Quantifying the Spatial Distribution of Soil Nitrogen under Long-Term Drip Fertigation

• Main Authors: Bi, X. (Author), Bi, Y. (Author), Chen, Y. (Author), Hou, L. (Author), Liao, R. (Author), Wang, L. (Author), Wu, W. (Author)
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: Drip irrigation; Fertigations; Fractals; Irrigation; long-term drip fertigation; Long-term drip fertigation; Multifractal analysis; multifractal theory; Multifractal theory; Nitrate-N; Nitrates; Nitrogen; soil nitrogen; Soil nitrogen; Soil sample; Soil surveys; Soils; Spatial distribution; Spatial heterogeneity; spatial variation; Spatial variations
• Online Access: View Fulltext in Publisher

 Quantifying the spatial distribution of nitrogen (N) in the soil under long-term drip fertigation events is essential for the optimal regulation of drip fertigation systems. In this study, a greenhouse soil that had been under drip irrigation for 20 years was selected as the research object, and soil samples were collected from the 0–50 cm soil depth. The concentrations of N in the soil samples were measured and their spatial distribution characteristics were quantified by classical statistical analysis and multifractal analysis. The results showed that long-term drip fertigation and the influence of natural factors resulted in the nitrate N mainly accumulating in the shallow layer of the soil and within a distance from the drip irrigation belt, and the spatial heterogeneity gradually decreased with increasing depth. The content of ammonium N was low, and its distribution was observed in the whole section. Multifractal analysis indicated that the ∆α value of nitrate N and inorganic N gradually increased with the increase in the research scale, i.e., the spatial heterogeneity gradually increased, and it did not appreciably change for ammonium N. Meanwhile, the local high value region was the main factor leading to the spatial heterogeneity of N, and this dominant effect gradually increased with increasing depth. Multifractal analysis can effectively reflect the local information of the N spatial distribution in the soil and provide a more detailed description of the spatial heterogeneity of soil properties. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.