Results and discussion Directory UMM :Data Elmu:jurnal:A:Agricultural & Forest Meterology:Vol102Issue4May2000:

A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 293 Fig. 1. Floodwater depth, surface energy balance and selected meteorological conditions during IREX96. a Floodwater depth d w , b windspeed at a height of 2.2 m U measured with a sonic anemometer and friction velocity u ∗ , c air temperature T a and saturation deficit of the air at a height of 2.4 m in mixing ratio D a , d net radiation R n , sensible heat flux H and latent heat flux λE.

4. Results and discussion

4.1. Vertical profiles of CO 2 and CH 4 concentrations Typical profiles of CO 2 and CH 4 concentrations in the daytime and at night under drained and flooded conditions are shown in Fig. 2. Each profile is a 2 h mean, and noted time represents the beginning of the averaging period. The CO 2 profile in the daytime showed a minimum at the middle layer of the canopy owing to CO 2 absorption by rice plants, while at night, the CO 2 profile showed a monotonic decrease with height reflecting respiration by plants and the soil. The CH 4 profiles showed a monotonic decrease with height both in the daytime and at night, but the vertical gradients of the concentrations at night un- der low wind conditions were 3–4 times as large as those in the daytime. A notable feature in Fig. 2 is that the vertical gradients of both gases were larger under drained conditions than under flooded condi- tions, although windspeeds were similar. The CO 2 concentrations near the ground were also larger under drained than flooded conditions. The vertical gradient of concentration above the canopy between 1.10 and 2.40 m decreased with u ∗ . Typical magnitude of the CH 4 gradient was 294 A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 Fig. 2. Examples of vertical profiles of CO 2 upper figures and CH 4 concentrations lower figures at a rice paddy in the daytime and at night. Each profile shows 2 h means of the difference from the concentration at 2.2 m. Closed circles indicate profiles under flooded condition with a depth of 10 cm, and open circles indicate profiles under drained condition. h c indicates canopy height. Beginning time of the averaging period and the mean horizontal windspeed are shown at the top of the figure. 15 ppbv m − 1 at u ∗ of 0.2 m s − 1 , and 10 ppbv m − 1 at 0.3 m s − 1 . The gradient increased markedly up to 220 ppbv m − 1 under stable atmospheric conditions with u ∗ 0.1 m s − 1 . 4.2. CO 2 fluxes under drained and flooded conditions The time course of CO 2 fluxes above the canopy measured by the eddy covariance method F CO2 is shown in Fig. 3. Also shown are the time courses of air temperature within the canopy and soil temper- atures at 2 and 5 cm depth. Missing data for F CO2 are mainly due to the open-path infrared gas analyzer being out of range at night. The differences in noc- turnal F CO2 between drained and flooded conditions are clearly shown in Fig. 3a. The nocturnal F CO2 under drained conditions from 7 to 8 August was 0.41±0.07 mg CO 2 m − 2 s − 1 the mean±the standard deviation; 1900–0500 hours, whereas under flooded conditions from 9 to 13 August it was 0.19±0.06 mg CO 2 m − 2 s − 1 . The nocturnal F CO2 under flooded conditions are within the range of aboveground rice respiration rate measured by chambers about a month before heading 0.1–0.3 mg CO 2 m − 2 s − 1 ; Yamaguchi A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 295 Fig. 3. Time courses of a CO 2 flux over the canopy by the eddy covariance method F CO2 , b air temperature at a height of 0.48 m, soil temperature at depths of 2 and 5 cm below the soil surface, c saturation deficit of the canopy D s and the canopy conductance G c . et al., 1975; Hirota and Takeda, 1978; Baker et al., 1992; Saitoh et al., 1998. This agreement confirms the nocturnal F CO2 measurement by the eddy co- variance method. Since mean nocturnal air temper- atures between drained and flooded conditions were very similar differences 0.3 ◦ C; see Fig. 3b, we expect plant respiration also to have been similar every night, and thus not responsible for observed differences in the nocturnal F CO2 between the two treatment periods. Possible