based on the 2017 and 2018 data. Month

Marsh Rain

ET

ET/Rain

Paddy Rain

Ir

ET

ET/(Rain+Ir)

April 2017 May 2017 June 2017 July 2017 August 2017 September 2017 October 2017 Sum 2017 April 2018 May 2018 June 2018 July 2018 August 2018 September 2018 October 2018 Sum 2018

5 43.9 155.7 155.8 123.4 50.2 10.0 539.0 3.4 56.7 68.6 178.3 77.7 56.5 10.2 452.4

5.4 63.5 61.2 98.2 64.7 56.4 33.8 383.1 5.8 55.3 84.9 107.5 92.8 75.4 17.8 439.5

1.08 1.43 0.39 0.63 0.52 1.12 3.38 0.71 1.71 0.95 1.23 0.61 1.19 1.33 1.75 0.97

0 43.9 155.7 155.8 123.4 50.2 10.0 539.0 3.4 56.7 68.6 178.3 77.7 56.5 1.2 442.4

205 122 53 88 85 83 0 636 240 138 92 81 90 93 0 733

25.5 147.3 120.2 163.2 126.5 82.9 27.8 693.3 36.8 137.6 117.8 116.3 104.1 68.1 16.4 597.1

0.13 0.89 0.58 0.67 0.61 0.62 2.78 0.59 0.15 0.71 0.73 0.45 0.62 0.46 13.67 0.52

ΔET (Pa-Ma) 20.1 83.8 59.0 65 61.8 26.5 − 6 310.2 31.0 82.3 32.9 8.8 11.3 − 7.3 − 1.4 157.6

Note: Ir refers to irrigation inflow which occurs in the paddy field. ΔET(Pa-Ma) indicates the difference in ET between the paddy field and the marsh

Fig. 3. Relationships between evapotranspiration (ET), net radiative energy (Rn) and vapor pressure deficit (VPD) at the two sites in 2017 and 2018.

average ratios of only 6% and 4% for the marsh and paddy sites, respectively. However, the surface water layer plays an important role in heat fluxes to the soil layer. The significant relationships between ΔW and H evident for both sites suggested that the surface water layer acts as an efficient transferor of energy. The directions of ΔW and G indicated that energy was absorbed by the land-surface from the atmosphere

before early September, and thereafter released back into the atmo­ sphere. On average, the land surface of the marshland site and paddy site absorbed 15.13 W m− 2 d− 1 and 4.16 W m− 2 d− 1 of radiation energy, respectively, and released 12.44 W m− 2 d− 1 and 6.30 W m− 2 d− 1 of radiation energy, respectively. This result indicated a considerable change to the capacity of energy storage and transfer in the land surface 8

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Fig. 4. Seasonal dynamics of the surface conductance term (gc) at the two sites in 2017 and 2018. The solid lines represent the 5-day sliding mean.

Fig. 5. Seasonal dynamics of the decoupling coefficient (Ω) and Priestley-Taylor coefficient (αeq) at the two sites in 2017 and 2018. The lines represent the 5-day sliding mean.

after the conversion of marshland to paddy field.

Peichl et al., 2013; Runkle et al., 2014). The present study reported average αeq values of 1.04 and 1.21 for the marsh and the paddy field, respectively. Both sites clearly received abundant water during most of growing season as standing water was consistently detected before the paddy maturity period. Therefore, it is clear that the factor limiting ET cannot be water availability, and therefore water availability cannot be the main driver resulting in the difference in ET between the two sites. The two sites showed the largest differences in ET during the spring months (Fig. 2), with the paddy field site showing an ET value that was higher than that of the marsh site by 2.7 mm d− 1 on average in May. The values of αeq and Ω indicated that the main processes driving ET between the two sites were different to a certain degree. It was clear that the paddy field site showed higher values of αeq and Ω in May compared to the marsh, indicating a higher degree of decoupling to VPD and a stronger control by radiation in the paddy field. The effect of plants on the difference could be excluded as the LAI values were less than 0.2 during this period. Therefore, evaporation from the water surface was clearly the main process driving ET during this period. In theory, the

