Increased riverine nitrogen (N) concentrations due to human activities is one of the leading causes of water quality decline, worldwide. Therefore, quantitative information about the N exported from watershed to the river (TN exports) is essential for defining N pollution control practices. This paper evaluated the changes in net anthropogenic N inputs (NANI) and the N stored in land ecosystems (legacy N) in the Jianghan Plain (JHP) from 1990 to 2019 and their impacts on TN exports. Moreover, an empirical model was developed to estimate TN exports, trace its source, and predict its future variations in 2020-2035 under different scenarios. According to the results, NANI exhibited a rise-decrease-rise-decrease M-shaped trend, with N fertilizer application being the dominant driver for NANI change. In terms of the NANI components, non-point-source was the primary N input form (96%). Noteworthy is that the correlation between NANI and TN exports became weaker over time, and large differences in changing trends were observed after 2014. A likely cause for this abnormal trend was that the accumulation of N surplus in soil led to N saturation in agricultural areas. Legacy N was also an important source of TN exports. However, the contribution of legacy N has rarely been considered when defining N pollution control strategies. An empirical model, incorporating legacy N, agricultural irrigation water use, and cropland area ratio, was developed. Based on this model, legacy N contributed a large proportion (15-31%). Furthermore, the results of future predictions indicated that legacy N had a larger impact on future TN exports changes compared to other factors, and increased irrigation water would increase rather than decrease TN exports. Therefore, an integrated N management strategy considering the impact of NANI, legacy N, and irrigation water use is crucial to control N pollution in areas with intensive agriculture.
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http://dx.doi.org/10.1016/j.jenvman.2023.117833 | DOI Listing |
Mol Biol Rep
January 2025
Plant Protection and Bimolecular Diagnosis Department, Arid Lands Cultivation Research Institute, City of Scientific Research and Technological Applications, New Borg El-Arab 21934, Alexandria, Egypt.
Background: Heavy metal contamination, particularly from lead (Pb), poses a significant threat to plant agriculture worldwide, adversely affecting growth, physiological functions, and yield. Signalling molecules such as calcium and salicylic acid are known to mitigate various stresses in plants, prompting this study to explore their interaction with Pb stress in wheat.
Methods: A pot experiment was conducted in which wheat grains were primed with either distilled water, 5 mM calcium (Ca), or 0.
Mar Pollut Bull
January 2025
College of Environmental Science and Engineering, Nankai University, Tianjin 300350, PR China.
Seawater intrusion and human activities have significantly impacted coastal groundwater quality in many regions worldwide. This study systematically assessed groundwater chemistry, its suitability for drinking and irrigation (sample size, n = 3034), and exposure risks (n = 2863) across three key sub-regions of the Bohai Sea area: Bohai Bay, Liaodong Bay, and Laizhou Bay. Significant seasonal variations observed in groundwater chemistry at different depths in Bohai Bay region, with severe contamination from salinity-alkalinity and nitrogen-fluoride.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Earth and Environmental Sciences, California State University, Fresno, CA, United States of America.
Rice-crab co-culture is an environmentally friendly agricultural and aquaculture technology with high economic and ecological value. In order to clarify the structure and function of soil and water microbial communities in the rice-crab symbiosis system, the standard rice-crab field with a ring groove was used as the research object. High-throughput sequencing was performed with rice field water samples to analyze the species and abundance differences of soil bacteria and fungi.
View Article and Find Full Text PDFPLoS One
January 2025
School of Civil and Architectural Engineering, Harbin University, Harbin, China.
This work explores an intelligent field irrigation warning system based on the Enhanced Genetic Algorithm-Backpropagation Neural Network (EGA-BPNN) model in the context of smart agriculture. To achieve this, irrigation flow prediction in agricultural fields is chosen as the research topic. Firstly, the BPNN principles are studied, revealing issues such as sensitivity to initial values, susceptibility to local optima, and sample dependency.
View Article and Find Full Text PDFEnviron Sci Pollut Res Int
January 2025
Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun, 248007, India.
This study provides a detailed approach to evaluating water quality in the Haridwar district, Uttarakhand, India, by integrating physicochemical and microbiological investigations. It employs multivariate analysis and applies water quality and trophic state indices to evaluate the current state of the water and identify potential sources of contamination. The results from the correlation matrix highlight the dynamic interactions between different water quality parameters.
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