explanations are discussed further. During IREX96, CO 2 emission rates from bare soil and from floodwater, F CO2,S were measured near the masts by using a dynamic, dark-chamber method. Fluxes from the soil were measured on 7 and 8 August under drained conditions, whereas those from flood- water were measured in the morning of 6 August. The fluxes from the soil ranged from 0.20 to 0.43 mg CO 2 m − 2 s − 1 when soil temperature at 5 cm varied be- tween 26.0 to 28.5 ◦ C the nocturnal range of soil tem- perature shown in Fig. 3b, whereas the fluxes from the floodwater were two orders of magnitude smaller, at several mg CO 2 m − 2 s − 1 . These results suggest that the higher nocturnal CO 2 fluxes measured above the canopy under drained conditions can be attributed to increased CO 2 emission from the bare soil compared to that from floodwater. The strong response of soil microbial and root respiration to temperature cannot be responsible for the observed change in net noctur- nal CO 2 flux, because under drained soil, nocturnal 1900–0500 hours mean soil temperatures at 2 and 5 cm were lower by 2.3 and 1.1 ◦ C, respectively, than under flooded conditions Fig. 3b. This should lead to lower fluxes. Instead, higher fluxes under drained conditions result from the elimination of the resistance caused by the floodwater to the transport of respired CO 2 from the soil to the atmosphere. Leuning et al. 2000 came to similar conclusions as a result of their analysis of sourcesink distributions within the canopy. The increase of soil respiration F CO2 , S under drained conditions must affect not only the noctur- nal F CO2 over the canopy but also F CO2 during the day. We can use our measurements of soil respiration 296 A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 Fig. 4. Relationship between net photosynthesis rate of rice plants P n , canopy conductance G c and photosynthetically active radiation flux density R p on drained days 7–8 August; closed circles and flooded days 10–12 August; open circles. In c and d, P n and G c are normalized to the constraint function of saturation deficit f D D s f D 10, where f D 10 is the value of f D when D s = 10 g kg − 1 . obtained at night to estimate the net photosynthesis rate of rice plants P n using P n =− F CO2 + F CO2,S . As a first approximation we assumed that F CO2,S = 0 mg CO 2 m − 2 s − 1 for flooded soil and F CO2,S = 0.21 mg CO 2 m − 2 s − 1 under drained conditions, the excess amount of the nocturnal mean F CO2 compared to flooded conditions. Fig. 4a shows the relationship between P n and photosynthetically active radiation flux density R p when the paddy was drained 7–8 August and flooded 10–12 August, the data on transitional 9 August were excluded. From the hy- perbolic curves fitted to the data, P n was larger when the paddy was drained than when it was flooded by 18 at R p of 1500 mmol m − 2 s − 1 , and by 22 at R p of 2000 mmol m − 2 s − 1 . We next examine whether the changes in canopy photosynthesis can be explained by the higher air tem- peratures and saturation deficits observed during the flooded days compared to the drained days Fig. 1c. To explore this, P n was analyzed in relation to canopy conductance in the so-called ‘big-leaf model’. The canopy conductance G c is defined as G c = E c ρD s 6 where E c is the evapotranspiration rate from rice plants, D s is saturation deficit at the big leaf surface expressed as specific humidity note that we are discussing the conductance and saturation deficit of the canopy only, excluding the soilwater surface. From the definition of the Penman–Monteith equation and Eq. 6, D s is given as follows Kelliher et al., 1993: D s = D a − ε + 1 G a ρ E c − ε ε + 1 R n,c λ 7 where D a is saturation deficit at a reference height 2.4 m, G a is the aerodynamic conductance, and R n,c is the net radiation absorbed by the canopy. The ther- modynamic coefficient ε is expressed as ε=λC p dq sat dT, where dq sat dT is the slope of the saturation specific humidity–temperature curve. In this study, G a was calculated from u ∗ and the mean horizontal wind- A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 297 speed U at a height of 2.2 m such as G a = u ∗ 2 U. R n,c was calculated from