Shihong Yang

Seasonal variations of CH4 and N2O emissions in response to water management of paddy fields located in Southeast China

Water management is one of the most important practices that affect methane (CH(4)) and nitrous oxide (N(2)O) emissions from paddy fields. A field experiment was designed to study the effects of controlled irrigation (CI) on CH(4) and N(2)O emissions from paddy fields, with traditional irrigation (TI) as the control. The effects of CI on CH(4) and N(2)O emissions from paddy fields were very clear. The peaks of CH(4) emissions from the CI paddies were observed 1-2d after the water layer disappeared. Afterward, the emissions reduced rapidly and remained low until the soil was re-flooded. A slight increase of CH(4) emission was observed in a short period after re-flooding. N(2)O emissions peaks from CI paddies were all observed 8-10d after the fertilization at the WFPS ranging from 78.1% to 85.3%. Soil drying caused substantial N(2)O emissions, whereas no substantial N(2)O emissions were observed when the soil was re-wetted after the dry phase. Compared with TI, the cumulative CH(4) emissions from the CI fields were reduced by 81.8% on the average, whereas the cumulative N(2)O emissions were increased by 135.4% on the average. The integrative global warming potential of CH(4) and N(2)O on a 100-year horizon decreased by 27.3% in the CI paddy fields, whereas no significant difference in the rice yield was observed between the CI and TI fields. These results suggest that CI can effectively mitigate the integrative greenhouse effect caused by CH(4) and N(2)O emissions from paddy fields while ensuring the rice yield.

Nitrogen Loss from Paddy Field with Different Water and Nitrogen Managements in Taihu Lake Region of China

High rates of nitrogen (N) fertilizer were applied to a paddy field in the Taihu Lake region of China to maximize crop production. Excessive N input has resulted in serious agricultural nonpoint pollution. Water and N management are two important approaches to regulating N loss from paddy fields. This study aimed to determine N losses through ammonia volatilization, runoff, and leaching from a paddy field during the rice-growing season in Taihu Lake region. Field experiments with two water and two N managements were conducted. The N exported to the environment through ammonia volatilization, runoff, and leaching from the paddy field was 37.2 kg N ha−1 to 102 kg N ha−1, with ammonia volatilization accounting for 69.6% to 83.5% of N loss. Ammonium and dissolved organic N significantly contributed to N loss through runoff and leaching. Controlled irrigation and site-specific N management (CS) significantly decreased N losses through ammonia volatilization, runoff, and leaching. Compared with the N and irrigation water inputs in traditional water and N management, those generated by controlled irrigation and site-specific N management were reduced by 34.6% to 43.0% and 59.2% to 63.3%, respectively. Moreover, the reduction in N and water input in the CS paddy field enabled the maintenance of high rice yield; it significantly increased N use efficiency by 15.1% to 34.9% and decreased the N exported to the environment by ammonia volatilization, runoff, and leaching by 53.1% to 56.1%. Therefore, the joint application of controlled irrigation and site-specific N management efficiently reduces agricultural nonpoint pollution through N loss from paddy fields.

Proper methods and its calibration for estimating reference evapotranspiration using limited climatic data in Southwestern China

Proper methods for estimating reference evapotranspiration (ET0) using limited climatic data are critical, if complete weather data are unavailable. Based on the weather data of 19 stations in Guizhou Province, China, several simple methods for ET0 estimation, including the Hargreaves, Priestley–Taylor, Irmak–Allen, McCloud, Turk, and Valiantzas methods, were involved in comparison with the standard FAO-56 Penman–Monteith (PM) method. The Turk equation performs well for estimating ET0 in humid locations. Both the Turk method and the Valiantzas method initially performed acceptably with mean root-mean-square difference (RMSD) of 0.1472 and 0.1282 mm d−1, respectively, with only requiring parameters of temperature (T), relative humidity (RH), and sunshine duration (n). The corresponding calibration formulas to Turk and Valiantzas method were suggested as the most appropriate method for ET0 estimation with the RMSD of 0.0098 and 0.0250 mm d−1, respectively. The local calibrated Hargreaves–Samani method performed well and can be applied as the substitute of FAO-56 PM method under the condition that only the daily mean, maximum, and minimum temperatures were available, and local calibrated McCloud method was acceptable if only the mean temperature was available.

