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【Objective】 Agriculture is responsible for 8.5% of greenhouse gasses emitted to the atmosphere. Improving agricultural management and reducing gas emissions from soils is hence important in the fight against global warming. In this paper, we investigate the effect of different irrigation and fertigation on reducing nitrogen losses from rice fields in Poyang Lake Basin in southern China. 【Method】 The field experiment was conducted at the Ganfu Plain Irrigation Area located at the Irrigation Experiment Center Station of Jiangxi Province. It consisted of an intermittent irrigation (W1) and a flooding irrigation (W0), each irrigation treatment had three nitrogen fertilizations: no fertilization (N0), fertilizing 135 kg/hm2 (N1), and 180 kg/hm2 of nitrogen (N2). Rice growth, its associated water use efficiency, and nitrogen emissions from each treatment were measured during the experiment. 【Result】 Irrigation impacted water consumption and leakage. Compared with W0, W1 reduced irrigation water usage by 18.12%~28.37%, water leakage by 13.68% to 22.85%, and saved water by 28.77%. Depending on nitrogen application, W1 treatments increased the average yield by 16.57% to 29.94% and reduced average nitrogen emissions by16.42%, compared to the W0 treatments. Increasing nitrogen fertilization led to an increase in nitrogen emission when the irrigation was the same; fertilization had a significant effect on ammonia volatilization. Irrigation-fertilization did not show a significant interactive impact on ammonia volatilization. 【Conclusion】 The optimal irrigation and fertilization for rice production in Poyang Lake Basin was intermittent irrigation coupled with fertilizing 135 kg/hm2 of N. Compared to W0+N2 - flooding irrigation with 180 kg/hm2 of nitrogen fertilization, the optimal irrigation and fertigation can increase rice yield by 9.82%, reduce irrigation amount, nitrogen pollution and nitrogen emissions by 27.54%, 25.67% and 11.90%, respectively.

【Objective】 Ammonia volatilization is a pathway of nitrogen cycling in soil. It is mediated by various biotic and abiotic processes. The objective of this paper is to study its variation and determinants in irrigated midseason rice fields in southern China plains. 【Method】 The field experiment was conducted in an irrigation experimental station in Jiangxi province. It consisted of two irrigation methods: intermittent irrigation (W1) and traditional flooding irrigation (W0), and three nitrogen fertilizations: 0 (N0), 135 kg/hm2 (N1), 180 kg/hm2 (N2). We measured the ammonia volatilization from each treatment and analyzed its correlation with different meteorological factors. 【Result】 When irrigation was the same, increasing nitrogen fertilization increased ammonia volatilization, while when nitrogen fertilization was the same, ammonia volatilization was less in flooded irrigation than in intermittent irrigation. Ammonia volatilization occurred mainly in the tillering, jointing and heading stages, the total ammonia volatilization during which accounted for more than half of the total ammonia volatilization in the whole growth season. Among the meteorological factors, sunshine duration positively impacted ammonia volatilization the most, followed by wind speed and evaporation but their influence was negative. 【Conclusion】 Compared with traditional flooding irrigation, intermittent irrigation increased ammonia volatilization, especially in early and middle stages of the growth season. Ammonia volatilization was positively correlated with sunshine duration and negatively with wind speed and evaporation.

Against the backdrop of growing worldwide attention towards environmental, social, and governance (ESG) considerations, this study investigates how ESG performance affects the probability of stock price crashes. The research explores samples of Chinese A‐share listed companies during the period from 2010 to 2019. The outcomes indicate that commendable ESG performance lowers the likelihood of stock price crashes, and these results persist robust even after executing a series of robustness and endogeneity examinations. Moreover, the available evidence indicates that good ESG performance mitigates the risk of stock price crashes by curbing both earnings management and corporate risk. However, the positive influence of good ESG performance on reducing the risk of stock price crashes diminishes when analyst coverage increases. Furthermore, the heterogeneity analysis infers that the effect of good ESG performance in reducing stock price crash risk is more significant for non‐state companies. Heightened economic policy uncertainty weakens the effect of good corporate ESG performance in mitigating stock price crash risk. Of the three ESG performance dimensions—environmental, social, and corporate governance—the latter is the most effective in lessening such risks. This research carries notable implications for reinforcing the ESG disclosure arrangement in China and other developing economies. It also guides government institutions and regulators in the creation of policies that foster high‐calibre economic progress. [ABSTRACT FROM AUTHOR]

