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The ecosystem services value of paddy fields has received increasing attention in agricultural policy decisions. This paper presents the first study to investigate the effects of rice water-saving irrigation on the economic value of gas exchange in a paddy field ecosystem based on a field experiment. The results showed that, compared to traditional flooding irrigation (FI), controlled irrigation (CI) decreased irrigation water input while maintaining high rice yield. Irrigation methods showed no significant influence on O2 production and its value in paddy fields. CI significantly reduced CH4 emissions and its negative economic value by 81.80%, but increased N2O by 136.86%. The economic value of CO2 uptake far outweighed the absolute value of negative economic values caused by CH4 and N2O emissions. Therefore, the irrigation methods showed no significant difference in economic value caused by greenhouse gas emissions (GHGs) from rice paddies. CI management significantly decreased ammonia volatilization (AV) and its economic value by 19.56%. Overall, CI increased economic value of gas exchange (O2 production, GHGs emission, and AV) by 8.96% compared to FI paddies. Our results suggest that CI significantly increased the economic value of gas exchange in a paddy field ecosystem while drastically reducing irrigation water input and ensuring rice yields. [ABSTRACT FROM AUTHOR]

Quantifying greenhouse gas (GHG) emissions from irrigated paddy fields is of great significance for addressing climate change. Machine learning (ML) provides an alternative to empirical models and biogeochemical models, but it has not been used to simulate GHG emissions from paddy fields. In this study, a three-year field experiment dataset of paddy fields under controlled irrigation (CI, a kind of water-saving irrigation (WSI) technology) and flood irrigation (FI) in Kunshan, China, was collected, as well as a global dataset on WSI and FI. Then, the stacking ensemble model was developed based on three basic ML models, random forest (RF), K-Nearest Neighbor regression (KNN), gradient boosting regression (GBR), and a meta-learner, linear Regression (LR). Those models were used for the first time to simulate CH 4 and N 2 O emissions on different time scales from paddy fields under WSI and FI. The results showed that the cumulative CH 4 and N 2 O emissions from the WSI paddy fields decreased by 61.14% and increased by 19.52%, respectively, compared with FI. The ML algorithm can be applied to simulate daily, growth stages, and cumulative GHG emissions from paddy fields, but the performance of the linear regression model was worse than other ML models. Compared with the basic models, the stacking model improved the accuracy, improving the R 2 by 0.37∼13.36% and reducing the RMSE by 3.23∼42.78%. Soil redox, temperature, and moisture are necessary for accurate modeling. Meanwhile, training the model using data from WSI and FI separately is beneficial to improve the accuracy of the model. The availability of the stacking model in other stations was verified based on literature data, with R 2 varying between 0.7634 and 0.9985. Therefore, the stacking model is recommended to predict GHG emissions at different time scales from paddy fields, and this method can be extended to estimate GHG from paddy fields at various stations around the world. [Display omitted] • Machine learning (ML) was used to predict CH4 and N2O emissions from paddy fields. • The stacking model was the best in modeling greenhouse gas at various time scales. • Soil redox, temperature, and moisture are necessary for accurate modeling. • Separate training for different irrigated paddy fields is recommended. • The simulation method can be extended to paddy fields in different places. [ABSTRACT FROM AUTHOR]

Based on the results of continuous flux measurements in the Taihu Lake Region of China, the carbon dioxide (CO 2 ) exchange of paddy fields under water-saving irrigation and its influence factors were analyzed. The net ecosystem exchange of CO 2 ( NEE ) were negative during the daytime and positive at night, and the minimum value appeared around noon. The peak CO 2 uptake in the flourishing period was approximately 1.5 times the values observed in the tillering and ripening stages. Frequent alternation of wetting and drying in paddy fields with water-saving irrigation resulted in larger NEE for the typical day before soil rewatering than that for the day after soil rewatering in the early growth stage. These alterations had a minimal effect on diurnal variation of NEE in the late rice growth stage. The average NEE for the typical days after soil rewatering in July and August were 2.30 and 1.38 times that before soil rewatering, respectively. CO 2 exchange in paddy field ecosystem under water-saving irrigation displayed seasonal variation with the change of rice plant growth. The total ecosystem respiration ( R eco ), NEE and gross primary productivity ( GPP ) were 1996.88, −1284.15 and 3281.03 g m −2 , respectively, throughout the growth stage. These results showed that the paddy field ecosystem under water-saving irrigation was a sink for atmospheric CO 2 . Frequent alternation of wetting and drying processes increased the ecosystem reparation of paddy fields under water-saving irrigation and produced smaller net CO 2 absorption compared to that of flooding irrigation. The net CO 2 absorption because of plant photosynthesis during the daytime and the net CO 2 release at night measured by static transparent chamber method were larger than those measured by eddy covariance method ( P < 0.05). The nighttime respiration of paddy field ecosystem under water-saving irrigation increased exponentially with temperature. Additionally, a larger temperature sensitivity coefficient ( Q 10 ) was observed for paddy fields under water-saving irrigation compared to that under flooding irrigation. The photosynthetic photon flux density ( PPFD ) was the most important factor for regulating daytime GPP . And the light saturation point during the heading-flowering and milk stages of paddy field ecosystem with water-saving irrigation (1500 μmol m −2 s −1 ) was higher than that of fields with flooding irrigation in previous studies. A significant positive correlation was found between the leaf area index ( LAI ) and the daily GPP . [ABSTRACT FROM AUTHOR]

