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【Objective】 Brackish waters including saline groundwater and treated wastewater have been increasingly used as a complimentary irrigation water resource in regions where freshwater is scarce. In the paper we investigate the effect of various concentrations of saltine irrigation water on photosynthetic characteristics of winter jujube. 【Method】 The experiment was conducted in 2020 in a jujube orchard, with the winter jujubes irrigated by mixtures of saltine groundwater and freshwater at concentrations of 1 (S1), 2 (S2), 3 (S3), 4 (S4) and 5 g/L (S5), respectively. In each treatment, we measured the spaciotemporal changes in soil water and salt, as well as the photosynthetic traits of the jujubes. 【Result】 Net photosynthetic rate, transpiration and stomatal conductance of the plant leaves varied with irrigation salinity nonlinearly, all peaking in S3 or S4. Compared with other treatments, S3 and S4 reduced the SPAD, maximum fluorescence and maximum quantum efficiency significantly. Compared to S1, S3 and S4 increased the apparent quantum efficiency, maximum net photosynthetic rate, light compensation point, and dark respiration rate, but reduced the light saturation point. These indicate that, although S3 and S4 reduced the range of available light intensity, they improved the physiological activity and efficient photosynthesis of the jujube leaves. 【Conclusion】 Irrigating the winter jujubes with saline water at concentration of 1-3 g/L during the fruit enlargement period can prevent light reaction inhibition and promote efficient photosynthesis. However, irrigation with water salinity exceeding 4 g/L led to salinity stress, thereby significantly reducing light energy utilization efficiency. To minimize soil salt accumulation and improve growth and development of the winter jujube, maintaining irrigation water salinity around 3 g/L is most beneficial.

【Objective】 To explore reasonable water and nitrogen management practices in the main winter wheat producing areas of North China. 【Method】 A field experiment was carried out at the Irrigation Experiment Centre Station of Shandong Province from 2020 to 2021 using "Qimai No.1" wheat as the material. Four irrigation treatments were set up, with the upper and lower limits of irrigation at 60%-70% (W1), 70%-80% (W2), 80%-90% (W3) and no irrigation (CK) of the field water holding capacity, and the application rate of nitrogen was 240 kg/hm2. The data from the experiments were used to determine the rate of the parameters of the RZWQM 2 model and to validate the model, and the model was applied to simulate the effects of the water and nitrogen regulation on the accumulation of soil nitrate nitrogen and nitrogen use. The model was used to simulate the effects of water and nitrogen regulation on soil nitrate nitrogen accumulation and nitrogen utilisation. 【Result】 The results showed that the standard root mean square errors (NRMSE) of soil profile water content, soil nitrate nitrogen amount and yield ranged from 9.3% to 25.0%, 0.3% to 29.7% and 4.03% to 11.19%, respectively, and the mean relative errors (MRE) ranged from 8.0% to 24.2%, 1.4% to 30.4%, and 5.29% to 11.98%, respectively, with consistency index D were all higher than 0.65; using the corrected RZWQM 2 model, five nitrogen levels (180, 200, 220, 240 kg/hm2and 260 kg/hm2) were set at W1, W2 and W3 moisture measurement and recharge levels, and the soil nitrate nitrogen accumulation produced at the W2 and W3 levels was increased by 30.9%-59.7% and 49.6%-79.6%, respectively, compared with the W1; The simulation concluded that N application of 220-240 kg/hm2 and W2 levels were more favourable for soil nitrate N accumulation in the 0-1 m soil layer, with accumulation of 108.30-125.10 kg/hm2. Nitrogen uptake efficiency and nitrogen fertilizer bias productivity of N application of 220 kg/hm2 and W2 levels were 59% and 23.4 kg/kg, respectively. 【Conclusion】 In conclusion, the RZWQM 2 model can be used to simulate soil nitrate nitrogen accumulation and nitrogen utilisation in the main production area of winter wheat in North China, and moisture supplemental irrigation W2 and nitrogen application of 220-240 kg/hm2 are more reasonable water and nitrogen management measures in this area.

【Objective】 The Xiaoqing River is located in Shandong province. In this paper, we analyze the contaminants in its estuary and assess its water quality. 【Method】 We selected the section from Shicun to Yangjiaogou for analysis. Water quality was evaluated based on data measured from 2019 to 2021 from four water sampling locations in the section. The main pollutants in the locations were analyzed using the principal component analysis method; we also analyzed the origin of these pollutants. 【Result】 Water quality in sampling locations in the section had improved from 2019 to 2021, with the water quality level changing to Class IV in 2021. The pollutants that exceeded the standard at these locations are total nitrogen (TN), of which nitrate (NO3-) is the main pollutant. NO3- at Shicun was affected by both non-point pollution and domestic sewage, while the origin of NO3- at Houxinzhuang was sewage and manure. Meteorological factors such as temperature and rainfall had indirect affect in water quality in the estuary. 【Conclusion】 The comprehensive water quality identification index combined with the combinatorial integration method is accurate for assessing water quality. The main pollutants in the estuary of Xiaoqing River are total nitrogen, especially nitrate.