4.2. Effects of reclamation on ET 4.2.1. Seasonal differences in ET and main drivers The results of the present study showed that reclamation of marsh­ land to paddy field resulted in a significant increase in ET. This result is both supported and contradicted by results of previous studies under different climates (Suzuki et al., 2014; Eichelmann et al., 2018), which emphasizes the significant role of the local environment and ecosystem on ET. Water availability, radiative energy and vegetation structure have been found to generally be the main factors driving ET. Available water and/or energy are the main factors dominating the ET processes in boreal ecosystems, which can be identified primarily by two indicators, the coefficient αeq and atmosphere decoupling term Ω. Many past studies have shown that well-watered wetlands such as bogs, fens and peatlands at similar or higher altitudes reported average αeq values of 0.55–1.04 (Admiral et al., 2006; Sun and Song, 2008; Sonnentag et al., 2010; 9

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lower decoupling to VPD in the marsh site was likely due to its higher aerodynamic roughness as this site was interspersed with randomlydistributed standing litter at a height of 0.4 m–0.6 m above the water surface. However, the evaporation at the marsh site was in fact not elevated under the low-decoupling condition, indicating that a more important factor can explain the difference in water evaporation. The paddy field site presented a significantly lower average ΔW (Fig. 2d; n = 138, P< 0.01) and a much higher water temperature (Fig. 1c; n = 138, P< 0.01) compared to the marsh site during spring, which could result in a much lower radiation consumption required for heating surface water in the paddy. There are two possible reasons for this result. Firstly, the lowering of the standing water level in the paddy site could result in the reduction in heat storage of the surface water. Secondly, the average temperature of the surface water of the paddy site was 6.7 ℃ higher than that of the marsh site, which indicated less dif­ ference in air temperature and much less heat exchange with the at­ mosphere. Therefore, it is likely that less radiation energy would be allocated to heating water in the paddy field, and hence a higher contribution of energy would be allocated to water evaporation. Therefore, more energy was consumed by evaporation resulting in stronger control of ET by radiation in the paddy field. It could be concluded that the changing hydrological environment resulting from wetland reclamation to paddy field was the most important factor driving energy partitioning and ET. The average difference in ET between the two sites during summer from June to late August was 1.3 mm d− 1. This period was characterized by the rapid increases in LAI, gc and Ω at both sites. The increase in LAI and gc at the marsh site coincided with an increase in αeq from 0.9 to 1.2, reaching a level similar to that of the paddy field. The changes to these parameters suggested both an increased contribution of plant transpi­ ration to ET and a strong influence of available radiation on ET. Surface conductance (gc) has generally been reported as a biophysical indicator of potential ET. gc is closely related to the leaf-level stomatal conduc­ tance and leaf area, and is also influenced by humidity deficits, soil moisture and photosynthetic capacity (Ma et al., 2015; Zhang et al., 2016; Liu et al., 2019a). The results of the present study found that ET was significantly related to gc during the growing season at both sites over the two years (paddy: n = 358, P < 0.05; marsh: n = 358, P < 0.05). The average gc of the paddy field over the summer season was clearly higher than that of the marsh site at 21.9 mm s-1 and 17.6 mm s-1, respectively, which could explain the presence of higher ET at the paddy site. A significant negative exponential relationship was noted between VPD and gc at both sites (Fig. 7), verifying that the ET processes were obstructed under a higher level of VPD (> 0.7 kPa) as concluded in Fig. 3. However, high VPD values > 0.7 kPa usually emerged during the spring season (Fig. 1). VPD did not limit ET over most of summer, thereby supporting the assertion that the ET processes were not controlled by VPD during summer, as inferred from high Ω values. Given the increased importance of plants on ET during summer, changes to plant biophysical characteristics must be considered when evaluating the effects of wetland reclamation to paddy field. The results of the present study showed that leaf stomatal conductance and tran­ spiration were higher within plants at the paddy site compared to those of the dominant plant within the marsh (Fig. 6). Therefore, it was clear that higher values of gc in the paddy field site were due to both larger stomatal conductance and higher canopy LAI. Importantly, the plants occupying the marsh and paddy sites differ in their natural efficiency of mass accumulation, which hints at different water use strategies. Paddy plants have been bred to accumulate as much dry mass as much as possible during the growing season regardless of water availability, whereas marsh plants have evolved to follow a balanced strategy. As shown in Fig. 8, the average values of GPP and NEE for the paddy site were as much as 1.7 and 2.6 times, respectively, of those of the marsh site, which suggests that the paddy site possesses a much greater ability to assimilate and exchange carbon with the atmosphere. Therefore, the paddy site required a much larger power for nutrient absorption and