A modified nonrectangular hyperbola equation for photosynthetic light-response curves of leaves with different nitrogen status

Chlorophyll index and leaf nitrogen status (SPAD value) was incorporated into the nonrectangular hyperbola (NRH) equation for photosynthetic light-response (PLR) curve to establish a modified NRH equation to overcome the parameter variation. Ten PLR curves measured on rice leaves with different SPAD values were collected from pot experiments with different nitrogen (N) dosages. The coefficients of initial slope of the PLR curve and the maximum net photosynthetic rate in NRH equation increased linearly with the increase of leaf SPAD. The modified NRH equation was established by multiplying a linear SPAD-based adjustment factor with the NRH equation. It was sufficient in describing the PLR curves with unified coefficients for rice leaf with different SPAD values. SPAD value, as the indicator of leaf N status, could be used for modification of NRH equation to overcome the shortcoming of large coefficient variations between individual leaves with different N status. The performance of the SPAD-modified NRH equation should be further validated by data collected from different kinds of plants growing under different environments.

Solubility and Leaching Risks of Organic Carbon in Paddy Soils as Affected by Irrigation Managements

Influence of nonflooding controlled irrigation (NFI) on solubility and leaching risk of soil organic carbon (SOC) were investigated. Compared with flooding irrigation (FI) paddies, soil water extractable organic carbon (WEOC) and dissolved organic carbon (DOC) in NFI paddies increased in surface soil but decreased in deep soil. The DOC leaching loss in NFI field was 63.3 kg C ha−1, reduced by 46.4% than in the FI fields. It indicated that multi-wet-dry cycles in NFI paddies enhanced the decomposition of SOC in surface soils, and less carbon moved downward to deep soils due to less percolation. That also led to lower SOC in surface soils in NFI paddies than in FI paddies, which implied that more carbon was released into the atmosphere from the surface soil in NFI paddies. Change of solubility of SOC in NFI paddies might lead to potential change in soil fertility and sustainability, greenhouse gas emission, and bioavailability of trace metals or organic pollutants.

Effects of soil heat storage and phase shift correction on energy balance closure of paddy fields

The eddy covariance technique was used to measure the energy fluxes of a paddy field under water-saving irrigation in the South China Plain for the stage of rice growth in 2013. This study analyzed the energy balance components and evaluated the energy balance closure. The study also discussed the response of surface energy balance to the change in soil heat storage between the heat flux plates buried at a specific depth and the surface, and the phase shift correction of energy balance components, by using three different statistical methods, namely ordinary least squares (OLS), energy balance ratio (EBR), and energy balance residual (D). The results showed that the OLS slope increased by an average of 8.8%, and the mean daily EBR increased by 5.0% after considering the change in soil heat storage. The range of half-hourly D over a four-month period decreased from –129 - 260 W m −2 to –102 - 194 W m −2 , and the absolute value of D decreased by 9.9% on the average. Considering the phase correction, the increase in OLS regression coefficients with an average of 11.3% and the decrease in half-hourly D, ranging from –61 to 176 W m −2 , both indicated that phase shift correction improved the surface energy balance closure at the half-hourly scale, specifically in the period from sunrise to noon, but had no use in the daily scale. Thus, the two correction methods are useful in improving the degree of energy balance closure shown in different temporal scales with proper evaluation index. Moreover, further research should be given with more attention for other correction aspects.

Validation of dual-crop coefficient method for calculation of rice evapotranspiration under drying-wetting cycle condition

Based on data collected from rice fields under drying–wetting cycle condition, the procedure of dual-crop coefficient (Kcd) approaches was calibrated and validated to reveal its feasibility and improve its performance in rice evapotranspiration (ETc) estimation. It was found that Kcd based on FAO-recommended basal crop coefficients (Kcb) underestimated dual-crop coefficients in monsoon climate region in East China. The recommended coefficient (Kcp) value of 1.2 was not high enough to reflect the pulse increase of rice ETc after soil wetting. The Kcb values were calibrated as 1.52 and 0.63 in midseason and late season, and the Kcp value was adjusted as 1.29 after soil wetting in rice field under drying–wetting cycle condition. The dual-crop coefficient curves based on locally calibrated KcbCal and KcpCor matched well with the measured crop coefficients and performed well in calculating rice evapotranspiration from paddy fields under drying–wetting cycle condition. So it can be concluded that the procedure of dual-crop coefficient method is feasible in rice ETc estimation, and locally calibrated Kcb and Kcp can improve its performance remarkably.