The temporal and spatial variation of soil respiration of farmland has great influence on regional and global carbon cycle. Irrigation is an important factor to soil respiration in farmland. Existing study on the effect of irrigation on farmland soil respiration mainly focused on the dry farmland, but less research focused on paddy fields. Relationships between soil respiration and water depth and short-term drying of paddy fields with flooding irrigation were analyzed in existing studies. In order to reveal the difference of soil respiration in paddy fields with water-saving irrigation and traditional irrigation, the diurnal variation of soil respiration, the impact of alternation of wetting and drying on soil respiration, and the influencing factors of soil respiration for paddy fields were analyzed based on lysimeter experiment. The results showed that diurnal variations of soil respiration of paddy fields with water-saving irrigation and normal irrigation were similar at the period when the status difference of soil moisture was small between the two irrigation modes. Diurnal variations of soil respiration of paddy field with water-saving irrigation showed wider range, and the fluxes and rangeability of soil respiration of paddy field with water-saving irrigation were larger than those for traditional irrigation when the status difference of soil moisture was large. The mean value of soil respiration of diurnal variation during the whole growth period for water-saving irrigation was 1.47 times that for traditional irrigation. But during early tillering stage, jointing-booting stage and milk stage in which water managements were obviously different, the mean values of soil respiration diurnal variations for water-saving irrigation were 3.85, 1.42 and 3.74 times those for traditional irrigation. This results could contribute to frequent alternation of wetting and drying of paddy fields with controlled irrigation. The processes of soil rewatering and soil moisture depletion both had a certain effect on soil respiration of paddy fields. Peaks of soil respiration appeared at the critical point of soil moisture depletion. In the critical point of soil rewatering, the increase of soil respiration rate was not obvious if the rewatering depth was thicker, and the increase was significant if the rewatering depth was thinner. And small peaks of soil respiration appeared when soil water content decreased close to the lower limit of soil water content of paddy field with controlled irrigation during the irrigation interval. Soil temperature and soil moisture had great impact on soil respiration of paddy field with water-saving irrigation. Good exponential dependence was showed between soil respiration flux and soil temperature in the depth of 5 cm in paddy fields, and the correlation reached significant level for paddy field with water-saving irrigation (P<0.05). Management mode without water layer for controlled irrigation led the soil moisture conditions to be similar to dry farmland, so the relationship between soil respiration and soil temperature of paddy fields with controlled irrigation was more consistent with the existing results in dry farmland and forest. Water layer was kept in field surface for a long time under traditional irrigation, which led the soil into strict anaerobic conditions, and the effects of soil temperature on soil respiration was relatively weaken. The soil volumetric moisture content of 43% was the critical point for soil respiration of paddy field with water-saving irrigation when the soil volumetric moisture content ranged from 35% to 55%. Soil respiration flux in paddy field with water-saving irrigation increased with the enhancement of soil moisture content when the soil volumetric water content was lower than the critical value (P<0.05). And soil respiration flux in paddy field with water-saving irrigation decreased with the increase of soil moisture content when the soil volumetric water content was larger than the critical value (P<0.05). This conclusion was consistent with the existing research results. The appropriate soil volumetric moisture content was about 43%, which could create a suitable environment for respirations of rice roots, soil microbes and so on, and increase soil respiration rate. The results of this paper can support for more comprehensively evaluating the ecological environment effect of rice water-saving irrigation. At the same time, it can be helpful to accurately evaluate the carbon source/sink features of paddy field ecosystem. [ABSTRACT FROM AUTHOR]

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 CH4emission flux and total CH4emission from paddy fields under CI decreased with the increase of percolation rates. Total CH4emissions during the growth stage of rice were 1.83, 1.16, and 1.05 g m−2in the 2, 5, and 8 mm d−1plots, 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−2in the 2, 5, and 8 mm d−1plots, respectively. The seasonal carbon dioxide (CO2) equivalent of CH4and N2O emissions from paddy fields under CI was lowest in the 2 mm d−1plot (1364 kg CO2ha−1). This value was 1.4% and 19.4% lower compared with that in the 5 and 8 mm d−1plots, respectively. The joint application of CI and controlled drainage may be an effective mitigation strategy for reducing the carbon dioxide equivalents of CH4and N2O emissions from paddy fields. [ABSTRACT FROM AUTHOR]