the extinction coefficient of net radiation by the rice canopy 0.66; Uchijima, 1961 and LAI. E c was calculated as E–E s , where E s is the evaporation rate from the soilwater surface which was estimated from the available energy at the soilwater surface Leuning et al., 2000. The estimated E c was 84, on average, of the total water vapor flux mea- sured above the canopy E, both for drained and flooded conditions, and the ratio is in good agreement with a previous study 86 at LAI=3.08; Uchijima, 1961. Daytime G a ranged from 10 to 60 mm s − 1 , except on 12 and 13 August when it was windy and G a in- creased up to 70 mm s − 1 . As shown in Fig. 3c, values of D s in the daytime were generally 10 g kg − 1 , but in the afternoon of 10 and 11 August, D s exceeded 13 g kg − 1 . As a result, G c around noon of these two days was 12–13 mm s − 1 , compared to peak values of 14–18 mm s − 1 on other days. On the windy day of 13 August, G c at midday exceeded 21 mm s − 1 when D s was small. The relationship between G c and R p Fig. 4b shows that canopy conductances on flooded days were smaller than drained days at the same R p level. To examine the influence of saturation deficit on G c quantitatively, we utilize constraint functions follow- ing Jarvis 1976 and Schulze et al. 1995: G c = G c,max f R R P f D D s f T T 1 8 where G c,max is the value of G c without constraints, and the functions f R , f D and f T between 0 and 1 ac- count for the constraints on G c,max imposed by, irra- diance, D s and leaf temperature T l , respectively. As a first approximation we assumed that f T = 1 no con- straint and that f D has the hyperbolic form f D D s = 1 1 + D s D s,12 9 where D s,12 is the value of D s at which G c = G c,max 2. We assumed a typical value of D s,12 = 10 g kg − 1 Le- uning, 1995, and normalized both P n and G c to a standard humidity deficit of 10 g kg − 1 through mul- tiplying by the factor f D 10f D D s . It is accept- able to normalize P n by this factor as well because it is relatively insensitive to changes in D s see Leun- ing, 1995. Relationships between the normalized P n and G c as a function of R p Fig. 4c and d, respec- tively now show little difference between the flooded Fig. 5. Daily CO 2 budget at the paddy. Daytime amounts are the sum of the CO 2 flux over the canopy from 0500 to 1900 hours, and nighttime amounts are from 1900 to 0500 hours on the following day. Bars indicate an uncertainty range of the estimated amount corresponding to the corrections to the CO 2 flux by the eddy covariance method for path-length averaging and sensor separation. and drained conditions. This suggests the difference in P n between drained and flooded days was principally due to the response of G c to an increase in saturation deficit. The larger saturation deficit on flooded days than on drained days was caused by the differences in synoptic-scale meteorological conditions rather than the state of flooding of the paddy. Daily CO 2 budgets for the rice paddy are shown in Fig. 5. In the summation of F CO2 , missing data were estimated from the P n –R p relation shown in Fig. 4a, while F CO2,S was assumed zero under flooded conditions and a constant 0.21 mg CO 2 m − 2 s − 1 under drained conditions. The summation period for the daytime was from 0500 to 1900 hours, and for the nocturnal period from 1900 to 0500 hours. Bars show the uncertainty range of F CO2 which was esti- mated to be the same magnitude as the corrections for path length averaging and sensor separation. Since we applied these corrections to recover missing cospectrum in high frequency range, the magnitude of the corrections shows the degree of uncertainty in F CO2 . The daily sum of R p was similar on most days, 51–52 mol m − 2 d − 1 , except for slightly larger values on 10 August 57 mol m − 2 d − 1 and 12 August 59 mol m − 2 d − 1 . As shown in Fig. 5, the average daytime CO 2 uptake was 29.2 g CO 2 m − 2 when the field was drained 7 and 8 August, 23 smaller than when it was flooded 10–12 August. The nighttime 298 A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 CO 2 emission on the drained days, on the other hand, was 14.7 mg CO 2 m − 2 , which was almost twice as much as on the flooded days. As