Multifractal Analysis of Temporal Variation in Soil Pore Distribution
Soil structure, a critical indicator of soil quality, significantly influences agricultural productivity by impacting on the soil’s capacity to retain and deliver water, nutrients, and salts. Quantitative study of soil structure has always been a challenge because it involves complex spatial-tempora...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/15/1/37 |
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| Summary: | Soil structure, a critical indicator of soil quality, significantly influences agricultural productivity by impacting on the soil’s capacity to retain and deliver water, nutrients, and salts. Quantitative study of soil structure has always been a challenge because it involves complex spatial-temporal variability. This study employs multifractal analysis to assess the temporal variation in soil pore distribution, a pivotal factor in soil structure. Field observation data were collected in a sandy loam area of the People’s Victory Canal Irrigation scheme in Henan Province, China. A 200 m × 200 m test plot with five sampling points was used to collect soil samples at three depth layers (10–30 cm, 30–50 cm, and 50–70 cm) for soil water retention curve and particle size composition analysis, with a total of seven sampling events throughout the growing season. The results revealed that while soil particle-size distribution (Particle-SD) showed minor temporal changes, soil pore-size distribution (Pore-SD) experienced significant temporal fluctuations over a cropping season, both following a generalized power law, indicative of multifractal traits. Multifractal parameters of Pore-SD were significantly correlated with soil bulk density, with the strongest correlation in the topsoil layer (10–30 cm). The dynamic changes in soil pore structure suggest potential variations during saturation–unsaturation cycles, which could be crucial for soil water movement simulations using the Richards equation. The study concludes that incorporating time-varying parameters in simulating soil water transport can enhance the accuracy of predictions. |
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| ISSN: | 2073-4395 |