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Abstract Biochar application is proposed having a potential of inhibiting greenhouse gases emissions from paddy fields, which is considered to be a main source of atmospheric greenhouse gases. However, the impacts of biochar on greenhouse gases from paddy field have not been investigated under controlled irrigation (CI). Field experiments were conducted during 2016–2017 to determine the effect of biochar application combined with controlled irrigation on rice yield and methane (CH 4) and nitrous oxide (N 2 O) emission from paddy fields in the Taihu Lake Region of China. Four treatments (0 t ha−1 biochar +CI, 20 t ha−1 biochar +CI, 40 t ha−1 biochar +CI, and 40 t ha−1 biochar + flooding irrigation (FI), named CA, CB, CC and FC, respectively) were designed in this study. The results showed that the effect of biochar application on greenhouse gases emissions from paddy fields under controlled irrigation had significant interannual differences. In the first season, CC decreased the global warming potential(GWP) of CH 4 and N 2 O emission, and the CB increased the GWP of CH 4 and N 2 O emission compared to CA, but these differences were not significant. For the second season, CB and CC decreased the GWP of CH 4 and N 2 O emission by 35.7% and 21.5% significantly compared to CA due to the significant mitigation of CH 4 and N 2 O emission. Biochar application significantly increased CH 4 emission and decreased N 2 O emission from paddy fields under flooding irrigation compared to controlled irrigation (CC), which led to the FC's GWP was 1.70 and 5.47 times higher than CC's in the first and second season. In addition, biochar application increased soil organic carbon, dissolved organic carbon and total nitrogen contents of paddy fields under controlled irrigation. And CB and CC increased rice yield by 16.7% and 24.3% and irrigation water productivity by 26.1% and 30.8% compared with CA (mean of two seasons). These results suggest that 20 and 40 t ha−1 biochar can be utilized under controlled irrigation not only for mitigation of CH 4 and N 2 O emission but also to increase rice yield, soil fertility and irrigation water productivity. Therefore, the combination of biochar amendment and controlled irrigation might be a good option for mitigating greenhouse gases emission and realizing the sustainable utilization of soil and water resources of paddy fields in the Taihu Lake Region of China. Highlights • 20 t ha−1 biochar application significantly increased soil DOC, TN, NH 4 +-N and decreased NO 3 −-N concentrations. • Biochar amendments increased rice yield and irrigation water productivity (mean of two rice seasons). • Biochar application combined with controlled irrigation reduced the mean GWP of two rice seasons. [ABSTRACT FROM AUTHOR]

[Display omitted] • DNDC-BC was established on the water balance principle and two-pool biochar model. • DNDC-BC can model GHG, SOC and rice yield of paddy under CI and biochar. • DNDC-BC performed better in simulating GHG and soil moisture than the original one. • Coupling CI and biochar decrease CH 4 and N 2 O emissions, boost SOC and rice yield. • CH 4 and N 2 O emissions from CI paddy are most sensitive to rainfall and irrigation. Simulating the impacts of biochar and controlled irrigation (CI, a water-saving irrigation technology without surface ponding of water) combination on greenhouse gas (GHG) emissions from paddy fields is crucial, however, the original DNDC model is not capable of capturing these management impacts on emissions. In this study, we have created a new modelling approach called DNDC-Biochar-Controlled Irrigation (DNDC-BC) by adding two modules to the original DNDC: the water balance principle, and the two-pool biochar model. The performance of the DNDC-BC was tested and validated using a two-year field experiment, designed with two irrigation treatments (flood irrigation (FI), and CI) and three biochar application rates (0, 20, and 40 t ha−1), carried in the Lake Taihu region, China. Results revealed that the DNDC-BC model performed satisfactorily in simulating impacts of biochar-CI combination on emissions of CH 4 , N 2 O, SOC, and grain yield. The corresponding R2 values of DNDC-BC increased by 22.63%-35.66%, 43.00%-71.26%, 1.06%-60.87% and 15.38%-34.78% compared with those of the original model. Sensitivity analysis for the DNDC-BC showed that CH 4 emissions were most sensitive to rainfall and irrigation; N 2 O emissions were sensitive to rainfall, irrigation and N fertilizer application rate, and SOC was sensitive to biochar application rates. Our results suggest that the combination of biochar- and CI can save water resources and mitigate GHG emissions without detrimental impacts on rice yield. The DNDC-BC can be used to estimate the long-term impacts of biochar-CI combination on GHG emission, crop productivity and climate change. [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]