Ammonia Volatilization Losses from Paddy Fields under Controlled Irrigation with Different Drainage Treatments

The effect of controlled drainage (CD) on ammonia volatilization (AV) losses from paddy fields under controlled irrigation (CI) was investigated by managing water table control levels using a lysimeter. Three drainage treatments were implemented, namely, controlled water table depth 1 (CWT1), controlled water table depth 2 (CWT2), and controlled water table depth 3 (CWT3). As the water table control levels increased, irrigation water volumes in the CI paddy fields decreased. AV losses from paddy fields reduced due to the increases in water table control levels. Seasonal AV losses from CWT1, CWT2, and CWT3 were 59.8, 56.7, and 53.0 kg N ha−1, respectively. AV losses from CWT3 were 13.1% and 8.4% lower than those from CWT1 and CWT2, respectively. A significant difference in the seasonal AV losses was confirmed between CWT1 and CWT3. Less weekly AV losses followed by TF and PF were also observed as the water table control levels increased. The application of CD by increasing water table control levels to a suitable level could effectively reduce irrigation water volumes and AV losses from CI paddy fields. The combination of CI and CD may be a feasible water management method of reducing AV losses from paddy fields.

Controlled irrigation and drainage of a rice paddy field reduced global warming potential of its gas emissions

The effect of controlled drainage on methane (CH4) and nitrous oxide (N2O) emissions from a paddy field under controlled irrigation (CI) was investigated by controlling the sub-surface drainage percolation rate with a lysimeter. CI technology is one of the major water-saving irrigation methods for rice growing in China. Water percolation rates were adjusted to three values (2, 5, and 8 mm d−1) in the study. On the one hand, the CH4 emission flux and total CH4 emission from paddy fields under CI decreased with the increase of percolation rates. Total CH4 emissions during the growth stage of rice were 1.83, 1.16, and 1.05 g m−2 in the 2, 5, and 8 mm d−1 plots, respectively. On the other hand, the N2O emission flux and total N2O emissions from paddy fields under CI increased with the increase of percolation rates. Total N2O emissions during the growth stage of rice were 0.304, 0.367, and 0.480 g m−2 in the 2, 5, and 8 mm d−1 plots, respectively. The seasonal carbon dioxide (CO2) equivalent of CH4 and N2O emissions from paddy fields under CI was lowest in the 2 mm d−1 plot (1364 kg CO2 ha−1). This value was 1.4% and 19.4% lower compared with that in the 5 and 8 mm d−1 plots, respectively. The joint application of CI and controlled drainage may be an effective mitigation strategy for reducing the carbon dioxide equivalents of CH4 and N2O emissions from paddy fields.

Prediction of daily reference evapotranspiration by a multiple regression method based on weather forecast data

Prediction of daily reference evapotranspiration (ET 0) is the basis of real-time irrigation scheduling. A multiple regression method for ET 0 prediction based on its seasonal variation pattern and public weather forecast data was presented for application in East China. The forecasted maximum temperature (T max), minimum temperature (T min) and weather condition index (WCI) were adopted to calculate the correction coefficient by multilinear regression under five time-division regimes (10 days, monthly, seasonal, semi-annual and annual). The multiple regression method was tested for its feasibility for ET 0 prediction using forecasted weather data as the input, and the monthly regime was selected as the most suitable. Average absolute error (AAE) and root mean square error (RMSE) were 0.395 and 0.522 mm d−1, respectively. ET 0 prediction errors increased linearly with the increase in temperature prediction error. A temperature error within 3 K is likely to result in acceptable ET 0 predictions, with AAE and average absolute relative error (AARE) <0.142 mm d−1 and 5.8%, respectively. However, one rank error in WCI results in a much larger error in ET 0 prediction due to the high sensitivity of the correction coefficient to WCI and the large relative error in WCI caused by one rank deviation. Improving the accuracy of weather forecasts, especially for WCI prediction, is helpful in obtaining better estimations of ET 0 based on public weather data.