Water resources are basic natural and economic resources of strategic significance and are vital for the high-quality agricultural development and ecological protection of the Yellow River Basin. To implement the national strategy of ecological protection and high-quality development in the Yellow River Basin, it is significant to improve the use efficiency and allocation of water resources in the basin. This study focuses on the high-efficiency utilization and sustainable development of agricultural water resources, adopts the research methods of systematic hydrology, and adheres to an all-encompassing approach to food. Based on the theories and technologies for the optimal allocation of water resources in the process of high-quality agricultural development, it explores the mechanism for the hydrologic process of farmlands and investigates the challenges faced in terms of water use efficiency improvement, optimal allocation of agricultural and ecological water resources, collaborative optimization of water, food, and ecosystem, and construction of farmland information systems. Countermeasures are further proposed. This study reviews the agricultural water-saving and water resource allocation capabilities of the whole Yellow River Basin from a water cycle perspective and is expected to provide basic support for the optimal allocation of land and water resources, high-quality agricultural development, and ecological protection collaboration in the Yellow River Basin.

The escalating focus on environmental concerns and the swift advancement of eco‐friendly biodegradable batteries raises a pressing demand for enhanced material design in the battery field. The traditional polypropylene (PP) that is monopolistically utilized in the commercial LIBs is hard to recycle. In this work, we prepare a novel water degradable separators via the cross‐linking of polyvinyl alcohol (PVA) and dibasic acid (tartaric acid, TA). Through the integration of non‐solvent liquid‐phase separation, we successfully produced a thermally stable PVA‐TA membrane with tunable thickness and a high level of porosity. These specially engineered PVA‐TA separators were implemented in LiFePO4 (LFP)|separator|Li cells, resulting in superior multiplicative performance and achieving a capacity of 88 mAh g−1 under 5 C. Additionally, the straightforward small molecule cross‐linking technique significantly reduced the crystalline region of the polymer, thereby enhancing ionic conductivity. Notably, after cycling, the PVA‐TA separators can be easily dissolved in 95 °C hot water, enabling its reutilization for the production of new PVA‐TA separators. Therefore, this work introduces a novel concept to design green and sustainable separators for recyclable lithium batteries. [ABSTRACT FROM AUTHOR]

One of the primary factors in the hydrological cycle is reference evapotranspiration (ET0). The prediction of ET0 is crucial to manage irrigation water in agriculture under climate change; however, little research has been conducted on the trends of ET0 changes in Shandong Province. In this study, to estimate ET0 in the entire Shandong Province, 245 sites were chosen, and the monthly ET0 values during 1901–2020 were computed using the Hargreaves–Samani formula. A deep learning model, termed SAO-CNN-BiGRU-Attention, was utilized to forecast the monthly ET0 during 2021–2100, and the predictions were compared to two CMIP6 climate scenarios, SSP2-4.5 and SSP5-8.5. The hierarchical clustering results revealed that Shandong Province encompassed three homogeneous regions. The ET0 values of Clusters H1 and H2, which were situated in inland regions and major agricultural areas, were the highest. The SAO-CNN-BiGRU-Attention and SSP5-8.5 forecasting results generally displayed a monotonically growing trend during the forecast period in the three regions; however, the SAO-CNN-BiGRU-Attention model displayed a declining tendency at a few points. According to the SAO-CNN-BiGRU-Attention and SSP5-8.5 results, during 2091–2100, H1, H2, and H3 will reach their peaks; the SSP2-4.5 results show that H1, H2, and H3 will peak in 2031–2040. At the end of the forecast period, for Clusters H1, H2, and H3, the prediction rate of SAO-CNN-BiGRU-Attention increased by 1.31, 1.56%, and 1.80%, respectively, whereas SSP2-4.5's prediction rate increased by 0.31%, 0.95%, and 1.57%, respectively, and SSP5-8.5's prediction rate increased by 10.88%, 10.76%, and 10.69%, respectively. The prediction results of SAO-CNN-BiGRU-Attention were similar to those of SSP2-4.5 (R2 > 0.96). The SAO-CNN-BiGRU-Attention deep learning model can be used to forecast future ET0. [ABSTRACT FROM AUTHOR]

Copper (Cu2+) is a metal chemical element closely related to human life and is widely used in many fields. However, with the discharge of copper wastewater, the water quality will be seriously affected, leading to excessive intake of Cu2+ and a variety of diseases. Hence, there is a pressing need for an effective detection method for Cu2+ in aqueous environments. Leveraging the remarkable attributes of GFP chromophores and indenone derivatives, we have created a novel colorimetric fluorescent probe P‐Cu2+, tailored for efficient copper ion detection. The addition of Cu2+ causes the solution to visibly change from colorless to a pronounced yellow, enabling naked‐eye detection and offering promise for real sample analysis. [ABSTRACT FROM AUTHOR]