Yield and rice quality indicators of crops are a direct reflection of the rational irrigation and fertilizer strategy. However, the effects of controlled irrigation (CI) combined with the split application of fertilization managements (straw returning, organic fertilizer, and conventional fertilizer) on rice quality are not clear in southeast China. This study aims at exploring the effects of three fertilization managements applied under CI or flooding irrigation on rice yield, quality, enzyme activity, and soluble sugar content including 43 indicators, to determine the optimal comprehensive evaluation model, management, and representative indexes. The results showed that compared with CF (CI + conventional fertilizer), CS (CI + straw returning) significantly increased yield (27.65%), irrigation water use efficiency (6.20%), chalky grain rate (9.67%), chalkiness (1.83%), protein content (4.29%), and amylose content (0.33%), indicating that CS improved yield and milling quality but decreased cooking and appearance quality. This was mainly because CS promoted the activities of alpha-amylase, ADPG (ADP-glucose pyrophosphorylase), and GBSS (granule-bound starch synthase) and reduced the soluble sugar content in rice. Grey relational degree analysis (GRD), the entropy method (ETM), and TOPSIS (the technique for order preference by similarity to an ideal solution) were used to comprehensively evaluate the rice quality and determined that CS treatments could synergistically improve yield and rice quality. The five indexes (adhesive strength, HPV, ADPG, soluble sugar (leaf), yield) and TOPSIS model can be used as the best indexes and model to evaluate the rice quality. These results could provide scientific management and evaluate practices for high-yield and high-quality rice cultivation, which may be promising for a cleaner production strategy. [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]

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−1to 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. [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]

Guangzhou city in South China has experienced an accelerated urban development since the 1980s. This paper examines the impact of the urban development on urban heat islands through a historical analysis of urban–rural air temperature differences. Remote sensing techniques were applied to derive information on land use/cover and land surface temperatures and to assess the thermal response patterns of land cover types. The results revealed an overriding importance of urban land cover expansion in the changes in heat island intensity and surface temperature patterns. Urban development was also related to a continual air temperature increase in the 1980s and 1990s. The combined use of satellite-derived vegetation and land cover distributions with land surface temperature maps provides a potential useful tool for many planning applications. The city''s greening campaigns and landscaping designs should consider the different cooling effects of forest, shrubs and grassy lawns for temperature control and should plant more tall trees. [Copyright &y& Elsevier]

• WHCNS model performed well in simulating water and N fates in rice systems. • Controlled irrigation greatly reduced irrigation water use and water consumption. • Site-specific N reduced N gas emission, N leaching, and runoff N loss. • Combining controlled irrigation and site-specific N practice enhanced WUE and NUE. Quantifying water consumption, nitrogen (N) fates, and crop yield is crucial in developing the best management practices for rice production systems. A 2-year field experiment was conducted in Taihu Lake region, China. The experiment consisted of water-saving controlled and conventional flooding irrigation regimes that are factorially combined with two N management practices (farmers' N fertilization and site-specific N management). A simple surface ponding water layer component was incorporated into the original WHCNS (soil water heat carbon nitrogen simulator) model to simulate and comprehensively evaluate water consumption, N fates, and rice yield for water-saving and conventional rice production systems. Field experiment data, including surface water ponding depth, soil water content, runoff, runoff N loss, crop N uptake, and yield, was measured to test the improved model. Results showed agreement between the measured and simulated values of surface ponding water depth, soil water content, runoff, N runoff loss, ammonia volatilization, crop N uptake, and yield and simulated values agreed well, with average relative root mean squared error values of 24.0%, 9.3%, 26.1%, 20.9%, 21.3%, 7.9%, and 4.6%, respectively. Crop yield showed no significant difference under different water and N management practices. Compared with conventional flooding system, controlled irrigation saved 34.1% of irrigation water and greatly reduced nonproductive water consumption (evaporation + runoff + deep percolation) by 16.9%–20.0%, thus increasing the water use efficiency (WUE). Site-specific N management substantially reduced N losses from ammonia volatilization, leaching, denitrification, and runoff by 50.1%, 33.8%, 13.3%, and 42.7%, respectively, compared with those of the farmers' N fertilization practice. These results indicated that the combination of controlled irrigation regime and site-specific N management regime reduced the water consumption, N losses, and N 2 O emission and increased WUE and N use efficiency. [ABSTRACT FROM AUTHOR]