Abstract: Water-saving practices for rice production has become one of the major agricultural policies in China due to the severe water scarcity. However, greenhouse gases emissions from paddy field may be changed with water-saving practices. In the two-year field experiment at Thaihu Lake Basin of China, CH4 and N2O fluxes from paddy field under controlled irrigation and continuous flooding irrigation were monitored using closed chambers. Total CH4 emission from paddy field under controlled irrigation during the rice-growing period were 2.47 and 1.88gm−2 in 2006 and 2007, respectively, reduced by 79.1% on average compared with continuous flooding irrigation. The CH4 emission from paddy field was further concentrated in the initial and middle tillering stages of rice growth under controlled irrigation for 2years. The N2O emission from paddy field under controlled irrigation was mostly larger than those from flooding irrigation during the rice-growing period. Total N2O emission from paddy field under controlled irrigation during the rice-growing period was 106mgm−2, increased by 10.6% compared with those from flooding irrigation. Carbon dioxide equivalents of CH4 and N2O emissions from paddy field during the rice-growing period under controlled irrigation were 788kg CO2 ha−1, reduced by 61.4% compared with those from flooding irrigation. It can be concluded that controlled irrigation is an effective technique for mitigating the carbon dioxide equivalents of CH4 and N2O emissions from paddy field. [Copyright &y& Elsevier]

Coordination of yield, quality and economic benefits increase remains an attractive problem in agricultural production. This study investigated how irrigation regimes could synergistically interact with different fertilization to increase irrigation water use efficiency (IWUE), yield, quality and output/input ratio in rice. A field experiment was conducted during 2020–2021 with three fertilization management (straw returning, organic fertilizer, conventional fertilizer) and two irrigation regimes (controlled irrigation (CI) and flood irrigation (FI)). This study reveals that CI reduced rice plant height (5.24% ∼ 11.99%), tiller number (9.52% ∼ 26.31%), SPAD (7.98% ∼ 15.83%), yield (9.12% ∼ 9.23%), and protein (4.85% ∼ 5.02%) compared to FI. Conversely, CI improved chalky grain rate (5.83% ∼ 8.52%), chalkiness (11.35% ∼ 14.68%), IWUE (51.01% ∼ 59.91%). CS (controlled irrigation + straw returning) and CM (controlled irrigation + organic fertilizer) significantly boosted rice quality and yield compared to CF (controlled irrigation + conventional fertilizer): setting rate increased by 20.23% (CS) and 18.20% (CM), yield rose by 19.43% (CS) and 19.83% (CM), and positive impacts were observed in polished rice rate, head milled rice rate, and protein content. However, both CS and CM led to reduced amylose content (0.35% and 1.06%) and taste value (0.82% and 3.25%). The study observed consistent interannual changes in straw returning, while variations were noted in organic fertilizer application. This difference was primarily attributed to the significant influence of temperature (with a 5.34 ℃ difference during the two years at the milky ripening stage). The analysis of economic benefits showed that the output/input ratio of CS was the highest, ranging from 2.69% to 2.88%. By employing the TOPSIS method, an integrated multi-index decision analysis approach, CS was identified as the optimal mode for rice in southern China. The study provides an optimal irrigation and fertilization model for the synergistic realization of water saving, high yield, high quality, economic benefits, and further achieves the goal of sustainable agricultural development. • Under controlled irrigation (CI), rice growth, yield, appearance and nutritional quality got worse. • CS (controlled irrigation + straw returning) could increase yield, milling, appearance and nutritional quality. • CM (controlled irrigation + organic fertilizer) can promote rice yield and quality, but unstable under climate influence. • The analysis of economic benefits shows that the output/input ratio of CS was the highest. • Using the TOPSIS method, the optimal management mode was determined as CS. [ABSTRACT FROM AUTHOR]

