Modeling of Infiltration Characteristics by Modified Kostiakov Method

Hasan, Mahbub; Chowdhury, Tamara; Drabo, Mebougna L.; Kassu, Aschalew; Glenn, Chance

doi:10.4236/jwarp.2015.716106

Cited by 9 publications

(4 citation statements)

References 1 publication

(1 reference statement)

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“…In general, Kostiakov showed to be more robust in all treatments (except S2.5) and in most of the WD cycles. Empirical models, such as Kostiakov, has proved to fit well to measure data although its parameters lack of physical meaning [35,38,[64][65][66]. As reported by Li et al [61], this good performance was obtained because the fitting parameters are not related to the wetting front depth.…”

Section: Discussionmentioning

confidence: 99%

Changes in Water Infiltration after Simulated Wetting and Drying Periods in two Biochar Amendments

Villagra-Mendoza

Horn

2019

Soil Systems

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Biochar impacts soil-water related processes such as infiltration and contributes to the hydrological response of catchments. The aim of this work is to determine the impact of wetting and drying conditions on the infiltration behavior of two biochar amendments and to validate the performance of three infiltration models: Kostiakov, Horton, and Philips. Two materials, sand and a sandy loam, were mixed with 0%, 2.5%, and 5% (by dry wt.) mango wood biochar produced at a highest heating rate of 600 °C and with a particle size of <63 μm. A sequence of four wetting and drying cycles were simulated. In each cycle, infiltration was measured. We found that biochar addition decreased infiltration because the formation of narrower pores reduced infiltration capacity. The higher the biochar dosage, the more resilient the treatment became concerning the changes on the water infiltrated. Repetitive wetting and drying cycles resulted in a reconfiguration of structural pores affecting the transport of water and air. The infiltration models of Kostiakov and Horton could predict the infiltration dynamics in the amended materials, although they show some instabilities along the WD cycles.

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Section: Discussionmentioning

confidence: 99%

Changes in Water Infiltration after Simulated Wetting and Drying Periods in two Biochar Amendments

Villagra-Mendoza

Horn

2019

Soil Systems

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“…For HS, the Kostiakov (Hasan, Chowdhury, Drabo, Kassu, & Glenn, 2015), Philip (Philip, 1992), and Green–Ampt (Selker & Assouline, 2017) models are commonly used to describe infiltration. The Kostiakov water infiltration model is derived as follows.…”

Section: Methodsmentioning

confidence: 99%

Application of a water infiltration model for simulating water repellency of humus soil

Zhao

Ren

Gong

et al. 2020

Hydrological Processes

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One-dimensional infiltration experiments were conducted using hydrophilic and water-repellent soils from the Guishui River Basin to study the effects of soil water repellency on cumulative infiltration (CI) and the infiltration rate (IR). The test results show that, for the hydrophilic soil (HS) sample, CI increases monotonously with time and IR decreases monotonously. For the water-repellent soil (W-RS), however, the following characteristics were observed: (a) There is an inflection point in CI and a sudden increase in IR. Larger values of the initial soil water content produce an earlier and more significant inflection point in CI, and a larger peak value of IR. (b) The postpeak stable IR is greater than the pre-peak value, ignoring the beginning of rapid infiltration, and the overall IR presents a single peak. The applicability of various water infiltration models was analysed for the two soil types. Numerical analysis suggests the following conclusions: (a) For both HS and W-RS, the Kostiakov function, Gamma function, and Beta function (BF) models exhibit good applicability. (b) For W-RS, the Gauss function model not only reflects the monotonous decrease in IR, but also produces a steady IR in the initial stage, a gradual increase before the peak value, and a gradual decrease after the peak value. Similarly, the BF model reflects the monotonous decrease in IR. A piecewise BF reproduces the U-shaped change in rapid infiltration before the inflection point, as well as the gradual increase and rightskewed distribution curve of W-RS infiltration before and after the inflection point.The BF model achieves the best simulation accuracy and has the widest applicability. K E Y W O R D Sdisappearance of water repellency, plant root growth, probability density function, single peak, soil volume expansion, soil water repellency, temperature rises, water infiltration model

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“…Soil surface infiltration was estimated from measured soil water content and time field data using the modified Kostiakov mathematical equation (Hasan et al ., ) written as:

I = k τ^{a} + c

i = \frac{\partial I}{\partial τ}

where, I is accumulative infiltration depth (in millimeters), τ is infiltration opportunity time in minutes, c is soil surface basic intake or infiltration capacity (in mm s −1 ) and was equivalent to steady state infiltration rate determined in this study from double ring experiment (in mm s −1 ), k and a empirical coefficients, and i infiltration rate in millimeters per second (mm s −1 ). Although infiltration rates are typically expressed in millimeters per hour (mm h −1 ), it was more practical to express infiltration time in number of minutes it takes soil to absorb each millimeter of water applied to the soil surface, an approach adopted in this study.…”

Section: Methodsmentioning

confidence: 99%

Characterizing infiltration and internal drainage of South African dryland soils

Mavimbela

Rensburg

2016

Earth Surf Processes Landf

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Surface infiltration and internal drainage properties of five soil types from arid drylands of South Africa were studied under double ring infiltrometer, rainfall simulation plots (1 m2) and instantaneous drainage plots (9 m2). Changes in soil water content during 40 minute rainfall simulation for a rainstorm with average intensity of 1.61 mm min−1 and 30 day drainage period were measured at various depths by 1.5 m long capacitance soil water measuring (DFM) probe. Different (P < 0.05) mean surface steady infiltration rate ranged from 0.05 to 4.47 mm min−1 and had a negative power relationship (R2 = 0.65) with horizon clay plus fine silt content. Power regression (R2 ≥ 86%) described rainstorm infiltration and obtained steady rates within an average time of 15 minutes. Mean total infiltrated soil water content was lowest (P < 0.05) from surface horizons with either 47.7% clay plus fine silt content or bulk density of 1.91 g cm−3 and exchangeable sodium of not less than 44 mg kg−1. Surface horizons with lower surface bulk density and total sand fraction of more than 72% had infiltrated depth and mean total infiltrated soil water content up to 40 cm deeper and 0.55 mm mm−1 greater, respectively. Drainage rate at drained upper limit calculated from the Wilcox drainage model (R2 ≤ 0.97%) was 0.2 mm day−1 or less were from underlying horizons with either clay plus fine silt of 45% or soft calcium carbonate. Higher drainage rate with accumulative drainage amount greater than 60 mm were from soil profile horizons with clay plus fine silt content of less than 20% and above unity steady infiltration rates. Rainstorm infiltration and drainage rates was shown to depend on permeability and coarseness of the respective soil surface and subsurface horizons; a phenomenon critical for harnessing rain and flood water to recharge groundwater. Copyright © 2016 John Wiley & Sons, Ltd.

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Modeling of Infiltration Characteristics by Modified Kostiakov Method

Cited by 9 publications

References 1 publication

Changes in Water Infiltration after Simulated Wetting and Drying Periods in two Biochar Amendments

Changes in Water Infiltration after Simulated Wetting and Drying Periods in two Biochar Amendments

Application of a water infiltration model for simulating water repellency of humus soil

Characterizing infiltration and internal drainage of South African dryland soils

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