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]

While vapor condensation in arid and semiarid areas has garnered much attention, such information is scarce for humid crop production areas such as rice fields. In a water-saving irrigation (WSI) rice field, high-precision weighed microlysimeters allowed the direct and independent quantification of condensation over plants (Cc) and soil (Cs) through mass balance calculations. The occurrence frequency and rate of Cc generally exceeded that of Cs. Predominantly occurring between sunset and sunrise, particularly between 0400 and 0500 local time, Cc showed an overall maximum rate of 0.096 mm h−1. In contrast, Cs was highest between 0100 and 1100 local time and showed an overall maximum rate of 0.044 mm h−1. The occurrence of Cc, unlike that of Cs, required a surface temperature lower than the ambient temperature or dewpoint. Of 65 rain-free days, Cc and Cs occurred on 60 and 33 days, respectively. Seasonal Cc, Cs, and Cc + Cs were estimated as 32.3, 3.1, and 35.4 mm, respectively, and their contributions to seasonal rice transpiration T, evaporation E, and evapotranspiration (ET) were 9.5%, 1.6%, and 6.7%, respectively. The seasonal Cc + Cs was similar in magnitude to a routine irrigation quota and accounted for 10.8% of rainfall and 14.4% of irrigation in the WSI rice field. Therefore, vapor condensation in rice fields in a subtropical monsoon climate is an important component of the hydrological cycle and cannot be ignored when tabulating the field water balance, calculating field water consumption, or in irrigation scheduling. [ABSTRACT FROM AUTHOR]

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 ET0estimation, 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 ET0in 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 ET0estimation 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. [ABSTRACT FROM AUTHOR]

• Variation of energy budget components was used to explain the pattern observed in EF. • The patterns of hourly, daytime and daily EF for WSI rice paddies were examined. • The time-of-day representativeness of EF in estimating daily ET was investigated. • A considerable gap serves in forming a relationship between ET EF,d and ET true,d. • An improved EF up-scaling method is proposed for estimating effective daily ET. Evaporative fraction (EF), which is known to exhibit variation in response to changes in crop species, soil and meteorologic conditions, plays an important role in interpreting the components of energy budget and estimating evapotranspiration (ET), while such information is scarce for humid rice fields. The present study discussed the variation of energy balance components and then examined the pattern of hourly, daytime and daily EF after monitoring energy components by eddy covariance for water-saving irrigated (WSI) rice paddies of 2015 and 2016. Then the daily ET was estimated by an improved EF up-scaling method in the subtropical monsoon climate region of East China. Diurnally, hourly EF is deemed as an approximately concave-up shape in different growth stages of rice season. The seasonal average EF varies gently, with a minimum around 10:00–11:00 AM. Seasonally, the mean daytime EF for the whole growth stage is 0.86, 7% lower than the daily value. Daily EF exhibits mostly higher than 0.8 except later yellow ripening period, approaching 1.0 in the milk stage. EF over WSI rice exhibits obviously greater than the reports that from upland crops. In addition, differences are noted in the results with respect to the daily ET estimation by EF up-scaling method. The estimated daily ET (ET EF,d) from hourly EF during 10:00–11:00 h is highly correlated to the measured ET (ET true) by the weighed micro-lysimeters though the ET EF,d value is underestimated. Such a considerable gap serves in forming a relationship between ET EF,d and ET true,d , that is, by simply multiplying the representativeness ET value based on the EF up-scaling method by a correction procedure calibrated for this region. In conclusion, an improved EF up-scaling method is proposed for extrapolating remote sensing based ET estimates to daily values. [ABSTRACT FROM AUTHOR]