Fig. 6. Comparison between leaf stomatal conductance and transpiration rate in the paddy field and for two main marsh plants in four selected sunny days of 2017.

carbon delivery produced by leaf transpiration. Similar studies have documented the importance of plant cover alteration for the change of ET in wetland, grassland and forest ecosystems, owing to changed plant physiology (Scott et al., 2006; Ward et al., 2013; Hirano et al., 2017). It can therefore be concluded that changes to plant types resulting from reclamation of marshland to paddy land in the Sanjiang Plain contrib­ uted to considerable differences in ET, particularly during summer time. 4.3. Implications of phenology The reclamation of marshland to paddy fields resulted in consider­ able changes in phenology, characterized by the disappearance of can­ opy LAI in paddy field between late April–late May (Fig. 1f). In contrast, all protogenetic plants in the marsh germinated rapidly before late May during which maximum LAI reached 0.2–0.3. Previous studies evalu­ ating the effect of phenological changes have generally reported consistent and positive linear relationships between ET and leaf area indices (LAI or the NDVI). These positive regressions have been reported for both highly-vegetated ecosystems such as forests and grasslands (Loukas et al., 2005; Nouri et al., 2014) as well as for sparsely vegetated ecosystems such as shrublands (Gong et al., 2017). However, the inde­ pendence between LAI and gc over the entire growing season as well as the parallelism between high paddy ET and minimum LAI before June suggested that LAI is not a suitable indicator for evaluating the effect of marshland reclamation on ET during the spring months in the Sanjiang Plain. The present study showed that the change in hydrological envi­ ronment, not LAI, resulted in the difference in ET during spring. Planting rhythm and irrigation management could be the most important factor driving changes to phenology and ET. 5. Conclusions The present study investigated in situ observations of radiation par­ titioning and ET at a natural marsh site and a reclaimed paddy field site over 2017 and 2018 to better understand the influence of wetland reclamation on the land-surface energy and water cycles in the Sanjiang Plain. Although the reclamation of marshland to paddy field resulted in minimal changes to the seasonal pattern and total quantity of land10

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Agricultural and Forest Meteorology 296 (2021) 108214

Fig. 7. Relationships between surface conductance and vapor pressure deficit (VPD) during sunny days of 2017 and 2018. The data only those collected in sunny days (no rains and cloud cover < 10%) were used in the figure.

Fig. 8. Seasonal dynamics of the net ecosystem exchange (NEE) and gross primary production (GPP) at the two sites in 2017 and 2018.

surface Rn, substantial increases in the LE/Rn and LE/H ratios were evident, indicating a considerable change to energy consumption by ET. Additionally, reclamation greatly reduced heat storage in surface water and soil layer due to a considerable decline in standing water level. Total ET over the growing season reached 411 mm and 645 mm on average in the marshland and paddy sites, respectively, indicating an increase of 57% after reclamation. The most drastic alterations in LE/H and ET occurred over spring during which the surface hydrology regime as well as surface temperature were thoroughly altered by irrigation using groundwater. Changes in dominant plant types contributed to the ma­ jority of differences in ET between the two sites during the summer

months. The plants at the paddy site showed a much higher transpiration potential compared to those at the marshland site due to the evolution of paddy plants to maximize mass production, which results in enhanced water consumption. The higher canopy conductance (gc) observed in the paddy field site confirmed the considerable influence of plant physi­ ology and canopy shape. As indicated by the dynamics of αeq and Ω, the main factor controlling ET in the marsh site changed from VPD to ra­ diation energy Rn during the growing season, whereas Rn remained the main factor controlling ET in the paddy site. Changes in canopy structure, physiology and transpiration potential together with hydrological environment all contributed to the increase 11

Agricultural and Forest Meteorology 296 (2021) 108214

Y. Guo et al.

in ET, suggesting that the changes in surface energy and ET processes resulting from marshland reclamation are complex. The observations made in the current study showed that the reclamation of marshland to paddy field greatly accelerated surface water cycling through ET. Given the great scale of marshland reclamation in the Sanjiang Plain, an inevitable excessive consumption of surface and ground water is pred­ icable, which may well result in a regional water resources deficit. Future studies should consider the inter-annual or long-term impacts of reclamation on regional water cycles, the interactions between the landscape and the atmosphere and should particularly investigate stra­ tegies for reducing ET in paddy fields.

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