A experiment was conducted at the Jiangxi Province Center Station of Irrigation Experiment from 2019 to 2021 to study the water and nitrogen balance under water and fertilizer regulation modes. The study aimed to propose a recommended mode for paddy fields that could save water, control pollution, reduce gas emission, and improve fertilizer use efficiency. This study examined the impact of different irrigation methods and nitrogen application levels on water saving and emission reduction in paddy fields. The experiment included six treatments, which involved two irrigation methods (intermittent irrigation and flooding irrigation, referred to as W1 and W0, respectively) and three application rates of nitrogen fertilizer (0 kg/ha, 135 kg/ha, 180 kg/ha, referred to as N0, N1 and N2, respectively). The study found that irrigation methods had a significant effect on the amount of irrigation, drainage, leakage, nitrogen load from drainage, soil nitrification potential, and ammonia volatilization. The results showed that compared to flooding irrigation, intermittent irrigation reduced the amount of irrigation, drainage, leakage and nitrogen load from drainage by an average of 25.98%, 16.03%, 8.43% and 10.86%, respectively. However, the study also found that the nitrification potential and ammonia volatilization increased by an average of 6.45% and 4.32%, respectively. Fertilization levels had a significant effect on drainage nitrogen load, early soil nitrification potential and ammonia volatilization. Compared with the treatment of N2 (180 kg N/ha), the drainage nitrogen load under the treatment of N1 (135 kg N/ha) decreased by 10.86% on average, while nitrification potential and ammonia volatilization increased by 38.74% and 3.33%, respectively. In terms of nitrogen output, the amount of nitrogen absorbed by crops was the largest, followed by the nitrogen load from field drainage, then ammonia volatilization, and then denitrification. Considering the goals of water saving, emission reduction, and the efficient utilization of water and fertilizer in paddy fields, the optimal water and fertilizer regulation mode was the W1N1 mode (intermittent irrigation combined with reduced nitrogen fertilizer application rate, 135 kg N/ha). [ABSTRACT FROM AUTHOR]

Polydisperse particles are ubiquitous in both the natural and engineered environment, and the precise prediction of the transport and capture of polydisperse particles in a saturated medium is crucial. Several efforts (Yao model, RT model, TE model, MPFJ model, NG model, MHJ model, and MMS model) were developed to obtain accurate correlation equations for the particle capture probability (single-collector removal efficiency), but the applicability of the existing models to the entire porous medium and the retention characteristic of the polydisperse particles are still unclear. In this study, sand column experiments were undertaken to investigate the transport and capture processes of the polydisperse particles in the saturated medium. The mass density was employed to quantize the effects of particle polydispersity and incorporated into the depth-dependent deposition rate. The experimental results showed that the polydisperse particles formed a hyper-exponential retention profile even under favorable conditions (no repulsion). The excellent agreement between the results obtained from the MMS model and the experimentally observed results of the breakthrough curves (BTCs), as well as the retention profiles demonstrated the validation of the MMS model, as the correlation coefficient and the standard average relative error were 0.99 and 0.005, respectively. The hyper-exponential retention profile is caused by the uneven capture of the polydisperse particles by the porous medium. This study highlights the influences of particle polydispersity on particle transport and capture in a saturated porous medium. [ABSTRACT FROM AUTHOR]

In order to study the effects of submergence and waterlogging on cotton yield, submergence and waterlogging experiments in lysimeters of three stress forms with different degrees and different growth stages were conducted in the Irrigation and Drainage Experiments Station of Wuhan University from 2008 to 2011. Three stress forms with different degrees included submergence for 1-3 days, waterlogging for 3-8 days, and submergence for 1-5 days followed by waterlogging for 3-8 days. The experiment was performed in 3 cotton growth stages: budding, flowering and boll opening stage. In this study, 2 types of drainage indexes including sum of flood depth and excess soil water under submergence (SWFDH), sum of excess soil water under waterlogging ( SEW30), sum of flood depth under submergence (SFW) and sum of excess soil water under submergence and waterlogging (SEW30), were used to quantify stress degrees of submergence and waterlogging. The effects of submergence and waterlogging on cotton yield were quantified by yield reduction rate factors (YR) of each stress forms, and thus weight factor of waterlogging was determined. The responses of three growth stages to submergence followed by waterlogging were quantified by YR of each growth stages, and thus generalizing yield reduction rate factors (NYR) of three growth stages were estimated. Based on NYR and weight factor of waterlogging, a new drainage index cumulative sum of flood depth and excess soil water (CSFEW30) was put forward. The results showed that the drainage indexes, SWFDH and SEW30, could well describe the relationship between the degree of submergence and waterlogging with yield reduction more stably than SFW and SEW30 in different years. The yield reduction rate factors of submergence and waterlogging were 0.266%/(cm∙d) and 0.202%/(cm∙d), respectively. Yield reduction under waterlogging was 0.759 times that under submergence. Without considering the effect of submergence on yield reduction of following waterlogging, the calculated yield reduction would be 43.1% higher than the actual yield reduction. And when the effect was taken into account, the yield reduction of waterlogging was 0.293 times as much as that of submergence. Flowering stage was the most insensitive growth stage for cotton under submergence and waterlogging, followed by budding stage and boll opening stage. Yield reduction rate factors of three growth stages are 0.114%/(cm∙d), 0.150%/(cm∙d) and 0.033%/(cm∙d), respectively, and thus the proportion of yield reduction in the three stages was 0.760:1:0.220. Without considering the effects of submergence and waterlogging in former growth stages on yield reduction in latter stages, the calculated yield reduction would be 8.8% higher than the actual yield reduction. The effects of submergence and waterlogging on yield in former stages would extend to latter stages slightly. Drainage index CSFEW30 was of highly significant (R²=0.629, n=15, P<0.001) linear relationship with yield reduction, which provides evidence for the determination of drainage standard of cotton under the submergence and waterlogging control. [ABSTRACT FROM AUTHOR]

