Modeling water movement in horizontal columns using fractal theory

Leão, Tairone Paiva; Perfect, Edmund

doi:10.1590/s0100-06832010000400042

Cited by 6 publications

(4 citation statements)

References 13 publications

(16 reference statements)

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“…The Philip's infiltration model parameters such as sorptivity 'S' values were found in the range of 0.167-0.288 cm/min 1/2 and conductivity constant 'A' values were obtained as -0.001 to -0.009 cm/min for all the six points. The estimated values for sorptivity 'S' were in close agreement to the values as reported by Leao and Perfect [52] . Azuka et al [53] described the high variability of these parameters along the toposequence.…”

Section: Models Estimated Parametersupporting

confidence: 89%

Estimation of infiltration models parameters and their comparison to simulate the onsite soil infiltration characteristics

Farid

Mahmood-Khan

Ahmad

et al. 2019

International Journal of Agricultural and Biological Engineering

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Detailed knowledge about soil characteristics and site-specific final steady infiltration rate could help to increase the irrigation water use efficiency and decrease water losses in agricultural system. The experiments were conducted on Agricultural Research Farm of Bahauddin Zakariya University, Multan, Pakistan during 2016. The cumulative infiltration depth was measured using double ring infiltrometer at selected six points of the study area. Most commonly used infiltration models such as Kostikov's, Philip's and Horton's were fitted to the field infiltration data for determination of model parameters and to find the best fit model for the study area. Kostikov's infiltration model's parameters such as empirical constant 'c' and infiltration decay constants 'k' were obtained in the ranges of 0.140-0.290 and 0.307-0.433, respectively. Philip's infiltration model's parameters such as sorptivity 'S' and conductivity constant 'A' were found in the ranges of 0.167-0.288 cm/min 1/2 and-0.001 to-0.009 cm/min, respectively. Similarly, the Horton's model's 'parameter 'k' was obtained in the range of-1.619 to-1.238. The value of infiltration capacity at onset of infiltration (fo) was obtained as 1.744 to 3.491 for all the six points. The analysis showed that the infiltration models using the estimated parameters have satisfactory prediction capability at all the selected points. Horton's model provided the lowest mean values for RMSE (0.235) and highest mean values for ME (94%); and the lowest mean values for MPD (0.127). This indicated that infiltration can be well-described by the Horton's model at the selected site.

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Section: Models Estimated Parametersupporting

confidence: 89%

Estimation of infiltration models parameters and their comparison to simulate the onsite soil infiltration characteristics

Farid

Mahmood-Khan

Ahmad

et al. 2019

International Journal of Agricultural and Biological Engineering

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“…From a non-fractal aspect, the position of any water content inside a porous medium column can be determined by the following equation (Leão & Perfect, 2010):…”

Section: Fractal Dimension Of Infiltration Curvementioning

confidence: 99%

“…The Hurst exponent is related to the time exponent (n). Hence, D I can be obtained as (Leão & Perfect, 2010):…”

Section: Fractal Dimension Of Infiltration Curvementioning

confidence: 99%

“…Also, the infiltration rates in the initial, transitional and stable phases were different among considered land uses. Leão and Perfect (2010) presented two fractal dimensions for the infiltration process from the Hurst exponent and the horizontal distribution of the first four iterations of a deterministic Cantor Bar. Chari and Dahmardeh Ghaleno (2019) presented a linear relationship between the fractal dimension of PSD and the fractal dimension of the soil water retention curve.…”

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Fractal analysis of the infiltration curve and soil particle size in a semi‐humid watershed

Omidvar

2020

European J Soil Science

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Although fractal mathematics has been commonly used to quantify particle size distribution (PSD), limited attention has been paid to the fractal dimension of the infiltration curve (D I ). Therefore, it is necessary to determine whether the D I and fractal dimensions of PSD (D m , D clay , D silt and D sand ) can reflect the infiltration process, and soil erodibility and degradation. Accordingly, this study aimed to provide new information on the quantification of infiltration processes, and soil erodibility and degradation, using D I and D m in the Soorak basin in the northern part of Iran. The soil and infiltration properties were calculated by field and laboratory practices on 46 topsoil samples and 34 infiltrometer double-ring tests. Correlation, regression and redundancy analysis (RDA) were used to identify relationships between the infiltration curve and PSD coordinates with soil and infiltration properties. Results indicated that the D I was significantly linearly correlated with other infiltration curve characteristics, with the correlation coefficient ranging from −0.737 to −0.403 (sig. = 0.000-0.037). However, there was no significant correlation between D I and D m , D clay , D silt and D sand . Different erodibility factors, especially K USLE , had significant relations with D m , D clay , D silt , D sand and D I (p < .01), suggesting that these fractal dimensions are indicators of soil degradation. Other findings indicated that the land use had no significant effect on D I and infiltration properties, whereas K USLE , D m , D clay , D Silt and D Sand were significantly affected by land-use patterns (p < .01). These findings demonstrate that fractal dimensions of PSD and infiltration can be practicable indices to analyse soil degradation under different land-use types. Highlights • How fractal geometry adds to understanding of the infiltration process and soil degradation. • Fractal dimensions of infiltration (D I ) can describe the infiltration process. • Fractal dimensions of soil (D m ) and D I can be used as indicators of the soil erodibility. • Erodibility and fractal properties of soil were significantly affected by land use.

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Diffusivity and sorptivity determination at different soil water contents from horizontal infiltration

et al. 2019

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Modeling water movement in horizontal columns using fractal theory

Cited by 6 publications

References 13 publications

Estimation of infiltration models parameters and their comparison to simulate the onsite soil infiltration characteristics

Estimation of infiltration models parameters and their comparison to simulate the onsite soil infiltration characteristics

Fractal analysis of the infiltration curve and soil particle size in a semi‐humid watershed

Diffusivity and sorptivity determination at different soil water contents from horizontal infiltration

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