a result, the average net daily 24 h CO 2 uptake on the drained days was 14.5 g CO 2 m − 2 , while it was 29.8 g CO 2 m − 2 on the flooded days. As described earlier, these differences in the CO 2 budget between the two treatment periods are mainly due to differences in the rate of CO 2 re- lease from the soil surface, and to a lesser extent the reduction of plant photosynthesis due to the larger saturation deficit on flooded days. A previous study on the same site and at a similar rice growth stage Tsukamoto, 1993, 1994 showed that the net downward CO 2 flux between 0500 and 1900 hours was 33 smaller when the field was drained than when it was flooded with 10 cm of wa- ter. The IREX96 results are similar to this study, and it is now clear that the decrease in the net daytime downward CO 2 flux under drained conditions was caused by an increase of CO 2 emission from the soil surface. In the short term, intermittent drainage thus reduces net CO 2 uptake from the atmosphere by rice paddies compared to continuously flooded paddies. 4.3. CH 4 fluxes under drained and flooded conditions The time courses of CH 4 fluxes over the canopy as determined by the K CO2 method K CO2 –F CH4 are shown in Fig. 6. Most of the missing flux data in Fig. 6 are due to condensation of water in the sampling line which caused the malfunction of the gas analyz- ers. Bars on K CO2 –F CH4 , which are shown only every hour for clarity, represent an uncertainty range of the flux corresponding to the standard error of the vertical difference of CH 4 and CO 2 concentrations and the un- certainty of CO 2 flux by the eddy covariance method. In Fig. 6, the large uncertainty in the daytime flux is due to small vertical differences in CH 4 concentration. As shown in Fig. 6, K CO2 –F CH4 on a 30 min basis showed large fluctuations ranging from 0.2 to 2.1 mg CH 4 m − 2 s − 1 , mainly due to the small vertical differ- ence of CH 4 concentration over the canopy. Even so, a 7-term running mean of K CO2 –F CH4 showed a dis- tinct diurnal variation under drained conditions, with larger fluxes 1.2–1.3 mg CH 4 m − 2 s − 1 in the after- noon than at night 0.3–0.4 mg CH 4 m − 2 s − 1 . The CH 4 flux showed a significant decrease after reflood- ing on 9 August, and diurnal variation of the flux de- clined on and after 10 August. The CH 4 fluxes on 13 August were uncertain because of large fluctuations and missing data, but it seems that the CH 4 fluxes were recovering. Detailed diurnal variations of K CO2 –F CH4 and the CH 4 flux by the aerodynamic method AD–F CH4 from midday of 8 August to the evening of 9 August are shown in Fig. 7. Also shown are the diurnal vari- ations of the soil temperature at a depth of 2 cm and the windspeed at a height of 2.2 m. Bars on AD–F CH4 represent a range corresponding to the standard error of the vertical CH 4 concentration difference and the uncertainty of conductance D Eq. 3 which origi- nates mainly from ζ . Under low windspeed conditions found at night, u ∗ and H determined by the eddy covariance method have considerable uncertainties. Since ζ is proportional to u ∗ − 3 Eq. 2, any mea- surement errors in u ∗ are greatly amplified in ζ . The measurement errors in H add further uncertainty to ζ . As a result, ζ and D under low windspeed conditions were not reliable. In fact, the estimated uncertainty in AD–F CH4 under such conditions was one order of magnitude greater than that in K CO2 –F CH4 . For these reasons, we excluded AD–F CH4 when u ∗ was 0.1 m s − 1 this threshold was equivalent to 0.7 m s − 1 in horizontal windspeed at 2.2 m from the figure and the following analysis. As shown in Fig. 7a, the day- time AD–F CH4 the 7-term running mean is a little smaller than K CO2 –F CH4 , but the fluxes by the two methods are generally in agreement with each other within the measurement error. Fig. 7 demonstrates that the pattern in the diurnal variation of the CH 4 fluxes is quite similar to those of soil temperature and windspeed, which decrease gradually from the afternoon through the night and increase from the morning to the afternoon. The daily budget of CH 4 flux from the paddy is shown in Fig. 8. Missing flux data from 7 to 9 August were interpolated using relationships