The rapid advancement of jujube industry has produced a large amount of jujube biomass waste, requiring the development of new methods for utilization of jujube resources. Herein, medium-temperature pyrolysis is employed to produce carbon materials from jujube waste in an oxygen-free environment. Ten types of jujube biochar (JB) are prepared by modifying different pyrolysis parameters, followed by physical activation. The physicochemical properties of JB are systematically characterized, and the adsorption characteristics of JB for NO₃⁻ and NH₄⁺ are evaluated via batch adsorption experiments. Furthermore, the pyrolysis and adsorption mechanisms are discussed. The results indicate that the C content, pH, and specific surface area of JB increase with an increase in the pyrolysis temperature from 300 °C to 700 °C, whereas the O and N contents, yield, zeta potential, and total functional groups of JB decrease gradually. The pyrolysis temperature more significantly effects the biochar properties than pyrolysis time. JB affords the highest adsorption capacity for NO₃⁻ (21.17 mg·g⁻¹) and NH₄⁺ (30.57 mg·g⁻¹) at 600 °C in 2 h. The Langmuir and pseudo-second-order models suitably describe the isothermal and kinetic adsorption processes, respectively. The NO₃⁻ and NH₄⁺ adsorption mechanisms of JB may include surface adsorption, intraparticle diffusion, electrostatic interaction, and ion exchange. In addition, π–π interaction and surface complexation may also be involved in NH₄⁺ adsorption. The pyrolysis mechanism comprises the combination of hemicellulose, cellulose, and lignin decomposition involving three stages. This study is expected to provide a theoretical and practical basis for the efficient utilization of jujube biomass to develop eco-friendly biochar and nitrogenous wastewater pollution prevention.

To overcome the difficulty that existing hydrological models cannot accurately simulate hydrological processes with limited information in irrigated paddy areas in southern China, this paper presents a prediction model combining the Ensemble Empirical Mode Decomposition (EEMD) method and the Long Short-Term Memory (LSTM) network. Meteorological factors were set as the multivariate input to the model. Rainfall, regarded as the main variable affecting runoff, was decomposed and reconstructed into a combination of new series with stronger regularity by using the EEMD and K-means algorithm. The LSTM was used to explore the data laws and then to simulate and predict the runoff of the irrigated paddy areas. The Yangshudang (YSD) watershed of the Zhanghe Irrigation System (ZIS) in Hubei Province, China was taken as the study area. Compared with the other models, the results show that the EEMD-LSTM multivariate model had better simulation performance, with an $NSE$ above 0.85. Among them, the $R^2$, $NSE$, $RMSE$ and $RAE$ of the EEMD-LSTM${}^{\left(3\right)}$ model were the best, and they were 0.85, 0.86, 1.106 and 0.35, respectively. The prediction accuracy of peak flows was better than other models, as well as the performance of runoff prediction in rainfall and nonrainfall events, while improving the $NSE$ by 0.05, 0.24 and 0.24, respectively, compared with the EEMD-LSTM${}^{\left(1\right)}$ model. Overall, the EEMD-LSTM multivariations model is suited for simulating and predicting the daily-scale rainfall–runoff process of irrigated paddy areas in southern China. It can provide technical support and help decision making for efficient utilization and management of water resources.

The presence of organic co-substrate in groundwater and soils is inevitable, and much remains to be learned about the roles of organic co-substrates during pyrite-based denitrification. Herein, an organic co-substrate (acetate) was added to a pyrite-based denitrification system, and the impact of the organic co-substrate on the performance and bacterial community of pyrite-based denitrification processes was evaluated. The addition of organic co-substrate at concentrations higher than 48 mg L⁻¹ inhibited pyrite-based autotrophic denitrification, as no sulfate was produced in treatments with high organic co-substrate addition. In contrast, both competition and promotion effects on pyrite-based autotrophic denitrification occurred with organic co-substrate addition at concentrations of 24 and 48 mg L⁻¹. The subsequent validation experiments suggested that competition had a greater influence than promotion when organic co-substrate was added, even at a low concentration. Thiobacillus, a common chemolithoautotrophic sulfur-oxidizing denitrifier, dominated the system with a relative abundance of 13.04% when pyrite served as the sole electron donor. With the addition of organic co-substrate, Pseudomonas became the dominant genus, with 60.82%, 61.34%, 70.37%, 73.44%, and 35.46% abundance at organic matter concentrations of 24, 48, 120, 240, and 480 mg L⁻¹, respectively. These findings provide an important theoretical basis for the cultivation of pyrite-based autotrophic denitrifying microorganisms for nitrate removal in soils and groundwater.

Field experiments and micro test pit experiments are conducted at the Four Lake Watershed with a shallow groundwater table in the Hubei province of China in order to study the effect of controlled pipe drainage on soil moisture and nitrogen under different experiment scales. Soil moisture and nitrogen contents are continuously observed at the effective soil depth; water and nitrogen balance are calculated after several heavy rainfalls. The results showed that controlled pipe drainage significantly reduced the fluctuation of soil water content in the entire growth stage. There is a positive correlation between the soil moisture and the control water level in the test pits but no obvious correlation between them in the field experiments, which is related to the vertical and lateral recharge of groundwater in the field. After rainfall, soil organic matter mineralization was enhanced, and the control pipe drainage measures increased the relative content of soil mineralized ammonia nitrogen, which enhanced the stability of soil nitrogen and helped to reduce the loss of nitrogen. The calculation of soil water and nitrogen balance in the field and micro-area after rainfall showed that the soil water storage increased in the effective soil layer under the control water level of 30 cm and 50 cm after rainfall, and the amount of nitrogen mineralization was larger than that under the free drainage treatment.

The objectives of this study were to clarify the effects of scale on farmland drainage water and the nitrogen and phosphorusload discharged in hilly irrigation areas. An experimental study was conducted to monitor the drainage water volume and nitrogen and phosphorus concentrations at the field, lateral ditch (with a control area of 1.16 km²), branch ditch (with a control area of 7.76 km²), and watershed (with a control area of 43.3 km²) scales in the Yangshudang watershed of the Zhanghe Irrigation District during the rice growth period in 2022. The results showed that from the field scale to the watershed scale, the volume of drainage water, total nitrogen load, nitrate nitrogen load, ammonia nitrogen load, and total phosphorus load per unit area were reduced by 74.6%, 88%, 85%, 87%, and 60%, respectively. The loads of total nitrogen, nitrate nitrogen, ammonia nitrogen, and total phosphorus decreased with the increase of scale, showing a pronounced scale effect; however, the infrequent recharge of ponds and weirs and the insufficient storage capacity of ditches led to an increase in nitrogen and phosphorus concentrations and hence an increase in the load discharge instead, as in the branch ditch scale of this study. The scale effect was mainly caused by the reuse of farmland drainage water; thus, the ability of ponds and weirs, ditches, and reservoirs in hilly irrigation areas to regulate nitrogen and phosphorus concentrations should be improved. Irrigation methods have a significant influence on nitrogen and phosphorus load discharge. The control of farmland non-point sources in hilly irrigation areas should focus on controlling drainage water at the late tillering stage and improving the recharge function of ponds and weirs and the storage capacity of ditches above the branch ditch scale so as to control the concentrations of nitrogen and phosphorus pollutants.

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.