A canopy-resistance-based Penman-Monteith (PM) model’s performance in estimating rice evapotranspiration (ET) under water-saving irrigation (WSI) condition at hourly and daily intervals was evaluated. To improve the performance of Jarvis-type canopy-resistance model in calculating rice ET under water-saving irrigation condition with Penman-Monteith (PM) model, a term of effective leaf area index was used to reflect the influence of canopy coverage condition, and field capacity was replace by saturated soil moisture (θ s ) in soil water response functions due to the specific field moisture condition in WSI rice fields. Two years of hourly rice ET measured using eddy covariance ( ET h EC ) with energy balance closure adjustment served to calibrate (2014 data) and validate (2015 data) a canopy-resistance-based PM model. Results indicate that the PM model’s output ( ET h sim ) with calibrated canopy resistance model parameters closely matched measured ET h EC , with a regression slope, intercept, coefficient of determination (R 2 ), root mean squared error (RMSE) and index of agreement (IOA) of 1.001, 0.010 mm h −1 , 0.942, 0.057 mm h −1 and 0.985, respectively for validation data set in 2015, better than the results calculated by model with parameters calibrated for general paddy field. The improved PM model performed well not only in a dense canopy condition ( LAI > 3) but also for a sparse canopy ( LAI < 3). The model also performed well both in sunny and cloudy days of each rice growth stages. A more detailed analysis indicated that ET h sim tended to overestimate or underestimate ET h EC in varied degrees at noon time or during the transition period from day to night. These differences between ET h sim and ET h EC associated with the variation of net radiation ( Rn ), soil heat flux ( G 0 ), and soil moisture ( θ ). Additionally, the PM model calibrated on hourly dataset, performed well in calculating the daily ET directly under WSI for 2014 ( R 2 = 0.973, RMSE = 0.237 mm d −1 , IOA = 0.993) and 2015 ( R 2 = 0.961, RMSE = 0.302 mm d −1 , IOA = 0.990). Therefore, the PM model calibrated using the hourly data was capable of accurately estimating both hourly and daily ET for rice under WSI condition. [ABSTRACT FROM AUTHOR]

Abstract: Ammonia volatilization (AV) is one of the main pathways of nitrogen (N) loss from a rice paddy, which results in low N use efficiency and many other environmental problems. To reveal AV losses from rice paddies with different combined irrigation and N managements, field experiments were conducted using site-specific nutrient management (SSNM), controlled released nitrogen management (CRN), and non-flooding controlled irrigation (NFI). The interactive effect of N management and irrigation management on AV losses is significant. N management is the dominant management factor of AV losses from a rice paddy. Weekly AV losses followed by fertilization comprise the majority of seasonal AV losses. Ammonium contents in surface water or top soil solutions determine the AV loss rate for both flooding irrigation (FI) and NFI paddies. Moreover, AV losses are less sensitive to surface ammonium nitrogen contents for the NFI paddy than that for the FI paddy. Shallower water condition in the NFI paddy immediately after fertilization may result in higher AV losses than that in the FI paddy in a short term during the first wet–dry cycle after fertilization. However, the following wet–dry cycles result in lower AV losses in most of the rice growth stages. Seasonal AV losses from the NFI paddy using farmers’ fertilization practice (FFP), SSNM, and CRN treatments were 125.27, 37.63, and 23.73kgNha−1, which account for 31.1%, 23.2%, and 13.2% of the seasonal N inputs, respectively. These results were reduced by 14.0%, −17.1%, and 28.7% compared with those from the FI paddy with the same N management. A combination of NFI and CRN is the optimal treatment, with the lowest AV losses and high potential in reducing nutrient leaching risks. Increasing the water depth and the duration of flooding for the first wet–dry cycle after fertilization is a promising measure to reduce AV losses and improve N use efficiency in an NFI paddy. [Copyright &y& Elsevier]

Surface energy distribution in paddy fields and the ratio of latent heat flux (LE) to available energy, termed as the evaporative fraction (EF), are essential for an understanding of water and energy processes. They are expected to vary in different ways in response to changes in the soil moisture condition under water-saving irrigation practice. In this study, the diurnal and seasonal variations in energy distribution were examined based on the data measured by the eddy covariance system and corrected with enforcing energy balance closure by the EF method in water-saving irrigated rice paddies in 2015 and 2016. Soil heat flux (G) values were similar in magnitude to sensible heat flux (Hs) values, with both accounting for approximately 5% of the energy input. Both magnitudes of G and Hs were significantly lower than that of LE. Generally, EF in water-saving irrigated rice paddies was larger than that of other ecosystems, and varied within a narrow range from 0.7 to 1.0. Diurnally, EF decreased till noon and then increased slowly in the afternoon till sunset. It was found be less varied between 10:00 and 14:00. Seasonally, the alternative drying-wetting soil water conditions in water-saving irrigated rice paddies resulted in a change in the variation of the EF. The LE flux is the largest component of available energy, with EF being mostly higher than 0.9. EF, increasing consistently till the tillering stage, remaining high from the late tillering to milk stage, and then following a declining trend. The maximum EF (approaching 1.0) was found in the milk stage. The results of EF in water-saving irrigated rice paddies will be helpful for estimating daily or long temporal scale evapotranspiration (ET) by the EF method based on satellite-derived ET. [ABSTRACT FROM AUTHOR]