between the flux and soil temperature at a depth of 2 cm. The relation- ships were determined each day by fitting a polyno- mial function of second degree using the least squares method the fitting passed the x 2 -test on a significant level of 5. For other days, missing data were in- terpolated using the average of each 5 data points be- fore and after the missing period. As shown again in Fig. 8, the fluxes by the AD method are systematically A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 299 Fig. 6. Time course of CH 4 flux over the rice canopy. Pluses represent the fluxes by the K CO2 method K CO2 –F CH4 , and bars, which are shown only every hour, represent a range of the flux corresponding to the standard error of the vertical differences of CH 4 and CO 2 concentrations and the uncertainty of the CO 2 flux measured by the eddy covariance method. Solid lines denote the 7-term running mean of individual K CO2 –F CH4 . Closed squares and open squares denote the flux by the chamber measurement on 13 August at the western site and the eastern site, respectively. Fig. 7. Diurnal variation of a CH 4 flux, b soil temperature at a depth of 2 cm solid line, and windspeed dotted line from midday of 8 August to the evening of 9 August. Closed circles and open circles in Fig. 7a denote the CH 4 fluxes by the K CO2 method K CO2 –F CH4 and by the AD method AD–F CH4 , respectively, and solid line and dotted line denote their 7-term running mean. Bars on K CO2 –F CH4 are the same as those in Fig. 6, while those on AD–F CH4 represent a range corresponding to the standard error of the vertical difference of CH 4 concentration and an uncertainty of the conductance in Eq. 3. 300 A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 Fig. 8. Accumulated amount of methane emission from the paddy in the daytime from 0500 to 1900 hours and at night from 1900 to 0500 hours on the following day obtained by the K CO2 method and the AD method. The AD method was not available at nights from 7 to 10 August because of calm conditions. Bars represent uncertainty ranges of the accumulated amount which were estimated from the uncertainties of individual 30 min fluxes. smaller than those by the K CO2 method, but the differ- ences between the two methods are within measure- ment error indicated by bars. The agreement between the two different micrometeorological methods gives us confidence in the calculated fluxes, although we have much fewer nighttime fluxes by the AD method than the K CO2 method. Day-to-day change of the daily CH 4 flux is well demonstrated in Fig. 8. The daytime fluxes from 0500 to 1900 hours by the K CO2 method on 7 and 8 August were 52 and 43 mg CH 4 m − 2 , respectively, which de- creased to 30–33 mg CH 4 m − 2 for the flooded paddy on 10–12 August. As shown by bars in Fig. 8, the dif- ferences in the daytime CH 4 flux are statistically in- significant except on 7 August, but a decreasing trend in the daytime CH 4 flux from 7 to 12 August is ap- parent. The nighttime flux from 1900 to 0500 hours, ranging between 15 and 28 mg CH 4 m − 2 , did not show a monotonic trend. As a result, the daily amount of CH 4 emission from the paddy on drained days in- cluding a transitional 9 August ranged from 58 to 80 mg CH 4 m − 2 , which decreased to less than 60 mg CH 4 m − 2 on following flooded days the average for 10–12 August was 53 mg CH 4 m − 2 . Among possible factors which affect the CH 4 flux, soil temperature can be influenced by drainage and flooding. In IREX96, however, daily maximum soil temperatures at a depth of 2 cm stayed at 32 ◦ C on and until 10 August, then dropped to 31 ◦ C Fig. 3b, whereas diurnal variation of CH 4 flux declined on 10 August Fig. 6. This indicates soil tempera- ture had a minor influence on the difference of CH 4 fluxes between the two treatment periods. Instead, as with the CO 2 flux, the increased CH 4 flux resulted from the absence of floodwater which reduced the resistance to gas diffusion from the soil to the air under drained conditions. The change is not as dra- matic as for CO 2 Fig. 3a because much of the CH 4 is released to the air through plant-mediated trans- port Minami and Neue, 1994 and the rest by dif- fusion from the soil