Evaluation of infiltration models with different numbers of fitting parameters in different soil texture classes

Mirzaee, Salman; Zolfaghari, Ali Asghar; Gorji, M.; Dyck, Miles; Ghorbani-Dashtaki, Shoja

doi:10.1080/03650340.2013.823477

Cited by 60 publications

(40 citation statements)

References 23 publications

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“…These models are developed for vertically homogeneous soils with fixed initial water content in soil, fixed density and over surface planes. A comparative study comprising the application of eight infiltration models using least square technique on the observed infiltration data was conducted by Mirzaee et al (2014). Based on the data collected from field and laboratory, Mishra et al (2003) suggested that semiempirical models performed better than the other infiltration models.…”

Section: Introductionmentioning

confidence: 99%

“…They showed that the modified Kostiakov and revised modified Kostiakov models gave a better performance. A comparative study comprising the application of eight infiltration models using least square technique on the observed infiltration data was conducted by Mirzaee et al (2014). They observed that the revised modified Kostiakov model gives accurate estimations when applied to clay loam, silty clay loam and loam soils.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of Infiltration Rate of Soil Using Empirical and Machine Learning‐Based Models

Kumar

Sihag

2019

Irrigation and Drainage

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The application of several infiltration models in evaluating the infiltration rate of soil is subject to the spatial variability of soil. Infiltration plays an important role in designing and evaluating surface irrigation systems as well as subsurface groundwater recharge systems. The main theme of this paper is to compare the empirical equation‐based models which are used to estimate the infiltration rate of various locations in Kurukshetra, India. Infiltration experiments were conducted at 20 different locations using a mini disc infiltrometer. The least square fitting method was used for each location separately to estimate the equation parameters and infiltration rate of three different empirical models, namely Kostiakov, modified Kostiakov and Novel models. The performance of these empirical infiltration models was further compared with the machine learning‐based adaptive neuro‐fuzzy inference system (ANFIS) and random forest regression (RF) techniques. Statistical performance evaluation parameters (R2, CC, RMSE and MAE) are used for the performance comparison of various models. The Novel infiltration model was observed to be the most reasonable amongst the empirical models tested. However, for machine‐learning methods, the RF approach is observed to be the most appropriate technique for the estimation of the infiltration data. © 2019 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of Infiltration Rate of Soil Using Empirical and Machine Learning‐Based Models

Kumar

Sihag

2019

Irrigation and Drainage

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“…Mishra et al () based on his extensive study reported Singh Yu model as best fit with Holtan, Huggins–Monke and Horton model also in good agreement with observed data. Mirzaee et al () reported that the revised modified Kostiakov model suitable for loam, clay loam and silty clay while modified Kostiakov model suitable for silty loam based on the comparative study of eight infiltration models for 95 sites of Iran.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of the novel infiltration model with other infiltration models

Zakwan

2018

Water & Environment J

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Variability in infiltration characteristics of soils creates need for selection of appropriate infiltration model. Recently, a novel infiltration model was proposed and reported to perform excellently in estimating infiltration rate of soils of Kurukshetra, India, however, this model need to be tested for its reliability at global level. In this regard, the present study analyses the reliability of the novel model based on infiltration database comprising of 16 data sets from different parts of the world to arrive at some generalized results on the reliability of novel model as compared to commonly used infiltration models. Comparative analysis reveals that out of the 16 data sets for 9 sites (57%). Horton model was found to be best model while novel model was found as best-fit model in five cases (31%). Based on the present study and earlier investigations, it may be inferred that novel model could be a useful model to estimate infiltration rate in loams.

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“…Santos et al (2014) tested the models of Kostiakov-Lewis, Horton and Philip and observed that Horton's was the most adequate to represent the behavior of soil water infiltration rate. On the other hand, Mirzaee et al (2014), testing the models of Kostiakov, Horton, modified Kostiakov and revised modified Kostiakov (RMK) in soils with different textural classes, observed that the RMK model showed the best performance for most of the studied soils.…”

Section: Introductionmentioning

confidence: 99%

“…The water infiltration in to the soil can be measured at the field or estimated by mathematical models, which can be empirical or theoretical physically based. Empirical models have the advantage of allowing relating model parameters to soil characteristics, without requiring them to have a physical meaning, and encompass, in the determination of their constants, factors that are difficult to be considered in theoretical models (Brandão et al, 2006;Mirzaee et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Modeling of soil water infiltration with rainfall simulator in different agricultural systems

Santos

Souza

Montenegro

2016

Rev. bras. eng. agríc. ambient.

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A B S T R A C TThis study aimed to compare models for predicting soil water infiltration rate and erosive rates using a rainfall simulator in different systems of common bean (Phaseolus vulgaris L.) cultivation. The evaluated mathematical models were: Kostiakov, Kostiakov-Lewis, Green-Ampt and Horton. Infiltration tests were carried out considering six treatments: bean cultivated on contour with rock barriers spaced at 0.5 m between crop rows (BC1); bean cultivated on contour with rock barriers spaced at 1.0 m between crop rows (BC2); bean cultivated downslope (BDS); bean cultivated on contour with mulch (BCM); bare soil (BS) and soil under natural cover (NC). Four replicates were considered, totaling 24 field tests. Kostiakov-Lewis's equation showed the lowest values of standard error. Soil water infiltration rate was equal to 53.3 mm h -1 in the natural vegetation treatment and to 9.49 mm h -1 in the downslope treatment. Surface roughness and the time of beginning of surface runoff were significantly higher for the conditions with mulch cover. Modelagem da infiltração de água no solo com simulador de chuvas em diferentes sistemas agrícolas R E S U M OObjetivou-se, com o presente trabalho, comparar modelos de previsão da velocidade de infiltração de água no solo e taxas erosivas em condição de campo utilizando simulador de chuvas, em diferentes sistemas de cultivo do feijão (Phaseolus vulgaris L.). Os modelos matemáticos avaliados foram Kostiakov, Kostiakov-Lewis, Green-Ampt e Horton. Os testes de infiltração foram realizados em seis tratamentos: feijão cultivado segundo curvas de nível (FN1) associado a fileiras de pedra, espaçadas 0,50 cm; feijão cultivado segundo curvas de nível (FN2) associado a fileiras de pedra, espaçadas 1,0 m; feijão cultivado morro abaixo (FMA); feijão cultivado em nível, com cobertura morta (CM); solo descoberto (SD) e solo com cobertura vegetal nativa (CN) em quatro repetições totalizando 24 testes de campo. A equação que apresentou menores valores de erro padrão foi a de KostiakovLewis. A taxa de infiltração básica de água no solo foi de 53,3 mm h -1

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Evaluation of infiltration models with different numbers of fitting parameters in different soil texture classes

Cited by 60 publications

References 23 publications

Assessment of Infiltration Rate of Soil Using Empirical and Machine Learning‐Based Models

Assessment of Infiltration Rate of Soil Using Empirical and Machine Learning‐Based Models

Comparative analysis of the novel infiltration model with other infiltration models

Modeling of soil water infiltration with rainfall simulator in different agricultural systems

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