Flood disaster occurs frequently in China and brings severe disaster to crops. Therefore, the crop plant structure in seasons prone to waterlogging becomes significant information for studies on flood loss, flood control, and disaster mitigation. Under these conditions, this paper presents a fast and convenient method to extract the crop plant structure in small scale areas during seasons prone to waterlogging, based on multi-sensor and multi-temporal remote sensing data. Landsat8 OLI and MODIS data were chosen because of the advantages such as it being free of charge and easy to search for and download. These two types of data showed the characteristics of crops' growth respectively in space and time, leading to a proper combination for crop planting structure extraction. If one only uses MODIS data to build the extraction model, the spatial resolution is too low to get the planting structure in small scale areas. On the other hand, just classifying the OLI images by visual interpretation sometimes could not determine the types of crops. The Jianli County in Jingzhou City, Hubei Province was chosen as the study area. The seasons prone to waterlogging in Jianli mainly include June, July, and August, and are related to crops such as early-season rice, middle-season rice, late rice, and cotton. Here are the extracting models for the four major kinds of crops: NDVI value of cotton grows to the peak in early July and stays high until September; early-season rice NDVI maximum value appears in middle June, and it becomes completely mature in late July; middle-rice NDVI value starts to increase at the end of May and reaches its peak in early or middle July before falling to a decline; NDVI value of late rice goes up in mid-July and the peak value appears in middle or late August, and then the value begins to decline. First, a time series curve of NDVI was built from the MODIS data, which was later smoothed by an improved Savitzky-Golay filter. The improved Savitzky-Golay filter reserved the authenticity of data at both ends of the NDVI time series while further improving the smoothness of the curve. To distinguish the types of crops, threshold values of NDVI for different crops were set according to corresponding phenophases. Based on the characteristics and threshold values of NDVI time series, appropriate ROIs (Region of Interest) in the Landsat8 OLI images in key growth stages of different crops were selected as prior knowledge for training. Finally, the area and distribution of the four studied crops were extracted by a BP Neural Net Supervised Classification. The experimental results agreed well with the statistical data and a ZY-3 image which had a spatial definition of 6 meters, and obtained an average precision above 90%. It was concluded that the proposed method in this paper is simple and easy operating. Moreover, it accurately reflected the real situation of crop distribution in the Jianli area, and is suited for extraction of the plant structure in small scale areas like Jianli. Therefore, this method provides a reliable basis for related research studies on flood disaster. [ABSTRACT FROM AUTHOR]

Drainage modulus is the rate of water removal per unit of area used in drainage design. Reasonable drainage modulus is of great importance for waterlogging control. With the urbanization in tidal river networks, more and more impermeable areas are gradually replacing original permeable areas, thus changing the rainfall-runoff process of drainage areas. Different from rural areas, storm water in urban areas is collected by drainage pipe network,routing storm water runoff directly to main pipes or channels, causing less infiltration, but more overland runoff. Urbanization, with the loss of vegetation and replacement of soil with impervious surfaces, makes traditional computing methods of drainage modulus inadequate for urbanized areas. While inland river stage is affected by tidal backwater in tidal river networks, waterlogging risks increase. Based on the characteristics of urbanized drainage areas in tidal river networks, a two-layer computing model of drainage modulus was built. In the model, the catchment of first layer was divided into two sub-drainage areas, urban and rural, which adopted SWMM and Guangzhou comprehensive unit hydrograph method to establish rainfall-runoff models, respectively. On the second layer, based on their shared drainage channels (rivers), a river networks dynamic model was established by MIKE11 HD. Lateral inflows of rainfall runoff were derived from the simulated data of first layer, coupled with MIKE11 HD. Using the Dagang drainage area as a case study, the impact of urbanization on drainage modulus was studied through this two-layer computing model of drainage modulus. Drainage modulus under different designed rainstorm in 2003 and in 2012 was calculated. The relationship between drainage modulus and return periods under different underlying surface condition in 2003 and 2012 was analyzed. Results showed that due to the increasing ratio of urban area from 9.69% to 24.25% from year 2003 to 2012, drainage modulus under design standards with return period of 20 years increased from 1.766 m3/(s·km2) to 2.808 m3/(s·km2), drainage modulus under design standards with return period of 30 years increased from 2.909 m3/(s·km2) to 4.197 m3/(s·km2), which showed that the resistibility of waterlogging was weakening. When drainage modulus reached the 1.766 m3/(s·km2), the drainage area can meet design standards with return periods of 20 years in 2003, but it can only satisfy design standards with return periods of about 15 years in 2012. When drainage modulus reached the 2.909 m3/(s·km2), the drainage area can meet design standards with return periods of 30 years in 2003, but it was not able to satisfy design standards with return periods of about 20 years in 2012, which showed that waterlogging control standards of the study area was reduced in the process of urbanization. The result of this study may provide a reference for computing drainage modulus and help determine a reasonable value of drainage modulus for drainage engineering design in tidal river networks of urbanized areas. [ABSTRACT FROM AUTHOR]