to the air. After the reflooding on 9 August, the CH 4 flux decreased because the diffusion from the soil to air was prevented by the water layer, but CH 4 was still released through the plant-mediated process. Although our measurements were aborted on 13 August by a typhoon, we expect the CH 4 flux would recover gradually with the progress of soil reduction under continuously flooded anaerobic conditions. Previous studies using chambers showed intensive CH 4 emission lasting some tens of hours following a drainage event Neue and Sass, 1994. In a Japanese rice paddy, Yagi 1997 observed an increased CH 4 emission after drainage which continued about two days and showed a diurnal variation with a maxi- mum in the daytime. From an analysis of the rela- tionship between the drainage duration and changes in CH 4 flux before and after a drainage, Yagi 1997 found drainage lasting more than 2 days reduced the CH 4 flux after reflooding for a few weeks to a lower level than before drainage. The trend in the day-to-day change of the daily CH 4 flux during IREX96 Fig. 8 was consistent with the findings of these previ- ous studies. In IREX96, the daily CH 4 flux on the drained days was larger than on the flooded days by 28 on average, while previous studies found much larger increases after drainage events Neue and Sass, 1994; Yagi, 1997. The amount and duration of the temporary increase of CH 4 emission after drainage depend on the accumulated amount of CH 4 in the soil before drainage. The intermittent drainage at the present study site prevented the recovery of the pro- duction and the accumulation of CH 4 in the soil, and this resulted in a smaller increase in the daily CH 4 flux after drainage than those observed in the previous studies. A. Miyata et al. Agricultural and Forest Meteorology 102 2000 287–303 301 As mentioned earlier, the diurnal variation in the CH 4 flux under drained conditions showed a distinct positive correlation with soil temperature and wind- speed Fig. 7. This is because temperatures up to 30–35 ◦ C accelerate CH 4 production by methanogenic bacteria in the soil, and the amount of CH 4 dissolved in the soil solution decreases with increasing temper- ature Minami and Neue, 1994. Plant-mediated CH 4 transport also shows an increase with increasing tem- perature Nouchi et al., 1994; Hosono and Nouchi, 1996, although the relationships found by these au- thors were between the seasonal variation of CH 4 flux and temperature rather than the diurnal variation ob- served here. As well as these temperature effects, the distinct diurnal variation of the CH 4 flux observed during IREX96 was influenced by windspeed which affects the diffusion resistance from the soil to the air under drained conditions. Drainage and flooding thus affect the CH 4 flux by changing the diffusion resistance to CH 4 transport from the soil to air as well as by changing the CH 4 production rates in the soil. Methane fluxes were also measured by the closed chamber method on 13 August. The measurements were made in the morning 0930–1100 hours and in the early afternoon 1215–1345 hours at two adja- cent locations at each site, and the average of each pair of measurements are shown in Fig. 6. The fluxes at the eastern site were 1.2 and 1.3 mg CH 4 m − 2 s − 1 , while those at the western site were 2.2 and 2.7 mg CH 4 m − 2 s − 1 . Measurements using the chamber at the eastern site were comparable with the running mean of K CO2 –F CH4 , but fluxes from the western site were double the peak observed from the mi- crometeorological measurements. It is likely that spatial inhomogeneity caused by variation in den- sity of rice plants, nutrient status of the soil and water depth are partly responsible for difference in fluxes measured by the chambers at the two sites. In one of the few other comparisons published, Kane- masu et al. 1995 found that CH 4 fluxes from rice paddies estimated using closed chambers exceeded micrometeorological measurements by a factor of 2. Further detailed studies are required to clarify whether spatial heterogeneity is sufficient to explain such discrepancies or whether there are systematic methodological differences between the measurement techniques.

5. Conclusion